• Personal and professional growth is often shaped by unexpected opportunities, the people we meet, and the experiences we choose to pursue.

• Internships can provide more than work experience by allowing young professionals to develop confidence, discover their strengths, and find their place within an industry.

• Building a future in agriculture takes faith, patience, and hard work, especially when that future has to be built from the ground up.

Where My Story Began

I was raised in Round Top, Texas, a small rural town between Houston and Austin. It was a unique place to grow up, where a trip to the grocery store could easily take 30 to 40 minutes, and graduating classes were small enough that everyone knew each other like siblings. I attended Round Top-Carmine from elementary school through high school and graduated in 2024 with a class of only 19 students. During that time, I became heavily involved in FFA, competed in speaking and communication events, served as a district officer my senior year, and showed pen heifers at local county shows. I did not necessarily know exactly where those experiences would take me, but they gave me an early connection to agriculture and eventually played a role in the path I chose.

A large part of who I am also comes from something that happened much earlier in my life. I lost my mom in 2009 when I was three years old. Although I was very young, losing her has shaped the way I look at life and the kind of life I want to build for myself. My faith is a huge part of that. I believe my mom is waiting for me in Heaven, and when it is eventually my time to see her again, I want to be proud of the life I get to tell her about. My faith pushes me to work hard, dream big, and trust that there is a reason for the people and opportunities God places in my life. I do not really believe in coincidence. I believe things happen as part of God’s plan, even when we do not understand that plan at the time.

After high school, I moved to Lubbock to attend Texas Tech University, where I am now a senior studying Agricultural Leadership and expect to graduate in May 2027. College has not always been easy, but I think that is part of what has made it so important to me. It has taught me how to be independent, how to work through difficult seasons, and also how important it is to appreciate where I am instead of constantly waiting for whatever comes next. People always say life is short, but I think sometimes life just feels short because we spend so much of it looking ahead. There are obviously times when planning for the future is necessary, but I have learned that when I slow down and pay attention to what is right in front of me, life looks a little different.

That is part of the reason I look at meeting John the way I do. I first met John and his wife, Amanda, when I went to pick up a Christmas tree I had purchased from them. During some small talk, John learned about my connection to agriculture and handed me his business card. I knew I needed an internship before graduation, and eventually I decided there was no harm in reaching out and asking if he might be looking for an intern. After several conversations and interviews, John gave me a chance. As he explains, “I did five internships while I was an undergrad, so from the very beginning of my career, I’ve believed in giving back just like so many others did for me. That’s what led us to start an internship program as soon as we were able.” Looking back now, it is funny to think that something as simple as picking up a Christmas tree led to all of this. Some will call it a coincidence, but I believe this was a part of God’s plan all along.

My Time at Sero

When I started at Sero Ag Strategies, I really did not know what my internship would turn into. I knew I needed the experience for school and wanted an opportunity that would actually teach me something about working in agriculture, but I did not walk in with a perfectly defined role. A lot of my internship developed as John learned what I was capable of and I learned where I could be useful. That eventually led to me taking on Sero’s social media and building a more consistent presence for the company across its platforms.

Social media became something I could really make my own. I started creating content, developing posting schedules, filming videos with John, promoting newsletters and other projects, and thinking more about how we could explain what Sero does to people who may not work in the same part of agriculture. My mission was never just to post something every day for the sake of posting. I wanted Sero’s social media to be educational while still feeling approachable, especially for younger people who might be interested in agriculture but do not always understand some of the more technical conversations surrounding sustainability, water, economics, and technology. It has been rewarding to look back at where we started and see something that I helped build become part of how Sero communicates.

Some of my favorite experiences, though, happened outside of social media. I was able to travel with John to Kansas, attend meetings with him, meet people working in different parts of agriculture, and tour High Plains Ponderosa Dairy. Being able to sit in those rooms and see those operations gave me a completely different kind of education than I could get in a classroom. John did not treat me like I was only there because I was the intern. He gave me opportunities to listen, participate, ask questions, and understand more about the actual work happening behind the projects about which I was helping communicate.

That is probably what I will take away most from my time at Sero. I was given enough trust to figure things out for myself while still having someone there to teach me when I needed it. I have learned a lot about communication and agriculture, but I have also become more confident in my own ability to contribute professionally. As I move closer to graduation, I hope to continue working with John and supporting Sero, especially through the social media and communication work I helped start. What began as an internship I needed for college turned into something I genuinely care about continuing to build.

Looking Beyond Graduation

After graduation, I hope to continue building a career in agriculture. I have not completely decided whether graduate school will be part of that path, but it is something I want to keep open as an option. What I do know is that my strongest passion is in the beef industry and the ranching way of life. That is something my significant other, Lio, and I share. Lio also attends Texas Tech, where he is studying Animal Science with an industry concentration, and this summer he completed an internship at Friona Feedyard in Friona, Texas. We have spent our time in college gaining different experiences and building our own careers, but ultimately we are working toward a lot of the same things.

One of our biggest goals is to eventually build a cow-calf operation together. Neither of us is inheriting an established ranch, a herd of cattle, or an operation that someone else has already spent generations building. If we want that life, we are going to have to start from the ground up. We know that means there will probably be plenty of mistakes, sacrifices, long days, and times when progress feels slower than we want it to. But I also think the fact that we are willing to start with very little says a lot about how badly we want to be part of this industry and create something of our own.

Within the next year, we hope to purchase our first group of heifers and begin figuring it out together. Obviously, a few heifers are a long way from the ranch we picture someday, but everybody has to start somewhere. We want to be more than cattle owners. We want to contribute to the agricultural community around us, be part of producing American beef, and know that the work we are doing ultimately helps put food on someone’s table. There is something meaningful to both of us about being able to say we had a hand in that.

Our long-term goal is to grow that small beginning into an operation we are proud of and, hopefully, something our future family can continue someday. We may not be inheriting a ranch ourselves, but maybe we have the opportunity to build one worth passing down. I have no idea exactly what our lives will look like 10 or 20 years from now, and I am learning to be okay with that. My faith reminds me that I do not have to know every part of the plan. For now, we can work hard toward the future we want while still being thankful for where we are and the opportunities already in front of us.

Making Space for the Next Young Professional

One of the most meaningful parts of my experience at Sero is simply that John was willing to take a chance on me. I did not start this internship knowing exactly what I was doing, and I definitely did not know everything I know now. Instead of expecting me to already have all the answers, John gave me real responsibilities, let me ask questions, and trusted me enough to try things on my own. That allowed me to discover skills and interests that I probably would not have found sitting in a classroom.

I think young professionals need more experiences like that. An internship should be more than a title to add to a résumé or a list of small tasks nobody else wants to do. Young professionals need people who are willing to teach them, bring them into conversations, and give them meaningful work even when they are still learning. Agriculture talks a lot about supporting the next generation, and I think this is one of the simplest ways we can actually do it. Someone has to be willing to open the door and let a young professional get started.

John has expressed that he wants to continue hosting interns at Sero in the future, and I hope he does. Their experience probably will not look exactly like mine, nor should it. I hope they come in with different strengths, find something they can make their own, and continue building on what has already been started. I also hope that some of the things I have built during my time here make it a little easier for the next young professional to come in and find their own place within Sero.

John has talked about how the internships he had made him want to provide the same opportunity for someone else. Now I understand that a little better. Someday, when I am further along in my own career, I hope I am in a position to take a chance on a young professional too. It is strange to think that this entire experience started because I went to pick up a Christmas tree, John handed me a business card, and I decided to reach out. But I think that is also what makes the story so special. I am still at the beginning of figuring out where my own life and career are going, and I am learning that I do not have to rush through that part. There is a lot to look forward to, but there is also a lot worth appreciating right now.

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About Serō Ag Strategies

At Serō Ag Strategies, we bridge farmers and supply chain partners by transforming complex agricultural data and policy into actionable insights. We also work to create and grow markets for commodity crops by aligning production with evolving demand, policy shifts, and sustainability goals. Combining multinational expertise with the personal touch of boutique consulting, we specialize in economic and sustainability analysis that drives strategic innovation.

Click here to learn more about Serō Ag Strategies.

• Water is essential to agriculture, public health, and economic stability, but usable freshwater is far more limited than its global abundance suggests.

• Water crises are not always as visible as declining lakes or the Aral Sea; groundwater depletion can remain hidden until wells deepen, costs rise, and access begins to fail.

• The Indo-Gangetic Aquifer shows how a water-management problem can become far more serious when the same resource supports food production and the daily needs of hundreds of millions of people.

Water Is Life

Photo via Unsplash

Water is central to nearly every conversation in agriculture because the industry depends on it. It influences what can be grown, where production can occur, and how productive the land is over time. It also supports livestock, food processors, rural businesses, and the communities built around agricultural production.

Its importance extends far beyond the farm. Approximately 60 percent of the adult human body is water, and about 71 percent of the Earth’s surface is covered by it. Yet only about 2.5 percent of the planet’s water is freshwater, and much of that is stored underground or frozen in glaciers and ice.

Water may appear abundant at the global level, but the amount that is fresh, safe, accessible, and located where people need it is much more limited. Global water abundance does not necessarily translate into local water security because it must be available in the right place, at the right time, and in a condition that allows people to use it safely.

Those who work in agriculture understand this distinction well. When water becomes less available, less reliable, or otherwise more expensive to access, the effects extend beyond crop and livestock production. They can influence everything from farm income to the stability of rural communities.

The Water Crises We Recognize

Several water challenges in the U.S. have become visible examples of resource decline. In the Desert Southwest, falling shorelines around Lake Mead and Lake Powell have helped draw attention to the pressure facing the Colorado River Basin, while California has experienced recurring drought, extensive groundwater pumping, dry domestic wells, and land subsidence. In each case, the evidence can be seen with the naked eye and makes the problem hard to ignore.

Photo via KTNV News

Across the Great Plains, producers and communities continue to confront the decline of portions of the Ogallala Aquifer. The aquifer underlies parts of eight states and supports one of the country’s most productive agricultural regions. However, conditions vary considerably across the system. Many northern areas remain stable while parts of the southern High Plains have experienced substantial declines. Some areas have seen complete and total depletion while others are pumping on borrowed time.

Those differences serve as a reminder that the Ogallala cannot be treated as one identical water source from north to south. A region with stronger recharge and greater remaining capacity does not face the same immediate pressure as a county where irrigation capacity has already fallen considerably. In the most affected areas, producers may eventually need to reduce irrigation, change crops, improve water-use efficiency, or transition some acreage to dryland production.

Abandoned irrigation infrastructure aside, groundwater depletion is often difficult to observe. Wells gradually deepen, pumping costs rise, and smaller domestic wells may fail long before the larger system appears to be in crisis. The Ogallala has been experiencing this for decades, with the earliest well abandonments and resulting adverse community impacts occurring in some pockets of the southern High Plains as early as the 1950s.

Map via National Climate Assessment

Beyond the Aral Sea

Globally, perhaps no water crisis is more visually recognizable than the decline of the Aral Sea, once the world’s fourth-largest lake. Images of large ships resting on a dry desert floor communicate the scale of the loss without requiring much explanation. Those vessels once traveled across a body of water that supported fishing, transportation, and employment in surrounding communities and the greater Uzbekistan-Kazakhstan region and beyond.

The Aral Sea is not the only global water system showing the consequences of long-term stress. Dead Sea levels continue to decline, fossil groundwater is being depleted in parts of the Arabian Peninsula, Central Mexico has experienced severe groundwater overdraft and land subsidence, and here at home, aside from the cases already discussed, the Great Salt Lake is even in crisis. Bangladesh presents a different but not unrelated concern, as naturally occurring arsenic has made groundwater from many wells unsafe to drink.

Although each of these situations has different causes and consequences, they reveal a similar pattern. Water can continue supporting agriculture, households, and economic activity even as the long-term stability of the resource declines. The immediate benefits of water use are easy to recognize, while depletion and contamination may remain largely hidden until the consequences become costly and difficult, or even impossible, to reverse.

Photo via Journal of Nomads

The Indo-Gangetic Aquifer and the Looming Humanitarian Crisis

The Indo-Gangetic Aquifer stretches beneath portions of Pakistan, India, Nepal, and Bangladesh. It lies below one of the most densely populated and agriculturally important regions in the world and supports farms, cities, villages, industries, and hundreds of millions of people. The aquifer is essential to the production of rice, wheat, and other crops that contribute to regional food security. Its importance, however, extends far beyond agriculture. Groundwater also supplies drinking water and supports household, municipal, and industrial needs throughout much of the region.

Like the Ogallala, conditions are not identical across the aquifer. Some areas remain relatively stable, while others face rapid depletion. In portions of the eastern region, water-quality concerns such as arsenic and salinity may present a more immediate risk than the total amount of water stored underground. Some of the most heavily documented declines have occurred in northwestern India, particularly in Punjab, Haryana, Rajasthan, and Delhi. Research examining part of the early 2000s estimated groundwater losses of approximately 17.7 cubic kilometers per year, with water tables in some locations falling by as much as one foot annually.

The human consequences could be staggering. India’s government has estimated that approximately 600 million people may face water stress by 2030, while inadequate access to safe water is already linked to an estimated 200,000 deaths each year. As groundwater levels fall and contamination worsens, more families may be left with water that is unsafe to drink, too expensive to pump, or simply beyond the reach of their wells. In a region supporting hundreds of millions of people, that is not merely water scarcity; it is the foundation of a humanitarian crisis.

Map via Britannica Kids

A Cautionary Tale

As is almost always the case, from the perspective of the individual farmer in the region, pumping groundwater is often a practical and necessary decision. Irrigation protects crops while reducing the risk associated with uncertain rainfall and supporting household income. The larger problem emerges when the withdrawals of millions of users collectively exceed what the aquifer is able to replace. It is one of the world’s best examples of the tragedy of the commons.

The Indo-Gangetic and Ogallala aquifers are not interchangeable. They differ in climate, population density, agricultural systems, infrastructure, recharge, and patterns of water use. And, they differ in the severity of the humanitarian crisis their overuse will one day bring. However, they offer the common lesson that groundwater systems can continue supporting production even as their long-term stability weakens underground, and the severity of the situation may not be fully understood until it is (much) too late.

Water may be renewable, but that does not make it unlimited. Early action provides more opportunities to improve efficiency, adjust production systems, strengthen drinking-water infrastructure, and prepare for lower availability. Waiting until wells fail leaves farmers and regional planners far fewer and much more disruptive options for adjustment. The Indo-Gangetic Aquifer shows that once access becomes unsafe, unaffordable, or physically out of reach, the consequences extend far beyond agriculture.

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About Serō Ag Strategies

At Serō Ag Strategies, we bridge farmers and supply chain partners by transforming complex agricultural data and policy into actionable insights. We also work to create and grow markets for commodity crops by aligning production with evolving demand, policy shifts, and sustainability goals. Combining multinational expertise with the personal touch of boutique consulting, we specialize in economic and sustainability analysis that drives strategic innovation.

Click here to learn more about Serō Ag Strategies.

• Sustainability has become one of agriculture’s most important conversations, but industries often define it differently.

• What works as a sustainability benchmark in one production system may not make sense in another.

• Understanding sustainability starts with understanding what each industry is actually trying to sustain.

One Word, Many Meanings

Few words carry more weight in agriculture today than sustainability. Food companies are setting sustainability goals, retailers are requesting sustainability data, and investors are paying closer attention to environmental and social performance. Across the food system, sustainability has become one of the defining conversations shaping agriculture’s future. Yet for a term used so frequently, sustainability remains surprisingly difficult to define, and one definition all industries can share remains elusive. Most public discussions treat it as though it were a single destination, which is understandable. Yet, animal agriculture tells a much different story.

The deeper one dives into the industries responsible for producing animal protein, the harder it becomes to find a single definition that captures every challenge and every priority. Sustainability is often discussed as a one-size-fits-all definition, but in reality, it’s influenced by geography, production methods, resource demands, economics, and the realities of individual industries. This doesn’t mean sustainability lacks meaning, and if anything, it highlights how complex the concept has become. Because of this complexity, different industries often address sustainability from very different starting points.

Sustainability Depends on What You're Trying to Sustain

Sustainability is often described as meeting today’s needs without compromising the ability of future generations to meet theirs. It is a simple definition, but applying it becomes much more complicated in practice. To do so, it is first necessary to ask what exactly is being sustained. Food production, natural resources, rural communities, producer profitability, and consumer trust are all common priorities within animal agriculture, and in many cases, the answer is all of the above.

Balancing these priorities can be challenging, as they often conflict or vary in importance depending on the production system. As a result, sustainability does not look the same across every sector of animal agriculture, with each industry defining and pursuing it in ways that reflect its unique production systems and priorities.

Agriculture occupies a unique position in this discussion because it depends on natural resources while simultaneously managing them. Producers must think about environmental outcomes, but they must also remain productive enough to meet demand, resilient enough to withstand changing markets, and most importantly, profitable enough to remain in business. This balancing act is often overlooked in broader sustainability conversations where the public discussion frequently focuses strictly on outcomes. Meanwhile, producers must focus on outcomes and feasibility. A solution that appears sustainable on paper must also function in the real world. That reality helps explain why sustainability looks so different from one industry to the next.

Different Industries, Different Challenges

The clearest evidence of sustainability’s complexity can be found by examining how individual animal agriculture sectors define and pursue it. While the broader goal is shared, the challenges each industry faces and the strategies used to address them are often quite different.

For the beef industry, sustainability has become closely tied to stewardship and the long-term management of natural resources. While caring for grazing lands and livestock has always been central to cattle production, the industry’s sustainability efforts have increasingly focused on documenting measurable improvements in environmental performance while maintaining productive and economically viable operations.

The dairy industry has taken a different path. Rather than emphasizing a single environmental outcome, dairy has become one of the most coordinated sectors in agriculture, investing heavily in benchmarking, environmental measurement, and industry-wide collaboration. Sustainability has become as much about demonstrating progress as it is about achieving it.

Sheep and goat producers offer another perspective. Their sustainability efforts are often rooted in managed grazing and land stewardship, with production systems that support vegetation management, control of invasive species, and the productive use of landscapes that may be less suitable for other forms of agriculture.

The poultry and swine industries have built much of their sustainability progress on efficiency. Decades of improvements in genetics, nutrition, animal health, and production management have allowed producers to generate more food while using fewer resources. For swine producers, nutrient management and the productive use of manure have become central sustainability priorities, while poultry has paired production efficiency with growing attention to animal welfare and responsible management practices.

Aquaculture presents perhaps the most unique perspective. Unlike terrestrial livestock industries, aquaculture production is more directly connected to surrounding aquatic ecosystems, making environmental stewardship even more inseparable from production itself. Water quality, responsible feed sourcing, biosecurity, traceability, and certification programs all play important roles in demonstrating that seafood can be produced while protecting the environments on which the industry depends.

These examples illustrate an important point. Although every sector is pursuing sustainability, they are often solving different problems. The challenge is not determining which approach is most sustainable, but recognizing that each industry must balance environmental, economic, and social priorities within the realities of its own production system.

The Pressure to Find One Standard

Despite agriculture’s diversity, there is growing pressure from consumer packaged goods companies, nongovernmental organizations, and even some within agriculture to simplify sustainability into a set of common benchmarks. Their motivation is understandable. Consumers want transparency, retailers want consistency, food companies want measurable goals, and Wall Street analysts want comparable data and a simple story to tell investors. The result has been a proliferation of frameworks and certifications, and, in many ways, this represents significant progress. After all, better management and more consistent reporting can increase transparency and drive continuous improvement.

But standardization becomes much more complicated when industries operate under fundamentally different conditions. Agriculture isn’t a single production system. Rather, it’s a collection of highly specialized industries, each interacting with different resources, biological systems, environmental conditions, and market forces. That complexity doesn’t disappear simply because we create a common reporting framework. Ironically, these frameworks often make it more apparent.

The Risk of Oversimplification

One of the challenges facing modern sustainability discussions is the temptation to reduce complex systems into simple metrics. Metrics help measure progress, compare performance, and communicate results. However, metrics can also create the impression that sustainability can be distilled into a single scorecard, and agriculture rarely works that way.

A sustainability indicator that provides meaningful insight within one production system may offer little context in another. A practice that generates measurable improvements in one industry may be impractical, unnecessary, or even counterproductive in a different setting. This is not a weakness of sustainability measurement; rather, it reflects the complexity of agriculture itself. The reality is that sustainability often involves tradeoffs. Improving one outcome may affect another, and environmental goals must be considered alongside economic realities. Production decisions that work well in one region may not be suitable in another.

As conversations around sustainability continue to evolve, preserving this context becomes increasingly important. Without it, there’s a risk that agricultural systems become evaluated based on what’s easiest to measure rather than what’s most meaningful to improve.

What the Industries Actually Share

For all the differences that exist across animal agriculture, there are also important similarities. Every sector is investing in research, innovation, and continuous improvement while searching for ways to use resources more efficiently, strengthen long-term viability, and respond to changing expectations from consumers and supply chain partners. Perhaps most importantly, every industry is attempting to answer the same fundamental question of how to continue to produce food while preserving the resources that make future production possible (all while keeping consumers satisfied).

The answer may look different depending on whether the conversation involves grazing lands, dairy operations, poultry houses, pork production, or aquaculture facilities. Yet the broader objective remains remarkably similar, and this fact is often lost in public discussions that focus exclusively on individual metrics or isolated outcomes. Industries may disagree on methods, priorities, or measurements, but they’re largely working toward the same long-term goal of ensuring that agriculture remains capable of meeting future demand. In that sense, sustainability may be less about reaching a destination and more about maintaining the capacity to adapt and improve over time.

Looking Beyond a Single Definition

Sustainability will likely remain one of the defining conversations shaping the future of agriculture. As consumer expectations evolve and supply chains place greater emphasis on transparency and accountability, the pressure to measure and communicate sustainability performance will continue to grow. That isn’t necessarily a challenge agriculture should avoid. Rather, it’s an opportunity to better understand how different industries are approaching similar objectives through different pathways.

The lesson from animal agriculture is that sustainability can’t always be reduced to a single definition. Different industries face different challenges and rely on different resources. They operate within different environments and respond to different market forces. It shouldn’t be surprising that their sustainability priorities reflect those realities.

The future of sustainable agriculture may depend less on finding a universal standard and more on recognizing that meaningful progress can take many forms. Because while the routes may differ, the destination remains the same: producing food responsibly while preserving the resources and systems needed to support future generations. Sustainability isn’t a one-size-fits-all concept, and understanding that complexity isn’t a barrier to progress. Rather, it’s the foundation for it.

Interested in learning more? Our latest white paper, “Sustainability in Animal Agriculture,” takes a deeper look at how major animal agriculture sectors are approaching sustainability and what those differences reveal about the future of food production.

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• A large data center uses up to 5 million gallons of water per day, and Texas data centers could consume up to 161 billion gallons annually by 2030.

• Water is where the rubber meets the road — data centers cool their servers by evaporating it, and in a state already drawing down the Ogallala Aquifer, a new industrial neighbor with a 5-million-gallon-a-day habit is not an abstraction.

• The electricity concerns may be overstated, but the water concerns aren’t — closed-loop cooling technology exists that could dramatically reduce consumption, which means how hard farmers and ranchers push on permitting policy will directly shape how much water these facilities actually use.

Everyone is talking about it, but almost no one understands it

No one can ignore the latest industry coming to a field near you. Data centers are popping up everywhere to support the rapid growth in the use of artificial intelligence (AI), and, generally, people aren’t happy about it. Even with promises of jobs and tax revenue, it’s easy to see why people are scared of these centers and why some are even calling for moratoria. What will they draw from water and energy sources that are already stretched thin? Are the numbers being thrown around on the internet true? What does this mean for both municipalities and agriculture? Do we really need to worry, or is this all just being blown out of proportion?

At the end of the day, more data centers equals more draw on our natural resources. How much that will impact each of our daily lives and our businesses (and how much impact is too much relative to the benefits to our increasingly AI-driven economy) remains to be seen. But we aren’t without some answers that will give us a clue about what we’re in for.

What is a data center?

Data centers are the physical infrastructure behind the internet itself. They are the server farms that store your photos, run your bank’s website, process credit card transactions, and power AI tools. AI in particular has turbocharged demand. Training a single large AI model requires enormous sustained computing power, and those computers run hot around the clock.

Texas is a hot spot for this expansion, coming in second for the number of data centers within a state. Texas offers cheap energy, vast open land, a business-friendly regulatory environment, and its own independent power grid. There are already 458 data centers in operation or development in the state. Google announced plans for three additional Texas facilities in late 2025, costing $40 billion. OpenAI and Oracle’s Stargate campus in Abilene, with a projected capacity of 1.2 gigawatts, is already partly online.

Data centers are popping up all over the country with no signs of slowing down. While in some places people are fighting to keep them away, it seems they’ll eventually find their way into our communities. And that isn’t all bad. No one can deny the positive impact of AI on our lives and businesses. Is it all positive? Absolutely not, but these tools do represent transformational opportunity if used responsibly.

Data centers’ electricity usage is no joke

As reported by the International Energy Agency, an AI-focused data center uses as much as 100,00 households. However, the Abilene OpenAI Stargate data center is a 1.2 gigawatt (GW) facility, an amount of energy that could power 900,000 to 1 million homes. And that number is set to grow, with plans to expand the facility to 5 GW. Granted, this is probably the largest that a data center would get (at least for our current AI computing needs).

The scale of that growth becomes clearer when you look at ERCOT’s own long-term load forecast. In 2025, data centers registered essentially no load on the Texas grid’s official projections. By 2031, ERCOT projects they will account for 24,195 MW. That’s more than crypto mining (8,466 MW), industrial users (7,548 MW), hydrogen production (9,010 MW), and oil and gas (3,131 MW) combined. Total grid demand is projected to grow from 87 GW today to 145 GW by 2031, and data centers are the largest driver of that growth.

Electricity prices are a concern, but may not be as bad as you think

This is where the picture becomes less alarming, but not entirely reassuring. Data from the Energy Information Administration shows that electricity usage and prices have historically had a weaker correlation than most people assume. When demand rises, generation capacity tends to expand to meet it, which keeps prices in check.

Researchers at Carnegie Mellon University estimate that AI-driven data center growth could push electricity bills up by roughly 8% nationally, though some regional markets could see increases as high as 25%. Scientists at Lawrence Berkeley National Laboratory add that sustained demand growth can actually reduce costs over time through scale and efficiency gains as long as new generation capacity comes online fast enough.

The key caveat is Texas specifically. ERCOT projects a potential supply shortfall as early as 2027. When we model Texas electricity prices using natural gas prices as a proxy (a reasonable approach given the state’s generation mix), we estimate prices could increase by approximately 25% by 2035 under a high-demand scenario.

That said, this scenario assumes new generation capacity fails to keep pace with demand, which is not guaranteed. Projects are ramping up to add new capacity to ERCOT, and solar and wind interconnection requests in the state are running five-to-one over natural gas requests. The picture is volatile, but not predetermined.

Will we have enough water to drink?

Via Tank Superstore

The electricity numbers are concerning, but the water numbers deserve serious attention. Data centers use water primarily for cooling by running it over hot server equipment, then evaporating it to release heat. The scale varies widely depending on cooling technology. An average data center uses about 300,000 gallons per day. A larger hyperscale facility can consume up to 5 million gallons per day, which is equivalent to a town of up to 50,000 people. According to research by the Houston Advanced Research Center (HARC) and the University of Houston, data centers in Texas used an estimated 49 billion gallons of water in 2025. Projections suggest that the number could reach 399 billion gallons by 2030, nearly an eightfold increase in five years.

It would be incomplete not to compare data center water use to agriculture’s own footprint, and frankly, it’s information you need to have before someone else uses it against you. The High Plains Water District’s 2021 Irrigation Assessment Program found an average of 15.3 acre-inches of water applied per acre of irrigated corn. At 27,154 gallons per acre-inch, that’s approximately 415,000 gallons per acre. Multiply that by the 920,272 irrigated corn acres in Texas in 2025, and you get roughly 3.82 trillion gallons of water applied to corn alone every year in the state.

To match that level of consumption, you’d need approximately 209 hyperscale data centers operating at full capacity simultaneously, and we’re nowhere near that yet. Even under HARC’s higher projections, data center water use in Texas won’t approach agricultural scale within the next five years.

If you’re going to make the case that data centers are straining local water supplies, and that case is absolutely worth making, you’ll want to be ready for the moment an AI executive points to agriculture’s water footprint and tries to turn your argument around. The response is simple: agricultural water use feeds people, supports rural economies, and has been part of these communities for generations. Data center water use cools servers. Those are not equivalent uses, and we should say so plainly. But walking into that fight without knowing your own numbers is how you lose it.

Furthermore, there is a silver lining in the data center cooling technology itself. Closed-loop cooling systems that recirculate rather than evaporate water can reduce consumption dramatically. Some newer facilities report daily consumption comparable to a handful of households rather than a small city. The gap between the worst and best performers in the industry is enormous, which means policy has leverage here. To learn more about data center cooling, take a look at this infographic from Microsoft.

How farmers can get involved

Texas agriculture was already under pressure before the data center boom arrived, losing nearly 18,000 farms between 2017 and 2022 due to drought, rising input costs, and consolidation, according to the USDA 2022 Census of Agriculture. Data centers are now competing for the same land, water, and electricity that remain. Whether that competition accelerates farmland loss is still an open question, but it is one that farmers and ranchers have every reason to be watching closely. Here’s where your attention is best spent.

1. Get Involved in Water Policy Before the Permits Are Filed

Groundwater conservation districts and river authorities make the decisions that determine whether a data center can drill a new well or tap a local aquifer. These are locally elected or appointed bodies, and they respond to organized constituent pressure. The Texas Farm Bureau is already engaging the legislature on interim charges related to data center oversight. This is exactly the moment to show up to your local groundwater conservation district board meetings, submit public comments, and make sure agricultural water rights are represented in any new permitting frameworks.

Several states are now considering requiring data centers to disclose water use, meet efficiency benchmarks before permits are issued, or demonstrate they won’t deplete local supplies. Texas SB 6 (2025) began addressing grid strain from large loads, and water-side regulation is the next frontier. Advocate for it.

2. Understand Your Electricity Rights and Costs

ERCOT’s deregulated market means that large industrial customers can negotiate different rate structures than small agricultural users. If you’re irrigating on ERCOT, now is the time to review your electricity contracts, understand your exposure to wholesale price spikes, and explore whether time-of-use pricing or demand response programs could reduce your risk, if they are available.

Cooperatives and agricultural associations may also have leverage to negotiate group rates or demand that public utility commissions require large loads like data centers to contribute more to grid infrastructure costs, rather than having those costs spread to all ratepayers.

3. Consider Whether There’s a Deal to Be Made

This is the hardest one to say in a sustainable ag newsletter, but it’s worth saying: some farmers are finding exits, and some of those exits are data centers. If you’re in a county where the aquifer is declining, your input costs are rising, and you’re looking at whether the next generation wants the operation, a land sale at data center prices may be a better outcome than being stuck with land that isn’t used.

That kind of decision should be made with full information and genuine choice, not under financial duress or because water policy failures made farming unviable. The goal of engagement is to make sure agriculture isn’t squeezed out by a policy vacuum.

The Bottom Line

Data centers aren’t going away, and I don’t believe we want them to. However, the electricity and water demands of AI infrastructure are growing faster than most projections anticipated even two years ago, and in water-stressed rural regions, concentrated local impacts can be severe even when national-scale comparisons look manageable.

The picture isn’t one of inevitable catastrophe, either. New generation capacity is coming online, and cooling technology is improving. Plus, we have the power to help shape the policy around this, both locally and nationally.

Agriculture has navigated the arrival of pipelines, wind turbines, and mineral extraction on its land before. Each of those came with tradeoffs and cautionary tales from those who engaged too late. The data center boom is no different. The people who will fare best are those who show up informed, organized, and ready to negotiate, not those who simply hope the next campus gets built somewhere else.

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• The current fertilizer spike tells a geopolitical story while exposing structural weaknesses that were already in place.

• Farmers are being squeezed by rising input costs without the crop price support that helped offset previous shocks.

• The biggest issues are reliance on a system with environmental leakage, finite resources, and limited flexibility.

The new fertilizer shock everyone is watching

The current fertilizer situation is being framed as a supply disruption, and that’s not wrong. The closure and restriction of the Strait of Hormuz have tightened global flows at exactly the wrong time in the production cycle, and markets are reacting accordingly. 

Fertilizer feedstocks are concentrated to the area. Depending on your source, the Persian Gulf region accounts for 40–50% of global urea exports, 26–30% of ammonia exports, and nearly 44% of seaborne sulfur (used to produce phosphate fertilizer). This affects almost every fertilizer we use. Even in the most optimistic scenario, prices are expected to remain elevated well beyond this season. NDSU modeling shows urea peaking around $782–$784 per ton in moderate scenarios and approaching $996 per ton under extended disruption, with elevated pricing persisting through at least 2027.

Why this is different than 2022

It’s easy to compare this moment to 2021–2022 fertilizer price spikes resulting from the Russia-Ukraine war and COVID, and assume we’ve seen this before. But the underlying dynamics are different this time. In 2022, the fertilizer shock was paired with a grain price rally. As described by NDSU, corn above $7.00 and strong commodity markets helped offset the increase in input costs. It wasn’t painless, but there was a built-in cushion that allowed many operations to absorb higher fertilizer prices without fundamentally changing their approach.

That cushion isn’t there today. The Strait of Hormuz is critical for fertilizer and energy flows, but it carries very little grain trade. This shock is heavily concentrated on the input side, with no corresponding upward pressure on crop prices, resulting in an asymmetric hit to farm margins. Crop prices are materially lower, which means the same or even slightly lower fertilizer prices create a much tighter margin environment. NDSU’s modeling reinforces that point.

Duration is a second significant difference. The 2022 spike was sharp and relatively short-lived, driven in part by panic buying and rapid market adjustment. The current disruption is expected to be slower. Infrastructure damage, shipping constraints, and energy market impacts all point toward elevated prices lasting multiple seasons.

A system already under pressure

Fertilizer was already a problem before the ships stopped moving. On the environmental side, we’ve produced a system where a meaningful portion of applied nutrients never actually makes it into the plant. When nitrogen, phosphorus, and potassium (NPK) are not taken up by plants, they are lost from the soil through processes like leaching (being washed deeper into the soil by water), runoff into nearby waterways, and in nitrogen’s case, volatilization or denitrification back into the atmosphere, often leading to environmental issues like water eutrophication. This causes both environmental and economic issues. When fertilizer prices rise, every lost unit of nutrient becomes more expensive to absorb.

So even before this disruption, agriculture was operating inside a system with three structural challenges: nutrient loss at scale, environmental consequences that continue to compound, and a resource base that is constrained and geopolitically sensitive.

The pressure farmers are feeling

According to the American Farm Bureau Federation, 70% of farmers report they cannot afford all the fertilizer they need this season, and six in ten say their financial situation has worsened. They reported nitrogen fertilizer prices have risen more than 30%, urea prices have increased 47%, and diesel prices have climbed 46%, increasing costs across fieldwork, transportation, and irrigation.

The difference from past fertilizer shocks lies on the revenue side. As mentioned previously, higher crop prices helped offset higher input costs previously. NDSU’s analysis shows fertilizer affordability as measured as the amount of crop needed to pay for fertilizer, reaching levels significantly worse than 2022, even when nominal prices are lower. We’re already seeing reduced application rates, shifts toward less fertilizer-intensive crops, and decisions to stretch inputs further across acres. Below you’ll see the fertilizer affordability figure considering an extended conflict scenario. To see the data from NDSU’s other scenarios, we highly recommend checking out the full paper.

The uncomfortable middle ground

When systems come under pressure, alternatives start to surface. That’s where the fertilizer conversation is heading now. Some of the responses are incremental. Farmers are already adjusting timing, splitting applications, leaning harder on efficiency tools, and in some cases shifting acreage toward crops that are less nutrient-intensive. We’re also seeing more interest in biologicals, enhanced efficiency fertilizers, and management strategies designed to reduce loss. None of these are new, but higher prices force them from “nice to have” into “necessary to consider.”

At the same time, there are structural questions starting to get louder. If a meaningful portion of nutrients is consistently lost from the system, then improving efficiency alone may not be enough. That’s where conversations enter the picture around entirely different approaches to fertilizer management.

One example is phosphite-based systems. The premise is that enabling crops to utilize phosphite instead of traditional phosphate could reduce total phosphorus demand and limit some of the loss pathways that exist today. There are claims around improved efficiency and reduced runoff, but it’s also true that these systems are not widely adopted, not fully validated at scale, and still carry a fair amount of skepticism.

So the question becomes, how seriously is the industry willing to evaluate a broader set of options? And how willing is it to adapt if the current system keeps tightening?

Where this leaves us

The fertilizer situation today will eventually stabilize, but thankfully, the policy response already underway suggests this is being treated as more than a short-term disruption.

Across multiple fronts, the federal government is signaling that fertilizer has become a heightened priority. USDA leadership has explicitly framed fertilizer dependence on foreign sources as a strategic risk, with a stated goal of reducing reliance on imports from countries like Russia and China over time. 

The federal government is moving on two tracks: stabilizing supply in the near term through trade adjustments and expanded import flexibility, while accelerating domestic production capacity through funding, permitting support, and broader coordination across agencies. U.S. Agriculture Secretary Brook Rollins projects that expansion could be meaningful over the next two years; however, this approach likely won’t completely insulate farmers from price increases in that time. Fertilizer is being elevated to a strategic priority, with policy increasingly focused on building a more resilient and durable supply system. This is a notable direction signaling that this isn’t a problem being left to solve itself.

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Check out Tech2Market AgVisory, and reach out if you have any questions.

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• Without quick remediation, Corpus Christi’s water situation means major reductions in use at best.

• Corpus Christi is the example; the rest of Texas now has a choice to follow in its footsteps or choose another path.

• Texas isn’t alone in its water woes. Much of the country relies on water from aquifers that could take thousands of years to replenish.

The situation on the Texas coast

The past couple of weeks brought unsurprising news of the latest water situation in Corpus Christi. City officials have projected the city could hit a level 1 water emergency – being 180-days from when the total water supply is not enough to meet the total water demand – by November 2026, with two of their water sources being empty by May 2027.

The city didn’t arrive here overnight. It’s the result of solving for short-term shortages without making way for a full long-term plan. After a major drought in the 1990s, the city expanded its supply by building the Mary Rhodes Pipeline to bring in water from Lake Texana, later adding Colorado River water. This helped stabilize supply but did not eliminate reliance on local reservoirs (Choke Canyon and Lake Corpus Christi) that remain foundational to the system. Meanwhile, rapid industrial expansion for refining, petrochemicals, and port activity drove sustained increases in water demand, locking in a higher baseline level of use that the system now has to support.

The city planned large-scale desalination as its pivotal long-term solution (see page 991 of the City Council minutes for background), but it hasn’t materialized on the timeline needed to offset that risk. The Inner Harbor desalination plant was intended to provide a drought-resilient supply, but years of delays, rising costs, and political conflict stalled progress while reservoir levels continued to fall. Meanwhile, major industrial users cannot easily reduce water use without creating safety risks, since consistent water flow is critical for cooling operations, a constraint reflected in the city’s drought planning framework. Corpus Christi is now looking toward a water diversification plan, but it remains to be seen if that plan can move forward in the time needed to avoid major water-use reduction. What looks like a sudden crisis is actually the confluence of long-term reliance on vulnerable surface water, delayed investment in resilient supply, a web of political complications, and demand growth that outpaced water supply.

If water needs to be trucked in while these projects are underway, the cost could be catastrophic for low-income households and small businesses, according to one former Water District official. And it is why city reassurances that there is “no need for panic” don’t sit well next to the project schedules and depletion curves the public can already see. 

“Canary in the coal mine” - Texas State Agriculture Commissioner Sid Miller

Irrigated vs non-irrigated sorghum crop

State Agriculture Commissioner Sid Miller called the situation a “canary in the coal mine” for Texas. Governor Greg Abbott called out leadership, saying, “Corpus Christi is a victim not because of lack of water. They’re a victim because of a lack of ability to make a decision.” Taken together, this is a stark warning. Most of Texas is facing a future water crisis. It’s human nature to put out the fires you’re having now, and say “let’s hope it doesn’t happen” to problems that are coming years down the line. That’s how the water issue is panning out for many Texas regions, and many are operating with the same tension as Corpus: growing populations, expanding industry, and water systems that were never built with today’s reality in mind. But we don’t all need to find ourselves in the same critical situation.

In Midland, Odessa, and San Angelo, water is tied directly to the oil and gas economy. Hydraulic fracturing and energy production require significant volumes of water, with a USGS publication estimating direct water use for oil/gas in the Texas Permian growing from 3,003 to 72,220 million gallons per year (MG/yr) between 2010 and 2019. While the industry has made strides in recycling produced water, the demand is still substantial. That creates layered pressure: communities are competing not just with population growth, but with one of the most economically important industries in the state. Further east, in places like Conroe and Magnolia, rapid population growth is colliding with groundwater constraints and regulatory limits on pumping, forcing shifts to more expensive surface water supplies and new infrastructure. San Antonio is often held up as the model, with years of investment in aquifer management, conservation, and reuse have bought the city flexibility. But even there, continued growth means they can’t afford to get complacent.

Corpus Christi is going to show us what happens when water decline isn’t treated with the urgency it deserves. The state now has the chance to advocate for solving this problem before our taps run dry.

The rest of the country isn’t in better shape

Across the country, groundwater is both the “hidden reservoir” that enables growth and a slowly replenished store that is being treated like an annual account. The Times’ analysis of groundwater frames the dependence side starkly. Aquifers account for around 90% of U.S. water systems, and declines have outweighed rises every year since 1940. Among 84,544 monitored sites, nearly half show significant declines over 40 years, while 40% hit record lows in the last decade. Groundwater withdrawals convert stored water to extracted flow, and once pumping draws heavily from long-stored reserves, the system can require centuries to millennia to recover, if it recovers at all.

Regionally, the depletion signal is measurable in both feet of drawdown and tens of millions of acre-feet of lost storage. In the High Plains (Ogallala) system, USGS estimates recoverable water in storage 2.91 billion acre-feet (2019), down 286.4 million acre-feet (10%) since predevelopment, as well as an area‑weighted average water‑level decline of 16.5 ft (and 44.1 ft in Texas on an area‑weighted basis). Kansas Geological Survey cites “an overall decline of 0.91 feet across the region, marking the fifth straight year [as of 2024] of overall declines. Groundwater levels across the region fell 0.17 feet in 2023, 1.9 feet in 2022, about a foot in 2021 and 0.85 feet in 2020. Annual change in groundwater levels across the region averaged -0.42 feet from 1996 to 2024.” In the Central Valley of California, satellite/model synthesis tells a story of intensifying drought-era losses. Peer‑reviewed GRACE-based work reports Central Valley depletion accelerating to 8.58 km³/yr (≈7.0 million acre-feet/yr) from 2019 to 2021.

This is a crisis that’s often masked by technology and short-term workarounds until those options start to run out. That’s what makes the Corpus Christi situation worth paying attention to.

We can’t sit around and hope this gets solved

The practical takeaway is pretty straightforward. Pay attention to what your local leadership is actually doing on water, and hold them accountable to what they say they’re planning. Look at council agendas. Track timelines on infrastructure projects. If something keeps getting pushed, ask why. If supply and demand aren’t penciling out, ask how they plan to close the gap.

You don’t need a large platform to influence this. Cities respond to patterns. When the same questions come up repeatedly, it forces prioritization. Show up to meetings, submit comments, and make sure the issue stays visible in your local network.

If there’s one thing to take from Corpus Christi, it’s that water problems don’t fix themselves, and waiting usually makes the solution harder. The earlier communities push for clear plans and progress, the better their odds of avoiding the same outcome.

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Strong agricultural innovation stalls because there’s no clear path from discovery to on-farm adoption.

Tech2Market AgVisory was built to close that gap.

Grounded in real production agriculture and backed by experience across the innovation pipeline, Tech2Market AgVisory helps startups, research teams, and ag innovators translate promising technology into practical, scalable solutions that actually reach the farm gate.

Whether it’s refining a go-to-market strategy, navigating commercialization requirements tied to grant funding, or identifying the right supply chain and industry partners, the focus is simple: make sure good ideas don’t stall out before they make an impact.

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• Conservation programs deliver important benefits, but when enrollment reaches scale, it can impact the structure of the community.

• In agriculture-dependent counties without diversified economic anchors, sustained land retirement can compound existing fragility and contribute to long-term population decline.

• Land retirement requires strategic economic diversification to allow communities to thrive.

Every good thing has a cost

Conservation is a hot topic today for good reason. Nearly every region in the United States faces resource constraints or the risk of overproduction. We need to be hyper-focused on making the most of the resources we have left. A common option is converting land back to grass, as is done when landowners participate in the Conservation Reserve Program (CRP). And it can be exciting to convert that land and see the wildlife come back and flourish. But conservation decisions have a ripple effect. When land goes back to grass, it can cause cash flow to shrink for input suppliers, elevators, gins, schools, hospitals, and even local small businesses. So the hard question is this: what happens to the people when production disappears?

A case study on the Texas Plains

The best way to explain this is through an example from the Texas High Plains. While CRP enrollment affects population decline, it’s not the only factor. We’ve analyzed three counties: Castro, Hockley, and Swisher. On the surface, these counties look pretty similar. They are all blessed with (or suffer from, your choice) a semi-arid climate and rely heavily on groundwater from the Ogallala. They all depend on large-scale row crop farming. They largely grow the same crops, like cotton and sorghum. Each county’s population is rural, with low population density, and they’re all seeing some level of population decline from the mid-20th century, with aging populations to boot. There are also some big differences. First of all is scale. Castro has a population of 7,371; Hockley 21,537; and Swisher 6,971. Castro County has a diversified agricultural presence, with large commercial feed yards and a number of dairies. Hockley County is home to a community college, providing a source of non-ag employment that draws people to the area and provides stability outside the farm. Swisher County includes a state prison, providing state-funded jobs, but likely not attracting people to the point of population growth. Let’s take a look at how all of these factors affect population decline in these counties.

CRP enrollment in Swisher, Castro, and Hockley was not a one-time phenomenon following the program’s launch in the late 1980s. In each county, enrollment peaked around the mid-2000s. This signaled an expanding role for land retirement from CRP’s start in the mid 1980s to that time, rather than a temporary response to initial incentives. At that peak, between 27% and 32% of total cropland was enrolled in CRP. In Swisher, nearly one-third of cropland moved out of production, and even today, more than 28% remains enrolled, which is only about 6% below its peak. This tells us that CRP has become a near-permanent feature of the county’s land base. Castro experienced a sharper reduction, with CRP acreage falling more than 40% from its 2007 high, while Hockley sits between the two, with a moderate decline but still a meaningful enrollment footprint. The key distinction is not just magnitude, but persistence. When one-quarter to one-third of a county’s productive base transitions out of active production for decades, the consequences extend well beyond conservation metrics, influencing local throughput, infrastructure viability, and the broader economic fabric that depends on sustained agricultural activity.

If you look at Swisher, Castro, and Hockley over the last several decades, you see that rural population decline did not begin with CRP. Swisher peaked demographically in 1960, Castro around 1970, and Hockley closer to 1990. The slide was already underway long before peak CRP enrollment in the mid-2000s. That forces us to shift somewhat from the narrative that conservation single-handedly triggered collapse. What we are seeing instead is a pressure stack. Mechanization reduced labor costs per acre. Consolidation reduced the number of operators. Water constraints increased production risk. Commodity cycles tightened margins. Young people left for more diversified job opportunities. Then, layered on top of that, came sustained land retirement.

Okay, so what?

If conservation can compound fragility in already vulnerable counties, then the question is how we design conservation so it doesn’t unintentionally hollow out the communities it’s meant to support.

At peak enrollment, roughly 27% to 32% of total cropland in these counties was enrolled in CRP. When a quarter to a third of a county’s productive base transitions out of active production for decades, the implications affect elevator throughput, retail input demand, equipment turnover, and seasonal labor. Infrastructure in rural America is built on volume. It adjusts in steps. An elevator does not close because 5% of acres disappear. It closes when volume drops below break-even. A school does not shrink because one family leaves. It shrinks when enrollment crosses funding thresholds.

The current structure of land retirement programs, including CRP, evaluates success acre by acre: Did erosion fall? Did habitat increase? Did water quality improve? Those are measurable and important outcomes, but they are incomplete. From its inception, CRP has operated under national and county-level caps, with the county-level cap at around 25% of a county’s cropland. Those caps acknowledge that beyond a certain threshold, land retirement begins to reshape the production base. A county carrying 5% of its cropland in CRP can absorb the shift, but one carrying one-third of its cropland in retirement for two decades is operating under a fundamentally different economic model. If conservation policy does not account for that difference, it risks concentrating economic contraction in the places least equipped to buffer it.

So what changes?

First, we begin evaluating conservation exposure at the community level, which CRP has in place. CRP tracks intensity as a percentage of total cropland and flags counties above certain thresholds for additional review. Second, we prioritize working-lands conservation where possible, using practices that keep acres productive while improving environmental outcomes. Third, we consider pairing land-retirement incentives with rural economic resilience investments, whether through infrastructure support, diversification grants, or institutional anchors that stabilize local employment.

Economic diversification is key for rural communities

Conservation tools are important and not going away. As water constraints get worse and acres become unproductive, some acreage will transition. The evidence from Swisher, Castro, and Hockley does not suggest that conservation caused rural decline. Population loss began decades earlier. But it does show that when land retirement reaches sustained, high levels in counties heavily dependent on agriculture, it can compound existing fragility. In vulnerable places, economic diversification is a must-have. Sustainable stewardship and economic vitality are not opposing goals. But they do not automatically reinforce each other. Communities that invest in diversified employment, institutional anchors, and economic breadth will absorb land-use transitions differently than those that do not.

The difference across these counties makes the point clear. Hockley, with a community college and providing a larger employment base, absorbed elevated CRP intensity with comparatively more demographic stability. Swisher, with a more concentrated agricultural base and a more persistent CRP footprint, experienced steady population decline alongside sustained land retirement. Castro reduced CRP intensity after 2007, but infrastructure and population did not automatically rebound.

The real risk is monoculture — in both crops and economies.

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Click here to learn more about Serō Ag Strategies.

• Different carbon models exist because they were built to answer different questions, not always because the science is inconsistent

• Using the wrong model in the wrong context can quietly distort policy outcomes, markets, and farm economics

• You don’t need to know every tool, but you do need to understand the assumptions and downstream use of the ones that affect your decisions

A guide to carbon quantification tools

If you spend any time around environmental policy, sustainable agriculture, or low-carbon fuels, you likely hear model names thrown around on a daily basis. GREET, FD-CIC, COMET, Fieldprint, and openLCA are just a few. It’s hard to keep track, and even harder to get a solid level setting of all of the models.

Part of the challenge is that these tools weren’t built to do the same thing. Some were designed to support federal or state policy, others to inform corporate reporting or supply chain decisions, and others still to guide on-farm practice changes. Over time, they’ve become intertwined in conversations about sustainability and carbon intensity, even when they’re operating at very different scales or answering fundamentally different questions. That overlap can make it difficult to know which model is appropriate for a given decision, or how much confidence to place in the outputs.

This isn’t an exhaustive list. There are many other models and tools in active use across policy development, market design, and project evaluation. The ones covered here are simply some of the most commonly referenced and most likely to show up in day-to-day conversations. For readers looking to get oriented without wading into unnecessary theory, understanding these models is a solid place to start.

GREET and its many flavors

The Greenhouse gases, Regulated Emissions, and Energy use in Technologies model, or GREET is the granddaddy of lifecycle assessment tools originally built for fuels and vehicle systems. Developed by Argonne National Laboratory (ANL), GREET tracks emissions across entire supply chains, from raw material extraction through manufacturing, transportation, use, and disposal. It’s incredibly detailed, which is exactly why regulators love it.

Various states and programs have created their own GREET versions. California operates CA-GREET as a dedicated GREET implementation for its Low Carbon Fuel Standard, while Oregon applies GREET-based methodologies through its Clean Fuels Program. New Mexico developed a GREET-based framework to support its recent adoption of the Clean Transportation Fuels Standard. The federal government created 45ZCF_GREET for the Clean Fuel Production Credit under the Inflation Reduction Act. Each variation matters because the numbers directly determine whether a fuel qualifies for credits and how much those credits are worth. For farmers growing feedstocks for fuel production, the GREET pathway their buyer uses literally helps set their crop’s price floor.

The challenge is that GREET wasn’t originally designed for agriculture-specific questions. It handles fuel pathways beautifully, but if you want to model a practice change like switching to no-till, you’ll find inputs that don’t quite fit. That’s where FD-CIC comes in.

FD-CIC

The Feedstock Carbon Intensity Calculator, or FD-CIC, is GREET’s agriculture-focused cousin. Originally developed by ANL with key assists from USDA along the way, FD-CIC was built specifically to model on-farm practices and their carbon impact. Today, there are a couple different versions, including the legacy tool still curated by ANL and a new version for the Clean Fuel Production Credit. While GREET excels at big-picture lifecycle analysis of the finished fuel, both versions of FD-CIC zoom in on what happens in the field.

FD-CIC and GREET work together. FD-CIC calculates farming carbon intensity, accounting for tillage, fertilizer use, crop rotations, and soil carbon changes. That value then feeds into GREET as the agricultural input for full fuel pathway analysis. FD-CIC provides farm-level detail that GREET always ran in the background but couldn’t be easily tweaked to reflect practice changes.

This matters enormously because FD-CIC can differentiate between management practices. No-till versus conventional tillage. Cover crops versus bare soil. Different nitrogen rates and timing. A corn farmer who adopts cover crops and reduces tillage can get a better carbon intensity score for their grain, making it more valuable to ethanol producers chasing low-carbon fuel credits. Everyone benefits when the model sees what’s happening on the ground.

COMET Tools

COMET-Farm and COMET-Planner are USDA tools designed to estimate on-farm carbon sequestration and emissions changes from conservation practices. They’re built on biogeochemical models like DayCent and are widely referenced in conservation programs.

These models are not especially useful for regulatory CI modeling or supply chain LCAs. Why? First, they’re scenario tools, not accounting systems. They estimate changes relative to a baseline, not absolute emissions in a way that cleanly plugs into GREET or similar frameworks. Second, they rely heavily on generalized assumptions and coarse spatial resolution. Third, the outputs are often not structured in a way that downstream LCA tools can readily ingest.

COMET is intended to add value earlier in the process, helping farmers and their advisors understand the relative impact of different practice changes and explore potential pathways for improvement. As a planning and engagement tool, it was designed to support decision-making on the ground. The challenge comes when those exploratory results are stretched beyond what the model was designed to support.

FARM ES

The FARM Environmental Stewardship module is specifically designed for dairy operations as part of the National Dairy FARM Program. It’s built for dairy’s unique emissions profile and is inclusive of whole-farm emissions, including enteric fermentation, manure management, feed production and energy use.

What makes FARM ES valuable is its integration with the broader FARM Program. Dairy farmers already tracking animal welfare and antibiotic stewardship can add environmental metrics seamlessly. It provides standardized benchmarking for farmers and for processors and brands, it offers credible supplier data. For the industry, it creates consistent measurement and reporting. The model updates regularly to reflect new dairy emissions research, and because it’s administered through FARM, there’s built-in quality assurance.

The limitation of FARM ES is portability. FARM ES is not designed to be a modular component in broader fuel or bioenergy LCAs, and it doesn’t pretend to be. It’s a compliance and benchmarking tool for a specific supply chain.

COOL Farm Tool

The COOL Farm Tool is widely used by food and beverage companies to estimate environmental impacts at the field and farm level, including greenhouse gas emissions, water use, soil carbon, and biodiversity. It’s built to be accessible across geographies and production systems, which is a big reason it has gained traction in global supply chains and corporate sustainability programs.

The tool also allows users to explore farm management scenarios to understand how those decisions might affect environmental performance. That makes it useful for screening and prioritization, even when detailed farm data aren’t available.

As with any practice-based tool, the results depend heavily on the quality of the inputs. Data gaps, approximations, or default assumptions can influence outcomes, especially for first-time users or complex operations. In practice, COOL Farm works best as a directional tool, but isn’t the best for more detailed, policy-grade modeling.

Fieldprint Calculator

The Field to Market Fieldprint Platform covers sustainability measurement and farm-level benchmarking. It evaluates GHG emissions, land use, water use, erosion, and nutrient loss using a standardized, crop- and region-specific framework. Rather than focusing on a single outcome, it’s designed to give a more complete picture of environmental performance at the field level.

What makes Fieldprint interesting isn’t the underlying calculations, but the ability to compare results across farms, regions, and time. That benchmarking capability allows growers, brands, and programs to understand performance in context, identify areas for improvement, and track progress using a common language. In practice, Fieldprint is used almost exclusively to support corporate sustainability reporting and supply chain benchmarking rather than as a guide for day-to-day decision-making on the farm.

Like COOL Farm, Fieldprint is not intended for fuel policy or regulatory CI modeling. Its strength is in continuous improvement and credible, consistent reporting and data visualization across food and fiber supply chains.

GHGenius

GHGenius is Canada’s answer to GREET. Developed by (S&T)² Consultants Inc. for Natural Resources Canada, it performs lifecycle analysis of transportation fuels calibrated for Canadian conditions, fuel pathways, and policy requirements. The model matters because Canada has its own Clean Fuel Regulations, and GHGenius is the approved tool for calculating carbon intensities. For anyone producing or trading renewable fuels in Canada, understanding GHGenius is non-negotiable.

What’s interesting is how GHGenius and GREET sometimes produce different carbon intensity values for the same fuel pathway because they use different regional data. Canadian canola yields, fertilizer patterns, and processing infrastructure differ from US assumptions. For cross-border fuel trading, this creates complexity that producers need to navigate carefully.

ILUC Models: FAsom, CCLUB, and AEZ-EF

We’ve covered indirect land use change before, but it’s worth revisiting the models that quantify ILUC because they play a huge role in biofuel policy. When land is converted to grow biofuel feedstocks, there’s concern this displaces food production, which gets picked up elsewhere, potentially through deforestation. In theory, that displacement creates indirect emissions that should arguably count against biofuel’s carbon benefits.

FASOM (Forest and Agricultural Sector Optimization Model), CCLUB (Carbon Calculator for Land Use Change from Biofuels Production), and AEZ-EF (Agro-Ecological Zones Emission Factor model) all model these complex global market dynamics. They use economic modeling to predict land use shifts from increased biofuel demand, then translate shifts into carbon emissions. These models require assumptions about global agricultural markets, future policy, technological change, and farmer behavior across continents. Small assumption changes produce vastly different ILUC estimates.

Despite uncertainties, ILUC factors get incorporated into fuel carbon intensity scores under programs like California’s LCFS, directly affecting biofuel economics. For farmers, ILUC feels frustratingly abstract. They’re penalized for theoretical land changes elsewhere. For policy makers, it’s an attempt to account for unintended consequences. The debate shows no signs of ending.

openLCA

openLCA occupies a different category. Rather than being a pre-built model for specific applications, it’s open-source software for lifecycle assessment that can model virtually anything. Think of it as the difference between a pre-made meal (GREET, FD-CIC) and a fully equipped kitchen where you cook whatever you want.

The power is flexibility. You can build custom models, incorporate your own data, and conduct analyses that don’t fit existing tools. The software supports multiple lifecycle inventory databases, handles complex supply chains, and models environmental impacts beyond greenhouse gases.

The trade-off is complexity. openLCA has a steep learning curve, and you need a deep lifecycle assessment understanding to use it correctly. You’re responsible for data quality and sound assumptions For most farmers and many businesses, it’s overkill. But for research institutions, specialized consultancies, and companies doing sophisticated sustainability analysis, it enables analyses that wouldn’t otherwise be possible.

The biogeochemical models in the background

Like the ILUC models and openLCA, DayCent, CENTURY, SALUS, EPIC, SWAT+, and MEMS fall into a different category than most of the tools discussed above. These are process-based biogeochemical and agroecosystem models that simulate how carbon, nitrogen, water, and biomass move through agricultural systems over time. They rely on inputs like weather, soils, crops, and management practices to estimate outcomes such as soil carbon change, nitrous oxide emissions, nutrient loss, and yield response.

While these models are rarely used directly by farmers or companies, they strongly influence results elsewhere. Outputs from models like DayCent or CENTURY often underpin emission factors, response curves, and assumptions embedded in higher-level tools such as COMET, FD-CIC, and agricultural inputs to GREET-based analyses. In practice, they function much like ILUC models: largely invisible to end users, difficult to interrogate, and highly consequential for downstream carbon intensity scores and program outcomes.

The challenge is that these models are complex, assumption-heavy, and intentionally inaccessible to most users. Small changes in inputs or calibration can lead to very different results, and validation at scale is inherently difficult. You don’t choose these models so much as inherit them through the tools built on top of them. Understanding their role in the modeling stack, rather than their mechanics, is what matters for anyone trying to interpret carbon numbers responsibly.

Context matters as much as the tool

The proliferation of models isn’t accidental. Different stakeholders need different levels of detail, geographic scope, and outputs, and the tools have evolved to meet those specific demands. Selecting the “right” tool is only part of the equation. What matters just as much is understanding the context in which that tool operates. What assumptions it makes, what questions it was built to answer, and how its outputs will be used downstream. A model that’s perfectly appropriate for benchmarking or planning can create real problems if it’s treated as policy-grade accounting. Likewise, a regulatory model can look opaque or blunt if you don’t understand the constraints it was designed under.

The good news is that you don’t need to master every model. You just need to be clear on what you’re trying to accomplish and where the numbers are headed next. Understanding not just how a model works, but why it exists and how it’s applied, is becoming table stakes for operating in the carbon economy. The models will continue to evolve as science improves and policies change, but the core challenge remains the same: how to quantify agricultural climate impacts in ways that are credible, practical, and economically viable. For all their imperfections, these models are our best current attempts to do exactly that.

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About Serō Ag Strategies

At Serō Ag Strategies, we bridge farmers and supply chain partners by transforming complex agricultural data and policy into actionable insights. We also work to create and grow markets for commodity crops by aligning production with evolving demand, policy shifts, and sustainability goals. Combining multinational expertise with the personal touch of boutique consulting, we specialize in economic and sustainability analysis that drives strategic innovation.

Click here to learn more about Serō Ag Strategies.

When it comes to sustainability benefits, team real tree or fake tree? The fake tree often gets a pass because it’s reusable, not to mention convenient and customizable. The sad truth is, they don’t beat real trees, even if real trees are being cut down and replaced every year. Most fake trees are made from PVC plastic, steel, and chemical additives, shipped halfway around the world, and are nearly impossible to recycle. Fake trees break down into microplastics, adding one more thing to your home that may be quietly contributing to health issues. And, ultimately, many say you’d need to keep a fake tree for at least a decade to break even with the impacts of a real one.

Real Christmas trees are grown on farms specifically planted for harvest, meaning no forests are being cleared to make room for them. While they’re growing, they sequester carbon, stabilize soil, support wildlife habitat, and often help keep agricultural land from being sold off for development. After the holidays, most real trees can be composted, mulched, or recycled into erosion control or habitat projects. There’s also a long history here worth remembering. Christmas tree farming in the U.S. took off in the early 20th century as a way for farmers to diversify income and stabilize rural economies. Today, there are thousands of family-run tree farms across all 50 states. Buying a real tree is a vote for working lands staying working lands.

But there’s still a fair critique of the traditional cut tree model: one tree, one season. That’s where tree rental comes in. Tree rental programs provide a living, potted tree that you keep for the holidays and then return to be reused year after year, until the tree is too big to be a decoration and is planted either at a farm or, in some cases, as part of restoration projects. The same tree can celebrate a decade of Christmases, providing environmental benefits all the while.

Sustainability is often about choosing the least-wasteful option that fits real life. Christmas traditions are often criticized for their encouragement of overconsumption, but luckily, we can make a few choices here and there that reduce the waste. Real Christmas trees give us a cleaner option while supporting farmers. All we have to do is accept wrapping lights on them ourselves. And if you’re already decked out with fake trees, the key is take care of them so they last as long as possible before heading to the landfill.

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If you haven’t already, check out our previous newsletters.

About Serō Ag Strategies

At Serō Ag Strategies, we bridge farmers and supply chain partners by transforming complex agricultural data and policy into actionable insights. We also work to create and grow markets for commodity crops by aligning production with evolving demand, policy shifts, and sustainability goals. Combining multinational expertise with the personal touch of boutique consulting, we specialize in economic and sustainability analysis that drives strategic innovation.

Click here to learn more about Serō Ag Strategies.

The turkey industry is embracing the idea that sustainability and operational success are complementary goals. Across the country, producers are implementing changes that make both economic and environmental sense. We’re seeing solar panels on barn roofs, sophisticated monitoring systems that optimize energy use, and water management technologies that squeeze efficiency out of every drop. Even turkey litter is getting a second life as nutrient-rich fertilizer, turning what was once considered waste into a valuable resource for crop production.

Last week, Carlee attended the Sustainable Ag Summit and sat in on a session that showed if we want to meaningfully reduce emissions in meat production, we have to look at feed as a major component. Feed represents the bulk of a turkey operation’s environmental impact, making it one of the most promising levers for positive change. One clear approach involves incorporating alternative grains like sorghum into feed formulations, which offers sustainability benefits due to its lower water requirements and ability to sequester carbon through its deep root structure. It’s a small shift that demonstrates how thoughtful ingredient choices can make a big difference.

Another area where gains are being made is genetics. Through selective breeding programs, feed conversion ratios improve, allowing modern turkeys to produce more meat on less feed year after year. When you combine these breeding advances with tighter biosecurity protocols and improved barn management—better ventilation systems, more precise environmental controls, thorough cleaning and disinfection between flocks—you’re looking at operations that are both more profitable and more sustainable.

The investments being made today in technology, genetics, and operational efficiency are setting the industry up to meet tomorrow’s challenges, whatever they may be. As consumer expectations evolve and markets shift, turkey producers who’ve been steadily improving their operations will find themselves well-positioned.

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If you haven’t already, check out our previous newsletters.

About Serō Ag Strategies

At Serō Ag Strategies, we bridge farmers and supply chain partners by transforming complex agricultural data and policy into actionable insights. We also work to create and grow markets for commodity crops by aligning production with evolving demand, policy shifts, and sustainability goals. Combining multinational expertise with the personal touch of boutique consulting, we specialize in economic and sustainability analysis that drives strategic innovation.

Click here to learn more about Serō Ag Strategies.

• Indirect land use change (ILUC) was born from a good idea: preventing deforestation linked to global biofuel demand.

• The models used to estimate ILUC rely on economic theory, not measurable land conversion.

• A risk-based approach keeps the goal intact while grounding policy in observable reality.

Land use change defined

Land use change has been a highly debated topic for nearly twenty years. It’s a lingering aspect of renewable fuel policy, and rulemaking goes back and forth on penalties included for indirect land use change (ILUC). Many people were first introduced to the concept in 2008, when Princeton researcher Timothy Searchinger published a paper suggesting that biofuels might be worse for the planet than fossil fuels. His logic stated that if U.S. grain acres shift from food to fuel, global markets respond. Higher prices encourage farmers abroad to plow up grasslands or forests to replace the lost supply. Even if biofuels shrink emissions at home, they could spark deforestation abroad.

This idea caught on with government officials and nongovernmental organizations alike. Rulemakers assigned carbon intensity penalties based on the idea. Farmers and ethanol producers suddenly found themselves on the hook for emissions from land they’d never seen. But ILUC has always been more theory than fact. The models rely on economic guesses about how distant farmers might behave, not on measurable, observed data. Furthermore, it’s almost impossible to prove that a farmer in Brazil leveled part of the forest as a result of the actions of a farmer in Iowa. And fifteen years later, the policy still hasn’t caught up with that lack of evidence.

Before we dig into why that matters, it’s worth defining the terms. Direct land use change happens when land use physically shifts, for example, grass to crops, or crops to pavement. Indirect land use change tries to capture the ripple effect. It’s the idea that when a grain is redirected to biofuel production in one part of the world, it triggers farmers in other parts of the world to make up for the loss by deforesting acres to produce grain for food. Land use change is the umbrella that includes both direct and indirect effects.

As you can see, we’re talking about many things when we say “land use change.” The concept brings with it many questions and a lot of frustration for domestic farmers. While we can appreciate the sentiment of wanting to stop deforestation, this is a fraught path toward that end.

When an idea becomes legislation

When Congress expanded the Renewable Fuel Standard (RFS) under the Energy Independence and Security Act of 2007, the goal was to reduce dependence on foreign oil and cut greenhouse gas emissions through biofuel use. To ensure the program delivered actual climate benefits, lawmakers required the EPA to calculate the lifecycle emissions of each fuel pathway. That directive opened the door for the idea of indirect land use change to enter the policy conversation. Around the same time, Searchinger’s 2008 paper made national headlines. Environmental groups seized on the theory, framing ILUC as the hidden cost of biofuels. Policymakers who were eager to appear cautious about unintended consequences adopted the concept before the science had matured. When EPA finalized the RFS2 rule in 2010, it included modeled ILUC emissions in the carbon intensity scores used to determine which fuels qualified as “renewable.”

That decision was a watershed moment. It cemented a theoretical construct into federal regulation, turning economic forecasts into compliance penalties. To justify the inclusion, EPA relied heavily on early versions of models like GTAP and FAPRI, which attempted to simulate how global agriculture might respond to increased biofuel demand. But even at the time, those models produced significantly different outcomes, some showing major land conversion, others showing minimal change. Rather than treating ILUC as an open research question, regulators treated it as a known quantity, effectively baking uncertainty into the law. The result was a system that burdened biofuels with hypothetical emissions while giving fossil fuels a pass on their own indirect effects, such as geopolitical instability or long-term land degradation from extraction. In short, ILUC became policy not because it was proven, but because it was politically convenient at a moment when environmental advocates and regulators aligned.

How land use change is calculated – models upon models

The most straightforward answer for calculating land use change is: land use change equals direct land use change plus indirect land use change. But of course, it’s a bit more complicated than that.

Direct land use change is calculated using measurable data on how land physically shifts from one category to another. Analysts use satellite imagery, land cover databases, and field surveys to quantify the number of acres converted. Those acreage changes are then paired with known carbon stock values for soil and vegetation to estimate emissions or sequestration. The result is a calculation grounded in observed evidence of actual land conversion multiplied by carbon flux per acre.

Indirect land use change is calculated through economic modeling, usually using computable general equilibrium (CGE) or partial equilibrium (PE) models. CGE models simulate how the entire global economy adjusts to policy or market shifts, linking agriculture with energy, trade, and manufacturing. Partial equilibrium (PE) models narrow that focus to agriculture alone, using market data to estimate how production and trade might respond. Land use and emission accounting models estimate how changes in land cover or management affect greenhouse gas emissions, combining spatial data, crop and soil parameters, and carbon stock values to quantify the climate impact of agricultural or policy-driven land shifts. Econometric models analyze historical data while spatial and biophysical models map how land could change based on physical factors. Hybrid models combine some number of these other models for a more nuanced approach. Together, all of these represent different ways of answering the same question: how markets, people, and landscapes react when demand for crops shifts. But none yet offer a definitive, measurable picture of indirect land use change. Let’s now dive into some specific models that address land use change (not a full list, but a good starting point).

The Global Trade Analysis Project (GTAP) and its Agro-Ecological Zone Emission Factor (AEZ-EF) model are often used together to estimate indirect land use change (ILUC). GTAP is a global economic model that simulates how production, trade, and land allocation might respond to policy shocks like increased biofuel demand. Its outputs, however, rely on assumed elasticities and market theory rather than observed land behavior. AEZ-EF converts GTAP’s projected land shifts into carbon emissions by dividing the world into climate- and soil-based zones, each with its own emission factor. While AEZ-EF adds spatial detail, its results are only as reliable as GTAP’s hypothetical inputs.

Other models emphasize real-world calibration over global theory. The Food and Agricultural Policy Research Institute (FAPRI) model uses historical agricultural data to simulate market responses, producing more conservative and intuitive ILUC estimates but missing cross-sector feedback. The Forest and Agricultural Sector Optimization Model (FASOM) builds on FAPRI data to project how U.S. producers shift land among crops, pasture, and forests, offering detailed national insights but limited global reach. The Carbon Calculator for Land Use and Land Management Change from Biofuels Production (CCLUB) translates modeled land changes, often from GTAP, into carbon outcomes using regional soil and biomass data. Linked to GREET, it ties land use emissions to full fuel life cycles, but like AEZ-EF, its accuracy depends on the validity of its input scenarios.

All of these models share a common flaw. They depend on each other’s assumptions more than on observed evidence. Economic models generate hypothetical land shifts, and carbon accounting tools convert those projections into emissions, layering uncertainty on top of uncertainty. The result is a chain of inference that drifts further from reality with each link. Yet each model continues to shape how policy is made. GTAP underpins EPA’s and CARB’s official lifecycle analyses, making it the foundation of regulatory carbon accounting. AEZ-EF translates those GTAP outputs into the emission factors that ultimately determine whether a biofuel meets federal carbon-reduction thresholds. FAPRI guides USDA and congressional projections of how crop prices and acreage respond to biofuel demand, influencing perceptions of market impact. FASOM informs U.S. land and forestry policy, helping estimate domestic carbon stocks under different land-use scenarios. And CCLUB, tied to the GREET model, links all of that back to the final lifecycle emission scores used in fuel policies like the Low Carbon Fuel Standard in California. Together, they form the scaffolding of modern biofuel regulation. Models feeding models until theoretical assumptions become enforceable policy. After more than a decade of refinement, the science of indirect land use change still rests on models built to explain theory, not to measure fact.

How modeling breaks down into uneven, unfair penalties

The first flaw lies in how ILUC modeling assigns carbon penalties unevenly across countries and crops. Under the frameworks used by EPA and California’s Air Resources Board, Brazilian sugarcane ethanol typically carries a lower indirect land use change penalty than U.S. corn ethanol, even though deforestation and grassland conversion in Brazil are well-documented and ongoing. The models assume that when U.S. crops are used for fuel, global demand shifts production to places like Brazil, where farmers clear land to grow crops for food. Yet when Brazilian sugarcane is used for ethanol, that expansion is treated as a lower risk. The result is an upside-down logic where American farmers are penalized for theoretical land clearing abroad, while producers in countries with active deforestation are rewarded with lower carbon scores.

Second, the policy implication creates an unfair competitive advantage. Because ILUC penalties feed into carbon-intensity scores, they influence market access, credits, blending requirements, and export viability. When Brazilian sugarcane ethanol carries more favorable scores, it effectively gains preferential treatment in both domestic and international biofuel markets. At the same time, U.S. ethanol is burdened with higher assumed emissions even though the actual empirical chain of “U.S. crop → global crop shift → deforestation” is tenuous at best. Some analysts have pointed out that regulators continue to apply relatively large ILUC penalties despite mounting evidence that the primary land-use response globally has been increased efficiency rather than massive new conversion. Moreover, U.S. grain production has consistently outpaced demand, with record yields and stable acreage across corn, sorghum, and other ethanol feedstocks. Even as a share of these crops goes to biofuel, carryout stocks remain high and exports struggle to clear the surplus. There is no evidence that diverting grain to ethanol causes food shortages or new land conversion when the U.S. continues to produce more grain than the market can absorb. All of this means U.S. farmers and biofuel producers shoulder model-based liabilities while facing tougher market conditions.

Finally, this logic collapse undermines the credibility of the entire regulatory structure around ILUC. If models treat the same feedstock differently depending on geography, then policy ends up penalizing or rewarding stakeholders based more on where they operate than what they do. That’s a fundamental logical problem that demands policymakers recalibrate how indirect land use change is handled if the goal is fairness and accuracy.

The intent isn’t the issue

It’s important to say this plainly: the people who first pushed for indirect land use change penalties weren’t wrong to care. The idea came from a good place. If land expansion in one part of the world really does undo the carbon savings of biofuels somewhere else, then it should be part of the climate accounting. That logic is sound in theory. The trouble is that indirect land use change isn’t something we can observe.

It stands to reason that land use change could cause emissions elsewhere. Markets are connected, and agricultural decisions in one country ripple through the global system. But the further those ripples spread, the harder they are to trace back to a single cause. That’s where ILUC modeling breaks down. It tries to pin global cause and effect to one variable in a noisy, adaptive system shaped by weather, policy, technology, and human behavior. Even the most sophisticated models can’t separate one signal from the rest without leaning on speculation.

So while the principle behind ILUC reflects a serious concern, the practice of turning it into a policy penalty does more harm than good. In fact, one study looked at the social implications of an ILUC penalty and found that adding ILUC penalties to biofuel policy delivers little additional climate benefit for the cost of higher fuel prices, reduced biofuel investment, and lost emissions savings from displaced fossil fuels..

A better way forward

There’s a smarter way to deal with the risk of indirect land use change without pretending we can calculate it precisely. A risk-based approach, like the one already used in Canada and reflected in the European Union’s Renewable Energy Directive III (RED III), shifts the focus from speculative modeling to measurable safeguards. Instead of assigning blanket carbon penalties based on global assumptions, regulators evaluate the likelihood that feedstock production in a given region contributes to deforestation or habitat loss. Low-risk pathways, including those grown on existing cropland or under certified sustainability systems, qualify without penalty. High-risk pathways, such as those linked to new land conversion, face tighter scrutiny or are simply excluded.

This approach keeps the intent of ILUC modeling intact. It still discourages land conversion, but grounds it in observable criteria rather than theoretical linkages. Canada’s Clean Fuel Regulations already use this framework, requiring biofuel producers to demonstrate that their feedstocks come from established agricultural land rather than newly cleared areas. The EU’s RED III builds on the same concept, flagging “high ILUC-risk” crops and rewarding verified “low-risk” supply chains. Both systems acknowledge that risk exists but stop short of pretending to know exactly how much carbon it represents.

A risk-based model offers fairness, transparency, and real-world accountability. It recognizes that not all production carries equal risk and that data should drive regulation. In doing so, it keeps global markets open to sustainable biofuels while closing the door on practices that genuinely threaten forests and grasslands. That’s how you address land use change without punishing the farmers and ethanol producers who are part of the solution.

Rethinking the path

At its core, indirect land use change began as a moral question: how do we make sure solving one problem doesn’t create another? That question still matters. But after fifteen years of modeling, debate, and shifting penalties, it’s clear that the way we’ve tried to answer it hasn’t worked. The models built to measure ILUC have become more precise in form but not in truth. A risk-based framework offers a way out: it keeps global accountability on the table while returning fairness, logic, and observation to the center of the conversation. If policy is meant to follow evidence, not imagination, then it’s time we build a system that does the same.

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About Serō Ag Strategies

At Serō Ag Strategies, we bridge farmers and supply chain partners by transforming complex agricultural data and policy into actionable insights. We also work to create and grow markets for commodity crops by aligning production with evolving demand, policy shifts, and sustainability goals. Combining multinational expertise with the personal touch of boutique consulting, we specialize in economic and sustainability analysis that drives strategic innovation.

Click here to learn more about Serō Ag Strategies.

• What’s great today won’t be “good enough” next year. An essential feature of durable leadership is continuous improvement.

• From Microsoft’s reinvention to Steph Curry’s shot-tracking to Kansas farmers managing water together, the results demonstrate the power of innovating from a position of leadership.

• The next generation of ag leaders will move beyond today’s standards, embracing new methods including precision technology and the discipline to prove it’s working.

We’re excited to share that this edition was written in collaboration with Dan Northrup, Principal, Science and Technology, Galvanize.

Is “good enough” holding us back?

“Good enough.” It’s the phrase we use when we’re tired, when resources are thin, when we just want to move on to the next thing. It gets the job done, at least for today. But history shows us something uncomfortable: “good enough” today won’t be good enough tomorrow. In the moment, it feels practical. In hindsight, it’s the first symptom of decline.

Agriculture cannot afford to rest on its laurels. The industry has a proud record of innovation and efficiency gains, but past progress is no guarantee of future resilience. If anything, history shows that when agriculture settles for “good enough,” it risks being overtaken by new challenges faster than it can adapt. Consider water: if we continue relying on the same pumping practices that built prosperity in the twentieth century, we risk draining away the foundation of tomorrow. Aquifers like the Ogallala are already showing the strain. What once seemed like “good enough” resource management now carries the very real possibility of leaving farms, towns, and entire regions without the water they need to survive. The stakes are too high to assume the old playbook will keep working.

Reinvention over obsolescence

The first lesson comes from technology, where many companies have faced “good enough” traps, while others use market pressure to pivot and become more successful than ever. For decades, Microsoft’s boxed Office products and enterprise software licenses dominated the market with billions in annual revenue and monopolistic market share. If any company had earned the right to rest on “good enough,” it was Microsoft in the early 2000s.

But when Amazon Web Services (AWS) emerged, the ground shifted for Microsoft. AWS proved that computing could move to the cloud and deliver speed, cost savings, and virtually unlimited scalability. Companies no longer had to build and maintain their own data centers. Instead, they could share massive infrastructure with thousands of others and pay only for what they used. Workloads could shift seamlessly across servers and regions, outages could be absorbed without shutting businesses down, and scaling up no longer required years of capital investment. The old model of boxed software tied to on-premise hardware began to look fragile, while the cloud opened the door to an entirely new revenue stream.

Microsoft responded by reinventing itself with Azure, Office 365, and a subscription-based model that emphasized continuous innovation. Moving into cloud infrastructure not only preserved its role as a leader in software and productivity but also created a powerful new growth engine. The company gained another advantage as well. Many retailers and competitors prefer not to run their systems on Amazon-owned infrastructure, giving Microsoft an opening that Azure has been able to fill. Microsoft’s pivot reminds us that even market leaders can’t assume dominance will last.

Redefining the geometry of success

Sports offers a second lens where the best got better: Steph Curry’s refusal to accept “good enough” redefined the geometry of basketball. Curry was already one of the best shooters in the league. Most players looked at the three-point line as the limit of their range, Curry treated it as a suggestion. By going further, he forced the entire sport to recalibrate. Defenders had to extend their range six or even ten feet farther. That change reshaped spacing, ball movement, and offensive philosophy across the league. The ripple effects were enormous: teams redesigned rosters around long-range shooting, defensive schemes stretched and fractured, and analytics departments rewrote their models for efficiency.

Curry used every tool he could to maximize his ability. He added shot-tracking technology to measure entry angle, arc, and depth. Just making shots wasn’t enough. Some makes are better than others, and Curry got better in practice to add tolerance under pressure. His relentless pursuit of excellence made his past successes the raw material for improvement.

Curry’s influence went far beyond the court. He changed how kids practice in driveways, how coaches design youth leagues, how front offices draft and trade, and even how broadcasters tell the story of a game. The true measure of his legacy is in how completely he rewired the expectations of an entire sport.

A new model for shared water

You’ve heard us sing the praises of Kansas’s Local Enhanced Management Areas before, but let us serenade you again. Kansas farmers in Groundwater Management District 4 faced a stark reality: the Ogallala Aquifer was declining faster than it could recharge. For decades, “good enough” meant pumping what was needed to meet annual production goals without a thought of aquifer health. But the reality caught up with this approach. Without change, wells would run dry and with them the economic base of western Kansas.

Instead of waiting for top-down regulation, they built something new: the state’s first Local Enhanced Management Area (LEMA). This framework allowed producers themselves to set voluntary limits on pumping, tailored to local hydrology and cropping systems. It was not a symbolic gesture. Farmers accepted reductions in water use, betting that smarter allocation could stretch the aquifer’s life without sacrificing their livelihoods. The gamble paid off: water use fell, aquifer declines slowed, yields remained stable, and, most importantly, incomes went up. Producers discovered that “using less” doesn’t equal “producing less.”

The map below shows just how uneven the Ogallala’s decline has been across western Kansas. In some areas, the aquifer has lost more than half its saturated thickness since irrigation began, while other pockets remain relatively stable. That patchwork of red and blue underscores why one-size-fits-all regulation won’t work. Local Enhanced Management Areas succeed precisely because they adapt to these differences.

The LEMA model is a proof of concept. It shows that agriculture can manage shared resources before a crisis forces it. It demonstrates that communities can innovate collectively, and in doing so, preserve both their land and their future. Most of all, it reminds us that “good enough” water practices, the kind that once fueled growth, won’t sustain it. Progress comes not from defending the past, but from redefining what responsible stewardship looks like in the present.

When margins are hard to find, ag needs all the help it can get

For decades, agriculture has been on the cusp of breakthrough after breakthrough. Precision agriculture, artificial intelligence, computer vision, and fungicides are all within reach. Each of these tools promises to move us beyond efficiency into true resilience. Yet too often, we’ve treated them as optional add-ons instead of necessities.

Fertilizer is a perfect example of this tension. Higher yields require higher inputs. It’s a simple reality that most critics of agriculture overlook. The obligation is to use it better. Every pound applied is both a cost and a responsibility. Misapplied, it drains value: lost nutrients, wasted dollars, and environmental consequences that critics seize on. Applied with precision, it is one of the sharpest tools farmers have to protect both their bottom line and their reputation. Stewardship and profitability rise together, and when agriculture invests in better use of fertilizer, it takes the higher ground in answering its critics.

Take precision agriculture. Variable-rate technology, GPS-guided planters, and real-time soil monitoring allow farmers to apply nutrients and water exactly where they are needed. The potential is to maximize yields while cutting waste and reducing environmental impact. But the adoption curve has flattened. Too many operations still treat precision tools as bells and whistles rather than standard practice.

Artificial intelligence offers another leap forward. Algorithms can already aggregate agronomic research, digest complex data sets, and deliver field-specific recommendations faster than any extension bulletin or seed guide. This could collapse the time lag between discovery and practice, shrinking decades of research translation into a single season. Yet in many cases, AI is used to fine-tune existing decisions rather than to rethink the system itself. Or, it isn’t being used at all.

The same pattern holds in computer vision and automation. We now have implements that can scan for weeds in real time and deliver micro-doses of herbicide only where needed, slashing chemical use and fuel consumption. This should be a watershed moment, transforming input economics and environmental outcomes in one sweep. But instead of embracing it as the new baseline, much of the industry still leans on traditional broadcast spraying. Certainly, there are cost considerations. Adding technology to this farm economy is difficult, and low farm profitability has ripple effects that affect everyone in the industry including seed and input providers. But is the upside worth figuring the economic piece out? History seems to imply that it is, particularly when you look at progress and technology adoption in other geographies, particularly South America.

Just like Steph Curry needed more than a high shooting percentage to redefine basketball, farmers need more than yield monitors to prove they’re improving. Curry broke down his shot with tools that tracked details that separated the good from the great. Agriculture has the same opportunity. Precision tools let farmers study their fields in greater depth and capture progress even when weather muddies the scoreboard. Deeper metrics like nutrient-use efficiency, water-use efficiency, and soil moisture retention paint a fuller picture of progress. Growing sophistication with on-farm testing has the potential to create shot trackers for production ag. Farmers gathering data can demonstrate improvements and provide key points to counter critics who are often using old or inaccurate arguments.

These technologies show what agriculture could do. They offer a future where profitability and sustainability are not at odds but mutually reinforcing. The danger is not that the tools don’t exist. The danger is that we stop short, congratulating ourselves on incremental progress while the real transformation remains unfinished. That is what “good enough” looks like in agriculture today—not failure, but the refusal to pursue the full measure of what’s possible.

From good enough to greatness

The lesson across all these examples is the same: “good enough” is rarely good for long. Kansas farmers proved that voluntary restraint is stronger than complacency. Microsoft proved that reinvention is critical to relevance, even for current market leaders. Curry proved that even the best can get better.

The uncomfortable but liberating truth is that your standing as the best is only as good as the next thing that comes along. And that’s not bad news. It’s an invitation to set a higher bar.

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If you haven’t already, check out our previous newsletters.

About Serō Ag Strategies

At Serō Ag Strategies, we bridge farmers and supply chain partners by transforming complex agricultural data and policy into actionable insights. We also work to create and grow markets for commodity crops by aligning production with evolving demand, policy shifts, and sustainability goals. Combining multinational expertise with the personal touch of boutique consulting, we specialize in economic and sustainability analysis that drives strategic innovation.

Click here to learn more about Serō Ag Strategies.

• Gerrymandering goes back to 1812, when a Massachusetts district was shaped like a salamander to give one party an edge. It’s been a political tool used by both sides ever since.

• While not called the same thing, gerrymandering isn’t limited to the United States. Post-WWII Eastern Europe led the USSR to manipulate lines to get access to valuable resources, and left Central Asia handling water conflicts once the superpower was dissolved.

• We argue gerrymandering isn’t limited to votes. The same line-drawing can apply to water, land, and even economic resources.

Gerry-what?

Calling gerrymandering a hot topic is an understatement. According to Merriam-Webster (yes, it’s in the dictionary), gerrymandering is the practice of dividing or arranging a territorial unit into election districts in a way that gives one political party an unfair advantage in elections. From its origins in the early 1800s to today’s razor-thin races, drawing lines on a map has long been a political weapon. Both parties have embraced and condemned it depending on who benefits. These days, politicians rarely admit they’re “gerrymandering.” Instead, they talk about “updating” or “fixing” district boundaries. But voters aren’t fooled. Most people understand that the way districts are drawn can tilt the playing field long before a single ballot is cast.

But this line-drawing game doesn’t stop with congressional seats. It shows up in the borders of water districts, natural resource districts, and even school and hospital districts that decide who gets access to what. Industrial hubs have seen lines drawn to funnel funding toward manufacturing, just as agricultural regions have watched maps shift to strengthen or weaken farm voices in Congress. The lines on a map can determine not just who holds office, but who controls land, water, and the flow of money.

Gerrymandering’s political roots

Gerrymandering has deep roots in U.S. history. The term itself comes from an 1812 “Gerry-mander” cartoon, satirizing a Massachusetts district contorted (like a salamander) to favor Gov. Elbridge Gerry’s party.

Since then, politicians have been tempted to “choose their voters” by drawing odd-shaped districts that all but guarantee outcomes. This is a bipartisan game; both Republicans and Democrats engage in gerrymandering whenever they have the chance. If you’re a Democrat in a blue state, you tend to love the map you drew; if you’re a Republican in a red state, you love your map. The recent example of Texas redistricting and the California response shows this very clearly. The common techniques are “packing” (cramming your opponents’ voters into a few districts) and “cracking” (splitting opposing voters across many districts) to dilute their influence.

This practice has only intensified in recent years. After the Supreme Court ruled in 2019 that partisan gerrymanders can’t be challenged in federal court, mapmakers grew even bolder. This resulted in skewed maps where elections can almost be decided before a single vote is cast, and whole communities find themselves politically carved up. But gerrymandering’s impact doesn’t end with election results. It ripples into how resources are allocated and who gets a voice in policy debates. In other words, the same mapping tricks used to secure votes can also secure advantages in agriculture, water, and industry.

Gerrymandering spans the globe

Gerrymandering might seem like an American invention, but drawing lines to gain an advantage is a global phenomenon. History offers stark examples. After World War II, Joseph Stalin obsessively redrew borders across Eastern Europe and Central Asia, not only to expand Soviet territory, but to divide and destabilize populations. These new lines deliberately mixed or separated ethnic groups in a classic “divide-and-rule” strategy. The goal: set ethnic communities against each other so they couldn’t unite against Moscow’s influence. In making border changes, Stalin had an eye on natural resources and strategic assets as well. For instance, he shifted Soviet republic boundaries to secure oil fields and warm-water ports for the USSR. In one case, Stalin united the Azerbaijani-populated areas across borders specifically to bring additional oil reserves under Soviet control. In another, he sought to make an entire sea (the Sea of Okhotsk) effectively a Soviet lake. The new map lines achieved his security and resource goals, but they left a legacy of geopolitical tension. Some countries emerged from this era with awkward borders that lacked access to key resources.

For decades, Moscow had treated water as a regional utility. Reservoirs built in Kyrgyzstan and Tajikistan fed vast irrigation networks that stretched into the cotton fields of Uzbekistan and the grain lands of Kazakhstan. Nobody cared that the pipelines and canals crossed internal borders, because the whole system was centrally managed. But when internal borders hardened into international ones, reality shifted overnight. Suddenly, the upstream countries held the keys to the dams, while their downstream neighbors were left bargaining for the flows that kept their farms alive. The result? Unequal leverage at the negotiating table, constant disputes, and water deliveries that often came too little, too late, or were tainted by poor quality. Farmers downstream found themselves living with the consequences of decisions made decades earlier, when planners in Moscow prioritized economic output over the natural geography of rivers and basins. And more than thirty years later, the region is still grappling with the legacy of those mismatched lines.

Gerrymandering beyond politics

When we hear “district,” we usually think of voting districts. But not all districts are electoral – some are drawn purely to manage resources. In the United States, water and land management often rely on their own mapped zones. And just like political districts, how those lines are drawn can create winners and losers.

Case 1: Nebraska’s Natural Resource Districts (NRDs). Nebraska took a unique approach in the 1970s by establishing 23 Natural Resources Districts. These are local governance units for soil and water conservation. Crucially, these districts were drawn along river basin boundaries, not county lines. The idea was to manage resources based on natural watersheds. Each NRD has an elected board with authority to allocate groundwater, limit well drilling, levy taxes for projects, and enforce conservation rules. In essence, if your farm lies within the boundary of a given NRD, that local board decides how much water you can pump and what practices you must follow. Drawing the boundaries around watersheds was meant to be fair. Most people who rely on the same river basin or the portion of an aquifer within a given Natural Resources District are managed by the same NRD board, since NRD boundaries are based on watershed lines, not county borders. However, some aquifers and water-quality issues cross NRD boundaries, so not everyone using the same groundwater resource will always fall under a single management authority. This avoids the situation where an upstream county overuses water while a downstream county runs dry. By basing districts on hydrology, Nebraska tried to ensure resource decisions match natural conditions. Of course, even watershed-based lines have consequences: if a particularly valuable resource (say, an especially full section of the Ogallala Aquifer) lies inside one district, that district’s residents hold greater sway over that water. Farmers inside the boundary might welcome stricter pumping limits to sustain their wells, while those just outside could have less say, even if they share the underground water indirectly. The NRD system shows that how we draw resource districts can directly affect who gets a seat at the table for managing vital assets. And Nebraska isn’t alone, numerous other states manage their water similarly.

Case 2: California’s Water Districts. In the western U.S., water is so critical that entire authorities are created to manage its delivery. California, in particular, is a patchwork of regulatory authorities, some small, some enormous, that don’t always align with city or county lines. And there’s debate over whether some of those lines were drawn to favor certain powerful interests. Take the Westlands Water District in California’s Central Valley. Big landowners formed Westlands in the 1950s, and it serves more than 1,000 square miles of farmland. Why draw such a huge district? Aside from geographic rationale, uniting that vast area under one district gave Westlands farmers collective clout to secure federal irrigation water. In fact, Westlands now holds a permanent contract for up to 1.15 million acre-feet of water per year – more than double what Los Angeles uses in a year. Thanks to the district’s clout, its growers gained extraordinary control over a massive water supply. Critics have long argued that Westlands’ boundaries (and those of other large water districts) were drawn because valuable resources lay within. By encircling the fertile west side of the San Joaquin Valley, Westlands ensured that water from federal projects would be largely dedicated to those lands and not to surrounding communities.

If a prominent farming bloc can draw a district line around itself and thereby claim the lion’s share of a river or aquifer, that’s effectively gerrymandering of natural resources. If you live inside such a resource district, you might have reliable water delivered and political leverage to keep it that way. If you live outside, you could be left high and dry.

The industry effect

Political lines on a map can also group (or split) economic engines. Heavy industrial regions can end up concentrated in a single district or carved into pieces, and both scenarios carry consequences. Lawmakers know that a district full of factories and blue-collar neighborhoods has different needs (and opportunities) than one of suburbs or farms. So when drawing maps, there could be a temptation to either isolate these areas or lump them with others, depending on the goal.

One approach is to pack industrial sites together into one district. For example, consider a state legislature drawing a district around Cleveland’s historic manufacturing belt or the steel mills of western Pennsylvania. Cramming as many of those sites as possible into one district can effectively create a representative whose constituency is “all industry, all the time.” That representative, secure in a district dominated by factory workers and an industrial tax base, will fight hard for industry-friendly funding and policies. In fact, channeling a high concentration of industry into a district can attract government investment. A district known as the “industrial hub” might get priority for federal grants to clean up brownfields, new highway projects, or economic redevelopment funds. Recent clean energy investments reveal a surprising trend: many of the congressional districts attracting new cleantech manufacturing projects are represented by Republicans. These districts tend to be industrial or rural areas with ample land, workforce availability, and political willingness to host large-scale projects. Investment flows tend to favor regions that can provide the resources and support for such developments, highlighting how political representation, local capacity and geography have come together to influence the location of the clean energy boom. In short, drawing the lines to include key industrial assets can channel public and private resources into that lucky district.

On the other hand, there’s the tactic of splitting industrial areas among multiple districts, a form of “cracking” not of voters, but of communities with common economic interests. This is often done to dilute the political power of urban, working-class populations (who might demand stricter pollution controls or vote against incumbents). The concerns of the industrial zone, like pollution, brownfield cleanup, and public health, can then be downplayed by a representative whose voters mostly live in cleaner, leafier areas. This kind of gerrymandering can muffle the voice of communities living next to smokestacks. If they were kept intact in one district, they could elect a champion to press for air quality monitoring or cleanup funds if needed. Cracked apart, they’re minority voices in districts dominated by others.

Finally, consider rich value-added agricultural regions that include the packing plants, grain elevators, and ethanol plants that dot rural America. If a powerful lawmaker’s district includes a cluster of corn ethanol plants, you can bet they will fight tooth and nail for favorable renewable fuel policies. Ensuring those facilities are inside one sympathetic district (rather than split among several) might make it easier to secure targeted infrastructure. While hard to prove intent, it’s conceivable that some lines are drawn to concentrate (or dilute) economic power centers, making gerrymandering both about gaining partisan advantage and securing economic opportunity.

How this might affect the farm

All these line-drawing shenanigans come down to a few key things: who represents you in the halls of power, how agricultural policy is shaped and who controls the resources. The Farm Bill is a prime example. For decades, it’s been a bargain between rural lawmakers pushing farm programs and urban lawmakers pushing nutrition assistance. But when gerrymandering eliminates districts that blend farms and cities, the middle ground weakens or even disappears. Rep. Angie Craig of Minnesota leads a district that spans both suburban and rural communities, but leaders like her are becoming rare. If future maps erase these “bridge” districts, Congress risks splitting into camps that rarely overlap: one focused on crops and insurance, the other on food availability and air quality.

District lines also decide which voices carry weight in resource fights. A watershed split across several districts might leave farmers without strong backing on irrigation, while a unified ag district could produce a loud champion. Likewise, urban concerns about water quality or sustainability can be diluted or overshadowed depending on how the map is drawn. In short, maps can ultimately dictate priorities. The next time an ag bill advances or a water rule shifts, remember: the outcome may trace back to who drew the lines in the first place.

What to do when it gets out of hand

Gerrymandering may start with politics, but it ends with power. We began with a question: If political borders can be drawn to favor certain voters, resources, or industries, who is really deciding the future of your interests? Those who hold the pen in drawing the map hold enormous sway over real-world outcomes. If this makes you uneasy, it should. But it’s also empowering: once we recognize the hidden influence of district lines, we can do something about it. This isn’t Soviet Russia. It’s still the United States, and though we’re working through our fair share of problems today, we the people still have the luxury of participation in these processes. That’s what makes our system great.

First, get informed. Take a closer look at how your own voting districts are drawn. Investigate your local resource districts too: Who decided the boundaries of your water district, or conservation district, and when? Was it done for sound management or possibly to benefit a select group? Public records, local meetings, and independent watchdogs can shed light on these questions.

Second, demand fairness and transparency. Many states and counties are moving toward independent redistricting commissions or clearer criteria (like keeping “communities of interest” together) to curb the worst map tricks. If you’re in agriculture, push to keep farming regions intact when maps are redrawn so that your community’s voice isn’t diluted. At the same time, consider the flip side: truly fair maps might mean rural areas might get somewhat less representation than they do in gerrymandered setups. Fairness ensures everyone’s voice is heard in proportion to their numbers, but there are tradeoffs that must be weighed.

Finally, remember that awareness is the antidote to manipulation. Gerrymandering, political or otherwise, thrives in the shadows of wonky algorithms and opaque deals. By bringing it into the light, we can make it a kitchen-table issue. Talk to your neighbors: Does it make sense that a city 100 miles away shares your district but the valley next door does not? Who benefits from that? Such conversations build pressure for change if change is needed.

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About Serō Ag Strategies

At Serō Ag Strategies, we bridge farmers and supply chain partners by transforming complex agricultural data and policy into actionable insights. We also work to create and grow markets for commodity crops by aligning production with evolving demand, policy shifts, and sustainability goals. Combining multinational expertise with the personal touch of boutique consulting, we specialize in economic and sustainability analysis that drives strategic innovation.

Click here to learn more about Serō Ag Strategies.

• Plastic revolutionized our world. It touches almost every aspect of our lives, making things more efficient and scalable, but it has a price.

• We’re finding plastic in soil, air, water, and even our own bodies. Plastic doesn’t break down for centuries, making this a persistent and prevalent issue.

• Given the potential for chronic health problems as a result of plastic, we have to ask ourselves if this is a problem worth solving.

Where our pile of plastic started

We don’t often think of plastic as an agricultural input, but we should. Plastic is woven into modern farming. It’s prevalent in every system we use, ingrained in the supply chain. Like virtually every other industry, plastic has replaced other materials anywhere it can. It’s efficient, cheap, and disposable. It’s quite literally everywhere. And that’s precisely the problem – plastic doesn’t stay put. Over time, it cracks, crumbles, and chips into something smaller and more insidious.

Microplastics are tiny plastic fragments, less than 5 millimeters, and they’ve quietly become one of the most persistent pollutants on Earth. They were first coined as a concept in 2004 by marine biologist Richard Thompson, who started finding microscopic plastic bits in sand and seawater. But the truth is, they’ve been around far longer, and the more plastic we produce, the more microplastic we have to deal with.

Plastics are a 20th-century miracle material turned 21st-century necessary evil. Widespread use of plastic started in the 1950s. In that time, we produced about 2 million tons globally in a year. In modern times, plastic production has grown to over 400 million tons per year. That equals about 9 billion tons of plastic that’s been produced to date. Less than 10% has ever been recycled. The rest goes to landfills, gets incinerated, or flows into oceans and soils and slowly degrades into smaller and smaller particles that never really go away.

We’ve built a system that depends on plastic. But we’re just now starting to ask: at what cost?

You’ve heard about plastic in the ocean, but that’s not the half of it

When we talk about plastic pollution, the ocean usually takes center stage. But by weight and impact, farmland may actually be the biggest sink for microplastics on Earth. Plastic mulch, irrigation tubing, fertilizer bags, seed coatings, and bale wrap all break down over time, embedding tiny fragments in soil. Farms also receive plastic unintentionally through sewage sludge (biosolids), animal manure used as fertilizer (because microplastic is passed through animals’ systems), contaminated irrigation water, and even wind-blown debris. One estimate suggests that farmland in Europe and North America receive more microplastics annually from sludge than oceans do from all sources combined. In U.S. soils, concentrations typically range from 82 to 340 particles per kilogram, and in some plastic-heavy zones, that number climbs into the thousands.

What happens once those particles settle in? Early studies suggest microplastics disrupt both the structure and biology of soil. They can change porosity and water retention, making soils too compact or too crumbly for healthy root growth. More troubling, they interact with chemicals in the field, binding to pesticides or heavy metals and forming toxic hotspots. Microbes may go dormant. Soil organisms that support fertility can suffer gut blockages or reduced reproduction. In one lab test, soybean germination dropped from over 90% to just 39% when soil contained 0.5% microplastics. Other crops like carrots, lettuce, and barley have shown stunted roots and oxidative stress, suggesting a pattern of subtle but cumulative harm.

And the ripple effects don’t end at the soil line. Microplastics can carry contaminants directly into plant tissue, with possible implications for food safety. Some evidence points to reduced photosynthesis and modest yield declines across staple crops. Not every field is affected equally, and not all studies show catastrophic results, but the consensus is forming: microplastics are an emerging agronomic stressor. And if it begins to show up in food, the risk shifts from agronomic to reputational. We could soon see calls for “microplastic-free” certification, or even restrictions on practices that contribute to long-term soil contamination.

That water bottle you’re drinking from will outlast you… And 20 generations after you

One reason plastics are such a vexing pollution problem is their incredibly slow degradation. Unlike organic materials that rot and metals that corrode, most conventional plastics don’t truly biodegrade; they fragment. The big pieces become smaller pieces, then become micro- and nano-particles, but those tiny bits may persist for geological timescales. The NOAA Marine Debris Program bluntly says that plastics “could stay in the ocean and Great Lakes for an indefinite amount of time.” There are some stats out there about plastic decomposition anyway. For example, a plastic shopping bag takes 10 to 20 years to break down. A plastic beverage bottle takes around 450 years. Styrofoam takes about 50 years. A disposable diaper goes up to 500 years.

These figures are rough guesses based on lab tests and observed environmental weathering. In truth, plastics never fully “go away”; even after centuries, you end up with microplastic powder and nanoplastic specks. Degradation rates also depend on conditions like UV exposure, temperature, and microbes. In landfills or deep ocean, where it’s dark and oxygen-poor, plastics could endure much longer than the earlier stated figures. Even so-called biodegradable or compostable plastics can persist if they don’t encounter the right conditions; many require industrial composters to fully break down. Researchers estimate that even under good conditions, traditional plastics might take thousands of years to mineralize completely into CO₂ and water, effectively making plastic pollution a permanent addition to the planet’s ecosystem.

This persistence is why environmental scientists talk of a “Plasticene” era. Every year we keep adding more plastics into the environment. Just 9% of all plastic ever made has been recycled, so the vast majority remains out there accumulating. We face a growing load of microplastics in soil and water that essentially cannot be removed and will not degrade. It’s an intergenerational impact: the plastic we discard today will be an inheritance for many generations to come.

Plastic surrounds us, but it also invades us

Here’s a question you don’t often hear, but you should start thinking about… How much plastic did I eat today? As plastics have infiltrated air, water, and food, humans are unknowingly eating, drinking, and breathing microplastics every day. But pinning down exact amounts is challenging. Early headlines said that the average person eats a credit card’s worth of plastic each week (around 5 grams). This attention-grabbing stat came from a 2019 WWF-sponsored study, which extrapolated from microplastic levels in drinking water, shellfish, sugar, and other foods. However, the “credit card a week” figure is likely an overestimate under current science. More recent reviews have pointed out methodological flaws in those early calculations.

A 2019 analysis in Environmental Science & Technology estimated that American adults ingest 39,000 to 52,000 microplastic particles per year from food and water, and inhale a similar amount from the air. That’s between 74,000 and 121,000 particles annually, which breaks down to between 200 and 330 particles a day. These are on the order of tens of microns to a few millimeters in size. That number also fluctuates dramatically based on how you get your drinking water. If you only drink bottled water, your yearly consumption of plastic from water only goes up by 90,000 particles. In comparison, those who only drink tap water are looking about 4,000 particles consumed per year from drinking water. This fluctuation extends to the types of food you eat as well, considering seafood tends to contain more microplastics than land-raised meats.

So while “credit card per week” makes for a catchy headline, a more grounded takeaway is that we each unwittingly consume dozens to hundreds of microscopic plastic specks every single day. Over a lifetime, that could be on the order of millions of particles in our digestive tracts.

We likely aren’t immune to health impacts

We’ve established that plastic is accumulating inside of us, but how much? And what does that mean for our health?

Studies have found plastic particles in human blood, lung tissue, even the brain and placenta. Some particles are small enough to slip past the body’s natural defenses, embedding in organs or circulating through the bloodstream. While concentrations are still low, in the parts per million or billion range, the idea that synthetic materials can cross into the very systems that regulate immunity, hormones, and development is deeply unsettling.

So far, the health effects aren’t fully understood, but the risks are mounting. Microplastics appear to trigger inflammation, disrupt digestion, and irritate the lungs. Some carry harmful chemicals like BPA or phthalates that are known endocrine disruptors tied to fertility issues, metabolic disorders, and developmental delays. Others may act as toxic sponges, absorbing pollutants like heavy metals and delivering them straight into our food and water. Perhaps most concerning, microplastics found in placental tissue suggest exposure may begin before birth, potentially shaping health outcomes for a lifetime.

We are the plastic generation. The scary thing is that we don’t fully know the impact of plastic in our bodies. All we do know is that it is likely hitting us at a chronic illness scale, causing inflammation and toxin exposure that can cause immune and hormone disruption, to microbiome imbalance. These long-developing effects are much less likely to get the attention that the dramatic acute illnesses caused by lead paint or asbestos did. And that’s why the evidence connecting plastic to major disease is lacking. Could plastic be found as the next substance causing major human disease? Unfortunately, only time and more research can tell.

So what now? If plastic is in our systems, soil and human alike, can we remove it?

Can we eliminate plastics?

Given the audience of this newsletter, we’ll use agriculture as a model for plastic elimination. Is it even feasible?

In reality, eliminating plastic from agriculture would be extremely difficult with today’s technology and demand for efficiency. The strategy, therefore, may be more about minimizing and managing plastic rather than outright elimination. A Nature commentary suggested focusing on “rational use and reduction, collection, reuse, and innovative recycling” as key measures for ag plastics. Essentially, use plastics smarter and recapture them after use so they don’t end up as pollution.

Policies could drive change too: Extended Producer Responsibility (EPR) schemes for agricultural plastics could make manufacturers take back used films and containers (some regions already have pesticide container recycling programs, for example). Subsidies or cost-share for biodegradable alternatives could accelerate their adoption. And as waste disposal costs rise (or landfill bans on certain plastics appear), the economic calculus may shift farmers toward alternatives.

Can the “downfall” of plastic be capitalized upon?

Cotton Incorporated is successfully positioning cotton as the natural, microplastic-free alternative the market is now craving. Whereas synthetic fibers shed persistent microplastics that linger, cotton fibers biodegrade quickly in all tested environments, including wastewater, freshwater, saltwater, and soil. In fact, up to 90% of cotton microfibers can break down within 40 days, even when treated with dyes, softeners, or finishes. Meanwhile, polyester fibers remain largely intact, threatening to persist for centuries. Textiles are responsible for around 35% of ocean microplastic pollution, with washing synthetic clothing identified as a key driver.

Consumers don’t realize their clothes contribute to microplastic pollution, and cotton is filling that awareness gap. If you just take a look at the “discovercotton” Instagram account, you’ll see clear messaging that cotton is an eco-friendly fabric, making it a strategic tool for both environmental and reputational risk management. With cotton’s biodegradability, circular recyclability, and growing consumer demand, agribusinesses and textile players have fertile ground to pivot toward genuine plastic alternatives before the regulatory tide shifts further.

Furthermore, the Make America Healthy Again report recently flagged microplastics as a contributor to chronic disease, and global negotiations like the UN Plastics Treaty are now targeting them explicitly. If public health, food safety, and environmental policy converge, as they seem poised to do, the ground could shift fast.

We get it, microplastics are bad, but is replacing them worth the cost?

The case for plastic (or at least for caution)

It’s easy to vilify plastic, but let’s pause. If we’re going to be honest about the risks, we also need to be honest about the alternatives. And the truth is, ditching plastic might carry environmental, social, and economic consequences we’re not ready to face.

Start with the obvious: plastic is cheap, durable, lightweight, and endlessly adaptable. That’s why it replaced glass, paper, jute, metal, and even wood in food systems. But what happens if we try to swap it out? Bioplastics, compostables, natural fibers, etc., sound good in theory. But most require more resources to produce. If we pivot hard to plant-based inputs, we’re just moving tradeoffs. Land that could grow food might now grow packaging. Water needed for crops might go to fiber hemp or industrial starches. And ironically, many of the so-called “green alternatives” still behave like plastics in the environment, especially if they don’t end up in a commercial composting facility, which most people don’t have access to.

There’s also the economic layer. For many farmers, especially small and mid-sized ones, plastic is part of what makes margins work. It protects crops from spoilage. It stretches harvest windows. It reduces labor. Replacing it with something more expensive, more fragile, or more complicated could price people out of the supply chain entirely. Are we willing to make local food less accessible? Are we okay with higher costs trickling down to consumers, especially in regions already struggling with food insecurity? If the “solution” to plastic is a system that only works for the wealthy, have we actually solved anything?

When it comes to plastic, considering what we can control is crucial

Microplastics represent a huge consideration in pollution. They’re omnipresent yet largely invisible, potentially harmful yet hard to pin down. Plastics have delivered tremendous benefits to agriculture and food supply chains, but their unchecked use has a dark side that is coming back to haunt our soils, water, and bodies in minuscule form. The science is telling us that every acre of soil and every mouthful of food now carries a trace of our plastic legacy. The onus is now on us: farmers, industry, consumers, policymakers, to reckon with that legacy and chart a more sustainable course. It’s worth ending on a note of optimism: Human ingenuity got us into this plastic predicament, and human ingenuity can get us out.

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At Serō Ag Strategies, we bridge farmers and supply chain partners by transforming complex agricultural data and policy into actionable insights. We also work to create and grow markets for commodity crops by aligning production with evolving demand, policy shifts, and sustainability goals. Combining multinational expertise with the personal touch of boutique consulting, we specialize in economic and sustainability analysis that drives strategic innovation.

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• The legacy: Fertilizer made modern agriculture possible but is now entangled in climate targets, water quality battles, and volatile geopolitics

• The reality: Farmers are using smarter tools and better data, yet still carry the weight of environmental outcomes and shifting market demands

• The bigger picture: Fertilizer use reaches far beyond the farm, touching everything from backyard lawns to global power struggles over key minerals

The story on fertilizer is way more involved than you think

Fertilizer might just be agriculture’s most paradoxical input. It has enabled one of humanity’s greatest achievements: the ability to feed billions of people on a finite amount of land. It’s hard to overstate its contribution to modern food security. Without synthetic nitrogen, the global population would look very different. Fertilizer remains one of the most effective tools in a farmer’s toolkit, driving yields, supporting economic viability, and enabling intensive production systems that sustain rural communities and global markets alike. Yet for all its value, fertilizer is also increasingly implicated in some of the most urgent environmental and political debates of our time. Conversations around water quality, greenhouse gas emissions, and global supply chain volatility inevitably lead back to how we fertilize the crops we grow.

Despite its centrality, the fertilizer conversation often remains piecemeal. We talk about nitrogen runoff in the Midwest, phosphorus loading in Lake Erie, or rising global potash prices, but rarely do we connect the dots in a way that reflects the full complexity of the system. Fertilizer use shapes soil health, public trust, regulatory priorities, and the long-term sustainability of agriculture itself. How we manage fertility on the farm affects not only yield potential but also the viability of the land we rely on, the quality of the water beneath our feet, the resilience of the climate we farm within, and the credibility of an industry facing increasing public and policy scrutiny. In that way, fertilizer is a mirror reflecting the broader tensions between productivity and stewardship that define agriculture today.

Where did fertilizer come from, and why do we rely on it so heavily?

Fertilizer, in some form, has supported agriculture since the earliest human settlements. Ancient farmers may not have understood chemistry, but they could see the difference in crop performance where livestock had roamed. Manure enriched soils and led to better harvests, establishing a basic but effective form of nutrient cycling. Over time, the practice grew more intentional. In both Europe and the United States, farmers began to collect bones, sometimes even purchasing them, grinding them into powder, and applying them to fields to supply nutrients that would otherwise be depleted by repeated planting. These early practices weren’t guided by formal science, but by observation, trial and error, and a growing awareness that the land required more than just labor to stay productive

The scientific breakthrough came in the 19th century with German chemist Justus von Liebig, whose Theory of Mineral Nutrients and Law of the Minimum laid the foundation for modern agronomy. Liebig’s work formalized what many farmers already sensed—that nutrients like nitrogen (N), phosphorus (P), and potassium (K) are essential to healthy plant growth, and that the scarcest one will always limit a crop’s potential. This understanding unlocked a new era, one that would accelerate dramatically with the development of the Haber-Bosch process in the early 20th century. By converting atmospheric nitrogen into synthetic fertilizer, the process made it possible to nourish crops at a scale never seen before.

During World War II, chemical manufacturing grew rapidly to meet military needs, and after the war, that capacity turned toward agriculture. Fertilizer production surged, food supplies recovered, and global population growth followed. The ability to feed more people more reliably became a defining achievement of the 20th century. But as production rose, so too did the need to grapple with the long-term consequences of how fertilizer is made, managed, and lost.

Dynamics of fertilizer across the globe

Today, fertilizer is deeply embedded in the architecture of modern agriculture. Companies like Nutrien, Mosaic, and UPL hold enormous economic and political influence. These firms operate far beyond the bounds of farm supply, engaging directly in the policymaking process through lobbying, research sponsorship, and strategic personnel shifts between the private sector and regulatory agencies. Their reach is broad, and their messaging is effective. With food security hanging in the balance, governments are understandably reluctant to challenge the practices of companies that supply the nutrients keeping harvests on track and food shelves stocked. Environmental concerns may emerge, but they’re often met with a reminder that’s hard to argue against: disrupting fertilizer production risks disrupting the global food supply. That framing is powerful, and it grants these companies significant leverage in shaping the rules they play by. I really can’t disagree with the path we’ve taken to get here, particularly as a member of a farm family. Fertilizer is a key driver behind plentiful harvests, and I don’t particularly want to see our current trend toward ever-increasing abundance disrupted, even if I wonder about unintended, negative indirect impacts of the current system.

But corporate politics is only part of the equation. Geography plays an equally pivotal role. The world’s phosphate reserves are not evenly distributed, and that asymmetry has consequences. More than 70 percent of known global reserves lie in Morocco, giving the region disproportionate control over a critical component of crop fertility. In an era where food security can be invoked as a national security issue, the country’s resource dominance gives it leverage on the world stage. That concentration of supply introduces a level of fragility to the system. Any political unrest, environmental disruption, or trade restriction in the region carries global implications.

The Russia-Ukraine war made this fragility painfully clear. Sanctions on Russia and Belarus—both major exporters of nitrogen and potash—sent shockwaves through global fertilizer markets. Belarus alone accounts for up to 20 percent of potash production. Natural gas prices, a key input in nitrogen production, surged in parallel, pushing fertilizer prices to historic highs. For farmers in Ukraine, the war’s impacts were immediate and devastating. Nearly 2.8 million hectares went unplanted in 2022, a 22 percent reduction in sown area. Globally, the consequences were even more dire. The Food Security Information Network reported that 258 million people faced acute food insecurity in 2022, the highest figure in the report’s history. Some farmers simply stopped applying fertilizer, forced by price volatility to gamble on lower input strategies that risked yield penalties. As prices rose and yields fell, the effects rippled outward, with commodity markets tightening, and the already fragile balance between supply and demand in global agriculture became even more precarious.

Taking a step back… What resources do plants actually need, and are they really getting them?

Crops need seventeen essential nutrients, but N, P, and K dominate the conversation. Nitrogen drives leafy growth. Phosphorus fuels root development and energy transfer. Potassium helps plants manage stress, water, and disease. Yet for all our technological advances, nutrient efficiency remains elusive. Much of the nitrogen we apply escapes, volatilizing into the atmosphere as ammonia, leaching into groundwater as nitrate, or transforming into nitrous oxide (N₂O), a greenhouse gas almost 300 times as potent as CO₂. Phosphorus, while less mobile, can be just as problematic. It binds to soil particles, and when those particles move during heavy rainfall or irrigation runoff, so does the phosphorus.

It’s easy to say the system is broken. But the truth is more complicated. Fertilizer efficiency has improved dramatically over the last several decades. Most farmers aren’t overapplying nutrients out of laziness or neglect. In fact, with today’s prices, no one can afford to. Variable rate technology, split applications, nitrification inhibitors, and precision sampling are becoming the new standard. Farmers are making data-driven decisions with tools that didn’t exist twenty years ago. And yet, the environmental outcomes remain problematic. The dead zone in the Gulf of Mexico, fed by nutrient runoff from the Mississippi River Basin, reaches thousands of square miles every summer. Algal blooms in Lake Erie, driven largely by phosphorus from agriculture, have rendered municipal water undrinkable. In Iowa, the Des Moines Water Works case drew national attention to nitrate levels in drinking water and the murky legal territory where urban and rural interests collide.

None of this is helped by the growing prominence of carbon intensity (CI) as a metric for sustainable agriculture. Fertilizer is at the center of the emissions scoring for good reason. The upstream emissions from nitrogen production are massive. Add in the downstream losses from volatilization and leaching, and fertilizer becomes one of the largest contributors to a farm’s carbon footprint. Some CI modeling shows nitrogen alone accounting for more than half of a field’s total greenhouse gas emissions. As food companies, ethanol producers, and carbon markets lean more heavily into CI scoring, farmers will find themselves under increasing pressure to account for and reduce nutrient-related emissions.

Wait a second… Is agriculture really to blame?

The ag blame game only goes so far because fertilizer is being applied far beyond the farm. In fact, turfgrass in the US, including lawns, golf courses, parks, and public spaces, receives staggering amounts of nitrogen each year. One estimate puts the annual total at nearly 90 million pounds of N, much of it applied with little precision, timing, or regard for runoff. Let’s run the numbers. A typical bag of commercial lawn fertilizer recommends 1 pound of nitrogen per 1,000 square feet. That equates to 43.5 pounds per acre. Apply that three or four times a year, and you’re pushing an amount of nitrogen comparable to many corn acres in the Midwest. But without split applications, accounting for weather, thinking about plant uptake or performing soil tests, the efficiency of that turf nitrogen is often abysmal. And yet, when water quality lawsuits are filed and nitrate standards are debated, the spotlight rarely turns to the suburbs.

That’s not to excuse agricultural fertilizer pollution. But it is to say that if we’re serious about nutrient management, we need to widen the frame. Because if we don’t consider all of the fertilizer users, we won’t have an accurate understanding of the problems.

At the end of the day, fertilizer remains a significant piece of the puzzle

Still, the responsibility on farmers is real and growing. So, what does a path forward look like? It starts with aligning incentives. Conservation programs need to be farmer-friendly but reward real-world outcomes, weather permitting. Carbon markets need to credit reductions in nutrient losses. Food companies need to support low-CI sourcing with real premiums. And state and federal policy needs to take a more holistic view—one that considers both the environmental and economic dimensions of fertility management.

Farmers want to be part of the solution; they already are, in many cases. But the burden of sustainability cannot rest on their shoulders alone. Fertilizer is everyone’s problem, and that means the solutions must be shared. We have to build a food system that can endure—economically, environmentally, and agronomically. Fertilizer helped get us here. Now we have to decide what role it plays in getting us through.

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At Serō Ag Strategies, we bridge farmers and supply chain partners by transforming complex agricultural data and policy into actionable insights. We also work to create and grow markets for commodity crops by aligning production with evolving demand, policy shifts, and sustainability goals. Combining multinational expertise with the personal touch of boutique consulting, we specialize in economic and sustainability analysis that drives strategic innovation.

Click here to learn more about Serō Ag Strategies.

• California’s new climate disclosure laws (SB 253 and SB 261) will affect over 10,000 large companies, including those with only minimal business ties to the state.

• Key questions remain around definitions and a tight implementation timeline that may leave businesses scrambling before rules are even finalized.

• While compliance won’t require cutting emissions, public reporting will likely trigger reputational scrutiny, and companies that act early may shape the rules and avoid last-minute chaos.

California’s Climate Disclosure Laws Move Forward—But Questions Remain

On May 29, 2025, the California Air Resources Board (CARB) held its first public workshop on implementing Senate Bills 253 and 261—two landmark laws that promise to reshape how large businesses approach climate disclosure. Though the workshop was formal and structured, it was a pivotal moment showing that these bills are being taken seriously by Californians and businesses alike. It’s no doubt that as this unfolds, these bills will continue to be watched closely both nationally and internationally. About 10,000 companies that do business in California and meet the revenue threshold for these bills. While much is still unclear, these bills are still in effect, and for affected businesses, the clock is already ticking on finding a path to adherence.

These two laws, while framed as transparency tools, signal a broader shift. California is setting out to regulate not just emissions, but the quality of climate-related data in the corporate domain, data that investors, consumers, and policymakers increasingly use to evaluate financial and reputational risk. And because of the scale and interconnectedness of the U.S. economy, the implications of these laws will stretch far beyond California’s borders.

A New Layer of Reporting for America’s Largest Companies

SB 253, known as the Climate Corporate Data Accountability Act, requires public and private companies with over $1 billion in global annual revenue to report their greenhouse gas emissions if they do business in California. Senator Scott Wiener noted that about 5,400 businesses meet these requirements. Beginning in 2026, companies will be required to disclose Scope 1 and Scope 2 emissions—those from direct operations and purchased energy, respectively. In 2027, Scope 3 emissions reporting begins. Scope 3 includes emissions across the entire supply chain, from product inputs to consumer use and disposal of the product. SB 253 also requires companies to obtain third-party assurance, starting with limited assurance and moving toward reasonable assurance over time.

SB 261 casts a slightly wider net, applying to companies with over $500 million in annual revenue that operate in California. While the exact number of companies affected by this is unknown, NAICS reports that nationally, 4,070 businesses fall between $500 million and $999.9 million. These companies, along with those making over $1 billion in revenue, must publish a report on climate-related financial risks every two years. The intent is to bring climate risk disclosures in line with frameworks like the now-disbanded Task Force on Climate-Related Financial Disclosures (TCFD), now carried forward by the International Sustainability Standards Board (ISSB). Reports must describe not only risks, but also strategies for mitigating or adapting to them.

These requirements are sweeping in scale, including many multinational firms, national retailers, manufacturers, and agricultural processors that do business in California but are headquartered elsewhere.

“Doing Business in California”: A Low Threshold, Big Implications

A repeated question during the workshop was how to define the phrase “doing business in California,” because that definition determines whether a company falls under the law’s scope. CARB is currently proposing to adopt the definition used in Section 23101 of the California Revenue and Tax Code. Under that standard, a company is considered to be doing business in California if it is commercially domiciled in the state or meets any one of the following thresholds: annual California sales exceeding $735,000; property in California worth more than $73,500; or California payroll above $73,500.

This creates a striking scenario. A company with a global footprint generating $10 billion in revenue might be drawn into the law’s scope simply for having a sales relationship, warehouse lease, or staff presence totaling a fraction of a percent of its business in California. To be clear, the $1 billion and $500 million thresholds in SB 253 and SB 261 refer to total global revenue, not California-based revenue. So long as the company meets the economic activity triggers in California, the law applies. This broad reach has raised eyebrows, especially among companies with only marginal ties to the state. Some stakeholders have asked whether CARB might consider proportionality, taking into account how much of a company’s total business is conducted in California. So far, CARB has given no indication that such an adjustment is under serious consideration.

CARB staff argued that harmonizing with existing tax code language offers legal clarity and administrative efficiency. But even they acknowledged concerns from stakeholders that this might cast too wide a net. The agency is now seeking public feedback on how to ensure the rules are both inclusive and practical.

Parent Companies, Subsidiaries, and the Challenge of Corporate Structure

Another key issue is how the law will apply across complex corporate entities. If a subsidiary is doing business in California but the parent company is not, who is responsible for reporting? CARB’s initial concept borrows from its Cap-and-Trade program: if a parent entity owns or controls more than 50% of a subsidiary, the two are considered part of a single “corporate association.” Under this framework, the entire enterprise could be subject to disclosure obligations even if the reporting entity is not itself operating directly in California.

Corporate structures often exist for legal, tax, and operational reasons. For companies with subsidiaries incorporated across states or countries, the question of who bears responsibility and how data should be aggregated could become a major compliance challenge. Moreover, if revenue is calculated at the parent level but emissions reporting is done at the subsidiary level, or vice versa, the result could be inconsistencies or unintended compliance gaps. CARB has opened the door to stakeholder input on how best to manage this, but the early framing suggests a desire to apply the rules broadly and uniformly.

Scope 3: The Achilles’ Heel of Climate Reporting?

Of all the requirements under SB 253, Scope 3 emissions are likely to be the most contentious. While Scope 1 and 2 emissions can generally be measured through utility bills and direct equipment data, Scope 3 emissions span every facet of a company’s supply chain and customer base. That includes emissions from purchased goods and services, transportation, use of sold products, and waste generated during product end-of-life. For many companies, Scope 3 makes up the majority of their emissions footprint, sometimes as much as 70% to 90%.

Yet Scope 3 is also the least standardized area of climate disclosure. During the workshop, the UCLA Anderson Center for Impact presented data showing that while Scope 3 reporting is increasing among S&P 500 companies, it remains uneven and shallow. The most commonly disclosed category, business travel, makes up only a small fraction of total Scope 3 emissions. In contrast, categories like purchased goods or downstream asset use, which are far more material, are often overlooked.

CARB is considering whether to allow companies to apply “materiality thresholds” to Scope 3 disclosures. This would allow firms to focus on the categories most relevant to their operations, rather than reporting across all fifteen categories. While this would reduce the compliance burden, some worry it could also water down the very transparency the law aims to create. Striking the right balance will be crucial.

Financial Risk Reporting: A Bridge Too Far?

Under SB 261, companies must assess and publicly disclose climate-related financial risks. The goal here is to get firms thinking ahead: how might physical climate impacts or regulatory shifts affect future earnings, operations, or liabilities?

The challenge, of course, is that these risks are often speculative and unevenly distributed. Most companies aren’t in the business of long-term climate modeling, and boards are rightly cautious about disclosing liabilities that may be difficult to verify or quantify.

CARB’s proposal allows firms to use voluntary standards like those from the International Sustainability Standards Board (ISSB), the successor to TCFD. That’s a smart move, since many companies are already familiar with these frameworks. But CARB is still weighing whether this program should be implemented via regulation or non-binding guidance.

For businesses, that’s a big distinction. Regulation implies enforcement and legal risk. Guidance implies flexibility. In an environment where companies are already navigating inflation, labor challenges, and supply chain volatility, many will favor the latter.

Lessons from Abroad and at Home

CARB staff noted that California’s effort mirrors similar initiatives around the world. Jurisdictions like the European Union, Japan, and New Zealand have all moved toward corporate climate disclosure. Many of these programs are aligning with ISSB standards, which bodes well for harmonization.

Still, California’s approach differs in some ways. It emphasizes public disclosure and state-level oversight. And with Scope 3 included in the mix, it goes further than many existing U.S. frameworks. As Montrose Environmental pointed out in its technical presentation, regulatory programs tend to emphasize Scope 1 emissions and verification, while voluntary protocols offer more flexibility in Scopes 2 and 3—but often lack transparency.

Montrose’s takeaway? Companies juggling multiple reporting frameworks will need clear, consistent guidance and time to adjust. Otherwise, overlapping requirements could increase compliance costs without improving data quality.

Implementation Timeline Is Approaching Fast

While the implementation timeline has not changed, it also wasn’t clarified in the workshop. The SB 253 legislation says reporting for 2025 scope 1 and 2 emissions starts on January 1, 2026, however, there is still confusion on what that means.

In 2025, CARB will complete the pre-rulemaking phase, including workshops like this one and the development of draft regulatory concepts. In late 2025 or early 2026, the agency will enter formal rulemaking. This involves releasing a standardized regulatory impact assessment (SRIA), publishing the proposed rule text, and collecting public comments during a 45-day window. Additional revisions could trigger a 15-day comment period. Once finalized, the rules will be submitted to the Office of Administrative Law for review.

Here’s where it gets tight. By law, CARB must adopt final regulations within one year of issuing its Notice of Proposed Rulemaking. That’s a compressed window for a complex rule with national implications. And yet, companies will be expected to begin disclosing Scope 1 and Scope 2 emissions in 2026, the very same year the final rule is likely to be adopted. In 2027, Scope 3 disclosures begin. SB 261 climate risk reports are also due in 2026.

This timeline raises real concerns. How can companies build new reporting systems, hire auditors, review legal risks, and align cross-functional teams when the rules themselves may not be final until months before reporting is due? CARB has offered some assurance that penalties will not apply in 2026 if a company shows a “good faith effort” to comply. But good faith effort is undefined. Until clarity is provided, companies will be forced to operate in a gray zone.

Additionally, there’s the risk of litigation. Given the scope and novelty of these laws, legal challenges seem likely. If a court delays or alters the implementation schedule, companies could find themselves stuck between evolving compliance requirements and frozen regulatory timelines.

A Note on Governance and Who’s Driving This

One subtle thread running through the UCLA report was the role of corporate governance in driving climate performance. Only 7% of board members across the S&P 500 were found to have relevant environmental competencies. This suggests that many of the individuals tasked with overseeing climate disclosures may lack the technical background to do so effectively.

This raises a question: Will CARB encourage competency-building at the board level? Or will it rely on external consultants and auditors to fill the gap?

Either way, companies that proactively strengthen internal oversight now will be better positioned when the rubber meets the road.

What Do The People Think?

If there was one clear signal from the workshop, it was this: people still have a lot of questions. The Q&A portion stretched well past the official end time, and nearly every comment circled back to a central theme—clarity. Attendees pressed for more detail on the meaning behind key phrases like “doing business in California” and “good faith effort,” which remain vague yet critical to compliance. Others raised practical concerns, particularly around the risk of duplicative reporting. Several participants urged state agencies to align reporting requirements with existing frameworks, hoping to avoid a scenario where companies are forced to submit multiple emissions disclosures for essentially the same data.

The timeline also drew scrutiny. While the law states that Scope 1 and 2 emissions must be reported in 2026, that leaves open a critical question: when in 2026? If the deadline is set for January 1, for instance, it’s virtually impossible for companies to include data from December 2025. That would leave them either rushing to produce incomplete figures or relying on estimates, neither of which sets the state up for success in launching a credible program.

Ultimately, the questions raised were about feasibility. If this regulation is going to succeed, the implementing agencies will need to eliminate as much ambiguity as possible to ensure consistency and provide the kind of guidance that turns legislative intent into workable action on the ground.

The Work Ahead

This workshop did two things: it confirmed that California is moving ahead with aggressive climate disclosure laws, and it acknowledged that many details are still up for discussion.

For the business community, that’s both a challenge and an opportunity. Complying with SB 253 and 261 will not be easy, especially for firms that haven’t yet developed robust ESG programs. But those who engage early by submitting comments, shaping definitions, and developing internal systems will have a head start and a voice in the process.

It’s also worth noting that these rules are about transparency, not performance. They don’t require companies to change their emissions, only to report them. In that sense, they may serve more as a reputational and investor-relations tool than a driver of near-term operational change. That could help ease concerns from those wary of regulatory overreach.

But make no mistake: disclosure often begets pressure. And as these reports become public, the data will shape everything from capital flows to procurement decisions to public perception.

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About Serō Ag Strategies

At Serō Ag Strategies, we bridge farmers and supply chain partners by transforming complex agricultural data and policy into actionable insights. We also work to create and grow markets for commodity crops by aligning production with evolving demand, policy shifts, and sustainability goals. Combining multinational expertise with the personal touch of boutique consulting, we specialize in economic and sustainability analysis that drives strategic innovation.

Click here to learn more about Serō Ag Strategies.

Too long, didn’t read:

• The Renewable Fuel Standard (RFS) built a powerful market mechanism that linked carbon reduction to real economic value, but it’s overdue for a reset.

• Low Carbon Fuel Standards (LCFS) are spreading beyond California, and how these programs are structured will determine whether ethanol thrives or gets sidelined.

• Section 45Z is a game-changing opportunity to reward low-carbon ethanol, but realizing its full value depends on carbon capture, farm practices, and readiness across the supply chain.

The Renewable Fuel Standard: A Vision Ahead of Its Time

When Congress created the Renewable Fuel Standard (RFS), it didn’t just mandate blending targets — it created an entire market ecosystem designed to reward innovation and environmental performance. At the center of that system are three interlocking components: fuel pathways, Renewable Identification Numbers (RINs), and Renewable Volume Obligations (RVOs).

Pathways are where it all begins. To qualify as a renewable fuel under the RFS, a producer must operate within an EPA-approved fuel pathway — a specific combination of feedstock, production technology, and fuel type that meets greenhouse gas (GHG) reduction thresholds compared to baseline petroleum. If a producer installs new technology that reduces their emissions, or if they want to use novel feedstocks, they have to petition EPA to approve a new pathway. Without pathway approval, even the cleanest fuel can’t generate RINs. (Pathway applications are incredibly complex, technical, political, and time-consuming processes, and no two are alike. Yours truly has been involved in more of them perhaps than anyone alive. For those considering such an undertaking, find someone with experience to help guide you and get ready for a bumpy process unlike any you’ve ever been part of.)

RINs are the mechanism that moves the market. Every gallon of renewable fuel that meets an approved pathway generates a RIN, which is a unique tracking number that refiners and importers use to demonstrate compliance with the RFS. RINs are tradable commodities: refiners who can’t or won’t blend enough renewable fuel must purchase RINs on the open market to meet their obligations. That means producers creating cleaner, more valuable fuels not only earn revenue from selling gallons, they also capture additional value from the RINs associated with those gallons.

RVOs, or Renewable Volume Obligations, are the pressure points that keep the system moving. Each year, EPA sets the RVOs that define how much renewable fuel must be blended into the fuel supply. (Remember, Congress included an original vision for blending levels in the RFS2, but EPA sets yearly targets based on fuel market factors.) These targets create the demand that drives RIN generation and trading. Higher RVOs increase demand for blending and RINs; lower RVOs loosen the market. The balance between RIN supply, blending capacity, and RVO requirements determines the value of RINs and the health of the renewable fuel market overall.

This architecture of pathways creating eligibility, RINs creating value, and RVOs creating demand was a true policy innovation. It didn’t rely on direct subsidies or government handouts. Instead, it used market forces to drive continuous investment in cleaner fuels.

One of the smartest features of the system was how it was designed to accelerate the next generation of renewable fuels. RINs for advanced and cellulosic biofuels were intended to be worth much more than conventional ethanol RINs, creating a powerful financial incentive to develop and scale up technologies like cellulosic ethanol, algae fuels, and other low-carbon innovations.

For a while, RFS2 worked exactly as intended. But post-Great Recession gasoline demand not recovering and the subsequent development of the Blend Wall were Black Swans nobody saw coming. The wave of SREs and lawsuits that flowed from this friction combined with soft RVOs destabilized the RIN market, discouraged investment in advanced biofuels, and triggered a cascade of political fallout. At the same time, the promise of using high-value RINs to accelerate advanced fuel development began to fade. Compliance pressure was consumed by conventional blending struggles. And the opportunity to scale next-generation technologies through strong advanced fuel markets never fully materialized. Annual ethanol blending levels sometimes fail to meet the relatively soft RVOs that are set, despite ethanol production capacity being well in excess of these targets. This situation is a prime example of the impact of the regulatory uncertainty that reigns supreme in today’s ethanol market.

Despite these challenges, ethanol producers continued innovating. They invested in efficiency, carbon capture, and advanced technologies. To truly unlock ethanol’s full potential and make the RFS work as intended, higher blends like E15, E20, and even E30 must become widespread. The technology exists. The infrastructure is catching up. What’s missing is regulatory certainty and a market structure that supports scaling beyond E10.

In the end, the architecture was brilliant. But the system collided with economic forces that no one had fully anticipated. Today, the RFS still provides the backbone of support for America’s ethanol industry, but its full potential to rapidly scale low-carbon innovation remains, in many ways, unfinished business.

The Low Carbon Fuel Standard: The First Real Carbon Market

A Low Carbon Fuel Standard (LCFS) is a market-based policy designed to gradually reduce the carbon intensity of transportation fuels. Unlike mandates that require specific volumes or ban certain fuels, LCFS programs work by setting an annual carbon intensity benchmark that declines over time. Fuels that fall below this benchmark generate credits. Fuels that exceed it generate deficits. Obligated parties — typically fuel refiners and importers — must balance their performance by either blending or selling cleaner fuels, purchasing credits, or both. The result is a flexible framework that allows the market to determine the most cost-effective way to cut emissions, while encouraging innovation across all fuel types.

California launched the first LCFS in 2011 under the direction of the California Air Resources Board (CARB). The program was designed to reduce the carbon intensity of transportation fuels by 10% by 2020, using 2010 as a baseline. From the beginning, California’s approach stood out because it focused on lifecycle greenhouse gas emissions, rather than prescribing or banning specific fuels. Ethanol, biodiesel, renewable diesel, and electricity were all eligible to compete — so long as they could prove their carbon intensity was low enough. This performance-based structure allowed a broad mix of technologies to flourish, and positioned California as a global leader in transportation carbon policy.

Today, California’s LCFS is among the most comprehensive and technically complex carbon markets in the world. It now targets a 20% carbon intensity reduction by 2030, and in 2023 alone, more than 17 million LCFS credits were generated across a wide range of fuels. Ethanol remains a significant contributor, especially from Midwest producers using low-CI technologies like cogeneration and recycled process heat. These fuels not only generate credits for themselves, but help obligated parties — like refiners — meet their compliance obligations. Credit prices have ranged from $75 to over $200 per metric ton of CO₂e over the last few years, creating strong market signals and tangible value for low-carbon fuels.

In late 2024, CARB proposed a major amendment to the LCFS that would significantly tighten the program. The update would increase the 2030 carbon intensity reduction target from 20% to 30%, introduce a one-time 5% benchmark drop in 2025, and set a long-term goal of a 90% reduction by 2045. It also proposed an “Automatic Acceleration Mechanism” to tighten future targets if progress stalls, and introduced new restrictions on crop-based feedstocks, including third-party sustainability certification and land use protections. However, in early 2025, California’s Office of Administrative Law (OAL) disapproved the proposal, citing issues with regulatory clarity, temporarily delaying implementation of the amendments. This is not to say that the amendments won’t be put in place. CARB is currently making updates to the amendments to satisfy OAL the amendments will likely move forward.

At the same time, California politics are increasingly dominated by a drive to electrify the entire transportation sector. The state’s regulatory agencies, including CARB, are prioritizing electric vehicle deployment to such an extent that they risk overlooking — or actively excluding — low-carbon liquid fuels like ethanol. Ethanol producers, despite offering measurable and immediate carbon reductions, are seeing fewer opportunities to participate in the state’s long-term climate strategy. In some cases, new rules appear structured to limit the role of biofuels simply because they’re not electric. This is a critical policy tension: while EVs are essential to long-term decarbonization, ethanol can deliver substantial GHG reductions now. Sidelining these solutions because they don’t align with a single technology path risks slowing overall progress toward emissions goals.

California’s LCFS has become the blueprint for similar programs around the country — and even internationally. Oregon and Washington have implemented nearly identical clean fuels programs, and Canada’s Clean Fuel Regulations were modeled in part on California’s experience. British Columbia has maintained a provincial LCFS since 2010. In the U.S., several additional states are moving toward their own standards. New York has introduced LCFS legislation in multiple sessions, and New Mexico has authorized a Clean Transportation Fuel Program. Meanwhile numerous states across the country are in early discussions about clean fuel standards. As these programs proliferate, the structure, pace, and priorities set by California’s LCFS will influence national carbon markets for years to come.

For ethanol, the path forward in LCFS programs hinges on one thing: performance-based policy. So long as lifecycle carbon reductions remain the currency of compliance, and so long as fuels are rewarded for real emissions savings regardless of their form, ethanol can and will continue to compete. But if future LCFS programs begin to mirror California’s political bias toward electrification at all costs, they risk leaving behind powerful, proven solutions.

Creating Global Demand

The U.S. Grains Council (USGC) continues to lead the charge in expanding global markets for U.S. ethanol, positioning it as a key solution for countries aiming to lower carbon emissions and boost energy security. The Council is driving initiatives that support ethanol blending targets — most notably in Japan, which plans to reach a 20% ethanol blend in gasoline by 2040. These efforts underscore ethanol’s value not only as a renewable fuel but also as a vital component across industries such as chemicals, pharmaceuticals, and cosmetics.

But the global conversation isn’t limited to ethanol. Distillers Dried Grains with Solubles (DDGS), a nutrient-rich co-product of ethanol production, is emerging as a high-demand animal feed ingredient. The DDGS market is projected to nearly double in value by 2034, driven by rising global demand for sustainable, high-protein feed. The U.S. remains a dominant supplier, and countries like Brazil are ramping up production to meet both domestic and export needs.

Despite the strong outlook, trade policies and geopolitical tensions continue to shape market dynamics. For example, tariffs on Mexican imports could have ripple effects on DDGS exports, as Mexico has long been one of the largest buyers. Navigating these uncertainties will require ongoing engagement and adaptation. With its proactive global strategy, the USGC remains a cornerstone in both promoting U.S. agricultural products and shaping the future of clean energy and sustainable feed.

On the sustainability front, Canada recently implemented its Clean Fuel Regulations (CFR), a major policy aimed at reducing the carbon intensity of transportation fuels by 15% by 2030. The CFR mirrors many aspects of California’s LCFS, establishing a lifecycle carbon reduction framework that rewards lower-carbon fuels like ethanol. American ethanol, with its demonstrated carbon reductions and robust supply chain, is perfectly positioned to meet a substantial portion of this new demand.

In Europe, the Renewable Energy Directive (RED II and III) has established a framework for renewable fuels to play a major role in achieving ambitious climate targets. First adopted by the European Union in 2009, RED established binding targets for renewable energy use across member states, including a 10% renewable energy requirement for the transportation sector by 2020. RED introduced strict sustainability and lifecycle greenhouse gas (GHG) reduction criteria for biofuels entering the EU market.

Under RED II, implemented in 2021, these requirements tightened: biofuels must achieve at least a 50% GHG savings compared to fossil fuels (rising to 65% for new facilities) and meet strict land use and traceability rules. For U.S. ethanol producers, RED represents both an opportunity and a challenge. Accessing the European market requires compliance with RED sustainability standards, including detailed lifecycle carbon accounting and proof that feedstocks were grown without contributing to deforestation or land use change. For producers who can meet these benchmarks — particularly those investing in low-CI practices and traceable supply chains — Europe remains a valuable, premium outlet for U.S. ethanol exports. But compliance costs and paperwork burdens can be significant.

The International Sustainability and Carbon Certification (ISCC) system emerged in 2010 as a global certification standard designed to verify compliance with programs like RED and other voluntary sustainability frameworks. ISCC certification covers the full supply chain, from agricultural feedstock production to final fuel processing, and focuses on criteria like GHG savings, land use, biodiversity protection, and social responsibility. For U.S. ethanol producers, ISCC certification has become the de facto passport for international trade into regulated low-carbon fuel markets, not just in Europe, but also in emerging markets in Asia and South America. Ethanol producers certified under ISCC can more easily demonstrate RED compliance and qualify for premium pricing in jurisdictions that recognize ISCC standards. However, certification requires rigorous data collection, supply chain transparency, and regular audits, adding both operational complexity and cost. Still, for many U.S. ethanol exporters, ISCC certification has become a critical part of their global market strategy.

Although European politics often lean heavily toward electrification, ethanol remains an important compliance tool under RED. Several EU member states, such as France, Germany, Spain, and The Netherlands have implemented their own national biofuel blending mandates that exceed the baseline RED requirements. Meanwhile, the UK, post-Brexit, has established its own Renewable Transport Fuel Obligation (RTFO), which includes both volume targets and carbon intensity metrics with ethanol serving as a key compliance option.

To the south, Brazil, one of the world’s ethanol powerhouses, continues to expand its RenovaBio program, which creates tradable decarbonization credits (CBIOs) for low-carbon fuel producers. RenovaBio has significantly strengthened Brazil’s ethanol market and is creating a blueprint for carbon intensity-based programs in emerging markets. Other nations, including Japan, Colombia, and China, have either established national ethanol blending mandates or are actively pursuing them as part of broader clean energy strategies. In total, more than 36 countries today have formal clean fuel blending targets — some with sharp teeth and others more aspirational, creating a strong foundation for continued global growth.

Section 45Z: Ethanol’s Biggest Opportunity Since RFS2

In 2022, Congress passed the Inflation Reduction Act, one of the most significant pieces of clean energy legislation in American history. Embedded within it was Section 45Z, the Clean Fuel Production Credit — and for ethanol, it may be the most transformational opportunity since the passage of RFS2 nearly two decades ago. Unlike the RFS, which mandates blending volumes, 45Z directly rewards carbon intensity reduction. Beginning in 2025, fuel producers will earn a production tax credit based entirely on how much they can lower the carbon intensity (CI) of their fuel relative to a baseline. Ethanol plants with lower CI scores will receive higher credits, with values scaling up to a $1 per gallon for the cleanest fuels.

The U.S. Department of Agriculture’s newly released Feedstock Carbon Intensity Calculator (FD-CIC) will standardize how low-carbon farm practices are recognized, ensuring that sustainable agriculture becomes an integral part of the biofuels value chain. For ethanol, this creates an unprecedented opportunity: To extend value creation beyond the biorefinery and into the fields themselves, and to turn America’s farmers into direct participants in the low-carbon fuel economy.

Perhaps the most immediate lever to unlock value under 45Z is carbon capture and storage (CCS). Facilities that invest in CO₂ capture, transportation, and sequestration can dramatically reduce their carbon intensity scores — and dramatically increase their 45Z credit value. Proposed Midwest CO₂ pipelines that are designed to aggregate carbon from multiple ethanol plants and permanently store it underground have faced delays due to lawsuits, permitting battles, and local opposition. Where will these fights land? It’s anybody’s guess today, but without CCS, many ethanol plants will leave tens of millions of dollars on the table annually once 45Z credits go live.

Section 45Z represents a new chapter for ethanol — one where carbon performance becomes the coin of the realm. It aligns perfectly with ethanol’s strengths: existing infrastructure, measurable decarbonization, rural economic benefits, and the ability to scale improvements rapidly. It also reaffirms a core truth that policymakers, investors, and environmentalists are increasingly recognizing: Carbon markets based on real products and real emission reductions, like ethanol through LCFS and 45Z, are far superior as compared to speculative offset schemes.

As 45Z takes effect, the plants, farmers and companies that move first will lead the next era of American clean energy innovation, and ethanol will once again prove that the future is being built in America’s fields and biorefineries.

Conclusion

In a world that too often chases future technologies at the expense of practical solutions, ethanol stands apart. It is not a science experiment, a pilot project, or an unfunded mandate. Ethanol is real. It is ready. It is delivering cleaner fuels, stronger rural economies, and real greenhouse gas reductions today — at scale.

From its early days in Midwest barnyards to its central role in today’s low-carbon fuel standards, ethanol has proven again and again that American innovation can solve the world’s toughest problems. Ethanol created the first real carbon market. Ethanol brought measurable, verifiable decarbonization to the transportation sector. Ethanol saves drivers billions at the pump and revitalizes communities across rural America. Now, with transformational policies like E15 expansion, 45Z, and the growth of low carbon fuel standards at home and abroad, ethanol is poised to drive the next wave of clean energy leadership. Not in ten years. Not someday. Now.

The challenges ahead — from global climate change to national energy security — demand real action, not slogans. Ethanol is action. It is working today. It is improving every year. And it is ready to do even more. For policymakers, for consumers, for investors, for farmers — the message is simple:

If you want cleaner energy, stronger economies, and faster results, ethanol is the answer.

Recent Articles

Advanced tech moves sorghum into the future in Kansas Farmer

Beyond exports: How ethanol keeps sorghum farmers thriving in uncertain times in Kansas Farmer

If you haven’t already, check out our previous newsletters.

About Serō Ag Strategies

At Serō Ag Strategies, we bridge farmers and supply chain partners by transforming complex agricultural data and policy into actionable insights. We also work to create and grow markets for commodity crops by aligning production with evolving demand, policy shifts, and sustainability goals. Combining multinational expertise with the personal touch of boutique consulting, we specialize in economic and sustainability analysis that drives strategic innovation.

Click here to learn more about Serō Ag Strategies.

Too long, didn’t read:

• Ethanol is already delivering — not just cleaner fuels, but economic value, rural growth, and consumer savings.

• E15 expansion is the fastest, most practical way to unlock more market space for ethanol without rewriting the law.

• Ethanol improves gasoline quality, reduces harmful emissions, and saves drivers money, all while supporting American farmers.

Ethanol: An Often Overlooked Piece of the Energy Picture

The conversation around energy, environment, and economic security is shifting faster than ever. Rising costs, supply chain disruptions, and uncertainty in global markets are reshaping national priorities. Rural America desperately needs new markets, and American consumers need relief on essential purchases.

Across all of these challenges, ethanol stands not as a future solution, but as a proven one, ready today. Ethanol is America’s first and most successful carbon market, a real marketplace where low-carbon innovation is rewarded, rural economies are revitalized, and consumers save real money.

This isn’t theory. It’s already happening. While policymakers debate what the future should look like, ethanol plants across the heartland are delivering cleaner energy, cutting emissions, and strengthening the foundation of tomorrow’s economy. With new opportunities like E15 expansion, 45Z incentives, and a growing global market for low-carbon fuels, ethanol stands poised to become an even more important part of the solution to many of the problems we face as a nation.

A Brief History of Ethanol: From Vision to Vital Industry

Photo via Kansas Farmer

The roots of ethanol fuel stretch back over a century. Henry Ford, a fierce believer in renewable energy, famously envisioned a future where fuel could be made from crops like corn, weeds, and even sawdust. While the popular story that the Model T was designed to run on ethanol has been disputed, Ford’s optimism about biofuels was real and remarkably prescient.

In the early 20th century, Midwestern states championed gasohol, a blend of ethanol and gasoline, as a way to empower rural economies and diversify America’s energy sources. But Prohibition struck a devastating blow. Although industrial alcohol was technically exempt from the Volstead Act, enforcement was often blunt and destructive. Stills producing fuel alcohol were smashed right alongside illicit whiskey operations, stifling the young ethanol industry before it could mature.

Ethanol resurfaced during World War II, when wartime shortages drove a surge in production. Yet once the war ended and oil became cheap again, ethanol faded back into the shadows. It wasn’t until the energy crisis of the 1970s, and the founding of the Environmental Protection Agency in the wake of environmental disasters like the Cuyahoga River fire, that the United States began seriously reconsidering its energy dependencies and the environmental impacts of growing industrialization. As gasoline prices skyrocketed and environmental awareness grew, ethanol reemerged as a clean, renewable option.

The farm crisis of the 1980s gave ethanol new urgency. Small “barnyard” plants across the Midwest helped farmers add value to their grain. Companies like POET (then Broin Companies) and ADM radically scaled production and built modern bioprocessing facilities. In 1981, the Renewable Fuels Association was founded to advocate for the industry. The stage was set for the ethanol boom of the early 2000s, driven by high oil prices, mounting concerns about “peak oil,” and the passage of the Renewable Fuel Standard (RFS1 in 2005 and RFS2 in 2007). Most of the ethanol industry as we know it today was built during the boom that followed. In just a few years, dozens of new plants came online across the Corn Belt. The buildout was fast, massive, and hugely optimistic.

But the optimism didn’t last. The 2008 financial crisis hit hard. Fuel demand cratered, commodity prices surged, and ethanol margins collapsed. Plants closed. Investors fled. And just as the industry began recovering, the 2012 drought pushed corn prices to record highs — further squeezing producers. Meanwhile, post-recession gasoline demand never recovered to the levels Congress had assumed when RFS2 was written.

That’s when the market started breaking down. Unable to meet RFS2 targets under the constraints of 10% ethanol blending (E10), refiners began scrambling for compliance. RIN prices skyrocketed, triggering what came to be known as “RINsanity.” Merchant refiners without blending operations began lobbying for relief, and the EPA responded with a flood of Small Refinery Exemptions (SREs), effectively waiving RFS requirements for dozens of facilities. To make matters worse, the EPA also began setting Renewable Volume Obligations (RVOs) well below the statutory targets in the law, citing market constraints. Lawsuits followed, challenging both the exemptions and the rulemakings.

And that brings us to recent history. The lawsuits continue. Gasoline demand remains well below what Congress projected when it passed RFS2. And no one wants to open the law for fear of what might happen if the legislative process goes sideways. The truth is, there’s no politically viable way to reconcile Congress’s original vision with today’s fuel market, at least not at E10.

If only there were a way to grow the market without rewriting the law.

Oh wait — there is.

It’s E15.

E15: Unlocking Ethanol’s Full Potential

For more than a decade, ethanol production has bumped up against a hard reality known as the “Blend Wall” — the practical limit on how much ethanol can be blended into the U.S. gasoline supply under an E10 standard. As gasoline consumption declined after the Great Recession and vehicle fuel efficiency improved, the Blend Wall became a growing constraint. Yet America’s ethanol plants have capacity well beyond what E10 can absorb.

Enter E15, gasoline blended with 15% ethanol. E15 offers a ready solution to break through the Blend Wall, drive down emissions, create new markets for American farmers, and lower prices at the pump. Data shows that E15 can save drivers 5 to 10 cents per gallon compared to E10, without compromising engine performance or vehicle warranties for cars built after 2001.

For years, however, E15 was only available year-round in a handful of states, thanks to outdated fuel volatility rules known as Reid Vapor Pressure (RVP) regulations. Even though ethanol reduces volatility when blended properly, the rules prevented E15 from being sold in summer months unless a specific waiver was issued — which the EPA had been granting on an emergency basis year to year. This week saw the trend continue when the EPA announced a waiver that allows nationwide sales from May 1 through May 20, the maximum number of days allowed under the Clean Air Act.

With the immediate days covered, the industry will continue working with Congress and the Trump Administration to pass permanent legislation that offers Americans unfettered access to E15. Doing so will open a market pathway for ethanol producers that can absorb some idle capacity, offering an outlet for the gallons we’re capable of producing, but haven’t been able to sell under E10 limits. It will also boost investor confidence and send a clear market signal that ethanol demand has headroom to grow. For consumers, it will mean more consistent access to a cleaner, higher-octane, lower-cost fuel. With year-round availability secured, fuel retailers will have the incentive and certainty to invest in offering E15 at more locations, giving drivers more choice and more savings at the pump.

While E15 alone won’t solve every challenge facing the industry, it is a critical and immediate step forward. It will break the logjam, reduce regulatory uncertainty, and give ethanol room to grow within the existing fuel system — all without requiring new vehicle technologies or sweeping legislative reform.

Octane, Value and the Ethanol Advantage

Ethanol’s benefits extend beyond simply replacing petroleum. It improves petroleum itself.

Thanks to ethanol’s natural octane rating of about 110 — far higher than gasoline — refiners routinely produce suboctane base gasoline (around 82 octane) and use ethanol blending to reach the 87-88 octane levels consumers expect. This blending strategy saves refiners significant costs and helps consumers access cleaner-burning fuel at lower prices.

Without ethanol, refiners would be forced to add expensive aromatic hydrocarbons like benzene and toluene to boost octane. The use of these chemicals drives up the cost of fuel and contributes to harmful tailpipe emissions linked to cancer and respiratory diseases. With ethanol, America enjoys a cleaner, cheaper octane source that reduces greenhouse gas emissions and improves air quality. This blending advantage translates directly to savings at the pump. For instance, in early 2022, OPIS reported that ethanol was priced at $2.09 per gallon, a $0.13 decline from the monthly average. By contrast, ethanol-free gasoline (E0) components like 84-AKI blendstock and 87-AKI E0 gasoline rose by 26 to 29 cents per gallon. Based on these spreads, E10 could have been produced for 28 cents per gallon less than E0, while E15 offered a discount of 37 cents per gallon. That kind of cost advantage matters, especially for working families managing inflation and higher costs across the board.

Historical data reinforces ethanol’s value as an octane booster. From 2012 to 2020, ethanol consistently provided a significant octane premium, averaging $1.22 per gallon, while its energy penalty — due to lower energy content compared to gasoline — averaged just -$0.54 per gallon. This net benefit of about $0.68 per gallon highlights why refiners rely on ethanol: it delivers high-octane value at a lower cost. Even accounting for the energy difference, ethanol remains a cost-effective, cleaner-burning solution that strengthens fuel quality and affordability.

I’m sure you’ve heard that ethanol leads to reduced mileage and engine wear. However, concerns about reduced mileage are often overstated. Ethanol contains slightly less energy per gallon than gasoline, but real-world differences in fuel economy are small, typically less than 5%. And for many drivers, the cost savings more than offset the slight decrease in miles per gallon. On the question of engine wear, the facts are clear: every car built since 2001 can safely run on E15, and modern engines actually perform better with higher octane fuels. Ethanol isn’t just compatible with today’s engines — it’s an essential part of maximizing their efficiency and durability.

Ethanol is a strategic fuel component that improves gasoline’s quality, environmental profile, and affordability. It replaces toxic aromatics with a renewable, American-grown octane source. It gives refiners flexibility and lowers the overall cost of producing finished fuel. It gives consumers cleaner-burning, more affordable choices at the pump. And it helps the nation move closer to true energy independence by tapping into the productivity of American agriculture rather than relying on imported petroleum. Ethanol is the upgrade gasoline needed, and it’s delivering those benefits every day.

To be continued…

Stay tuned tomorrow for the rest of the ethanol story!

Recent Articles

Advanced tech moves sorghum into the future in Kansas Farmer

Beyond exports: How ethanol keeps sorghum farmers thriving in uncertain times in Kansas Farmer

If you haven’t already, check out our previous newsletters.

About Serō Ag Strategies

At Serō Ag Strategies, we bridge farmers and supply chain partners by transforming complex agricultural data and policy into actionable insights. We also work to create and grow markets for commodity crops by aligning production with evolving demand, policy shifts, and sustainability goals. Combining multinational expertise with the personal touch of boutique consulting, we specialize in economic and sustainability analysis that drives strategic innovation.

Click here to learn more about Serō Ag Strategies.

• Artificial intelligence (AI) is sophisticated technology, but it’s incredibly easy to use. You can start using it to assist you in small tasks today–there’s no need to wait until new AI-enabled tools specific to agriculture are available.

• Agriculture is not immune to AI’s effects. In fact, AI will likely impact every part of the ag supply chain eventually. From crop breeding to pest control, AI can process massive datasets to optimize decisions, speeding up innovation and increasing efficiency.

• With agriculture being one of the slowest adopters of certain (but certainly not all) aspects of technology, making use of AI now will put you ahead of the curve and give you a better chance of future-proofing your agribusiness.

What Even Is AI?

AI, or artificial intelligence, is essentially machines that can think, or at least act like they do, by learning from data and adapting over time. Rather than relying on rigid programming, AI systems learn from past experiences, observe current trends, make predictions, and refine their outputs through continuous learning. In many industries, this could look like an AI tool analyzing patterns to determine the best time for a specific action or optimizing a process based on ever-evolving data. Think of AI as a really sharp assistant who’s always on the clock, refining its approach with each new piece of information. AI relies on vast amounts of high-quality data to train its models, uncovering insights that might elude human perception. The real potential of AI is that it can handle tasks that are too complex, too time-consuming, or too unpredictable for us to manage on our own, allowing us to focus on what really matters while it continuously gets better at what it does.

Beneath the surface, AI is powered by a combination of complex algorithms, neural networks, and statistical models. This is where it gets a bit nerdy, but stick with me. At its core is a concept called machine learning, where the system identifies patterns in massive datasets and refines its predictions over time. More advanced systems rely on deep learning, which simulates human brain structures with layers of artificial neurons that continuously tweak and adjust based on new data. These systems use algorithms like gradient descent to minimize errors by adjusting each neuron’s weight and bias after each data pass. It’s like tuning a piece of equipment until it runs perfectly, except AI does this automatically, thousands of times per second. Some models even use convolutional neural networks (CNNs) to analyze images, which helps drones identify pests or detect crop stress, while recurrent neural networks (RNNs) handle sequential data like weather patterns to improve long-term yield forecasts. The math behind it–matrix multiplication, activation functions like ReLU (Rectified Linear Unit), and stochastic gradient descent–is complex, but the result is simple: AI systems that get smarter, faster, and more accurate the longer they run.

Moore’s Law tells us that computing power doubles every two years while costs drop. Some people question whether this can keep happening since computers are becoming so powerful that it’s hard to keep adding more power to a single processor. Isn’t it incredible that technology is advancing so quickly we’re actually reaching the limits of what a single chip can handle? What once required a supercomputer now runs on a smartphone, and AI is following that same exponential curve into production, becoming smarter, faster, and more affordable.

As with any emerging technology, the challenge isn’t just about what AI can do. It’s about how we, as an industry, can actually integrate it into everyday practices. While the power of AI is evident, there are still significant hurdles to overcome before it’s widely accessible and beneficial for all types of operations.

Take something I did on my laptop yesterday, for example. I wanted to create a simple Excel macro–something that might take me an afternoon, if not longer, if I could even code in VBA (Visual Basic for Applications, or the programming language used to write macros in Excel) to begin with. But with AI’s help, I knocked it out in about 20 minutes with no prior experience coding in VBA. (Yes, you read that italicized part correctly.) While it was a small task, it really highlights how AI can streamline even routine work and make us that much more efficient–to say nothing of enabling us to leapfrog by giving us access to tools we didn’t previously have access to.

So, the question becomes: is agriculture truly ready to embrace AI, or are we still in the early stages of figuring out how to unlock its full potential?

AI is Ripe for Agriculture, but Is Agriculture Ready to Reap Its Benefits?

AI is certainly making its way into agriculture, but it’s not being rapidly or universally adopted at the individual farm level. While AI technology is evolving quickly and seeing adoption on large farms, research facilities, and by agricultural technology companies, smaller and even medium-sized farms may not yet be realizing the full benefits–or any at all.

The reality is that the widespread integration of AI into everyday farming tasks is still in its early stages for virtually all growers, if it has occurred at all. Will AI advance so quickly that it gets integrated into the tools farmers already use, without them ever interacting directly with the raw AI technology themselves? Highly likely if not probable. The question isn’t really if AI will change farming, but how soon it will become accessible and practical for everyone, and what level of accessibility farmers will have versus simply reaping the benefits of better products and services. For those who actively engage, how quickly will they be able to adapt, and will they be prepared to take full advantage of the technology as it evolves? While it’s true that AI is evolving quickly and could revolutionize certain aspects of farming, other growers will decide the costs aren’t worth the benefits to engage with AI themselves. But even these will one day be affected–and hopefully aided–by AI.

To those who are hesitant to dive in themselves: I encourage you to engage with currently available AI tools. Pick one of the dozen free applications, like ChatGPT. If this one is your choice, you’ll immediately be staring at a question when you visit the link: “What can I help with?” I urge you to take its advice and “Ask anything” by typing your question in the box below. Try asking it for the most recent closing price for the December corn futures contract traded on the Chicago Mercantile Exchange. Is it right? Is it wrong? If it’s wrong, tell it it was wrong. Ask it to try again. Maybe add a link to the website and tell it to carefully analyze the site before answering. If it’s wrong again, ask it how to craft a better question that minimizes its chances of a hallucination, or an incorrect answer. If it’s right, positively reinforce it; that’s how it learns. While I don’t think you’ll find this is the best use of AI, it will help you understand how it thinks and how to prompt it.

Accelerating Crop Breeding through AI-Assisted Data Analysis

One area where AI has serious potential is crop breeding. Traditional breeding cycles take years–cross this, plant that, wait and see. But AI can process massive datasets, including plant genetics, soil profiles, weather patterns, and yield histories, to predict which crosses are worth pursuing. It would be like having a plant breeder who never stops working and learns from every outcome. For the commodity side of things, this means faster development of hybrids and varieties tailored to regional performance, disease resistance, and yield stability. Companies could also use AI-driven phenotyping to analyze thousands of genetic markers and their accompanying physical expressions in days rather than months, identifying traits that might have been overlooked using traditional methods. Or, imagine selecting seeds not just based on visible traits but on their predicted ability to handle drought stress, resist fungal diseases, or convert sunlight into energy efficiently before they even hit the field for trials.

Traditional breeding takes time. It often relies on phenotypic selection, which can be time-consuming and influenced by environmental factors and even factors related to labor. You plant, observe, and make selections, but the environment plays a huge role in how those plants perform, which can make it tough to pinpoint the best genetics. With AI, breeders could perform genomic selection by analyzing huge datasets of genetic information to predict the performance of various genotypes. Machine learning models can process these datasets to identify patterns and associations between genetic markers and desirable traits like drought tolerance or disease resistance. If large-scale breeding programs could find a way to get this done, what could previously take years might be shortened to a single season.

Researchers at Iowa State University back this up, saying that the technology is primed to be used for crop improvement, but many just don’t know where to start. As an answer to that charge, they created an excellent overview of how AI can be used to accelerate crop improvement that defines AI and explains its potential usage.

AI-Driven Precision: Minimizing the Unknown Variables

Planting is another area where AI could really change the game. It moves beyond autosteer and variable rate plating into deeper decision-making. AI could be used to analyze soil texture, last season’s yield data, and weather predictions to recommend where certain hybrids should go, how deep to plant, and how many seeds to drop. Instead of treating a 160-acre field as one big unit, AI systems break it down into hundreds or thousands of “microfields,” each getting a tailored planting strategy. In corn, for example, hybrids with strong stalks might be planted in areas of a field and soils prone to wind damage, while higher-yielding but weaker-stalked hybrids are placed in more sheltered spots. Obviously, there are equipment-based obstacles to such a strategy, but this practice is already occurring today, albeit in a less sophisticated sense. Think about it. How many farmers get planting recommendations from their agronomist who went through a similar process either manually or with the help of precision agriculture software? Put simply, AI could automate this process and enable it on a much larger scale.

AI could also help optimize timing in a way that takes the guesswork out of planting. The technology could predict the best planting window based on upcoming weather and soil temperatures, taking the unknowns out of the equation to the extent possible (after all, AI still can’t tell the future). Fertilizer applications could also become more precise. Instead of broad, season-long application plans, AI-driven nitrogen management systems could use satellite imagery and in-field sensors to track biomass development and chlorophyll levels in real-time, adjusting recommendations as the crop grows. It’s the difference between spoon-feeding nutrients when the plants need them most. And again, this is nothing new, but AI could take these practices to the next level.

It should come as no surprise that pest control is yet another factor that could benefit from AI’s help. (By now, you might be like me and wondering what area of crop production can’t benefit from AI!) AI can analyze drone or satellite images to detect early signs of infestation–not just identifying damaged areas, but recognizing specific patterns linked to different pests. Systems could even integrate with autonomous sprayers that target pests only where they’re detected, reducing chemical use and minimizing resistance buildup. Instead of blanket applications, imagine a sprayer treating only affected plants with pinpoint accuracy. Oh, wait, that already exists and is using early generation AI technology. If that’s the state of the art today, think about what will be possible tomorrow.

Our last newsletter covered our need to preserve water sources in-depth, as water scarcity is not only a global issue, but one that we’re staring down here in large portions of the U.S. Automating and optimizing irrigation scheduling is yet another way we can secure our water future. By blending weather forecasts, soil moisture data, and evapotranspiration rates, AI could optimize irrigation schedules to avoid over- or under-watering, allowing for every drop to count. Systems could be configured to combine satellite imagery with thermal sensors to detect heat stress before it’s visible to the eye, triggering irrigation adjustments automatically.

In the Jordan Valley, researchers from MIT’s Global Engineering and Research (GEAR) Lab have developed a low-cost precision irrigation controller designed to make advanced technology accessible to small-scale farmers. This AI-driven system automates water delivery by analyzing real-time data on soil moisture, weather patterns, and crop needs, ensuring each section of the field gets the right amount of water at the right time. At one Moroccan test site, the technology reduced water consumption by 44 percent as compared to neighboring farms using traditional drip irrigation. What makes this system particularly farmer-friendly is that it allows growers to decide how much automation they want to use. They can either let the AI handle everything or adjust schedules manually based on their own experience and preferences. This flexibility helps farmers blend technology with their own instincts, creating a balance between modern innovation and traditional know-how.

What’s especially powerful about this approach is how it shifts the balance of agricultural technology. Precision irrigation has often been a tool reserved for the larger, better-funded operations many of us are more familiar with or grew up on. But this system proves that AI can empower smaller farms, too. It’s a reminder that the future of farming isn’t just about high-tech machinery or vast data networks–it’s about making those innovations accessible and adaptable to the people who need them most. By giving farmers control over the level of automation used, the technology becomes a partner rather than a replacement for their expertise. When AI supports small-scale growers this way, it doesn’t just improve individual farms; it strengthens food security and reliability for entire communities. If this is possible on smallholder operations in some of the poorest, least connected and least technically sophisticated parts of the world, think about the scale of water reductions that can be delivered on farms here in the U.S.

AI in Market Forecasting and Supply Chain Optimization

Commodity price forecasting has always been a blend of data and gut instinct, but AI could bring unprecedented precision. Advanced models can pull in the usual suspects of global weather patterns and historical yield data along with shipping logistics and even trade policy chatter to better predict market movements. By integrating AI with market data, farmers could more effectively anticipate price fluctuations and make better decisions about when to sell, when to store, and how to hedge against potential downturns. For instance, an AI-powered model might tell a farmer that the price of corn traditionally peaks in six weeks based on historical trends, indicating the time to clean out bins to maximize profit is close at hand. This level of precision would take much of the guesswork out of commodity markets, offering strategic insight that extends beyond traditional methods. How accurate are those tools today? Many would argue a farmer’s gut may still be more accurate, and I probably wouldn’t disagree. But I would argue that any additional insight is helpful, and if it removes emotion from the marketing process–ironically enabling a farmer to follow his gut sooner, it will lead to better outcomes.

Beyond forecasting prices, AI could revolutionize how agricultural products are transported from farm to table. The supply chain is one of the most complex and costly aspects of agriculture, and inefficiencies in transportation, storage, and distribution can eat into profits. AI could help streamline this by predicting demand shifts and optimizing logistics at every stage. AI systems could track and predict potential disruptions in the supply chain, whether it’s bad weather, port congestion, or labor shortages, and reroute shipments or adjust schedules in real time. These systems could forecast fuel price fluctuations or delays caused by natural disasters, allowing traders and transporters to adapt quickly.

Grain storage facilities could use AI to predict spoilage risks based on temperature, humidity, and airflow. By adjusting ventilation and moving grain proactively, losses that would traditionally go unnoticed until too late could be prevented. These improvements will increase efficiency, reduce waste, and help maintain product quality. AI could also be integrated into processing plants to even more effectively sort, package, and manage inventory (tasks that are already aided by a version of machine learning but could be made even more effective with today’s AI technology). For example, AI-driven sniffers could even detect spoilage in grain more effectively. This would represent a significant step forward in reducing human error and ensuring that products leaving storage facilities are each optimized for sale.

Another exciting use case for AI is in the area of food waste. From better storage practices to more efficient transportation routes, AI could ensure that food reaches consumers faster, fresher, and with less loss along the way. Imagine a system that predicts spoilage in real-time and suggests adjustments to transportation routes, ensuring that perishable goods like fruit and vegetables stay fresh. It would be a win for the entire supply chain.

The Downside of AI and Digital Ag

If you’re reading this and thinking all of it sounds great, but what about when it fails, you’re not alone. Reliability of AI systems is and will be a concern, considering its dependence on the internet, satellite data, and cloud processing, meaning a temporary connectivity issue could cause a temporary halt to work. In theory, having backups like that don’t rely on those things would be really smart. But who has the resources for redundant equipment? Sure, we’d also like to have backups for a million reasons. For example, a mechanical-plate planter is something many farmers would love to have sitting around their equipment yard, but few still do. Same with a tractor that doesn't require a Deere technician to come out if it breaks down. Few have that either.

I could go on, but the real issue isn’t just the possibility of over-reliance on AI–it’s digital agriculture at-large. Every piece of equipment requires investment, upkeep, and storage, and in a business with tight margins, most farmers simply can’t afford to keep a second set of tools on standby just in case. So while AI is valuable, the real problem isn’t just making sure there are backups, it’s that we need to rethink how digital agriculture can be built to keep farms running without requiring an expensive safety net that most can’t afford.

AI is Here to Stay–How Can You Start Getting to Know It?

AI is already reshaping the way agriculture operates, and it’s happening faster than many expected–and in many cases, without much fanfare. Those who lean into this technology now will lead the charge, setting the pace for what modern agriculture looks like. But the truth is, AI isn’t an all-or-nothing leap. Everyone in the supply chain can start by using one tool at a time. Farmers might begin with AI-guided decision-making using one of the free platforms. Seed companies can take an extra step and accelerate breeding pipelines. Researchers can harness AI to analyze massive datasets faster and more accurately. CPG companies and traders can begin to leverage AI for supply chain forecasting, ensuring they’re sourcing from the most efficient, reliable, and resilient producers. And anyone can simply use it to help shave a few minutes off each day by using it to aid in mundane tasks like answering email. It’s that easy to get started.

The point is just that: start somewhere. Every incremental step builds an advantage–more efficiency, better yields, lower input costs, smarter marketing decisions, and a more resilient supply chain from seed to shelf. And here’s the thing–when more parts of the industry embrace AI, data grows more robust, algorithms improve, and everyone benefits from stronger, more reliable insights. It’s a rising tide that lifts the entire sector.

So don’t wait to see if AI works. It already does. The only thing left to decide is whether you’ll lead the way. The companies, researchers, farmers, and organizations that figure out how to make it work for them first are the ones that will still be thriving, shaping markets, and feeding the world for generations to come.

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About Serō Ag Strategies

At Serō Ag Strategies, we bridge farmers and supply chain partners by transforming complex agricultural data and policy into actionable insights. Our approach combines multinational expertise with boutique consulting’s personal touch, specializing in sustainability and economic analysis that drives strategic innovation.

Click here to learn more about Serō Ag Strategies.

• Water scarcity is a growing problem impacting agriculture, economies, and ecosystems, with no easy solutions and conflicting approaches to water preservation.

• The Aral Sea disaster serves as a stark warning of the consequences of prioritizing short-term economic boom over water longevity.

• Collaborative solutions like the Sheridan 6 LEMA show that reducing water use is possible without sacrificing profitability—aligning economic incentives with resource prosperity is key.

Water: A Defining Challenge for an Entire Generation

Water scarcity is the defining challenge of our generation. It’s a problem that touches everything—from food production to economic stability. Unlike many other pressing issues, there’s no arguing over the urgency of this one. Water shortages are a reality that everyone can agree on, no matter where they’re located or what their political views are. That agreement shows just how serious the situation is. But recognizing the problem is the easy part. The real work begins when we start looking for solutions. Water is crucial for life, agriculture, and industry, yet overuse, poor management, and unpredictable weather patterns are stretching our resources thin. With populations growing and demand rising, the question isn’t whether we need to act—it’s how we can come together to ensure a stable water supply for the generations to come.

The real roadblocks? First, there’s no easy fix. And second, no one agrees on the best way forward given the difficulty of addressing the problem. While it’s easy to see that one exists, proposed solutions spark heated debate. Some push for stronger government intervention, believing regulations and policies are the only way to manage water equitably and effectively. Others argue for market-driven strategies, advocating for private property rights and economic incentives to encourage preservation. More on that later… First, let’s look at one of the many environmental catastrophes related to water…

Disaster on the Aral Sea: A Mini Case Study

The Aral Sea disaster is a cautionary tale of what happens when short-term agricultural goals take precedence over long-term well-being. Once the fourth-largest lake in the world—larger than Lake Huron, the Aral Sea spanned the border of Kazakhstan and Uzbekistan, supporting a thriving fishing industry and providing livelihoods for tens of thousands. But in the mid-20th century, the Soviet Union had a different vision for the region—one centered on output, not resource optimization.

Starting in the 1950s, the Soviet government launched an ambitious plan to transform Central Asia into a major cotton-producing region. The goal? Agricultural self-sufficiency and dominance in the global cotton market. To make this happen, officials diverted massive amounts of water from the region’s two major rivers, the Amu Darya and Syr Darya, to irrigate millions of acres of newly cultivated land. At first, the plan seemed successful—cotton production soared. But the cost? A rapidly disappearing Aral Sea.

By the late 20th century, the consequences were undeniable. As water levels plummeted, the once-prosperous fishing industry collapsed—fish catches dropped 60% by 1970, becoming non-existent by the 1980s. Entire communities lost their livelihoods, and what remained of the sea became too salty and polluted to support aquatic life. Today, much of the former seabed is an arid wasteland, prone to toxic dust storms that have worsened public health and further devastated local agriculture.

The rusting fishing boats stranded in the desert stand as a stark reminder of the unintended consequences of large-scale irrigation projects. The Aral Sea’s story is more than just history—it’s a warning. When water management decisions prioritize short-term economic gains over lasting availability, agriculture, communities, and entire ecosystems pay the price.

Why Such a Challenging Problem to Solve?

Addressing water scarcity in agriculture isn’t a simple fix. It’s a tangled web of interconnected challenges. Crop insurance is perhaps the most successful agricultural policy ever conceived, and it’s certainly the most popular with farmers. But the programs are built around historical yields, which unintentionally reward farmers for sticking with the status quo. So, for those who want to transition to less thirsty cropping systems, the financial guarantee isn’t there because they have no history with the new systems. In other words, moving to different practices means smaller insurance guarantees—a real financial deterrent for farmers who rely on crop insurance. This would be true of any transition. And it’s not a knock on crop insurance; it’s just a reality of actuarial science, which relies on loss history to calculate guarantees and rate insurance products. This science is part of what makes crop insurance so successful. But it further complicates an already difficult problem to solve.

But that’s just one piece of the puzzle. The financial ecosystem in agriculture complicates things even more. Banks lend to farmers based on crop insurance guarantees, so when those guarantees drop, borrowing power follows suit. Plus, loan repayment structures often hinge on maintaining or boosting revenue, which can push farmers to prioritize short-term profits over long-term water availability. This pressure is made worse by the structure of agricultural cooperatives and value-added enterprises that are heavily reliant on high-volume production. Farmers whose balance sheets are tied to these ventures may feel the need to keep water-intensive practices in play to ensure volume is maintained, which just perpetuates the cycle.

The landlord-tenant dynamic adds yet another layer of complexity. In areas where share rent agreements are common, landlords might resist tenants’ attempts to reduce water use. They worry that using less water could mean lower yields and, as a result, lower rental income. This disconnect between landlords and tenants over water-saving measures creates a significant barrier to change, even if the tenants understand the need for more sustainable practices. The fear of losing access to land is real, and it can pressure tenants to keep using water intensively.

But there’s more. Legal and policy frameworks also play a role in water overuse. Some states have “use it or lose it” policies for water rights, which push farmers to use as much water as possible to preserve future rights. Even without these policies, the belief that if one farmer doesn’t use the water, a neighbor will, can lead to the dreaded “tragedy of the commons” effect. Add to that the economic logic of immediate profit over future availability, and you’ve got a recipe for unmaintainable practices. In all this, it’s important to remember that farmers aren’t the problem. They’re just responding to the economic signals and policies they’ve been given. The real challenge is redesigning these systems so that economic incentives align with the need for water preservation. That could mean anything from creating financial products that reward long-term water stewardship to revisiting water rights policies to encourage reduced use.

Water Scarcity Goes Mainstream

Water scarcity in agriculture is no longer just a problem in the field; it’s something that’s seeped into our culture, making its way into music, film, and literature. James McMurtry’s 1995 song “Levelland” paints a haunting picture of the consequences of water misuse in farming. With lines like, “Daddy’s cotton grows so high; sucks the water table dry; rolling sprinklers circle back; bleeding it to the bone,” McMurtry makes it personal—and painfully relatable. For me, the song hits home because I’m from Levelland. My dad grows cotton, and like the song describes, our sprinklers circle endlessly, drawing from nearly 42 wells. I can confirm, we’re bleeding it to the bone. The song’s imagery of lush cotton fields and relentless irrigation highlights the troubling truth: a thriving farm that’s living off a resource we’re rapidly depleting.

Hollywood, of course, hasn’t missed the drama surrounding water and agriculture. The 1974 classic Chinatown fictionalizes the notorious California water wars of the early 20th century, mixing corruption and power struggles with the fight for water rights. And for a lighter take on the issue, there’s Rango (2011), an animated film that my kids love. Beneath its quirky surface, it tackles the issue of water scarcity in a pointed way.

Then there’s the real-life story of Stewart and Lynda Resnick, the couple who control one of the largest farming empires in the U.S. and live in Beverly Hills. Even as water in California becomes frighteningly scarce, they have to continue to increase their usage to maintain their business and continue supporting thousands of farmworkers and the small towns they call home. It’s a glaring example of the ethical quandaries we face today: water as both a commodity and a lifeblood of agriculture.

Water isn’t just a resource; it’s ingrained in our culture and the way we live. It’s the most important compound on Earth, and the question is: What happens when it runs out?

Okay, John; I’m convinced. What do we do?

Government regulation is one option. Personally, I’m a small-government, pro-property rights advocate, so government intervention isn’t my favorite option. Addressing the issue this way is no easy feat, especially with the maze of water districts and rules that vary from state to state. Government regulation often leads to long, drawn-out legal battles—especially when it comes to disputes between states. Take a look at the recent Supreme Court ruling on the Rio Grande Compact. The complexities of interstate water disagreements are enough to make your head spin, and when you throw the federal government’s interests into the mix, it only gets messier. This kind of legal limbo can leave water users in the dark for years, with no quick fix for the immediate water management challenges at hand.

A more promising approach could be compensating farmers for pumping less and involving the entire agricultural supply chain in reducing water usage. This approach, which has been championed by the sorghum industry in recent years, focuses on collaboration rather than top-down regulation. It encourages everyone—farmers, processors, retailers, and even consumers—to work together toward water-saving goals. By aligning economic incentives with water preservation across the whole supply chain, we can drive meaningful change without adding more regulatory weight to farmers’ shoulders.

It’s not impossible. The Sheridan 6 Local Enhanced Management Area (LEMA) in northwestern Kansas is a standout example of how communities can tackle groundwater issues head-on. Established in 2013, this 99-square-mile area in Sheridan and Thomas counties set a bold goal: a 20% reduction in water use over five years. The results are impressive. Groundwater use dropped by 23.1%, and the rate of aquifer decline slowed from two feet per year to less than half a foot annually. What’s even more remarkable is that farmers within the LEMA managed to maintain—or even increase—their profits while using less water. They made this possible by adjusting their crop choices, including boosting sorghum production by 335.4%. This success shows that we can make significant strides in water preservation without compromising agricultural productivity or economic stability.

The story of the Sheridan 6 LEMA holds valuable lessons for the broader region, especially for those relying on the High Plains Aquifer. According to the Kansas Geological Survey’s Q-stable model, an approximate 30% reduction in pumping could stabilize groundwater levels in many areas. While this may sound like a heavy lift, the Sheridan 6 example proves it’s achievable and, in fact, can be beneficial for farmers’ bottom lines. These farmers showed that by improving irrigation efficiency, adjusting crop selections, and adopting new management practices, they could thrive with less water. What’s more, if the responsibility for water preservation use is spread across the entire agricultural supply chain—from farmers to processors, retailers, and consumers—this goal becomes even more attainable. A collaborative effort not only makes the shift easier for individual farmers but also ensures the long-term viability of agriculture in areas facing water scarcity.

Takeaways

To wrap up, water scarcity is not a problem we can put off any longer. It’s a challenge that touches everything from our farms to our futures. But here’s the thing: while the problem is clear, the solution isn’t quite as simple. We’ve seen some promising examples, like the Sheridan 6 LEMA, that show what’s possible when we work together—farmers, communities, and even consumers. Their success proves that we can reduce water usage without sacrificing productivity or profits. And it’s not just about cutting back; it’s about making smarter choices, improving irrigation efficiency, and shifting crop choices to better align with the needs of our future. The road ahead may not be easy, but the sooner we get started, the better off we’ll all be.

About Serō Ag Strategies

At Serō Ag Strategies, we bridge farmers and supply chain partners by transforming complex agricultural data and policy into actionable insights. Our approach combines multinational expertise with boutique consulting’s personal touch, specializing in sustainability and economic analysis that drives strategic innovation.

Click here to learn more about Serō Ag Strategies.