Why Systems Thinking Is the Key to Farm and Ranch Survival

By Brian Dougherty

Systems Thinking in Agriculture: 4 Traps That Undermine Farm and Ranch Profitability 

Farm and ranch management decisions are rarely as simple as they appear. Focusing on individual practices, short-term results, or isolated problems can lead to unintended consequences that undermine soil health, farm profitability, and long-term resilience. Systems thinking in agriculture helps farmers and ranchers recognize these connections, identify the root causes of problems, and avoid management decisions that create greater challenges down the road. In Part 2 of this series, we will explore four common traps that prevent producers from seeing the big picture, from chasing yield instead of profit and treating symptoms rather than underlying problems to accepting declining soil performance and relying on agricultural research that overlooks the complexity of real-world farming systems. 

Part 2: Four Common Farm Management Traps That Prevent Systems Thinking

In part 1 of this series, I argued that systems thinking is one of the most important skills a farm or ranch manager can develop. When we manage within a narrow boundary, we create internal costs the farm pays and external costs that society pays. This leads to farms and ranches designed to produce the results we’re getting, not necessarily the results we want. In this post, we’ll examine some common traps that cause us to lose sight of the big picture. 

Trap #1: Seeking the Wrong Goal for Farm and Ranch Management 

When your goal is defined using a narrow boundary view, the system will inevitably produce a result nobody actually wants. This is a result of seeking the wrong goal. Yield is the classic example in agriculture. Yield isn’t a bad number; it’s just an incomplete one. A yield figure tells you nothing about how the crop was grown, what it cost to grow it, what it did to the soil, what it did to the neighbors downstream, or how nutritious it was. In a previous series on nitrogen I showed that pushing N rates up to and beyond the so-called “economic optimum” makes perfect sense if yield is the goal. It makes no sense if profit is the goal. A goal of maximum profit without accounting for internalities and externalities will inevitably erode the ability to make a profit in the future. 

Trap #2: Treating Symptoms Instead of Addressing the Root Causes 

This is a trap I see often. It happens when a solution relieves the symptom but does nothing to solve the underlying problem. Worse, the intervention hinders the system’s ability to solve the problem on its own. The system becomes ever more dependent on the intervention, and more and more of it is needed to get the same result. Drug addiction is a classic example.

Think about how this works in a crop field. When we add too much inorganic nitrogen to the soil, plants cut back on the root exudates that feed free-living nitrogen fixers and the rest of the soil food web. The soil supplies less, so we apply more the next year to make up the difference. When we supply abundant soluble phosphorus, plants have less reason to feed mycorrhizal fungi and root colonization drops, leading to reduced availability of all nutrients, leading to more applied the next year. Fungicides and insecticides are used to treat problems that are really symptoms of poor plant health and an imbalanced soil system. Their use  impairs nutrient cycling, leading to poor plant health, leading to more fungicide and insecticide applied the next year. Drainage tile and bioreactors are installed to deal with a dysfunctional water cycle, which is the result of a leaky, dysfunctional soil, which resulted from the more-on approach above.

Ranches fall into the same trap. Continuous grazing weakens plants and reduces diversity, so we feed hay and supplement for more months of the year. Routine deworming knocks parasites back in the short term, but it breeds resistance and harms dung beetles, which slows manure breakdown and breaks the mineral cycle. Each fix is rational on its own. Taken together, they make the ranch more expensive to run each year.

In Thinking in Systems, Donella Meadows calls this trap shifting the burden to the intervenor. The way out of this trap that lines up exactly with what we teach at Understanding Ag. First, strengthen the system’s ability to carry its own load, then step back. If you are already dependent on the intervention, build the system’s capacity back up before you pull the crutch away, and start now, because the longer you wait the harder the withdrawal is. There are three pathways for making this change: efficiency, substitution, and redesign. Making inputs more efficient and swapping in more biology-friendly products are good steps. But only redesign, by implementing the six principles of soil health, actually gets you out of the trap.

Trap #3: Accepting Declining Soil Health and Lower Farm Performance  

“That pasture always ponds.” “Our soils just don’t hold water.” “That ground never yields well.” I hear these all the time. Meadows calls this drift to low performance. When we let past performance set our standards, especially when we remember the bad years more clearly than the good ones, expectations decline over time. We accept new lows as normal. The way out of this trap is to keep standards absolute. We have a perfect absolute standard sitting right under the fencerow. Dig a hole in the field, then dig one in an undisturbed area. Do an infiltration test in each area. If the undisturbed soil is darker, crumblier, and smells better, or if it infiltrates water 5x faster than your field, those are your benchmarks. They are not a fantasy. They are what your soil is capable of when we stop getting in its way. 

Trap #4: Why Agricultural Research Doesn't Always Reflect Real-World Farming Systems  

Meadows doesn’t specifically list this trap in her book, but I added it because I see it all the time. A lot of the agricultural research that farmers rely on to make decisions is built on a fiction: that you can change one or two variables and hold everything else constant.

Consider a typical cover crop study. Researchers set up plots with and without a cover crop. To make it a “fair” comparison, everything else stays the same: the same tillage, the same herbicide program, the same nitrogen rate and timing, the same planting date, the same hybrid. No livestock, because the plots are too small to graze. At the end of two or three years the yields are compared, and the paper may conclude that cover crops caused a yield drag. That conclusion gets passed along to farmers as the “result” of planting the cover crop. Full disclosure: this is a real-world example that I participated in at a university, only the trial was 8 years long. No farmer would ever put up with a practice that caused a yield drag for that long. They would change their management to address the problem or just stop doing it. The problem with multiyear replicated research plots is that you can’t make changes along the way. Doing so would make statistical analysis impossible, meaning the results would likely never be published because researchers couldn't establish cause and effect.

However, adding a cover crop is never just adding a cover crop. It changes soil moisture and soil temperature at planting. It affects nutrient cycling dynamics. It changes the amount of residue, pest and weed pressure, biological activity, aggregation, and infiltration. The herbicide program may need to change to optimize for the presence of the cover crop. Holding all other management constant doesn’t hold the system constant. It just means the rest of the system isn’t being managed for the change.

It’s like hiring a talented new herd manager and then only letting them change one thing about how the herd is managed. When improvement is minimal, you conclude that the hiring was a mistake. A cover crop that succeeds usually comes with other changes: a more diverse mix, adjusted nitrogen rate and timing, a different herbicide program, different hybrids or maturity dates, a planter set up to handle more residue, and possibly livestock to harvest the forage. The study didn’t test whether cover crops “work”. It tested whether cover crops work in a system designed to not need them.

The Limitations of Agricultural Research: Delays, Boundaries, and Measurements  

There are three more problems with single-variable research, and Meadows names all of them. The first is delays. Every “stock” in a system comes with a delay. Soil organic matter, stable aggregates, and fungal networks are stocks that take years to build. A short-term study captures the cost of the transition and misses most of the payoff. Systems research and systems thinkers need to pay attention to and account for delays.

The second is boundaries. Meadows observes that the right boundary for a problem rarely lines up with the boundary of an academic discipline, and she calls universities living monuments to boundary rigidity. The agronomist measures yield, the soil scientist measures organic matter, the entomologist counts bugs, and the economist figures out the budget. Nobody determines whether the whole farm is a functioning system that meets the operators goals.  

The third is what gets measured. Yield or rate of gain gets measured because it is easy to measure. Meadows urges us to pay attention to what is important, not just what is quantifiable, and warns that pretending something doesn’t exist because it is hard to measure leads to faulty assumptions and flawed models. Soil and plant health, nutrient density, input dependency, and resilience to extreme weather are all important but they don’t show up in the research results.

None of this means we should ignore research. It means we should read it with both narrow and wide boundary views in mind. Every time you read a study, ask what was held constant that should have been allowed to change. Better yet, run your own trials. Compare whole systems, not single practices, and do it over multiple years. Measure profit per acre under various scenarios, not just yield. Evaluate whether that system meets your goals or not. Dig some holes to see what is happening below the soil surface. Your own farm or ranch is the only place that has the right boundary for your decisions.

There are many other traps that I have not listed here. What they all have in common is that they arise from looking at the system through too narrow of a boundary. We chase the wrong goal, treat symptoms instead of causes, lower our expectations, and trust research that doesn’t evaluate the whole system. Escaping the traps starts with recognizing them. In part 3, we’ll look at how the system itself can hide the consequences of our decisions, sometimes for years.

Stop Treating Symptoms. Start Improving the System.

Building a more profitable and resilient farm or ranch starts with understanding how the pieces work together. Instead of continually spending money to manage recurring problems, you can take steps to address their underlying causes and improve the health and function of your entire operation.

Understanding Ag consultants work alongside farmers and ranchers to identify opportunities, develop practical management strategies, and implement regenerative practices suited to their land and goals.

Reach out to an Understanding Ag consultant to learn more about avoiding traps that prevent you from achieving your goals.