Mental Models in Agronomy and Farming
In 2013 I was exposed to a fascinating YouTube recording of a speech that Berkshire Hathaway’s Charlie Munger gave called “The Psychology of Human Misjudgement”. In his speech Charlie talks about cognitive biases and “mental lattice works” to understand the world around us holistically vs. silo’d into our areas of expertise. I was already extremely interested in human psychology, but this speech opened a whole new world into cognitive biases and mental models that have shaped me and the way I think today. I think they have a huge place in agronomy and farming as a whole to help us better understand the ag world around us and make better decisions.
So what are mental models?
When we think of ‘models’ of something many of our brains go to schematics or mock ups of concepts. We might even think about models from a scientific/mathematic perspective modeling out a theory with algorithms. These are all models, mental models are simply in your head.
Mental models are how we understand the world around us. They not only shape what and how we think/understand but they shape the connections and opportunities that we make as well as help to determine what information we filter. Mental models are how we simplify complexity, why we consider some things more relevant than others, and how we reason. A mental model can be stated as a representation of how something works. The world is full of complexity and we cannot keep all of the details within our brains, so we use models to simplify into understandable components.
Not everyone’s mental models are the same. Models are mainly used for efficiency to filter and interpret the swaths of information that come at us. However, our goal should be to optimize our models to best understand the situation at hand and ultimately make better decisions.
So what does this have to do with agronomy?
Agronomy itself is a holistic approach to crop production encompassing entomology, soil science, biology, plant physiology, chemistry, economics, pathology, technology and more! The scope of agronomy (let alone farming!) is wide! In order to be effective agronomists we need to have a fundamental understanding of core concepts plus all of the different interactions between these intersecting disciplines in a dynamic, changing environment.
After taking this interest in mental models I decided to better understand some of the basic models/concepts in agronomy as well as constantly strive to identify new ones and curate my own.
My goal isn’t to list all of the necessary agronomic models, nor even the most important (everyone’s priorities would vary) but some that I refer to often:
1. Mulders Chart – a chart showing how the presence or absence of various elements influences the uptake of other elements by plants
Soil chemistry is one of the most complex components of agronomy. It is chaos by most definitions of the word! However, understanding some of the core interactions of soil nutrients helps us better understand plant nutrition and soil fertility. Whether we are making a recommendation, interpreting a soil/tissue test, figuring out a deficiency or otherwise, Mulder's Chart is a pivotal model to understand. Note: The list of nutrient based models could be never ending! The nutrient availability by pH Chart, Safe Seed Placed Fertilizer as well as the Soil/Plant Nutrient Mobility understanding is exceptionally valuable to know like the back of your hand! These models and knowing what I’ll call the grey area within them can be a huge differentiator in making recommendations, applying forensic agrology practices or simply making better farming decisions.
2. Nitrogen Cycle – “the biogeochemical cycle by which nitrogen is converted into multiple chemical forms as it circulates among atmosphere, terrestrial, and marine ecosystems”
I still remember an influential agronomists advice to me when I was a summer student when I asked “What should I be learning?” Her response was the nitrogen cycle. Understanding the different forms of nitrogen, how weather and soil influences them and the how of the cycling gives great insight into the 4R’s of Nutrient Stewardship, what type of Nitrogen products to be utilizing/why/when(and what their shortcomings are) to what nitrogen stabilizer products may have a fit. Note: There are also lesser referenced phosphorous, potassium and sulfur cycles that are of value as well.
3. Pesticide Characteristics – This is tough to model simply, but it is important to learn and comprehend. All pesticide (herbicide, fungicide, insecticide etc) active ingredients have varying chemical characteristics: pH, soil persistence, toxicology, efficacy on weeds/diseases/insects, affinity for volatilization, breakdown within plants, mode of action, tank mix characteristics/antagonisms, water preference and much, much more. The complexity behind pesticides can be very daunting, especially in the face of all of the other considerations agronomists/farmers have to understand. But overtime there is a way to understand them. Learning the specifics of each active ingredient and we can begin to know the ins and outs of not just the actives, but every product that active is in! For example, fluroxypyr is a very common group 4 active in 20+ different brand name herbicides in western Canada. Being observant, asking questions, reading and putting in the effort to learn the specifics behind all of the most common active ingredients will go a long way to having a latticework and ultimately mental model of what the best product option is from the perspective of efficacy, future recropping, cost, crop injury and more. Having a model of each active ingredient in our heads allows us to understand the best fits based on the scenario we are encountering.
4. Law of Diminishing Returns – “the decrease in the marginal (incremental) output of a production process as the amount of a single factor of production is incrementally increased, while the amounts of all other factors of production stay constant.”
You can’t have good agronomics without economics. Having an understanding of the law of diminishing returns ensures that when we make recommendations, we have the financial considerations in mind as well.
5. “Think like a Plant” – This is a very broad one, that has some fundamentals grounded in basic plant physiology, but then would have specifics by plant type for example. The logic is engrained in understanding why a plant is doing what it is doing, or what will happen if you do x, y or z…or if x, y or x happens to it. The goal as an agronomist becomes how can I prepare the plant/crop for what is coming, how can I react and treat to support the plant/crop through the current situation or what can I do moving forward now that I know what I know. For example, basic plant physiology tells us that when we plant wheat at lower seeding rates (less seeds per square foot), we end up with less plants, which increases tillers which influences maturity, which impacts time susceptible to certain diseases/pests and best application timings of corresponding crop protection products and so on.
Even within agronomy, there are a tonne of overarching mental models from all different sciences and disciplines that should be utilized on a daily basis to not only improve your agronomy expertise, but how you see the world as a whole. Concepts like Entropy, Second Order Thinking and The Red Queen Effect are just a few that can be applied on a daily basis, no matter what you are doing. The key to utilization of mental models, agronomic or not, is to continually update them as new information becomes available, better understand when to deploy and utilize them, and how to use them in conjunction with one another to improve thinking, minimize bias and achieve better outcomes for farmers, yourself and the betterment of the industry.
Here are some great articles to reference discussing many of the mental models out there:
What are some of your most referenced mental agronomic models? How do you use mental models when practicing agronomy?