“All animals are equal, but some systems are more connected than others.”
— a nod to Orwell, (George Orwell’s Animal Farm)Reimagined for climate adaptation
The morning it changed, Michael O’Brien was standing at the gate of the lower paddock watching eleven Friesian cows refuse, with great dignity, to move.
They had grazed the upper field all week without complaint. They had walked to the milking parlour, eaten their ration, and done everything cows are supposed to do. But this morning, when Michael opened the gate to the lower field, the one the soil tests said was perfectly healthy, they simply stood there. Patient. Immovable. Staring at something only they could see.
His daughter Dorthy walked out with two mugs of tea and watched for a moment.
“The grass is greener up there,” she said.
“The soil test says the lower field has better nutrient levels.”
“Maybe the cows didn’t read the report.”
She was joking. But she was also right. And what followed was the slow, strange realisation that the cows were detecting something the instruments had missed, which became the beginning of the most important shift in how Michael and Dorthy managed their farm. It was the beginning of systems thinking.
What Manor Farm never understood (and what Animal Farm got wrong, too)
George Orwell’s Animal Farm is a story about power, but read it again slowly, and you will find that it is also a story about a farm that was managed in parts. Old Major understood the injustice. Napoleon understood hierarchy. Boxer understood loyalty. But no one, and not even Orwell’s pigs at their cleverest, understood the farm as a connected, living system. They replaced one set of rules with another. They never replaced the thinking.
Michael and Dorthy had been doing the same thing without knowing it. They had been treating their farm like a machine: fixing the soil here, adjusting the feed there, upgrading the equipment, and applying fertiliser on schedule. Each part is managed separately. Each problem is solved in isolation. Each solution creates a new problem downstream. The kind that wouldn’t show up until the following season, by which time they had forgotten the original cause.
Systems Thinking
Source: i4Agri, “Applying Systems Thinking to Farm Management Decision-Making” (2025)
It is a broad approach that looks at the various connections, interrelations, and wider, long-term impacts of actions, events or processes.
It goes beyond asking how to get from A to B. It asks what the wider effects of getting there might be. On a farm, this means feedback loops are everywhere: a plant is unhealthy → chemical protection products are applied → soil health declines → the next crop is less healthy → more products are applied. Systems thinking makes these loops visible before they become expensive.
The cows had felt a feedback loop before Michael and Dorthy could see one. The lower field, despite its nutrient readings, had subtly compacted soil from overgrazing the previous autumn. The compaction reduced water infiltration. That reduced microbial activity. That reduced the actual availability of the nutrients the test had detected. The grass was technically rich but practically inaccessible.
No single measurement told that story. Only the system did.
Michael’s daughter, Mai, understanding the situation, began drawing it out on the kitchen table. Not a financial plan. Not a grazing chart. A web. Every element of the farm is connected to every other element by arrows that could go in both directions.
The agribusiness literature calls these system linkages: the structural relationships between different components of an agricultural enterprise that determine how a change in one part ripples through everything else. The Agriculture Institute identifies four core linkage systems that interact continuously on any farm.
Source: Agriculture Institute, “Understanding Linkages in the Agribusiness System”
“The cows crossed all four at once,” Mai said, looking at her drawing and explaining to her father. The animals’ refusal had told them something about the production system (soil compaction), which was a consequence of a failure in the input system (overgrazing schedule), which had never been flagged by the support system (their advisor), because it didn’t show up in the market system signals (milk yield was fine until it wasn’t).
Orwell’s pigs never drew this web. They managed the farm as a power structure. Management as domination rather than a relationship. And so Animal Farm, like all farms managed in parts, eventually stopped working for everyone, including the pigs.
Sources: WEF Food Innovation Hubs Report (2023); ELD Initiative; JRC Farmland Research Programme
Then, their neighbour’s son, Rohan, came by on a Tuesday with a drone, a tablet, and the energy of someone who had recently discovered that NDVI vegetation indices could change everything. He was studying agricultural technology at university and had come, ostensibly, to show off his drone footage. He ended up staying for three hours.
“This is what your farm looks like from above,” he said, tilting the screen toward Michael.
The image showed stress zones Michael had never seen. Pockets of moisture retention in unexpected hollows. A heat signature across the lower paddock that mapped almost exactly onto where the cows had refused to walk.
“The cows saw this before the satellite did. They just couldn’t tell you in a language the spreadsheet accepts.”
What Rohan was demonstrating was connected farming, the integration of sensors, drones, IoT devices, satellite imagery, and data analytics into a single real-time picture of how the farm system is actually functioning, rather than how it was last measured.
Sources: ElifTech, “Connected Farming: A Short Guide” (2023); WEF, “How Innovation Is Helping Agriculture” (2023)
But Rohan was careful about something that many tech enthusiasts skip over. “The drone doesn’t tell you what’s wrong,” he said. “It tells you where to look. The rest is your father’s knowledge and yours.”
Michael thought about the cows again. They had been the original sensor network. Eleven animals, each with more soil intuition than any instrument he owned, patiently broadcasting a signal he hadn’t known how to read.
The wisdom the animals carried (and what Šūmane et al. found)
There is a paper that Michael and Dorthy would never normally read, but Mai and Rohan found, published in the Journal of Rural Studies in 2017, drawing on eleven case studies across Europe within the international RETHINK research programme. Its title is modest. Its finding is not. Šūmane, Kunda, Knickel, and colleagues found that farmers operating within multi-actor knowledge networks, weaving their own experiential, informal knowledge with formal scientific knowledge, consistently achieved better sustainability and resilience outcomes than those relying on either source alone. The cows, in their own way, had just demonstrated the paper’s central argument.
The eleven Friesian cows were informal knowledge, embodied and broadcast through behaviour. Rohan’s drone was formal knowledge, standardised and transmitted through pixels. Neither was wrong. Neither was complete. And when Michael and Mai started integrating both, walking the NDVI stress zones with the cows’ historical grazing patterns layered on top, they began to see the farm the way the farm had always been: a living story, not a set of parts.
By the following spring, Michael, Dorthy, and Mai had done six things that individually looked small and collectively changed everything. They shifted the grazing rotation based on Rohan’s heat maps. They moved the soil sensors to where the cows congregated. They applied for the ACRES scheme, not because they understood every detail, but because the peer group Michael had joined helped them navigate it. They seeded the compacted lower field with a mixed species sward. They stopped using the same fertiliser schedule they had used for twelve years. And they started keeping a notebook of what the animals did in the mornings before decisions were made.
The World Economic Forum’s 2023 analysis of agricultural innovation identifies a clear distinction between innovation that improves individual components and innovation that connects systems. The most impactful interventions, precision fermentation, ML-based water management, and AI-driven crop forecasting, work precisely because they generate feedback between parts of the system that were previously invisible to each other.
Sources: WEF (2023); Šūmane et al. (2017); EIP-Agri; Kilimo.com
Standing on the ridge at the end of that summer, watching Rohan’s drone footage play back on the tablet, Michael finally saw what the cows had seen in February. The farm was not a collection of fields with different soil test results. It was a web of soil, water, animals, microclimate, grazing pressure, human decision-making, policy incentives, market signals, peer knowledge, and family memory, all running through each other continuously, shaping and being shaped.
Animal Farm failed because the animals replaced one type of management with another. They never changed the model of management. Napoleon ran Manor Farm as efficiently as Mr Jones had, just with different beneficiaries. The feedback loops that mattered most, the ones between the animals’ well-being, the soil’s health, and the farm’s long-term survival, were never wired up. They remained invisible.
The farm was always a living story. The question is whether the farmer is a character in it or an engineer standing outside it.
Michael’s family chose to become characters. They stopped optimising parts. They started reading relationships. And the eleven Friesian cows, patient, stubborn, warm-breathed, and possessed of more systems intelligence than any single soil test, became the farm’s first and most reliable sensor network.
Behavioural concept: Interdependence and Systems Awareness
Interdependence means every element in a system influences, and is influenced by, others. In farming, as in climate adaptation, this means soil, water, animals, climate, policy, markets, and farmer decisions form a web of relationships that cannot be understood or managed by optimising any single node.Seeing connections instead of parts is the foundation of systems thinking, and the precondition for genuine resilience. It is also, as Šūmane et al. (2017) argue, the precondition for the integration of informal and formal knowledge that makes sustainable agriculture possible.
Read Animal Farm by George Orwell and comment your perspective!
JK Studio 