“What’s past is prologue.” — William Shakespeare, The Tempest
The line came back to Michael unexpectedly as he walked the lower field. The soil had turned the colour of old pottery – pale, brittle, unwilling to hold shape. It reminded him of the summer five years ago. The one everyone still called the bad one.
Back then, the drought had arrived like a thief. Quiet at first. Then merciless. He had survived it, barely. He culled animals he never wanted to part with. He watched neighbours scramble for feed, water, and emergency support. He lay awake doing the arithmetic of losses, listening to fields that had gone silent.
But survival had left a mark deeper than the losses. It had changed the way he looked at the sky, the soil, and the future. This time, he wasn’t waiting. This time, he was preparing early. And that shift, from coping to anticipating, is what climate researchers call anticipatory adaptation.
Anticipatory Adaptation
Actions taken before climate impacts intensify, based on foresight, memory, and perceived future risk. It contrasts with reactive adaptation, which occurs only after damage is felt.
The key insight: memory of past shocks is one of the strongest predictors of early adaptive action, but only when paired with accessible science and enabling policy.
The 2018 drought was the moment Ireland learned it was not insulated from what climate science had been predicting for decades. Michael lost nearly a third of his forage that year. What he didn’t know, until later, was that the same system had scorched most of northern Europe simultaneously.
The report described something Michael recognised instantly: farms that had diversified early suffered less, recovered faster, and needed fewer emergency supports. It wasn’t luck. It was anticipation. But when he spoke to his neighbours that winter, most of them were making the same plans they had always made. The shock had not yet translated into change.
This is the gap that behavioural scientists call the intention-action gap, the space between knowing something and doing something about it. Understanding why that gap persists is as important as understanding the climate itself.
Michael had begun reading more widely after the drought. Not out of curiosity but out of necessity. He found stories that mirrored his own, but with different endings. Places that had been through their version of the bad one and come out the other side with new practices built into the rhythm of the year.
Global cases: Anticipatory Adaptation in Practice
Australia after the Millennium Drought
Post-drought farms adopted soil moisture probes, water-efficient irrigation and drought-resilient pasture mixes. CSIRO found these farms improved water productivity even in dry years.
+20–25% water productivity (CSIRO)
Brazil Cerrado integrated systems
Farmers facing erratic rainfall shifted to Integrated Crop–Livestock Systems (ICLS). Research shows higher soil organic matter, improving drought resilience structurally.
+30% soil organic matter (Embrapa)
New Zealand Anticipatory Grazing
Dairy farmers using forward-looking grazing plans, not reacting season by season, showed markedly lower losses during drought events.
15–20% fewer losses vs. reactive farms (NIWA)
India Dryland Farming Systems
In Rajasthan and Maharashtra, johad (rainwater harvesting) revival and sorghum-legume intercropping, traditional systems re-adopted anticipatorily, showed strong household resilience.
40% reduced crop failure incidence (ICRISAT)
These were not just success stories. They were a pattern. In every case, the farms that fared better had done two things: they had trusted a signal (from a model, a peer, a memory), and they had acted on it before the signal became a crisis. Both steps were required. Neither alone was sufficient.
One evening, Michael’s daughter Mai returned from university with a laptop full of maps. She had been working with a climate modelling group using downscaled CMIP6 projections to predict local drought risk. She opened a map showing rainfall anomalies for their region. The colours deepened from pale yellow to burnt orange over the next 20 years.
“This isn’t a forecast,” Mai said. “It’s a trajectory.”
Michael looked at the map for a long time. He had seen forecasts before, single-season predictions that were wrong as often as they were right. But a trajectory was different. A trajectory was a direction. And he knew, from standing in that field five years ago, that he had already felt the beginning of it.
What Mai brought was not just data. It was a bridge between the scientific world and the one his father stood in every morning. The real question, the one behavioural researchers spend entire careers on, is why that bridge is still so rarely crossed. Why do many farms still have no written adaptation plan, even till 2026, with so much already known about?
Walking the fields together, Michael and Mai began to build a plan. But the plan didn’t emerge from science alone. It emerged from the interaction between what the data said, what Michael was willing and able to believe, and what support structures existed to make action feel possible rather than overwhelming.
This is what researchers call the science–behaviour–policy triangle. Each corner is necessary. None is sufficient on its own.
Michael and Mai’s plan was modest but deliberate. Reseed 20% of land with drought-resilient species mixes, install two soil moisture sensors, build a small rainwater harvesting system, shift grazing rotation earlier in the season, and trial a drought-tolerant forage crop. None of these guarantees safety. But together, they guaranteed readiness.
Readiness, Michael realised, was the new form of resilience. And it required not just knowing, but deciding and then doing. This is ultimately a story about the gap between those three verbs. Closing that gap is not a scientific problem. It is a human one. Which is why it may be the hardest problem of all, and the most important one to solve.
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