--- title: "What a Climate Assessment Paper Is Actually For" description: "A University of Maine professor co-authored the opening paper in a national series meant to steer disaster preparedness research" author: "Nate Ledger" published: 2026-10-04T04:52:47.738Z modified: 2026-10-04T10:59:34Z url: https://rews.cc/a/what-a-climate-assessment-paper-is-actually-for-145847 language: en tags: ["climate", "disaster", "indigenous", "research", "resilience", "science", "world"] publisher: "Rews (https://rews.cc)" --- # What a Climate Assessment Paper Is Actually For *A University of Maine professor co-authored the opening paper in a national series meant to steer disaster preparedness research* By Nate Ledger · October 4, 2026 · https://rews.cc/a/what-a-climate-assessment-paper-is-actually-for-145847 ## In brief - UMaine professor John Daigle co-authored the first paper in a joint AGU–AMS collection on climate assessment science - The paper, led by Melissa A. Kenney, sets research priorities for future U.S. national and subnational climate assessments - Priorities include how emissions and laws compound extreme weather, how social systems shape planning, and whether mitigation efforts work - Daigle contributed analysis of climate risks to Indigenous peoples and the value of Indigenous knowledge for adaptation - The paper appears in the Bulletin of the American Meteorological Society and Earth’s Future Suppose you are a town in Maine, or a tribal nation, or a state emergency office, and you would like to know what the next twenty years of weather are going to do to your roads, your fishing grounds and your budget. You cannot run this experiment yourself. What you can do is read the national climate assessments, the big periodic syntheses of climate science that tell governments at every level what is coming, and then build your disaster plans on top of them. Which means the assessments matter a lot, and which means, one step further back, that the question of what the assessments ought to study matters a lot too. That is the layer of the stack where the news sits this week. John Daigle, a professor of forest recreation management at the University of Maine, is a co-author of a paper called “Research Priorities for Robust Climate Assessments in the United States,” the first contribution to a joint special collection run by the American Geophysical Union and the American Meteorological Society. The collection — the U.S. Climate Collection informing Assessment of Risks and Solutions — is designed to gather climate assessment science and research synthesis papers that will feed future national and subnational assessments. The paper appears in the *Bulletin of the American Meteorological Society* and in *Earth’s Future*, with Melissa A. Kenney as lead author. It is, in effect, a memo from the research community to its future self: here is what the next round of assessments should bother to figure out. The memo’s to-do list has four items on it, and they are telling. The authors want more work on how greenhouse gas emissions and laws compound the effects of extreme weather; on how social systems shape planning; on how climate-related weather risks threaten infrastructure and institutions; and on how well the existing intervention, mitigation, adaptation and disaster management efforts actually work. Note what is mostly not on that list: more proof that climate change is happening. The research frontier, as these authors frame it, has moved from “is this real” to “which of our responses to it are worth the money,” which is a much more uncomfortable question for everyone involved, because it has a right answer that someone will have to measure. ## The place-based problem Daigle’s particular contribution concerns Indigenous peoples, and it illustrates why the social-systems item is on the list in the first place. Climate change, he said, “impacts the relationships between people and nature, particularly for Indigenous peoples and other communities with strong place-based cultural ties. Changes in timing of biological events, range shifts of plants and animals, and function can disrupt cultural practices, subsistence activities and identity.” A standard risk model can put a dollar figure on a flooded road. It has a much harder time with the loss of a subsistence harvest that a community’s practices and identity are built around, because that loss does not clear a market. The flip side, in Daigle’s telling, is that those same communities hold knowledge that the models lack. “At the same time, Indigenous knowledges and relational worldviews offer valuable insights for adaptation and stewardship,” he said. The argument is not merely that vulnerable groups should be counted more carefully, though they should; it is that people who have managed a specific landscape for a very long time know things about how it behaves under stress that a continental-scale dataset does not. Daigle’s broader pitch is that assessments have spent too long cataloguing stuff and not long enough modelling how stuff behaves. “Future assessments will be more useful if they go beyond species inventories to focus on dynamic processes, adaptive capacity, integrated system-level responses, and social and ecological feedbacks,” he said. “By synthesizing insights from ecological, cultural and governance domains, the scientific community can better anticipate, manage and leverage ecological transformation as climate change accelerates.” A species inventory tells you what is there. A dynamic-process model tells you what happens next, which is the thing a town manager actually needs. None of this is binding on anyone. A research-priorities paper has no budget and no enforcement arm; it is a coordination device, a way for a scattered field to agree on which questions are worth the grant applications. But coordination devices have a quiet power. The assessments inform the disaster plans, the disaster plans inform the funding requests, and the funding requests inform what gets built before the storm rather than after. The paper at the top of that chain is a long way from a sandbag. It still points somewhere.