Managing uncertainty in climate-driven ecological models to inform adaptation to climate change
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The impacts of climate change on forest ecosystems are likely to require changes in forest planning and natural resource management. Changes in tree growth, disturbance extent and intensity, and eventually species distributions are expected. In natural resource management and planning, ecosystem models are typically used to provide a “best estimate” about how forests might work in the future and thus guide decision-making. Ecosystem models can be used to develop forest management strategies that anticipate these changes, but limited experience with models and model output is a challenge for managers in thinking about how to address potential effects of climate change. What do decision makers need to know about climate models, ecological models used for impacts assessments, and the uncertainty in model projections in order to use model output in strategies for adaptation to climate change? We present approaches for understanding and reducing the uncertainty associated with modeling the effects of climate change on ecosystems, focusing on multi-model approaches to clarify the strengths and limits of projections and minimize vulnerability to undesirable consequences of climate change. Scientific uncertainties about changes in climate or projections of their impacts on resources do not present fundamental barriers to management and adaptation to climate change. Instead, many of these uncertainties can be controlled by characterizing their effects on models and future projections from those models. There is uncertainty in decision making that does not derive just from the complex interaction of climate and ecosystem models, but in how modeling is integrated with other aspects of the decision environment such as choice of objectives, monitoring, and approach to assessment. Adaptive management provides a hedge against uncertainty, such that climate and ecosystem models can inform decision making.
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Uncertainties in projected fire changes are due to inherent differences among GCMs.
“These uncertainties are due to inherent differences among GCMs (Meehl et al. 2007, Littell et al. 2011), illustrated in our climate agreement maps, and are a key motivation for global multi-model ensemble analyses such as those presented here.”
From Climate change and disruptions to global fire activity (2012) · cites this paper as Littell et al. 2011
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- Authors
- Littell, J. S., McKenzie, D., Kerns, B. K., Cushman, S., & Shaw, C. G.
- Affiliations
- University of Washington (US)
- US Forest Service (US)
- Corresponding author
- Littell, Jeremy S.
- Venue
- Ecosphere
- Publisher
- Wiley
- Published
- 2011-09
- Volume
- 2
- Issue
- 9
- Pages
- art102
- ISSN
- 2150-8925 (ISSN-L)
- OpenAlex
- W2021343386
- Cited by
- 138
- References
- 79
- Citations by year
- 2026: 5 · 2025: 8 · 2024: 2 · 2023: 1 · 2022: 6 · 2021: 7 · 2020: 8 · 2019: 13 · 2018: 11 · 2017: 13 · 2016: 9 · 2015: 9 · 2014: 18 · 2013: 17 · 2012: 11
- FWCI
- 12.58
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Ecosphere (publishedVersion, cc-by)
- Funders
- Joint Institute for the Study of the Atmosphere and Ocean (NA17RJ1232)
- National Oceanic and Atmospheric Administration (NA17RJ1232)
- Western Wildland Environmental Threat Assessment Center
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Forest Management and Policy
- Physical Sciences › Environmental Science › Global and Planetary Change › Plant Water Relations and Carbon Dynamics
- Physical Sciences › Environmental Science › Nature and Landscape Conservation › Forest ecology and management
- Keywords
- climate change adaptation, forests, ecosystem models, uncertainty reduction, multi-model approach, adaptive management, forest management planning, natural resource management, climate change projections, decision making under uncertainty, tree growth, disturbance, species distribution
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