AUTHOR=Povak Nicholas A. , Manley Patricia N. TITLE=Evaluating climate change impacts on ecosystem resources through the lens of climate analogs JOURNAL=Frontiers in Forests and Global Change VOLUME=6 YEAR=2024 URL=https://www.frontiersin.org/journals/forests-and-global-change/articles/10.3389/ffgc.2023.1286980 DOI=10.3389/ffgc.2023.1286980 ISSN=2624-893X ABSTRACT=

As disturbances continue to increase in magnitude and severity under climate change, there is an urgency to develop climate-informed management solutions to increase resilience and help sustain the supply of ecosystem services over the long term. Towards this goal, we used climate analog modeling combined with logic-based conditions assessments to quantify the future resource stability (FRS) under mid-century climate. Analog models were developed for nine climate projections for 1 km cells across California. For each model, resource conditions were assessed at each focal cell in comparison to the top 100 climate analog locations using fuzzy logic. Model outputs provided a measure of support for the proposition that a given resource would be stable under future climate change. Raster outputs for six ecosystem resources exhibited a high degree of spatial variability in FRS that was largely driven by biophysical gradients across the State, and cross-correlation among resources suggested similarities in resource responses to climate change. Overall, about one-third of the State exhibited low stability indicating a lack of resilience and potential for resource losses over time. Areas most vulnerable to climate change occurred at lower elevations and/or in warmer winter and summer environments, whereas high stability occurred at higher elevation, or at mid-elevations with warmer summers and cooler winters. The modeling approach offered a replicable methodology to assess future resource stability across large regions and for multiple, diverse resources. Model outputs can be readily integrated into decision support systems to guide strategic management investments.