Climate change, wildfire, and vegetation shifts in a high-inertia forest landscape: Western Washington, U.S.A.
Fig 2
Conceptual overview of modeling process.
Ellipses represent model input and rectangles represent models. Unbounded text indicates model outputs. In step1, future climate scenario and biogeographic information are input into the MC2 Dynamic Global Vegetation Model. Within MC2, three sub-models typically interact to project potential future vegetation, wildfire, and carbon, among other output. For this analysis, we included a species distribution model of forest zones within the biogeography sub-model. In step 2, MC2 wildfire and forest zone projections for each climate scenario are analyzed to develop forest transition average probabilities and both wildfire and forest zone trends. In step 3, the MC2-derived trends and probabilities are used to develop climate-informed state-and-transition simulation models (cSTSMs) for each climate scenario. Within a cSTSM, area is permitted to shift across previously developed state-and-transition simulation models (two simplified example models are shown) following a stand-replacing disturbance (i.e., when landscape inertia is broken). Figure adapted from [46].