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Bioclimatic modeling of potential vegetation types as an alternative to species distribution models for projecting plant species shifts under changing climates

August 18, 2020

Land managers need new tools for planning novel futures due to climate change. Species distribution modeling (SDM) has been used extensively to predict future distributions of species under different climates, but their map products are often too coarse for fine-scale operational use. In this study we developed a flexible, efficient, and robust method for mapping current and future distributions and abundances of vegetation species and communities at the fine spatial resolutions that are germane to land management. First, we mapped Potential Vegetation Types (PVTs) using conventional statistical modeling techniques (Random Forests) that used bioclimatic ecosystem process and climate variables as predictors. We obtained over 50% accuracy across 13 mapped PVTs for our study area. We then applied future climate projections as climate input to the Random Forest model to generate future PVT maps, and used field data describing the occurrence of tree and non-tree species in each PVT category to model and map species distribution for current and future climate. These maps were then compared to two previous SDM mapping efforts with over 80% agreement and equivalent accuracy. Because PVTs represent the biophysical potential of the landscape to support vegetation communities as opposed to the vegetation that currently exists, they can be readily linked to climate forecasts and correlated with other, climate-sensitive ecological processes significant in land management, such as fire regimes and site productivity.

Citation Information

Publication Year 2020
Title Bioclimatic modeling of potential vegetation types as an alternative to species distribution models for projecting plant species shifts under changing climates
DOI 10.1016/j.foreco.2020.118498
Authors Robert Keane, Lisa M. Holsinger, Rachel A. Loehman
Publication Type Article
Publication Subtype Journal Article
Series Title Forest Ecology and Management
Series Number
Index ID 70212606
Record Source USGS Publications Warehouse
USGS Organization Alaska Science Center Geography

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