Forecasting climate change impacts on plant populations over large spatial extents

By: , and 



Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. We overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates in the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Forecasting climate change impacts on plant populations over large spatial extents
Series title Ecosphere
DOI 10.1002/ecs2.1525
Volume 7
Issue 10
Year Published 2016
Language English
Publisher Ecological Society of America
Contributing office(s) Coop Res Unit Seattle, Earth Resources Observation and Science (EROS) Center, Fort Collins Science Center
Description e01525; 16 p.
Country United States
State Wyoming
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