Estimating the sensitivity of sagebrush to climate change from muli-year monitoring data

Understanding how climate change will affect the abundance of dominant plants is a critical question for conservation in the 21^st century. We used long-term field observations of sagebrush (<i>Artemisia tridentata</i>) cover and production to estimate sagebrush sensitivity to annual precipitation and temperature across its range. Our analysis draws from 17 published and unpublished datasets and includes 5709 observations of year-to-year change in sagebrush cover or production from 944 monitoring sites located across western North America. We coupled these data with monthly precipitation and temperature data for each site from the PRISM and DAYMET climate datasets. We analyzed the effects of spring through fall temperatures and fall through spring accumulated precipitation on sagebrush abundance observed in each year. Our statistical model allowed these short-term climate effects to vary depending on the long-term average climate of each site. Overall, the sensitivity of sagebrush to annual climate covariates was weak compared to unexplained year-to-year variation. Of the climate covariates tested, average temperature of the preceding three growing seasons had the largest effect: sagebrush responded negatively to warmer years in hotter climates but positively to warmer years in colder climates. Our model predicts that sagebrush cover would show an increase at the coldest sites and a decrease at the warmest sites in response to 2°C of warming. However, 95% confidence intervals around these predicted changes were wide and overlapped zero at most sites, indicating low confidence in these predictions. Our analysis shows how long-term monitoring data can be put to use now to predict the ecological effects of climate change in the near future.