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Our analysis draws from 17 published and unpublished datasets and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.