Tue, Aug 03, 2021:On Demand
Background/Question/Methods
Climate change will exacerbate drought stress in arid ecosystems, including piñon-juniper woodlands of the intermountain western U.S. Tree growth can be used to assess risks to climate change and is a complex process that depends on multiple ecological drivers. Interannual climate variability, tree size, site conditions, and local adaptation can have interacting and complex effects on tree growth responses to current and future climate. We used tree-ring data collected in the U.S. Forest Service’s Forest Inventory and Analysis (FIA) Program’s spatial network of permanent sample plots in Arizona, Utah, Colorado, and New Mexico to investigate the response of Pinus edulis (common pinyon, two-needle piñon) to climate variability and how it varies across the species’ geographic distribution. We used regression models implemented in a Bayesian framework to predict the absolute width of annual growth rings as a function of tree size, climate normals, and time-varying climate variables from 1900-1995. The best-fit model included the effects of tree size, mean annual temperature and precipitation, annually varying monsoon and winter precipitation, and spring and fall temperature, along with all two-way interactions between the effects. Using this model we explored the response to climate of over 700 individual trees across the region.
Results/Conclusions Winter precipitation and mean annual temperature both have strong positive effects on Pinus edulis ring widths. Spring and fall temperatures both have negative effects on growth. A positive interaction between mean annual temperature and precipitation results in higher growth at warm and wet locations, but trees at cool and dry locations have stronger positive responses to winter precipitation. Furthermore, positive interactions between 1) winter precipitation and spring temperature and 2) monsoon precipitation and spring temperature indicate that higher-than-average precipitation could partially offset the stress of higher temperatures. While climate change will result in warmer temperatures and increased drought stress, it is uncertain how future winter and monsoon precipitation will change. Hence, the negative effects of higher interannual seasonal temperatures will likely reduce growth of Pinus edulis. The regional variation in climate response suggests that local adaptation may influence the response to climate change. This contrasts with most studies of climate vulnerability which estimate climate response at the species level. Our spatio-temporal analysis adds to a growing body of evidence that forest climate response varies across scales, from tree to plot to species, highlighting the need to account for variability at these scales to predict forest responses to future climate.
Results/Conclusions Winter precipitation and mean annual temperature both have strong positive effects on Pinus edulis ring widths. Spring and fall temperatures both have negative effects on growth. A positive interaction between mean annual temperature and precipitation results in higher growth at warm and wet locations, but trees at cool and dry locations have stronger positive responses to winter precipitation. Furthermore, positive interactions between 1) winter precipitation and spring temperature and 2) monsoon precipitation and spring temperature indicate that higher-than-average precipitation could partially offset the stress of higher temperatures. While climate change will result in warmer temperatures and increased drought stress, it is uncertain how future winter and monsoon precipitation will change. Hence, the negative effects of higher interannual seasonal temperatures will likely reduce growth of Pinus edulis. The regional variation in climate response suggests that local adaptation may influence the response to climate change. This contrasts with most studies of climate vulnerability which estimate climate response at the species level. Our spatio-temporal analysis adds to a growing body of evidence that forest climate response varies across scales, from tree to plot to species, highlighting the need to account for variability at these scales to predict forest responses to future climate.