Spatial patterns of vegetation response to climate variability across the American Southwest

Background/Question/Methods

In the American Southwest, the early 21^st century has seen arguably the most severe drought in history.  The prolonged drought and high temperatures seen in the early 21^st century are similar to the future conditions predicted by climate models. The objective of this study was to investigate the patterns in vegetation response to the early 21^st century drought across ecosystem types. We hypothesized that current-year above-ground net primary productivity (ANPP) would be explained by both the precipitation in the current year and the productivity in the previous year for all ecosystems.  We tested this hypothesis at ten Ameriflux sites in various ecosystem types ranging from desert grasslands to ponderosa pine forests, using Daymet for meteorological information, and using NASA MODIS Enhanced Vegetation Index (EVI) measurements as a surrogate for Aboveground Net Primary Production (ANPP). The EVI was compared to in situ measurements of productivity (Gross Ecosystem Production and Net Ecosystem Exchange) from the Ameriflux towers to assess the similarity of temporal trends at monthly and annual time scales. 

Results/Conclusions

For low-elevation grasslands and shrublands, we determined that current-year ANPP (ANPP_CY) was controlled by current-year precipitation (P_CY) and previous-year production (ANPP_PY).  However, the contribution of ANPP_PY to ANPP_CY was small, and thus, models were improved when ANPP_CY was predicted with only P_CY. For high elevation woodlands and forests, ANPP_CY was not related to P_CY precipitation and ANPP_PY. Instead, we are combining snowpack data with P_CY to more accurately determine winter precipitation at high elevation sites, and incorporating summer daily maximum temperature to explain variations in ANPP_CY at these sites. These results advanced our understanding of herbaceous and non-herbaceous responses to climate variability and allowed a generalization of the functional responses of vegetation to predicted future climate conditions.