Ecosphere (Dec 2019)
Local‐regional similarity in drylands increases during multiyear wet and dry periods and in response to extreme events
Abstract
Abstract Climate change is predicted to impact ecosystems through altered precipitation (PPT) regimes. In the Chihuahuan Desert, multiyear wet and dry periods and extreme PPT pulses are the most influential climatic events for vegetation. Vegetation responses are most frequently studied locally, and regional responses are often unclear. We present an approach to quantify correlation of PPT and vegetation responses (as Normalized Difference Vegetation Index [NDVI]) at the Jornada ARS‐LTER site (JRN; 550 km2 area) and the surrounding dryland region (from 0 to 500 km distance; 400,000 km2 study area) as a way to understand regional similarity to locally observed patterns. We focused on fluctuating wet and dry years, multiyear wet or dry periods of 3–4 yr, and multiyear wet periods that contained one or more extreme high PPT pulses or extreme low rainfall. In all but extreme high PPT years, JRN PPT was highly correlated (r > 0.9) to PPT across the regional study area (0–500 km distance; high correlation from 25th to 75th percentiles) and was highly correlated across a greater PPT range subregionally (0–200 km distance; high correlation from 10th to 90th percentiles). In contrast, the statistical distribution of JRN NDVI was less similar to that of regional NDVI. Yet, local‐regional NDVI similarity increased during multiyear periods to a maximum of >90% similarity for 10th–90th percentiles in a number of years. Thus, local‐regional heterogeneity in PPT and vegetation responses is reduced in both multiyear wet and dry periods, with the largest changes in climatic forcing and responses during multiyear wet periods. These wet and dry events support greater similarity between local‐regional PPT and vegetation response patterns. We conclude that site‐based research on multiyear periods can be extended to anticipate larger regional responses, and illustrate the opportunity to enhance understanding of future PPT change through increased focus on multiyear periods.
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