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Net primary production (NPP) and climate data from Sevilleta LTER core and control sites in desert grassland and shrubland ecosystems, 1999 - 2017

This dataset and R code were used to create the figures, tables and statistical analyses for the following publication: Rudgers, JA et al. 2018. Climate sensitivity functions and net primary production: A framework for incorporating climate mean and variability. Ecology. Data were collected by the Sevilleta LTER program, which is located in the Sevilleta National Wildlife Refuge (SNWR), New Mexico. These are long-term, continuing data sets. Data collection started in 1999 at the black grama grassland and creosote shrubland, and in 2002 for blue grama grassland. Meteorological stations started recording data as early as 1989. The study abstract from Rudgers et al. 2018 is: Understanding controls on net primary production (NPP) has been a long-standing goal in ecology. Climate is a well-known control on NPP, although the temporal differences among years within a site are often weaker than the spatial pattern of differences across sites. Climate sensitivity functions describe the relationship between an ecological response (e.g., NPP) and both the mean and variance of its climate driver (e.g., aridity index), providing a novel framework for understanding how climate trends in both mean and variance vary with NPP over time. Nonlinearities in these functions predict whether an increase in climate variance will have a positive effect (convex nonlinearity) or negative effect (concave nonlinearity) on NPP. The influence of climate variance may be particularly intense at ecosystem transition zones, if species reach physiological thresholds that create nonlinearities at these ecotones. Long-term data collected at the confluence of three dryland ecosystems in central New Mexico revealed that each ecosystem exhibited a unique climate sensitivity function that was consistent with long-term vegetation change occurring at their ecotones. Our analysis suggests that rising temperatures in drylands could alter the nonlinearities that determine the relative costs and benefits of varia

ShareScore

44/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
12
Harmonization
12
Access
4
Reuse readiness
8
Engagement
8

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