As rainfall extremes are expected to increase in novel magnitude and
frequency, especially in dryland regions, we asked how prolonged and
directional shifts to water availability may affect ecosystem carbon
and nitrogen dynamics. This data set includes foliar and soil carbon
and nitrogen stable isotope and concentration data collected from
multiple long-term rainfall manipulation experiments at the Jornada
Basin LTER. Datasets also include rainfall data adjusted to rainfall
manipulation intensities. Collection dates range from 5 to 14 years
since the onset of experimental treatments. The primary plant
species targeted for this study were the dominant grass, Bouteloua
eriopoda, and the dominant shrub, Prosopis glandulosa.
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Dataset and analyses for publication entitled: “Acclimation of the nitrogen cycle to changes in precipitation”
This dataset contains data and analysis code for the paper entitled
“Acclimation of the nitrogen cycle to changes in precipitation"
by Currier et al. As the frequency of precipitation extremes are
expected to increase, especially in arid regions, we asked how
prolonged shifts in water availability facilitate acclimation of the
N cycle in a semiarid grassland. Using natural abundances of stable
nitrogen isotopes for dominant plants and soils and rainfall
manipulation experiments, we tested the hypothesis that N cycling
will interact with water availability further amplifying the
openness of the N cycle through time. For the dominant plant
species, we found the relationship for N availability vs. ambient
annual precipitation to be significantly positive, contrary to
global spatial models. We also considered the temporal dynamics of
our experiments, which imposed directional rainfall manipulations in
duration ranging from 5 to 14 years. The slopes of these
relationships decreased (became less positive) with more time since
the onset of the directional precipitation extremes. These data and
metadata supplement long-term foliar and soil isotope data from the
Jornada LTER (Dataset ID: knb-lter-jrn.210586001) with a large
spatial dataset from NEON data package DP1.10026.001 and Craine et
al. 2018 (https://doi.org/10.5061/dryad.v2k2607).
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- Award ID(s):
- 2025166
- PAR ID:
- 10472488
- Publisher / Repository:
- Environmental Data Initiative
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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