five

California Drought Assessment

收藏
KNB Data Repository2016-01-01 更新2026-05-11 收录
下载链接:
https://knb.ecoinformatics.org/view/doi:10.5063/F1N29TW1
下载链接
链接失效反馈
官方服务:
资源简介:
Drought is a global issue that is exacerbated by climate change and increasing anthropogenic water demands. The recent occurrence of drought in California provides an important opportunity to examine drought response across ecosystem classes (forests, shrublands, grasslands, and wetlands), which is essential to understand how climate influences ecosystem structure and function. We quantified ecosystem resilience to drought by comparing changes in satellite derived estimates of water use efficiency (WUE = net primary productivity (NPP)/ evapotranspiration (ET)) under baseline and drought conditions (Î WUE = WUE2014 â baseline WUE). With this method, areas with increasing WUE under drought conditions are considered more resilient than systems with declining WUE. Changes in water availability had a significant effect on carbon (C) dynamics in California ecosystems. Baseline WUE varied across California (0.08 to 3.85 g C mm-1 H2O) and WUE generally increased under extreme drought conditions in 2014 (p< 0.001; R2 = 0.83). Strong correlations between Î WUE, precipitation and LAI indicate possible physiological response to drought. For instance, ecosystems with a lower average leaf area index (LAI, i.e. grasslands) maintained greater C uptake rates when water was limiting by increasing WUE and/or elevating carbon uptake efficiency (CUE = NPP/ LAI). We also found that systems with a baseline WUE â ¤ 0.4 exhibited lower WUE under drought conditions, suggesting that a low baseline WUE and Î WUE is indicative of low drought resilience. Drought severity, precipitation and WUE were identified as important drivers of shifts in ecosystem classes over the study period. These findings have important implications for understanding climate change effects on primary productivity and C sequestration across ecosystems and how this may influence ecosystem resilience in the future.
提供机构:
Rocky Mountain Research Station
创建时间:
2016-01-01
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作