AUTHOR=Gao Mengmeng , Liu Qiong , Liu Yali , Yang Nan , Wang Yi , Li Xiaolei TITLE=Spatial and temporal variations of vegetation water use efficiency and its response to climate change and human activities in the West Liao River Plain, China JOURNAL=Frontiers in Ecology and Evolution VOLUME=11 YEAR=2023 URL=https://www.frontiersin.org/journals/ecology-and-evolution/articles/10.3389/fevo.2023.1176131 DOI=10.3389/fevo.2023.1176131 ISSN=2296-701X ABSTRACT=

Water use efficiency [WUE = gross primary production (GPP)/evapotranspiration (ET)] is an important indicator of the degree of coupling between carbon and water cycles in ecosystems. However, the response of the carbon and water cycles to climate change and human activities,as well as the underlying driving mechanisms in the West Liao River Plain (WLRP), a typical farming–pasturing ecotone in northern China, remain unclear. This study examined the temporal and spatial variation characteristics of WUE in the WLRP from 2000 to 2020 using linear regression and the coefficient of variation (CV) method based on MODIS GPP and ET datasets. The relationships between WUE, meteorological factors, and human activities as well as the mechanism driving WUE changes were revealed through correlation analyses, residual analysis, and the grey correlation model. The interannual change of WUE from 2000 to 2020 showed a fluctuating but weakly upward trend. The intra-annual change in WUE followed an M-type bimodal trend, with two peaks from May to June and August to September. Areas with increased WUE accounted for 50.82% of the study area, and 11.11% of these showed a significant increasing trend. WUE was mainly positively correlated with temperature and solar radiation and negatively correlated with precipitation and VPD and presented obvious regional differences. Solar radiation had the most significant impact on WUE. WUE change is not entirely driven by climate change, and human activities have also played an important role. In areas where WUE increased, The average contribution rate of climate change was 72.4%, and that of human activities was 27.6%. This study reveals the temporal and spatial dynamics of WUE in the WLRP and highlights the influence of human activities on WUE changes.