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Ecosystem water use efficiency (WUE) and ecosystem photosynthetic efficiency (EPE) are key indicators in studies of the carbon–water cycle in terrestrial ecosystems. Analyses of WUE and EPE can enhance our understanding of the relationship between ecosystem light use efficiency and WUE. Although several studies of individual indexes (i.e., either WUE or EPE) have been conducted, analyses of variation in both WUE and EPE, as well as their relationships, have rarely been conducted. Here, we analyzed spatial and temporal variation in WUE and EPE in Central Asia. Specifically, time trend analysis was conducted to characterize temporal and spatial changes in WUE and EPE in Central Asia from 2001 to 2020 at different altitudes and latitudes. Pearson correlation analysis was used to characterize the effects of precipitation and temperature on WUE and EPE. WUE decreased and EPE increased in Central Asia over the 20-year study period; this might have been due to interannual variations in precipitation and temperature. WUE was highest in August, and EPE was highest in June and July. Substantial spatial heterogeneity in WUE and EPE was observed; WUE was highly variable in Central Asia as well as in western and southern Central Asia. Major changes in EPE were observed in northern, eastern, and southern Central Asia. We also found that both WUE and EPE decreased with the increase in altitude. WUE was positively correlated with temperature and negatively correlated with precipitation, whereas EPE was positively correlated with both temperature and precipitation. The increase in photosynthetic efficiency might be one of the main factors contributing to increases in ecosystem productivity in arid environments. The temporal and spatial variation in WUE and EPE observed in our study will aid ecosystem research, providing a reliable theoretical basis for ecosystem research in areas with scarce large-scale data, integrated water resources management, and ecosystem restoration efforts. Our findings also enhance our understanding of the terrestrial carbon–water cycle and have implications for predicting ecosystem responses to climate change. The results of this study provide insights that will aid studies of the terrestrial carbon–water cycle under the background of climate change. It is of great significance to further study the carbon water cycle in the future. [ABSTRACT FROM AUTHOR]

Aerosols significantly contribute to global and regional climate change by altering the surface solar radiation, thereby affecting plant productivity. Central Asia is a primary source of global dust aerosols. However, the mechanisms of how aerosols affect terrestrial gross primary productivity (GPP), especially in Central Asia, are not clearly understood. In this study, we investigated the spatial variation in aerosol optical depth (AOD) and GPP and the relationship between them during the growing season (April–October) from 2001 to 2018 using remote sensing data from several sources. We created a GWR-SEM model consisting of a geographically weighted model (GWR) coupled with a structural equation model (SEM) to quantify and analyze the effects of AOD on GPP. The results show that AOD decreased slightly at a rate of −0.0002 y−1 during the study period and that there was a tendency towards spatial aggregation. The extent of AOD pollution in the northwest region (around the Aral Sea) was slightly greater than that in the southeast. GPP increased significantly at a rate of 7.2965 g C m−2 y−2, especially in the northern region. There were some differences in the effects of AOD on GPP between different vegetation types; the highest AOD–GPP correlation was found in shrublands and croplands. Analysis of the GWR-SEM model suggested that AOD and two forms of radiation (surface net radiation, SNR, and photosynthetically active radiation, PAR) explained 72.4% (63.4% for 2001, 66.8% for 2018) of the spatial variation in GPP. SNR had the greatest effect on GPP, followed by AOD. Diffuse PAR had the greatest indirect effect on GPP. The findings of this study highlight the importance of aerosol pollution on spatial variation in gross primary productivity, and they provide a methodological framework for investigating the relationship between AOD and GPP in arid areas. [Display omitted] • Spatial and temporal variations of AOD and GPP over Central Asia are evaluated against MODIS products. • The correlation between AOD and GPP over Central Asia are revealed. • A GWR-SEM model is used to quantitatively evaluate aerosol effects on GPP. • The major drivers of GPP change with time and vegetation types. [ABSTRACT FROM AUTHOR]