Satellite Observations of the Recovery of Forests and Grasslands in Western China

The Grain for Green Program (GGP), which combats and reverses the landscape-scale habitat degradation by converting agricultural lands to forests and grasslands, was launched in 1999 in western China. An assessment of the extent to which the GGP has altered the vegetation cover and ecological functions in these regions is much needed. The present study initially analyzed land use and cover change of forests and grasslands over western China between 2000 and 2015. A variety of satellite-based ecological indicators, including net primary productivity, normalized difference vegetation index, leaf area index, carbon use efficiency, and water use efficiency, were used to reflect the biophysical consequences of the GGP in western China. Results indicated that the spatial extent of forests and grasslands increased by 13.97 x 10(3) and 11.13 x 10(3) km(2), respectively, which were mainly converted from deserts and croplands. The ecosystem functions of forests and grasslands showed an asymmetric response in northwestern and southwestern China. The normalized difference vegetation index and water use efficiency of forests, as well as the net primary productivity and water use efficiency of grasslands, increased significantly over this period. The GGP also has led to an increase in leaf area index and carbon use efficiency of forests and grasslands. The Loess Plateau and the Three Rivers Source area represent the most effectively recovered regions in western China. Rising precipitation rates have contributed to vegetation recovery to some extent, especially in northwestern China, whereas the GGP was the prominent reason for the improvement of ecosystem functions across the entire region of western China. Plain Language Summary Land degradation has caused severe environmental problems in many areas worldwide and severely restrains the sustainable development of numerous local economies. Land degradation also undermines the livelihoods and food security of people, especially in the economically underprivileged regions. Western China has experienced land degradation because of both its geological location and climatic conditions. To combat and mitigate this situation, the Chinese government implemented a series of national-scale ecological policies and programs during the late 1990s and early 2000s. Nearly 20 years have passed since the implementation of these projects. Therefore, it is appropriate to comprehensively assess the biophysical consequences of these programs. The present study aims to evaluate the extent to which the vegetation of western China recovered during the 2000-2015 period based on a variety of remotely sensed data streams. Results indicated that the spatial extent of forests and grasslands have expanded. The ecosystem functions of forests and grasslands showed an asymmetric response in the southwest and northwest regions of western China. These findings may provide guidelines for government agencies and policy makers involved in initiating adaptation strategies designed to adapt to climate change and to manage vegetation production.PublishedYe

Spatial-temporal Patterns and Factors of Soil Moisture in the Middle Reaches of the Yellow River under Changing Environments

[Objective] To identify the main driving factors of soil moisture in the middle reaches of the Yellow River, to analyze the impact of land cover and climate change on soil moisture changes in the middle reaches of the Yellow River, and to provide a theoretical basis for regional ecological environmental protection and high-quality development. [Methods] The SiB2 model was used to simulate the surface soil moisture (SSM) and root zone soil moisture (RZSM) in the middle reaches of the Yellow River for the years 2000, 2005, 2010, 2015 and 2020, and to analyze their spatial and temporal distribution patterns. The main driving factors were analyzed by combining the GeoDetector, Random Forest, and SHAP, and the contribution of land cover and climate change to the changes of SSM and RZSM was analyzed by using scenario-setting method. [Results] 1) The SiB2 model could better simulate the soil moisture in the middle reaches of the Yellow River after the parameter calibration. 2) Soil moisture in the middle reaches of the Yellow River showed overall spatial distribution characteristics of high in the south and low in the north, and there were differences in the distribution characteristics of SSM and RZSM under different ecological zones, different seasons and different land cover types. 3) Precipitation, soil type and downward shortwave radiation were the main drivers of SSM in the middle reaches of the Yellow River, and precipitation, soil type and land cover type were the main drivers of RZSM in the middle reaches of the Yellow River, and there were differences in the drivers of soil moisture in different ecological zones. 4) The effect of land cover type conversion on RZSM in the middle reaches of the Yellow River was regionally different, and the main direction of change was the decrease of RZSM due to the increase of leaf area index (LAI). 5) Compared to 2000, the decline in SSM and RZSM in 2020 was dominated by differences in climate change and land cover change, respectively. [Conclusion] Land cover changes in the middle reaches of the Yellow River from 2000 to 2020 led to a decline in soil moisture in the root zone, and precipitation magnitude had an important effect on changes in soil moisture after land cover type conversion

Drought-Induced Carbon and Water Use Efficiency Responses in Dryland Vegetation of Northern China

Given the context of global warming and the increasing frequency of extreme climate events, concerns have been raised by scientists, government, and the public regarding drought occurrence and its impacts, particularly in arid and semi-arid regions. In this paper, the drought conditions for the forest and grassland areas in the northern region of China were identified based on 12 years of satellite-based Drought Severity Index (DSI) data. The impact of drought on dryland vegetation in terms of carbon use efficiency (CUE) and water use efficiency (WUE) were also investigated by exploring their correlations with DSI. Results indicated that 49.90% of forest and grassland experienced a dry trend over this period. The most severe drought occurred in 2001. In general, most forests in the study regions experienced near normal and wet conditions during the 12 year period. However, grasslands experienced a widespread drought after 2006. The forest CUE values showed a fluctuation increase from 2000 to 2011, whereas the grassland CUE remained steady over this period. In contrast, WUE increased in both forest and grassland areas due to the increasing net primary productivity (NPP) and descending evapotranspiration (ET). The CUE and WUE values of forest areas were more sensitive to droughts when compared to the values for grassland areas. The correlation analysis demonstrated that areas of DSI that showed significant correlations with CUE and WUE were 17.24 and 10.37% of the vegetated areas, respectively. Overall, the carbon and water use of dryland forests was more affected by drought than that of dryland grasslands

Stomatal responses of terrestrial plants to global change

Quantifying the stomatal responses of plants to global change factors is crucial for modeling terrestrial carbon and water cycles. Here we synthesize worldwide experimental data to show that stomatal conductance (gs) decreases with elevated carbon dioxide (CO2), warming, decreased precipitation, and tropospheric ozone pollution, but increases with increased precipitation and nitrogen (N) deposition. These responses vary with treatment magnitude, plant attributes (ambient gs, vegetation biomes, and plant functional types), and climate. All two-factor combinations (except warming + N deposition) significantly reduce gs, and their individual effects are commonly additive but tend to be antagonistic as the effect sizes increased. We further show that rising CO2 and warming would dominate the future change of plant gs across biomes. The results of our meta-analysis provide a foundation for understanding and predicting plant gs across biomes and guiding manipulative experiment designs in a real world where global change factors do not occur in isolation

High-spatial-resolution monthly temperature and precipitation dataset for China for 1901-2017

The dataset with 0.5 arcminute (~1 km) was spatially downscaled from CRU TS v4.02 based on Delta downscaling method, including monthly minimum, maximum, and mean temperatures and precipitation from 1901.1 to 2017.12. The dataset covers the main land area of China. The dataset was evaluated by 745 national weather stations across China, and the evaluation indicated that the downscaled dataset is reliable for the investigations related to climate change across China