The lower reaches of the Jinsha River is the main distribution area of hot-dry valleys in China. While it suffers from frequent droughts, the spatiotemporal variation and driving forces of drought in this area under climate change are still unclear. The spatiotemporal variations of Temperature Vegetation Drought Index (TVDI) and drivers of drought were explored using MODIS land surface temperature and NDVI data from 2000 to 2020. The results are fivefold. (1) TVDI was highly correlated with soil moisture content at a depth of 0-7 cm, indicating that it can accurately reflect the drought situation in the study area. (2) The spatial variability of TVDI was highly heterogeneous, with a multi-year average of 0.59, and the drought level was mainly between normal and dry. (3) From 2000 to 2020, TVDI showed a slightly increasing trend. It increased in 63% of the study area, and significantly increased in 21% of the study area. At the same time, the area at the dry level increased by 14.5% in 2020 from the normal level in 2000. (4) Slightly different from the standard phenomenon of “dry gets drier, wet gets wetter”, we found that both dry and wet areas were becoming drier. (5) TVDI was positively correlated with annual mean temperature in 86% of the region, of which 43% of the region showed a significant correlation. The increasing temperature was the main driving force for the increase in drought in the study area. Our results can provide new insights into the spatiotemporally heterogeneous response of drought to climate change in the lower reaches of the Jinsha River.

Wetlands are one of the most complex ecosystem types on the planet, and ecological sensitivity assessment is an important foundation for the scientific planning of wetland park systems. The Minjiang River estuary, located in the coastal city of Fuzhou, has outstanding regional characteristics in terms of its ecosystem and biodiversity. The nearby waters are among the richest in marine species in the world and the richest in offshore marine species at that latitude in the northern hemisphere. It has at least four indicators meeting the criteria for internationally important wetlands. In this study, the analytic hierarchy process (AHP) was used to determine the weights of factors, and the comprehensive ecological sensitivity of Minjiang Estuary National Wetland Park was evaluated using the weighted-overlap method by the Remote Sensing (RS) and Geographic Information System (GIS). An ecological sensitivity evaluation index system for wetland parks was constructed using Delphi, and then an ecological sensitivity assessment of Minjiang Estuary National Wetland Park was built. The sensitivities of different areas in the Minjiang Estuary National Wetland Park were divided five ecological sensitivity levels: extremely sensitive, highly sensitive, moderately sensitive, minimally sensitive, and insensitive. The results show that the riverbanks, beaches, canals, ponds, and surrounding areas were in the range of highly and moderately sensitive areas, while insensitive and minimally sensitive areas were distributed in the artificial landscape environments such as woodlands, farmland, and parks.

Global climate change and human activities continue to threaten watershed ecosystems. The Jinsha River constitutes the upper reaches of the Yangtze River, so studying its ecosystem services (ES) is of great significance for maintaining ecological security and promoting ecological sustainability in the entire Yangtze River Basin. By using the integrated valuation of ecosystem services and trade-offs (InVEST) models and revised universal soil-loss equation (RUSLE) models, we evaluated five ecosystem services of water yield (WY), habitat quality (HQ), soil retention (SR), food supply (FS), and carbon storage (CS) provided by the Jinsha River Basin ecosystem from 2000 to 2020, as well as their spatial-temporal variations and driving factors. The results show three main features of this system. (1) From 2000 to 2020, each ecosystem service in the Jinsha River Basin exhibited different degrees of fluctuation, except for habitat quality, and each ecosystem service basically showed a spatial distribution pattern of high in the southeast and low in the northwest. (2) There were significant synergistic relationships between CS_SR_HQ and WY_SR_FS, and a significant trade-off between WY_CS. (3) The main driving factors of CS_SR_HQ were net primary productivity (NPP) and land-use type (LU), the main driving factors of WY_SR_FS were annual precipitation (PRE), LU, and rainfall erosivity (R), and the main driving factors of WY_CS varied considerably during the study period.

Revealing the mechanism by which land use influences ecosystem service function in karst urban watersheds is of great significance for social and economic development and ecological environmental protection. In this study, the Nanming River Basin, a typical karst basin in Guizhou Province, was used as an example. The spatiotemporal dynamic changes in land use in the basin during three periods from 2000 to 2020 were analyzed using ArcGIS, and the ecosystem service functions of the different land use types in the basin were evaluated using an integrated valuation of ecosystem services and tradeoffs (InVEST) model. This analysis led to three outcomes. (1) Forest, cultivated land, and grassland make up most of the land uses. The land use change was mostly dependent on the growth of construction land, which expanded by 13.07%. (2) The watershed's water conservation function was significantly boosted during the study period. In contrast, the carbon stock function became slightly impaired, and the physical quality of both was regionally distributed as high in the northeast and low in the southwest. (3) The contributions of forest to total water conservation and carbon stock of the watershed are always the greatest, exceeding 57%, and the conversions of forest to construction land and cultivated land to forest are the two primary types of land use change in which the ecosystem service function was impaired and strengthened, respectively. The results of this study can provide important data support and scientific reference for land use structure optimization, soil and water resource exploitation, and sustainable ecosystem management in ecologically fragile areas.