Spatiotemporal Variation and Climate Influence Factors of Vegetation Ecological Quality in the Sanjiangyuan National Park

The Sanjiangyuan National Park is the first Chinese national park system, and the ecological environment is inherently fragile and sensitive. Therefore, for environmental protection, it is imperative to understand the spatiotemporal variation characteristics of the ecological quality of vegetation and its climate influence factors. We used the MODIS normalized difference vegetation index (NDVI) dataset, meteorological dataset, and Carnegie–Ames–Stanford Approach (CASA) model to investigate the spatiotemporal patterns and change trends of the NDVI and the net primary productivity (NPP) of the vegetation in the Sanjiangyuan National Park from 2000 to 2016. A linear regression model was used to explore the influence of the ecological quality of vegetation and climatic factors. The results showed that (1) the NDVI and NPP were high in the southeast area and low in the northwest area. The Yangtze River headwater region had the lowest NDVI (0–0.3) and NPP (0–100 gC/m²). The Lancang River had the highest NDVI (0.4–0.8) and NPP (100–250 gC/m²). (2) From 2000–2016, approximately 23.46% of the area showed a significant positive trend of the NDVI that was mainly distributed in the prairie areas in the midlands and the north of the Yangtze River headwater region, and was scattered in the midlands and the north of Yellow River headwater region. Furthermore, 24.32% of the NPP was determined to have increased significantly, which was mainly distributed in the midlands and the north of the Yangtze River headwater region, as well as the midlands and the east of the Yellow River headwater region. (3) The vegetation growth in the Sanjiangyuan National Park was regulated by both water and heat conditions. The NDVI was significantly affected by precipitation during the growing season and by the annual precipitation. In addition, the NPP was significantly affected by temperature during the growing season and by the annual average temperature of the study area.