Journal of Geophysical Research Biogeosciences · 2021 · 48 citations · 50 references
Life SciencesEcologyClimatologyPlant EcologyTerrestrial EcologySalt MarshesVegetation IndicesVegetation MonitoringWetland ConservationWetland EcologyWetland ManagementMarsh EcologyNormalized Difference Vegetation Index MappingSpatiotemporal Change AnalysisSpatiotemporal Change DetectionWetland Change AnalysisWetland Vegetation Change DetectionWetland Vegetation DynamicsWetland Vegetation Monitoring
Abstract China has the third largest area of marshes in the world. Understanding the change of marsh, vegetation and its response to climate change in China is important for the protection of wetland ecosystem. Based on the climate and normalized difference vegetation index (NDVI) data, we investigated the spatiotemporal variation in vegetation and its response to climate change for different types of marshes in China. The results indicated that growing season NDVI increased significantly (0.02/decade, P < 0.01) over the whole marshes of China from 2000 to 2019. The increased precipitation and minimum temperature during the growing season could promote the growth of marsh vegetation over China. This study found for the first time that the increase of temperature during the day and at night had asymmetric effects on vegetation growth in marshes of China, and the positive effect of night warming was more significant. Spatially, increasing growing season precipitation was beneficial to the vegetation growth of herbaceous marshes, marsh meadows, inland salt marshes, and seasonal saltwater marshes in eastern Inner Mongolia. Increased growing season minimum temperature could greatly promote the vegetation growth of marsh meadows, herbaceous marshes, inland salt marshes, forest swamp, and bush swamp in cold and high‐altitude regions of Northern Northeast China and the Tibet Plateau. In the context of global climate change, more attention should be paid to the different responses of vegetation to climate change for different marsh types, especially when we use the model to simulate the impact of climate change on vegetation in different marsh regions of China.
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