| Summary: | Context Global biodiversity decreases rapidly, driven by various factors ranging from climate change to anthropogenic activities. Identifying driving forces of population decline is critical for biological conservation. Time-series data are especially valuable for this goal, but unfortunately, high-quality time-series data are generally lacking, hampering evidences-based conservation policy making. Objectives In this study, we examined how population growth rates of wintering waterbird species changed across 34 years (1986-2019) in response to changes in landscape context, climatic, ecological and anthropogenic factors in the Yangtze River Floodplain. Specifically: we aimed to (1) understand the factors that are correlated with the population trend of each waterbird species, and (2) identify the spatial scale at which each waterbird species responds to surrounding landscape changes. Methods We systemically collected wintering survey data from 1986 to 2019 in Shengjin Lake National Nature Reserve for six waterbird species including Oriental stork (Ciconia boyciana), Eurasian spoonbill (Platalea leucorodia), Tundra swan (Cygnus columbianus), Swan goose (Anser cygnoid), Hooded crane (Grus monacha) and White-naped crane (Grus vipio), coupled with climatic and anthropogenic data. Satellite images were analyzed to characterize ecological variables and landscape context (both in landscape and class levels). Results Our results suggested that anthropogenic landscape changes surrounding wetland habitats (i.e., landscape context) acted as the primary factors driving the waterbird population changes and were responsible for the observed population declines. In particular, increasing built-up areas and decreasing cropland areas associated with urbanization and human settlement expansion largely explained the declining population size. Our results also showed that different variables operated at a different scale of the landscape context, highlighting the importance of the surrounding landscape configuration at both small ...
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