Habitat loss is widely regarded as one of the most destructive factors threatening native biodiversity. Because migratory waterbirds include some of the most globally endangered species, information on their sensitivity to landscape would benefit their conservation. While citizen science data on waterbird species occurrence are subjected to various biases, their appropriate interpretation can provide information of benefit to species conservation. We apply a bootstrapping procedure to citizen science data to reduce sampling biases and report the relative sensitivity of waterbird species to natural versus human‐dominated landscapes. Analyses are performed on 30,491 data records for 69 waterbird species referred to five functional groups observed in China between 2000 and 2018. Of these taxa, 30 species (43.5%) are significantly associated with natural landscapes, more so for cranes, geese, and ducks than for shorebirds and herons. The relationship between land association and the threat status of waterbirds is significant when the range size of species is considered as the mediator, and the higher the land association, the higher the threat status. Sensitive species significantly associated with natural landscapes are eight times more likely to be classified as National Protected Species (NPS) Classes I or II than less sensitive species significantly associated with human‐dominated landscapes. We demonstrate the potential for citizen science data to assist in conservation planning in the context of landscape changes. Our methods might assist others to obtain information to help relieve species decline and extinction.

The inundation areas of floodplains are crucial to wetland ecosystems, especially in supporting biodiversity. Accurately identifying the spatial and temporal patterns of inundation areas is important for understanding floodplain ecosystem processes. Here, lakes in the Yangtze River Floodplain were divided into two types according to hydrological conditions: the natural connected lakes (Dongting Lake and Poyang Lake) with natural water level fluctuations and the isolated lakes (lakes in Jianghan Plain) with stable water levels. We established a method to identify inundation areas using multi-sources remote sensing data based on the Google Earth Engine. The dynamics of inundation areas were determined, and the relative indices were calculated in common year (2017) and a drought year (2018). The differences between the connected lakes and the isolated lakes were analyzed, and impacts of hydrological fluctuations on inundation area and habitat quality were evaluated. The results show that lakes with natural hydrological fluctuations have a greater regulative flexibility, with both patch density (PD) and submerged elasticity index (SEI) values higher than that of isolated lakes. The trend of the vegetation index in the connected lakes and in the isolated lakes is also different. The mean EVI in Dongting Lake and Poyang Lake showed a U-shaped trend which is similar to the shape of the trend of PD. The trend of mean enhanced vegetation index (EVI) in the isolated lakes is the opposite and has a lower range of variation over a year. This study provides new indicators and rapid methods for habitat quality assessment in floodplains, as well as presenting scientific information useful for improving wetland management in the middle and lower Yangtze River.