An integrated model for prediction of hydrologic anomalies for habitat suitability of overwintering geese in a large floodplain wetland, China.

Climate anomalies and increasing human activities cause a high frequency of extreme hydrological events in wetlands, which has put waterbirds under greater survival pressure than ever. Therefore, it is crucial to predict the impact of this phenomenon on the habitat suitability of waterbirds. This study investigated the response of the goose distribution probability to hydrological variations using the flood duration index (FD), enhanced vegetation index (EVI), and waterbirds GPS tracking data in Poyang Lake. An overwintering geese habitat suitability index (HSI) is built based on the FD, EVI, and threat index and verifies the accuracy of the model simulation. Then, the effects of drought and flood on the goose habitat especially sub-lakes with different connectivity were analyzed. The findings reveal that in dry and flood years, geese will broaden their range of feeding vegetation (more fresh or mature vegetation) in response to environmental deterioration. Both drought and flood can lead to a decline in the HSI, especially flood. Connected sub-lakes are more vulnerable to hydrological anomalies than controlled sub-lakes. This research establishes a scientific foundation for floodplain wetland hydrology management and waterbird conservation.

Using citizen science data to inform the relative sensitivity of waterbirds to natural versus human-dominated landscapes in China.

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.