AUTHOR=Duan Houlang , Yu Xiubo , Xia Shaoxia , Liu Yu TITLE=Combining Bootstrapping Procedure and Citizen Science Data to Elucidate Waterbirds’ Dependence on Coastal Wetland JOURNAL=Frontiers in Marine Science VOLUME=Volume 9 - 2022 YEAR=2022 URL=https://www.frontiersin.org/journals/marine-science/articles/10.3389/fmars.2022.888535 DOI=10.3389/fmars.2022.888535 ISSN=2296-7745 ABSTRACT=Coastal wetland of Yellow and Bohai seas, China along the East Asian–Australasian Flyway (EAAF) migratory route provide important stopover sites for waterbirds. Natural wetland loss caused by external stress have posed serious threat to waterbirds population. Elucidating the extent to which species depend on natural wetland and provide conservation and management recommendations for species is an important step toward relieving such population declines. We created natural landscape index (NL) along the coastal wetland of the Yellow and Bohai seas, China by inverse distance-weighted nearest-neighbour approach. Then using bootstrapping procedure to combined NL with 11485 occurrence records for 80 waterbird species attributed to four functional groups (shorebirds, ducks, herons, gulls) to quantify species’ dependence on the coastal natural wetland. Twenty-seven out of the 80 species selected (16 shorebird, 3 duck, 4 heron, and 4 gull species) significantly depended on natural wetland. The shorebirds (standardized effect size (SES)=4.37) and herons (SES=2.56) were more dependent on natural wetland than the ducks (SES=-0.02) and gulls (SES=-3.22). The threatened species (those are classified as Critically Endangered, Endangered, Vulnerable, or Near Threatened) had significantly higher dependence on natural wetland than the non-threatened species (t=2.613, df=78, p<0.05). Of the 27 species with significant dependence on natural wetland, only nine species were listed as National Protected Species. Threatened species which highly depends on natural wetland need more attention, these species could face greater risk due to natural wetlands loss.