Abstract

AbstractAimTo assess the abiotic correlations between indicator species and others in the community. Additionally, we evaluated the importance of environmental variables in driving the co‐occurrence patterns of the coexisting riparian bird species within a threatened aquatic and terrestrial system.LocationSeven classic submontane rivers in riparian ecosystems of the Changbai Mountains in eastern Jilin Province, China, elevation ranging from 351 to 942 m.MethodsJoint species distribution models (JSDMs) were applied to examine the relative importance of abiotic and potential species associations driving the abundance and cooccurrence of bird species along submontane riparian zones. The abiotic factors were examined with a focus on the scaly‐sided Merganser and the coexisting bird species potentially sharing or interacting within the same niche.ResultsWe found that the co‐occurrence patterns of submontane riparian bird species were dominantly driven by numerous positive correlations when incorporating abiotic variables. The scaly‐sided Merganser exhibited the greatest number of correlations with other species and exhibited significant responses to most of the measured environmental variables. Land cover diversity, proportion of gravel bars, and channel width were the most common environmental factors affecting riparian bird species distribution.ConclusionsUsing JSDM, we found that the indicator roles of the scaly‐sided Merganser are mainly derived from shared environmental responses with coexisting riparian bird species; moreover, the composition of submontane riparian bird communities is affected by both environmental variables and potential species associations. Our results verified the central role of the scaly‐sided Merganser as an indicator species in submontane riparian ecosystems due to their strict physical environment preferences and extensive connections with other sympatric riparian bird species, primarily through shared environmental intersections. Our results emphasize the crucial necessity for simultaneously considering environmental predictors and potential species associations in modelling species distributions and to better realizing the roles of indicators in practical applications.

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