Habitat characterization and species distribution model of the only large-lake population of the endangered Silver Chub (Macrhybopsis storeriana, Kirtland 1844)

濒危物种银鲦(Macrhybopsis storeriana,Kirtland 1844)唯一大型湖泊种群的栖息地特征和物种分布模型

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Abstract

The endangered Silver Chub (Macrhybopsis storeriana, Kirtland 1844) is native to North America and primarily riverine, with the only known large-lake population in Lake Erie. Once a major component of the Lake Erie fish community, it declined and became nearly extirpated in the mid-1900s. Recent collections in western Lake Erie suggest that Silver Chub may be able to recover, but their habitat and distribution are poorly known. A recent work showed an extensive area of western Lake Erie with the potential to support large numbers of Silver Chub, but was based on a geographically limited dataset. We developed a neural network-based species distribution model for the Silver Chub in western Lake Erie, improved by new synoptic data and using habitat variables resistant to anthropogenic activities. The Potential model predictions were compared with a model that included anthropogenic-sensitive variables. The Potential model used 10 habitat variables and performed well, explaining > 99% of data variation and had generally low error rates. Predictions indicated that a large area of the waters approximately 2-9 m deep contained Appropriate habitat and the highest abundances should be supported by habitat in a wide arc through the western end of the basin. The model indicated that Appropriate Silver Chub habitat was associated with relatively deep water, near coastal wetlands, where effective fetch is less than average. Disturbance model predictions were similar, but predicted poorer Silver Chub habitat in more areas than that predicted by the Potential model. Our Potential model reveals Appropriate habitat conditions for Silver Chub and its spatial distribution, indicating that extensive areas of western Lake Erie could support Silver Chub. Comparisons with Disturbance model predictions demonstrate that Potential model predictions may be used in conjunction with analyses of degrading conditions in the system to better conserve and manage for this endangered species.

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