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• W4366990280 abstract "Endemic species are threatened by invasive species, habitat loss, and climate change. Endemic species are also an important group that maintains biodiversity. Understanding population dynamics of endemic species is needed to maintain or restore their populations. Advancements in models that describe population dynamics of endemic species and species of conservation need has been made possible by the application of novel quantitative methods. One such modeling tool is state-space modeling. These models provide a flexible framework to describe population dynamics using simple mortality models and more complex integrated population models. Here we develop a state-space model to describe survival and population size of the Sicklefin Redhorse (Catostomidae: Moxostoma sp.), a species of conservation concern from two rivers located in North Carolina, USA. This model is structured to combine information across similar rivers and to account for complex interactions of sex, time, variable sampling effort, and river discharge. Survival of Sicklefin Redhorse was found to vary by sex, and annual variability was not consistent across rivers. Discharge was negatively related to capture probability for males. Capture probabilities also differed across sex. Population estimates revealed a large difference between sex where males outnumbered females each year in both rivers. We conclude that electrofishing is not an efficient capture method but when used, should consider discharge. Discharge was not included in the survival model, however, the 3 years with the lowest survival in the Little Tennessee River coincided with the three lowest discharge years in the time series. Future work should investigate the difference in survival between the rivers." @default.
• W4366990280 created "2023-04-27" @default.
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• W4366990280 date "2023-04-25" @default.
• W4366990280 modified "2023-10-14" @default.
• W4366990280 title "State-space models to describe survival of an endemic species in the Little Tennessee River basin" @default.
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• W4366990280 doi "https://doi.org/10.3389/fevo.2023.1097389" @default.
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