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Data from: Liming and spring salamander abundance

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Environmental acidification is affecting ecosystems around the globe, and as a result, managers are using limestone applications to mitigate the effects of acid rain and acid mine drainage. Limestone applications attempt to reverse acidification by increasing stream pH, however, studies assessing how liming affects species have shown mixed results. We examined the effects of liming on Gyrinophilus porphyriticus (the spring salamander) abundance. From June 10th to September 1st, 2013, we used multiple methods (i.e., leaf litterbags, visual encounter surveys, and area constrained flip and search methods) to sample spring salamanders within 11 different streams in the Monongahela National Forest, West Virginia. Using N-mixture models, which allow for estimation of abundance from count data and account for imperfect detection probabilities, we examined the effects of direct application liming (DAL) on spring salamander abundance and found that DAL and lime frequency had unexpected associations with spring salamander abundance. We found that a higher lime frequency resulted in lower spring salamander abundance, presumably due to the subsequent loss of spring salamander primary habitat when the hyporheic zone is filled. These results have and will continue to inform managers to the possible negative effects of high frequency liming on salamander communities and other stream organisms as well as inform adjustments that can be made to mitigate these impacts as a result of lime management.

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Please cite as: Elise Edwards, Brittany Mosher, Thomas Pauley, Shane Welch, Jayme L. Waldron. (2023) Data from: Liming and spring salamander abundance [Dataset] Cornell University eCommons Repository. https://doi.org/10.7298/0e1s-mm78

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2023

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detection probability; direct application liming; Gyrinophilus porphyriticus; N-Mixture; West Virginia

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Edwards, E., Pauley, T.K., and Waldron, J.L. 2016. Estimating spring salamander detection probability using multiple methods. Journal of Herpetology 50: 126–129, https://doi.org/10.1670/15-041

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https://doi.org/10.1670/15-041

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Government Document

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CC0 1.0 Universal

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dataset

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none

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