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Predicting habitat and distribution of an interior highlands regional endemic winter stonefly (Allocapnia mohri) in Arkansas using random forest models

Abstract

Stoneflies are a globally threatened aquatic insect order. In Arkansas, a diverse group of winter stonefly (Capniidae: Allocapnia ) have not been surveyed since the 1980s, likely because species-level identification requires the rarely-collected adult form. Allocapnia mohri , a regional endemic, was previously commonly found in mountainous, intermittent streams from the Ouachita Mountains ecoregion north to the Ozark Highlands, but no species distributional models including land use or climate variables exist to our knowledge. We collected adults from 71 stream reaches from the historic Arkansas range from November to April 2020 and 2021. We modeled distributions using random forest (RF) models populated with landscape, climate, and both data to determine which were most predictive of species presence. Correlations between landscape or climate variables and presence were examined using multiple logistic regression. The landscape RF models performed better than the climate or landscape + climate RF models. A. mohri presence sites tended to have a greater elevation, a lower mean July temperature, and a greater percentage of very slow infiltration soils in the watershed, compared to absence sites. A. mohri was absent at the Ouachita Mountains sites and may be experiencing a range contraction or migration northward.

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90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 33.50875350986783° to 36.49973760721201° latitude; -94.64880267254001° to -91.01694463644638° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

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BibTeXRIS

Brianna Annaratone, Camryn Larson, Clay Prater, Ashley Dowling, Daniel D. Magoulick, Michelle A. Evans-White. 2023-02-06. Predicting habitat and distribution of an interior highlands regional endemic winter stonefly (Allocapnia mohri) in Arkansas using random forest models. https://doi.org/10.3390/hydrobiology2010013

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