Finding the needle in the haystack: iterative sampling and modeling for rare taxa
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Much like finding a needle in a haystack, the effort required to detect a rare and endangered species increases inversely with limited taxa distribution. The infrequency of detections combined with limited fiscal resources often leaves scientists with knowledge gaps about the ecological niche and habitat requirements necessary for conserving rare species. The Arsapnia arapahoe snowfly (A. arapahoe), was thought to be a rare and cryptic aquatic invertebrate for which only 13 individuals from two locations were known to exist in Colorado. In response to potential listing by the US Fish and Wildlife Service as a threatened species, we sought to implement an improved sampling protocol and tested an iterative predictive modeling approach. Species distribution models successively employed annual presence data collected from 2015 to 2017 and detections improved. Although now understood to be a hybrid taxa, the model predicted the locations of seven additional localities while concurrently narrowing the search area and expanding the known geographic range of A. arapahoe. Given our results, we recommend an iterative species distribution modeling and sampling strategy to refine search areas and improve detection rates for rare and endangered species.
KeywordsCryptic Detection Maxent Software for assisted habitat modeling Species distribution model Survey
We thank Danielle Fuller, Brian Heinold, and Yann Lapotre for collecting specimens examined in this study. Three peer-reviewers provided helpful comments and suggestions. Natural Resources Ecology Laboratory, Colorado State University, Department of Bioagricultural Sciences and Pest Management, Colorado State University, and USDA Forest Service provided support and funding for this study.
This study was funded by the Natural Resources Ecology Laboratory, Colorado State University, Department of Bioagricultural Sciences and Pest Management, Colorado State University, and USDA Forest Service.
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Conflict of interest
The authors declare that they have no conflict of interest.
- Belcher T (2014) Estimating the population size and distribution of the arapahoe snowfly (Arsapnia arapahoe) (Plecoptera: Capniidae) along the northern front range of Colorado. Colorado State University, Fort CollinsGoogle Scholar
- Fairchild M, Belcher T III, Zuellig R, Vieira N, Kondratieff B (2017) A rare and cryptic endemic of the Central Rocky Mountains, U.S.A: the distribution of the Arapahoe snowfly, Arsapnia arapahoe (Nelson & Kondratieff, 1988) (Plecoptera: Capniidae). Illiesia 13:50–58Google Scholar
- Kumar S, Stohlgren TJ (2009) Maxent modeling for predicting suitable habitat for threatened and endangered tree Canacomyrica monticola in New Caledonia. J Ecol Nat Environ 1:094–098Google Scholar
- Nelson CR, Kondratieff BC (1988) A new species of Capnia (Plecoptera: Capniidae) from the rocky mountains of Colorado. Entomol News (USA) 99:77–80Google Scholar
- Phillips, S. J., Dudík, M., & Schapire, R. E. (2004) A maximum entropy approach to species distribution modeling. In Proceedings of the twenty-first international conference on Machine learning, pp.83. Alberta: ACMGoogle Scholar
- U.S. Geological Survey. (2013) National Hydrography Geodatabase: The National Map viewer. https://viewer.nationalmap.gov/viewer. Accessed July 17, 2013]
- Young MK, Smith RJ, Kondratieff BC, Pilgrim KL, Fairchild MP, Schwartz MK (2018) Integrative taxonomy refutes a species hypothesis: the asymmetric hybrid origin of Arsapnia arapahoe. Plecoptera, Capniidae (Submitted for publication) Google Scholar