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Identifying cryptic diversity with predictive phylogeography.
Proc Biol Sci. 2016 Oct 26; 283(1841)PB

Abstract

Identifying units of biological diversity is a major goal of organismal biology. An increasing literature has focused on the importance of cryptic diversity, defined as the presence of deeply diverged lineages within a single species. While most discoveries of cryptic lineages proceed on a taxon-by-taxon basis, rapid assessments of biodiversity are needed to inform conservation policy and decision-making. Here, we introduce a predictive framework for phylogeography that allows rapidly identifying cryptic diversity. Our approach proceeds by collecting environmental, taxonomic and genetic data from codistributed taxa with known phylogeographic histories. We define these taxa as a reference set, and categorize them as either harbouring or lacking cryptic diversity. We then build a random forest classifier that allows us to predict which other taxa endemic to the same biome are likely to contain cryptic diversity. We apply this framework to data from two sets of disjunct ecosystems known to harbour taxa with cryptic diversity: the mesic temperate forests of the Pacific Northwest of North America and the arid lands of Southwestern North America. The predictive approach presented here is accurate, with prediction accuracies placed between 65% and 98.79% depending of the ecosystem. This seems to indicate that our method can be successfully used to address ecosystem-level questions about cryptic diversity. Further, our application for the prediction of the cryptic/non-cryptic nature of unknown species is easily applicable and provides results that agree with recent discoveries from those systems. Our results demonstrate that the transition of phylogeography from a descriptive to a predictive discipline is possible and effective.

Authors+Show Affiliations

Department of Biological Sciences, University of Idaho, 875 Perimeter Drive MS 3051, Moscow, ID 83844-3051, USA anahi.espindola@gmail.com. Biological Sciences, Institute for Bioinformatics and Evolutionary Studies (IBEST), 875 Perimeter Drive MS 3051, Moscow, ID 83844-3051, USA.Department of Biological Sciences, University of Idaho, 875 Perimeter Drive MS 3051, Moscow, ID 83844-3051, USA. Biological Sciences, Institute for Bioinformatics and Evolutionary Studies (IBEST), 875 Perimeter Drive MS 3051, Moscow, ID 83844-3051, USA.Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, 318 W. 12th Avenue, 300 Aronoff Labs, Columbus, OH 43210-1293, USA.Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, 318 W. 12th Avenue, 300 Aronoff Labs, Columbus, OH 43210-1293, USA.Department of Biological Sciences, University of Idaho, 875 Perimeter Drive MS 3051, Moscow, ID 83844-3051, USA. Biological Sciences, Institute for Bioinformatics and Evolutionary Studies (IBEST), 875 Perimeter Drive MS 3051, Moscow, ID 83844-3051, USA.Department of Biological Sciences, University of Idaho, 875 Perimeter Drive MS 3051, Moscow, ID 83844-3051, USA. Biological Sciences, Institute for Bioinformatics and Evolutionary Studies (IBEST), 875 Perimeter Drive MS 3051, Moscow, ID 83844-3051, USA.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

27798300

Citation

Espíndola, Anahí, et al. "Identifying Cryptic Diversity With Predictive Phylogeography." Proceedings. Biological Sciences, vol. 283, no. 1841, 2016.
Espíndola A, Ruffley M, Smith ML, et al. Identifying cryptic diversity with predictive phylogeography. Proc Biol Sci. 2016;283(1841).
Espíndola, A., Ruffley, M., Smith, M. L., Carstens, B. C., Tank, D. C., & Sullivan, J. (2016). Identifying cryptic diversity with predictive phylogeography. Proceedings. Biological Sciences, 283(1841).
Espíndola A, et al. Identifying Cryptic Diversity With Predictive Phylogeography. Proc Biol Sci. 2016 Oct 26;283(1841) PubMed PMID: 27798300.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Identifying cryptic diversity with predictive phylogeography. AU - Espíndola,Anahí, AU - Ruffley,Megan, AU - Smith,Megan L, AU - Carstens,Bryan C, AU - Tank,David C, AU - Sullivan,Jack, PY - 2016/07/07/received PY - 2016/09/27/accepted PY - 2016/11/1/pubmed PY - 2017/12/13/medline PY - 2016/11/1/entrez KW - Pacific Northwest rainforest KW - cryptic diversity KW - lineage discovery KW - predictive phylogeography KW - random forest JF - Proceedings. Biological sciences JO - Proc Biol Sci VL - 283 IS - 1841 N2 - Identifying units of biological diversity is a major goal of organismal biology. An increasing literature has focused on the importance of cryptic diversity, defined as the presence of deeply diverged lineages within a single species. While most discoveries of cryptic lineages proceed on a taxon-by-taxon basis, rapid assessments of biodiversity are needed to inform conservation policy and decision-making. Here, we introduce a predictive framework for phylogeography that allows rapidly identifying cryptic diversity. Our approach proceeds by collecting environmental, taxonomic and genetic data from codistributed taxa with known phylogeographic histories. We define these taxa as a reference set, and categorize them as either harbouring or lacking cryptic diversity. We then build a random forest classifier that allows us to predict which other taxa endemic to the same biome are likely to contain cryptic diversity. We apply this framework to data from two sets of disjunct ecosystems known to harbour taxa with cryptic diversity: the mesic temperate forests of the Pacific Northwest of North America and the arid lands of Southwestern North America. The predictive approach presented here is accurate, with prediction accuracies placed between 65% and 98.79% depending of the ecosystem. This seems to indicate that our method can be successfully used to address ecosystem-level questions about cryptic diversity. Further, our application for the prediction of the cryptic/non-cryptic nature of unknown species is easily applicable and provides results that agree with recent discoveries from those systems. Our results demonstrate that the transition of phylogeography from a descriptive to a predictive discipline is possible and effective. SN - 1471-2954 UR - https://www.unboundmedicine.com/medline/citation/27798300/Identifying_cryptic_diversity_with_predictive_phylogeography_ DB - PRIME DP - Unbound Medicine ER -