ArticleProceedings. Biological sciences2016
Identifying cryptic diversity with predictive phylogeography.
Article in Proceedings. Biological sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Range-Wide Genomic Analysis of Pygmy Rabbits (Genes · 2026Article
- Five Hidden Species in a Widespread European Vertebrate: Disentangling the Alpine Newt Cryptic Species Complex Through Genomic Phylogeography.Molecular ecology · 2026Article
- Phylogeography reveals the complex impact of the Last Glacial Maximum on New Zealand's terrestrial biota.Journal of the Royal Society of New Zealand · 2024Review
- Hybrid zone analysis confirms cryptic species of banded newt and does not support competitive displacement since secondary contact.Ecology and evolution · 2023Article
- Reduced representation approaches produce similar results to whole genome sequencing for some common phylogeographic analyses.PloS one · 2023Article
- Environmentally driven phenotypic convergence and niche conservatism accompany speciation in hoary bats.Scientific reports · 2022Article
- Genomic evidence of an ancient inland temperate rainforest in the Pacific Northwest of North America.Molecular ecology · 2022Article
- Review
- Using natural history to guide supervised machine learning for cryptic species delimitation with genetic data.Frontiers in zoology · 2022Article
- The Evolution of Comparative Phylogeography: Putting the Geography (and More) into Comparative Population Genomics.Genome biology and evolution · 2022Review
- Assessing model adequacy for Bayesian Skyline plots using posterior predictive simulation.PloS one · 2022Article
- Delimiting cryptic species within the brown-banded bamboo shark, Chiloscyllium punctatum in the Indo-Australian region with mitochondrial DNA and genome-wide SNP approaches.BMC ecology and evolution · 2021Article
- Genomic Resources for the North American Water Vole (GigaByte (Hong Kong, China) · 2021Article
- Article
- Identifying genetic relationships among tarsier populations in the islands of Bunaken National Park and mainland Sulawesi.PloS one · 2020Article
- A demonstration of unsupervised machine learning in species delimitation.Molecular phylogenetics and evolution · 2019Article
- The role of glacial-interglacial climate change in shaping the genetic structure of eastern subterranean termites in the southern Appalachian Mountains, USA.Ecology and evolution · 2019Article
- Predicting plant conservation priorities on a global scale.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- Cryptic diversity within grass-associated Abacarus species complex (Acariformes: Eriophyidae), with the description of a new species, Abacarus plumiger n. sp.Experimental & applied acarology · 2018Article
- Combining allele frequency and tree-based approaches improves phylogeographic inference from natural history collections.Molecular ecology · 2018Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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