Cryptic species delimitation in the southern Appalachian Antrodiaetus unicolor (Araneae: Antrodiaetidae) species complex using a 3RAD approach

Newton, Lacie; Starrett, James; Hendrixson, Brent E.; Derkarabetian, Shahan; Bond, Jason E.

doi:10.22541/au.158231675.51684028

Cited by 5 publications

(15 citation statements)

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“…BFD* and VAE partitioned equally in Mussmann et al (2020), although their populations were relictual and without contemporary connectivity, whereas Terrapene reflects both historical (Figure 3d) and contemporary gene flow (Martin et al, 2020). In corroboration, other studies have also demonstrated reticulation to condense VAE clusters (Derkarabetian et al, 2019;Newton et al, 2020). Although not run on a full data set, dElimitR formed clusters consistent with (or similar to) several of the UML methods (e.g., iSomdS + GS; Figure 3d;…”

Section: Relative Performance Of Species-delimitation Methodssupporting

confidence: 71%

“…gently, yet we found highly filtered data sets were biased towards smaller K, generally retaining only nodes deepest within the phylogeny. The same pattern was identified using the VAE method (Newton et al, 2020), and is intuitive given expectations that a major subset of missing ddRAD data are systematically distributed (defined by mutation-disruption of restriction sites: Eaton et al, 2017;Gautier et al, 2013). Thus, indiscriminate exclusion may unintendedly bias information content leading to the underestimation of diversity (Arnold et al, 2013;Huang & Knowles, 2016;Leaché et al, 2015).…”

Section: Data Treatment and Assignment Consistencysupporting

confidence: 56%

“…Again, an ordination technique is simulated but without imposing linear/orthogonal constraints, such that a statistically interpretable result emerges that is appropriate for highlycomplex data (Derkarabetian et al, 2019). Some algorithms are robust to gene flow (Derkarabetian et al, 2019;Newton et al, 2020;Smith & Carstens, 2020), yet a greater number of tests must be performed across diverse systems so as to understand which parameters impinge upon performance.…”

Section: Introductionmentioning

confidence: 99%

“…Potentials include: Data quantity (Newton et al, 2020), the proportion of missing data (Mussmann et al, 2020), and evolutionary complexity (Austerlitz et al, 2009). Here, we employ M-L algorithms alongside coalescent methods such as BFD* (Leaché et al, 2014) as vehicles to parse a taxonomically recalcitrant clade.…”

Section: Introductionmentioning

confidence: 99%

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The choices we make and the impacts they have: Machine learning and species delimitation in North American box turtles (Terrapene spp.)

Martin

Chafin

Douglas

et al. 2021

Molecular Ecology Resources

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Model-based approaches that attempt to delimit species are hampered by computational limitations as well as the unfortunate tendency by users to disregard algorithmic assumptions. Alternatives are clearly needed, and machine-learning (M-L) is attractive in this regard as it functions without the need to explicitly define a species concept. Unfortunately, its performance will vary according to which (of several) bioinformatic parameters are invoked. Herein, we gauge the effectiveness of M-L-based species-delimitation algorithms by parsing 64 variably-filtered versions of a ddRADderived SNP data set collected from North American box turtles (Terrapene spp.). Our filtering strategies included: (i) minor allele frequencies (MAF) of 5%, 3%, 1%, and 0% (= none), and (ii) maximum missing data per-individual/per-population at 25%, 50%, 75%, and 100% (= no filtering). We found that species-delimitation via unsupervised M-L impacted the signal-to-noise ratio in our data, as well as the discordance among resolved clades. The latter may also reflect biogeographic history, gene flow, incomplete lineage sorting, or combinations thereof (as corroborated from previously observed patterns of differential introgression). Our results substantiate M-L as a viable species-delimitation method, but also demonstrate how commonly observed patterns of phylogenetic discordance can seriously impact M-L-classification.

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Section: Relative Performance Of Species-delimitation Methodssupporting

confidence: 71%

Section: Data Treatment and Assignment Consistencysupporting

confidence: 56%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The choices we make and the impacts they have: Machine learning and species delimitation in North American box turtles (Terrapene spp.)

Martin

Chafin

Douglas

et al. 2021

Molecular Ecology Resources

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show abstract

“…In light of these challenges, many modern delimitation frameworks have relied on genetic or genomic data to identify discrete evolutionary units and assign species identities to individuals, resulting in phylogenies that are consistent with a variety of species criteria (e.g., genomic integrity, genotypic cluster, or phylogenetic species concepts; Sperling, 2003, and reviews in de Queiroz, 2007; Hausdorf, 2011). However, integration of additional information, such as ecological associations, not only helps to resolve evolutionary relationships among cryptic taxa but also provides insight into mechanisms that underlie their divergence (i.e., the ecological species concept; Andersson, 1990; Newton et al, 2020; Nosil, 2012; Rissler & Apodaca, 2007; Van Valen, 1976; Villegas et al, 2021). These approaches, making use of multiple types of data and analytical frameworks, are generally referred to as integrative species delimitation (Dayrat, 2005; Edwards & Knowles, 2014; Puillandre et al, 2012; Roe & Sperling, 2007; Schlick‐Steiner et al, 2010; Viciriuc et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Genomics and ecological modelling clarify species integrity in a confusing group of butterflies

Campbell

MacDonald

Gage³

et al. 2022

Molecular Ecology

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Recent advances in both genomics and ecological modelling present new, multidisciplinary opportunities for resolving species boundaries and understanding the mechanisms that maintain their integrity in regions of contact. Here, we use a combination of high-throughput DNA sequencing and ecological niche modelling to resolve species boundaries and niche divergence within the Speyeria atlantis-hesperis (Lepidoptera: Nymphalidae) complex, a confusing group of North American butterflies. This complex is notorious for its muddled species delimitations, morphological ambiguity, and extensive mitonuclear discordance. Our admixture and multispecies coalescent-based analyses of single nucleotide polymorphisms identified substantial divergences between S. atlantis and S. hesperis in areas of contact, as well as between distinct northern and southern lineages within S. hesperis. Our results also provide evidence of past introgression relating to another species, S. zerene, which previous work has shown to be more distantly related to the S. atlantis-hesperis complex. We then used ecological models to predict habitat suitability for each of the three recovered genomic lineages in the S. atlantis-hesperis complex and assessed their pairwise niche divergence. These analyses resolved that these three lineages are significantly diverged in their respective niches and are not separated by discontinuities in suitable habitat that might present barriers to gene flow. We therefore infer that ecologically-mediated selection resulting in disparate habitat associations is a principal mechanism reinforcing their genomic integrity. Overall, our results unambiguously support significant evolutionary and ecological divergence between the northern and southern lineages of S. hesperis, sufficient to recognize the southern evolutionary lineage as a distinct species, called S. nausicaa based on taxonomic priority.

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Microgeographic population structuring in a genus of California trapdoor spiders and discovery of an enigmatic new species (Euctenizidae: Promyrmekiaphila korematsui sp. nov.)

Starrett,

Jochim,

Quayle

et al. 2024

Ecology and Evolution

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The recognition and delineation of cryptic species remains a perplexing problem in systematics, evolution, and species delimitation. Once recognized as such, cryptic species complexes provide fertile ground for studying genetic divergence within the context of phenotypic and ecological divergence (or lack thereof). Herein we document the discovery of a new cryptic species of trapdoor spider, Promyrmekiaphila korematsui sp. nov. Using subgenomic data obtained via target enrichment, we document the phylogeography of the California endemic genus Promyrmekiaphila and its constituent species, which also includes P. clathrata and P. winnemem. Based on these data we show a pattern of strong geographic structuring among populations but cannot entirely discount recent gene flow among populations that are parapatric, particularly for deeply diverged lineages within P. clathrata. The genetic data, in addition to revealing a new undescribed species, also allude to a pattern of potential phenotypic differentiation where species likely come into close contact. Alternatively, phenotypic cohesion among genetically divergent P. clathrata lineages suggests that some level of gene flow is ongoing or occurred in the recent past. Despite considerable field collection efforts over many years, additional sampling in potential zones of contact for both species and lineages is needed to completely resolve the dynamics of divergence in Promyrmekiaphila at the population–species interface.

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Cryptic species delimitation in the southern Appalachian Antrodiaetus unicolor (Araneae: Antrodiaetidae) species complex using a 3RAD approach

Cited by 5 publications

References 0 publications

The choices we make and the impacts they have: Machine learning and species delimitation in North American box turtles (Terrapene spp.)

The choices we make and the impacts they have: Machine learning and species delimitation in North American box turtles (Terrapene spp.)

Genomics and ecological modelling clarify species integrity in a confusing group of butterflies

Microgeographic population structuring in a genus of California trapdoor spiders and discovery of an enigmatic new species (Euctenizidae: Promyrmekiaphila korematsui sp. nov.)

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