Predicting impacts of global climatic change on genetic and phylogeographical diversity of a Neotropical treefrog

Abstract

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Neogene–Quaternary tectonic, eustatic and climatic events shaped the evolution of a South American treefrog

“…Scinax squalirostris has high overall nucleotide and haplotype diversities, as identified previously for the same species (Abreu‐Jardim et al, 2021), and similar to other South American anurans, such as Pseudopaludicola falcipes ( h = 0.92, π = 0.2119, Langone et al, 2016), S. eurydice ( h = 0.81, π = 0.0057, Menezes et al, 2016), Pithecopus megacephalus ( h = 0.94, π = 0.0054, Ramos et al, 2018), Leptodactylus bufonius ( h = 0.92, π = 0.00763, Brusquetti et al, 2019) and Bokermannohyla saxicola ( h = 0.98, π ~ 0.06, Oswald et al., 2022). High levels of genetic diversity within populations have been associated with high effective population sizes over long periods (Pabijan et al, 2012).…”

Treefrog Diversity in the Neotropics: Phylogenetic Relationships of Scinaxini (Anura: Hylidae: Hylinae)

“…13, as S. squalirostris ); Costa et al (2004: spermatozoid of S. squalirostris ); Alcalde (2005: tadpole of Scinax sp. 13, as S. squalirostris ); Kwet et al (2010: natural history of S. squalirostris ); Faria et al (2013: vocalizations of S. squalirostris ); Giaretta et al (2020: vocalizations of S. squalirostris ); Abreu-Jardim et al (2021: phylogeography); Pezzuti et al (2021: tadpole of S. squalirostris ). Boelter et al (2022: phenotypic variation in tadpoles of S. squalirostris and Scinax sp.…”

Anthropogenic pressures coincide with Neotropical biodiversity hotspots in a flagship butterfly group

“…This resolution is appropriate for niche models based on large‐scale predictors such as climate (McGill, 2010), limits commission errors (Di Marco et al, 2017) and appears sufficient to identify broad geographic patterns of diversity at a scale relevant to biodiversity conservation (e.g. Abreu‐Jardim et al, 2021; Gumbs et al, 2020; Robuchon et al, 2021; Roll et al, 2017). We selected climate, represented by annual temperature and humidity levels and seasonality (MERRAclim v.2.0; Vega et al, 2017), elevation (SRTM Dataset v.4.1; Farr et al, 2007) and vegetation cover (GLCF; Sexton et al, 2013), as environmental predictor variables for distribution modelling.…”

“…27.8 km × 27.8 km. This resolution is appropriate for niche models based on large-scale predictors such as climate(McGill, 2010), limits commission errors(Di Marco et al, 2017) and appears sufficient to identify broad geographic patterns of diversity at a scale relevant to biodiversity conservation (e.g Abreu-Jardim et al, 2021;Gumbs et al, 2020;Robuchon et al, 2021;Roll et al, 2017)…”