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Abstract Comparisons of intraspecific genetic diversity across species can reveal the roles of geography, ecology, and life history in shaping biodiversity. The wide availability of mitochondrial DNA (mtDNA) sequences in open-access databases makes this marker practical for conducting analyses across several species in a common framework, but patterns may not be representative of overall species diversity. Here, we gather new and existing mtDNA sequences and genome-wide nuclear data (genotyping-by-sequencing; GBS) for 30 North American squamate species sampled in the Southeastern and Southwestern United States. We estimated mtDNA nucleotide diversity for 2 mtDNA genes, COI (22 species alignments; average 16 sequences) and cytb (22 species; average 58 sequences), as well as nuclear heterozygosity and nucleotide diversity from GBS data for 118 individuals (30 species; 4 individuals and 6,820 to 44,309 loci per species). We showed that nuclear genomic diversity estimates were highly consistent across individuals for some species, while other species showed large differences depending on the locality sampled. Range size was positively correlated with both cytb diversity (phylogenetically independent contrasts: R2 = 0.31, P = 0.007) and GBS diversity (R2 = 0.21; P = 0.006), while other predictors differed across the top models for each dataset. Mitochondrial and nuclear diversity estimates were not correlated within species, although sampling differences in the data available made these datasets difficult to compare. Further study of mtDNA and nuclear diversity sampled across species’ ranges is needed to evaluate the roles of geography and life history in structuring diversity across a variety of taxonomic groups. 

BackgroundAmphibians are experiencing substantial declines attributed to emerging pathogens. Efforts to understand what drives patterns of pathogen prevalence and differential responses among species are challenging because numerous factors related to the host, pathogen, and their shared environment can influence infection dynamics. Furthermore, sampling across broad taxonomic and geographic scales to evaluate these factors poses logistical challenges, and interpreting the roles of multiple potentially correlated variables is difficult with traditional statistical approaches. In this study, we leverage frozen tissues stored in natural history collections and machine learning techniques to characterize infection dynamics of three generalist pathogens known to cause mortality in frogs. MethodsWe selected 12 widespread and abundant focal taxa within three ecologically distinct, co-distributed host families (Bufonidae, Hylidae, and Ranidae) and sampled them across the eastern two-thirds of the United States of America. We screened and quantified infection loadsviaquantitative PCR for three major pathogens: the fungal pathogenBatrachochytrium dendrobatidis(Bd), double-stranded viruses in the lineageRanavirus(Rv), and the alveolate parasite currently referred to as Amphibian Perkinsea (Pr). We then built balanced random forests (RF) models to predict infection status and intensity based on host taxonomy, age, sex, geography, and environmental variables and to assess relative variable importance across pathogens. Lastly, we used one-way analyses to determine directional relationships and significance of identified predictors. ResultsWe found approximately 20% of individuals were infected with at least one pathogen (231 single infections and 25 coinfections). The most prevalent pathogen across all taxonomic groups was Bd (16.9%; 95% CI [14.9–19%]), followed by Rv (4.38%; 95% CI [3.35–5.7%]) and Pr (1.06%; 95% CI [0.618–1.82%]). The highest prevalence and intensity were found in the family Ranidae, which represented 74.3% of all infections, including the majority of Rv infection points, and had significantly higher Bd intensities compared to Bufonidae and Hylidae. Host species and environmental variables related to temperature were key predictors identified in RF models, with differences in importance among pathogens and host families. For Bd and Rv, infected individuals were associated with higher latitudes and cooler, more stable temperatures, while Pr showed trends in the opposite direction. We found no significant differences between sexes, but juvenile frogs had higher Rv prevalence and Bd infection intensity compared to adults. Overall, our study highlights the use of machine learning techniques and a broad sampling strategy for identifying important factors related to infection in multi-host, multi-pathogen systems. 

Abstract AimIntraspecific genetic variation is key for adaptation and survival in changing environments and is known to be influenced by many factors, including population size, dispersal and life‐history traits. We investigated genetic variation within Neotropical amphibian species to provide insights into how natural history traits, phylogenetic relatedness, climatic and geographic characteristics can explain intraspecific genetic diversity. LocationNeotropics. TaxonAmphibians. MethodsWe assembled data sets using open‐access databases for natural history traits, genetic sequences, phylogenetic trees, climatic and geographic data. For each species, we calculated overall nucleotide diversity (π) and tested for isolation by distance (IBD) and isolation by environment (IBE). We then identified predictors ofπ, IBD and IBE using random forest (RF) regression or RF classification. We also fitted phylogenetic generalized linear mixed models (PGLMMs) to predictπ, IBD and IBE. ResultsWe compiled 4052 mitochondrial DNA sequences from 256 amphibian species (230 frogs and 26 salamanders), georeferencing 2477 sequences from 176 species that were not linked to occurrence data. RF regressions and PGLMMs were congruent in identifying range size and precipitation (σ) as the most important predictors ofπ, influencing it positively. RF classification and PGLMMs identified minimum elevation as an important predictor of IBD; most species without IBD tended to occur at higher elevations. Maximum latitude and precipitation (σ) were the best predictors of IBE, and most species without IBE occur at lower latitudes and in areas with more variable precipitation. Main ConclusionsThis study identified predictors of genetic variation in Neotropical amphibians using both machine learning and phylogenetic methods. This approach was valuable to determine which predictors were congruent between methods. We found that species with small ranges or living in zones with less variable precipitation tended to have low genetic diversity. We also showed that Western Mesoamerica, Andes and Atlantic Forest biogeographic units harbour high diversity across many species that should be prioritized for protection. These results could play a key role in the development of conservation strategies for Neotropical amphibians. 

Abstract Natural history collections (NHCs) are important resources for a diverse array of scientific fields. Recent digitization initiatives have broadened the user base of NHCs, and new technological innovations are using materials generated from collections to address novel scientific questions. Simultaneously, NHCs are increasingly imperiled by reductions in funding and resources. Ensuring that NHCs continue to serve as a valuable resource for future generations will require the scientific community to increase their contribution to and acknowledgement of collections. We provide recommendations and guidelines for scientists to support NHCs, focusing particularly on new users that may be unfamiliar with collections. We hope that this perspective will motivate debate on the future of NHCs and the role of the scientific community in maintaining and improving biological collections.