Biology subjects

McLaughlin, J. F.

Publications and source records attributed to McLaughlin, J. F..

8 recordsLinked to original sources

bioRxiv2024

Bird Name-a-thon: Categorizing English bird names using crowdsourcing

Common names of species are important for communicating with the general public. In principle, these names should provide an accessible way to engage with and identify species. The common names of species have historically been labile without standard guidelines, even within a language. Currently, there is no systematic assessment of how often common names communicate identifiable and biologically relevant characteristics about species. This is a salient issue in ornithology, where common names are used more often than scientific names for species of birds in written and spoken English, even by professional researchers. To gain a better understanding of the types of terminology used in the English-language common names of bird species, a group of 85 professional ornithologists and non-professional contributors classified unique descriptors in the common names of all recognized species of birds. In the AvianLexiconAtlas database produced by this work, each species common name is assigned to one of ten categories associated with aspects of avian biology, ecology, or human culture. Across 10,906 species of birds, 89% have names describing the biology of the species, while the remaining 11% of species have names derived from human cultural references, human names, or local non-English languages. Species with common names based on features of avian biology are more likely to be related to each other or be from the same geographic region. The crowdsourced data collection also revealed that many common names contain specialized or historic terminology unknown to many of the data collectors, and we include these terms in a glossary and gazetteer alongside the dataset. The AvianLexiconAtlas can be used as a quantitative resource to assess the state of terminology in English-language common names of birds. Future research using the database can shed light on historical approaches to nomenclature and how people engage with species through their names.

zoology↗

bioRxiv2024

A hybrid approach to invertebrate biomonitoring using computer vision and DNA metabarcoding

O_LIAutomated invertebrate classification using computer vision has shown significant potential to improve specimen processing efficiency. However, challenges such as invertebrate diversity and morphological similarity among taxa can make it difficult to infer fine-scale taxonomic classifications using computer vision. As a result, many invertebrate computer vision models are forced to make classifications at coarser levels, such as at family or order. C_LIO_LIHere we propose a novel modular method to combine computer vision and bulk DNA metabarcoding specimen processing pipelines to improve the accuracy and taxonomic granularity of individual specimen classifications. To improve specimen classification accuracy, our methods use multimodal fusion models that combine image data with DNA-based assemblage data. To refine the taxonomic granularity of the models classifications, our methods cross-references the classifications with DNA metabarcoding detections from bulk samples. We demonstrated these methods using a continental-scale, invertebrate bycatch dataset collected by the National Ecological Observatory Network. We also introduce the CV.eDNA R package, which aims to assist practitioners looking to implement our methods. C_LIO_LIUsing our methods, we reached a classification accuracy of 79.6% across the 17 taxa using real DNA assemblage data, and 83.6% when the assemblage data was "error-free", resulting in a 2.2% and 6.2% increase in accuracy when compared to a model trained using only images. After cross-referencing with the DNA metabarcoding detections, we improved taxonomic granularity in up to 72.2% of classifications, with up to 5.7% reaching species-level. C_LIO_LIBy providing computer vision models with coincident DNA assemblage data, and refining individual classifications using DNA metabarcoding detections, our methods the potential to greatly expand the capabilities of biological computer vision classifiers. Our methods allow computer vision classifiers to infer taxonomically fine-grained classifications when it would otherwise be difficult or impossible due to challenges of morphologic similarity or data scarcity. These methods are not limited to terrestrial invertebrates and could be applied in any instance where image and DNA metabarcoding data are concurrently collected. C_LI

bioinformatics↗

bioRxiv2023

Comparative phylogeography reveals widespread cryptic diversity driven by ecology in Panamanian birds

Widespread species often harbor unrecognized genetic diversity, and investigating the factors associated with such cryptic variation can help us better understand the forces driving diversification. Here, we identify potential cryptic species based on a comprehensive dataset of COI mitochondrial DNA barcodes from 2,333 individual Panamanian birds across 429 species, representing 391 (59%) of the 659 resident landbird species of the country, as well as opportunistically sampled waterbirds. We complement this dataset with additional publicly available mitochondrial loci, such as ND2 and cytochrome b, obtained from whole mitochondrial genomes from 20 taxa. Using barcode identification numbers (BINs), we find putative cryptic species in 19% of landbird species, highlighting hidden diversity in the relatively well-described avifauna of Panama. Whereas some of these mitochondrial divergence events corresponded with recognized geographic features that likely isolated populations, such as the Cordillera Central highlands, the majority (74%) of lowland splits were between eastern and western populations. The timing of these splits are not temporally coincident across taxa, suggesting that historical events, such as the formation of the Isthmus of Panama and Pleistocene climatic cycles, were not the primary drivers of cryptic diversification. Rather, we observed that forest species, understory species, insectivores, and strongly territorial species--all traits associated with lower dispersal ability--were all more likely to have multiple BINs in Panama, suggesting strong ecological associations with cryptic divergence. Additionally, hand-wing index, a proxy for dispersal capability, was significantly lower in species with multiple BINs, indicating that dispersal ability plays an important role in generating diversity in Neotropical birds. Together, these results underscore the need for evolutionary studies of tropical bird communities to consider ecological factors along with geographic explanations, and that even in areas with well-known avifauna, avian diversity may be substantially underestimated. LAY SUMMARY- What factors are common among bird species with cryptic diversity in Panama? What role do geography, ecology, phylogeographic history, and other factors play in generating bird diversity? - 19% of widely-sampled bird species form two or more distinct DNA barcode clades, suggesting widespread unrecognized diversity. - Traits associated with reduced dispersal ability, such as use of forest understory, high territoriality, low hand-wing index, and insectivory, were more common in taxa with cryptic diversity. Filogeografia comparada revela amplia diversidad criptica causada por la ecologia en las aves de Panama RESUMENEspecies extendidas frecuentemente tiene diversidad genetica no reconocida, y investigando los factores asociados con esta variacion criptica puede ayudarnos a entender las fuerzas que impulsan la diversificacion. Aqui, identificamos especies cripticas potenciales basadas en un conjunto de datos de codigos de barras de ADN mitocondrial de 2,333 individuos de aves de Panama en 429 especies, representando 391 (59%) de las 659 especies de aves terrestres residentes del pais, ademas de algunas aves acuaticas muestreada de manera oportunista. Adicionalmente, complementamos estos datos con secuencias mitocondriales disponibles publicamente de otros loci, tal como ND2 o citocroma b, obtenidos de los genomas mitocondriales completos de 20 taxones. Utilizando los numeros de identificacion de codigo de barras (en ingles: BINs), un sistema taxonomico numerico que proporcina una estimacion imparcial de la diversidad potencial a nivel de especie, encontramos especies cripticas putativas en 19% de las especies de aves terrestres, lo que destaca la diversidad oculta en la avifauna bien descrita de Panama. Aunque algunos de estos eventos de divergencia conciden con caracteristicas geograficas que probablemente aislaron las poblaciones, la mayoria (74%) de la divergencia en las tierras bajas se encuentra entre las poblaciones orientales y occidentales. El tiempo de esta divergencia no coincidio entre los taxones, sugiriendo que eventos historicos tales como la formacion del Istmo de Panama y los ciclos climaticos del pleistoceno, no fueron los principales impulsores de la especiacion. En cambio, observamos asociaciones fuertes entre las caracteristicas ecologicas y la divergencia mitocondriale: las especies del bosque, sotobosque, con una dieta insectivora, y con territorialidad fuerte mostraton multiple BINs probables. Adicionalmente, el indice mano-ala, que esta asociado a la capacidad de dispersion, fue significativamente menor en las especies con BINs multiples, sugiriendo que la capacidad de dispersion tiene un rol importamente en la generacion de la diversidad de las aves neotropicales. Estos resultos demonstran la necesidad de que estudios evolutivos de las comunidades de aves tropicales consideren los factores ecologicos en conjunto con las explicaciones geograficos. Palabras clave: biodiversidad tropical, biogeografia, codigos de barras, dispersion, especies cripticas

evolutionary biology↗

bioRxiv2023

Multimodal models of animal sex: breaking binaries leads to a better understanding of ecology and evolution

Sex is often used to describe a suite of phenotypic and genotypic traits of an organism related to reproduction. However, these traits - gamete type, chromosomal inheritance, physiology, morphology, behavior, etc. - are not necessarily coupled, and the rhetorical collapse of variation into a single term elides much of the complexity inherent in sexual phenotypes. We argue that consideration of sex as a constructed category operating at multiple biological levels opens up new avenues for inquiry in our study of biological variation. We apply this framework to three case studies that illustrate the diversity of sex variation, from decoupling sexual phenotypes to the evolutionary and ecological consequences of intrasexual polymorphisms. We argue that instead of assuming binary sex in these systems, some may be better categorized as multivariate and nonbinary. Finally, we conduct a meta-analysis of terms used to describe diversity in sexual phenotypes in the scientific literature to highlight how a multivariate model of sex can clarify, rather than cloud, studies of sexual diversity within and across species. We argue that such an expanded framework of sex better equips us to understand evolutionary processes, and that as biologists it is incumbent upon us to push back against misunderstandings of the biology of sexual phenotypes that enact harm on marginalized communities.

zoology↗

bioRxiv2022

Time in allopatry does not predict the outcome of secondary contact in lowland Panamanian birds

Geographic speciation models assume that time in allopatry should result in greater reproductive isolation between populations. Here we test the prediction that greater time in allopatry results in greater reproductive isolation using comparative ultraconserved element (UCE) data from ten bird lineages in secondary contact in Panama, measuring both genome-wide divergence and the geographic extent of hybridization. The best-fit models for the proportion of fixed Z-linked and autosomal loci to our data includes a combination of both time (as measured by mtDNA divergence) and hand-wing index, emphasizing that the role of time is tempered by dispersal capability. Furthermore, time does not predict the extent of genome-wide introgression as measured by the median width of diagnostic loci clines or the degree of variation in cline centers or widths. These metrics of the outcome of secondary contact were best predicted by ecological and genomic factors, including diet, hand-wing index, and genome-wide FST respectively, that are understood to serve as proxies for dispersal, the variability of population size, and overall genomic divergence. We find a primary role for ecological factors instead of isolation time in determining secondary contact outcomes for a lineage, highlighting how ecology shapes the development of reproductive isolation.

evolutionary biology↗

bioRxiv2021

Estimating movement rates between Eurasian and North American birds that are vectors of avian influenza (AI)

1.1Avian influenza (AI) is an emerging zoonotic disease that will likely be involved in future pandemics. Because waterbird movements are difficult to quantify, determining the host-specific risk of Eurasian-origin AI movements into North America is challenging. We estimated relative rates of movements, based on long-term evolutionary averages of gene flow, between Eurasian and North American waterbird populations to obtain bidirectional baseline rates of the intercontinental movements of these AI hosts. We used population genomics and coalescent-based demographic models to obtain these gene-flow-based movement estimates. Inferred rates of movement between these populations varies greatly among species. Within dabbling ducks, gene flow, relative to effective population size, varies from [~]3-24 individuals/generation between Eurasian and American wigeons (Mareca penelope - M. americana) to [~]100-300 individuals/generation between continental populations of northern pintails (Anas acuta). These are evolutionary long-term averages and provide a solid foundation for understanding the relative risks of each of these host species in potential intercontinental AI movements. We scale these values to census size for evaluation in that context. In addition to being AI hosts, many of these species are also important in the subsistence diets of Alaskans, increasing the risk of direct bird-to-human exposure to Eurasian-origin AI virus. We contrast species-specific rates of intercontinental movements with the importance of each species in Alaskan diets to understand the relative risk of these taxa to humans. Greater scaup (Aythya marila), mallard (Anas platyrhynchos), and northern pintail (Anas acuta) were the top three species presenting the highest risks for intercontinental AI movement both within the natural system and through exposure to subsistence hunters. These directly comparable, species-based intercontinental movement rates and relative risk rankings should help in modeling, monitoring, and mitigating the impacts of intercontinental host and AI movements.

genomics↗

bioRxiv2021

Population genomics indicate three different modes of divergence and speciation with gene flow in the green-winged teal duck complex

The processes leading to divergence and speciation can differ broadly among taxa with different life histories. We examine these processes in a small clade of ducks with historically uncertain relationships and species limits. The green-winged teal (Anas crecca) complex is a Holarctic species of dabbling duck currently categorized as three subspecies (Anas crecca crecca, A. c. nimia, and A. c. carolinensis) with a close relative, the yellow-billed teal (Anas flavirostris) from South America. We examined divergence and speciation patterns in this group, determining their phylogenetic relationships and the presence and levels of gene flow among lineages using both mitochondrial and genome-wide nuclear DNA obtained from 1,393 ultraconserved element (UCE) loci. Phylogenetic relationships using nuclear DNA among these taxa showed A. c. crecca, A. c. nimia, and A. c. carolinensis clustering together to form one polytomous clade, with A.flavirostris sister to this clade. This relationship can be summarized as (crecca, nimia, carolinensis)(flavirostris). However, whole mitogenomes revealed a different phylogeny: (crecca, nimia)(carolinensis, flavirostris). The best demographic model for key pairwise comparisons supported divergence with gene flow as the probable speciation mechanism in all three contrasts (crecca-nimia, crecca-carolinensis, and carolinensis-flavirostris). Given prior work, gene flow was expected among the Holarctic taxa, but gene flow between North American carolinensis and South American flavirostris (M [~]0.1 - 0.4 individuals/generation), albeit low, was not expected. Three geographically oriented modes of divergence are likely involved in the diversification of this complex: heteropatric (crecca-nimia), parapatric (crecca-carolinensis), and (mostly) allopatric (carolinensis-flavirostris). Ultraconserved elements are a powerful tool for simultaneously studying systematics and population genomics in systems like this. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/459850v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@e476ddorg.highwire.dtl.DTLVardef@137c666org.highwire.dtl.DTLVardef@c270e9org.highwire.dtl.DTLVardef@182f757_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2020

An empirical examination of sample size effects on population demographic estimates in birds using single nucleotide polymorphism (SNP) data

Sample size is a critical aspect of study design in population genomics research, yet few empirical studies have examined the impacts of small sample sizes. We used datasets from eight diverging bird lineages to make pairwise comparisons at different levels of taxonomic divergence (populations, subspecies, and species). Our data are from loci linked to ultraconserved elements (UCEs) and our analyses used one SNP per locus. All individuals were genotyped at all loci (McLaughlin et al. 2020). We estimated population demographic parameters (effective population size, migration rate, and time since divergence) in a coalescent framework using Diffusion Approximation for Demographic Inference ({delta}a{delta}i; Gutenkunst et al. 2009), an allele frequency spectrum (AFS) method. Using divergence-with-gene-flow models optimized with full datasets, we subsampled at sequentially smaller sample sizes from full datasets of 6 - 8 diploid individuals per population (with both alleles called) down to 1:1, and then we compared estimates and their changes in accuracy. Accuracy was strongly affected by sample size, with considerable differences among estimated parameters and among lineages. Effective population size parameters ({nu}) tended to be underestimated at low sample sizes (fewer than 3 diploid individuals per population, or 6:6 haplotypes in coalescent terms). Migration (m) was fairly consistently estimated until [≤] 2 individuals per population, and no consistent trend of over- or underestimation was found in either time since divergence (T) or{Theta} (4Nref). Lineages that were taxonomically recognized above the population level (subspecies and species pairs; i.e., deeper divergences) tended to have lower variation in scaled root mean square error (SMRSE) of parameter estimation at smaller sample sizes than population-level divergences, and many parameters were estimated accurately down to 3 diploid individuals per population. Shallower divergence levels (i.e., populations) often required at least 5 individuals per population for reliable demographic inferences using this approach. Although divergence levels might be unknown at the outset of study design, our results provide a framework for planning appropriate sampling and for interpreting results if smaller sample sizes must be used.

genomics↗