Biology subjects

Provost, K. L.

Publications and source records attributed to Provost, K. L..

10 recordsLinked to original sources

bioRxiv2026

Lark Sparrows have Ecogeographic Song Variation across North America

Machine learning models can be used to analyze large bioacoustics datasets and explore variation due to geography or habitat. We find that in the monotypic Lark Sparrow (Chondestes grammacus), both environmental variables and geographic distance influence song variation in this species. Bird song is an important method of communication within avian species. The variation in bird song within a species can be due to a variety of factors, including genetic drift and isolation by distance. However, it remains unclear in species with wide ranges how environmental factors in particular can cause changes to the song. In this study, the song C. grammacus was analyzed via machine learning to determine if it had significant variation based on multiple geographical metrics. We trained a convolutional neural network to segment individual syllables of 91 C. grammacus recordings, then extracted song characteristics. We found that ecoregion and state explain variation in C. grammacus songs. Our results demonstrate the efficacy of using machine learning models to analyze large datasets, as well as the impact that ecogeographic variation has on song variance.

evolutionary biology↗

bioRxiv2026

subsppLabelR: a wrapper package in R to automatically label and filter subspecies occurrence data

O_LIOccurrence data is the basis for many fundamental ecoevolutionary analyses, and many ways of filtering them to be robust enough for analysis have been developed. One issue that still remains is separating out the boundaries of taxa, especially taxa below the species level which often have vague definitions. C_LIO_LIsubsppLabelR is an R package that uses labeled data on taxa to automatically define boundaries between them, with various levels of uncertainty. I tested the features of the package on three species of bird that vary in the number and location of subspecies, as well as one sister-species pair with a known overlap in their distribution. I then used existing ecological niche modeling software to compare and contrast their niche space. C_LIO_LIsubsppLabelR performs well in scenarios where subspecies are well-sampled and cover large geographic areas, but rare or highly endemic subspecies are difficult to resolve without further input. C_LIO_LIThis package serves to automatically define geographic boundaries of taxa, identifying any sympatric overlaps, and provides an alternate way to clean occurrence data for ecological and evolutionary analyses. C_LI Data/Code for peer review statementCode and data are available with peer review. Raw Data and the package are available as .ZIP files as well as an R script.

ecology↗

bioRxiv2024

Bats of a feather: Range characteristics and wing morphology predict phylogeographic breaks in volant vertebrates

Intraspecific genetic variation and phylogeographic structure can be influenced by factors such as landscape features, environmental gradients, historical biogeography, and organismal traits such as dispersal ability. Since deep genetic structure is often considered a precursor to speciation, identifying the factors that are associated with genetic structure can contribute to a greater understanding about diversification. Here, we use repurposed data to perform a global analysis of volant vertebrates (i.e., bats and birds) to estimate where intraspecific phylogeographic breaks occur and identify the factors that are important predictors of these breaks. We estimate phylogeographic breaks using Monmoniers maximum difference barrier algorithm and conduct a Random Forests analysis using the presence of a phylogeographic break as a response variable. In bats, phylogeographic breaks are concentrated in biodiversity hotspots while breaks estimated in bird species are more widespread across temperate and tropical zones. However, for both clades geographical features such as maximum latitude, measures of wing morphology, and organismal traits associated with feeding ecology were found to be important predictors of phylogeographic breaks. Our analysis identifies geographical areas as wells as suites of organismal traits that could serve as a starting point for more detailed studies of biodiversity processes.

evolutionary biology↗

bioRxiv2023

Evolution in action: Brown-headed Cowbirds (Molothrus ater) adapt songs to 50 years of Ohio urbanization

Technological advances in the last century have allowed humans to rapidly alter the landscape, resulting in a global loss of biodiversity. Of such alterations, is the conversion of rural land into urban space. In birds, urbanization has been found to impact song to facilitate improved auditory communication between conspecifics in areas with increased background noise. Given that birdsong is an important reproductive behavior, it is possible that urbanization promotes the evolution of birdsong through differences in fitness between individuals in urban acoustic environments. Here, we investigated if urbanization across Ohio impacts song characteristics of Brown-headed Cowbirds (Molothrus ater), a brood parasite associated with cropland and other altered habitats. To assess change in M. ater song over space and time, we compared syllable shape and syllable properties with metrics of urbanization. It was found that M. ater song differs significantly across geographic space and time, and is associated with changes in urbanization. Cowbird song of conspecifics in preferred habitat, such as cropland, demonstrates different syllable shape than conspecifics in urban space. This suggests that urbanization could facilitate change in M. ater song over time. These results provide additional insight into how anthropogenic habitat alteration facilitates cultural evolution in birds, and allows for increased understanding of how human behavior contributes to altered ecological interactions.

evolutionary biology↗

bioRxiv2023

Environmental factors and cultural drift influence song evolution in New World Sparrows

Variation in bird song is often assumed to be determined by sexual selection, rather than natural selection. However, most investigations to date have drawn their conclusions from a handful of species due to the challenges with manually processing sound data. Here, we use deep machine learning to investigate nearly all species of New World Sparrows. We leverage existing data to identify the processes that structure variation in bird song and to determine how this variation corresponds to patterns in genes and traits. Song variation in ~40% of species can be explained by environment, geography, and time. Across a community and global scale, the action of natural selection on the evolution of song is at least as impactful as it is on other genetically-determined traits.

evolutionary biology↗

bioRxiv2023

Dialect differences correlate with environment in migratory coastal White-crowned Sparrows

Vocalization behavior in birds, especially songs, strongly affects reproduction, but it is also highly impacted by geographic distance, climate, and time. For this reason, phenotypic differences in vocalizations between different bird populations are often interpreted as evidence of lineage divergence. Previous work has demonstrated that there is extensive variation in the songs of White-crowned Sparrow (Zonotrichia leucophrys) throughout the species range, including between neighboring (and genetically distinct) subspecies Z. l. nuttalli and Z. l. pugetensis. However, it is unknown whether the divergence in their songs correlates to environmental or geographical factors. Previous work has been hindered by time-consuming traditional methods to study bird songs that rely on the manual annotation of song spectrograms into individual syllables. Here we explore the performance of automated machine learning methods of song annotation, which can process large datasets more efficiently, paying attention to the question of subspecies differences. We utilize a recently published artificial neural network to automatically annotate hundreds of White-crowned Sparrow vocalizations across two subspecies. By analyzing differences in syllable usage and composition, we find that Z. l. nuttalli and Z. l. pugetensis have significantly different songs. Our results are consistent with the interpretation that these differences are caused by the changes in syllables in the White-crowned Sparrow repertoire. However, the large sample size enabled by the AI approach allows us to demonstrate that divergence in song is correlated with environmental difference and migratory status, but not with geographical distance. Our findings support the hypothesis that the evolution of vocalization behavior is affected by environment, in addition to population structure. LAY SUMMARYO_LIBirdsong is an important behavior because it is important in bird communication and reproduction. C_LIO_LIWhite-crowned Sparrows in western North America are known to use different songs along their range, but it is unknown if those songs vary due to the environment. C_LIO_LIWe used machine learning to analyze these songs and found that populations of White-crowned Sparrows can be differentiated based on their songs. C_LIO_LIEnvironmental factors during the breeding season exert a greater influence on song evolution in migratory subspecies. C_LI

evolutionary biology↗

bioRxiv2022

The genomic landscapes of desert birds are structured by contemporary features

Spatial models show that genetic differentiation between populations can be explained by factors ranging from geographic distance to environmental resistance across the landscape. However, genomes exhibit a landscape of differentiation, which could indicate that multiple spatial models better explain divergence in different portions of the genome. We test whether alternative geographic predictors of intraspecific differentiation vary across the genome in ten bird species that co-occur in Sonoran and Chihuahuan Deserts of North America. Using population-level genomic data, we characterized the genomic landscapes across species and modeled five predictors that represented historical and contemporary mechanisms. The characteristics of genomic landscapes differed across the ten species, influenced by varying levels of population structuring and admixture between deserts. General dissimilarity matrix modeling indicated that the best-fit models differed from the whole genome and partitions along the genome. Almost all of the historical and contemporary mechanisms were important in explaining genetic distance, but particularly historical and contemporary environment, while contemporary abundance, position of the barrier to gene flow, and distance explained relatively less. Individual species have significantly different patterns of genomic variation. These results illustrate that the genomic landscape of differentiation was influenced by alternative geographic factors operating on different portions of the genome.

evolutionary biology↗

bioRxiv2022

The impacts of transfer learning, phylogenetic distance, and sample size on big-data bioacoustics

Vocalizations in animals, particularly birds, are critically important behaviors that influence their reproductive fitness. While recordings of bioacoustic data have been captured and stored in collections for decades, the automated extraction of data from these recordings has only recently been facilitated by artificial intelligence methods. These have yet to be evaluated with respect to accuracy of different automation strategies and features. Here, we use a recently published machine learning framework to extract syllables from ten bird species ranging in their phylogenetic relatedness from 1 to 85 million years, to compare how phylogenetic relatedness influences accuracy. We also evaluate the utility of applying trained models to novel species. Our results indicate that model performance is best on conspecifics, with accuracy progressively decreasing as phylogenetic distance increases between taxa. However, we also find that the application of models trained on multiple distantly related species can improve the overall accuracy to levels near that of training and analyzing a model on the same species. When planning big-data bioacoustics studies, care must be taken in sample design to maximize sample size and minimize human labor without sacrificing accuracy.

evolutionary biology↗

bioRxiv2020

Comparative phylogeography reveals how a barrier filters and structures taxa in North American warm deserts

The study of biogeographic barriers have been instrumental in understanding the evolution and distribution of taxa. Now with the increased availability of empirical datasets, it is possible to infer emergent patterns from communities by synthesizing how barriers filter and structure populations across species. We assemble phylogeographic data for a barrier and perform spatially-explicit simulations to quantify temporal and spatial patterns of divergence, the influence of species traits on these patterns, and understand the statistical power of differentiating alternative diversification modes. We incorporate published datasets to examine taxa around the Cochise Filter Barrier, separating the Sonoran and Chihuahuan deserts of North America, to synthesize phylogeographic structuring across the community with respect to organismal functional traits. We then use a simulation and machine learning pipeline to assess the power of phylogeographic model selection. Taxa distributed across the Cochise Filter Barrier show heterogeneous responses to the barrier in levels of gene flow, phylogeographic structure, divergence timing, barrier width, and divergence mechanism. These responses vary concordantly with locomotor and thermoregulatory traits. Many taxa show a Pleistocene population genetic break, often with introgression after divergence. Allopatric isolation and isolation-by-environment are the primary mechanisms purported to structure taxa. Simulations reveal that in spatially-explicit isolation-with-migration models across the barrier, age of divergence, presence of gene flow, and presence of isolation-by-distance can confound the interpretation of evolutionary history and model selection by producing easily-confusable results. By synthesizing phylogeographic data for the Cochise Filter Barrier we show a pattern where barriers interact with species traits to differentiate taxa in communities over millions of years. Identifying the modes of differentiation across the barriers for these taxa remains challenging because commonly invoked demographic models may not be identifiable across a range of likely parameter space.

evolutionary biology↗

bioRxiv2018

Genomic divergence in allopatric Northern Cardinals of the North American warm deserts is associated with behavioral differentiation

Biogeographic barriers are thought to be important in initiating speciation through geographic isolation, but they rarely indiscriminately and completely reduce gene flow across the entire community. Understanding which species attributes regulate a barrier could help elucidate how speciation is initiated. Here, we investigated the association of behavioral isolation on population differentiation in Northern Cardinals (Cardinalis cardinalis) distributed across the Cochise Filter Barrier, a region of transitional habitat which separates the Sonoran and Chihuahuan deserts. Using genome-wide markers, we modeled demographic history by fitting the data to isolation and isolation-with-migration models. The best-fit model indicated that desert populations diverged in the mid-Pleistocene and there has been historically low, unidirectional gene flow into the Sonoran Desert. We then tested song recognition using reciprocal call-broadcast experiments to compare song recognition between deserts, controlling for song dialect changes within deserts. We found that male Northern Cardinals in both deserts were most aggressive to local songs and failed to recognize across-barrier songs. A correlation of genomic differentiation despite historic introgression and strong song discrimination is consistent with a model where speciation is initiated across a barrier and maintained by behavioral isolation.

evolutionary biology↗