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Harrigan, R. J.

Publications and source records attributed to Harrigan, R. J..

5 recordsLinked to original sources

Environmentally-mediated selection parallels population divergence across a chimpanzee subspecies contact zone

Species evolve from populations with ancestor-descendant relationships in a bifurcating process shaped by geography, gene flow, genetic drift, and natural selection leading to local adaptation to prevailing environmental and ecological conditions. Building on this foundational understanding, we explored local adaptation in chimpanzees (Pan troglodytes) at a key geographical intersection in Cameroon where the two main chimpanzee phylogenetic lineages converge. The Nigeria-Cameroon chimpanzee (P. t. ellioti) and central chimpanzee (P. t. troglodytes) last shared a common ancestor about 500 thousand years ago, with occasional gene flow between them. The evolutionary processes driving their prolonged separation are not fully understood, but neutral evolutionary mechanisms alone cannot account for the observed divergence pattern. Cameroon is often referred to as Africa in miniature because the Gulf of Guinea Forest, Congo Basin Forest, and savanna converge there, forming an ecotone. Thus, this contact zone between subspecies in Cameroon provides a unique natural laboratory that enabled us to investigate how environmental variation and natural selection shape divergence in chimpanzees. We developed a genome-wide panel of single-nucleotide polymorphisms (SNPs) in 112 wild chimpanzees sampled in multiple habitats across this contact zone. We augmented SNP discovery by sequencing eight new chimpanzee genomes from Cameroon and analyzing them with previously published chimpanzee genomes. We found that P. t. ellioti and P. t. troglodytes diverged from one another around 478,000 years ago and occasionally exchange migrants. We identified 1,690 unique SNPs across 905 genes associated with 31 environmental variables that describe the habitat. These genes are involved in essential biological processes, including immune response, neurological development, behavior, and dietary adaptations. This study highlights the importance of understanding the geographical context of natural selection, paving the way for future studies to interpret evidence for genetic variation with phenotypic traits and deepening our understanding of how populations diverge in response to environmental pressures. Author SummaryWe investigated how local adaptation contributes to shaping the diversification of chimpanzee subspecies at the geographical convergence point for the two major branches of the chimpanzee phylogenetic tree. We analyzed genome-wide SNP genotypes of 112 chimpanzees sampled from natural communities located in this understudied area. We used tiered methods that identified 905 genes subject to selection, each associated with one or more of 31 environmental predictors describing the habitat. We found strong signals of selection in immune response genes that separate P. t. troglodytes from P. t. ellioti, highlighting the important role of different pathogen histories in their evolution. We also found evidence of selection in genes associated with neurological development, behavior, and diet, that separate both the subspecies and populations of P. t. ellioti that occupy different niches. These findings suggest that ecological and cultural factors may also contribute to shaping the diversification of chimpanzees across the contact zone.

genomics↗

A highly contiguous genome assembly for the Yellow Warbler (Setophaga petechia)

The Yellow Warbler (Setophaga petechia) is a small songbird in the New World Warbler family (Parulidae) that exhibits phenotypic and ecological differences across a widespread distribution and is important to Californias riparian habitat conservation. Here, we present a high-quality de novo genome assembly of a vouchered female Yellow Warbler from southern California. Using HiFi long-read and Omni-C proximity sequencing technologies, we generated a 1.22 Gb assembly including 687 scaffolds with a contig N50 of 6.80 Mb, scaffold N50 of 21.18 Mb, and a BUSCO completeness score of 96.0%. This highly contiguous genome assembly provides an essential resource for understanding the history of gene flow, divergence, and local adaptation and can inform conservation management of this charismatic bird species.

evolutionary biology↗

From zero to infinity: minimum to maximum diversity of the planet by spatio-parametric Rao's quadratic entropy

AimThe majority of work done to gather information on Earth diversity has been carried out by in-situ data, with known issues related to epistemology (e.g., species determination and taxonomy), spatial uncertainty, logistics (time and costs), among others. An alternative way to gather information about spatial ecosystem variability is the use of satellite remote sensing. It works as a powerful tool for attaining rapid and standardized information. Several metrics used to calculate remotely sensed diversity of ecosystems are based on Shannons Information Theory, namely on the differences in relative abundance of pixel reflectances in a certain area. Additional metrics like the Raos quadratic entropy allow the use of spectral distance beside abundance, but they are point descriptors of diversity, namely they can account only for a part of the whole diversity continuum. The aim of this paper is thus to generalize the Raos quadratic entropy by proposing its parameterization for the first time. InnovationThe parametric Raos quadratic entropy, coded in R, i) allows to represent the whole continuum of potential diversity indices in one formula, and ii) starting from the Raos quadratic entropy, allows to explicitly make use of distances among pixel reflectance values, together with relative abundances. Main conclusionsThe proposed unifying measure is an integration between abundance- and distance-based algorithms to map the continuum of diversity given a satellite image at any spatial scale.

ecology↗

A Biodiversity Composition Map of California Derived from Environmental DNA Metabarcoding and Earth Observation

Unique ecosystems globally are under threat from ongoing anthropogenic environmental change. Effective conservation management requires more thorough biodiversity surveys that can reveal system-level patterns and that can be applied rapidly across space and time. We offer a way to use environmental DNA, community science and remote sensing together as methods to reduce the discrepancy between the magnitude of change and historical approaches to measure it. Taking advantages of modern ecological models, we integrate environmental DNA and Earth observations to evaluate regional biodiversity patterns for a snapshot of time, and provide critical community-level characterization. We collected 278 samples in Spring 2017 from coastal, shrub and lowland forest sites in California, a large-scale biodiversity hotspot. We applied gradient forest to model 915 family occurrences and community composition together with environmental variables and multi-scalar habitat classifications to produce a statewide biodiversity-based map. 16,118 taxonomic entries recovered were associated with environmental variables to test their predictive strength on alpha, beta, and zeta diversity. Local habitat classification was diagnostic of community composition, illuminating a characteristic of biodiversity hotspots. Using gradient forest models, environmental variables predicted 35% of the variance in eDNA patterns at the family level, with elevation, sand percentage, and greenness (NDVI32) as the top predictors. This predictive power was higher than we found in published literature at global scale. In addition to this indication of substantial environmental filtering, we also found a positive relationship between environmentally predicted families and their numbers of biotic interactions. In aggregate, these analyses showed that strong eDNA community-environment correlation is a general characteristic of temperate ecosystems, and may explain why communities easily destabilize under disturbances. Our study provides the first example of integrating citizen science based eDNA with biodiversity mapping across the tree of life, with promises to produce large scale, high resolution assessments that promote a more comprehensive and predictive understanding of the factors that influence biodiversity and enhance its maintenance.

ecology↗

Identifying Migrant Origins Using Genetics, Isotopes, and Habitat Suitability

O_LIIdentifying migratory connections across the annual cycle is important for studies of migrant ecology, evolution, and conservation. While recent studies have demonstrated the utility of high-resolution SNP-based genetic markers for identifying population-specific migratory patterns, the accuracy of this approach relative to other intrinsic tagging techniques has not yet been assessed.\nC_LIO_LIHere, using a straightforward application of Bayes' Rule, we develop a method for combining inferences from high-resolution genetic markers, stable isotopes, and habitat suitability models, to spatially infer the breeding origin of migrants captured anywhere along their migratory pathway. Using leave-one-out cross validation, we compare the accuracy of this combined approach with the accuracy attained using each source of data independently.\nC_LIO_LIOur results indicate that when each method is considered in isolation, the accuracy of genetic assignments far exceeded that of assignments based on stable isotopes or habitat suitability models. However, our joint assignment method consistently resulted in small, but informative increases in accuracy and did help to correct misassignments based on genetic data alone. We demonstrate the utility of the combined method by identifying previously undetectable patterns in the timing of migration in a North American migratory songbird, the Wilson's warbler.\nC_LIO_LIOverall, our results support the idea that while genetic data provides the most accurate method for tracking animals using intrinsic markers when each method is considered independently, there is value in combining all three methods. The resulting methods are provided as part of a new computationally-efficient R-package, GIAIH, allowing broad application of our statistical framework to other migratory animal systems.\nC_LI

ecology↗