Biology subjects

Hickerson, M. J.

Publications and source records attributed to Hickerson, M. J..

5 recordsLinked to original sources

bioRxiv2022

Global determinants of the distribution of insect genetic diversity

Understanding global patterns of genetic diversity (GD) is essential for describing, monitoring, and preserving life on Earth. To date, efforts to map macrogenetic patterns have been restricted to vertebrates, which comprise only a small fraction of Earths biodiversity. Here, we construct the first global map of predicted insect mitochondrial (COI) GD, derived from publicly available data. We calculate the mitochondrial GD mean (GDM) and evenness (GDE) of insect assemblages across the globe, identify their environmental correlates, and make predictions of mitochondrial GD levels in unsampled areas based on environmental data. Using the largest single-locus genetic dataset yet assembled, we find that mitochondrial GDE follows a quadratic latitudinal gradient peaking in the subtropics. Both mitochondrial GDM and GDE positively correlate with seasonally hot temperatures, as well as climate stability since the last glacial maximum. Our models explain 27.9% and 24.0% of the observed variation in mitochondrial GDM and GDE in insects, respectively, making an important step towards understanding global biodiversity patterns in the most diverse animal taxon.

evolutionary biology↗

bioRxiv2020

A unified model of species abundance, genetic diversity, and functional diversity revealsthe mechanisms structuring ecological communities

Biodiversity accumulates hierarchically by means of ecological and evolutionary processes and feedbacks. Reconciling the relative importance of these processes is hindered by current theory, which tends to focus on a single spatial, temporal or taxonomic scale. We introduce a mechanistic model of community assembly, rooted in classic island biogeography theory, which makes temporally explicit joint predictions across three biodiversity data axes: i) species richness and abundances; ii) population genetic diversities; and iii) trait variation in a phylogenetic context. We demonstrate that each data axis captures information at different timescales, and that integrating these axes enables discriminating among previously unidentifiable community assembly models. We combine our massive eco-evolutionary synthesis simulations (MESS) with supervised machine learning to fit the parameters of the model to real data and infer processes underlying how biodiversity accumulates, using communities of tropical trees, arthropods, and gastropods as case studies that span a range of spatial scales.

evolutionary biology↗

bioRxiv2018

An integrated model of population genetics and community ecology

AimQuantifying abundance distributions is critical for understanding both how communities assemble, and how community structure varies through time and space, yet estimating abundances requires considerable investment in field work. Community-level population genetic data potentially offer a powerful way to indirectly infer richness, abundance, and the history of accumulation of biodiversity within a community. Here we introduce a joint model linking neutral community assembly and comparative phylogeography to generate both community-level richness, abundance and genetic variation under a neutral model, capturing both equilibrium and non-equilibrium dynamics.\n\nLocationGlobal.\n\nMethodsOur model combines a forward-time individual-based community assembly process with a rescaled backward-time neutral coalescent model of multi-taxa population genetics. We explore general dynamics of genetic and abundance-based summary statistics and use approximate Bayesian computation (ABC) to estimate parameters underlying the model of island community assembly. Finally, we demonstrate two applications of the model using community-scale mtDNA sequence data and densely sampled abundances of an arachnid community on La Reunion. First, we use genetic data alone to estimate a summary of the abundance distribution, ground-truthing this against the observed abundances. Then we jointly use the observed genetic data and abundances to estimate the proximity of the community to equilibrium.\n\nResultsSimulation experiments of our ABC procedure demonstrate that coupling abundance with genetic data leads to improved accuracy and precision of model parameter estimates compared with using abundance-only data. We further demonstrate reasonable precision and accuracy in estimating a metric underlying the shape of the abundance distribution, temporal progress toward local equilibrium, and several key parameters of the community assembly process. For the insular arachnid assemblage, we find the joint distribution of genetic diversity and abundance approaches equilibrium expectations, and that the Shannon entropy of the observed abundances can be estimated using genetic data alone.\n\nMain ConclusionsThe framework that we present unifies neutral community assembly and comparative phylogeography to characterize the community-level distribution of both abundance and genetic variation through time, providing a resource that should greatly enhance understanding of both the processes structuring ecological communities and the associated aggregate demographic histories.

evolutionary biology↗

bioRxiv2018

Detecting spatial dynamics of range expansions with geo-referenced genome-wide SNP data and the geographic spectrum of shared alleles

Uncovering the spatial dynamics of range expansions is a major goal in studies of historical demographic inference, with applications ranging from understanding the evolutionary origins of domesticated crops, epidemiology, invasive species, and understanding specieslevel responses to climate change. Following the surge in advances that make explicit use of the spatial distribution of genetic data from georeferenced SNP variants, we present a novel summary statistic vector, the geographic spectrum of shared alleles (GSSA). Using simulations of twodimensional serial expansion, we find that the information from the GSSA, summarized with Harpendings Raggedness Index (RI), can accurately detect the spatial origins of a range expansion under serial founder models, even with sparse sampling of only ten individuals. When applying to SNP data from two species of the holarctic butterfly genus Lycaeides, the suggested origins of expansion are consistent with hindcasts obtained from ecological niche models (ENMs). These results demonstrate the GSSA to be a useful exploratory tool for generating hypotheses of range expansion with genomewide SNP data. Our simulation experiments suggest high performance even with sampling found in studies of nonmodel organisms (one sampled individual per location, no outgroup information, and only 5,000 SNP loci).

evolutionary biology↗

bioRxiv2018

Climate explains recent population divergence, introgression and persistence in tropical mountains: phylogenomic evidence from Atlantic Forest warbling finches

Taxa with disjunct distributions are common in montane biotas and offer excellent opportunities to investigate historical processes underlying genetic and phenotypic divergence. In this context, subgenomic datasets offer novel opportunities to explore historical demography in detail, which is key to better understand the origins and maintenance of diversity in montane regions. Here we used a large ultraconserved elements dataset to get insights into the main biogeographic processes driving the evolution of the Montane Atlantic Forest biota. Specifically, we studied two species of warbling finches disjunctly distributed across a region of complex geological and environmental history. We found that a scenario of three genetically differentiated populations is best supported by genomic clustering methods. Also, demographic simulations support simultaneous isolation of these populations at ~10 kya, relatively stable population sizes over recent time, and recent gene flow. Our results suggest a dual role of climate: population divergence, mediated by isolation in mountain tops during warm periods, as well as population maintenance - allowing persistence mediated by shifts in elevation distribution during periods of climate change, with episodic bouts contact and gene flow. Additional support for the role of climate comes from evidence of their contact in a recent past. We propose that two major gaps, which we call Sao Paulo and Caparao subtropical gaps, have been historically important in the divergence of cold adapted organisms in the Atlantic Forest, and could be associated to cryptic diversity. Finally, our results suggest that shallow divergence and past gene flow may be common in montane organisms, but complex demographic histories may be detectable only when using subgenomic or genomic datasets.

evolutionary biology↗