Biology subjects

Warren, D. L.

Publications and source records attributed to Warren, D. L..

4 recordsLinked to original sources

bioRxiv2026

Molecular and ecological determinants of effective reassortment in orthohantaviruses

A central unsolved problem in RNA virus evolution is understanding why some viral reassortants establish and persist while others do not. To answer this question, we reconstructed reassortant histories across 553 viral genomes from seven orthohantavirus species between 1983 and 2024 using phylogenetic reconciliation and molecular dating. We found that the frequency of retained reassortants varied among orthohantaviruses. For example, reassortment ranged from absent in Andes virus to frequent in Dobrava-Belgrade, Sin Nombre, Seoul, Puumala, and Tula viruses, showing that effective reassortment is not a genus-wide constant. Our Bayesian hierarchical models identified local host overlap as the strongest ecological factor associated with viral reassortment, while cross-segment linkage and terminal RNA structure serve as a molecular filter. We found that the probability of reassortment establishment is highest when ecological opportunity is paired with molecular permissiveness, with their interaction term inferred as the strongest signal in our establishment models (posterior probability = 0.97). These results suggest that reassortment in orthohantaviruses is a sequentially filtered evolutionary process in which divergent lineages must first meet in a host through ecological overlap, exchange segments that are molecularly compatible, and do so within a lineage background permissive to establishment in the host population.

evolutionary biology↗

bioRxiv2022

Incorporating sampling bias into permutation tests for niche and distribution models

Randomization tests are often used with species niche and distribution models to estimate model performance, test hypotheses, and measure methodological biases. Many of these tests involve building null models representing the hypothesis that there is no association between the species occurrences and the environmental predictors, then comparing the empirical model to null distributions built from these models. These null models are commonly based on points randomly selected with a uniform probability from the study area. However, spatial sampling bias, a near-universal feature of the occurrence data used to build niche and distribution models, results in a non-uniform probability of observing species in different areas even when species occurrences are unrelated to environmental predictors. Failing to account for this bias in randomization tests results in null distributions that do not accurately represent the null hypothesis, potentially leading to incorrect conclusions. In this study, we use simulations to demonstrate that uniform sampling in randomization tests can lead to unacceptable rates of type I error and poor estimates of methodological bias when spatial sampling bias is present in the occurrence data. We present a new method that incorporates a bias estimate into replicate simulations for these randomization tests, and show that this adjustment can reduce type I error rates to an acceptable level.

ecology↗

bioRxiv2021

Reevaluating claims of ecological speciation in Halichoeres bivittatus

Understanding the role of ecological processes in speciation has become one of the most active areas of research in marine population biology in recent decades. The traditional view was that allopatry was the primary driver of speciation in marine taxa, but the geography of the marine environment and the dispersal capabilities of many marine organisms render this view somewhat questionable. One of the earliest and most highly cited empirical examples of ecological speciation with gene flow in marine fishes is that of the slippery dick wrasse, Halichoeres bivittatus. Evidence for this cryptic or incipient speciation event was primarily in the form of a deep north-south divergence in a single mitochondrial locus, combined with a finding that these two haplotypes were associated with different habitat types in the Florida Keys and Bermuda, where they overlap. Here we examine habitat assortment in the Florida Keys using a broader sampling of populations and habitat types than were available for the original study, and find no evidence to support the claim that haplotype frequencies differ between habitat types, and little evidence to support any differences between populations. These results severely undermine claims of ecological speciation with gene flow in Halichoeres bivittatus. We argue that future claims of this type should be supported by multiple lines of evidence that illuminate potential mechanisms and allow researchers to rule out alternative explanations for spatial patterns of genetic differences.

evolutionary biology↗

bioRxiv2019

Evaluating species distribution models with discrimination accuracy is uninformative for many applications

AimSpecies distribution models are used across evolution, ecology, conservation, and epidemiology to make critical decisions and study biological phenomena, often in cases where experimental approaches are intractable. Choices regarding optimal models, methods, and data are typically made based on discrimination accuracy: a models ability to predict subsets of species occurrence data that were withheld during model construction. However, empirical applications of these models often involve making biological inferences based on continuous estimates of relative habitat suitability as a function of environmental predictor variables. We term the reliability of these biological inferences \"functional accuracy.\" We explore the link between discrimination accuracy and functional accuracy.\n\nMethodsUsing a simulation approach we investigate whether models that make good predictions of species distributions correctly infer the underlying relationship between environmental predictors and the suitability of habitat.\n\nResultsWe demonstrate that discrimination accuracy is only informative when models are simple and similar in structure to the true niche, or when data partitioning is geographically structured. However, the utility of discrimination accuracy for selecting models with high functional accuracy was low in all cases.\n\nMain conclusionsThese results suggest that many empirical studies and decisions are based on criteria that are unrelated to models usefulness for their intended purpose. We argue that empirical modeling studies need to place significantly more emphasis on biological insight into the plausibility of models, and that the current approach of maximizing discrimination accuracy at the expense of other considerations is detrimental to both the empirical and methodological literature in this active field. Finally, we argue that future development of the field must include an increased emphasis on simulation; methodological studies based on ability to predict withheld occurrence data may be largely uninformative about best practices for applications where interpretation of models relies on estimating ecological processes, and will unduly penalize more biologically informative modeling approaches.

ecology↗