A few quick updates on introgress and bgc.

CRAN dropped introgress. I moved it to GitHub. You can now install it as follows:

install.packages("devtools")
library(devtools)
install_github("zgompert/introgress")

bgc is also now on GitHub and is undergoing development. I plan to release a new bgc R package that will include some of the plotting functions from introgress in May or June of this year (2023).

The links on my software page should now be for the GitHub versions of both software packages.

The Gompert lab in the Department of Biology at Utah State University (USU) is seeking a highly motivated and enthusiastic PhD student with interests in forecasting ecological and evolutionary processes from time-series data. Research in the lab addresses a range of fundamental questions in ecology and evolutionary biology. We are particularly interested in the ecological causes and evolutionary consequences of natural selection, the causes and consequences of genetic variation in the wild, the role of hybridization in evolution, and the nature and evolution of species boundaries and barriers to gene flow. This specific position is funded through a NSF LTREB award to Zach Gompert (and collaborator Matt Forister at the University of Nevada). A stipend will be provided via a mixture of teaching and research assistantships. Review of applicants will begin November 1, 2021. The start date for the PhD project is fall 2022.

Project Overview: The history of life on Earth has many periods of mass extinction, when many species cease to exist. These periods are usually studied through use of fossils. Although fossils have revealed a lot about extinction, they’ve been unable to solve the basic riddle of why some species go extinct and others seem unaffected. Humans are now witnessing a mass extinction event, which provides biologists an opportunity to study in real time how species differ in their responses to climate change and other stressors. Some may go extinct within our lifetimes; others won’t. This project builds on one of North America’s longest-running studies of (butterfly) insect populations by continuing data collection at five sites in the Sierra Nevada Mountains of Northern California. Encompassing more than 150 species of butterflies, this NSF funded LTREB project will explore habitat use by both butterflies and caterpillars to better understand climate impacts on insect populations. Of particular interest is the role of extreme droughts, which are affecting the western United States with increasing frequency. Results from the project will inform our understanding of ongoing insect and pollinator declines.

Specific Responsibilities: We are looking for a PhD student interested in collaborating on the project. Specifically, the PhD student will use computational methods, including hierarchical Bayesian models and neural networks, to make predictions about future butterfly population demographics while accounting for uncertainty in future climate and possible effects of adaptive evolutionary change. The student will be tasked with maintaining a website making forecasts available to the public. Additional components of the PhD student’s dissertation will be tailored to the student’s interests and background. Possible projects could make connections to Gompert’s funded work on contemporary evolution and fluctuating selection in Lycaeides butterflies, but this is not required. The student will have the opportunity to visit the field sites, but collecting the butterfly count data is not a key part of the student’s project.

The successful candidate should have previous training in ecology, evolutionary biology, population genetics, applied math and statistics, or computational biology. Some proficiency with programming (e.g., moderate comfort with R, C, java, perl, or python) is desirable. Experience working with climate models or ecological forecasting would be an asset, but is not essential. Students with or without a Master’s degree are encouraged to apply. We welcome and encourage enthusiastic and open-minded applicants from any nation, ethnicity, gender, sexual orientation or socioeconomic class. For more information about the Gompert lab, including a statement of mentoring philosophy and expectations, please visit the lab website at https://gompertlab.com/.

USU is a public land-grant research university in Logan, Utah (USA). The Department of Biology and USU offer excellent opportunities for education, training, funding, and collaboration. Graduate students in the department have the option of pursuing a PhD in Biology or in the inter-departmental Ecology program. Located in the Rocky Mountains, the Logan area also offers exceptional opportunities for outdoor recreation.

Interested students should e-mail me (zach.gompert@usu.edu) with the following:

1. A cover letter describing the student’s background and training, goals and reasons for pursuing a PhD, and the specific reasons why this opportunity is of exceptional interest.
2. A CV, including contact information for three academic references.
3. A writing sample. This could be in the form of a published or draft manuscript, an undergraduate thesis, or some other substantial document that constitutes scientific writing.

Effective population size is a central parameter in population genetic models, which affects the efficacy of selection, rates of drift and diversity levels. When populations are subdivided into multiple demes connected by gene flow, evolution can depend on both the local (demic) and global (species) effective population size. In our new paper, now available from Molecular Ecology,we use population genomic data from multiple populations and generations to show that Northern blue butterfly (Lycaeides idas) populations experience sufficient gene flow to maintain high diversity levels (consistent with their global effective population size), but still experience high rates of evolution by drift (consistent with their local effective population sizes). Thus, we demonstrate that genome-wide change and the maintenance of diversity are driven largely by different processes, drift versus gene flow, and reflect dramatically different effective population sizes. As we discuss in this paper, these findings add further complexity to arguments about the use of genetic diversity metrics in conservation biology and might shed light on longstanding questions concerning the determinants of diversity levels in nature (i.e., Lewontin’s paradox).

I am excited to announce that my (collaborative) NSF LTREB project on predicting the success of montane (butterfly) species in an era of climatic upheaval has been funded. This project builds on a long-term data set generated by Art Shapiro at UC Davis and is a collaborative project with Matt Forister at the University of Nevada. I will be advertising soon for a PhD student to work on this project starting fall 2022. The award abstract follows:

The history of life on Earth has many periods of mass extinction, when many species cease to exist. These periods are usually studied through use of fossils. Although fossils have revealed a lot about extinction, they’ve been unable to solve the basic riddle of why some species go extinct and others seem unaffected. Humans are now witnessing a mass extinction event, which provides ecologists an opportunity to study in real time how species differ in their responses to climate change and other stressors. Some may go extinct within our lifetimes; others won’t. This project builds on one of North America’s longest-running studies of insect populations by continuing data collection at five sites in the Sierra Nevada Mountains of Northern California. Encompassing more than 150 species of butterflies, the project will explore habitat use by both butterflies and caterpillars to better understand climate impacts on insect populations. Of particular interest is the role of extreme droughts, which are affecting the western United States with increasing frequency. Results from the project will inform our understanding of ongoing insect and pollinator declines. Scientists will engage the public through a novel forecasting website and by involvement of local school groups in activities, including the creation of larger-than-life biological models of common species.

This project extends nearly five decades of observations in a dynamic system that has played an important role in our understanding of insects in the Anthropocene. Previous work with this long-term data has suggested that the impacts of climate change (particularly warming and drying trends) might be as important as the effects of habitat loss and degradation through pesticide accumulation and other processes. In this project, researchers investigate the role of montane environments as refugia during periods of climatic upheaval. In addition to continuing core data collection (biweekly presence/absence surveys), new information will be gathered on trophic networks and the response of insect populations to shifting climatic conditions mediated through plant resources (nectar sources in particular). Multiple types of observational data will be integrated into a statistical modeling framework that emphasizes forecasting with climatic uncertainty, and which will be validated on an annual basis through real-time forecasts updated within and among field seasons. Outcomes from this project will include inter-disciplinary tools for prediction with heterogeneous data sources, as well as advances on ecological theories of animals interacting with topographic complexity while responding to novel climatic conditions.

Check out our recent opinion piece in Science where we argue that speciation often involves genetic differentiation at many loci (genes) across the genome. This likely occurs because the effects of natural selection can be coupled across statistically correlated genes, such that selection on one locus spills over to other correlated loci. Thus, one key to understanding the speciation process is understanding the processes by which genes and traits become coupled and cause a transition from polymorphism within a population to geographic variation to genome-wide differentiation and distinct species.

We are excited to welcome two new lab members this fall.

Linyi Zhang is a new postdoc in the lab. She completed her PhD with Scott Egan at Rice. She is broadly interested in adaptation and speciation, and her past work focused on how divergent host use promotes reproductive isolation among sympatric populations of gall wasps. She is currently combing genome-wide association mapping and whole genome sequencing of natural butterfly populations to determine the causes and consequences of (potentially) fluctuating selection on polygenic traits.

Brian Kissmer began his PhD in the lab this fall. He is interested how the nature and repeatability of adaptation depends on the degree to which a population is maladapted to a novel environment. He is initially addressing this question using experimental evolution in Callosobruchus maculatus seed beetles.

Theory indicates that non-linear selection (e.g., stabilizing, disruptive, or correlational selection) on traits can result in epsitasis for fitness even when alleles have additive affects on traits. In a paper recently published in Nature Ecology and Evolution, we demonstrate this in a field experiment with Timema stick insects. In particular, we show that color is determined mostly by alleles with additive effects, but that selection for crypsis favors color combinations resulting in epistasis for fitness. This in turn results in a rugged fitness landscape with respect to the color loci.

See our blog post for more thoughts and background on the paper.

Timema petita (photo by R. Villoutreix)

In a new paper in Science we show how a large-scale (1 million base pair) deletion converts a continuum of body colors into discrete color morhps, and thereby likely increases crypsis in Timema stick insects. This deletion is also the breakpoint of an inversion, and thus our work shows that inversions can affect evolution in ways other than by suppressing recombination, that is by directly causing major mutations. More generally, this paper demonstrates a way that gene complexes can be packaged into (semi) discrete units of diversity, which has implications for understanding the evolution of other units such as sexes and species.

You can read more about the paper on EurkaAlert and the EcoEvo blog.

Arguably, research in speciation has focused more on how the process begins, that is, how the first barriers evolve, than on the later stages of the speciation process (i.e., the evolution of [nearly] complete reproductive isolation). A recent special issue in Philosophical Transactions of the Royal Society B seeks to partially rectify this issue. We analyze this issue in the context of host shifts in Timema stick insects. In particular, in an article in this special issue we show that host shifts to closely related plant species are common, but cause only weak reproductive isolation. In contrast, much rarer host shifts from flowering plants to gymnosperms generate strong reproductive isolation. Thus, such rare and difficult events might be important for generating fully isolated species.