Reproductive Isolation in the Genus Pinus
You have reached the project homepage for the following NSF-funded project:
Principal Investigator: Andrew J. Eckert (VCU)
Project Partners: Jill Wegrzyn (UConn) & Jeffrey Ross-Ibarra (UCD)
Project Identifier: NSF-DEB-2423013
Active Period: 09/01/2024 - 08/31/2027 (36 months)
This site will be populated with project outputs, including data, scripts, and publications as they become available. If you have questions, please reach out to the PI (aeckert2@vcu.edu).
Project Summary
Species represent the basic units by which biodiversity is quantified. It is thus paramount to understand the processes affecting the formation of new species, especially as accelerated environmental change threatens numerous species with extinction. A key component to the formation of new species is the development of reproductive isolation (RI), defined as the reduction and eventual cessation of gene flow across diverging populations. Despite more than a century of research into the the ecological, genetic, and developmental drivers of speciation across diverse organisms, there remains gaps in our collective knowledge regarding the relative roles of adaptation and demography to the formation of reproductive isolation. This project attempts to fill these gaps for pines, a group of ecologically dominant and economically important temperate plants displaying enormously variable levels of reproductive isolation. Filling these gaps is crucial to ensure the long-term survival of pines as changes to their habitats continue to accelerate. As such, the next generation of forest scientists must be diverse, multidisciplinary, and well trained. This project will capitalize on VCU’s status as a minority serving institution to train the next generation of diverse forest scientists in cutting edge methodologies, develop teaching modules about pine and tree diversity for local elementary schools, and expand existing resources and training for forest managers to better understand the role of hybridization (i.e., the lack of reproductive isolation) during population-level responses to changing environments.
The relative roles of demography and adaptation to standing levels of reproductive isolation for pines will be quantified using a two-tiered combination of phylogenetics, genomics, demographic inference, and landscape genomics. First, phylogenetically informed meta-analyses will relate interspecific crossing rates to climate niche similarities (adaptation surrogate) and range size (demography surrogate) across the entire genus. Existing data suggest that each predictor significantly affects reproductive isolation for pines. Second, exon-based, pull-down sequencing of tens of thousands of genic regions in a reduced set of species will be used to test the hypothesis that climate adaptation and accumulation of deleterious genetic load within species as a function of demographic history are the primary determinants of crossing rate variability for pines. These efforts capitalize on the unique biology of pines (e.g., large genome size, rapid decay of linkage disequilibrium, polyembryony) relative to other well-studied plant systems and will provide foundational information for further comparative studies across long-lived plants.
Project Activities
The project is divided into two tiers. The first tier (Tier 1) is a literature review addressing the preponderance of hybridization within the genus Pinus. This includes analyses linking the degree of hybridization, also referred to as the ability cross, to evolutionary history, climate adaptation, and demography. The second tier (Tier 2) will generate new data for the southeastern hard pines to test the role of deleterious genetic variation, also referred to as genetic load, and a adaptive genetic variation to extant patterns of hybridization. Note, the degree of hybridization is an inverse measure of reproductive isolation.
Tier 1 Activities & Outputs
These activities rely solely on published and archived data sources from peer-reviewed journals, government reports, and government agencies. Data and associated scripts will be released here, with the original source for the data noted in the released documents. As noted above, these activities rely on four sources of data: crossing rates, evolutionary history, climate adaptation, and demography. For these data, crossing rates are the response variable while all others are explanatory variables.
NOTE: This site is under construction. Items will be added and updated as they are finished.
Explanatory Variables
There are three explanatory variables in this portion of the project: evolutionary history, climate adaptation, and demography.
Evolutionary History
Evolutionary history is represented as pairwise divergence times in millions of years ago (mya) extracted from two published studies: Jin et al. (2021) and Saladin et al. (2017). The data, R script, and a summary of the results from the R script, can be obtained from the following links:
Data: The data are phylogenetic trees from each study. These are the trees displayed in each study (coincidentally, Figure 2 from each study). Please see the summary below for more details.
R script: This is a R markdown file containing code for the analyses, as well as a record of the interpretations along the way. You will need to modify the paths in the code once you download the data above.
Summary: This is an html file resulting from rendering the R markdown file. You can download it here or view it in the window below. Viewing is not available when using mobile devices.
Climate Adaptation
Climate adaptation is represented as pairwise measures of niche overlap. The measure of niche overlap is Schoener's D. This measure is a similarity metric, so larger values mean more similar climate niches. Climate niches are quantified using principal components derived from the 19 bioclimate variables available from the WorldClim ver. 2.1 website.
