
NSF Org: |
IOS Division Of Integrative Organismal Systems |
Recipient: |
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Initial Amendment Date: | August 16, 2022 |
Latest Amendment Date: | August 16, 2022 |
Award Number: | 2220928 |
Award Instrument: | Standard Grant |
Program Manager: |
Aardra Kachroo
akachroo@nsf.gov (703)292-7826 IOS Division Of Integrative Organismal Systems BIO Directorate for Biological Sciences |
Start Date: | January 1, 2023 |
End Date: | December 31, 2026 (Estimated) |
Total Intended Award Amount: | $399,383.00 |
Total Awarded Amount to Date: | $399,383.00 |
Funds Obligated to Date: |
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History of Investigator: |
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Recipient Sponsored Research Office: |
2601 WOLF VILLAGE WAY RALEIGH NC US 27695-0001 (919)515-2444 |
Sponsor Congressional District: |
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Primary Place of Performance: |
2601 Wolf Village Way Raleigh NC US 27695-7214 |
Primary Place of
Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): |
Evolutionary Processes, Systematics & Biodiversity Sci, ORCC-Organism Resp Clim Change |
Primary Program Source: |
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Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.074 |
ABSTRACT
Successful conservation of global biodiversity requires that biologists accurately predict the risk of species extinction under future climate conditions. However, current models often make simplifying assumptions about the biology of plants and animals. For example, some models assume that a species can easily migrate through the landscape when this is not the case, or that a species is not able to evolve rapidly to environmental change when this is actually a possibility. Our interdisciplinary team will study the biology of a plant species to determine what data researchers and conservationists need to predict how climate change will influence extinction risk for plants in the natural environment. We will use the partridge pea (Chamaecrista fasciculata), a common and widespread plant in natural grasslands, to identify the type of data needed to improve ecological models for conservation planning. We will evaluate genetic differences and rates of gene flow among populations and estimate these populations? ability to evolve in response to climate change to identify models that best describe or forecast rates of change under new climate conditions. In collaboration with the Georgia Plant Conservation Alliance and the Southeastern Grasslands Initiative, we will apply what we learn to develop a series of tools that practitioners can use to predict extinction risks under climate change for at-risk grassland species. This work will significantly improve our ability to protect biodiversity in the southeastern U.S. and in habitats around the world.
Populations across the range of a species vary in their migratory and adaptive potential under climate change. Most approaches aimed at predicting population persistence under climate change make simplifying assumptions about plasticity, adaptation, and gene flow that are commonly violated in natural systems. We combine approaches from evolutionary biology, field ecology, and population genomics to forecast range-wide dynamics under climate change in a broadly distributed native legume (Chamaecrista fasciculata). Our studies examine the migratory potential of populations under climate change using population genomic estimators of historical gene flow. To evaluate adaptive potential, we will expose paternal half-sib families from 12 populations to contemporary climates and simulated climate change in common gardens across the range. Finally, we will forecast eco-evolutionary dynamics under climate change using models that differ in the degree to which they incorporate data on species occurrence, additive genetic variance in fitness in response to climate, trait expression, sequence variation, and gene flow. Our work will provide a robust framework for predictions of range-wide responses to climate change in systems that are less amenable to manipulation. We will collaborate with conservation practitioners in the Georgia Plant Conservation Alliance and Southeastern Grasslands Initiative to produce risk assessment tools that project range dynamics under climate change for endangered plant species. In workshops, we will discuss our progress and provide opportunities for our trainees to forge connections with conservation practitioners. The PIs will recruit, train, and mentor scholars from historically marginalized backgrounds in population genomics, quantitative genetics, data analysis, and ecological modeling.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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