| NSF Org: |
DEB Division Of Environmental Biology |
| Recipient: |
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| Initial Amendment Date: | August 6, 2021 |
| Latest Amendment Date: | August 6, 2021 |
| Award Number: | 2129589 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Jason West
jwest@nsf.gov (703)292-7410 DEB Division Of Environmental Biology BIO Directorate for Biological Sciences |
| Start Date: | August 1, 2021 |
| End Date: | July 31, 2025 (Estimated) |
| Total Intended Award Amount: | $2,372,311.00 |
| Total Awarded Amount to Date: | $2,372,311.00 |
| Funds Obligated to Date: |
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| Recipient Sponsored Research Office: |
1850 RESEARCH PARK DR STE 300 DAVIS CA US 95618-6153 (530)754-7700 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
OR/Sponsored Programs Davis CA US 95618-6134 |
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Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | Cross-BIO Activities |
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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
Biodiversity is critical for the health of ecosystems, our biosphere, and humankind. However, biodiversity is threatened by habitat loss and climate change. Habitat loss and climate change have resulted in the acceleration of species extinctions across the world. Within species, the extinction or persistence of populations determines whether a species will survive at all. Thus, understanding the factors that contribute to population persistence or extinction is critical for predicting future population dynamics and managing biodiversity in a changing world. Population persistence is determined by genetic composition, ecological habitat, environmental stresses, and interactions among these factors. This award will integrate advances in genomics, remote sensing, and statistical modelling to develop new predictive models of population persistence and extinction. The models created in this project will be critical for understanding population dynamics, predicting responses to future change, and providing tools to direct the implementation of genetically-informed conservation strategies. The project also includes an educational component that will provide research and training opportunities for a new generation of biologists to prepare them to incorporate integrative approaches to understand complex aspects of climate change and its effect on biological systems. Training the next generation of biologists to be able to integrate across fields is vital to addressing the complex impacts of climate change. To achieve this, graduate level workshops in Field Ecology, Remote Sensing, Genomic Data Analysis, Demographic Modeling, and Science Communication and Professionalism will be developed and taught. To help build an inclusive STEM pipeline, an integrative Course based Undergraduate Research Experience (CURE) for freshmen will be developed, and the project will support Master?s students for summer research as part of the Advancing Diversity to Educate the Professors of Tomorrow (ADEPT) program.
The ability to predict how the genetic composition of populations impacts their long-term persistence or extinction in different and changing environments requires integrating analysis techniques and data across diverse fields. Evolutionary genomics can identify past targets of selection and current determinants of fitness, but has not been effectively integrated with demography to explain multi-generation population dynamics. Conversely, demographic modeling can determine which aspects of organismal establishment, growth, survival, and reproduction (life history) are most critical for population growth or decline, but does not usually consider genomic determinants of these fitness components. Streptanthus tortuosus (Mountain Jewelflower) will be used for this research. S. tortuosus is an ideal species for this research due to its sensitivity to climate, variation within and among populations in traits and life history timing, and demographic and genomic tools currently in development. This project will: 1) use genomics to quantify genetic variation among individuals; 2) apply spectral remote sensing to understand the impact of stressors, the environment, and genotype on plant physiology and growth; and, 3) develop a statistical and demographic modeling framework to integrate these measures to understand and predict the factors underlying population persistence or extinction. While past research has investigated these components individually and some interactions among them, this award explores whether population dynamics is an emergent property that can be best understood by developing new demographic models that integrate all of these inputs. Together, understanding how diversity in genes, traits, physiology, and environment scales to impact individual performance and population dynamics will provide critical new insights into the ecological and evolutionary processes driving persistence or extinction. The resulting integrative demography models will provide a road map for conservation biologists and managers to use genomic information to predict effects of different conservation strategies, such as assisted migration or introducing genetic variation, which can be applied across wild, managed, and agricultural populations.
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.
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