Award Abstract # 1926568
Collaborative Proposal: MRA: Local- to continental-scale drivers of biodiversity across the National Ecological Observatory Network (NEON)

NSF Org: DEB
Division Of Environmental Biology
Recipient: BRYN MAWR COLLEGE
Initial Amendment Date: July 26, 2019
Latest Amendment Date: July 23, 2021
Award Number: 1926568
Award Instrument: Standard Grant
Program Manager: Matthew Kane
mkane@nsf.gov
 (703)292-7186
DEB
 Division Of Environmental Biology
BIO
 Directorate for Biological Sciences
Start Date: October 1, 2019
End Date: November 30, 2022 (Estimated)
Total Intended Award Amount: $368,331.00
Total Awarded Amount to Date: $427,601.00
Funds Obligated to Date: FY 2019 = $94,450.00
FY 2021 = $59,270.00
History of Investigator:
  • Sydne Record (Principal Investigator)
    sydne.record@maine.edu
Recipient Sponsored Research Office: Bryn Mawr College
101 N MERION AVE
BRYN MAWR
PA  US  19010-2899
(610)526-5496
Sponsor Congressional District: 05
Primary Place of Performance: Bryn Mawr College
PA  US  19010-2899
Primary Place of Performance
Congressional District:
05
Unique Entity Identifier (UEI): K6QTMYRRT6S5
Parent UEI:
NSF Program(s): Population & Community Ecology,
Cross-BIO Activities,
MacroSysBIO & NEON-Enabled Sci
Primary Program Source: 01001920DB NSF RESEARCH & RELATED ACTIVIT
01002122DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 102Z, 108Z, 1228, 9251
Program Element Code(s): 112800, 727500, 795900
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.074

ABSTRACT

Understanding how natural and human-made factors affect geographic patterns of biodiversity is essential for planning conservation efforts, especially in the face of rapid global changes. Geographic patterns of biodiversity are expected to be influenced by a combination of local biological factors, like competition among species, and by regional to continental physical factors, such as climate. However, this expectation has not been evaluated from local to continental scales across diverse species lineages. In addition, natural and human-made disturbances are likely to alter this expectation. This study uses the geographic design of the National Ecological Observatory Network (NEON) across the USA to test this idea, by quantifying multiple biological and physical factors affecting biodiversity patterns of small mammals, fish, and ground beetles at nested spatial scales. The study will add new, publicly available data to NEON including measures of animal body sizes, species diversity, and geospatial layers for disturbance and land use histories, climate, geology, and topography. Teaching modules will highlight data science skills needed to work with NEON data. Undergraduates, graduate students, and postdocs will engage directly with the research. The study will also engage the public and increase awareness of the biosphere and environmental change with an interactive exhibit for Science on a Sphere developed with computer science students, a natural history museum, and a large science festival.

The proposed research will advance the field of ecology by connecting fine-grained measurements of individual organism traits, like body size, to cross-scale drivers of biodiversity from plot to continental scales. This research develops a conceptual framework that describes relationships among intraspecific trait variation (ITV) in body size, biodiversity, and drivers related to disturbance, past land use, and their interactions. This framework will advance basic theory and prediction of spatial biodiversity patterns by linking ITV to drivers of biodiversity across scales. Three main questions include: (1) How does spatial scale influence body size ITV and its relationship with biodiversity across taxa within NEON? (2) How is disturbance regime explained by different scales of climate, geodiversity and land cover, and past land use across NEON? (3) How do relationships among climate, geodiversity and land cover, past land use, disturbance regime, and body size ITV explain variation in biodiversity across taxa from local to continental scales? The proposed research will meet a major research need within NEON, to quantify disturbance and land use history data from the plot to the domain scale. Such data are essential to interpretation of observational ecological data and will be publicly disseminated as a geospatial and tabular database containing code for linking other NEON plot, site, and domain data products. These new data and biodiversity analyses will serve to establish a baseline for future spatiotemporal NEON data products that concern ecological communities and ITV.

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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Jarzyna, Marta A. and Norman, Kari E. and LaMontagne, Jalene M. and Helmus, Matthew R. and Li, Daijiang and Parker, Stephanie M. and Perez Rocha, Mariana and Record, Sydne and Sokol, Eric R. and Zarnetske, Phoebe L. and Surasinghe, Thilina D. "Community stability is related to animal diversity change" Ecosphere , v.13 , 2022 https://doi.org/10.1002/ecs2.3970 Citation Details
Kamoske, Aaron G. and Dahlin, Kyla M. and Read, Quentin D. and Record, Sydne and Stark, Scott C. and Serbin, Shawn P. and Zarnetske, Phoebe L. "Towards mapping biodiversity from above: Can fusing lidar and hyperspectral remote sensing predict taxonomic, functional, and phylogenetic tree diversity in temperate forests?" Global Ecology and Biogeography , v.31 , 2022 https://doi.org/10.1111/geb.13516 Citation Details
Liang, Maowei and Baiser, Benjamin and Hallett, Lauren M. and Hautier, Yann and Jiang, Lin and Loreau, Michel and Record, Sydne and Sokol, Eric R. and Zarnetske, Phoebe L. and Wang, Shaopeng "Consistent stabilizing effects of plant diversity across spatial scales and climatic gradients" Nature Ecology & Evolution , 2022 https://doi.org/10.1038/s41559-022-01868-y Citation Details
Li, Daijiang and Record, Sydne and Sokol, Eric R. and Bitters, Matthew E. and Chen, Melissa Y. and Chung, Y. Anny and Helmus, Matthew R. and Jaimes, Ruvi and Jansen, Lara and Jarzyna, Marta A. and Just, Michael G. and LaMontagne, Jalene M. and Melbourne, "Standardized NEON organismal data for biodiversity research" Ecosphere , v.13 , 2022 https://doi.org/10.1002/ecs2.4141 Citation Details
Nagy, R. Chelsea and Balch, Jennifer K. and Bissell, Erin K. and Cattau, Megan E. and Glenn, Nancy F. and Halpern, Benjamin S. and Ilangakoon, Nayani and Johnson, Brian and Joseph, Maxwell B. and Marconi, Sergio and ORiordan, Catherine and Sanovia, James "Harnessing the NEON data revolution to advance open environmental science with a diverse and datacapable community" Ecosphere , v.12 , 2021 https://doi.org/10.1002/ecs2.3833 Citation Details
O'Brien, Margaret and Smith, Colin A. and Sokol, Eric R. and Gries, Corinna and Lany, Nina and Record, Sydne and Castorani, Max C.N. "ecocomDP: A flexible data design pattern for ecological community survey data" Ecological Informatics , 2021 https://doi.org/10.1016/j.ecoinf.2021.101374 Citation Details
Record, Sydne and Jarzyna, Marta A and Hardiman, Brady and Richardson, Andrew D "Open data facilitate resilience in science during the COVID19 pandemic" Frontiers in Ecology and the Environment , v.20 , 2022 https://doi.org/10.1002/fee.2468 Citation Details
Smith, Annie C. and Dahlin, Kyla M. and Record, Sydne and Costanza, Jennifer K. and Wilson, Adam M. and Zarnetske, Phoebe L. "The geodiv r package: Tools for calculating gradient surface metrics" Methods in Ecology and Evolution , v.0 , 2021 https://doi.org/10.1111/2041-210X.13677 Citation Details

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