Extracted from the NSF award abstract:
The goal of this project is to develop a tractable modeling framework for estimating marine metapopulation connectivity and its demographic consequences. This will be achieved using a multifaceted approach which draws upon gravity, demographic, and biological/hydrodynamic coupled models. The objectives are to: (1) Determine reliable predictors of population connectivity from a range of habitat and oceanographic metrics that influence larval dispersal and settlement. The predictive ability of these metrics will be assessed through the development of gravity models which incorporate both natal and settlement site attributes as well as "distance" functions derived from habitat distributions and biological-hydrodynamic coupled models which describe how dispersal probability declines with travel time. (2) Evaluate the robustness of these predictors and different forms of the gravity model at various temporal and spatial scales to examine their suitability for a range of marine metapopulations. (3) Develop matrix metapopulation models to improve understanding of how physical oceanographic processes and dispersal behavior influence the dynamics and spatial connectivity of marine metapopulations. Extensive research of spatial recruitment patterns across a no-take marine reserve network in Kimbe Bay, Papua New Guinea, will provide the empirical data to develop and evaluate a modeling framework for estimating metapopulation connectivity in marine communities where direct estimation of larval dispersal and settlement patterns remains intangible. These efforts will be guided by DNA parentage and trans-generational isotope labeling research of two coral reef fishes with different life histories and habitat usage. These datasets represent the most spatially expansive analysis of recruitment patterns to date and will allow evaluation of modeling approaches across multiple spatial and temporal scales to create a general modeling framework which is both empirically relevant and adaptable to other marine metapopulations with less a priori knowledge of population connectivity.
Dataset | Latest Version Date | Current State |
---|---|---|
Data associated with a connectivity modeling study in Kimbe Bay, Papua New Guinea (Metapopulation Connectivity project) | 2016-10-24 | Preliminary and in progress |
Lead Principal Investigator: Rubao Ji
Woods Hole Oceanographic Institution (WHOI)
Co-Principal Investigator: Julie Kellner
Woods Hole Oceanographic Institution (WHOI)
Co-Principal Investigator: Michael G. Neubert
Woods Hole Oceanographic Institution (WHOI)
Co-Principal Investigator: Simon Thorrold
Woods Hole Oceanographic Institution (WHOI)