Contributors | Affiliation | Role |
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Buston, Peter | Boston University (BU) | Principal Investigator, Contact |
Lindo-Atichati, David | University of Miami Rosenstiel School of Marine and Atmospheric Science (UM-RSMAS) | Co-Principal Investigator, Contact |
Paris-Limouzy, Claire B. | University of Miami Rosenstiel School of Marine and Atmospheric Science (UM-RSMAS) | Co-Principal Investigator |
Ake, Hannah | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Outputs from four ocean models.
LOLA and HOLA model dataset parameters:
Name | Description | Units |
Longitude | Longitude | degrees east |
Latitude | Latitude | degrees north |
Time | Time | days since 1900-12-31 |
zu | Eastward seawater velocity | meters per second |
zv | Northward seawater velocity | meters per second |
zw | Downward seawater velocity | meters per second |
HOHA and HOHAT model dataset parameters:
Name | Description | Units |
Longitude | Longitude | degrees east |
Latitude | Latitude | degrees north |
MT | Time | days since 1900-12-31 00:00:00 |
u | Eastward seawater velocity | meters per second |
v | Northward seawater velocity | meters per second |
w_velocity | Downward seawater velocity | meters per second |
water_temp | Seawater temperature | degrees Celsius |
salinity | Seawater salinity | PSU |
pot_density | Seawater potential density | sigma |
bathymetry | Bathymetry | meters |
ilt | Ocean mixed layer thickness | meters |
mlt | Ocean mixed layer thickness | meters |
ssh | Sea surface elevation | meters |
Methodology:
Methodology is explained in Lindo-Atichati et al. (2016). As a brief summary, we constructed a hierarchy of four ocean-atmosphere models operating at multiple scales within a 1 × 1 deg domain of the Belizean Barrier Reef. The four models are: 1) A Low-resolution Ocean model and Low-resolution Atmospheric model (LOLA); (2) A High-resolution Ocean model and Low-resolution Atmospheric model (HOLA); (3) A High-resolution Ocean model and High-resolution Atmospheric model (HOHA); (4) A High-resolution Ocean model and High-resolution Atmospheric model with Tidal forcing (HOHAT). The ocean models are based on the HYbrid Coordinate Ocean Model (HYCOM, Bleck, 2002; Chassignet et al., 2003; Wallcraft et al., 2009). The atmospheric models are based on the non-hydrostatic Weather Research and Forecasting (WRF) and on the Navy Operational Global Atmospheric Prediction System (NOGAPS). The drifter data was from surface drifters provided by the Consortium for Advanced Research on Transport of Hydrocarbon in the Environment (CARTHE).
Sampling and analytical procedures:
From May 30 to July 2 of 2013, 55 drifter deployments were made at 1–5 km off a 40 km stretch of the BBR centered on South Water Caye (16.82 deg N, 87.97 deg W) (Fig. 2 b and c of Lindo-Atichati et al (2016)). The hierarchy of four ocean-atmosphere models were used for the larger area from 16.35 to 17.30 deg N, and from 87.48 to 88.47 deg W (Fig. 1 of Lindo-Atichati et al (2016)).
Data was processed with AWK IEEE Std 1003.1-2008 for data extraction, with Matlab version R2014a for data manipulation and statistical analysis, and with Generic Mapping Tools GMT version 4 for mapping.
BCO-DMO Data Processing Notes:
-Added decimal degree lat and lon to data
-Reformatted dates to yyyy/mm/dd
-Reformatted column names to comply with naming standards
-Replaced blank cells with nd
File |
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model.csv (Comma Separated Values (.csv), 982 bytes) MD5:d3b9d6d8f191a403caa517bb94fe23ba Primary data file for dataset ID 729886 |
Parameter | Description | Units |
Name | Name of model | unitless |
Download_link | Download link for model output data | unitless |
File_size | File size of model output data | unitless |
Description | Description of model outpout data | unitless |
Website | |
Platform | lab Buston |
Description | Buston lab expeditions to Belize beginning in 2010. |
Understanding the patterns, causes and consequences of larval dispersal is a major goal of 21st century marine ecology. Patterns of dispersal determine the rates of larval exchange, or connectivity, between populations. Both physical factors (e.g., water movement) and biological factors (e.g., larval behavior) cause variation in population connectivity. Population connectivity, in turn, has major consequences for all aspects of an organism's biology, from individual behavior to metapopulation dynamics, and from evolution within metapopulations to the origin and extinction of species. Further, understanding population connectivity is critical for the design of effective networks of marine reserves, creation of vital tools in conservation, and the development of sustainable fisheries.
Over the last decade, three methods, each of which tells something slightly different, have emerged as leading contenders to provide the greatest insights into population connectivity. First, coupled biophysical models make assumptions regarding water flow, larval behavior and ecology, to predict population connectivity. Second, indirect genetic methods use spatial distributions of allele frequencies to infer population connectivity. Third, direct genetic methods use parentage analyses, tracing recruits to specific adults, to measure population connectivity. Despite advances, lack of integration means that we do not know the predictive skill of biophysical models, or the extent to which patterns of dispersal predict spatial genetic structure. The overall objective of this proposal is to conduct an integrated investigation of population connectivity, using all three methods in one tractable system: the neon goby, Elacatinus lori, on the Belizean Barrier Reef. There are three motives for this choice of study system: i) fourteen highly polymorphic microsatellite loci have been developed, facilitating the assignment of recruits to parents using parentage analyses and the measurement of dispersal; ii) the physical oceanography of the Belizean Barrier Reef is well-studied, facilitating the development and testing of coupled biophysical models; and, iii) E. lori has a relatively small biogeographic range, facilitating analysis of the spatial distribution of allele frequencies throughout its range.
Broader Impacts. The grant will support one postdoc and two graduate students who will be trained in scientific diving, marine fieldwork, population genetics, biophysical modeling, and mathematical modeling, and will gain collaborative research experience. PIs will incorporate research findings in their courses, which cover all these topics. The grant will also broaden participation of under-represented groups by supporting six undergraduates from groups traditionally underrepresented in STEM fields. In each year of the project there will be an All Participants meeting to reinforce the network of participants. A project website will be developed, in English and Spanish, on the theme of larval dispersal and population connectivity. This will include a resource for K-12 marine science educators developed in collaboration with a marine science educator. All PIs will ensure that results are broadly disseminated to the scientific community and general public via appropriate forms of media.
Funding Source | Award |
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NSF Division of Ocean Sciences (NSF OCE) |