Contributors | Affiliation | Role |
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Buston, Peter | Boston University (BU) | Principal Investigator, Contact |
D'Aloia, Cassidy C. | Woods Hole Oceanographic Institution (WHOI) | Co-Principal Investigator |
Ake, Hannah | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Data from fish genotyped at 14 and 20 loci at different life stages. Sampling completed on the Belizean Barrier Reef in 2013.
We surveyed a 41 km-long transect of the Belize Barrier reef, centered at Carrie Bow Cay, by SCUBA to conduct a genetic parentage study of the reef fish Elactinus lori. All underwater sampling was conducted using SCUBA at an average (±SD) depth of 16.03 ± 2.19 m. A waypoint was recorded from the boat at the beginning and end of every collection dive, with the midpoint of each dive taken as the location for all individuals sampled on that dive. To collect settlers, we sampled ~ 100 individuals every kilometer. Individuals were collected from the outsides of sponges using slurp guns and placed them in plastic bags. At the surface, settlers were anesthetized with MS-222. For adults, we collected non-lethal tissue samples at three regions along the transect (n ≈ 1,000 per region). Each adult was collected with a slurp gun and restrained in a net; we took a small tissue sample from the caudal fin using scissors. All tissue was stored in 95% EtOH. At each adult collection sponge, we also measured: sponge depth (m, using dive computers), number of tubes per sponge, and length of largest sponge tube (nearest cm, using a tape measure).
For genetic analyses, DNA was extracted using a HotSHOT protocol; fragments were amplified using the Type-It Microsatellite PCR Kit (Qiagen) and screened on an ABI 3730 automated sequencer.
Otoliths were extracted from the 120 settlers that were assigned to parents. Otoliths were dissected, cleared of tissue, immersed in oil for 2-7 days, and rings were counted under a 50× oil immersion lens
Further details on all methods can be found in D’Aloia et al. (2015), PNAS.
Alleles were scored using GENEMAPPER v.4.0.
BCO-DMO Data Processing Notes:
-Combined 14 and 20 loci data into one spreadsheet
-Replaced ? with nd
-Added year column, and loci column to identify the number of loci sampled
File |
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genotypes.csv (Comma Separated Values (.csv), 1.23 MB) MD5:2ce38ad23e2476301a67ac46e621ddb9 Primary data file for dataset ID 738724 |
Parameter | Description | Units |
individual_id | Unique ID assigned to each fish | unitless |
year | Year of sampling | unitless |
loci | The number of loci individuals were genotyped at; 14 loci or 20 loci. Individuals genotyped at 20 loci were used in the final parentage analysis. Each loci have two columns because each individual has two alleles per locus. | unitless |
life_stage | Whether an individual is a potential offspring (O) or parent (P). | unitless |
tetB_25745 | The number of reptitive units in the microsatellite allele. | count |
tetB_25745_2 | The number of reptitive units in the microsatellite allele. | count |
tetB_29109 | The number of reptitive units in the microsatellite allele. | count |
tetB_29109_2 | The number of reptitive units in the microsatellite allele. | count |
triB_1419 | The number of reptitive units in the microsatellite allele. | count |
triB_1419_2 | The number of reptitive units in the microsatellite allele. | count |
triG_18144 | The number of reptitive units in the microsatellite allele. | count |
triG_18144_2 | The number of reptitive units in the microsatellite allele. | count |
tetG_985 | The number of reptitive units in the microsatellite allele. | count |
tetG_985_2 | The number of reptitive units in the microsatellite allele. | count |
tetY_6326 | The number of reptitive units in the microsatellite allele. | count |
tetY_6326_2 | The number of reptitive units in the microsatellite allele. | count |
tetR_25632 | The number of reptitive units in the microsatellite allele. | count |
tetR_25632_2 | The number of reptitive units in the microsatellite allele. | count |
tetB_6231 | The number of reptitive units in the microsatellite allele. | count |
tetB_6231_2 | The number of reptitive units in the microsatellite allele. | count |
triB_23889 | The number of reptitive units in the microsatellite allele. | count |
triB_23889_2 | The number of reptitive units in the microsatellite allele. | count |
triG_25362 | The number of reptitive units in the microsatellite allele. | count |
triG_25362_2 | The number of reptitive units in the microsatellite allele. | count |
triG_21378 | The number of reptitive units in the microsatellite allele. | count |
triG_21378_2 | The number of reptitive units in the microsatellite allele. | count |
tetY_14528 | The number of reptitive units in the microsatellite allele. | count |
tetY_14528_2 | The number of reptitive units in the microsatellite allele. | count |
triY_6266 | The number of reptitive units in the microsatellite allele. | count |
triY_6266_2 | The number of reptitive units in the microsatellite allele. | count |
tetR_23415 | The number of reptitive units in the microsatellite allele. | count |
tetR_23415_2 | The number of reptitive units in the microsatellite allele. | count |
tetB_24561 | The number of reptitive units in the microsatellite allele. | count |
tetB_24561_2 | The number of reptitive units in the microsatellite allele. | count |
tetB_5796 | The number of reptitive units in the microsatellite allele. | count |
tetB_5796_2 | The number of reptitive units in the microsatellite allele. | count |
tetB_1184 | The number of reptitive units in the microsatellite allele. | count |
tetB_1184_2 | The number of reptitive units in the microsatellite allele. | count |
tetG_24777 | The number of reptitive units in the microsatellite allele. | count |
tetG_24777_2 | The number of reptitive units in the microsatellite allele. | count |
tetG_26721 | The number of reptitive units in the microsatellite allele. | count |
tetG_26721_2 | The number of reptitive units in the microsatellite allele. | count |
tetY_25176 | The number of reptitive units in the microsatellite allele. | count |
tetY_25176_2 | The number of reptitive units in the microsatellite allele. | count |
Dataset-specific Instrument Name | GPSMAP 76Cx (Garmin) |
Generic Instrument Name | GPS receiver |
Dataset-specific Description | Used to collect GPS data |
Generic Instrument Description | Acquires satellite signals and tracks your location.
This term has been deprecated. Use instead: https://www.bco-dmo.org/instrument/560 |
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) |