Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
  • BCO-DMO Processing Description
  • Problem Description
• Data Files
• Related Publications
• Related Datasets
• Parameters
• Instruments
• Project Information
• Funding

17 adult specimens were collected by boat off Stonington Borough, CT (41° 20’37.8” N 71° 54’51.4” W) between September 15th and October 10th, 2022 to act as a wild ‘pre-migratory’ baseline (‘fall’, n = 17) and an additional 21 individuals were collected from the same location on April 27^th 2021 to act as a wild “post-migratory” baseline (‘spring’, n = 21). Upon collection, individuals were immediately euthanized with MS-222 and measured for length (TL; 33.7 ± 4.4 cm), body depth (BD; 8 ± 0.9 cm), and wet weight (wW; 532.6 ± 227 g). During dissections, the stomach was removed to calculate a stomachless whole weight to standardize for consumed prey items, and the liver and gonad was then removed, individually weighed (0.01 g) and frozen at -20°C for future lipid extractions. A subsample of dorsally located white muscle tissue was also removed and frozen.

For all adults, we calculated gonadosomatic (GSI; %) and hepatosomatic (HSI; %) indices using stomachless fish mass (wW – stomach mass), to standardize for stomach contents, as {e.g., 100 × [(gonad or liver mass, g) / (stomachless fish mass)].

We quantified gonad, liver, and white muscle, storage lipid, lean-mass, and ash weights of each surviving experimental individual and baseline specimen. Samples were frozen at -50°C for 1 week and remeasured for whole body dry weight (dWb, 0.001 g). Following published protocols (Schultz and Conover 1997, Guo et al. 2021, 2022, Zavell et al. 2023), dried specimens were loaded into preweighed Alundum medium-porosity extraction thimbles and transferred to a custom-designed Soxhlet apparatus, where they were bathed in petroleum ether for 3.5 h to extract all metabolically available lipids. Samples were then dried overnight (60°C) and re-measured, with the change in pre- and post-extraction weights (ΔdW), representing the storage-lipid fraction (dWLipid). Samples were then muffle furnaced for 4 h at 550°C and reweighed with ΔdW, representing the lean-mass fraction (dWLean) and the remaining mass represents the inorganic fraction (dWAsh). 

Organism Identifier (LSID, Life Sciences Identifier)
Centropristis striata, urn:lsid:marinespecies.org:taxname:159348

See methods section. 

* Sheet "Wild Fish" of submitted file "Adult-BSB-Overwintering-Wild-Fish-BCO-DMO-V4.xlsx" was imported into the BCO-DMO data system as the primary data table for this dataset.
** Missing data values are displayed differently based on the file format you download.  They are blank in csv files, "NaN" in MatLab files, etc.

* Column names adjusted to conform to BCO-DMO naming conventions designed to support broad re-use by a variety of research tools and scripting languages. [Only numbers, letters, and underscores.  Can not start with a number]

* Dates converted to ISO 8601 format
* Latitude and Longitude converted to decimal degree format (South and west are negative). example lon 71.9332°W to -71.9332

NSF Abstract:

Oceans are large, open habitats, and it was previously believed that their lack of obvious barriers to dispersal would result in extensive mixing, preventing organisms from adapting genetically to particular habitats. It has recently become clear, however, that many marine species are subdivided into multiple populations that have evolved to thrive best under contrasting local environmental conditions. Nevertheless, we still know very little about the genomic mechanisms that enable divergent adaptations in the face of ongoing intermixing. This project focuses on the Atlantic silverside (Menidia menidia), a small estuarine fish that exhibits a remarkable degree of local adaptation in growth rates and a suite of other traits tightly associated with a climatic gradient across latitudes. Decades of prior lab and field studies have made Atlantic silverside one of the marine species for which we have the best understanding of evolutionary tradeoffs among traits and drivers of selection causing adaptive divergence. Yet, the underlying genomic basis is so far completely unknown. The investigators will integrate whole genome sequencing data from wild fish sampled across the distribution range with breeding experiments in the laboratory to decipher these genomic underpinnings. This will provide one of the most comprehensive assessments of the genomic basis for local adaptation in the oceans to date, thereby generating insights that are urgently needed for better predictions about how species can respond to rapid environmental change. The project will provide interdisciplinary training for a postdoc as well as two graduate and several undergraduate students from underrepresented minorities. The findings will also be leveraged to develop engaging teaching and outreach materials (e.g. a video documentary and popular science articles) to promote a better understanding of ecology, evolution, and local adaptation among science students and the general public.

The goal of the project is to characterize the genomic basis and architecture underlying local adaptation in M. menidia and examine how the adaptive divergence is shaped by varying levels of gene flow and maintained over ecological time scales. The project is organized into four interconnected components. Part 1 examines fine-scale spatial patterns of genomic differentiation along the adaptive cline to a) characterize the connectivity landscape, b) identify genomic regions under divergent selection, and c) deduce potential drivers and targets of selection by examining how allele frequencies vary in relation to environmental factors and biogeographic features. Part 2 maps key locally adapted traits to the genome to dissect their underlying genomic basis. Part 3 integrates patterns of variation in the wild (part 1) and the mapping of traits under controlled conditions (part 2) to a) examine how genomic architectures underlying local adaptation vary across gene flow regimes and b) elucidating the potential role of chromosomal rearrangements and other tight linkage among adaptive alleles in facilitating adaptation. Finally, part 4 examines dispersal - selection dynamics over seasonal time scales to a) infer how selection against migrants and their offspring maintains local adaptation despite homogenizing connectivity and b) validate candidate loci for local adaptation. Varying levels of gene flow across the species range create a natural experiment for testing general predictions about the genomic mechanisms that enable adaptive divergence in the face of gene flow. The findings will therefore have broad implications and will significantly advance our understanding of the role genomic architecture plays in modifying the gene flow - selection balance within coastal environments.

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.