Barriers in a sea of elasmobranchs
Cite this dataset
Hirschfeld, Maximilian; Dudgeon, Christine; Sheaves, Marcus; Barnett, Adam (2022). Barriers in a sea of elasmobranchs [Dataset]. Dryad. https://doi.org/10.5061/dryad.bvq83bk8w
The interplay of animal dispersal and environmental heterogeneity is fundamental for the distribution of biodiversity on earth. In the ocean, the interaction of physical barriers and dispersal has primarily been examined for organisms with planktonic larvae. Animals that lack a planktonic life stage and depend on active dispersal are however likely to produce distinctive patterns.
We used available literature on population genetics and phylogeography of elasmobranchs (sharks, rays and skates), to examine how marine barriers and dispersal ecology shape genetic connectivity in animals with active dispersal. We provide a global geographic overview of barriers extracted from the literature and synthesize the geographic and hydrologic factors, spatial and temporal scales to characterize different types of barriers. The three most studied barriers were used to analyse the effect of elasmobranch dispersal potential and barrier type on genetic connectivity.
We characterized nine broad types of marine barriers, with the three most common barriers being related to ocean bathymetry. The maximum depth of occurrence, maximum body size and habitat of each species were used as proxies for dispersal potential, and were important predictors of genetic connectivity with varying effect depending on barrier type. Environmental tolerance and reproductive behaviour may also play a crucial role in population connectivity in animals with active dispersal. However, we find that studies commonly lack appropriate study designs based on a priori hypotheses to test the effect of physical barriers while accounting for animal behaviour.
Our synthesis highlights the relative contribution of different barrier types in shaping elasmobranch populations. We provide a new perspective on how barriers and dispersal ecology interact to rearrange genetic variation of marine animals with active dispersal. We illustrate methodological sources that can bias the detection of barriers and provide potential solutions for future research in the field.
Peer-reviewed publications that reported intra-specific genetic or genomic differentiation in one or more elasmobranch species were obtained via the online search engines Google Scholar and Web of Science by entering combinations of the key words, ‘shark’, ‘ray’, ‘genetic*’, ‘genomic*’, ‘phylogeograph*’, ‘population structure’, ‘connectivity’ (until 16 January 2020) and were screened to discover additional publications. Obligate fresh-water species were excluded. Additional information was compiled on the taxonomy and biology (maximum depth of occurrence, maximum body size, and habitat) for each elasmobranch species from secondary literature and fishbase.org (Ebert et al. 2013; Last et al. 2016; Weigmann 2016; Froese & Pauly. 2018). Elasmobranch habitat was described as one of three broad categories: 1. Benthopelagic habitat on the continental shelves and upper slopes, 2. neritic habitat of the water column above the continental shelves and upper slopes, 3. oceanic habitat including the pelagic and deep sea. Finally, we extracted information on the type and number of genetic markers used to study elasmobranch population genetic structure from the primary literature.
Genetic comparisons across barriers were then extracted from the publications. A genetic comparison was recorded as a single data point if sampling design was adequate to formally test for intra-specific genetic differentiation across a single barrier. Sampling was considered adequate if there was at least one sampling location with a minimum of five samples on either side of a barrier and there were no other barriers that could simultaneously act on the genetic differentiation between the same locations. Genetic differentiation between the locations must have been statistically assessed using pairwise fixation or differentiation indices between individual locations or analysis of molecular variance (AMOVA) between groups of sampling locations (Weir & Cockerham 1984; Excoffier, Smouse & Quattro 1992; Meirmans & Hedrick 2011). Pairs of locations that lack any physical barriers between them and are separated by the same or smaller geographic distances than locations on either side of a barrier of interest can be used as controls because genetic differences are likely caused by geographic distance alone, not a barrier. Therefore, data points of significant genetic differences across barriers were not included if authors also reported significant differences between control locations, because differences could be caused by geographic distance, the barrier, or both. Data points were also excluded if behaviour, specifically reproductive philopatry, was identified as the main driver of genetic differentiation between locations on either side of a physical barrier in question. They were excluded to avoid bias in our synthesis because it is not possible to distinguish between the effect of a physical barrier or behaviour on genetic differentiation if not explicitly tested for separately. We then synthesized information on the barriers extracted from the literature to characterized different barrier types based on similarity of the geographic and hydrologic factors that form each barrier, their geographic scale, time scale and temporal variability. Detailed information on each barrier and source references are reported in the Appendix 1 Table A3 of the main manuscript (Global Ecology and Biogeography: Barriers in a sea of elasmobranchs: From fishing for populations to testing hypotheses in population genetics).
This data set forms part of the manuscript Barriers in a sea of elasmobranchs: From fishing for populations to testing hypotheses in population genetics submitted to Global Ecology and Biogeography.
The data set was used to create the figures, tables and models reported in the main text and the Appendix 1 of the main manuscript. Please also refer to the main manuscript and the Dryad Data Description section for additional information.
The data set contains three documents:
- Readme file (this document): ReadMe_Hirschfeld_et_al2021_Barriers_in_a_sea_of_Elasmobranchs.docx)
- A data base in .csv format: (Hirschfeld_et_al2021_Barriers_in_a_sea_of_Elasmobranchs_data.csv) curated for and used to construct the figures, tables and data analyses reported in the main manuscript of the article and the supplementary information. See a description of each column in the data set below.
- R Markdown document: Hirschfeld_et_al2021_Barriers_in_a_sea_of_Elasmobranchs_SuppInfo.pdf. This document contains background information, a description of the data set and information on any missing data points as well as an annotated R code of the analyses used to produce the models and graphical output that were included in the main manuscript.
Sea World, Award: SWR/3/2017
Sea World, Award: SWR/5/2018
Galapagos Conservation Trust
Holsworth Wildlife Research Endowment & The Ecological Society of Australia
Rufford Foundation, Award: 18898-2