Barriers in a sea of elasmobranchs

Background 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. Methods 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. Results 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. Main conclusions 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. Methods 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).背景 动物扩散与环境异质性的相互作用，是地球生物多样性分布格局形成的核心基础。在海洋环境中，学界针对具有浮游幼体（planktonic larvae）阶段的生物，已围绕物理屏障与扩散的交互作用开展了大量研究。然而，缺乏浮游生活史阶段、依赖主动扩散（active dispersal）的海洋动物，其种群分布格局往往具有独特性。 研究方法 本研究依托已发表的板鳃类（elasmobranchs，包括鲨鱼、鳐和魟）种群遗传学（population genetics）与系统生物地理学（phylogeography）相关文献，旨在探究海洋物理屏障与扩散生态学如何塑造依赖主动扩散的海洋动物的遗传连通性（genetic connectivity）。我们系统梳理了文献中记载的全球海洋物理屏障分布概况，并综合屏障形成的地理与水文因子、空间及时间尺度，对不同类型的物理屏障进行分类表征。选取学界研究最多的三类屏障，分析板鳃类扩散潜力（dispersal potential）与屏障类型对遗传连通性的影响。 研究结果 本研究共表征出9大类海洋物理屏障，其中最为常见的三类屏障均与海洋测深地形（ocean bathymetry）相关。我们以物种的最大栖息深度、最大体型及栖息生境作为扩散潜力的替代指标，这些指标均为遗传连通性的重要预测因子，其效应强度随屏障类型的不同而存在差异。环境耐受度与繁殖行为，同样可能对依赖主动扩散的海洋动物的种群连通性起到关键调控作用。但本研究发现，现有研究普遍缺乏基于先验假设的合理实验设计，无法在考量动物行为的前提下检验物理屏障的作用效果。 主要结论 本研究综合分析明确了不同类型物理屏障在塑造板鳃类种群格局中的相对贡献。我们为理解屏障与扩散生态学如何共同作用，进而重塑依赖主动扩散的海洋动物的遗传变异格局提供了全新视角。同时，本研究阐明了可能干扰物理屏障检测效果的方法学缺陷，并为该领域未来的研究方向提供了可行的解决方案。 研究方法（续） 本研究通过谷歌学术（Google Scholar）与Web of Science两大在线学术搜索引擎，以关键词组合「shark」「ray」「genetic*」「genomic*」「phylogeograph*」「population structure」「connectivity」检索2020年1月16日前发表的同行评议文献，筛选出报道了一种或多种板鳃类种内遗传或基因组分化的研究，并通过引文追踪获取额外相关文献。本研究排除了专性淡水生板鳃类物种。我们从二手文献及FishBase数据库（Ebert等，2013；Last等，2016；Weigmann，2016；Froese & Pauly，2018）中整理了各板鳃类物种的分类学与生物学信息，包括最大栖息深度、最大体型及栖息生境。板鳃类的栖息生境被划分为三大类：1. 大陆架与上陆坡区域的底栖浮游混合生境；2. 大陆架及上陆坡上方水体的近岸浅海生境；3. 包括远洋与深海区域的大洋生境。最后，我们从原始文献中提取了用于研究板鳃类种群遗传结构的遗传标记类型与数量信息。 我们从文献中提取了跨物理屏障的遗传比较数据。若采样设计可正式检验单一屏障两侧的种内遗传分化，则该遗传比较可被记为一个有效数据点。当满足以下条件时，采样设计被视为合格：屏障两侧至少各有一个采样点位，且每个点位的样本量不低于5；同时不存在其他可同时影响该组采样点位间遗传分化的物理屏障。点位间的遗传分化必须通过两种方式进行统计学评估：一是单个点位间的成对固定指数或分化指数，二是采样点位组间的分子变异分析（Analysis of Molecular Variance，AMOVA）（Weir & Cockerham，1984；Excoffier等，1992；Meirmans & Hedrick，2011）。若两组采样点位之间不存在任何物理屏障，且其地理间隔与目标屏障两侧的采样点位间隔相同或更小，则可将其作为对照样点——因为此时点位间的遗传差异仅可能由地理距离导致，而非物理屏障。因此，若文献作者同时报道了对照样点间存在显著遗传差异，则跨屏障的显著遗传差异数据点将被排除，因为此时的遗传差异可能由地理距离、物理屏障或二者共同导致。若研究将特定行为（尤其是繁殖归巢行为（reproductive philopatry））认定为目标物理屏障两侧点位间遗传分化的主要驱动因素，则该数据点也将被排除。排除此类数据是为了避免综合分析出现偏倚：若未单独设计实验区分物理屏障与行为对遗传分化的影响，则无法明确二者的相对作用。随后，我们基于文献中提取的屏障信息，根据形成屏障的地理与水文因子相似性、地理尺度、时间尺度及时间变异性，对不同物理屏障类型进行分类表征。各屏障的详细信息及引用文献详见主文稿的附录1表A3（发表于"Global Ecology and Biogeography"：《板鳃类的海洋屏障：从种群捕捞到种群遗传学假设检验》）。