Search

Coastal marine environments are subject to a variety of anthropogenic pressures that can negatively impact habitats and the biodiversity they harbor. Conservation actions such as marine protected areas, marine reserves, and other effective area-based conservation measures, are pivotal tools for protecting coastal biodiversity. However, to be effective, conservation area networks must be planned through a systematic conservation planning (SCP) approach. Recently, such approaches have begun to orient their goals toward the conservation of different biodiversity facets and to integrate different types of data. In this review, we illustrate how genetic data and molecular techniques can bring useful knowledge for SCP approaches that are both more comprehensive (sampling the full range of biodiversity) and more adequate (ensuring the long-term persistence of biodiversity). With an emphasis on coastal organisms and habitats, we focus on phylogenetic analysis, the estimation of neutral and adaptive intraspecific genetic diversity at different spatial levels (alpha, beta, and gamma), the study of connectivity and dispersal, and the information obtainable from environmental DNA techniques. For each of these applications, we discuss the benefits of its integration into SCP for coastal systems, its strengths and weaknesses, and the aspects yet to be developed. [ABSTRACT FROM AUTHOR]

Multilocus genetic processes in subdivided populations can be complex and difficult to interpret using theoretical population genetics models. Genetic simulators offer a valid alternative to study multilocus genetic processes in arbitrarily complex scenarios. However, the use of forward‐in‐time simulators in realistic scenarios involving high numbers of individuals distributed in multiple local populations is limited by computation time and memory requirements. These limitations increase with the number of simulated individuals. We developed a genetic simulator, MetaPopGen 2.0, to model multilocus population genetic processes in subdivided populations of arbitrarily large size. It allows for spatial and temporal variation in demographic parameters, age structure, adult and propagule dispersal, variable mutation rates and selection on survival and fecundity. We developed MetaPopGen 2.0 in the R environment to facilitate its use by non‐modeler ecologists and evolutionary biologists. We illustrate the capabilities of MetaPopGen 2.0 for studying adaptation to water salinity in the striped red mullet Mullus surmuletus. [ABSTRACT FROM AUTHOR]

Abstract: Genetic variation, as a basis of evolutionary change, allows species to adapt and persist in different climates and environments. Yet, a comprehensive assessment of the drivers of genetic variation at different spatial scales is still missing in marine ecosystems. Here, we investigated the influence of environment, geographic isolation, and larval dispersal on the variation in allele frequencies, using an extensive spatial sampling (47 locations) of the striped red mullet (Mullus surmuletus) in the Mediterranean Sea. Univariate multiple regressions were used to test the influence of environment (salinity and temperature), geographic isolation, and larval dispersal on single nucleotide polymorphism (SNP) allele frequencies. We used Moran's eigenvector maps (db‐MEMs) and asymmetric eigenvector maps (AEMs) to decompose geographic and dispersal distances in predictors representing different spatial scales. We found that salinity and temperature had only a weak effect on the variation in allele frequencies. Our results revealed the predominance of geographic isolation to explain variation in allele frequencies at large spatial scale (>1,000 km), while larval dispersal was the major predictor at smaller spatial scale (<1,000 km). Our findings stress the importance of including spatial scales to understand the drivers of spatial genetic variation. We suggest that larval dispersal allows to maintain gene flows at small to intermediate scale, while at broad scale, genetic variation may be mostly shaped by adult mobility, demographic history, or multigenerational stepping‐stone dispersal. These findings bring out important spatial scale considerations to account for in the design of a protected area network that would efficiently enhance protection and persistence capacity of marine species. [ABSTRACT FROM AUTHOR]

Population genetics simulation models are useful tools to study the effects of demography and environmental factors on genetic variation and genetic differentiation. They allow for studying species and populations with complex life histories, spatial distribution and many other complicating factors that make analytical treatment impracticable. Most simulation models are individual-based: this poses a limitation to simulation of very large populations because of the limits in computer memory and long computation times. To overcome these limitations, we propose an intermediate approach that allows modelling of very complex demographic scenarios, which would be intractable with analytical models, and removes the limitations imposed by large population size, which affect individual-based simulation models. We implement this approach in a software package for the r environment, MetaPopGen. The innovative concept of this approach with respect to the other population genetic simulators is that it focuses on genotype numbers rather than on individuals. Genotype numbers are iterated through time by using random number generators for appropriate probabilistic distributions to reproduce the stochasticity inherent to Mendelian segregation, survival, dispersal and reproduction. Features included in the model are age structure, monoecious and dioecious (or separate sexes) life cycles, mutation, dispersal and selection. The model simulates only one locus at a time. All demographic parameters can be genotype-, sex-, age-, deme- and time-dependent. MetaPopGen is therefore indicated to study large populations and very complex demographic scenarios. We illustrate the capabilities of MetaPopGen by applying it to the case of a marine fish metapopulation in the Mediterranean Sea. [ABSTRACT FROM AUTHOR]

Long-distance (>40-km) dispersal from marine reserves is poorly documented; yet, it can provide essential benefits such as seeding fished areas or connecting marine reserves into networks. From a meta-analysis, we suggest that the spatial scale of marine connectivity is underestimated due to the limited geographic extent of sampling designs. We also found that the largest marine reserves (>1000 km2) are the most isolated. These findings have important implications for the assessment of evolutionary, ecological, and socio-economic long-distance benefits of marine reserves. We conclude that existing methods to infer dispersal should consider the up-to-date genomic advances and also expand the spatial scale of sampling designs. Incorporating long-distance connectivity in conservation planning will contribute to increase the benefits of marine reserve networks. Highlights Marine dispersal distance estimates are limited by the spatial scale of sampling design and therefore biased downwards. Active larval behavior, oceanographic eddies and fronts, tsunamis, marine debris, and translocations are potentially important, but overlooked, dispersal vectors over long distances. The largest marine reserves have the highest potential for massive and long-distance benefits but are the most isolated reserves. Long-distance dispersal has important consequences for the design of marine reserve networks. [ABSTRACT FROM AUTHOR]

Understanding larval connectivity patterns is critical for marine spatial planning, particularly for designing marine protected areas and managing fisheries. Patterns of larval dispersal and connectivity can be inferred from numerical transport models at large spatial and temporal scales. We assess model-based connectivity patterns between seamounts of the Southwestern Indian Ocean (SWIO) and the coastal ecosystems of Mauritius, La Réunion, Madagascar, Mozambique and South Africa, with emphasis on three shallow seamounts (La Pérouse [LP], MAD-Ridge [MR] and Walters Shoal [WS]). Using drifter trajectory and a Lagrangian model of ichthyoplankton dispersal, we show that larvae can undertake very long dispersion, with larval distances increasing with pelagic larval duration (PLD). There are three groups of greater connectivity: the region between the eastern coast of Madagascar, Mauritius and La Réunion islands; the seamounts of the South West Indian Ridge; and the pair formed by WS and a nearby un-named seamount. Connectivity between these three groups is evident only for the longest PLD examined (360 d). Connectivity from seamounts to coastal ecosystems is weak, with a maximum of 2% of larvae originating from seamounts reaching coastal ecosystems. Local retention at the three focal seamounts (LP, MR and WS) peaks at about 11% for the shortest PLD considered (15 d) at the most retentive seamount (WS) and decreases sharply with increasing PLD. Information on PLD and age of larvae collected at MR and LP are used to assess their putative origin. These larvae are likely self-recruits but it is also plausible that they immigrate from nearby coastal sites, i.e. the southern coast of Madagascar for MR and the islands of La Réunion and Mauritius for LP. [ABSTRACT FROM AUTHOR]