Cross-ocean patterns and processes in fish biodiversity on coral reefs through the lens of eDNA metabarcoding.

Increasing speed and magnitude of global change threaten the world's biodiversity and particularly coral reef fishes. A better understanding of large-scale patterns and processes on coral reefs is essential to prevent fish biodiversity decline but it requires new monitoring approaches. Here, we use environmental DNA metabarcoding to reconstruct well-known patterns of fish biodiversity on coral reefs and uncover hidden patterns on these highly diverse and threatened ecosystems. We analysed 226 environmental DNA (eDNA) seawater samples from 100 stations in five tropical regions (Caribbean, Central and Southwest Pacific, Coral Triangle and Western Indian Ocean) and compared those to 2047 underwater visual censuses from the Reef Life Survey in 1224 stations. Environmental DNA reveals a higher (16%) fish biodiversity, with 2650 taxa, and 25% more families than underwater visual surveys. By identifying more pelagic, reef-associated and crypto-benthic species, eDNA offers a fresh view on assembly rules across spatial scales. Nevertheless, the reef life survey identified more species than eDNA in 47 shared families, which can be due to incomplete sequence assignment, possibly combined with incomplete detection in the environment, for some species. Combining eDNA metabarcoding and extensive visual census offers novel insights on the spatial organization of the richest marine ecosystems.

Incorporating putatively neutral and adaptive genomic data into marine conservation planning.

The availability of genomic data for an increasing number of species makes it possible to incorporate evolutionary processes into conservation plans. Recent studies show how genetic data can inform spatial conservation prioritization (SCP), but they focus on metrics of diversity and distinctness derived primarily from neutral genetic data sets. Identifying adaptive genetic markers can provide important information regarding the capacity for populations to adapt to environmental change. Yet, the effect of including metrics based on adaptive genomic data into SCP in comparison to more widely used neutral genetic metrics has not been explored. We used existing genomic data on a commercially exploited species, the giant California sea cucumber (Parastichopus californicus), to perform SCP for the coastal region of British Columbia (BC), Canada. Using a RAD-seq data set for 717 P. californicus individuals across 24 sampling locations, we identified putatively adaptive (i.e., candidate) single nucleotide polymorphisms (SNPs) based on genotype-environment associations with seafloor temperature. We calculated various metrics for both neutral and candidate SNPs and compared SCP outcomes with independent metrics and combinations of metrics. Priority areas varied depending on whether neutral or candidate SNPs were used and on the specific metric used. For example, targeting sites with a high frequency of warm-temperature-associated alleles to support persistence under future warming prioritized areas in the southern coastal region. In contrast, targeting sites with high expected heterozygosity at candidate loci to support persistence under future environmental uncertainty prioritized areas in the north. When combining metrics, all scenarios generated intermediate solutions, protecting sites that span latitudinal and thermal gradients. Our results demonstrate that distinguishing between neutral and adaptive markers can affect conservation solutions and emphasize the importance of defining objectives when choosing among various genomic metrics for SCP.

Incorporación de Datos Genómicos Putativamente Neutros y Adaptativos dentro de la Planeación de la Conservación Marina Resumen La disponibilidad de los datos genómicos para un número creciente de especies posibilita la incorporación de los procesos evolutivos dentro de los planes de conservación. Los estudios recientes muestran cómo los datos genéticos pueden informar a la priorización de la conservación espacial (PCE) pero tienden a enfocarse más en las medidas de la diversidad y la distinción derivadas principalmente de los conjuntos de datos genéticos neutrales. La identificación de los marcadores genéticos adaptativos puede proporcionar información importante con respecto a la capacidad de las poblaciones para adaptarse al cambio ambiental. Aun así, no se ha explorado el efecto de la inclusión de las medidas basadas en los datos genéticos adaptativos dentro de la PCE y cómo se comparan con las medidas genéticas neutrales de uso más amplio. Usamos datos genómicos existentes sobre una especie de explotación comercial, el pepino de mar gigante de California (Parastichopus californicus), para realizar la PCE para la región costera de la Columbia Británica (BC) en Canadá. Usamos un conjunto de datos RAD-seq para 717 individuos de la especie P. californicus en 24 localidades de muestreo para identificar los polimorfismos de un solo nucleótido (PSNs) putativamente adaptativos (es decir, candidatos) con base en las asociaciones genotipo-ambiente manifestadas con la temperatura del fondo marino. Calculamos varias medidas para los PSNs neutrales y los PSNs candidatos y comparamos los resultados de la PCE con medidas independientes y con combinaciones de medidas. Las áreas prioritarias variaron dependiendo de si se usaron los SNP neutrales o los candidatos y de la medida específica que se utilizó. Por ejemplo, enfocarse en sitios con una frecuencia alta de alelos asociados con agua cálida para fortalecer la persistencia frente al futuro calentamiento prioriza las áreas en la región del sur de la costa. Al contrario, enfocarse en sitios con una alta heterocigosidad esperada en los loci de los candidatos para fortalecer la persistencia frente a la incertidumbre ambiental prioriza las áreas en la parte norte de la costa. Cuando combinamos las medidas, todos los escenarios generaron soluciones intermedias, protegiendo así los sitios que abarcan gradientes latitudinales y gradientes térmicos. Nuestros resultados demuestran que la distinción entre los marcadores neutrales y los adaptativos puede afectar las soluciones de conservación y también enfatizan la importancia de la definición de los objetivos cuando se elige entre varias medidas genómicas para la PCE.

Accounting for stochasticity in demographic compensation along the elevational range of an alpine plant.

Demographic compensation arises when vital rates change in opposite directions across populations, buffering the variation in population growth rates, and is a mechanism often invoked to explain the stability of species geographic ranges. However, studies on demographic compensation have disregarded the effects of temporal variation in vital rates and their temporal correlations, despite theoretical evidence that stochastic dynamics can affect population persistence in temporally varying environments. We carried out a seven-year-long demographic study on the perennial plant Arabis alpina (L.) across six populations encompassing most of its elevational range. We discovered demographic compensation in the form of negative correlations between the means of plant vital rates, but also between their temporal coefficients of variation, correlations and elasticities. Even if their contribution to demographic compensation was small, this highlights a previously overlooked, but potentially important, role of stochastic processes in stabilising population dynamics at range margins.

Soil environment is a key driver of adaptation in Medicago truncatula: new insights from landscape genomics.

Spatial differences in environmental selective pressures interact with the genomes of organisms, ultimately leading to local adaptation. Landscape genomics is an emergent research area that uncovers genome-environment associations, thus allowing researchers to identify candidate loci for adaptation to specific environmental variables. In the present study, we used latent factor mixed models (LFMMs) and Moran spectral outlier detection/randomization (MSOD-MSR) to identify candidate loci for adaptation to 10 environmental variables (climatic, soil and atmospheric) among 43 515 single nucleotide polymorphisms (SNPs) from 202 accessions of the model legume Medicago truncatula. Soil variables were associated with a large number of candidate loci identified through both LFMMs and MSOD-MSR. Genes tagged by candidate loci associated with drought and salinity are involved in the response to biotic and abiotic stresses, while those tagged by candidates associated with soil nitrogen and atmospheric nitrogen, participate in the legume-rhizobia symbiosis. Candidate SNPs identified through both LFMMs and MSOD-MSR explained up to 56% of variance in flowering traits. Our findings highlight the importance of soil in driving adaptation in the system and elucidate the basis of evolutionary potential of M. truncatula to respond to global climate change and anthropogenic disruption of the nitrogen cycle.

Predicting genotype environmental range from genome-environment associations.

Genome-environment association methods aim to detect genetic markers associated with environmental variables. The detected associations are usually analysed separately to identify the genomic regions involved in local adaptation. However, a recent study suggests that single-locus associations can be combined and used in a predictive way to estimate environmental variables for new individuals on the basis of their genotypes. Here, we introduce an original approach to predict the environmental range (values and upper and lower limits) of species genotypes from the genetic markers significantly associated with those environmental variables in an independent set of individuals. We illustrate this approach to predict aridity in a database constituted of 950 individuals of wild beets and 299 individuals of cultivated beets genotyped at 14,409 random single nucleotide polymorphisms (SNPs). We detected 66 alleles associated with aridity and used them to calculate the fraction (I) of aridity-associated alleles in each individual. The fraction I correctly predicted the values of aridity in an independent validation set of wild individuals and was then used to predict aridity in the 299 cultivated individuals. Wild individuals had higher median values and a wider range of values of aridity than the cultivated individuals, suggesting that wild individuals have higher ability to resist to stress-aridity conditions and could be used to improve the resistance of cultivated varieties to aridity.

Insights into the genetic relationships among plants of Beta section Beta using SNP markers.

KEY MESSAGE: Using a much higher number of SNP markers and larger sample sizes than all the previous studies, we characterized the genetic relationships among wild and cultivated plants of section Beta. We analyzed the genetic variation of Beta section Beta, which includes wild taxa (Beta macrocarpa, B. patula, B. vulgaris subsp. adanensis and B. vulgaris subsp. maritima) and cultivars (fodder beet, sugar beet, garden beet, leaf beet, and swiss chards), using 9724 single nucleotide polymorphism markers. The analyses conducted at the individual level without a priori groups confirmed the strong differentiation of B. macrocarpa and B. vulgaris subsp. adanensis from the other taxa. B. vulgaris subsp. maritima showed a complex genetic structure partly following a geographical pattern, which confounded the differences between this taxon and the cultivated varieties. Cultivated varieties were structured into three main groups: garden beets, fodder and sugar beets, and leaf beets and swiss chards. The genetic structure described here will be helpful to correctly estimate linkage disequilibrium and to test for statistical associations between genetic markers and environmental variables.

Taxonomic, spatial and adaptive genetic variation of Beta section Beta.

KEY MESSAGE: The genetic variation of Beta section Beta is structured into four taxonomic and spatial clusters. There are significant associations between molecular markers and environmental variables. ABSTRACT: We investigated the genetic diversity of Beta section Beta, which includes the wild and cultivated relatives of the sugar beet. The taxa included in the study were: Beta vulgaris subsp. maritima, B. vulgaris subsp. adanensis, B. macrocarpa, B. patula and B. vulgaris subsp. vulgaris (garden beet, leaf beet and swiss chards). We collected 1264 accessions originating from the entire distribution area of these taxa and genotyped them for 4436 DArT markers (DArTs). We showed that the genetic variation of these accessions is structured into four taxonomic and spatial clusters: (1) samples of Beta macrocarpa, (2) samples of Beta vulgaris subsp. adanensis, (3) Mediterranean and Asian samples and (4) Atlantic and Northern European samples. These last two clusters were mainly composed of samples of Beta vulgaris subsp. maritima. We investigated in deeper detail the genetic structure of B. vulgaris subsp. maritima, which constituted the majority (80%) of the wild samples. This subspecies exhibited a clinal genetic variation from South-East to North-West. We detected some markers significantly associated to environmental variables in B. vulgaris subsp. maritima. These associations are interpreted as results of natural selection. The variable most often involved in the associations was annual mean temperature. Therefore, these markers can be useful for the development of frost-tolerant winter beets and drought-tolerant rain-fed beets.

Environmental DNA recovers fish composition turnover of the coral reefs of West Indian Ocean islands.

Islands have been used as model systems to study ecological and evolutionary processes, and they provide an ideal set-up for validating new biodiversity monitoring methods. The application of environmental DNA metabarcoding for monitoring marine biodiversity requires an understanding of the spatial scale of the eDNA signal, which is best tested in island systems. Here, we investigated the variation in Actinopterygii and Elasmobranchii species composition recovered from eDNA metabarcoding along a gradient of distance-to-reef in four of the five French Scattered Islands in the Western Indian Ocean. We collected surface water samples at an increasing distance from reefs (0 m, 250 m, 500 m, 750 m). We used a metabarcoding protocol based on the 'teleo' primers to target marine reef fishes and classified taxa according to their habitat types (benthic or pelagic). We investigated the effect of distance-to-reef on ß diversity variation using generalised linear mixed models and estimated species-specific distance-to-reef effects using a model-based approach for community data. Environmental DNA metabarcoding analyses recovered distinct fish species compositions across the four inventoried islands and variations along the distance-to-reef gradient. The analysis of ß-diversity variation showed significant taxa turnover between the eDNA samples on and away from the reefs. In agreement with a spatially localised signal from eDNA, benthic species were distributed closer to the reef than pelagic ones. Our findings demonstrate that the combination of eDNA inventories and spatial modelling can provide insights into species habitat preferences related to distance-to-reef gradients at a small scale. As such, eDNA can not only recover large compositional differences among islands but also help understand habitat selection and distribution of marine species at a finer spatial scale.

Effect of stage-specific vital rates on population growth rates and effective population sizes in an endangered iteroparous plant.

Effective population size (N(e)) determines the strength of genetic drift and can influence the level of genetic diversity a population can maintain. Assessing how changes in demographic rates associated with environmental variables and management actions affect N(e) thus can be crucial to the conservation of endangered species. Calculation of N(e) through demographic models makes it possible to use elasticity analyses to study this issue. The elasticity of N(e) to a given vital rate is the proportional change in N(e) associated with a proportional increase in that vital rate. In addition, demographic models can be used to study N(e) and population growth rate (λ) simultaneously. Simultaneous examination is important because some vital rates differ diametrically in their associations with λ and N(e). For example, in some cases increasing these vital rates increases λ and decreases N(e). We used elasticity analysis to study the effect of stage-specific survival and flowering rates on N(e), annual effective population size (N(a)), and λ in seven populations of the endangered plant Austrian dragonhead (Dracocephalum austriacum). In populations with λ ≥ 1, the elasticities of N(e) and N(a) were similar to those of λ. Survival rates of adults were associated with greater elasticities than survival rates of juveniles, flowering rates, or fecundity. In populations with λ < 1, N(e) and N(a) exhibited greater elasticities to juvenile than to adult vital rates. These patterns are similar to those observed in other species with similar life histories. We did not observe contrasting effects of any vital rate on λ and N(e); thus, management actions that increase the λ of populations of Austrian dragonhead will not increase genetic drift. Our results show that elasticity analyses of N(e) and N(a) can complement elasticity analysis of λ. Moreover, such analyses do not require more data than standard matrix models of population dynamics.

Arabis alpina: A perennial model plant for ecological genomics and life-history evolution.

Many model organisms were chosen and achieved prominence because of an advantageous combination of their life-history characteristics, genetic properties and also practical considerations. Discoveries made in Arabidopsis thaliana, the most renowned noncrop plant model species, have markedly stimulated studies in other species with different biology. Within the family Brassicaceae, the arctic-alpine Arabis alpina has become a model complementary to Arabidopsis thaliana to study the evolution of life-history traits, such as perenniality, and ecological genomics in harsh environments. In this review, we provide an overview of the properties that facilitated the rapid emergence of A. alpina as a plant model. We summarize the evolutionary history of A. alpina, including genomic aspects, the diversification of its mating system and demographic properties, and we discuss recent progress in the molecular dissection of developmental traits that are related to its perennial life history and environmental adaptation. From this published knowledge, we derive open questions that might inspire future research in A. alpina, other Brassicaceae species or more distantly related plant families.

Evolving spatial conservation prioritization with intraspecific genetic data.

Spatial conservation prioritization (SCP) is a planning framework used to identify new conservation areas on the basis of the spatial distribution of species, ecosystems, and their services to human societies. The ongoing accumulation of intraspecific genetic data on a variety of species offers a way to gain knowledge of intraspecific genetic diversity and to estimate several population characteristics useful in conservation, such as dispersal and population size. Here, we review how intraspecific genetic data have been integrated into SCP and highlight their potential for identifying conservation area networks that represent intraspecific genetic diversity comprehensively and that ensure the long-term persistence of biodiversity in the face of global change.

Genetic patchiness in European eel adults evidenced by molecular genetics and population dynamics modelling.

Disentangling the demographic processes that determine the genetic structure of a given species is a fundamental question in conservation and management. In the present study, the population structure of the European eel was examined with a multidisciplinary approach combining the fields of molecular genetics and population dynamics modelling. First, we analyzed a total of 346 adult specimens of known age collected in three separate sample sites using a large panel of 22 EST-linked microsatellite loci. Second, we developed a European eel-specific model to unravel the demographic mechanisms that can produce the level of genetic differentiation estimated by molecular markers. This is the first study that reveals a pattern of genetic patchiness in maturing adults of the European eel. A highly significant genetic differentiation was observed among samples that did not follow an Isolation-by-Distance or Isolation-by-Time pattern. The observation of genetic patchiness in adults is likely to result from a limited parental contribution to each spawning event as suggested by our modelling approach. The value of genetic differentiation found is predicted by the model when reproduction occurs in a limited number of spawning events isolated from each other in time or space, with an average of 130-375 breeders in each spawning event. Unpredictability in spawning success may have important consequences for the life-history evolution of the European eel, including a bet-hedging strategy (distributing reproductive efforts over time) which could in turn guarantee successful reproduction of some adults.

MetaPopGen 2.0: A multilocus genetic simulator to model populations of large size.

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.

How many replicates to accurately estimate fish biodiversity using environmental DNA on coral reefs?

Quantifying fish species diversity in rich tropical marine environments remains challenging. Environmental DNA (eDNA) metabarcoding is a promising tool to face this challenge through the filtering, amplification, and sequencing of DNA traces from water samples. However, because eDNA concentration is low in marine environments, the reliability of eDNA to detect species diversity can be limited. Using an eDNA metabarcoding approach to identify fish Molecular Taxonomic Units (MOTUs) with a single 12S marker, we aimed to assess how the number of sampling replicates and filtered water volume affect biodiversity estimates. We used a paired sampling design of 30 L per replicate on 68 reef transects from 8 sites in 3 tropical regions. We quantified local and regional sampling variability by comparing MOTU richness, compositional turnover, and compositional nestedness. We found strong turnover of MOTUs between replicated pairs of samples undertaken in the same location, time, and conditions. Paired samples contained non-overlapping assemblages rather than subsets of one another. As a result, non-saturated localized diversity accumulation curves suggest that even 6 replicates (180 L) in the same location can underestimate local diversity (for an area <1 km). However, sampling regional diversity using ~25 replicates in variable locations (often covering 10 s of km) often saturated biodiversity accumulation curves. Our results demonstrate variability of diversity estimates possibly arising from heterogeneous distribution of eDNA in seawater, highly skewed frequencies of eDNA traces per MOTU, in addition to variability in eDNA processing. This high compositional variability has consequences for using eDNA to monitor temporal and spatial biodiversity changes in local assemblages. Avoiding false-negative detections in future biomonitoring efforts requires increasing replicates or sampled water volume to better inform management of marine biodiversity using eDNA.

Long-Distance Benefits of Marine Reserves: Myth or Reality?

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 (>1000km2) 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.

Geographic isolation and larval dispersal shape seascape genetic patterns differently according to spatial scale.

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.

Global mismatch between fishing dependency and larval supply from marine reserves.

Marine reserves are viewed as flagship tools to protect exploited species and to contribute to the effective management of coastal fisheries. Yet, the extent to which marine reserves are globally interconnected and able to effectively seed areas, where fisheries are most critical for food and livelihood security is largely unknown. Using a hydrodynamic model of larval dispersal, we predict that most marine reserves are not interconnected by currents and that their potential benefits to fishing areas are presently limited, since countries with high dependency on coastal fisheries receive very little larval supply from marine reserves. This global mismatch could be reversed, however, by placing new marine reserves in areas sufficiently remote to minimize social and economic costs but sufficiently connected through sea currents to seed the most exploited fisheries and endangered ecosystems.

MetaPopGen: an r package to simulate population genetics in large size metapopulations.

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.

Low connectivity between Mediterranean marine protected areas: a biophysical modeling approach for the dusky grouper Epinephelus marginatus.

Marine protected areas (MPAs) are major tools to protect biodiversity and sustain fisheries. For species with a sedentary adult phase and a dispersive larval phase, the effectiveness of MPA networks for population persistence depends on connectivity through larval dispersal. However, connectivity patterns between MPAs remain largely unknown at large spatial scales. Here, we used a biophysical model to evaluate connectivity between MPAs in the Mediterranean Sea, a region of extremely rich biodiversity that is currently protected by a system of approximately a hundred MPAs. The model was parameterized according to the dispersal capacity of the dusky grouper Epinephelus marginatus, an archetypal conservation-dependent species, with high economic importance and emblematic in the Mediterranean. Using various connectivity metrics and graph theory, we showed that Mediterranean MPAs are far from constituting a true, well-connected network. On average, each MPA was directly connected to four others and MPAs were clustered into several groups. Two MPAs (one in the Balearic Islands and one in Sardinia) emerged as crucial nodes for ensuring multi-generational connectivity. The high heterogeneity of MPA distribution, with low density in the South-Eastern Mediterranean, coupled with a mean dispersal distance of 120 km, leaves about 20% of the continental shelf without any larval supply. This low connectivity, here demonstrated for a major Mediterranean species, poses new challenges for the creation of a future Mediterranean network of well-connected MPAs providing recruitment to the whole continental shelf. This issue is even more critical given that the expected reduction of pelagic larval duration following sea temperature rise will likely decrease connectivity even more.

An integrated genetic-demographic model to unravel the origin of genetic structure in European eel (Anguilla anguilla L.).

The evolutionary enlightened management of species with complex life cycles often requires the development of mathematical models integrating demographic and genetic data. The genetic structure of the endangered European eel (Anguilla anguilla L.) has been thoroughly analyzed in several studies in the past years. However, the interpretation of the key demographic and biologic processes that determine the observed spatio-temporal genetic structure has been very challenging owing to the complex life cycle of this catadromous species. Here, we present the first integrated demographic-genetic model applied to the European eel that explicitly accounts for different levels of larval and adult mixing during oceanic migrations and allows us to explore alternative hypotheses on genetic differentiation. Our analyses show that (i) very low levels of mixing occurring during larval dispersal or adult migration are sufficient to erase entirely any genetic differences among sub-populations; (ii) small-scale temporal differentiation in recruitment can arise if the spawning stock is subdivided in distinct reproductive groups; and (iii) the geographic differentiation component might be overestimated if a limited number of temporal recruits are analyzed. Our study can inspire the scientific debate on the interpretation of genetic structure in other species characterized by complex life cycle and long-range migrations.