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Locations for new protected areas should be identified with consideration of intraspecific genetic diversity because genetic variation enhances the adaptability of species to novel environmental conditions. The process of siting new protected areas is called spatial conservation prioritization and is often formulated as a mathematical problem to be solved with the aid of computer software. Integrating multidimensional continuous metrics of genome-wide genetic diversity in spatial conservation prioritization involves significant challenges in terms of computation speed and memory requirements. In this study, we tested and compared several approaches to approximate the multidimensional continuous metrics of genetic diversity using multidimensional discrete genetic clusters or unidimensional discrete conservation features. To this end, we applied two tools for spatial conservation prioritization, raptr and prioritizr , to genomic datasets of two fish species (the white seabream Diplodus sargus and the red mullet Mullus surmuletus) sampled throughout most of their distribution range in the Mediterranean Sea. We found that most of the approximations tested either did not achieve all genetic conservation targets or resulted in excessively high conservation costs. Nonetheless, approaches based on multidimensional genetic clusters allowed generating prioritizations with relatively small gaps in genetic objectives at very high computation speed. This might be an interesting option for exploratory or interactive analyses such as those performed in workshop with stakeholders. • Genome-wide genetic diversity helps species persist against environmental change. • Siting new protected areas should consider genome-wide genetic diversity. • We explore different approaches to integrate it in conservation prioritization. • We used two Mediterranean species as example. • No approach was best in terms of computation efficiency and objectives met. [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]

Highlights: [•] We review the main topics of 10 years of landscape genetics. [•] We suggest perspectives for the future of landscape genetics. [•] We describe how landscape genetics can be useful in conservation. [•] We describe how landscape genetics will contribute to informing global change. [ABSTRACT FROM AUTHOR]

Abstract: The fate of European arctic–alpine species during Pleistocene climatic oscillations still remains debated. Did these cold-adapted species invade much of the continental steppe or did they remain restricted to warmer slopes of inner mountain massifs? To examine this question, we investigated the phylogeography of Gentiana nivalis, a typical European arctic–alpine plant species. Genome fingerprinting analyses revealed that four genetic pools are actually unevenly distributed across the continent. One cluster covers almost all mountain massifs as well as northern areas, and thus coincides with a scenario of past distribution covering a large part of the European glacial steppe. In contrast, the three other lineages are strongly restricted spatially to western, central, and eastern Alps, respectively, thus arguing towards a scenario of in situ glacial survival. The coexistence of lineages with such contrasting demographic histories in Europe challenges our classical view of refugia and corroborates several hypotheses of biogeographers from the twentieth century. [Copyright &y& Elsevier]

Understanding the processes and patterns of gene flow and local adaptation requires a detailed knowledge of how landscape characteristics structure populations. This understanding is crucial, not only for improving ecological knowledge, but also for managing properly the genetic diversity of threatened and endangered populations. For nearly 80 years, population geneticists have investigated how physiognomy and other landscape features have influenced genetic variation within and between populations. They have relied on sampling populations that have been identified beforehand because most population genetics methods have required discrete populations. However, a new approach has emerged for analyzing spatial genetic data without requiring that discrete populations be identified in advance. This approach, landscape genetics, promises to facilitate our understanding of how geographical and environmental features structure genetic variation at both the population and individual levels, and has implications for ecology, evolution and conservation biology. It differs from other genetic approaches, such as phylogeography, in that it tends to focus on processes at finer spatial and temporal scales. Here, we discuss, from a population genetic perspective, the current tools available for conducting studies of landscape genetics. [Copyright &y& Elsevier]

Detecting the extrinsic selective pressures shaping genomic variation is critical for a better understanding of adaptation and for forecasting evolutionary responses of natural populations to changing environmental conditions. With increasing availability of geo-referenced environmental data, landscape genomics provides unprecedented insights into how genomic variation and underlying gene functions affect traits potentially under selection. Yet, the robustness of genotype–environment associations used in landscape genomics remains tempered due to various limitations, including the characteristics of environmental data used, sampling designs employed, and statistical frameworks applied. Here, we argue that using complementary or new environmental data sources and well-informed sampling designs may help improve the detection of selective pressures underlying patterns of local adaptation in various organisms and environments. The increasing availability of new, high-quality geo-referenced environmental data(bases) is stimulating landscape genomic studies of terrestrial and aquatic organisms. Environmental data (e.g., climate, soil, and topography) are now available at multiple spatial and temporal scales and, together with environmentally and genetically informed sampling designs, enable us to capture selection pressures at high resolution in various organisms. Statistical advances in genotype–environment association methods now allow testing the response of population genomic variation to complex environments, using nonredundant and informative environmental predictors. Our understanding of the environmental constraints underlying local adaptation of living organisms has provided insights into the potential responses of populations to environmental changes such as global warming. This understanding is a key component of well-informed biodiversity conservation programmes. [ABSTRACT FROM AUTHOR]

Understanding the factors that shape adaptive genetic variation across species niches has become of paramount importance in evolutionary ecology, especially to understand how adaptation to changing climate affects the geographic range of species. The distribution of adaptive alleles in the ecological niche is determined by the emergence of novel mutations, their fitness consequences and gene flow that connects populations across species niches. Striking demographical differences and source—sink dynamics of populations between the centre and the margin of the niche can play a major role in the emergence and spread of adaptive alleles. Although some theoretical predictions have long been proposed, the origin and distribution of adaptive alleles within species niches remain untested. In this paper, we propose and discuss a novel empirical approach that combines landscape genetics with species niche modelling, to test whether alleles that confer local adaptation are more likely to occur in either marginal or central populations of species niches. We illustrate this new approach by using a published data set of 21 alpine plant species genotyped with a total of 2483 amplified fragment length polymorphisms (AFLP), distributed over more than 1733 sampling sites across the Alps. Based on the assumption that alleles that were statistically associated with environmental variables were adaptive, we found that adaptive alleles in the margin of a species niche were also present in the niche centre, which suggests that adaptation originates in the niche centre. These findings corroborate models of species range evolution, in which the centre of the niche contributes to the emergence of novel adaptive alleles, which diffuse towards niche margins and facilitate niche and range expansion through subsequent local adaptation. Although these results need to be confirmed via fitness measurements in natural populations and functionally characterised genetic sequences, this study provides a first step towards understanding how adaptive genetic variation emerges and shapes species niches and geographic ranges along environmental gradients. [ABSTRACT FROM AUTHOR]

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. Conservation area networks on land and sea need to be expanded to meet the objectives of the post-2020 global biodiversity framework. Spatial conservation prioritization (SCP) is a rigorous framework to identify suitable areas for protection on the basis of scientific data. Integrating intraspecific genetic data in SCP can help identify networks of conservation areas that are more representative of biological diversity and likely better at ensuring its long-term persistence. [ABSTRACT FROM AUTHOR]

Due to their static nature, protected areas (PAs) are vulnerable to global change, and resident species will likely need to colonize new sites and exchange migrants to sustain viable local populations. Alpine habitats often have a high level of protection, yet extensive environmental heterogeneity and the limited dispersal ability of many endemic species makes it unclear whether PA networks provide sufficient connectivity to protect vulnerable species. We assess landscape connectivity in the European alpine PA network by combining measures of habitat and genetic connectivity using community landscape genetics approaches. Examining 27 plant species, we compare levels of genetic diversity in PA and non-PA sites, and rank non-PA sites for their potential value in facilitating genetic and habitat connectivity, as well as preserving species richness in 893 alpine plants. Non-PA sites do not significantly enhance overall levels of genetic variability across species. However, spatial genetic turnover (allele frequency variation across space) is influenced by geographical and environmental distance, suggesting that genetic connectivity, and by extension landscape connectivity, is impacted by gaps in the PA network. A subset of non-PA sites, when measured for habitat connectivity, genetic connectivity and species richness using spatial graphs, substantially increase landscape connectivity for alpine plants, although there are discrepancies among metrics in ranking sites. We provide the first example of the evaluation and prediction of new PAs including levels of intraspecific genetic diversity for a whole community. This has significance for the management and extension of the European alpine network, especially in identifying valuable unprotected sites. [ABSTRACT FROM AUTHOR]

• We analyzed the quantity of fish eDNA inside/outside 6 Mediterranean marine reserves. • We found no difference in the total quantity of eDNA inside and outside reserves. • The Demerso-pelagic to Benthic fish eDNA ratio (DeBRa) was higher inside reserves. • The DeBRa can be computed with incomplete reference databases, whatever the habitat. • The DeBRa seems to be a reliable indicator of fishing pressure. In a context of marine biodiversity erosion, the need to better understand the effects of overfishing stands out. New genetic techniques such as environmental DNA (eDNA) metabarcoding have emerged and allow the detection of a wider range of species compared to conventional methods, but still fall short of providing reliable abundance estimations and subsequent ecological indicators. In this paper, we propose a combination of metabarcoding and quantitative polymerase chain reaction to obtain the quantity of eDNA molecules per species. This method was used inside and outside six no-take Mediterranean marine reserves to measure the effect of the protection on fish species and build a new indicator. Even if the total quantity of fish eDNA molecules was not different between the inside and outside of the reserves, we detected that cryptobenthic fish eDNA was significantly associated to the outside of reserves. Based on this observation, we propose a novel ecological indicator, the Demerso-pelagic to Benthic fish eDNA Ratio (DeBRa), taking advantage of the eDNA capacity to detect cryptobenthic reef fishes which are often missed by classical surveys. The DeBRa was significantly higher inside reserves, reflecting a higher relative quantity of eDNA molecules belonging to pelagic and demersal fishes under protection against fishing, therefore it appears to be a reliable eDNA-based indicator of human pressure. Furthermore, the DeBRa was not sensitive to habitat or environmental variations and does not require a complete reference database of eDNA sequences since it can rely on sequences assigned at the genus or family scale if possible and necessary. [ABSTRACT FROM AUTHOR]

Landscape genetics is the amalgamation of landscape ecology and population genetics to help with understanding microevolutionary processes such as gene flow and adaptation. In this review, we examine why landscape genetics of plants lags behind that of animals, both in number of studies and consideration of landscape elements. The classical landscape distance/resistance approach to study gene flow is challenging in plants, whereas boundary detection and the assessment of contemporary gene flow are more feasible. By contrast, the new field of landscape genetics of adaptive genetic variation, establishing the relationship between adaptive genomic regions and environmental factors in natural populations, is prominent in plant studies. Landscape genetics is ideally suited to study processes such as migration and adaptation under global change. [ABSTRACT FROM AUTHOR]