A Landscape Ecologist’s Agenda for Landscape Genetics

Move it or lose it: Predicted effects of culverts and population density on Mojave desert tortoise (Gopherus agassizii) connectivity

Roadways and railways can reduce wildlife movements across landscapes, negatively impacting population connectivity. Connectivity may be improved by structures that allow safe passage across linear barriers, but connectivity could be adversely influenced by low population densities. The Mojave desert tortoise is threatened by habitat loss, fragmentation, and population declines. The tortoise continues to decline as disturbance increases across the Mojave Desert in the southwestern United States. While underground crossing structures, like hydrological culverts, have begun receiving attention, population density has not been considered in tortoise connectivity. Our work asks a novel question: How do culverts and population density affect connectivity and potentially drive genetic and demographic patterns? To explore the role of culverts and population density, we used agent-based spatially explicit forward-in-time simulations of gene flow. We constructed resistance surfaces with a range of barriers to movement and representative of tortoise habitat with anthropogenic disturbance. We predicted connectivity under variable population densities. Simulations were run for 200 non-overlapping generations (3400 years) with 30 replicates using 20 microsatellite loci. We evaluated population genetic structure and diversity and found that culverts would not entirely negate the effects of linear barriers, but gene flow improved. Our results also indicated that density is important for connectivity. Low densities resulted in declines regardless of the landscape barrier scenario (> 75% population census size, > 97% effective population size). Results from our simulation using current anthropogenic disturbance predicted decreased population connectivity over time. Genetic and demographic effects were detectable within five generations (85 years) following disturbance with estimated losses in effective population size of 69%. The pronounced declines in effective population size indicate this could be a useful monitoring metric. We suggest management strategies that improve connectivity, such as roadside fencing tied to culverts, conservation areas in a connected network, and development restricted to disturbed areas.

Landscape Genetics for Brazilian Equines

Optimization of DNA collection for National gene bank and conservation programs requires information on spatial and genetic distribution of animals countrywide. The relationship between genetic and geographic distances were examined in 8 Brazilian horse breeds (Baixadeiro, Crioulo, Campeiro, Lavradeiro, Marajoara, Mangalarga Marchador, Pantaneiro and Puruca) using Single Nucleotide Polymorphism markers and collection point locations. Mantel correlations, Genetic Landscape Shape Interpolation, Allelic Aggregation Index Analyses and Spatial autocorrelation tests indicated a nonrandom distribution of horses throughout the country. Minimum collection distances for the national Gene Bank should be 530km, with clear divisions seen in genetic structure of horse populations in both North/South and East/West directions. Comparing Pantaneiro and North/Northeastern breeds, physical distance is not necessarily the defining factor for genetic differentiation. This should be considered when sampling these local breeds. These data can help optimise GenBank collection routines and conservation strategies for these breeds.

Effects of Anthropogenic Habitat Fragmentation on the Genetic Connectivity of the Threatened and Endemic Campylorhynchus yucatanicus (Aves, Trogloditydae) in the Yucatan Peninsula, Mexico

Identifying connectivity patterns among remnant bird populations and their relationships with land use practices and adjacent habitat fragments is key to implementing appropriate long-term management strategies for species conservation. The coastal scrub and dune vegetation complex of the northern Yucatan Peninsula is rich in endemisms and has been affected by human development, which threatens the survival of the Yucatan Wren (Campylorhynchus yucatanicus) population, an endemic bird species. To identify possible anthropogenic barriers to the connectivity of C. yucatanicus along 14 localities in the Yucatan (Mexico) coastal north, we explored the relationship between the species population’s genetic variability at each sampled site and landscape structure using regression models, in addition to the relationship between genetic distance and landscape resistance. Seven nuclear microsatellite loci were used as genetic markers. Four genetic populations were highlighted by the clustering method implemented in the Geneland program. Human settlement and availability of adequate habitat were significantly related to genetic distance (Fst), suggesting limited connectivity among sites due to ongoing land use changes. We suggest changing the IUCN threat category of C. yucatanicus to endangered as we found a significant loss of genetic variability in addition to restricted distribution, small population, habitat degradation, and loss of connectivity.

Global genetic diversity status and trends: towards a suite of Essential Biodiversity Variables (EBVs) for genetic composition

Biodiversity underlies ecosystem resilience, ecosystem function, sustainable economies, and human well‐being. Understanding how biodiversity sustains ecosystems under anthropogenic stressors and global environmental change will require new ways of deriving and applying biodiversity data. A major challenge is that biodiversity data and knowledge are scattered, biased, collected with numerous methods, and stored in inconsistent ways. The Group on Earth Observations Biodiversity Observation Network (GEO BON) has developed the Essential Biodiversity Variables (EBVs) as fundamental metrics to help aggregate, harmonize, and interpret biodiversity observation data from diverse sources. Mapping and analyzing EBVs can help to evaluate how aspects of biodiversity are distributed geographically and how they change over time. EBVs are also intended to serve as inputs and validation to forecast the status and trends of biodiversity, and to support policy and decision making. Here, we assess the feasibility of implementing Genetic Composition EBVs (Genetic EBVs), which are metrics of within‐species genetic variation. We review and bring together numerous areas of the field of genetics and evaluate how each contributes to global and regional genetic biodiversity monitoring with respect to theory, sampling logistics, metadata, archiving, data aggregation, modeling, and technological advances. We propose four Genetic EBVs: (i) Genetic Diversity; (ii) Genetic Differentiation; (iii) Inbreeding; and (iv) Effective Population Size (N_e). We rank Genetic EBVs according to their relevance, sensitivity to change, generalizability, scalability, feasibility and data availability. We outline the workflow for generating genetic data underlying the Genetic EBVs, and review advances and needs in archiving genetic composition data and metadata. We discuss how Genetic EBVs can be operationalized by visualizing EBVs in space and time across species and by forecasting Genetic EBVs beyond current observations using various modeling approaches. Our review then explores challenges of aggregation, standardization, and costs of operationalizing the Genetic EBVs, as well as future directions and opportunities to maximize their uptake globally in research and policy. The collection, annotation, and availability of genetic data has made major advances in the past decade, each of which contributes to the practical and standardized framework for large‐scale genetic observation reporting. Rapid advances in DNA sequencing technology present new opportunities, but also challenges for operationalizing Genetic EBVs for biodiversity monitoring regionally and globally. With these advances, genetic composition monitoring is starting to be integrated into global conservation policy, which can help support the foundation of all biodiversity and species' long‐term persistence in the face of environmental change. We conclude with a summary of concrete steps for researchers and policy makers for advancing operationalization of Genetic EBVs. The technical and analytical foundations of Genetic EBVs are well developed, and conservation practitioners should anticipate their increasing application as efforts emerge to scale up genetic biodiversity monitoring regionally and globally.

Habitat specialisation and matrix resistance predict responses of butterfly populations to landscape features in tropical grassland-forest complexes

A fundamental question in ecology is to understand how a species is distributed in a landscape. In terrestrial landscapes, the size and isolation of habitat patches, and matrix properties, are thought to drive population density patterns. Yet, given the same set of landscape features, why do species from a single taxon vary so widely in their density patterns? A primary hypothesis for such variation, proposed by community-level studies, is that key ecological characteristics of species influence how they respond to landscape features. However, robust tests of this hypothesis, which require measurements of populations of multiple species in an assemblage, are still scarce. We investigated the ability of ecological specialisation and the interaction of species with the matrix (matrix resistance) to predict population responses of butterfly species to patch size and connectivity in naturally heterogeneous tropical forest-grassland complexes. We surveyed 56 habitat patches in a 65 sq. km area by laying 276 transects, along which the identity and abundances of butterfly species were recorded. We also used transects that cut across two habitats to estimate matrix resistance. We find that habitat specialisation predicted the strength of area-density and isolation-density relationships. Matrix resistance also predicted variation in area-density relationships, highlighting the importance of species interactions with the matrix. Specialists showed higher matrix resistance and stronger area and isolation effects than did generalists. Our findings suggest that investigating how traits related to ecological specialisation and matrix resistance affect demographic parameters can contribute towards understanding mechanisms underlying species distributions in heterogeneous landscapes.

Assessing the influence of the amount of reachable habitat on genetic structure using landscape and genetic graphs

Genetic structure, i.e. intra-population genetic diversity and inter-population genetic differentiation, is influenced by the amount and spatial configuration of habitat. Measuring the amount of reachable habitat (ARH) makes it possible to describe habitat patterns by considering intra-patch and inter-patch connectivity, dispersal capacities and matrix resistance. Complementary ARH metrics computed under various resistance scenarios are expected to reflect both drift and gene flow influence on genetic structure. Using an empirical genetic dataset concerning the large marsh grasshopper (Stethophyma grossum), we tested whether ARH metrics are good predictors of genetic structure. We further investigated (i) how the components of the ARH influence genetic structure and (ii) which resistance scenario best explains these relationships. We computed local genetic diversity and genetic differentiation indices in genetic graphs, and ARH metrics in the unified and flexible framework offered by landscape graphs, and we tested the relationships between these variables. ARH metrics were relevant predictors of the two components of genetic structure, providing an advantage over commonly used habitat metrics. Although allelic richness was significantly explained by three complementary ARH metrics in the best PLS regression model, private allelic richness and MIW indices were essentially related with the ARH measured outside the focal patch. Considering several matrix resistance scenarios was also key for explaining the different genetic responses. We thus call for further use of ARH metrics in landscape genetics to explain the influence of habitat patterns on the different components of genetic structure.

Forest cover at landscape scales increases male and female gametic diversity of palm seedlings

Genetic diversity shapes the evolutionary potential of plant populations. For outcrossing plants, genetic diversity is influenced by effective population size and by dispersal, first of paternal gametes through pollen, and then of paternal and maternal gametes through seeds. Forest loss often reduces genetic diversity, but the degree to which it differentially impacts the paternal and maternal contributions to genetic diversity and the spatial scale at which these impacts are most pronounced are poorly understood. To address these questions, we genotyped 504 seedlings of the animal-dispersed palm Oenocarpus bataua collected from 29 widely distributed sites across Ecuador and decomposed the contribution of paternal and maternal gametes to overall genetic diversity. The amount of forest cover at a landscape scale (>10 km radius) had an equally significant positive association with both male and female gametic diversity. In addition, there was a significant positive association between forest cover and effective population size. Stronger fine-scale spatial genetic structure for female versus male gametes was observed at sites with low forest cover, but this did not scale up to differences in male versus female gametic diversity. These findings show that reductions in forest cover at spatial scales much larger than those typically evaluated in ecological studies lead to significant, and equivalent, decreases of diversity in both male and female gametes, and that this association between landscape level forest loss and genetic diversity may be driven directly by reductions in effective population size of O. bataua, rather than by indirect disruptions to local dispersal processes.

Differing, multiscale landscape effects on genetic diversity and differentiation in eastern chipmunks

Understanding how habitat loss and fragmentation impact genetic variation is a major goal in landscape genetics, but to date, most studies have focused solely on the correlation between intervening matrix and genetic differentiation at a single spatial scale. Several caveats exist in these study designs, among them is the inability to include measures of genetic diversity in addition to differentiation. Both genetic metrics help predict population persistence, but are expected to function at differing spatial scales, which requires a multiscale investigation. In this study, we sampled two distinct spatial scales in 31 independent landscapes along a gradient of landscape context (i.e., forest amount, configuration, and types of intervening matrix) to investigate how landscape heterogeneity influences genetic diversity and differentiation in the forest-associated eastern chipmunk (Tamias striatus). Overall, quality of intervening matrix was correlated with genetic differentiation at multiple spatial scales, whereas only configuration was associated with regional scale genetic diversity. Habitat amount, in contrast, did not influence genetic differentiation or diversity at either spatial scale. Based on our findings, landscape effects on genetic variation appears to differ based on spatial scale, the type of genetic response variable, and random variation among landscapes, making extrapolation of results from single scale, unreplicated studies difficult. We encourage landscape geneticists to utilize multiscale, replicated landscapes with both genetic diversity, and differentiation to gain a more comprehensive understanding of how habitat loss and fragmentation influence genetic variation.

Influence of environmental factors on the genetic variation of the aquatic macrophyte Ranunculus subrigidus on the Qinghai-Tibetan Plateau

BACKGROUND

Due to the environmental heterogeneity along elevation gradients, alpine ecosystems are ideal study objects for investigating how ecological variables shape the genetic patterns of natural species. The highest region in the world, the Qinghai-Tibetan Plateau, is a hotspot for the studies of evolutionary processes in plants. Many large rivers spring from the plateau, providing abundant habitats for aquatic and amphibious organisms. In the present study, we examined the genetic diversity of 13 Ranunculus subrigidus populations distributed throughout the plateau in order to elucidate the relative contribution of geographic distance and environmental dissimilarity to the spatial genetic pattern.

RESULTS

A relatively low level of genetic diversity within populations was found. No spatial genetic structure was suggested by the analyses of molecular variance, Bayesian clustering analysis and Mantel tests. Partial Mantel tests and multiple matrix regression analysis showed a significant influence of the environment on the genetic divergence of the species. Both climatic and water quality variables contribute to the habitat heterogeneity of R. subrigidus populations.

CONCLUSIONS

Our results suggest that historical processes involving long-distance dispersal and local adaptation may account for the genetic patterns of R. subrigidus and current environmental factors play an important role in the genetic differentiation and local adaptation of aquatic plants in alpine landscapes.

Habitat Loss Does Not Always Entail Negative Genetic Consequences

Although habitat loss has large, consistently negative effects on biodiversity, its genetic consequences are not yet fully understood. This is because measuring the genetic consequences of habitat loss requires accounting for major methodological limitations like the confounding effect of habitat fragmentation, historical processes underpinning genetic differentiation, time-lags between the onset of disturbances and genetic outcomes, and the need for large numbers of samples, genetic markers, and replicated landscapes to ensure sufficient statistical power. In this paper we overcame all these challenges to assess the genetic consequences of extreme habitat loss driven by mining in two herbs endemic to Amazonian savannas. Relying on genotyping-by-sequencing of hundreds of individuals collected across two mining landscapes, we identified thousands of neutral and independent single-nucleotide polymorphisms (SNPs) in each species and used these to evaluate population structure, genetic diversity, and gene flow. Since open-pit mining in our study region rarely involves habitat fragmentation, we were able to assess the independent effect of habitat loss. We also accounted for the underlying population structure when assessing landscape effects on genetic diversity and gene flow, examined the sensitivity of our analyses to the resolution of spatial data, and used annual species and cross-year analyses to minimize and quantify possible time-lag effects. We found that both species are remarkably resilient, as genetic diversity and gene flow patterns were unaffected by habitat loss. Whereas historical habitat amount was found to influence inbreeding; heterozygosity and inbreeding were not affected by habitat loss in either species, and gene flow was mainly influenced by geographic distance, pre-mining land cover, and local climate. Our study demonstrates that it is not possible to generalize about the genetic consequences of habitat loss, and implies that future conservation efforts need to consider species-specific genetic information.

Landscape genomics to the rescue of a tropical bee threatened by habitat loss and climate change

Habitat degradation and climate change are currently threatening wild pollinators, compromising their ability to provide pollination services to wild and cultivated plants. Landscape genomics offers powerful tools to assess the influence of landscape modifications on genetic diversity and functional connectivity, and to identify adaptations to local environmental conditions that could facilitate future bee survival. Here, we assessed range-wide patterns of genetic structure, genetic diversity, gene flow, and local adaptation in the stingless bee Melipona subnitida, a tropical pollinator of key biological and economic importance inhabiting one of the driest and hottest regions of South America. Our results reveal four genetic clusters across the species' full distribution range. All populations were found to be under a mutation-drift equilibrium, and genetic diversity was not influenced by the amount of reminiscent natural habitats. However, genetic relatedness was spatially autocorrelated and isolation by landscape resistance explained range-wide relatedness patterns better than isolation by geographic distance, contradicting earlier findings for stingless bees. Specifically, gene flow was enhanced by increased thermal stability, higher forest cover, lower elevations, and less corrugated terrains. Finally, we detected genomic signatures of adaptation to temperature, precipitation, and forest cover, spatially distributed in latitudinal and altitudinal patterns. Taken together, our findings shed important light on the life history of M. subnitida and highlight the role of regions with large thermal fluctuations, deforested areas, and mountain ranges as dispersal barriers. Conservation actions such as restricting long-distance colony transportation, preserving local adaptations, and improving the connectivity between highlands and lowlands are likely to assure future pollination services.

Everything you always wanted to know about gene flow in tropical landscapes (but were afraid to ask)

The bulk of the world’s biodiversity is found in tropical regions, which are increasingly threatened by the human-led degradation of natural habitats. Yet, little is known about tropical biodiversity responses to habitat loss and fragmentation. Here we review all available literature assessing landscape effects on gene flow in tropical species, aiming to help unravel the factors underpinning functional connectivity in the tropics. We map and classify studies by focus species, the molecular markers employed, statistical approaches to assess landscape effects on gene flow, and the evaluated landscape and environmental variables. We then compare qualitatively and quantitatively landscape effects on gene flow across species and units of analysis. We found 69 articles assessing landscape effects on gene flow in tropical organisms, most of which were published in the last five years, were concentrated in the Americas, and focused on amphibians or mammals. Most studies employed population-level approaches, microsatellites were the preferred type of markers, and Mantel and partial Mantel tests the most common statistical approaches used. While elevation, land cover and forest cover were the most common gene flow predictors assessed, habitat suitability was found to be a common predictor of gene flow. A third of all surveyed studies explicitly assessed the effect of habitat degradation, but only 14 of these detected a reduced gene flow with increasing habitat loss. Elevation was responsible for most significant microsatellite-based isolation by resistance effects and a single study reported significant isolation by non-forested areas in an ant. Our study reveals important knowledge gaps on the study of landscape effects on gene flow in tropical organisms, and provides useful guidelines on how to fill them.

Habitat Fragmentation Reduces Genetic Diversity and Connectivity of the Mexican Spotted Owl: A Simulation Study Using Empirical Resistance Models

We evaluated how differences between two empirical resistance models for the same geographic area affected predictions of gene flow processes and genetic diversity for the Mexican spotted owl (Strix occidentalis lucida). The two resistance models represented the landscape under low- and high-fragmentation parameters. Under low fragmentation, the landscape had larger but highly concentrated habitat patches, whereas under high fragmentation, the landscape had smaller habitat patches that scattered across a broader area. Overall habitat amount differed little between resistance models. We tested eight scenarios reflecting a factorial design of three factors: resistance model (low vs. high fragmentation), isolation hypothesis (isolation-by-distance, IBD, vs. isolation-by-resistance, IBR), and dispersal limit of species (200 km vs. 300 km). Higher dispersal limit generally had a positive but small influence on genetic diversity. Genetic distance increased with both geographic distance and landscape resistance, but landscape resistance displayed a stronger influence. Connectivity was positively related to genetic diversity under IBR but was less important under IBD. Fragmentation had a strong negative influence on the spatial patterns of genetic diversity and effective population size (Ns). Despite habitats being more concentrated and less widely distributed, the low-fragmentation landscape had greater genetic diversity than the high-fragmentation landscape, suggesting that highly concentrated but larger habitat patches may provide a genetic refuge for the Mexican spotted owl.

Functional connectivity in replicated urban landscapes in the land snail (Cornu aspersum)

Urban areas are highly fragmented and thereby exert strong constraints on individual dispersal. Despite this, some species manage to persist in urban areas, such as the garden snail, Cornu aspersum, which is common in cityscapes despite its low mobility. Using landscape genetic approaches, we combined study area replication and multiscale analysis to determine how landscape composition, configuration and connectivity influence snail dispersal across urban areas. At the overall landscape scale, areas with a high percentage of roads decreased genetic differentiation between populations. At the population scale, genetic differentiation was positively linked with building surface, the proportion of borders where wooded patches and roads appeared side by side and the proportion of borders combining wooded patches and other impervious areas. Analyses based on pairwise genetic distances validated the isolation-by-distance and isolation-by-resistance models for this land snail, with an equal fit to least-cost paths and circuit-theory-based models. Each of the 12 landscapes analysed separately yielded specific relations to environmental features, whereas analyses integrating all replicates highlighted general common effects. Our results suggest that urban transport infrastructures facilitate passive snail dispersal. At a local scale, corresponding to active dispersal, unfavourable habitats (wooded and impervious areas) isolate populations. This work upholds the use of replicated landscapes to increase the generalizability of landscape genetics results and shows how multiscale analyses provide insight into scale-dependent processes.

Geography and Environment Shape Landscape Genetics of Mediterranean Alpine Species Silene ciliata Poiret. (Caryophyllaceae)

The study of the drivers that shape spatial genetic structure across heterogeneous landscapes is one of the main approaches used to understand population dynamics and responses in changing environments. While the Isolation-by-Distance model (IBD) assumes that genetic differentiation increases among populations with geographical distance, the Isolation-by-Resistance model (IBR) also considers geographical barriers and other landscape features that impede gene flow. On the other hand, the Isolation-by-Environment model (IBE) explains genetic differentiation through environmental differences between populations. Although spatial genetic studies have increased significantly in recent years, plants from alpine ecosystems are highly underrepresented, even though they are great suitable systems to disentangle the role of the different factors that structure genetic variation across environmental gradients. Here, we studied the spatial genetic structure of the Mediterranean alpine specialist Silene ciliata across its southernmost distribution limit. We sampled three populations across an altitudinal gradient from 1850 to 2400 m, and we replicated this sample over three mountain ranges aligned across an E-W axis in the central part of the Iberian Peninsula. We genotyped 20 individuals per population based on eight microsatellite markers and used different landscape genetic tools to infer the role of topographic and environmental factors in shaping observed patterns along the altitudinal gradient. We found a significant genetic structure among the studied Silene ciliata populations which was related to the orography and E-W configuration of the mountain ranges. IBD pattern arose as the main factor shaping population genetic differentiation. Geographical barriers between mountain ranges also affected the spatial genetic structure (IBR pattern). Although environmental variables had a significant effect on population genetic diversity parameters, no IBE pattern was found on genetic structure. Our study reveals that IBD was the driver that best explained the genetic structure, whereas environmental factors also played a role in determining genetic diversity values of this dominant plant of Mediterranean alpine environments.