Landscape genetics as a tool for conservation planning: predicting the effects of landscape change on gene flow

Individual-based landscape genomics for conservation: An analysis pipeline

Landscape genomics can harness environmental and genetic data to inform conservation decisions by providing essential insights into how landscapes shape biodiversity. The massive increase in genetic data afforded by the genomic era provides exceptional resolution for answering critical conservation genetics questions. The accessibility of genomic data for non-model systems has also enabled a shift away from population-based sampling to individual-based sampling, which now provides accurate and robust estimates of genetic variation that can be used to examine the spatial structure of genomic diversity, population connectivity and the nature of environmental adaptation. Nevertheless, the adoption of individual-based sampling in conservation genetics has been slowed due, in large part, to concerns over how to apply methods developed for population-based sampling to individual-based sampling schemes. Here, we discuss the benefits of individual-based sampling for conservation and describe how landscape genomic methods, paired with individual-based sampling, can answer fundamental conservation questions. We have curated key landscape genomic methods into a user-friendly, open-source workflow, which we provide as a new R package, A Landscape Genomics Analysis Toolkit in R (algatr). The algatr package includes novel added functionality for all of the included methods and extensive vignettes designed with the primary goal of making landscape genomic approaches more accessible and explicitly applicable to conservation biology.

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.

Genetic structure of recently fragmented suburban populations of European stag beetle

Habitat loss and fragmentation due to urbanization can negatively affect metapopulation persistence when gene flow among populations is reduced and population sizes decrease. Inference of patterns and processes of population connectivity derived from spatial genetic analysis has proven invaluable for conservation and management. However, a more complete account of population dynamics may be obtained by combining spatial and temporal sampling. We, therefore, performed a genetic study on European stag beetle (Lucanus cervus L.) populations in a suburban context using samples collected in three locations and during the period 2002-2016. The sampling area has seen recent landscape changes which resulted in population declines. Through the use of a suite of F ST, clustering analysis, individual assignment, and relatedness analysis, we assessed fine scale spatiotemporal genetic variation within and among habitat patches using 283 individuals successfully genotyped at 17 microsatellites. Our findings suggested the three locations to hold demographically independent populations, at least over time scales of relevance to conservation, though with higher levels of gene flow in the past. Contrary to expectation from tagging studies, dispersal appeared to be mainly female-biased. Although the life cycle of stag beetle suggests its generations to be discrete, no clear temporal structure was identified, which could be attributed to the varying duration of larval development. Since population bottlenecks were detected and estimates of effective number of breeders were low, conservation actions are eminent which should include the establishment of suitable dead wood for oviposition on both local and regional scales to increase (re)colonization success and connectivity among current populations.

Contribution of Connectivity Assessments to Green Infrastructure (GI)

A major goal of green infrastructure (GI) is to provide functional networks of habitats and ecosystems to maintain biodiversity long-term, while at the same time optimizing landscape and ecosystem functions and services to meet human needs. Traditionally, connectivity studies are informed by movement ecology with species-specific attributes of the type and timing of movement (e.g., dispersal, foraging, mating) and movement distances, while spatial environmental data help delineate movement pathways across landscapes. To date, a range of methods and approaches are available that (a) are relevant across any organism and movement type independent of time and space scales, (b) are ready-to-use as standalone freeware or custom GIS implementation, and (c) produce appealing visual outputs that facilitate communication with land managers. However, to enhance the robustness of connectivity assessments and ensure that current trends in connectivity modeling contribute to GI with their full potential, common denominators on which to ground planning and design strategies are required. Likewise, comparable, repeatable connectivity assessments will be needed to put results of these scientific tools into practice for multi-functional GI plans and implementation. In this paper, we discuss use and limitations of state-of-the-art connectivity methods in contributing to GI implementation.

Feeding and Mobility Traits Influence Grasshopper Vulnerability to Agricultural Production in the Cape Floristic Region Biodiversity Hotspot

To be able to foretell which species will be at risk of extinction from possible expansion of agriculture into natural areas, we need to determine how land use affects animal groups especially insects with different life history traits. Intuitively, we can predict that the proportion of specialist versus generalist grasshoppers and widespread versus localised species can be an indicator of change in vegetation patterns in a landscape. As a result, the study examined the relationship between the extent of range distribution and mobility of grasshoppers and land-use type in the Cape Floristic Region (CFR) biodiversity hotspot. It aimed at examining grasshopper assemblage composition in association with different land uses. We specifically related the number and type of sites occupied by grasshopper species to their mobility and distribution type to find out which characters improve species survival under highly modified habitats. Grasshopper assemblages were dominated by highly mobile generalists that tolerated transformed landscapes, and mostly geographically widespread. This contrasts with the low- to medium-mobile, range-restricted specialists, which make up close to 30% of the total collection, with a lower tolerance for anthropogenically modified landscapes in the CFR. This study also reveal that the fynbos biome is an important habitat for low-mobility and range-restricted species, and hence require conscious conservation efforts to conserve such species to prevent possible future biotic erosion and homogenisation in this hotspot. This result can be used to assess the possible extent of biotic erosion or otherwise in order to recommend better conservation efforts in the CFR.

Predicting species occurrences with habitat network models

Biodiversity conservation requires modeling tools capable of predicting the presence or absence (i.e., occurrence-state) of species in habitat patches. Local habitat characteristics of a patch (lh), the cost of traversing the landscape matrix between patches (weighted connectivity [wc]), and the position of the patch in the habitat network topology (nt) all influence occurrence-state. Existing models are data demanding or consider only local habitat characteristics. We address these shortcomings and present a network-based modeling approach, which aims to predict species occurrence-state in habitat patches using readily available presence-only records.For the tree frog Hyla arborea in the Swiss Plateau, we delineated habitat network nodes from an ensemble habitat suitability model and used different cost surfaces to generate the edges of three networks: one limited only by dispersal distance (Uniform), another incorporating traffic, and a third based on inverse habitat suitability. For each network, we calculated explanatory variables representing the three categories (lh, wc, and nt). The response variable, occurrence-state, was parametrized by a sampling intensity procedure assessing observations of comparable species over a threshold of patch visits. The explanatory variables from the three networks and an additional non-topological model were related to the response variable with boosted regression trees.The habitat network models had a similar fit; they all outperformed the non-topological model. Habitat suitability index (lh) was the most important predictor in all networks, followed by third-order neighborhood (nt). Patch size (lh) was unimportant in all three networks.We found that topological variables of habitat networks are relevant for the prediction of species occurrence-state, a step-forward from models considering only local habitat characteristics. For any habitat patch, occurrence-state is most prominently influenced by its habitat suitability and then by the number of patches in a wide neighborhood. Our approach is generic and can be applied to multiple species in different habitats.

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.

Landscape genetics identifies streams and drainage infrastructure as dispersal corridors for an endangered wetland bird

Anthropogenic alterations to landscape structure and composition can have significant impacts on biodiversity, potentially leading to species extinctions. Population‐level impacts of landscape change are mediated by animal behaviors, in particular dispersal behavior. Little is known about the dispersal habits of rails (Rallidae) due to their cryptic behavior and tendency to occupy densely vegetated habitats. The effects of landscape structure on the movement behavior of waterbirds in general are poorly studied due to their reputation for having high dispersal abilities. We used a landscape genetic approach to test hypotheses of landscape effects on dispersal behavior of the Hawaiian gallinule (Gallinula galeata sandvicensis), an endangered subspecies endemic to the Hawaiian Islands. We created a suite of alternative resistance surfaces representing biologically plausible a priori hypotheses of how gallinules might navigate the landscape matrix and ranked these surfaces by their ability to explain observed patterns in genetic distance among 12 populations on the island of O`ahu. We modeled effective distance among wetland locations on all surfaces using both cumulative least‐cost‐path and resistance‐distance approaches and evaluated relative model performance using Mantel tests, a causal modeling approach, and the mixed‐model maximum‐likelihood population‐effects framework. Across all genetic markers, simulation methods, and model comparison metrics, surfaces that treated linear water features like streams, ditches, and canals as corridors for gallinule movement outperformed all other models. This is the first landscape genetic study on the movement behavior of any waterbird species to our knowledge. Our results indicate that lotic water features, including drainage infrastructure previously thought to be of minimal habitat value, contribute to habitat connectivity in this listed subspecies.

Alpine glacial relict species losing out to climate change: The case of the fragmented mountain hare population (Lepus timidus) in the Alps

Alpine and Arctic species are considered to be particularly vulnerable to climate change, which is expected to cause habitat loss, fragmentation and-ultimately-extinction of cold-adapted species. However, the impact of climate change on glacial relict populations is not well understood, and specific recommendations for adaptive conservation management are lacking. We focused on the mountain hare (Lepus timidus) as a model species and modelled species distribution in combination with patch and landscape-based connectivity metrics. They were derived from graph-theory models to quantify changes in species distribution and to estimate the current and future importance of habitat patches for overall population connectivity. Models were calibrated based on 1,046 locations of species presence distributed across three biogeographic regions in the Swiss Alps and extrapolated according to two IPCC scenarios of climate change (RCP 4.5 & 8.5), each represented by three downscaled global climate models. The models predicted an average habitat loss of 35% (22%-55%) by 2100, mainly due to an increase in temperature during the reproductive season. An increase in habitat fragmentation was reflected in a 43% decrease in patch size, a 17% increase in the number of habitat patches and a 34% increase in inter-patch distance. However, the predicted changes in habitat availability and connectivity varied considerably between biogeographic regions: Whereas the greatest habitat losses with an increase in inter-patch distance were predicted at the southern and northern edges of the species' Alpine distribution, the greatest increase in patch number and decrease in patch size is expected in the central Swiss Alps. Finally, both the number of isolated habitat patches and the number of patches crucial for maintaining the habitat network increased under the different variants of climate change. Focusing conservation action on the central Swiss Alps may help mitigate the predicted effects of climate change on population connectivity.

Multi-scale and multi-site resampling of a study area in spatial genetics: implications for flying insect species

The use of multiple sampling areas in landscape genetic analysis has been recognized as a useful way of generalizing the patterns of environmental effects on organism gene flow. It reduces the variability in inference which can be substantially affected by the scale of the study area and its geographic location. However, empirical landscape genetic studies rarely consider multiple sampling areas due to the sampling effort required. In this study, we explored the effects of environmental features on the gene flow of a flying long-horned beetle (Monochamus galloprovincialis) using a landscape genetics approach. To account for the unknown scale of gene flow and the multiple local confounding effects of evolutionary history and landscape changes on inference, we developed a way of resampling study areas on multiple scales and in multiple locations (sliding windows) in a single large-scale sampling design. Landscape analyses were conducted in 3*104 study areas ranging in scale from 220 to 1,000 km and spread over 132 locations on the Iberian Peninsula. The resampling approach made it possible to identify the features affecting the gene flow of this species but also showed high variability in inference among the scales and the locations tested, independent of the variation in environmental features. This method provides an opportunity to explore the effects of environmental features on organism gene flow on the whole and reach conclusions about general landscape effects on their dispersal, while limiting the sampling effort to a reasonable level.

Detecting black bear source-sink dynamics using individual-based genetic graphs

Source-sink dynamics affects population connectivity, spatial genetic structure and population viability for many species. We introduce a novel approach that uses individual-based genetic graphs to identify source-sink areas within a continuously distributed population of black bears (Ursus americanus) in the northern lower peninsula (NLP) of Michigan, USA. Black bear harvest samples (n = 569, from 2002, 2006 and 2010) were genotyped at 12 microsatellite loci and locations were compared across years to identify areas of consistent occupancy over time. We compared graph metrics estimated for a genetic model with metrics from 10 ecological models to identify ecological factors that were associated with sources and sinks. We identified 62 source nodes, 16 of which represent important source areas (net flux > 0.7) and 79 sink nodes. Source strength was significantly correlated with bear local harvest density (a proxy for bear density) and habitat suitability. Additionally, resampling simulations showed our approach is robust to potential sampling bias from uneven sample dispersion. Findings demonstrate black bears in the NLP exhibit asymmetric gene flow, and individual-based genetic graphs can characterize source-sink dynamics in continuously distributed species in the absence of discrete habitat patches. Our findings warrant consideration of undetected source-sink dynamics and their implications on harvest management of game species.

Consequences of population topology for studying gene flow using link-based landscape genetic methods

Many landscape genetic studies aim to determine the effect of landscape on gene flow between populations. These studies frequently employ link‐based methods that relate pairwise measures of historical gene flow to measures of the landscape and the geographical distance between populations. However, apart from landscape and distance, there is a third important factor that can influence historical gene flow, that is, population topology (i.e., the arrangement of populations throughout a landscape). As the population topology is determined in part by the landscape configuration, I argue that it should play a more prominent role in landscape genetics. Making use of existing literature and theoretical examples, I discuss how population topology can influence results in landscape genetic studies and how it can be taken into account to improve the accuracy of these results. In support of my arguments, I have performed a literature review of landscape genetic studies published during the first half of 2015 as well as several computer simulations of gene flow between populations. First, I argue why one should carefully consider which population pairs should be included in link‐based analyses. Second, I discuss several ways in which the population topology can be incorporated in response and explanatory variables. Third, I outline why it is important to sample populations in such a way that a good representation of the population topology is obtained. Fourth, I discuss how statistical testing for link‐based approaches could be influenced by the population topology. I conclude the article with six recommendations geared toward better incorporating population topology in link‐based landscape genetic studies.

Population genetic and field-ecological analyses return similar estimates of dispersal over space and time in an endangered amphibian

The explosive growth of empirical population genetics has seen a proliferation of analytical methods leading to a steady increase in our ability to accurately measure key population parameters, including genetic isolation, effective population size, and gene flow, in natural systems. Assuming they yield similar results, population genetic methods offer an attractive complement to, or replacement of, traditional field‐ecological studies. However, empirical assessments of the concordance between direct field‐ecological and indirect population genetic studies of the same populations are uncommon in the literature. In this study, we investigate genetic isolation, rates of dispersal, and population sizes for the endangered California tiger salamander, Ambystoma californiense, across multiple breeding seasons in an intact vernal pool network. We then compare our molecular results to a previously published study based on multiyear, mark–recapture data from the same breeding sites. We found that field and genetic estimates of population size were only weakly correlated, but dispersal rates were remarkably congruent across studies and methods. In fact, dispersal probability functions derived from genetic data and traditional field‐ecological data were a significant match, suggesting that either method can be used effectively to assess population connectivity. These results provide one of the first explicit tests of the correspondence between landscape genetic and field‐ecological approaches to measuring functional population connectivity and suggest that even single‐year genetic samples can return biologically meaningful estimates of natural dispersal and gene flow.

Assessing the habitat suitability of agricultural landscapes for characteristic breeding bird guilds using landscape metrics

Many of the processes behind the decline of farmland birds can be related to modifications in landscape structure (composition and configuration), which can partly be expressed quantitatively with measurable or computable indices, i.e. landscape metrics. This paper aims to identify statistical relationships between the occurrence of birds and the landscape structure. We present a method that combines two comprehensive procedures: the "landscape-centred approach" and "guild classification". Our study is based on more than 20,000 individual bird observations based on a 4-year bird monitoring approach in a typical agricultural area in the north-eastern German lowlands. Five characteristic bird guilds, each with three characteristic species, are defined for the typical habitat types of that area: farmland, grassland, hedgerow, forest and settlement. The suitability of each sample plot for each guild is indicated by the level of persistence (LOP) of occurrence of three respective species. Thus, the sample plots can be classified as "preferred" or "less preferred" depending on the lower and upper quartiles of the LOP values. The landscape structure is characterized by 16 different landscape metrics expressing various aspects of landscape composition and configuration. For each guild, the three landscape metrics with the strongest rank correlation with the LOP values and that are not mutually dependent were identified. For four of the bird guilds, the classification success was better than 80%, compared with only 66% for the grassland bird guild. A subset of six landscape metrics proved to be the most meaningful and sufficiently classified the sample areas with respect to bird guild suitability. In addition, derived logistic functions allowed the production of guild-specific habitat suitability maps for the whole landscape. The analytical results show that the proposed approach is appropriate to assess the habitat suitability of agricultural landscapes for characteristic bird guilds.

Navigating the pitfalls and promise of landscape genetics

The field of landscape genetics has been evolving rapidly since its emergence in the early 2000s. New applications, techniques and criticisms of techniques appear like clockwork with each new journal issue. The developments are an encouraging, and at times bewildering, sign of progress in an exciting new field of study. However, we suggest that the rapid expansion of landscape genetics has belied important flaws in the development of the field, and we add an air of caution to this breakneck pace of expansion. Specifically, landscape genetic studies often lose sight of the fundamental principles and complex consequences of gene flow, instead favouring simplistic interpretations and broad inferences not necessarily warranted by the data. Here, we describe common pitfalls that characterize such studies, and provide practical guidance to improve landscape genetic investigation, with careful consideration of inferential limits, scale, replication, and the ecological and evolutionary context of spatial genetic patterns. Ultimately, the utility of landscape genetics will depend on translating the relationship between gene flow and landscape features into an understanding of long-term population outcomes. We hope the perspective presented here will steer landscape genetics down a more scientifically sound and productive path, garnering a field that is as informative in the future as it is popular now.

Exotic Fish in Exotic Plantations: A Multi-Scale Approach to Understand Amphibian Occurrence in the Mediterranean Region

Globally, amphibian populations are threatened by a diverse range of factors including habitat destruction and alteration. Forestry practices have been linked with low diversity and abundance of amphibians. The effect of exotic Eucalyptus spp. plantations on amphibian communities has been studied in a number of biodiversity hotspots, but little is known of its impact in the Mediterranean region. Here, we identify the environmental factors influencing the presence of six species of amphibians (the Caudata Pleurodeles waltl, Salamandra salamandra, Lissotriton boscai, Triturus marmoratus and the anurans Pelobates cultripes and Hyla arborea/meridionalis) occupying 88 ponds. The study was conducted in a Mediterranean landscape dominated by eucalypt plantations alternated with traditional use (agricultural, montados and native forest) at three different scales: local (pond), intermediate (400 metres radius buffer) and broad (1000 metres radius buffer). Using the Akaike Information Criterion for small samples (AICc), we selected the top-ranked models for estimating the probability of occurrence of each species at each spatial scale separately and across all three spatial scales, using a combination of covariates from the different magnitudes. Models with a combination of covariates at the different spatial scales had a stronger support than those at individual scales. The presence of predatory fish in a pond had a strong effect on Caudata presence. Permanent ponds were selected by Hyla arborea/meridionalis over temporary ponds. Species occurrence was not increased by a higher density of streams, but the density of ponds impacted negatively on Lissotriton boscai. The proximity of ponds occupied by their conspecifics had a positive effect on the occurrence of Lissotriton boscai and Pleurodeles waltl. Eucalypt plantations had a negative effect on the occurrence of the newt Lissotriton boscai and anurans Hyla arborea/meridionalis, but had a positive effect on the presence of Salamandra salamandra, while no effect on any of the other species was detected. In conclusion, eucalypts had limited effects on the amphibian community at the intermediate and broad scales, but predatory fish had a major impact when considering all the scales combined. The over-riding importance of introduced fish as a negative impact suggests that forest managers should prevent new fish introductions and eradicate fish from already-occupied ponds whenever possible.

Isolation-by-distance in landscapes: considerations for landscape genetics

In landscape genetics, isolation-by-distance (IBD) is regarded as a baseline pattern that is obtained without additional effects of landscape elements on gene flow. However, the configuration of suitable habitat patches determines deme topology, which in turn should affect rates of gene flow. IBD patterns can be characterized either by monotonically increasing pairwise genetic differentiation (for example, FST) with increasing interdeme geographic distance (case-I pattern) or by monotonically increasing pairwise genetic differentiation up to a certain geographical distance beyond which no correlation is detectable anymore (case-IV pattern). We investigated if landscape configuration influenced the rate at which a case-IV pattern changed to a case-I pattern. We also determined at what interdeme distance the highest correlation was measured between genetic differentiation and geographic distance and whether this distance corresponded to the maximum migration distance. We set up a population genetic simulation study and assessed the development of IBD patterns for several habitat configurations and maximum migration distances. We show that the rate and likelihood of the transition of case-IV to case-I FST-distance relationships was strongly influenced by habitat configuration and maximum migration distance. We also found that the maximum correlation between genetic differentiation and geographic distance was not related to the maximum migration distance and was measured across all deme pairs in a case-I pattern and, for a case-IV pattern, at the distance where the FST-distance curve flattens out. We argue that in landscape genetics, separate analyses should be performed to either assess IBD or the landscape effects on gene flow.