A pinboard by
Jan Engler

I'm a biologist with a keen interest in birds and how environmental changes affect species distributions across spatial scales.

I like to learn about the world and to contribute to World's knowledge. Next to my research, I want to support early career researcher to become better scientists


Key papers on how landscape affect genetic exchange and might lead to adaptive processes

The distribution of genetic diversity emerges from myriads of individual decisions where to go and how successful these individuals are to find a mate and successfully pass their genetic legacy to the next generation. In most species, the landscape in which they life offers drives individual movement decisions in which some landscape elements can act as barriers while others become highways of genetic exchange. The field of landscape genetics combines spatial tools from landscape ecology with genetic methods from molecular ecology to understand how landscapes dive this functional connectivity that maintain population networks and hence species distributions. This pinboard lists key references of the field to provide a concise overview to anyone who would like to start in this field.


Adaptive vs. neutral genetic diversity: implications for landscape genetics

Abstract: Genetic diversity is important for the maintenance of the viability and the evolutionary or adaptive potential of populations and species. However, there are two principal types of genetic diversity: adaptive and neutral – a fact widely neglected by non-specialists. We introduce these two types of genetic diversity and critically point to their potential uses and misuses in population or landscape genetic studies. First, most molecular-genetic laboratory techniques analyse neutral genetic variation. This means that the gene variants detected do not have any direct effect on fitness. This type of genetic variation is thus selectively neutral and tells us nothing about the adaptive or evolutionary potential of a population or a species. Nevertheless, neutral genetic markers have great potential for investigating processes such as gene flow, migration or dispersal. Hence, they allow us to empirically test the functional relevance of spatial indices such as connectivity used in landscape ecology. Second, adaptive genetic variation, i.e. genetic variation under natural selection, is analysed in quantitative genetic experiments under controlled and uniform environmental conditions. Unfortunately, the genetic variation (i.e. heritability) and population differentiation at quantitative, adaptive traits is not directly linked with neutral genetic diversity or differentiation. Thus, neutral genetic data cannot serve as a surrogate of adaptive genetic data. In summary, neutral genetic diversity is well suited for the study of processes within landscapes such as gene flow, while the evolutionary or adaptive potential of populations or species has to be assessed in quantitative genetic experiments. Landscape ecologists have to mind these differences between neutral and adaptive genetic variation when interpreting the results of landscape genetic studies.

Pub.: 01 Aug '06, Pinned: 25 Sep '17

Landscape genetics: where are we now?

Abstract: Landscape genetics has seen rapid growth in number of publications since the term was coined in 2003. An extensive literature search from 1998 to 2008 using keywords associated with landscape genetics yielded 655 articles encompassing a vast array of study organisms, study designs and methodology. These publications were screened to identify 174 studies that explicitly incorporated at least one landscape variable with genetic data. We systematically reviewed this set of papers to assess taxonomic and temporal trends in: (i) geographic regions studied; (ii) types of questions addressed; (iii) molecular markers used; (iv) statistical analyses used; and (v) types and nature of spatial data used. Overall, studies have occurred in geographic regions proximal to developed countries and more commonly in terrestrial vs. aquatic habitats. Questions most often focused on effects of barriers and/or landscape variables on gene flow. The most commonly used molecular markers were microsatellites and amplified fragment length polymorphism (AFLPs), with AFLPs used more frequently in plants than animals. Analysis methods were dominated by Mantel and assignment tests. We also assessed differences among journals to evaluate the uniformity of reporting and publication standards. Few studies presented an explicit study design or explicit descriptions of spatial extent. While some landscape variables such as topographic relief affected most species studied, effects were not universal, and some species appeared unaffected by the landscape. Effects of habitat fragmentation were mixed, with some species altering movement paths and others unaffected. Taken together, although some generalities emerged regarding effects of specific landscape variables, results varied, thereby reinforcing the need for species-specific work. We conclude by: highlighting gaps in knowledge and methodology, providing guidelines to authors and reviewers of landscape genetics studies, and suggesting promising future directions of inquiry.

Pub.: 21 Aug '10, Pinned: 25 Sep '17

A new analytical approach to landscape genetic modelling: least-cost transect analysis and linear mixed models.

Abstract: Landscape genetics aims to assess the effect of the landscape on intraspecific genetic structure. To quantify interdeme landscape structure, landscape genetics primarily uses landscape resistance surfaces (RSs) and least-cost paths or straight-line transects. However, both approaches have drawbacks. Parameterization of RSs is a subjective process, and least-cost paths represent a single migration route. A transect-based approach might oversimplify migration patterns by assuming rectilinear migration. To overcome these limitations, we combined these two methods in a new landscape genetic approach: least-cost transect analysis (LCTA). Habitat-matrix RSs were used to create least-cost paths, which were subsequently buffered to form transects in which the abundance of several landscape elements was quantified. To maintain objectivity, this analysis was repeated so that each landscape element was in turn regarded as migration habitat. The relationship between explanatory variables and genetic distances was then assessed following a mixed modelling approach to account for the nonindependence of values in distance matrices. Subsequently, the best fitting model was selected using the statistic. We applied LCTA and the mixed modelling approach to an empirical genetic dataset on the endangered damselfly, Coenagrion mercuriale. We compared the results to those obtained from traditional least-cost, effective and resistance distance analysis. We showed that LCTA is an objective approach that identifies both the most probable migration habitat and landscape elements that either inhibit or facilitate gene flow. Although we believe the statistical approach to be an improvement for the analysis of distance matrices in landscape genetics, more stringent testing is needed.

Pub.: 29 Jun '12, Pinned: 25 Sep '17

How to make landscape genetics beneficial for conservation management?

Abstract: Many landscape genetic studies promise results that can be applied in conservation management. However, only few landscape genetic studies have been used by practitioners. Here, we identified scientific topics in landscape genetics that need to be addressed before results can more successfully be applied in conservation management. For each topic, weaknesses of common practice in landscape genetic analysis are described by presenting examples from current studies and further recommendations for improvements are outlined. First, we suggest matching the extent of the study area with those of conservation management units and the study species’ dispersal potential when designing landscape genetic studies. Second, the quality of the underlying statistical models should be optimised, and models should include variables that are useful for management implementation. Third, to further improve the applicability of landscape genetic studies, thresholds for landscape effects on gene flow should be identified. Fourth, landscape genetic models could be used for the development of conservation planning tools, which ideally also incorporate the above described thresholds. Fifth and as discussed in earlier studies, the use of multiple species and replication at the landscape scale is recommended. Although it appears that only few landscape genetic studies have been applied in practical management until now, examples presented in this article show that landscape genetic methods can provide important information to formulate concrete management implications. Thus, addressing the above-mentioned scientific topics in landscape genetic studies would enhance the benefits of their results for practitioners.

Pub.: 18 Dec '14, Pinned: 25 Sep '17

Comparative landscape genetics of two frugivorous bats in a biological corridor undergoing agricultural intensification.

Abstract: Agricultural intensification in tropical landscapes poses a new threat to the ability of biological corridors to maintain functional connectivity for native species. We use a landscape genetics approach to evaluate impacts of expanding pineapple plantations on two widespread and abundant frugivorous bats in a biological corridor in Costa Rica. We hypothesize that the larger, more mobile Artibeus jamaicensis will be less impacted by pineapple than the smaller Carollia castanea. In 2012 and 2013, we sampled 735 bats in 26 remnant forest patches surrounded by different proportions of forest, pasture, crops, and pineapple. We used 10 microsatellite loci for A. jamaicensis and 16 microsatellite loci for C. castanea to estimate genetic diversity and gene flow. Canonical correspondence analyses indicate that land cover type surrounding patches has no impact on genetic diversity of A. jamaicensis. However, for C. castanea, both percentage forest and pineapple surrounding patches explained a significant proportion of the variation in genetic diversity. Least-cost transect analyses (LCTA) and pairwise G"st suggest that for A. jamaicensis, pineapple is more permeable to gene flow than expected, while as expected, forest is the most permeable land cover for gene flow of C. castanea. For both species, LCTA indicate that development may play a role in inhibiting gene flow. The current study answers the call for landscape genetic research focused on tropical and agricultural landscapes, highlights the value of comparative landscape genetics in biological corridor design and management, and is one of the few studies of biological corridors in any ecosystem to implement a genetic approach to test corridor efficacy. This article is protected by copyright. All rights reserved.

Pub.: 04 Jul '17, Pinned: 25 Sep '17

Amphibian population genetics in agricultural landscapes: does viniculture drive the population structuring of the European common frog (Rana temporaria)?

Abstract: Amphibian populations have been declining globally over the past decades. The intensification of agriculture, habitat loss, fragmentation of populations and toxic substances in the environment are considered as driving factors for this decline. Today, about 50% of the area of Germany is used for agriculture and is inhabited by a diverse variety of 20 amphibian species. Of these, 19 are exhibiting declining populations. Due to the protection status of native amphibian species, it is important to evaluate the effect of land use and associated stressors (such as road mortality and pesticide toxicity) on the genetic population structure of amphibians in agricultural landscapes. We investigated the effects of viniculture on the genetic differentiation of European common frog (Rana temporaria) populations in Southern Palatinate (Germany). We analyzed microsatellite data of ten loci from ten breeding pond populations located within viniculture landscape and in the adjacent forest block and compared these results with a previously developed landscape permeability model. We tested for significant correlation of genetic population differentiation and landscape elements, including land use as well as roads and their associated traffic intensity, to explain the genetic structure in the study area. Genetic differentiation among forest populations was significantly lower (median pairwise FST = 0.0041 at 5.39 km to 0.0159 at 9.40 km distance) than between viniculture populations (median pairwise FST = 0.0215 at 2.34 km to 0.0987 at 2.39 km distance). Our analyses rejected isolation by distance based on roads and associated traffic intensity as the sole explanation of the genetic differentiation and suggest that the viniculture landscape has to be considered as a limiting barrier for R. temporaria migration, partially confirming the isolation of breeding ponds predicted by the landscape permeability model. Therefore, arable land may act as a sink habitat, inhibiting genetic exchange and causing genetic differentiation of pond populations in agricultural areas. In viniculture, pesticides could be a driving factor for the observed genetic impoverishment, since pesticides are more frequently applied than any other management measure and can be highly toxic for terrestrial life stages of amphibians.

Pub.: 18 Jul '17, Pinned: 25 Sep '17

Landscape genetic analyses reveal fine-scale effects of forest fragmentation in an insular tropical bird.

Abstract: Within the framework of landscape genetics, resistance surface modelling is particularly relevant to explicitly test competing hypotheses about landscape effects on gene flow. To investigate how fragmentation of tropical forest affects population connectivity in a forest-specialist bird species, we optimized resistance surfaces without a priori specification, using least-cost (LCP) or resistance (IBR) distances. We implemented a two-step procedure in order i) to objectively define the landscape thematic resolution (level of detail in classification scheme to describe landscape variables) and spatial extent (area within the landscape boundaries) and then ii) to test the relative role of several landscape features (elevation, roads, land cover) in genetic differentiation in the Plumbeous Warbler (Setophaga plumbea). We detected a small-scale reduction of gene flow mainly driven by land cover, with a negative impact of the non-forest matrix on landscape functional connectivity. However, matrix components did not equally constrain gene flow, as their conductivity increased with increasing structural similarity with forest habitat: urban areas and meadows had the highest resistance values whereas agricultural areas had intermediate resistance values. Our results revealed a higher performance of IBR compared to LCP in explaining gene flow, reflecting sub-optimal movements across this human-modified landscape, challenging the common use of LCP to design habitat corridors and advocating for a broader use of circuit theory modelling. Finally, our results emphasize the need for an objective definition of landscape scales (landscape extent and thematic resolution) and highlight potential pitfalls associated with parameterization of resistance surfaces. This article is protected by copyright. All rights reserved.

Pub.: 21 Jul '17, Pinned: 25 Sep '17

Comparative landscape genetics of pond-breeding amphibians in Mediterranean temporal wetlands: the positive role of structural heterogeneity in promoting gene flow.

Abstract: Comparative landscape genetics studies can provide key information to implement cost-effective conservation measures favoring a broad set of taxa. These studies are scarce, particularly in Mediterranean areas, which include diverse but threatened biological communities. Here we focus on Mediterranean wetlands in central Iberia and perform a multi-level, comparative study of two endemic pond-breeding amphibians, a salamander (Pleurodeles waltl) and a toad (Pelobates cultripes). We genotyped 411 salamanders from 20 populations and 306 toads from 16 populations at 18 and 16 microsatellite loci, respectively, and identified major factors associated with population connectivity through the analysis of three sets of variables potentially affecting gene flow at increasingly finer levels of spatial resolution. Topographic, land use/cover, and remotely sensed vegetation/moisture indices were used to derive optimized resistance surfaces for the two species. We found contrasting patterns of genetic structure, with stronger, finer-scale genetic differentiation in Pleurodeles waltl, and notable differences in the role of fine-scale patterns of heterogeneity in vegetation cover and water content in shaping patterns of regional genetic structure in the two species. Overall, our results suggest a positive role of structural heterogeneity in population connectivity in pond-breeding amphibians, with habitat patches of Mediterranean scrubland and open oak woodlands ("dehesas") facilitating gene flow. Our study highlights the usefulness of remotely sensed continuous variables of land cover, vegetation and water content (e.g., NDVI, NDMI) in conservation-oriented studies aimed at identifying major drivers of population connectivity. This article is protected by copyright. All rights reserved.

Pub.: 29 Jul '17, Pinned: 25 Sep '17

A simulation-based evaluation of methods for inferring linear barriers to gene flow.

Abstract: Different analytical techniques used on the same data set may lead to different conclusions about the existence and strength of genetic structure. Therefore, reliable interpretation of the results from different methods depends on the efficacy and reliability of different statistical methods. In this paper, we evaluated the performance of multiple analytical methods to detect the presence of a linear barrier dividing populations. We were specifically interested in determining if simulation conditions, such as dispersal ability and genetic equilibrium, affect the power of different analytical methods for detecting barriers. We evaluated two boundary detection methods (Monmonier's algorithm and WOMBLING), two spatial Bayesian clustering methods (TESS and GENELAND), an aspatial clustering approach (STRUCTURE), and two recently developed, non-Bayesian clustering methods [PSMIX and discriminant analysis of principal components (DAPC)]. We found that clustering methods had higher success rates than boundary detection methods and also detected the barrier more quickly. All methods detected the barrier more quickly when dispersal was long distance in comparison to short-distance dispersal scenarios. Bayesian clustering methods performed best overall, both in terms of highest success rates and lowest time to barrier detection, with GENELAND showing the highest power. None of the methods suggested a continuous linear barrier when the data were generated under an isolation-by-distance (IBD) model. However, the clustering methods had higher potential for leading to incorrect barrier inferences under IBD unless strict criteria for successful barrier detection were implemented. Based on our findings and those of previous simulation studies, we discuss the utility of different methods for detecting linear barriers to gene flow.

Pub.: 04 May '12, Pinned: 25 Sep '17

A comparative framework to infer landscape effects on population genetic structure: are habitat suitability models effective in explaining gene flow?

Abstract: Most current methods to assess connectivity begin with landscape resistance maps. The prevailing resistance models are commonly based on expert opinion and, more recently, on a direct transformation of habitat suitability. However, habitat associations are not necessarily accurate indicators of dispersal, and thus may fail as a surrogate of resistance to movement. Genetic data can provide valuable insights in this respect.We aim at directly comparing the utility of habitat suitability models for estimating landscape resistance versus other approaches based on actual connectivity data.We develop a framework to compare landscape resistance models based on (1) a genetic-based multi model optimization and (2) a direct conversion of habitat suitability into landscape resistance. We applied this framework to the endangered brown bear in the Cantabrian Range (NW Spain).We found that the genetic-based optimization produced a resistance model that was more related to species movement than were models produced by direct conversion of habitat suitability. Certain land cover types and transport infrastructures were restrictive factors for species occurrence, but did not appear to impede the brown bear movements that determined observed genetic structure.In this study case, habitat suitability is not synonymous with permeability for dispersal, and does not seem to provide the best way to estimate actual landscape resistance. We highlight the general utility of this comparative approach to provide a comprehensive and practical assessment of factors involved in species movements, with the final aim of improving the initiatives to enhance landscape connectivity in conservation planning.

Pub.: 02 Apr '15, Pinned: 25 Sep '17

A plea for simultaneously considering matrix quality and local environmental conditions when analysing landscape impacts on effective dispersal.

Abstract: Landscape genetics has tremendous potential for enhancing our understanding about landscape effects on effective dispersal and resulting genetic structures. However, the vast majority of landscape genetic studies focus on effects of the landscape among sampling locations on dispersal (i.e. matrix quality), while effects of local environmental conditions are rather neglected. Such local environmental conditions include patch size, habitat type or resource availability and are commonly used in (meta-) population ecology and population genetics. In our opinion, landscape genetic studies would greatly benefit from simultaneously incorporating both matrix quality and local environmental conditions when assessing landscape effects on effective dispersal. To illustrate this point, we first outline the various ways in which environmental heterogeneity can influence different stages of the dispersal process. We then propose a three-step approach for assessing local and matrix effects on effective dispersal and review how both types of effects can be considered in landscape genetic analyses. Using simulated data, we show that it is possible to correctly disentangle the relative importance of matrix quality vs. local environmental conditions for effective dispersal. We argue that differentiating local and matrix effects in such a way is crucial for predicting future species distribution and persistence, and for optimal conservation decisions that are based on landscape genetics. In sum, we think it is timely to move beyond purely statistical, pattern-oriented analyses in landscape genetics and towards process-oriented approaches that consider the full range of possible landscape effects on dispersal behaviour and resulting gene flow.

Pub.: 13 Mar '14, Pinned: 25 Sep '17

Molecular road ecology: exploring the potential of genetics for investigating transportation impacts on wildlife.

Abstract: Transportation infrastructures such as roads, railroads and canals can have major environmental impacts. Ecological road effects include the destruction and fragmentation of habitat, the interruption of ecological processes and increased erosion and pollution. Growing concern about these ecological road effects has led to the emergence of a new scientific discipline called road ecology. The goal of road ecology is to provide planners with scientific advice on how to avoid, minimize or mitigate negative environmental impacts of transportation. In this review, we explore the potential of molecular genetics to contribute to road ecology. First, we summarize general findings from road ecology and review studies that investigate road effects using genetic data. These studies generally focus only on barrier effects of roads on local genetic diversity and structure and only use a fraction of available molecular approaches. Thus, we propose additional molecular applications that can be used to evaluate road effects across multiple scales and dimensions of the biodiversity hierarchy. Finally, we make recommendations for future research questions and study designs that would advance molecular road ecology. Our review demonstrates that molecular approaches can substantially contribute to road ecology research and that interdisciplinary, long-term collaborations will be particularly important for realizing the full potential of molecular road ecology.

Pub.: 08 Sep '09, Pinned: 25 Sep '17

Use of resistance surfaces for landscape genetic studies: considerations for parameterization and analysis.

Abstract: Measures of genetic structure among individuals or populations collected at different spatial locations across a landscape are commonly used as surrogate measures of functional (i.e. demographic or genetic) connectivity. In order to understand how landscape characteristics influence functional connectivity, resistance surfaces are typically created in a raster GIS environment. These resistance surfaces represent hypothesized relationships between landscape features and gene flow, and are based on underlying biological functions such as relative abundance or movement probabilities in different land cover types. The biggest challenge for calculating resistance surfaces is assignment of resistance values to different landscape features. Here, we first identify study objectives that are consistent with the use of resistance surfaces and critically review the various approaches that have been used to parameterize resistance surfaces and select optimal models in landscape genetics. We then discuss the biological assumptions and considerations that influence analyses using resistance surfaces, such as the relationship between gene flow and dispersal, how habitat suitability may influence animal movement, and how resistance surfaces can be translated into estimates of functional landscape connectivity. Finally, we outline novel approaches for creating optimal resistance surfaces using either simulation or computational methods, as well as alternatives to resistance surfaces (e.g. network and buffered paths). These approaches have the potential to improve landscape genetic analyses, but they also create new challenges. We conclude that no single way of using resistance surfaces is appropriate for every situation. We suggest that researchers carefully consider objectives, important biological assumptions and available parameterization and validation techniques when planning landscape genetic studies.

Pub.: 21 Aug '10, Pinned: 25 Sep '17