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.

For conservation managers, it is important to know whether landscape changes lead to increasing or decreasing gene flow. Although the discipline of landscape genetics assesses the influence of landscape elements on gene flow, no studies have yet used landscape-genetic models to predict gene flow resulting from landscape change. A species that has already been severely affected by landscape change is the large marsh grasshopper (Stethophyma grossum), which inhabits moist areas in fragmented agricultural landscapes in Switzerland. From transects drawn between all population pairs within maximum dispersal distance (< 3 km), we calculated several measures of landscape composition as well as some measures of habitat configuration. Additionally, a complete sampling of all populations in our study area allowed incorporating measures of population topology. These measures together with the landscape metrics formed the predictor variables in linear models with gene flow as response variable (F(ST) and mean pairwise assignment probability). With a modified leave-one-out cross-validation approach, we selected the model with the highest predictive accuracy. With this model, we predicted gene flow under several landscape-change scenarios, which simulated construction, rezoning or restoration projects, and the establishment of a new population. For some landscape-change scenarios, significant increase or decrease in gene flow was predicted, while for others little change was forecast. Furthermore, we found that the measures of population topology strongly increase model fit in landscape genetic analysis. This study demonstrates the use of predictive landscape-genetic models in conservation and landscape planning.

1. Dispersal is an important process for any organism, but especially for endangered species in fragmented landscapes. To enhance the dispersal of a certain species, connectivity measures are implemented, which require knowledge on the species' dispersal behaviour and habitat. It is often assumed, that the preferred reproductive habitat of a species is also used as the main dispersal habitat. Although this assumption has often been confirmed, there are also cases where it has been disproved.2. With a combination of a mark-resight study and genetic analysis conducted in a fragmented agricultural landscape in Switzerland, the dispersal habitats of the threatened damselfly Coenagrion mercuriale were analysed for different distance classes. In addition, maximum dispersal distances were estimated.3. The mark-resight study detected movement over short distances (<= 500 m) mainly within the reproductive habitat of C. mercuriale (i.e. streams).4. In contrast, the genetic study detected both short-and long-distance dispersal. Short-distance dispersal occurred along streams, and discontinuity of streams hindered dispersal. Long-distance dispersal was suggested to happen along more or less straight lines and crossing agricultural land. Genetic analysis also showed that populations were well connected and that few individuals dispersed over larger distances (<= 4500 m).5. Our study showed that connected reproductive habitat enhanced short-distance dispersal in C. mercuriale. Although short-distance dispersal occurred frequently, long-distance dispersal was rare, but important to connect more isolated populations. Therefore, it would be relevant to differentiate between these two dispersal types when planning connectivity measures.

•Mapped suitable habitats are not identified as main dispersal habitats.•Grasshoppers’ habitat connectivity is little affected by an agricultural landscape.•Landscape affects movement of a specialised and less mobile species.

Most landscape genetic studies assess the impact of landscape elements on species' dispersal and gene flow. Many of these studies perform their analysis on all possible population pairs in a study area and do not explicitly consider the effects of spatial scale and population network topology on their results. Here, we examined the effects of spatial scale and population network topology on the outcome of a landscape genetic analysis. Additionally, we tested whether the relevant spatial scale of landscape genetic analysis could be defined by population network topology or by isolation-by-distance (IBD) patterns. A data set of the wetland grasshopper Stethophyma grossum, collected in a fragmented agricultural landscape, was used to analyse population network topology, IBD patterns and dispersal habitats, using least-cost transect analysis. Landscape genetic analyses neglecting spatial scale and population network topology resulted in models with low fits, with which a most likely dispersal habitat could not be identified. In contrast, analyses considering spatial scale and population network topology resulted in high model fits by restricting landscape genetic analysis to smaller scales (0-3 km) and neighbouring populations, as represented by a Gabriel graph. These models also successfully identified a likely dispersal habitat of S. grossum. The above results suggest that spatial scale and potentially population network topology should be more explicitly considered in future landscape genetic analyses.

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.

Stethophyma grossum is a threatened Eurosiberian grasshopper species. Since it is bound to wetlands, S. grossum is often used as indicator for extensive wet meadows. To study its movement capability and dispersal habitat in landscape genetic analyses, we developed ten polymorphic microsatellite markers, making use of next generation sequencing. Markers were tested on 75 individuals collected in five populations from Switzerland. We found four to 18 alleles per locus. Observed and expected heterozygosities varied between 0.215–0.893 and 0.397–0.831, respectively. One marker seems to be sex-chromosome X-linked and one showed high null allele frequencies, a phenomenon generally detected in microsatellite studies on grasshoppers.

Summary1. Landscape genetic approaches were used to assess functional connectivity of populations of the endangered damselfly Coenagrion mercuriale in a fragmented agricultural landscape in Switzerland. Spatial genetic clustering methods combined with interpolation by kriging and landscape genetic corridor analysis were applied to identify landscape elements that enhance or hinder dispersal and gene flow.2. Spatial genetic clustering analysis divided the sampled populations into a northern and a southern genetic group. The boundary between the two groups coincided with a hill ridge intersecting the study area. Landscape corridor analysis identified five landscape elements that significantly affected gene flow. Elevation change, Euclidian distance, patches of forest and flowing waterbodies acted as barriers, whereas open agricultural land enhanced gene flow between populations of C. mercuriale.3. This study showed that movement of C. mercuriale was not restricted to its preferred habitat (i.e. streams). Populations linked via continuous open agricultural land were functionally well connected if they were not more than about 1.5–2 km apart. In contrast, substantial elevation change and larger forest patches separated populations. These findings may serve as a basis to define conservation units and should be considered when planning connectivity measures, such as determining the locations of stepping stones, or the restoration of streams.

Leucorrhinia caudalis is a dragonfly species threatened throughout Europe. Despite evidence of the recent extension of its distribution range, it is unknown whether L. caudalis regularly or hardly ever migrates among ponds. The contemporary migration patterns of the species were investigated using Bayesian assignment tests and the migration rates related to landscape structural and thematic variables (distance between ponds, forest area, area of water body, area of hedgerow). Migration rates of L. caudalis are independent of any landscape element. Thus, landscape structure is not a barrier or corridor for migration in this species. The tendency of L. caudalis to disperse is largely independent of the nature of the landscape, at least at the scale of the present study.

Leucorrhinia caudalis is a rare dragonfly, threatened throughout its European distribution. The species was formerly widespread in the Swiss lowlands, but only a single population remained in the 1980s. However, a spread has recently been observed, with additional ponds being colonised, sometimes at considerable distance. Despite this evidence of recent long-distance dispersal, it is unknown whether L. caudalis regularly moves among ponds or whether this is a rather rare event. A combination of an ecological mark-resight and a population genetic study was applied to investigate contemporary dispersal and the genetic footprint of the recent population history of L. caudalis in Switzerland. DNA for genetic microsatellite analysis was extracted from exuviae. The mark-resight study and the genetic analysis gave congruent results. They showed that L. caudalis is mostly a sedentary species, with only a few contemporary dispersal events over distances up to 5km being observed. The genetic analysis was in agreement with the recent population history of the Swiss populations. The oldest and largest population showed large genetic diversity and acted as source population for the recent spread of L. caudalis in Switzerland. Recurrent gene flow among this source population and close populations caused substantial local genetic variation in the latter, as well as low population differentiation. The two recently founded distant populations (⩾30km distance) were genetically less diverse and highly differentiated. These distant populations and another recently colonised population also expressed signatures of genetic bottlenecks.

Leucorrhinia caudalis is a rare dragonfly, threatened throughout Europe. It only survived in a single population in Switzerland in the 1980s. However, it recently spread and colonized new ponds. In order to be able to study contemporary migration in this species, eight new microsatellite markers were developed and tested on 24 individuals from six Swiss ponds. We detected three to eleven alleles per polymorphic locus and found observed and expected heterozygosities of 0.250 to 0.875 and 0.215 to 0.840, respectively.