Landscape-level heterogeneity of agri-environment measures improves habitat suitability for farmland birds.

Agri-environment schemes (AESs), ecological focus areas (EFAs), and organic farming are the main tools of the common agricultural policy (CAP) to counteract the dramatic decline of farmland biodiversity in Europe. However, their effectiveness is repeatedly doubted because it seems to vary when measured at the field-versus-landscape level and to depend on the regional environmental and land-use context. Understanding the heterogeneity of their effectiveness is thus crucial to developing management recommendations that maximize their efficacy. Using ensemble species distribution models and spatially explicit field-level information on crops grown, farming practice (organic/conventional), and applied AES/EFA from the Integrated Administration and Control System, we investigated the contributions of five groups of measures (buffer areas, cover crops, extensive grassland management, fallow land, and organic farming) to habitat suitability for 15 farmland bird species in the Mulde River Basin, Germany. We used a multiscale approach to identify the scale of effect of the selected measures. Using simulated land-use scenarios, we further examined how breeding habitat suitability would change if the measures were completely removed and if their adoption by farmers increased to meet conservation-informed targets. Buffer areas, fallow land, and extensive grassland were beneficial measures for most species, but cover crops and organic farming had contrasting effects across species. While different measures acted at different spatial scales, our results highlight the importance of land-use management at the landscape level-at which most measures had the strongest effect. We found that the current level of adoption of the measures delivers only modest gains in breeding habitat suitability. However, habitat suitability improved for the majority of species when the implementation of the measures was increased, suggesting that they could be effective conservation tools if higher adoption levels were reached. The heterogeneity of responses across species and spatial scales indicated that a mix of different measures, applied widely across the agricultural landscape, would likely maximize the benefits for biodiversity. This can only be achieved if the measures in the future CAP will be cooperatively designed in a regionally targeted way to improve their attractiveness for farmers and widen their uptake.

Hybridization may aid evolutionary rescue of an endangered East African passerine.

Introgressive hybridization is a process that enables gene flow across species barriers through the backcrossing of hybrids into a parent population. This may make genetic material, potentially including relevant environmental adaptations, rapidly available in a gene pool. Consequently, it has been postulated to be an important mechanism for enabling evolutionary rescue, that is the recovery of threatened populations through rapid evolutionary adaptation to novel environments. However, predicting the likelihood of such evolutionary rescue for individual species remains challenging. Here, we use the example of Zosterops silvanus, an endangered East African highland bird species suffering from severe habitat loss and fragmentation, to investigate whether hybridization with its congener Zosterops flavilateralis might enable evolutionary rescue of its Taita Hills population. To do so, we employ an empirically parameterized individual-based model to simulate the species' behaviour, physiology and genetics. We test the population's response to different assumptions of mating behaviour and multiple scenarios of habitat change. We show that as long as hybridization does take place, evolutionary rescue of Z. silvanus is likely. Intermediate hybridization rates enable the greatest long-term population growth, due to trade-offs between adaptive and maladaptive introgressed alleles. Habitat change did not have a strong effect on population growth rates, as Z. silvanus is a strong disperser and landscape configuration is therefore not the limiting factor for hybridization. Our results show that targeted gene flow may be a promising avenue to help accelerate the adaptation of endangered species to novel environments, and demonstrate how to combine empirical research and mechanistic modelling to deliver species-specific predictions for conservation planning.

A brief history and popularity of methods and tools used to estimate micro-evolutionary forces.

Population genetics is a field of research that predates the current generations of sequencing technology. Those approaches, that were established before massively parallel sequencing methods, have been adapted to these new marker systems (in some cases involving the development of new methods) that allow genome-wide estimates of the four major micro-evolutionary forces-mutation, gene flow, genetic drift, and selection. Nevertheless, classic population genetic markers are still commonly used and a plethora of analysis methods and programs is available for these and high-throughput sequencing (HTS) data. These methods employ various and diverse theoretical and statistical frameworks, to varying degrees of success, to estimate similar evolutionary parameters making it difficult to get a concise overview across the available approaches. Presently, reviews on this topic generally focus on a particular class of methods to estimate one or two evolutionary parameters. Here, we provide a brief history of methods and a comprehensive list of available programs for estimating micro-evolutionary forces. We furthermore analyzed their usage within the research community based on popularity (citation bias) and discuss the implications of this bias for the software community. We found that a few programs received the majority of citations, with program success being independent of both the parameters estimated and the computing platform. The only deviation from a model of exponential growth in the number of citations was found for the presence of a graphical user interface (GUI). Interestingly, no relationship was found for the impact factor of the journals, when the tools were published, suggesting accessibility might be more important than visibility.

Assortative mating frames establishment in a young island bird population.

Successful island colonizations are key events to understand range dynamic processes, but studying a young population right after it reaches establishment is a rare opportunity in natural systems. The genetic structure of a recently established population may offer unique insights into its colonization history and demographic processes that are important for a successful colonization. Here, we studied the population genetics of a recently established island population of Eurasian blackbirds (Aves: Turdus merula) located on the island of Heligoland in the German North Sea. Using microsatellites, we genotyped the majority of the island population, including the nestlings, over a 4-year period between 2004 and 2007. We also genotyped high numbers of migrants on stopover and mainland individuals, as they are potential founders of the island population. We identified two genetic clusters that comply with the migrating and mainland birds. While most of the island birds belong to the mainland cluster, some breeding individuals and a low fraction of the offspring belong to the genetic cluster found in migrating individuals with almost no admixture between the two, pointing to assortative mating acting on the island population. We did not find any evidence for founder events and detected deviations from the Hardy-Weinberg equilibrium that disappeared in cohorts of older age that coincide with a lower number of siblings in older cohorts. The observed genetic patterns unravel a complex colonization history to which migratory and mainland birds have contributed and which is characterized by assortative mating. Further research will be directed towards habitat selection and phenotypic differences as potential drivers of assortative mating in this island population.

Conservation genetics: Linking science with practice.

Conservation genetics is a well-established scientific field. However, limited information transfer between science and practice continues to hamper successful implementation of scientific knowledge in conservation practice and management. To mitigate this challenge, we have established a conservation genetics community, which entails an international exchange-and-skills platform related to genetic methods and approaches in conservation management. First, it allows for scientific exchange between researchers during annual conferences. Second, personal contact between conservation professionals and scientists is fostered by organising workshops and by popularising knowledge on conservation genetics methods and approaches in professional journals in national languages. Third, basic information on conservation genetics has been made accessible by publishing an easy-to-read handbook on conservation genetics for practitioners. Fourth, joint projects enabled practitioners and scientists to work closely together from the start of a project in order to establish a tight link between applied questions and scientific background. Fifth, standardised workflows simplifying the implementation of genetic tools in conservation management have been developed. By establishing common language and trust between scientists and practitioners, all these measures help conservation genetics to play a more prominent role in future conservation planning and management.

Coupling Satellite Data with Species Distribution and Connectivity Models as a Tool for Environmental Management and Planning in Matrix-Sensitive Species.

Climate change and anthropogenic habitat fragmentation are considered major threats for global biodiversity. As a direct consequence, connectivity is increasingly disrupted in many species, which might have serious consequences that could ultimately lead to the extinction of populations. Although a large number of reserves and conservation sites are designated and protected by law, potential habitats acting as inter-population connectivity corridors are, however, mostly ignored in the common practice of environmental planning. In most cases, this is mainly caused by a lack of quantitative measures of functional connectivity available for the planning process. In this study, we highlight the use of fine-scale potential connectivity models (PCMs) derived from multispectral satellite data for the quantification of spatially explicit habitat corridors for matrix-sensitive species of conservation concern. This framework couples a species distribution model with a connectivity model in a two-step framework, where suitability maps from step 1 are transformed into maps of landscape resistance in step 2 filtered by fragmentation thresholds. We illustrate the approach using the sand lizard (Lacerta agilis L.) in the metropolitan area of Cologne, Germany, as a case study. Our model proved to be well suited to identify connected as well as completely isolated populations within the study area. Furthermore, due to its fine resolution, the PCM was also able to detect small linear structures known to be important for sand lizards' inter-population connectivity such as railroad embankments. We discuss the applicability and possible implementation of PCMs to overcome shortcomings in the common practice of environmental impact assessments.

Comparative landscape genetics of three closely related sympatric Hesperid butterflies with diverging ecological traits.

To understand how landscape characteristics affect gene flow in species with diverging ecological traits, it is important to analyze taxonomically related sympatric species in the same landscape using identical methods. Here, we present such a comparative landscape genetic study involving three closely related Hesperid butterflies of the genus Thymelicus that represent a gradient of diverging ecological traits. We analyzed landscape effects on their gene flow by deriving inter-population connectivity estimates based on different species distribution models (SDMs), which were calculated from multiple landscape parameters. We then used SDM output maps to calculate circuit-theoretic connectivity estimates and statistically compared these estimates to actual genetic differentiation in each species. We based our inferences on two different analytical methods and two metrics of genetic differentiation. Results indicate that land use patterns influence population connectivity in the least mobile specialist T. acteon. In contrast, populations of the highly mobile generalist T. lineola were panmictic, lacking any landscape related effect on genetic differentiation. In the species with ecological traits in between those of the congeners, T. sylvestris, climate has a strong impact on inter-population connectivity. However, the relative importance of different landscape factors for connectivity varies when using different metrics of genetic differentiation in this species. Our results show that closely related species representing a gradient of ecological traits also show genetic structures and landscape genetic relationships that gradually change from a geographical macro- to micro-scale. Thus, the type and magnitude of landscape effects on gene flow can differ strongly even among closely related species inhabiting the same landscape, and depend on their relative degree of specialization. In addition, the use of different genetic differentiation metrics makes it possible to detect recent changes in the relative importance of landscape factors affecting gene flow, which likely change as a result of contemporary habitat alterations.

Mapping species distributions with MAXENT using a geographically biased sample of presence data: a performance assessment of methods for correcting sampling bias.

MAXENT is now a common species distribution modeling (SDM) tool used by conservation practitioners for predicting the distribution of a species from a set of records and environmental predictors. However, datasets of species occurrence used to train the model are often biased in the geographical space because of unequal sampling effort across the study area. This bias may be a source of strong inaccuracy in the resulting model and could lead to incorrect predictions. Although a number of sampling bias correction methods have been proposed, there is no consensual guideline to account for it. We compared here the performance of five methods of bias correction on three datasets of species occurrence: one "virtual" derived from a land cover map, and two actual datasets for a turtle (Chrysemys picta) and a salamander (Plethodon cylindraceus). We subjected these datasets to four types of sampling biases corresponding to potential types of empirical biases. We applied five correction methods to the biased samples and compared the outputs of distribution models to unbiased datasets to assess the overall correction performance of each method. The results revealed that the ability of methods to correct the initial sampling bias varied greatly depending on bias type, bias intensity and species. However, the simple systematic sampling of records consistently ranked among the best performing across the range of conditions tested, whereas other methods performed more poorly in most cases. The strong effect of initial conditions on correction performance highlights the need for further research to develop a step-by-step guideline to account for sampling bias. However, this method seems to be the most efficient in correcting sampling bias and should be advised in most cases.

Evolutionary history of wild barley (Hordeum vulgare subsp. spontaneum) analyzed using multilocus sequence data and paleodistribution modeling.

Studies of Hordeum vulgare subsp. spontaneum, the wild progenitor of cultivated barley, have mostly relied on materials collected decades ago and maintained since then ex situ in germplasm repositories. We analyzed spatial genetic variation in wild barley populations collected rather recently, exploring sequence variations at seven single-copy nuclear loci, and inferred the relationships among these populations and toward the genepool of the crop. The wild barley collection covers the whole natural distribution area from the Mediterranean to Middle Asia. In contrast to earlier studies, Bayesian assignment analyses revealed three population clusters, in the Levant, Turkey, and east of Turkey, respectively. Genetic diversity was exceptionally high in the Levant, while eastern populations were depleted of private alleles. Species distribution modeling based on climate parameters and extant occurrence points of the taxon inferred suitable habitat conditions during the ice-age, particularly in the Levant and Turkey. Together with the ecologically wide range of habitats, they might contribute to structured but long-term stable populations in this region and their high genetic diversity. For recently collected individuals, Bayesian assignment to geographic clusters was generally unambiguous, but materials from genebanks often showed accessions that were not placed according to their assumed geographic origin or showed traces of introgression from cultivated barley. We assign this to gene flow among accessions during ex situ maintenance. Evolutionary studies based on such materials might therefore result in wrong conclusions regarding the history of the species or the origin and mode of domestication of the crop, depending on the accessions included.

Evaluating the significance of paleophylogeographic species distribution models in reconstructing quaternary range-shifts of nearctic chelonians.

The climatic cycles of the Quaternary, during which global mean annual temperatures have regularly changed by 5-10°C, provide a special opportunity for studying the rate, magnitude, and effects of geographic responses to changing climates. During the Quaternary, high- and mid-latitude species were extirpated from regions that were covered by ice or otherwise became unsuitable, persisting in refugial retreats where the environment was compatible with their tolerances. In this study we combine modern geographic range data, phylogeny, Pleistocene paleoclimatic models, and isotopic records of changes in global mean annual temperature, to produce a temporally continuous model of geographic changes in potential habitat for 59 species of North American turtles over the past 320 Ka (three full glacial-interglacial cycles). These paleophylogeographic models indicate the areas where past climates were compatible with the modern ranges of the species and serve as hypotheses for how their geographic ranges would have changed in response to Quaternary climate cycles. We test these hypotheses against physiological, genetic, taxonomic and fossil evidence, and we then use them to measure the effects of Quaternary climate cycles on species distributions. Patterns of range expansion, contraction, and fragmentation in the models are strongly congruent with (i) phylogeographic differentiation; (ii) morphological variation; (iii) physiological tolerances; and (iv) intraspecific genetic variability. Modern species with significant interspecific differentiation have geographic ranges that strongly fluctuated and repeatedly fragmented throughout the Quaternary. Modern species with low genetic diversity have geographic distributions that were highly variable and at times exceedingly small in the past. Our results reveal the potential for paleophylogeographic models to (i) reconstruct past geographic range modifications, (ii) identify geographic processes that result in genetic bottlenecks; and (iii) predict threats due to anthropogenic climate change in the future.