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Analyzing wildlife tracking data frequently involves the estimation of home ranges. However, home range studies frequently lack important analytical steps, or only insufficiently report results. Thismakes it difficult for other researchers to evaluate, compare, and reproduce results from published home-range studies. To facilitate more thorough home-range analyses and reporting of analytical details, we developed a package for the statistical software package R that offers a user-friendly platform for comprehensive home-range analyses. Importantly, the package automatically generates a summary report that contains all analytical parameters used during analyses, and lists the main findings. To improve usability of the package, we also provide a graphical user interface that can be called from R without any programming skills. We currently implemented the calculation of site fidelity, time to statistical independence, minimum convex polygon, kernel density estimation, Brownian Bridge Movement Model, Jennrich–Turner Ellipses, local convex hull, estimation of home range asymptote, and area-independent core-area estimation.

Summary The successful movement of individuals is fundamental to life. Facilitating these movements by promoting ecological connectivity has become a central theme in ecology and conservation. Urban areas contain more than half of the world's human population, and their potential to support biodiversity and to connect their citizens to nature is increasingly recognized. Promoting ecological connectivity within these areas is essential to reaching this potential. However, our current understanding of ecological connectivity within urban areas appears limited. We reviewed the published scientific literature to assess the state‐of‐the‐art of ecological connectivity research in urban areas, summarized trends in study attributes and highlighted knowledge gaps. We found 174 papers that investigated ecological connectivity within urban areas. These papers addressed either structural (48) or functional connectivity (111), and some addressed both (15), but contained substantial geographic and taxonomic biases. These papers rarely defined the aspect of connectivity they were investigating and objective descriptions of the local urban context were uncommon. Formulated hypotheses or a priori predictions were typically unstated and many papers used suboptimal study designs and methods. We suggest future studies explicitly consider and quantify the landscape within their analyses and make greater use of available and rapidly developing tools and methods for measuring functional connectivity (e.g. biotelemetry or landscape genetics). We also highlight the need for studies to clearly define how the terms ‘urban’ and ‘connectivity’ have been applied. Knowledge gaps in ecological connectivity in urban areas remain, partly because the field is still in its infancy and partly because we must better capitalize on the state‐of‐the‐art technological and analytical techniques that are increasingly available. Well‐designed studies that employed high‐resolution data and powerful analytical techniques highlight our abilities to quantify ecological connectivity in urban areas. These studies are exemplary, setting the standards for future research to facilitate data‐driven and evidence‐based biodiversity‐friendly infrastructure planning in urban areas. Lay Summary

Increased availability of high-resolution movement data has led to the development of numerous methods for studying changes in animal movement behavior. Path segmentation methods provide basics for detecting movement changes and the behavioral mechanisms driving them. However, available path segmentation methods differ vastly with respect to underlying statistical assumptions and output produced. Consequently, it is currently difficult for researchers new to path segmentation to gain an overview of the different methods, and choose one that is appropriate for their data and research questions. Here, we provide an overview of different methods for segmenting movement paths according to potential changes in underlying behavior. To structure our overview, we outline three broad types of research questions that are commonly addressed through path segmentation: 1) the quantitative description of movement patterns, 2) the detection of significant change-points, and 3) the identification of underlying processes or ‘hidden states’. We discuss advantages and limitations of different approaches for addressing these research questions using path-level movement data, and present general guidelines for choosing methods based on data characteristics and questions. Our overview illustrates the large diversity of available path segmentation approaches, highlights the need for studies that compare the utility of different methods, and identifies opportunities for future developments in path-level data analysis.

Estimates of wildlife population size are critical for conservation and management, but accurate estimates are difficult to obtain for many species. Several methods have recently been developed that estimate abundance using kinship relationships observed in genetic samples, particularly parent-offspring pairs. While these methods are similar to traditional Capture-Mark-Recapture, they do not need physical recapture, as individuals are considered recaptured if a sample contains one or more close relatives. This makes methods based on genetically-identified parent-offspring pairs particularly interesting for species for which releasing marked animals back into the population is not desirable or not possible ( e.g. , harvested fish or game species). However, while these methods have successfully been applied in commercially important fish species, in the absence of life-history data, they are making several assumptions unlikely to be met for harvested terrestrial species. They assume that a sample contains only one generation of parents and one generation of juveniles of the year, while more than two generations can coexist in the hunting bags of long-lived species, or that the sampling probability is the same for each individual, an assumption that is violated when fecundity and/or survival depend on sex or other individual traits. In order to assess the usefulness of kin-based methods to estimate population sizes of terrestrial game species, we simulated population pedigrees of two different species with contrasting demographic strategies (wild boar and red deer), applied four different methods and compared the accuracy and precision of their estimates. We also performed a sensitivity analysis, simulating population pedigrees with varying fecundity characteristics and various levels of harvesting to identify optimal conditions of applicability of each method. We showed that all these methods reached the required levels of accuracy and precision to be effective in wildlife management under simulated circumstances ( i.e. , for species within a given range of fecundity and for a given range of sampling intensity), while being robust to fecundity variation. Despite the potential usefulness of the methods for terrestrial game species, care is needed as several biases linked to hunting practices still need to be investigated ( e.g. , when hunting bags are biased toward a particular group of individuals).

Revealing patterns of genetic diversity and barriers for gene flow are key points for successful conservation in endangered species. Methods based on molecular markers are also often used to delineate conservation units such as evolutionary significant units and management units. Here we combine phylo-geographic analyses (based on mtDNA) with population and landscape genetic analyses (based on microsatellites) for the endangered yellow-bellied toad Bombina variegata over a wide distribution range in Germany. Our analyses show that two genetic clusters are present in the study area, a northern and a southern/central one, but that these clusters are not deeply divergent. The genetic data suggest high fragmentation among toad occurrences and consequently low genetic diversity. Genetic diversity and genetic connectivity showed a negative relationship with road densities and urban areas surrounding toad occurrences, indicating that these landscape features act as barriers to gene flow. To preserve a maximum of genetic diversity, we recommend considering both genetic clusters as management units, and to increase gene flow among toad occurrences with the aim of restoring and protecting functional meta-populations within each of the clusters. Several isolated populations with especially low genetic diversity and signs of inbreeding need particular short-term conservation attention to avoid extinction. We also recommend to allow natural gene flow between both clusters but not to use individuals from one cluster for translocation or reintroduction into the other. Our results underscore the utility of molecular tools for species conservation, highlight outcomes of habitat fragmentation onto the genetic structure of an endangered amphibian and reveal particularly threatened populations in need for urgent conservation efforts.

LANDSCAPE GENETICS: CONCEPTS, METHODS, APPLICATIONS LANDSCAPE GENETICS: CONCEPTS, METHODS, APPLICATIONS Edited by Niko Balkenhol, Samuel A. Cushman, Andrew T. Storfer, Lisette P. Waits Landscape genetics is an exciting and rapidly growing field, melding methods and theory from landscape ecology and population genetics to address some of the most challenging and urgent ecological and evolutionary topics of our time. Landscape genetic approaches now enable researchers to study in detail how environmental complexity in space and time affect gene flow, genetic drift, and local adaptation. However, learning about the concepts and methods underlying the field remains challenging due to the highly interdisciplinary nature of the field, which relies on topics that have traditionally been treated separately in classes and textbooks. In this edited volume, some of the leading experts in landscape genetics provide the first comprehensive introduction to underlying concepts, commonly used methods, and current and future applications of landscape genetics. Consistent with the interdisciplinary nature of the field, the book includes textbook-like chapters that synthesize fundamental concepts and methods underlying landscape genetics (Part 1), chapters on advanced topics that deserve a more in-depth treatment (Part 2), and chapters illustrating the use of concepts and methods in empirical applications (Part 3). Aimed at beginning landscape geneticists and experienced researchers alike, this book will be helpful for all scientists and practitioners interested in learning, teaching, and applying landscape genetics.

The ability to acquire water from the soil is a major driver in interspecific plant competition and it depends on several root functional traits. One of these traits is the excretion of gel-like compounds (mucilage) that modify physical soil properties. Mucilage secreted by roots becomes hydrophobic upon drying, impedes the rewetting of the soil close to the root, the so called rhizosphere, and reduces water availability to plants. The function of rhizosphere hydrophobicity is not easily understandable when looking at a single plant, but it may constitute a competitive advantage at the ecosystem level. We hypothesize that by making the top soil hydrophobic, deep-rooted plants avoid competititon with shallow-rooted plants. To test this hypothesis we used an individual-based model to simulate water uptake and growth of two virtual plant species, one deep-rooted plant capable of making the soil hydrophobic and a shallow-rooted plant. We ran scenarios with different precipitation regimes ranging from dry to wet (350, 700, and 1400 mm total annual precipitation) and from high to low precipitation frequencies (1, 7, and 14 days). Plant species abundance and biomass were chosen as indicators for competitiveness of plant species. At constant precipitation frequency mucilage hydrophobicity lead to a benefit in biomass and abundance of the tap-rooted population. Under wet conditions this effect diminished and tap-rooted plants were less productive. Without this trait both species coexisted. The effect of root exudation trait remained constant under different precipitation frequencies. This study shows that mucilage secretion is a competitive trait for the acquisition of water. This advantage is achieved by the modification of the soil hydraulic properties and specifically by inducing water repellency in soil regions which are shared with other species.

The goal of landscape genetics is to detect and explain landscape effects on genetic diversity and structure. Despite the increasing popularity of landscape genetic approaches, the statistical methods for linking genetic and landscape data remain largely untested. This lack of method evaluation makes it difficult to compare studies utilizing different statistics, and compromises the future development and application of the field. To investigate the suitability and comparability of various statistical approaches used in landscape genetics, we simulated data sets corresponding to five landscape-genetic scenarios. We then analyzed these data with eleven methods, and compared the methods based on their statistical power, type-1 error rates, and their overall ability to lead researchers to accurate conclusions about landscape-genetic relationships. Results suggest that some of the most commonly applied techniques (e.g. Mantel and partial Mantel tests) have high type-1 error rates, and that multivariate, non-linear methods are better suited for landscape genetic data analysis. Furthermore, different methods generally show only moderate levels of agreement. Thus, analyzing a data set with only one method could yield method-dependent results, potentially leading to erroneous conclusions. Based on these findings, we give recommendations for choosing optimal combinations of statistical methods, and identify future research needs for landscape genetic data analyses.

The study of animal–habitat interactions is of primary importance for the formulation of conservation recommendations. Flying, gliding, and climbing animals have the ability to exploit their habitat in a three‐dimensional way, and the vertical canopy structure in forests plays an essential role for habitat suitability. Forest bats as flying mammals may seasonally shift their microhabitat use due to differing energy demands or changing prey availability, but the patterns are not well understood. We investigated three‐dimensional and seasonal habitat use by insectivorous bats in a temperate lowland old‐growth forest, the Belovezhskaya Pushcha in Belarus. We acoustically sampled broadleaved and mixed coniferous plots in the forest interior and in gaps in three heights during two reproductive periods (pregnancy/lactation vs. postlactation). In canopy gaps, vertical stratification in bat activity was less pronounced than in the forest interior. Vertical activity patterns differed among species. The upper canopy levels were important foraging habitats for the open‐space forager guild and for some edge‐space foragers like the Barbastelle bat Barbastella barbastellus and the soprano pipistrelle Pipistrellus pygmaeus. Myotis species had highest activity levels near the ground in forest gaps. Moreover, we found species‐dependent seasonal microhabitat shifts. Generally, all species and species groups considered except Myotis species showed higher activity levels during postlactation. Myotis species tended toward higher activity in the forest interior during postlactation. P. pygmaeus switched from high activity levels in the upper canopy during pregnancy and lactation to high activity levels near the ground during postlactation. We conclude that a full comprehension of forest bat habitat use is only possible when height in canopy and seasonal patterns are considered. We investigated three‐dimensional and seasonal habitat use by insectivorous bats in a temperate lowland old‐growth forest. We identified guild‐ and species‐specific differences in canopy height use and species‐dependent seasonal microhabitat shifts that can be explained by ecomorphological adaptations.

Collisions of vehicles with wildlife pose a serious risk to humans and animals, causing great financial and ecological damage each year. While various mitigation measures have been developed, only a few are economically and logistically feasible. Among these, wildlife warning reflectors arguably enjoy the greatest popularity, although recent studies have shown that they have no long-term impact on wildlife-vehicle collisions or on the behavior of animals along roads. However, belief in their temporary effect on animals and motorists persists among manufacturers and hunters. In our study, we analyzed the reactions of ungulates towards approaching vehicles and motorists towards wildlife near roads, before and after installation of modern multi-colored wildlife warning reflectors. We also tested for a potential habituation effect of both, animals as well as motorists, to the presence of wildlife warning reflectors. In total, we studied animal behavior on 13 study sites during a 12-month study period using thermal cameras before and after wildlife warning reflector installation, also controlling for seasonal variation in animal behavior. Exploratory analyses using linear mixed-effects models (LMM) and generalized linear mixed-effects models (GLMM) evaluated the effect of the reflectors on road crossing events, reactions of animals to vehicles (positive vs. negative; no reaction < alarm < locomotion < flight), flight events, flight initiation distance, and the braking responses of motorists when animals were nearby. Ungulates were more likely to leave the road side area (alarm > locomotion) with reflectors present. However, this effect only lasted 16.5 days und did not influence the risk of a collision with a vehicle. In addition, reflectors did not alter the driving behavior of motorists. We conclude that wildlife warning reflectors are not effective for reducing vehicle collisions with wildlife.