Wherever I may roam-Human activity alters movements of red deer (Cervus elaphus) and elk (Cervus canadensis) across two continents.

Human activity and associated landscape modifications alter the movements of animals with consequences for populations and ecosystems worldwide. Species performing long-distance movements are thought to be particularly sensitive to human impact. Despite the increasing anthropogenic pressure, it remains challenging to understand and predict animals' responses to human activity. Here we address this knowledge gap using 1206 Global Positioning System movement trajectories of 815 individuals from 14 red deer (Cervus elaphus) and 14 elk (Cervus canadensis) populations spanning wide environmental gradients, namely the latitudinal range from the Alps to Scandinavia in Europe, and the Greater Yellowstone Ecosystem in North America. We measured individual-level movements relative to the environmental context, or movement expression, using the standardized metric Intensity of Use, reflecting both the directionality and extent of movements. We expected movement expression to be affected by resource (Normalized Difference Vegetation Index, NDVI) predictability and topography, but those factors to be superseded by human impact. Red deer and elk movement expression varied along a continuum, from highly segmented trajectories over relatively small areas (high intensity of use), to directed transitions through restricted corridors (low intensity of use). Human activity (Human Footprint Index, HFI) was the strongest driver of movement expression, with a steep increase in Intensity of Use as HFI increased, but only until a threshold was reached. After exceeding this level of impact, the Intensity of Use remained unchanged. These results indicate the overall sensitivity of Cervus movement expression to human activity and suggest a limitation of plastic responses under high human pressure, despite the species also occurring in human-dominated landscapes. Our work represents the first comparison of metric-based movement expression across widely distributed populations of a deer genus, contributing to the understanding and prediction of animals' responses to human activity.

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.

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

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.

A simulation-based evaluation of methods for estimating census population size of terrestrial game species from genetically-identified parent-offspring pairs.

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).

No seasonal curtailment of the Eurasian Skylark's (Alauda arvensis) breeding season in German heterogeneous farmland.

The lack of suitable nesting sites is one key driver behind the farmland bird crisis in Europe. Winter cereals become impenetrable for ground-breeding birds like the Eurasian Skylark (Alauda arvensis), curtailing breeding time. Stable Skylark populations depend on multiple breeding attempts per year; thus, the widespread cultivation of winter cereals has strongly contributed to their tremendous decline. Crop diversification is thought to be a potential measure to counteract this development. Therefore, we explored how individual Skylarks respond to the decreasing suitability of winter cereals as nesting habitats in heterogeneous but otherwise conventionally managed farmland. Our study focused on: (i) the degree to which Skylarks prematurely cease nesting activity, switch nesting habitats, or breed on linear structures like tramlines. Additionally, we analyzed: (ii) if nest success decreases throughout the breeding season and (iii) how often Skylarks make a successful breeding attempt per year. We radio-tagged 28 adults in a German population during April 2018 and 2019, tracked half of them for more than 3 months, and measured their breeding success. Additionally, we monitored nests of untagged pairs, resulting in 96 nests found. None, except one tagged individual, stopped breeding activity before July 1st. Home ranges were mainly stable, but Skylarks switched nesting habitats away from winter cereals to crops like sugar beet or set-aside. High-risk nesting sites like corn and linear structures played a minor role in breeding. Overall, Mayfield logistic regressions revealed no seasonal decrease in nest success, and tagged Skylarks had sufficient time to make 1.5-1.8 breeding attempts, of which 0.8 were successful. We suggest that heterogeneous farmland in our study area, which enabled diversely composed home ranges, prevented a curtailment of the breeding season. Thus, our study reinforces the need for crop diversification which gives Skylarks a chance to survive in modern farmland.

Habitat use and foraging parameters of breeding Skylarks indicate no seasonal decrease in food availability in heterogeneous farmland.

Reduced food availability during chick raising is a major driver of farmland bird declines. For the Eurasian Skylark (Alauda arvensis), food availability is determined by various factors (i.e., arthropod abundance/diversity, accessibility of the vegetation, distance to foraging sites). In modern farmland, it is supposed to decrease over the breeding season due to less penetrable vegetation. We explored foraging habitat selection by chick-raising Skylarks with a focus on the seasonal dynamics of habitat use and food availability. We investigated (i) habitat selection concerning prey biomass/diversity, vegetation cover, and distance to foraging sites, (ii) the overall and seasonal habitat use, and (iii) seasonal developments of foraging parameters (e.g., the feeding frequency) as indicators of food availability. We collected data on foraging habitats and foraging parameters of chick-raising Skylark pairs at 51 nests from a Central European population in 2018 and 2019. Prey biomass/diversity and vegetation cover were measured for all habitats around 42 of these nests. As revealed by multivariate and compositional analyses, Skylarks mainly selected foraging habitats based on the proximity to nests. The most frequent habitats within home ranges could not be ranked according to an overall importance for foraging and their use partially changed over time. The feeding frequency increased throughout the breeding season, while other foraging parameters did not show significant changes. In contrast to our expectations, our data indicated therefore an increase, not a decrease in food availability in the late breeding season. This also implies that the way in which Skylarks used habitats was constantly suitable to raise offspring. We interpret this to be a consequence of the heterogeneous farmland composition of the study area that enabled Skylarks to establish a diverse home range and to benefit from the synergetic effects of neighboring habitat types. Thus, our findings provide support for the high importance of crop diversity in Skylark conservation.

Three-dimensional stratification pattern in an old-growth lowland forest: How does height in canopy and season influence temperate bat activity?

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.

Do all roads lead to resistance? State road density is the main impediment to gene flow in a flagship species inhabiting a severely fragmented anthropogenic landscape.

AIM: Connectivity conservation is ideally based on empirical information on how landscape heterogeneity influences species-specific movement and gene flow. Here, we present the first large-scale evaluation of landscape impacts on genetic connectivity in the European wildcat (Felis silvestris), a flagship and umbrella species for connectivity conservation across Europe. LOCATION: The study was carried out in the core area of the distributional range of wildcats in Germany, covering about 186,000 km2 of a densely populated and highly fragmented landscape. METHODS: We used data of 975 wildcats genotyped at 14 microsatellites and an individual-based landscape genetic framework to assess the importance of twelve landscape variables for explaining observed genetic connectivity. For this, we optimized landscape resistance surfaces for all variables and compared their relative impacts using multiple regression on distance matrices and commonality analysis. RESULTS: Genetic connectivity was best explained by a synergistic combination of six landscape variables and isolation by distance. Of these variables, road density had by far the strongest individual impact followed by synergistic effects of agricultural lands and settlements. Subsequent analyses involving different road types revealed that the strong effect of road density was largely due to state roads, while highways and federal roads had a much smaller, and county roads only a negligible impact. MAIN CONCLUSIONS: Our results highlight that landscape-wide genetic connectivity in wildcats across Germany is strongly shaped by the density of roads and in particular state roads, with higher densities providing larger resistance to successful dispersal. These findings have important implications for conservation planning, as measures to mitigate fragmentation effects of roads (e.g., over- or underpasses) often focus on large, federally managed transportation infrastructures. While these major roads exert local barrier effects, other road types can be more influential on overall connectivity, as they are more abundant and more widespread across the landscape.

Large area used by squirrel gliders in an urban area, uncovered using GPS telemetry.

The squirrel glider (Petaurus norfolcensis) is a threatened, gliding marsupial that persists in fragmented landscapes despite its restricted capacity to cross large gaps. As measures to maintain and/or restore suitable habitat depend on knowledge about the species' ecological requirements, we investigated the area used by squirrel gliders in an urban area near Newcastle, Australia. Using GPS telemetry data and the autocorrelated kernel density estimator, we estimated area used to average 10.8 ha and varied from 4.6 to 15 ha, which is equal to or greater than found in previous studies that spanned longer time periods. This has implications when identifying the minimum patch size necessary for ensuring the long-term conservation of a squirrel glider population.

Roads constrain movement across behavioural processes in a partially migratory ungulate.

BACKGROUND: Human disturbance alters animal movement globally and infrastructure, such as roads, can act as physical barriers that impact behaviour across multiple spatial scales. In ungulates, roads can particularly hamper key ecological processes such as dispersal and migration, which ensure functional connectivity among populations, and may be particularly important for population performance in highly human-dominated landscapes. The impact of roads on some aspects of ungulate behaviour has already been studied. However, potential differences in response to roads during migration, dispersal and home range movements have never been evaluated. Addressing these issues is particularly important to assess the resistance of European landscapes to the range of wildlife movement processes, and to evaluate how animals adjust to anthropogenic constraints. METHODS: We analysed 95 GPS trajectories from 6 populations of European roe deer (Capreolus capreolus) across the Alps and central Europe. We investigated how roe deer movements were affected by landscape characteristics, including roads, and we evaluated potential differences in road avoidance among resident, migratory and dispersing animals (hereafter, movement modes). First, using Net Squared Displacement and a spatio-temporal clustering algorithm, we classified individuals as residents, migrants or dispersers. We then identified the start and end dates of the migration and dispersal trajectories, and retained only the GPS locations that fell between those dates (i.e., during transience). Finally, we used the resulting trajectories to perform an integrated step selection analysis. RESULTS: We found that roe deer moved through more forested areas during the day and visited less forested areas at night. They also minimised elevation gains and losses along their movement trajectories. Road crossings were strongly avoided at all times of day, but when they occurred, they were more likely to occur during longer steps and in more forested areas. Road avoidance did not vary among movement modes and, during dispersal and migration, it remained high and consistent with that expressed during home range movements. CONCLUSIONS: Roads can represent a major constraint to movement across modes and populations, potentially limiting functional connectivity at multiple ecological scales. In particular, they can affect migrating individuals that track seasonal resources, and dispersing animals searching for novel ranges.

In the shadows of snow leopards and the Himalayas: density and habitat selection of blue sheep in Manang, Nepal.

There is a growing agreement that conservation needs to be proactive and pay increased attention to common species and to the threats they face. The blue sheep (Pseudois nayaur) plays a key ecological role in sensitive high-altitude ecosystems of Central Asia and is among the main prey species for the globally vulnerable snow leopard (Panthera uncia). As the blue sheep has been increasingly exposed to human pressures, it is vital to estimate its population dynamics, protect the key populations, identify important habitats, and secure a balance between conservation and local livelihoods. We conducted a study in Manang, Annapurna Conservation Area (Nepal), to survey blue sheep on 60 transects in spring (127.9 km) and 61 transects in autumn (134.7 km) of 2019, estimate their minimum densities from total counts, compare these densities with previous estimates, and assess blue sheep habitat selection by the application of generalized additive models (GAMs). Total counts yielded minimum density estimates of 6.0-7.7 and 6.9-7.8 individuals/km2 in spring and autumn, respectively, which are relatively high compared to other areas. Elevation and, to a lesser extent, land cover indicated by the normalized difference vegetation index (NDVI) strongly affected habitat selection by blue sheep, whereas the effects of anthropogenic variables were insignificant. Animals were found mainly in habitats associated with grasslands and shrublands at elevations between 4,200 and 4,700 m. We show that the blue sheep population size in Manang has been largely maintained over the past three decades, indicating the success of the integrated conservation and development efforts in this area. Considering a strong dependence of snow leopards on blue sheep, these findings give hope for the long-term conservation of this big cat in Manang. We suggest that long-term population monitoring and a better understanding of blue sheep-livestock interactions are crucial to maintain healthy populations of blue sheep and, as a consequence, of snow leopards.

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

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.

Correction to: Towards the restoration of the Mesoamerican Biological Corridor for large mammals in Panama: comparing multi-species occupancy to movement models.

[This corrects the article DOI: 10.1186/s40462-019-0186-0.].

Towards the restoration of the Mesoamerican Biological Corridor for large mammals in Panama: comparing multi-species occupancy to movement models.

BACKGROUND: Habitat fragmentation is a primary driver of wildlife loss, and the establishment of biological corridors is a conservation strategy to mitigate this problem. Identifying areas with high potential functional connectivity typically relies on the assessment of landscape resistance to movement. Many modeling approaches exist to estimate resistance surfaces but to date only a handful of studies compared the outputs resulting from different methods. Moreover, as many species are threatened by fragmentation, effective biodiversity conservation requires that corridors simultaneously meet the needs of multiple species. While many corridor planning initiatives focus on single species, we here used a combination of data types and analytical approaches to identify and compare corridors for several large mammal species within the Panama portion of the Mesoamerican Biological Corridor. METHODS: We divided a large mammal assemblage into two groups depending on the species sensitivity to habitat disturbance. We subsequently used cost-distance methods to produce multi-species corridors which were modeled on the basis of (i) occupancy of nine species derived from camera trapping data collected across Panama, and (ii) step selection functions based on GPS telemetry data from white-lipped peccary Tayassu pecari, puma Puma concolor, and ocelot Leopardus pardalis. In addition to different data sources and species groups, we also used different transformation curves to convert occupancy and step-selection results into landscape resistance values. RESULTS: Corridors modeled differed between sensitive and tolerant species, between the data sets, and between the transformation curves. There were more corridors identified for tolerant species than for sensitive species. For tolerant species, several corridors developed with occupancy data overlapped with corridors produced with step selection functions, but this was not the case for sensitive species. CONCLUSION: Our study represents the first comparison of multispecies corridors parametrized with step selection functions versus occupancy models. Given the wide variability in output corridors, our findings underscore the need to consider the ecological requirements of several species. Our results also suggest that occupancy models can be used for estimating connectivity of generalist species. Finally, this effort allowed to identify important corridors within the MBC (i) at a country scale and (ii) for several species simultaneously to accurately inform the local authorities in conservation planning. The approach we present is reproducible in other sites and/or for other species.

Landscape genetics of wolverines (Gulo gulo): scale-dependent effects of bioclimatic, topographic, and anthropogenic variables.

Climate change can have particularly severe consequences for high-elevation species that are well-adapted to long-lasting snow conditions within their habitats. One such species is the wolverine, Gulo gulo, with several studies showing a strong, year-round association of the species with the area defined by persistent spring snow cover. This bioclimatic niche also predicts successful dispersal paths for wolverines in the contiguous United States, where the species shows low levels of genetic exchange and low effective population size. Here, we assess the influence of additional climatic, vegetative, topographic, and anthropogenic, variables on wolverine genetic structure in this region using a multivariate, multiscale, landscape genetic approach. This approach allows us to detect landscape-genetic relationships both due to typical, small-scale genetic exchange within habitat, as well as exceptional, long-distance dispersal among habitats. Results suggest that a combination of snow depth, terrain ruggedness, and housing density, best predict gene flow in wolverines, and that the relative importance of variables is scale-dependent. Environmental variables (i.e., isolation-by-resistance, IBR) were responsible for 79% of the explained variation at small scales (i.e., up to ~230 km), and 65% at broad scales (i.e., beyond ~420 km). In contrast, a null model based on only space (i.e., isolation-by-distance, IBD) accounted only for 17% and 11% of the variation at small and broad scales, respectively. Snow depth was the most important variable for predicting genetic structures overall, and at small scales, where it contributed 43% to the variance explained. At broad spatial scales, housing density and terrain ruggedness were most important with contributions to explained variation of 55% and 25%, respectively. While the small-scale analysis most likely captures gene flow within typical wolverine habitat complexes, the broad-scale analysis reflects long-distance dispersal across areas not typically inhabited by wolverines. These findings help to refine our understanding of the processes shaping wolverine genetic structure, which is important for maintaining and improving functional connectivity among remaining wolverine populations.

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

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.

Rhizosphere hydrophobicity: A positive trait in the competition for water.

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.

Path segmentation for beginners: an overview of current methods for detecting changes in animal movement patterns.

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.