Recent progress in positioning technology facilitates the collection of massive amounts of sequential spatial data on animals. This has led to new opportunities and challenges when investigating animal movement behaviour and habitat selection. Tools like Step Selection Functions (SSFs) are relatively new powerful models for studying resource selection by animals moving through the landscape. SSFs compare environmental attributes of observed steps (the linear segment between two consecutive observations of position) with alternative random steps taken from the same starting point. SSFs have been used to study habitat selection, human-wildlife interactions, movement corridors, and dispersal behaviours in animals. SSFs also have the potential to depict resource selection at multiple spatial and temporal scales. There are several aspects of SSFs where consensus has not yet been reached such as how to analyse the data, when to consider habitat covariates along linear paths between observations rather than at their endpoints, how many random steps should be considered to measure availability, and how to account for individual variation. In this review we aim to address all these issues, as well as to highlight weak features of this modelling approach that should be developed by further research. Finally, we suggest that SSFs could be integrated with state-space models to classify behavioural states when estimating SSFs.

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Rapidly increasing populations of wild boar in Sweden and Europe cause much damage to crops, and there is a critical need for more knowledge about their habitat utilization, especially of agricultural fields. In our study, we first assess the spatial pattern of damage in relation to the edges of agricultural fields. Next, with the aid of global positioning system collars, we studied the pattern of movement of wild boar on agricultural fields. Finally, in order to understand the role of agricultural fields, we studied how habitat selection may vary throughout the year. We found edge effects on damage patterns in agricultural fields. During winter and spring, we found wild boar not only to follow edges, but also to move along narrow landscape elements within agricultural fields. In our habitat analysis, we found strong avoidance of exposed agricultural fields throughout the year, but significantly less when crops are ripe.

Predation risk may affect space use and foraging patterns of prey animals, with strong down-stream effects on diet composition and ecological interactions. Wild boar Sus scrofa is a notorious crop raider but also a popular game species, yet little is known about how risk perception of human hunting affects wild boar space use. We studied the effects of human hunting on the movement of GPS-collared female wild boar. We found that the hunting method affected whether the wild boar fled or hid. After fleeing into refuge ranges, wild boar moved less and preferred habitats that provided cover and forage such as mast or crops. This suggests that the wild boar tried to reduce the risk of being detected, and possibly also that they avoided competition with resident wild boar in the refuge by using forage that could not be monopolised. The type of hunting thus strongly affected the type of avoidance behaviour displayed by wild boar, with implications for their movement and space use. This suggests that adjusting hunting method to season could be an important management tool for minimising crop losses.

In animal behaviour, there is a dichotomy between innate behaviours (e.g., temperament or personality traits) versus those behaviours shaped by learning. Innate personality traits are supposedly less evident in animals when confounded by learning acquired with experience through time. Learning might play a key role in the development and adoption of successful anti-predator strategies, and the related adaptation has the potential to make animals that are more experienced less vulnerable to predation. We carried out a study in a system involving a large herbivorous mammal, female elk, Cervus elaphus, and their primary predator, i.e., human hunters. Using fine-scale satellite telemetry relocations, we tested whether differences in behaviour depending on age were due solely to selection pressure imposed by human hunters, meaning that females that were more cautious were more likely to survive and become older. Or whether learning also was involved, meaning that females adjusted their behaviour as they aged. Our results indicated that both human selection and learning contributed to the adoption of more cautious behavioural strategies in older females. Whereas human selection of behavioural traits has been shown in our previous research, we here provide evidence of additive learning processes being responsible for shaping the behaviour of individuals in this population. Female elk are indeed almost invulnerable to human hunters when older than 9–10 y.o., confirming that experience contributes to their survival. Female elk monitored in our study showed individually changing behaviours and clear adaptation as they aged, such as reduced movement rates (decreased likelihood of encountering human hunters), and increased use of secure areas (forest and steeper terrain), especially when close to roads. We also found that elk adjusted behaviours depending on the type of threat (bow and arrow vs. rifle hunters). This fine-tuning by elk to avoid hunters, rather than just becoming more cautious during the hunting season, highlights the behavioural plasticity of this species. Selection on behavioural traits and/or behavioural shifts via learning are an important but often-ignored consequence of human exploitation of wild animals. Such information is a critical component of the effects of human exploitation of wildlife populations with implications for improving their management and conservation.

BackgroundDispersal has a critical influence on demography and gene flow and as such maintaining connectivity between populations is an essential element of modern conservation. Advances in satellite radiotelemetry are providing new opportunities to document dispersal, which previously has been difficult to study. This type of data also can be used as an empirical basis for defining landscapes in terms of resistance surfaces, enabling habitat corridors to be identified. However, despite the scale-dependent nature of habitat selection few studies have investigated selection specifically during dispersal. Here we investigate habitat selection during and around dispersal periods as well as the influence of age and sex on dispersal for a large ungulate.ResultsOf 158 elk (Cervus elaphus) tracked using GPS radiotelemetry almost all dispersers were males, with individuals dispersing up to 98 km. The dispersal period was distinct, with higher movement rates than before or after dispersal. At fine scale elk avoided the most rugged terrain in all time periods, but to a greater extent during and after dispersal, which we showed using step selection functions. In contrast, habitat selection by resident elk was less affected by ruggedness and more by an attraction to areas of higher forage availability. At the broad scale, however, movement corridors of dispersers were characterized by higher forage availability and slightly lower ruggedness then expected using correlated random walks.ConclusionsIn one of the first examples of its kind we document complete long-distance dispersal events by an ungulate in detail. We find dispersal to be distinct in terms of movement rate and also find evidence that habitat selection during dispersal may differ from habitat selection in the home-range, with potential implications for the use of resistance surfaces to define conservation corridors.Electronic supplementary materialThe online version of this article (doi:10.1186/s40462-014-0015-4) contains supplementary material, which is available to authorized users.

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Landscape connectivity describes how the movement of animals relates to landscape structure. The way in which movement among populations is affected by environmental conditions is important for predicting the effects of habitat fragmentation, and for defining conservation corridors. One approach has been to map resistance surfaces to characterize how environmental variables affect animal movement, and to use these surfaces to model connectivity. However, current connectivity modelling typically uses information on species location or habitat preference rather than movement, which unfortunately may not capture dispersal limitations. Here we emphasize the importance of implementing dispersal ecology into landscape connectivity, i.e., observing patterns of habitat selection by dispersers during different phases of new areas’ colonization to infer habitat connectivity. Disperser animals undertake a complex sequence of movements concatenated over time and strictly dependent on species ecology. Using satellite telemetry, we investigated the movement ecology of 54 young male elk Cervus elaphus, which commonly disperse, to design a corridor network across the Northern Rocky Mountains. Winter residency period is often followed by a spring-summer movement phase, when young elk migrate with mothers’ groups to summering areas, and by a further dispersal bout performed alone to a novel summer area. After another summer residency phase, dispersers usually undertake a final autumnal movement to reach novel wintering areas. We used resource selection functions to identify winter and summer habitats selected by elk during residency phases. We then extracted movements undertaken during spring to move from winter to summer areas, and during autumn to move from summer to winter areas, and modelled them using step selection functions. We built friction surfaces, merged the different movement phases, and eventually mapped least-cost corridors. We showed an application of this tool by creating a scenario with movement predicted as there were no roads, and mapping highways’ segments impeding elk connectivity.