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Abstract Step‐selection analysis (SSA) is ubiquitous for assessing local‐scale habitat selection by comparing relocations from telemetry data (used steps) to potential relocations given the movement of the animal (available steps). The case–control design of SSA is intended to estimate selection at the spatiotemporal scale of these steps. However, long‐term behaviour associated with recurring use of certain locations or resources may additionally impact movement decisions, potentially impacting the estimates produced by SSA. To determine the impact of recursive behaviour on local selection, we simulated movement trajectories in which animals exhibited patterns of recursion. Based on these simulated trajectories, we evaluated the impact of long‐term behaviour on estimates of step‐selection. Then, we developed a new approach to identify recursion points based on a time‐dependent kernel density estimate including latitude, longitude and time of day. Based on this information, we accounted for recursive behaviour by including the relationship between available steps to recursion points or using recursion points to adjust our sample of available steps. Finally, we apply this approach to estimate the response of white‐tailed deer (Odocoileus virginianus) to sources of risk. Recursive movement resulted in biased estimates of selection when using previously established step‐selection methods. However, we found that our correction models were able to produce accurate estimates across differing recursion scenarios. When applied to an empirical deer data set, these methods revealed a pattern of selection and avoidance for human modified areas that was masked by previous approaches. Our results suggest that long‐term recursive behaviour may have unappreciated effects on estimates from SSA. Specifically, since the used and available steps in SSA are associated with specific places and times, covariates must account for variation in spatial and temporal patterns of long‐term behaviour. Unless properly accounted for, the effects of long‐term recursive behaviour will inhibit the ability of SSA to characterize fine‐scale behaviours such as predator response or foraging ecology.

Abstract Background Triaxial accelerometers have revolutionized wildlife research by providing an unprecedented understanding of the behavior of free-living animals. Machine learning is often applied to acceleration data to classify diverse animal behaviors across taxa. However, the high frequency, continuous data collection typically favored for behavioral classification studies often generates very large data sets, which may inhibit remote data acquisition and make data storage challenging. Coarse-frequency sampling or non-continuous bursts of acceleration data reduce these problems. To analyze such data, a suite of variables that summarize key features of the behavior of interest can be generated. These variables can then be used in numerous classification approaches, accommodating variation in data collection methods or sampling regimes. We demonstrate the potential for non-continuous accelerometer data to identify long-duration behavior and employ machine learning to classify the nesting behaviors of the critically endangered eastern Santa Cruz giant tortoise (Chelonoidis donfaustoi). Results We field validated 112 nesting events from 21 giant tortoises. We then derived summary statistics based on accelerometry (e.g., overall dynamic body acceleration, metrics comparing acceleration before and after the probable event) and used them as inputs for Random Forest and Boosted Regression Tree classification algorithms. Our models produced a harmonic mean of precision and sensitivity (F1-score) of 0.91. We tested the generality of our model and found that the model performs well when applied to both novel individuals and years. The most important variable in accurately classifying data sequences was the proportion of acceleration data bursts above an activity threshold followed by the average overall dynamic body acceleration value of the bursts. Conclusions These results demonstrate the feasibility and efficacy of using non-continuous accelerometer data to identify prolonged, biologically relevant behaviors in free-living wildlife. By using summary variables that do not require continuous sampling, this approach facilitates long-term monitoring of animal behavior. Similar methodology has potential to inform priority questions in ecology and conservation, such as predicting wildlife responses to climate change and identifying critical habitats, with applications across diverse species and behaviors.

Abstract Background Spatial behavior, including home-ranging behaviors, habitat selection, and movement, can be extremely informative in estimating how animals respond to landscape heterogeneity. Responses in these spatial behaviors to features such as human land modification and resources can highlight a species’ spatial strategy to maximize fitness and minimize mortality. These strategies can vary on spatial, temporal, and individual scales, and the combination of behaviors on these scales can lead to very different strategies among species. Methods Harnessing the variation present at these scales, we characterized how species may respond to stimuli in their environments ranging from broad- to fine-scale spatial responses to human modification in their environment. Using 15 bobcat-years and 31 coyote-years of GPS data from individuals inhabiting a landscape encompassing a range of human land modification, we evaluated the complexity of both species’ responses to human modification on the landscape through their home range size, habitat selection, and functional response behaviors, accounting for annual, seasonal, and diel variation. Results Bobcats and coyotes used different strategies in response to human modification in their home ranges, with bobcats broadly expanding their home range with increases in human modification and displaying temporal consistency in functional response in habitat selection across both season and time of day. Meanwhile, coyotes did not expand their home ranges with increased human modification, but instead demonstrated fine-scale responses to human modification with habitat selection strategies that sometimes varied by time of day and season, paired with functional responses in selection behaviors. Conclusions These differences in response to habitat, resources, and human modification between the two species highlighted the variation in spatial behaviors animals can use to exist in anthropogenic environments. Categorizing animal spatial behavior based on these spatiotemporal responses and individual variation can help in predicting how a species will respond to future change based on their current spatial behavior.

Abstract Invasive alien species are among the most pervasive threats to biodiversity. Invasive species can cause catastrophic reductions in populations of native and endemic species and the collapse of ecosystem function. A second major global conservation concern is the extirpation of large‐bodied mobile animals, including long‐distance migrants, which often have keystone ecological roles over extensive spatial extents. Here, we report on a potentially catastrophic synergy between these phenomena that threatens the endemic biota of the Galapagos Archipelago. We used GPS telemetry to track 140 migratory journeys by 25 Western Santa Cruz Island Galapagos tortoises. We plotted the spatial interaction between tortoise migrations and recently established non‐native forest dominated by the invasive tree Cedrela odorata (Cedrela forest). We qualified (a) the proportion of migratory journeys that traversed Cedrela forest, and (b) the probability that this observed pattern occurred by chance. Tortoise migrations were overwhelmingly restricted to small corridors between Cedrela forest blocks, indicating clear avoidance of those blocks. Just eight of 140 migrations traversed extensive Cedrela stands. Tortoises avoid Cedrela forest during their migrations. Further expansion of Cedrela forest threatens long‐distance migration and population viability of critically endangered Galapagos tortoises. Applied research to determine effective management solutions to mitigate Cedrela invasion is a high priority.

Abstract Background Movement is a core mechanism through which animals interact with their environment. GPS telemetry is a popular approach used to investigate animal movement, providing access to both the spatial and temporal behavioral patterns exhibited by an individual or population. However, while some species are easily tracked through traditional GPS attachment methods (such as GPS collars or backpacks), other species such as the North American beaver (Castor canadensis) present unique challenges given their fusiform shape and tapered neck. Results We tested three different GPS transmitter attachment methods (tail-mounted, lower back glued-on, and upper back glued-on) for beavers over two seasons to determine which treatment was most effective in terms of retention time (RT, total number of days a transmitter remains attached) and GPS fix success rate (FSR, % of successful fixes vs. attempted) and investigated to what degree various factors (season, sex, and age class) affected these results. We then evaluated whether the data collected were sufficient for identifying home-ranging behavior (when an individual begins to display restricted space use and range residency). We found transmitters attached to the lower back during the fall to be the top performing treatment, having a similar mean FSR (51.59%) to upper back attachments in fall, but a significantly greater average RT (42.8 days). Of the 23 individuals included in the home-ranging behavior analysis, all but two had sufficient data for identifying home-ranging behavior. Conclusions Our tests show that glued-on GPS tags can provide up to 2 months of fine-scale relocation data in a safe and effective manner. This allows the opportunity to answer novel questions regarding movement patterns of beavers and other semi-aquatic mammals.

Abstract Host contact structure affects pathogen transmission in host populations, but many measures of host contact do not distinguish contacts that are relevant to pathogen transmission from those that are not. Scrapes are sites for chemical communication by white‐tailed deer (Odocoileus virginianus) during the breeding season and potential sites of transmission of prions, the causative agent of chronic wasting disease (CWD). Scrape‐related behaviors vary in their probability of transmitting prions to or from the environment, suggesting that behavior be combined with contact structure to better reflect potential heterogeneity in prion transmission at scrapes. We recorded visits and behaviors by deer at scrapes throughout DeSoto National Wildlife Refuge, Nebraska in 2005 and 2006. We recorded 2013 interactions by 169 unique identifiable males and 75 females. Adult males performed the most scrape‐related behaviors and spent the most time at scrapes, especially smelling the overhanging branch (70%), smelling the scrape (59%), licking/grasping the overhanging branch (44%), and scraping (36%). We used social network analysis to test the effect of behavior on indirect contact networks among deer at scrapes. By weighting edges based on the frequency and duration of behaviors, we produced networks representing sources of variation in scrape use and compared these networks to evaluate the effects of behavior on network contact structure. Social networks based on scrape‐related behavior were highly connected and dependent upon the frequency, duration, and type of behavior exhibited at scrapes (e.g., scraping, interacting with a scrape or overhanging branch, rub‐urinating, grazing) as well as the age of the deer. Accounting for contact frequency produced networks with lower variation in contact, but higher ability to facilitate contact among disparate groups. Including behavior when defining edges did not preserve the network properties of simpler measures (i.e., unweighted networks) suggesting that heterogeneity in behaviors that affect transmission probability is important for inferring transmission networks from contact networks. High connectivity through indirect contacts suggests that scrapes may be effective targets for management. Adult male deer had the highest connectivity, suggesting that management strategies focused on reducing their interaction with scrapes through density reduction or behavioral modification could reduce the connectivity of indirect contact networks.