BackgroundCharacterizing the movement patterns of animals is an important step in understanding their ecology. Various methods have been developed for classifying animal movement at both coarse (e.g., migratory vs. sedentary behavior) and fine (e.g., resting vs. foraging) scales. A popular approach for classifying movements at coarse resolutions involves fitting time series of net-squared displacement (NSD) to models representing different conceptualizations of coarse movement strategies (i.e., migration, nomadism, sedentarism, etc.). However, the performance of this method in classifying actual (as opposed to simulated) animal movements has been mixed. Here, we develop a more flexible method that uses the same NSD input, but relies on an underlying discrete latent state model. Using simulated data, we first assess how well patterns in the number of transitions between modes of movement and the duration of time spent in a mode classify movement strategies. We then apply our approach to elucidate variability in the movement strategies of eight giant tortoises (Chelonoidis sp.) using a multi-year (2009–2014) GPS dataset from three different Galapagos Islands.ResultsWith respect to patterns of time spent and the number of transitions between modes, our approach out-performed previous efforts to distinguish among migration, dispersal, and sedentary behavior. We documented marked inter-individual variation in giant tortoise movement strategies, with behaviors indicating migration, dispersal, nomadism and sedentarism, as well as hybrid behaviors such as “exploratory residence”.ConclusionsDistilling complex animal movement into discrete modes remains a fundamental challenge in movement ecology, a problem made more complex by the ever-longer duration, ever-finer resolution, and gap-ridden trajectories recorded by GPS devices. By clustering into modes, we derived information on the time spent within one mode and the number of transitions between modes which enabled finer differentiation of movement strategies over previous methods. Ultimately, the techniques developed here address limitations of previous approaches and provide greater insights with respect to characterization of movement strategies across scales by more fully utilizing long-term GPS telemetry datasets.Electronic supplementary materialThe online version of this article (doi:10.1186/s40462-016-0080-y) contains supplementary material, which is available to authorized users.

In ungulates, parturition is correlated with a reduction in movement rate. With advances in movement-based technologies comes an opportunity to develop new techniques to assess reproduction in wild ungulates that are less invasive and reduce biases. DeMars et al. (2013, Ecology and Evolution 3:4149–4160) proposed two promising new methods (individual- and population-based; the DeMars model) that use GPS inter-fix step length of adult female caribou (Rangifer tarandus caribou) to infer parturition and neonate survival. Our objective was to apply the DeMars model to caribou populations that may violate model assumptions for retrospective analysis of parturition and calf survival. We extended the use of the DeMars model after assigning parturition and calf mortality status by examining herd-wide distributions of parturition date, calf mortality date, and survival. We used the DeMars model to estimate parturition and calf mortality events and compared them with the known parturition and calf mortality events from collared adult females (n = 19). We also used the DeMars model to estimate parturition and calf mortality events for collared female caribou with unknown parturition and calf mortality events (n = 43) and instead derived herd-wide estimates of calf survival as well as distributions of parturition and calf mortality dates and compared them to herd-wide estimates generated from calves fitted with VHF collars (n = 134). For our data, the individual-based method was effective at predicting calf mortality, but was not effective at predicting parturition. The population-based method was more effective at predicting parturition but was not effective at predicting calf mortality. At the herd-level, the predicted distributions of parturition date from both methods differed from each other and from the distribution derived from the parturition dates of VHF-collared calves (log-ranked test: χ2 = 40.5, df = 2, p < 0.01). The predicted distributions of calf mortality dates from both methods were similar to the observed distribution derived from VHF-collared calves. Both methods underestimated herd-wide calf survival based on VHF-collared calves, however, a combination of the individual- and population-based methods produced herd-wide survival estimates similar to estimates generated from collared calves. The limitations we experienced when applying the DeMars model could result from the shortcomings in our data violating model assumptions. However despite the differences in our caribou systems, with proper validation techniques the framework in the DeMars model is sufficient to make inferences on parturition and calf mortality.

Summary1. There is a growing need for scientific synthesis in ecology and evolution. In many cases, meta-analytic techniques can be used to complement such synthesis. However, missing data are a serious problem for any synthetic efforts and can compromise the integrity of meta-analyses in these and other disciplines. Currently, the prevalence of missing data in meta-analytic data sets in ecology and the efficacy of different remedies for this problem have not been adequately quantified. 2. We generated meta-analytic data sets based on literature reviews of experimental and observational data and found that missing data were prevalent in meta-analytic ecological data sets. We then tested the performance of complete case removal (a widely used method when data are missing) and multiple imputation (an alternative method for data recovery) and assessed model bias, precision and multimodel rankings under a variety of simulated conditions using published meta-regression data sets. 3. We found that complete case removal led to biased and imprecise coefficient estimates and yielded poorly specified models. In contrast, multiple imputation provided unbiased parameter estimates with only a small loss in precision. The performance of multiple imputation, however, was dependent on the type of data missing. It performed best when missing values were weighting variables, but performance was mixed when missing values were predictor variables. Multiple imputation performed poorly when imputing raw data which were then used to calculate effect size and the weighting variable. 4. We conclude that complete case removal should not be used in meta-regression and that multiple imputation has the potential to be an indispensable tool for meta-regression in ecology and evolution. However, we recommend that users assess the performance of multiple imputation by simulating missing data on a subset of their data before implementing it to recover actual missing data.

Habitat selection is a multi‐level, hierarchical process that should be a key component in the balance between food acquisition and predation risk avoidance (food–predation trade‐off). However, to date, studies have not fully elucidated how fine‐ and broad‐scale habitat decisions by individual prey can help balance food versus risk. We studied broad‐scale habitat selection by Newfoundland caribou Rangifer tarandus, focusing on trade‐offs between predation risk versus access to forage during the calving and post‐calving period. We improved traditional measures of habitat availability by incorporating fine‐scale movement patterns of caribou into the availability kernel, thus enabling separation of broad and fine scales of selection. Remote sensing and field surveys served to create a spatio‐temporal model of forage availability, whereas GPS telemetry locations from 66 black bears Ursus americanus and 59 coyotes Canis latrans provided models of predation risk. We then used GPS telemetry locations from 114 female caribou to assess food–predation trade‐offs through the prism of our refined model of caribou habitat availability. We noted that migratory movements of caribou were oriented mainly towards habitats with abundant forage and lower risk of bear and (to a lesser extent) coyote encounter. These findings were generally consistent across caribou herds and would not have been evident had we used traditional methods instead of our refined model when estimating habitat availability. We interpret these findings in the context of stereotypical migratory behaviour observed in Newfoundland caribou, which occurs despite the extirpation of wolves Canis lupus nearly a century ago. We submit that caribou are able to balance food acquisition against predation risk using a complex set of factors involving both finer and broader scale selection. Accordingly, our study provides a strong argument for using refined habitat availability estimates when assessing food–predation trade‐offs.