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Wolves (Canis lupus) are currently showing a remarkable comeback in the highly frag-mented cultural landscapes of Germany. We here show that wolf numbers increasedexponentially between 2000 and 2015 with an annual increase of about 36%. Wedemonstrate that the first territories in each newly colonized region were establishedover long distances from the nearest known reproducing pack on active militarytraining areas (MTAs). We show that MTAs, rather than protected areas, served asstepping-stones for the recolonization of Germany facilitating subsequent spreadingof wolf territories in the surrounding landscape. We did not find any significant differ-ence between MTAs and protected areas with regard to habitat. One possible reasonfor the importance of MTAs may be their lower anthropogenic mortality rates com-pared to protected and other areas. To our knowledge, this is the first documented casewhere MTAs facilitate the recolonization of an endangered species across large areas.
Plant regeneration is essential for maintaining forest biodiversity and ecosystem functioning, which are globally threatened by human disturbance. Here we present the first integrative meta-analysis on how forest disturbance affects multiple ecological processes of plant regeneration including pollination, seed dispersal, seed predation, recruitment and herbivory. We analysed 408 pairwise comparisons of these processes between near-natural and disturbed forests. Human impacts overall reduced plant regeneration. Importantly, only processes early in the regeneration cycle that often depend on plant-animal interactions, i.e. pollination and seed dispersal, were negatively affected. Later processes, i.e. seed predation, recruitment and herbivory, showed overall no significant response to human disturbance. Conserving pollination and seed dispersal, including the animals that provide these services to plants, should become a priority in forest conservation efforts globally.
Animal tracking and biologging devices record large amounts of data on individual movement behaviors in natural environments. In these data, movement ecologists often view unexplained variation around the mean as “noise” when studying patterns at the population level. In the field of behavioral ecology, however, focus has shifted from population means to the biological underpinnings of variation around means. Specifically, behavioral ecologists use repeated measures of individual behavior to partition behavioral variability into intrinsic among-individual variation and reversible behavioral plasticity and to quantify: a) individual variation in behavioral types (i.e. different average behavioral expression), b) individual variation in behavioral plasticity (i.e. different responsiveness of individuals to environmental gradients), c) individual variation in behavioral predictability (i.e. different residual within-individual variability of behavior around the mean), and d) correlations among these components and correlations in suites of behaviors, called ‘behavioral syndromes’. We here suggest that partitioning behavioral variability in animal movements will further the integration of movement ecology with other fields of behavioral ecology. We provide a literature review illustrating that individual differences in movement behaviors are insightful for wildlife and conservation studies and give recommendations regarding the data required for addressing such questions. In the accompanying R tutorial we provide a guide to the statistical approaches quantifying the different aspects of among-individual variation. We use movement data from 35 African elephants and show that elephants differ in a) their average behavior for three common movement behaviors, b) the rate at which they adjusted movement over a temporal gradient, and c) their behavioral predictability (ranging from more to less predictable individuals). Finally, two of the three movement behaviors were correlated into a behavioral syndrome (d), with farther moving individuals having shorter mean residence times. Though not explicitly tested here, individual differences in movement and predictability can affect an individual’s risk to be hunted or poached and could therefore open new avenues for conservation biologists to assess population viability. We hope that this review, tutorial, and worked example will encourage movement ecologists to examine the biology of individual variation in animal movements hidden behind the population mean.
Don't poke the bear : using tracking data to quantify behavioural syndromes in elusive wildlife
(2018)
Animal personality traits and the emergence of behavioural syndromes, i.e. between-individual correlation of behaviours, are commonly quantified from behavioural observations in controlled environments. Subjecting large and elusive wildlife to controlled test situations is, however, rarely possible, suggesting that ecologists should exploit alternative measures of behaviours for quantifying differences between individuals. Our goal was to test whether movement and space use data can be used to quantify behavioural syndromes in the wild. We quantified six behaviours from GPS and dual motion sensor tracking devices of 46 adult female brown bears followed in southcentral Sweden over the summer and early autumn. As well as daily travel distance, an indicator for activity, and daily displacement, an indicator for exploration, we quantified four behaviours that increase a bear's likelihood of encountering humans and could thus serve as indicators for boldness: diurnality, selection for roads and selection for two open habitat types, bogs and clearcuts, with low lateral cover. We tested (1) whether behaviours showed repeatable between-individual variation (animal personality) and (2) whether behaviours were correlated between individuals and thus formed a behavioural syndrome. Repeatability of behaviours ranged from 0.16 to 0.61 confirming between-individual variation in movement, activity and space use. A multivariate mixed model revealed significant positive correlations between travel distance, displacement and diurnality, suggesting the existence of an activity–exploration and potentially partial boldness syndrome in our bear population. Selection for exposed or human-frequented habitats were uncorrelated with the activity–exploration syndrome and with each other, albeit there was a trend for stronger road avoidance by bears that readily used clearcuts. We show that large tracking data sets can be used to quantify between-individual correlation in spatial behaviours. We suggest that delineating behavioural types from wildlife tracking data will be of increasing interest because of the importance of animal personality for ecological processes, wildlife conservation and human–wildlife coexistence.