Ungulate migrations are assumed to stem from learning and cultural transmission of information regarding seasonal distribution of forage, but this hypothesis has not been tested empirically. We compared the migratory propensities of bighorn sheep and moose translocated into novel habitats with those of historical populations that had persisted for hundreds of years. Whereas individuals from historical populations were largely migratory, translocated individuals initially were not. After multiple decades, however, translocated populations gained knowledge about surfing green waves of forage (tracking plant phenology) and increased their propensity to migrate. Our findings indicate that learning and cultural transmission are the primary mechanisms by which ungulate migrations evolve. Loss of migration will therefore expunge generations of knowledge about the locations of high-quality forage and likely suppress population abundance.

https://science.sciencemag.org/content/sci/361/6406/1023.full.pdf

Is ungulate migration culturally transmitted? Evidence of social learning from translocated animals

Recent advances in animal tracking reveal that many species display irregular movements that do not fall into classical categories of movement patterns such as range residency or migration. Here, we develop a unifying framework that distinguishes these nomadic movements based on their patterns, drivers, and mechanisms. Though they occur in diverse taxa and geographic regions, nomadic movements are united by both their underlying environmental drivers, mainly environmental stochasticity, and the resulting irregular, far-ranging movement patterns. The framework further classifies types of nomadic movements, including full, seasonal, phase, irruptive, and partial nomadism. Nomadic movements can have unique effects on populations, communities, and ecosystems, most notably providing intermittent disturbances and novel introductions of propagules.

Beyond Migration: Causes and Consequences of Nomadic Animal Movements

Accurately estimating home range and understanding movement behavior can provide important information on ecological processes. Advances in data collection and analysis have improved our ability to estimate home range and movement parameters, both of which have the potential to impact species conservation. Fitting continuous-time movement model to data and incorporating the autocorrelated kernel density estimator (AKDE), we investigated range residency of forty-four jaguars fit with GPS collars across five biomes in Brazil and Argentina. We assessed home range and movement parameters of range resident animals and compared AKDE estimates with kernel density estimates (KDE). We accounted for differential space use and movement among individuals, sex, region, and habitat quality. Thirty-three (80%) of collared jaguars were range resident. Home range estimates using AKDE were 1.02 to 4.80 times larger than KDE estimates that did not consider autocorrelation. Males exhibited larger home ranges, more directional movement paths, and a trend towards larger distances traveled per day. Jaguars with the largest home ranges occupied the Atlantic Forest, a biome with high levels of deforestation and high human population density. Our results fill a gap in the knowledge of the species’ ecology with an aim towards better conservation of this endangered/critically endangered carnivore—the top predator in the Neotropics.

/pdf/space-use-and-movement-of-a-neotropical-top-predator-the-1fyroyd3n5.pdf

Space Use and Movement of a Neotropical Top Predator: The Endangered Jaguar

The expansion of global communication networks and advances in animal-tracking technology make possible the real-time telemetry of positional data as recorded by animal-attached tracking units. When combined with continuous, algorithm-based analytical capability, unique opportunities emerge for applied ecological monitoring and wildlife conservation. We present here four broad approaches for algorithmic wildlife monitoring in real time--proximity, geofencing, movement rate, and immobility--designed to examine aspects of wildlife spatial activity and behavior not possible with conventional tracking systems. Application of these four routines to the real-time monitoring of 94 African elephants was made. We also provide details of our cloud-based monitoring system including infrastructure, data collection, and customized software for continuous tracking data analysis. We also highlight future directions of real-time collection and analysis of biological, physiological, and environmental information from wildlife to encourage further development of needed algorithms and monitoring technology. Real-time processing of remotely collected, animal biospatial data promises to open novel directions in ecological research, applied species monitoring, conservation programs, and public outreach and education.

https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1890/13-1971.1

Novel opportunities for wildlife conservation and research with real-time monitoring

Summary 1. Impediments to animal movement are ubiquitous and vary widely in both scale and permeability. It is essential to understand how impediments alter ecological dynamics via their influence on animal behavioural strategies governing space use and, for anthropogenic features such as roads and fences, how to mitigate these effects to effectively manage species and landscapes. 2. Here, we focused primarily on barriers to movement, which we define as features that cannot be circumnavigated but may be crossed. Responses to barriers will be influenced by the movement capabilities of the animal, its proximity to the barriers, and habitat preference. We developed a mechanistic modelling framework for simultaneously quantifying the permeability and proximity effects of barriers on habitat preference and movement. 3. We used simulations based on our model to demonstrate how parameters on movement, habitat preference and barrier permeability can be estimated statistically. We then applied the model to a case study of road effects on wild mountain reindeer summer movements. 4. This framework provided unbiased and precise parameter estimates across a range of strengths of preferences and barrier permeabilities. The quality of permeability estimates, however, was correlated with the number of times the barrier is crossed and the number of locations in proximity to barriers. In the case study we found that reindeer avoided areas near roads and that roads are semi-permeable barriers to movement. There was strong avoidance of roads extending up to c. 1 km for four of five animals, and having to cross roads reduced the probability of movement by 68� 6% (range 3� 5–99� 5%). 5. Human infrastructure has embedded within it the idea of networks: nodes connected by linear features such as roads, rail tracks, pipelines, fences and cables, many of which divide the landscape and limit animal movement. The unintended but potentially profound consequences of infrastructure on animals remain poorly understood. The rigorous framework for simultaneously quantifying movement, habitat preference and barrier permeability developed here begins to address this knowledge gap.

/pdf/you-shall-not-pass-quantifying-barrier-permeability-and-4xp7m364f5.pdf

'You shall not pass!': quantifying barrier permeability and proximity avoidance by animals.

Understanding the causes and consequences of animal movements is of fundamental biological interest because any alteration in movement can have direct and indirect effects on ecosystem structure and function. It is also crucial for assisting spatial wildlife management under variable environmental change scenarios. Recent research has highlighted the need of quantifying individual variability in movement behavior and how it is generated by interactions between individual requirements and environmental conditions, to understand the emergence of population-level patterns. Using a multi-annual movement data set of 213 individual moose (Alces alces) across a latitudinal gradient (from 56 degrees to 67 degrees N) that spans over 1100 km of varying environmental conditions, we analyze the differences in individual and population-level movements. We tested the effect of climate, risk, and human presence in the landscape on moose movements. The variation in these factors explained the existence of multiple movements (migration, nomadism, dispersal, sedentary) among individuals and seven populations. Population differences were primarily related to latitudinal variation in snow depth and road density. Individuals showed both fixed and flexible behaviors across years, and were less likely to migrate with age in interaction with snow and roads. For the predominant movement strategy, migration, the distance, timing, and duration at all latitudes varied between years. Males traveled longer distances and began migrating later in spring than females. Our study provides strong quantitative evidence for the dynamics of animal movements in response to changes in environmental conditions along with varying risk from human influence across the landscape. For moose, given its wide distributional range, changes in the distribution and migratory behavior are expected under future warming scenarios.

https://navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/singh_et_al._2012_ea.pdf

From migration to nomadism: movement variability in a northern ungulate across its latitudinal range

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From migration to nomadism: movement variability in a northern ungulate across its latitudinal range