Spatial Memory Drives Foraging Strategies of Wolves, but in Highly Individual Ways

The ability of wild animals to navigate and survive in complex and dynamic environments depends on their ability to store relevant information and place it in a spatial context. Despite the centrality of spatial memory, and given our increasing ability to observe animal movements in the wild, it is perhaps surprising how difficult it is to demonstrate spatial memory empirically. We present a cognitive analysis of movements of several wolves (Canis lupus) in Finland during a summer period of intensive hunting and den-centered pup-rearing. We tracked several wolves in the field by visiting nearly all GPS locations outside the den, allowing us to identify the species, location and timing of nearly all prey killed. We then developed a model that assigns a spatially explicit value based on memory of predation success and territorial marking. The framework allows for estimation of multiple cognitive parameters, including temporal and spatial scales of memory. For most wolves, fitted memory-based models outperformed null models by 20 to 50% at predicting locations where wolves chose to forage. However, there was a high amount of individual variability among wolves in strength and even direction of responses to experiences. Some wolves tended to return to locations with recent predation success-following a strategy of foraging site fidelity-while others appeared to prefer a site switching strategy. These differences are possibly explained by variability in pack sizes, numbers of pups, and features of the territories. Our analysis points toward concrete strategies for incorporating spatial memory in the study of animal movements while providing nuanced insights into the behavioral strategies of individual predators.Peer reviewe

Moving in the anthropocene: global reductions in terrestrial mammalian movements

Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission

Incorporating cognition into models of animal movement and predator--prey interaction

Thesis (Ph.D.)--University of Washington, 2014Incorporating cognition, i.e., learning and memory, into models of animal movement is increasingly important as models seek to answer more complex questions where individuals' prior experiences shape their choices. Two example are foraging behavior and predator avoidance. While models of predator--prey dynamics exist, the impact of cognition on movement and predator--prey interactions is largely unexplored. This dissertation presents a flexible, continuous-space, and continuous-time model incorporating an animal using memory to navigate a landscape of heterogeneous resources. The forager balances attraction to food with avoidance of predators in making movement decisions. Two streams make up the resource memory: a repulsive stream that drives the forager away from recently visited areas and an attractive stream that draws the forager back to high quality areas. The predator memory is solely repulsive. The model is used to examine questions related to the advantage of added cognitive complexity for animals in the context of foraging and balancing the food--safety trade-off with predators. First, foraging without predators is considered and several movement processes are compared: a simple correlated random walk; kinesis, a correlated random walk that switches between searching and feeding behaviors; and memory-informed movement. The model is used to examine for which landscapes the added cognitive complexity of maintaining memory is advantageous and to analyze the behavioral differences between using and not using memory. In general, a landscape where there is a larger payoff for finding a resource patch, whether in size, value, or difficulty in locating, favors memory. While memory-informed search can be difficult to differentiate from other sensory-driven search behavior, disproportionate spatial use of higher value areas, higher consumption rates, and consumption variability all point to memory influencing the movement direction. Next, predators are introduced that vary in their temporal predictability and in their correlation with the prey's resources. Memory outperforms simpler movement processes most for patchy landscapes and more predictable predators, which may be more easily avoided once learned. In these cases, memory aids foragers in managing the food--safety trade-off, as particular parameterizations of predator memory reduce predator encounters while maintaining consumption. Non-consumptive effects are highest in landscapes of concentrated, patchy resources and especially when predators are highly correlated with the forager's resources. These non-consumptive effects are also seen with the shift away from the best quality habitat compared to foraging in a predator-free environment. Finally, learning is examined in more detail with naive foragers introduced to new landscapes as well as predators introduced partway through the simulation. Most non-extreme learning rates provide the forager with sufficient information. In general, foragers that are low to moderately exploratory in new habitats are successful, though performance is habitat-dependent. In the case of introduced predators, predators vary in the area threatened and foragers vary in their memory state. While area threatened plays a key role in determining how much habitat use changes, the forager's knowledge of alternative habitats and exploratory inclinations affects what types of shifts occur

Appendix B: Supplemental figures and tables from Memory, not just perception, plays an important role in terrestrial mammalian migration

Additional figures and tables

Appendix A: Model Description from Memory, not just perception, plays an important role in terrestrial mammalian migration

The model description following the ODD (Overview, Design concepts, Details) protocol

Memory effects on movement behavior in animal foraging

An individual's choices are shaped by its experience, a fundamental property of behavior important to understanding complex processes. Learning and memory are observed across many taxa and can drive behaviors, including foraging behavior. To explore the conditions under which memory provides an advantage, we present a continuous-space, continuous-time model of animal movement that incorporates learning and memory. Using simulation models, we evaluate the benefit memory provides across several types of landscapes with variable-quality resources and compare the memory model within a nested hierarchy of simpler models (behavioral switching and random walk). We find that memory almost always leads to improved foraging success, but that this effect is most marked in landscapes containing sparse, contiguous patches of high-value resources that regenerate relatively fast and are located in an otherwise devoid landscape. In these cases, there is a large payoff for finding a resource patch, due to size, value, or locational difficulty. While memory-informed search is difficult to differentiate from other factors using solely movement data, our results suggest that disproportionate spatial use of higher value areas, higher consumption rates, and consumption variability all point to memory influencing the movement direction of animals in certain ecosystems

Sample generated landscapes for different combinations of patch concentration from patchy to smooth and patch size from small to large.

<p>Color indicates resource quality from none (white) to low (light green) to high (dark green). Total resources in each landscape are the same.</p

Widespread testing, case isolation and contact tracing may allow safe school reopening with continued moderate physical distancing: A modeling analysis of King County, WA data

Background: In late March 2020, a “Stay Home, Stay Healthy” order was issued in Washington State in response to the COVID-19 pandemic. On May 1, a 4-phase reopening plan began. We investigated whether adjunctive prevention strategies would allow less restrictive physical distancing to avoid second epidemic waves and secure safe school reopening. Methods: We developed a mathematical model, stratifying the population by age, infection status and treatment status to project SARS-CoV-2 transmission during and after the reopening period. The model was parameterized with demographic and contact data from King County, WA and calibrated to confirmed cases, deaths and epidemic peak timing. Adjunctive prevention interventions were simulated assuming different levels of pre-COVID physical interactions (pC_PI) restored. Results: The best model fit estimated ~35% pC_PI under the lockdown which prevented ~17,000 deaths by May 15. Gradually restoring 75% pC_PI for all age groups between May 15-July 15 would have resulted in ~350 daily deaths by early September 2020. Maintaining <45% pC_PI was required with current testing practices to ensure low levels of daily infections and deaths. Increased testing, isolation of symptomatic infections, and contact tracing permitted 60% pC_PI without significant increases in daily deaths before November and allowed opening of schools with <15 daily deaths. Inpatient antiviral treatment was predicted to reduce deaths significantly without lowering cases or hospitalizations. Conclusions: We predict that widespread testing, contact tracing and case isolation would allow relaxation of physical distancing, as well as opening of schools, without a surge in local cases and deaths

What is the animal doing? Tools for exploring behavioural structure in animal movements

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