Memory drives the formation of animal home ranges: Evidence from a reintroduction

How resource abundance and resource stochasticity affect organisms' range sizes

BACKGROUND

From megafauna to amoebas, the amount of space heterotrophic organisms use is thought to be tightly linked to the availability of resources within their habitats, such that organisms living in productive habitats generally require less space than those in resource-poor habitats. This hypothesis has widespread empirical support, but existing studies have focused primarily on responses to spatiotemporal changes in mean resources, while responses to unpredictable changes in resources (i.e., variance in resources or resource stochasticity) are still largely unknown. Since organisms adjust to variable environmental conditions, failing to consider the effects of resource unpredictability can result in an insufficient understanding of an organism's range size.

METHODS

We leverage the available literature to provide a unifying framework and hypothesis for the effects of resource abundance and stochasticity on organisms' range sizes. We then use simulated movement data to demonstrate how the combined effects of resource abundance and stochasticity interact to shape predictable patterns in range size. Finally, we test the hypothesis using real-world tracking data on a lowland tapir (Tapirus terrestris) from the Brazilian Cerrado.

RESULTS

Organisms' range sizes decrease nonlinearly with resource abundance and increase nonlinearly with resource stochasticity, and the effects of resource stochasticity depend strongly on resource abundance. Additionally, the distribution and predictability of resources can exacerbate the effects of other drivers of movement, such as resource depletion, competition, and predation.

CONCLUSIONS

Accounting for resource abundance and stochasticity is crucial for understanding the movement behavior of free-ranging organisms. Failing to account for resource stochasticity can lead to an incomplete and incorrect understanding of how and why organisms move, particularly during periods of rapid change.

How Can Overlooking Social Interactions, Space Familiarity or Other "Invisible Landscapes" Shaping Animal Movement Bias Habitat Selection Estimations and Species Distribution Predictions?

Species' future distributions are commonly predicted using models that link the likelihood of occurrence of individuals to the environment. Although animals' movements are influenced by physical and non-physical landscapes, for example related to individual experiences such as space familiarity or previous encounters with conspecifics, species distribution models developed from observations of unknown individuals cannot integrate these latter variables, turning them into 'invisible landscapes'. In this theoretical study, we address how overlooking 'invisible landscapes' impacts the estimation of habitat selection and thereby the projection of future distributions. Overlooking the attraction towards some 'invisible' variable consistently led to overestimating the strength of habitat selection. Consequently, projections of future population distributions were also biased, with animals following changes in preferred habitat less than predicted. Our results reveal an overlooked challenge faced by correlative species distribution models based on the observation of unknown individuals, whose past experience of the environment is by definition not known. Mechanistic distribution modeling integrating cognitive processes underlying movement should be developed.

Identifying signals of memory from observations of animal movements

Incorporating memory (i.e., some notion of familiarity or experience with the landscape) into models of animal movement is a rising challenge in the field of movement ecology. The recent proliferation of new methods offers new opportunities to understand how memory influences movement. However, there are no clear guidelines for practitioners wishing to parameterize the effects of memory on moving animals. We review approaches for incorporating memory into step-selection analyses (SSAs), a frequently used movement modeling framework. Memory-informed SSAs can be constructed by including spatial-temporal covariates (or maps) that define some aspect of familiarity (e.g., whether, how often, or how long ago the animal visited different spatial locations) derived from long-term telemetry data. We demonstrate how various familiarity covariates can be included in SSAs using a series of coded examples in which we fit models to wildlife tracking data from a wide range of taxa. We discuss how these different approaches can be used to address questions related to whether and how animals use information from past experiences to inform their future movements. We also highlight challenges and decisions that the user must make when applying these methods to their tracking data. By reviewing different approaches and providing code templates for their implementation, we hope to inspire practitioners to investigate further the importance of memory in animal movements using wildlife tracking data.

Naivety dies with the calf: calf loss to human hunters imposes behavioral change in a long-lived but heavily harvested ungulate

BACKGROUND

In prey, patterns of individual habitat selection and movement can be a consequence of an individuals' anti-predator behavior. Adjustments of anti-predator behavior are important for prey to increase their survival. Hunters may alter the anti-predator behavior of prey. In long-lived animals, experience may cause behavioral changes during individuals' lifetime, which may result in altered habitat selection and movement. Our knowledge of which specific events related to hunting activity induce behavioral changes in solitary living species is still limited.

METHODS

We used offspring loss in a solitary and long-lived ungulate species, moose (Alces alces), as our model system. We investigated whether offspring loss to hunters induces behavioral changes in a species subjected to heavy human harvest but free from natural predation. To test for behavioral change in relation to two proxies for experience (calf fate and age), we combined movement data from 51 adult female moose with data on their offspring survival and female age. We tested for adjustments in females' habitat selection and movement following calf harvest using Hidden Markov Models and integrated Step Selection Analysis to obtain behavioral state specific habitat selection coefficients.

RESULTS

We found that females with a harvested calf modified habitat selection and movement during the following hunting season. Female moose selected for shorter distance to roads during the night, selected for shorter distance to forests and greater distance to human settlements following calf harvest than females who had not lost a calf. The survival of twins in a given hunting season was related to female age. Older females we more likely to have twins survive the hunting season.

CONCLUSIONS

Our findings suggest that losing offspring to human harvest imposes behavioral changes in a long-lived ungulate species, leading to adjustments in females' habitat selection and movement behavior, which may lower the risk of encountering hunters. In our study, female moose that experienced calf loss selected for lower distance to forest and selected for greater distance to human settlements during periods of high hunting pressure compared to females without the experience of calf loss during the previous hunting season. We interpret this as potential learning effects.

Land cover and space use influence coyote carnivory: evidence from stable-isotope analysis

For many species, the relationship between space use and diet composition is complex, with individuals adopting varying space use strategies such as territoriality to facilitate resource acquisition. Coyotes (Canis latrans) exhibit two disparate types of space use; defending mutually exclusive territories (residents) or moving nomadically across landscapes (transients). Resident coyotes have increased access to familiar food resources, thus improved foraging opportunities to compensate for the energetic costs of defending territories. Conversely, transients do not defend territories and are able to redirect energetic costs of territorial defense towards extensive movements in search of mates and breeding opportunities. These differences in space use attributed to different behavioral strategies likely influence foraging and ultimately diet composition, but these relationships have not been well studied. We investigated diet composition of resident and transient coyotes in the southeastern United States by pairing individual space use patterns with analysis of stable carbon (δ13C) and nitrogen (δ15N) isotope values to assess diet. During 2016-2017, we monitored 41 coyotes (26 residents, 15 transients) with GPS radio-collars along the Savannah River area in the southeastern United States. We observed a canopy effect on δ13C values and little anthropogenic food in coyote diets, suggesting 13C enrichment is likely more influenced by reduced canopy cover than consumption of human foods. We also observed other land cover effects, such as agricultural cover and road density, on δ15N values as well as reduced space used by coyotes, suggesting that cover types and localized, resident-like space use can influence the degree of carnivory in coyotes. Finally, diets and niche space did not differ between resident and transient coyotes despite differences observed in the proportional contribution of potential food sources to their diets. Although our stable isotope mixing models detected differences between the diets of resident and transient coyotes, both relied mostly on mammalian prey (52.8%, SD = 15.9 for residents, 42.0%, SD = 15.6 for transients). Resident coyotes consumed more game birds (21.3%, SD = 11.6 vs 13.7%, SD = 8.8) and less fruit (10.5%, SD = 6.9 vs 21.3%, SD = 10.7) and insects (7.2%, SD = 4.7 vs 14.3%, SD = 8.5) than did transients. Our findings indicate that coyote populations fall on a feeding continuum of omnivory to carnivory in which variability in feeding strategies is influenced by land cover characteristics and space use behaviors.

The role of memory-based movements in the formation of animal home ranges

Most animals live in spatially-constrained home ranges. The prevalence of this space-use pattern in nature suggests that general biological mechanisms are likely to be responsible for their occurrence. Individual-based models of animal movement in both theoretical and empirical settings have demonstrated that the revisitation of familiar areas through memory can lead to the formation of stable home ranges. Here, we formulate a deterministic, mechanistic home range model that includes the interplay between a bi-component memory and resource preference, and evaluate resulting patterns of space-use. We show that a bi-component memory process can lead to the formation of stable home ranges and control its size, with greater spatial memory capabilities being associated with larger home range size. The interplay between memory and resource preferences gives rise to a continuum of space-use patterns-from spatially-restricted movements into a home range that is influenced by local resource heterogeneity, to diffusive-like movements dependent on larger-scale resource distributions, such as in nomadism. Future work could take advantage of this model formulation to evaluate the role of memory in shaping individual performance in response to varying spatio-temporal resource patterns.

A Review of Cervidae Visual Ecology

This review examines the visual systems of cervids in relation to their ability to meet their ecological needs and how their visual systems are specialized for particular tasks. Cervidae encompasses a diverse group of mammals that serve as important ecological drivers within their ecosystems. Despite evidence of highly specialized visual systems, a large portion of cervid research ignores or fails to consider the realities of cervid vision as it relates to their ecology. Failure to account for an animal's visual ecology during research can lead to unintentional biases and uninformed conclusions regarding the decision making and behaviors for a species or population. Our review addresses core behaviors and their interrelationship with cervid visual characteristics. Historically, the study of cervid visual characteristics has been restricted to specific areas of inquiry such as color vision and contains limited integration into broader ecological and behavioral research. The purpose of our review is to bridge these gaps by offering a comprehensive review of cervid visual ecology that emphasizes the interplay between the visual adaptations of cervids and their interactions with habitats and other species. Ultimately, a better understanding of cervid visual ecology allows researchers to gain deeper insights into their behavior and ecology, providing critical information for conservation and management efforts.

Lévy movements and a slowly decaying memory allow efficient collective learning in groups of interacting foragers

Many animal species benefit from spatial learning to adapt their foraging movements to the distribution of resources. Learning involves the collection, storage and retrieval of information, and depends on both the random search strategies employed and the memory capacities of the individual. For animals living in social groups, spatial learning can be further enhanced by information transfer among group members. However, how individual behavior affects the emergence of collective states of learning is still poorly understood. Here, with the help of a spatially explicit agent-based model where individuals transfer information to their peers, we analyze the effects on the use of resources of varying memory capacities in combination with different exploration strategies, such as ordinary random walks and Lévy flights. We find that individual Lévy displacements associated with a slow memory decay lead to a very rapid collective response, a high group cohesion and to an optimal exploitation of the best resource patches in static but complex environments, even when the interaction rate among individuals is low.

Open problems in PDE models for knowledge-based animal movement via nonlocal perception and cognitive mapping

The inclusion of cognitive processes, such as perception, learning and memory, are inevitable in mechanistic animal movement modelling. Cognition is the unique feature that distinguishes animal movement from mere particle movement in chemistry or physics. Hence, it is essential to incorporate such knowledge-based processes into animal movement models. Here, we summarize popular deterministic mathematical models derived from first principles that begin to incorporate such influences on movement behaviour mechanisms. Most generally, these models take the form of nonlocal reaction-diffusion-advection equations, where the nonlocality may appear in the spatial domain, the temporal domain, or both. Mathematical rules of thumb are provided to judge the model rationality, to aid in model development or interpretation, and to streamline an understanding of the range of difficulty in possible model conceptions. To emphasize the importance of biological conclusions drawn from these models, we briefly present available mathematical techniques and introduce some existing "measures of success" to compare and contrast the possible predictions and outcomes. Throughout the review, we propose a large number of open problems relevant to this relatively new area, ranging from precise technical mathematical challenges, to more broad conceptual challenges at the cross-section between mathematics and ecology. This review paper is expected to act as a synthesis of existing efforts while also pushing the boundaries of current modelling perspectives to better understand the influence of cognitive movement mechanisms on movement behaviours and space use outcomes.

Spatial memory predicts home range size and predation risk in pheasants

Most animals confine their activities to a discrete home range, long assumed to reflect the fitness benefits of obtaining spatial knowledge about the landscape. However, few empirical studies have linked spatial memory to home range development or determined how selection operates on spatial memory via the latter's role in mediating space use. We assayed the cognitive ability of juvenile pheasants (Phasianus colchicus) reared under identical conditions before releasing them into the wild. Then, we used high-throughput tracking to record their movements as they developed their home ranges, and determined the location, timing and cause of mortality events. Individuals with greater spatial reference memory developed larger home ranges. Mortality risk from predators was highest at the periphery of an individual's home range in areas where they had less experience and opportunity to obtain spatial information. Predation risk was lower in individuals with greater spatial memory and larger core home ranges, suggesting selection may operate on spatial memory by increasing the ability to learn about predation risk across the landscape. Our results reveal that spatial memory, determined from abstract cognitive assays, shapes home range development and variation, and suggests predation risk selects for spatial memory via experience-dependent spatial variation in mortality.

Reinforced diffusions as models of memory-mediated animal movement

How memory shapes animals' movement paths is a topic of growing interest in ecology, with connections to planning for conservation and climate change. Empirical studies suggest that memory has both temporal and spatial components, and can include both attractive and aversive elements. Here, we introduce reinforced diffusions (the continuous time counterpart of reinforced random walks) as a modelling framework for understanding the role that memory plays in determining animal movements. This framework includes reinforcement via functions of time before present and of distance away from a current location. Focusing on the interplay between memory and central place attraction (a component of home ranging behaviour), we explore patterns of space usage that result from the reinforced diffusion. Our efforts identify three qualitatively different behaviours: bounded wandering behaviour that does not collapse spatially, collapse to a very small area, and, most intriguingly, convergence to a cycle. Subsequent applications show how reinforced diffusion can create movement trajectories emulating the learning of movement routes by homing pigeons and consolidation of ant travel paths. The mathematically explicit manner with which assumptions about the structure of memory can be stated and subsequently explored provides linkages to biological concepts like an animal's 'immediate surroundings' and memory decay.

Defining null expectations for animal site fidelity

Site fidelity-the tendency to return to previously visited locations-is widespread across taxa. Returns may be driven by several mechanisms, including memory, habitat selection, or chance; however, pattern-based definitions group different generating mechanisms under the same label of 'site fidelity', often assuming memory as the main driver. We propose an operational definition of site fidelity as patterns of return that deviate from a null expectation derived from a memory-free movement model. First, using agent-based simulations, we show that without memory, intrinsic movement characteristics and extrinsic landscape characteristics are key determinants of return patterns and that even random movements may generate substantial probabilities of return. Second, we illustrate how to implement our framework empirically to establish ecologically meaningful, system-specific null expectations for site fidelity. Our approach provides a conceptual and operational framework to test hypotheses on site fidelity across systems and scales.

Effects of Simulated Nitrogen Deposition and Micro-Environment on the Functional Traits of Two Rare and Endangered Fern Species in a Subtropical Forest

Although the effects of N deposition on forest plants have been widely reported, few studies have focused on rare and endangered fern species (REFs). Information is also lacking on the effects of micro-environments on REFs. We investigated the effects of N addition (canopy and understory N addition, CAN, and UAN) and micro-environments (soil and canopy conditions) on the functional traits (growth, defense, and reproduction; 19 traits in total) of two REFs-Alsophila podophylla and Cibotium baromet-in a subtropical forest in South China. We found that, compared to controls, CAN or UAN decreased the growth traits (e.g., plant height, H) of C. baromet, increased its defense traits (e.g., leaf organic acid concentrations, OA), delayed its reproductive event (all-spore release date), and prolonged its reproductive duration. In contrast, A. podophylla showed increased growth traits (e.g., H), decreased defense traits (e.g., OA), and advanced reproductive events (e.g., the all-spore emergence date) under CAN or UAN. Meanwhile, the negative effects on the C. baromet growth traits and A. podophylla defense traits were stronger for CAN than for UAN. In addition, the soil chemical properties always explained more of the variations in the growth and reproductive traits of the two REFs than the N addition. Our study indicates that, under simulated N deposition, C. baromet increases its investment in defense, whereas A. podophylla increases its investment in growth and reproduction; this may cause an increasing A. podophylla population and decreasing C. baromet population in subtropical forests. Our study also highlights the importance of considering micro-environments and the N-addition approach when predicting N deposition impact on subtropical forest REFs.