How the interplay between individual spatial memory and landscape persistence can generate population distribution patterns

Memory-driven movement model for periodic migrations

We propose a model for memory-based movement of an individual. The dynamics are modeled by a stochastic differential equation, coupled with an eikonal equation, whose potential depends on the individual's memory and perception. Under a simple periodic environment, we discover that both long and short-term memory with appropriate time scales are essential for producing expected periodic migrations.

Movement rules determine nomadic species' responses to resource supplementation and degradation

In environments that vary unpredictably, many animals are nomadic, moving in an irregular pattern that differs from year to year. Exploring the mechanisms of nomadic movement is needed to understand how animals survive in highly variable environments, and to predict behavioural and population responses to environmental change. We developed a network model to identify plausible mechanisms of nomadic animal movement by comparing the performance of multiple movement rules along a continuum from nomadism to residency. Using simulations and analytical results, we explored how different types of habitat modifications (that augment or decrease resource availability) might affect the abundance and movement rates of animals following each of these rules. Movement rules for which departure from patches depended on resource availability and/or competition performed almost equally well and better than residency or uninformed movement under most conditions, even though animals using each rule moved at substantially different rates. Habitat modifications that stabilized resources, either by resource supplementation or degradation, eroded the benefits of informed nomadic movements, particularly for movements based on resource availability alone. These results suggest that simple movement rules can explain nomadic animal movements and determine species' responses to environmental change. In particular, landscape stabilization and supplementation might be useful strategies for promoting populations of resident animals, but would be less beneficial for managing highly mobile species, many of which are threatened by habitat disruption and changes in climate.

Crossover in spreading behavior due to memory in population dynamics

The reaction-diffusion equation is one of the possible ways for modeling animal movement, where the reactive part stands for the population growth and the diffusive part for random dispersal of the population. However, a reaction-diffusion model may not represent all aspects of the spatial dynamics, because of the existence of distinct mechanisms that can affect the movement, such as spatial memory, which results in a bias for one direction of dispersal. This bias is modeled through an advective term on an advection-reaction-diffusion equation. Thus, considering the effects of memory on the population spread, we propose a model composed of a coupled partial differential equation system with two equations: one for the population dynamics and the other for the memory density distribution. For the population growth, we use either the exponential or logistic growth function. The analytic approach shows that for the exponential and logistic growth, the minimum traveling wave speeds are the same with or without memory dynamics in which the variation of memory is infinitesimal. From the numerical analysis, we explore how our parameters, memory, growth rate, and carrying capacity, affect the population redistribution. The combinations of these parameters result in a redistribution pattern of the population associated with either diffusive or superdiffusive and imply the dispersal is faster than the diffusion. Further, in the parameter-space defined by memory and growth rate, we have shown that memory is a factor that switches the dynamics between two spreading behaviors, one faster than the other.

Intensive and extensive movements of feral camels in central Australia

A better understanding of the movement of feral dromedary camels (Camelus dromedarius) in Australia would be useful for planning removal operations (harvest or culling), because the pattern and scale of camel movement relates to the period they reside in a given area, and thus the search effort, timing and frequency of removal operations. From our results, we suspect that the dune direction influences how camels move across central Australia; particularly effects like the north–south longitudinal dune systems in the Simpson Desert, which appeared to elongate camel movement in the same direction as the dunes. We called this movement anisotropy. Research suggests camel movement in Australia is not migratory but partially cyclic, with two distinctive movement patterns. Our study investigated this further by using satellite tracking data from 54 camels in central Australia, recorded between 2007 and 2016. The mean tracking period for each animal was 363.9 days (s.e.m.=44.1 days). We used a method labelled multi-scale partitioning to test for changes in movement behaviour and partitioned more localised intensive movements within utilisation areas, from larger-scale movement, called ranging. This involved analysing the proximity of movement trajectories to other nearby trajectories of the same animal over time. We also used Dynamic Brownian Bridges Movement Models, which consider the relationship of consecutive locations to determine the areas of utilisation. The mean utilisation area and duration of a camel (n=658 areas) was found to be 342.6km2 (s.e.m.=33.2km2) over 23.5 days (s.e.m.=1.6 days), and the mean ranging distance (n=611 ranging paths) was a 45.1km (s.e.m.=2.0km) path over 3.1 days (s.e.m.=0.1 days).

Beyond Migration: Causes and Consequences of Nomadic Animal Movements

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.

Spatial memory shapes density dependence in population dynamics

Most population dynamics studies assume that individuals use space uniformly, and thus mix well spatially. In numerous species, however, individuals do not move randomly, but use spatial memory to visit renewable resource patches repeatedly. To understand the extent to which memory-based foraging movement may affect density-dependent population dynamics through its impact on competition, we developed a spatially explicit, individual-based movement model where reproduction and death are functions of foraging efficiency. We compared the dynamics of populations of with- and without-memory individuals. We showed that memory-based movement leads to a higher population size at equilibrium, to a higher depletion of the environment, to a marked discrepancy between the global (i.e. measured at the population level) and local (i.e. measured at the individual level) intensities of competition, and to a nonlinear density dependence. These results call for a deeper investigation of the impact of individual movement strategies and cognitive abilities on population dynamics.

Insights into feral goat movement in Australia using dynamic Brownian Bridges for movement analysis

Movement analyses were conducted for 50 goats across southern Australia using GPS satellite collars. A radio or satellite-tracked animal used to direct culling operations is generally called a ‘Judas’ animal. Goats used as ‘Judas’ animals in control operations were compared with non-‘Judas’ goats in the states of South Australia and Victoria, respectively. Their movement in two land systems were also compared. Dynamic Brownian Bridges Movement Models were used to calculate home ranges (95% utilisation areas). Changes in movement behaviour were identified to partition sedentary behaviour from long-distance movement events, defined here as ranging. Eleven goats exhibited ranging behaviour and moved from 9 to 33 km between their home ranges. After partitioning, their home ranges varied from 1.97 to 223.8 km2. In this study in the Southern Australian Mallee regions, non-‘Judas’ goats had significantly smaller home ranges than ‘Judas’ goats. However, no significant differences were found in the ranging distances between non-‘Judas’ goats and ‘Judas’ goats. Understanding these two distinct forms of goat movement is important in the planning and budgeting of removal operations. To demonstrate this a simple goat management decision tool is used to illustrate the biases that can result in the expected hours of removal operations when the assumptions about goat movement are ill-defined.

Metapopulation dynamics in a complex ecological landscape

We propose a general model to study the interplay between spatial dispersal and environment spatiotemporal fluctuations in metapopulation dynamics. An ecological landscape of favorable patches is generated like a Lévy dust, which allows to build a range of patterns, from dispersed to clustered ones. Locally, the dynamics is driven by a canonical model for the time evolution of the population density, consisting of a logistic expression plus multiplicative noises. Spatial coupling is introduced by means of two spreading mechanisms: diffusion and selective dispersal driven by patch suitability. We focus on the long-time population size as a function of habitat configurations, environment fluctuations, and coupling schemes. We obtain the conditions, that the spatial distribution of favorable patches and the coupling mechanisms must fulfill, to grant population survival. The fundamental phenomenon that we observe is the positive feedback between environment fluctuations and spatial spread preventing extinction.

Movement patterns, habitat use and site fidelity of the white croaker (Genyonemus lineatus) in the Palos Verdes Superfund Site, Los Angeles, California

White croaker (Genyonemus lineatus family: Sciaenidae) are a schooling, benthic foraging fish historically associated with soft sediment and wastewater outfalls in southern California. While they are often used as an indicator species due to their high organochlorine contaminant loads, little is known of their movements in relation to contaminated habitats. A Vemco Positioning System acoustic telemetry array was used to collect fine-scale movement data and characterize the site fidelity, area use, and dispersal of 83 white croaker on the Palos Verdes Shelf Superfund Site, California over 27 months. White croaker generally demonstrated low residency and recurrence to the Palos Verdes Shelf, and were observed to be largely nomadic. However, individual behavior was highly variable. Although the entire monitored shelf was visited by tagged white croaker, habitats in 0-200 m proximity to wastewater outfalls and between 25 and 35 m depth were used most frequently. Approximately half of white croaker migrated into Los Angeles and Long Beach Harbors; areas where they may be targeted by subsistence fishers. A model framework for incorporating fish movement data into contaminant exposure estimates was developed to better understanding organochlorine contaminant exposure for planning future remediation and monitoring.

Proximate cues to phases of movement in a highly dispersive waterfowl, Anas superciliosa

BACKGROUND

Waterfowl can exploit distant ephemeral wetlands in arid environments and provide valuable insights into the response of birds to rapid environmental change, and behavioural flexibility of avian movements. Currently much of our understanding of behavioural flexibility of avian movement comes from studies of migration in seasonally predictable biomes in the northern hemisphere. We used GPS transmitters to track 20 Pacific black duck (Anas superciliosa) in arid central Australia. We exploited La Niña conditions that brought extensive flooding, so allowing a rare opportunity to investigate how weather and other environmental factors predict initiation of long distance movement toward freshly flooded habitats. We employed behavioural change point analysis to identify three phases of movement: sedentary, exploratory and long distance oriented movement. We then used random forest models to determine the ability of meteorological and remote sensed landscape variables to predict initiation of these phases.

RESULTS

We found that initiation of exploratory movement phases is influenced by fluctuations in local weather conditions and accumulated rainfall in the landscape. Initiation of long distance movement phases was found to be highly individualistic with minor influence from local weather conditions.

CONCLUSIONS

Our study reveals how individuals utilise local conditions to respond to changes in resource distribution at broad scales. Our findings suggest that individual movement decisions of dispersive birds are informed by the integration of multiple weather cues operating at different temporal and spatial scales.

Consequences of animal interactions on their dynamics: emergence of home ranges and territoriality

Animal spacing has important implications for population abundance, species demography and the environment. Mechanisms underlying spatial segregation have their roots in the characteristics of the animals, their mutual interaction and their response, collective as well as individual, to environmental variables. This review describes how the combination of these factors shapes the patterns we observe and presents a practical, usable framework for the analysis of movement data in confined spaces. The basis of the framework is the theory of interacting random walks and the mathematical description of out-of-equilibrium systems. Although our focus is on modelling and interpreting animal home ranges and territories in vertebrates, we believe further studies on invertebrates may also help to answer questions and resolve unanswered puzzles that are still inaccessible to experimental investigation in vertebrate species.

Cognitive ecology: ecological factors, life-styles, and cognition

Cognitive ecology integrates cognition, ecology, and neurobiology in one topic and has recently broadened into an exciting diversity of themes covering the entire range of cognition and ecological conditions. The review identifies three major environmental factors interacting with cognition: environmental variation (predictable and unpredictable), environmental complexity and predation. Generally, variable environments favor cognitive abilities such as exploration, learning, innovation, memory and also result in larger brains as compared to stable environments. Likewise, cognition is enhanced in complex versus simple environments, whereas the relationship between predation and cognitive abilities can be positive or negative. However, organisms have often evolved entire life-styles (e.g., residency versus migration, food-caching versus noncaching, generalism versus specialism) to deal with these environmental factors. Considering cognition within this framework provides a much more diverse picture of how cognitive abilities evolved in conjunction with other adaptations to environmental challenges. This integrated approach identifies gaps of knowledge and allows the formulation of hypotheses for future testing. Several recently emerged approaches study cognitive abilities at a new and in part highly integrated level. For example, the effect that environment has on the development of cognitive abilities during ontogeny will improve our understanding about cause and effect and gene-environment interactions. Together with two recently emerged highly integrative approaches that link personality and pace-of-life syndromes with cognitive ecology these new directions will improve insight how cognition is interlinked with other major organizational processes. For further resources related to this article, please visit the WIREs website.

CONFLICT OF INTEREST

The author has declared no conflicts of interest for this article.

Stigmergy, collective actions, and animal social spacing

Collective animal behavior studies have led the way in developing models that account for a large number of individuals, but mostly have considered situations in which alignment and attraction play a key role, such as in schooling and flocking. By quantifying how animals react to one another's presence, when interaction is via conspecific avoidance rather than alignment or attraction, we present a mechanistic insight that enables us to link individual behavior and space use patterns. As animals respond to both current and past positions of their neighbors, the assumption that the relative location of individuals is statistically and history independent is not tenable, underscoring the limitations of traditional space use studies. We move beyond that assumption by constructing a framework to analyze spatial segregation of mobile animals when neighbor proximity may elicit a retreat, and by linking conspecific encounter rate to history-dependent avoidance behavior. Our approach rests on the knowledge that animals communicate by modifying the environment in which they live, providing a method to analyze social cohesion as stigmergy, a form of mediated animal-animal interaction. By considering a population of animals that mark the terrain as they move, we predict how the spatiotemporal patterns that emerge depend on the degree of stigmergy of the interaction processes. We find in particular that nonlocal decision rules may generate a nonmonotonic dependence of the animal encounter rate as a function of the tendency to retreat from locations recently visited by other conspecifics, which has fundamental implications for epidemic disease spread and animal sociality.

Ergodic crossover in partially self-avoiding stochastic walks

Consider a one-dimensional environment with N randomly distributed sites. An agent explores this random medium moving deterministically with a spatial memory μ. A crossover from local to global exploration occurs in one dimension at a well-defined memory value μ_{1}=log_{2}N. In its stochastic version, the dynamics is ruled by the memory and by temperature T, which affects the hopping displacement. This dynamics also shows a crossover in one dimension, obtained computationally, between exploration schemes, characterized yet by the trajectory size (N_{p}) (aging effect). In this paper we provide an analytical approach considering the modified stochastic version where the parameter T plays the role of a maximum hopping distance. This modification allows us to obtain a general analytical expression for the crossover, as a function of the parameters μ, T, and N_{p}. Differently from what has been proposed by previous studies, we find that the crossover occurs in any dimension d. These results have been validated by numerical experiments and may be of great value for fixing optimal parameters in search algorithms.