The evolution of an ‘intelligent’ dispersal strategy: biased, correlated random walks in patchy landscapes

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.

Recent trends in movement ecology of animals and human mobility

Movement is fundamental to life, shaping population dynamics, biodiversity patterns, and ecosystem structure. In 2008, the movement ecology framework (MEF Nathan et al. in PNAS 105(49):19052-19059, 2008) introduced an integrative theory of organismal movement-linking internal state, motion capacity, and navigation capacity to external factors-which has been recognized as a milestone in the field. Since then, the study of movement experienced a technological boom, which provided massive quantities of tracking data of both animal and human movement globally and at ever finer spatio-temporal resolutions. In this work, we provide a quantitative assessment of the state of research within the MEF, focusing on animal movement, including humans and invertebrates, and excluding movement of plants and microorganisms. Using a text mining approach, we digitally scanned the contents of [Formula: see text] papers from 2009 to 2018 available online, identified tools and methods used, and assessed linkages between all components of the MEF. Over the past decade, the publication rate has increased considerably, along with major technological changes, such as an increased use of GPS devices and accelerometers and a majority of studies now using the R software environment for statistical computing. However, animal movement research still largely focuses on the effect of environmental factors on movement, with motion and navigation continuing to receive little attention. A search of topics based on words featured in abstracts revealed a clustering of papers among marine and terrestrial realms, as well as applications and methods across taxa. We discuss the potential for technological and methodological advances in the field to lead to more integrated and interdisciplinary research and an increased exploration of key movement processes such as navigation, as well as the evolutionary, physiological, and life-history consequences of movement.

Population Growth and Long-Distance Vagrancy Leads to Colonization of Europe by Elegant Terns Thalasseus elegans

Elegant terns Thalasseus elegans breed in a very limited area of the northern Gulf of California and the Pacific coast of southern California, with up to 95% (mean 78%, 1991–2014, Perez et al., 2020) of the population nesting on Isla Rasa in the northern Gulf of California. On Isla Rasa, the primary nesting colony, elegant terns suffered predation by rodents which raised the possibility of population extinction, with a substantial proportion of the world population nesting on this single island. Because of this threat, rodents were successfully removed from Isla Rasa in 1995. The removal of rodents from Isla Rasa led to a near immediate increase in the population of elegant terns. That increase was associated with a changing pattern in dispersal by the terns, including extraordinary movements to the Gulf of Mexico, the Atlantic coast of the United States north to Massachusetts, and, remarkably, to western Europe. A few elegant terns successfully bred at these European localities during 2009 to the present. In this paper we use this exceptional example of long-distance dispersal to illustrate how rapid population growth during ∼ 1995 to present can lead to successful colonization of remote sites through repeated instances of vagrancy. We tested four Hypotheses that together support the idea that the growing population of elegant terns has produced increasing numbers of young, and these young have spread, through the mechanism of vagrancy, to the Pacific Northwest, the east coast of the United States, and western Europe. Our Hypotheses are: (1) The nesting population of elegant terns within their core nesting range has increased since removal of rodents from Isla Rasa; (2) Occurrence of vagrant elegant terns in the Pacific Northwest is driven by population growth within the core breeding range. (3) Occurrence of vagrant elegant terns at the east coast of the United States is driven by population growth within the core breeding range. (4) Occurrence and colonization of western Europe by elegant terns is driven by nesting population size within the core breeding range. Corollaries of these Hypotheses are, (i) that there is a time lag in occurrence of vagrants at each of these areas, based on increasing distance from the core breeding range and (ii) the number of vagrants in any given year is also related to sea surface temperature (SST), as expressed by Oceanic Niño Index, a proxy for food resource levels. Generally we found strong statistical support for each of these Hypotheses; an exception was for the occurrence of elegant terns in the Pacific Northwest, which initially occurred following El Niño events (low food supply) and profound breeding failure, but later corresponding to cold water years with high breeding success. We use elegant terns, exceptional for the highly restricted breeding range and sustained population growth over 25 years, to illustrate how growing populations may colonize very distant habitats through repeated instances of vagrancy.

Estimating Perceptual Range of Female Monarch Butterflies (Danaus plexippus) to Potted Vegetative Common Milkweed (Asclepias syriaca) and Blooming Nectar Resources

Habitat loss in the summer breeding range contributes to eastern North American monarch (Lepidoptera: Nymphalidae) population decline. Habitat restoration efforts include increasing native prairie plants for adult forage and milkweed (Asclepias spp.) for oviposition and larval development. As the monarch is a vagile species, habitat establishment at a grain that matches the monarch perceptual range will facilitate efficient movement, decrease fitness costs of dispersal, and increase oviposition. We released 188 experimental monarch females 5, 25, 50, and 75 m downwind from potted milkweed and blooming forbs in 4-32 ha sod fields. Perceptual range was estimated from monarchs that flew towards and landed on the milkweed and forbs. Flight patterns of 49 non-experimental monarchs that landed on the resources were also observed. In our experimental, resource-devoid setting, wind-facilitated movement occurred most frequently. Monarchs performed direct displacement as evidenced by shallow turn angles and similarity of Euclidian and total distances traveled. We hypothesize similar monarch flight behavior when traveling over other resource-devoid areas, such as crop fields. Although the majority of experimental monarchs flew downwind, eight experimental and 49 non-experimental monarchs were observed flying upwind toward, and landing on, the potted resources from distances ranging from 3 to 125 m (mean = 30.98 m, median = 25 m, mode = 25 m). A conservative estimate of the perceptual range is 125 m, as longer distances cannot be precluded; however, the majority of observations were ≤50 m. Our findings suggest establishing habitat patches ~ 50 m apart would create functional connectivity across fragmented agricultural landscapes.

Long-term survival probability, not current habitat quality, predicts dispersal distance in a stream salamander

Dispersal evolves as an adaptive mechanism to optimize individual fitness across the landscape. Specifically, dispersal represents a mechanism to escape fitness costs resulting from changes in environmental conditions. Decades of empirical work suggest that individuals use local habitat cues to make movement decisions, but theory predicts that dispersal can also evolve as a fixed trait, independent of local conditions, in environments characterized by a history of stochastic spatiotemporal variation. Until now, however, both conditional and fixed models of dispersal evolution have primarily been evaluated using emigration data (stay vs. leave), and not dispersal distances: a more comprehensive measure of dispersal. Our goal was to test whether conditional or fixed models of dispersal evolution predict variation in dispersal distance in the stream salamander Gyrinophilus porphyriticus. We quantified variation in habitat conditions using measures of salamander performance from 4 yr of spatially explicit, capture-mark-recapture (CMR) data across three headwater streams in the Hubbard Brook Experimental Forest in central New Hampshire, USA. We used body condition as an index of local habitat quality that individuals may use to make dispersal decisions, and survival probability estimated from multistate CMR models as an index of mortality risk resulting from the long-term history of environmental variation. We found that dispersal distances increased with declining survival probability, indicating that salamanders disperse further in risky environments. Dispersal distances were unrelated to spatial variation in body condition, suggesting that salamanders do not base dispersal distance decisions on local habitat quality. Our study provides the first empirical support for fixed models of dispersal evolution, which predict that dispersal evolves in response to a history of spatiotemporal environmental variation, rather than as a conditional response to current habitat conditions. More broadly, this study underscores the value of assessing alternative scales of environmental variation to gain a more complete and balanced understanding of dispersal evolution.

Inferring the rules of social interaction in migrating caribou

Social interactions are a significant factor that influence the decision-making of species ranging from humans to bacteria. In the context of animal migration, social interactions may lead to improved decision-making, greater ability to respond to environmental cues, and the cultural transmission of optimal routes. Despite their significance, the precise nature of social interactions in migrating species remains largely unknown. Here we deploy unmanned aerial systems to collect aerial footage of caribou as they undertake their migration from Victoria Island to mainland Canada. Through a Bayesian analysis of trajectories we reveal the fine-scale interaction rules of migrating caribou and show they are attracted to one another and copy directional choices of neighbours, but do not interact through clearly defined metric or topological interaction ranges. By explicitly considering the role of social information on movement decisions we construct a map of near neighbour influence that quantifies the nature of information flow in these herds. These results will inform more realistic, mechanism-based models of migration in caribou and other social ungulates, leading to better predictions of spatial use patterns and responses to changing environmental conditions. Moreover, we anticipate that the protocol we developed here will be broadly applicable to study social behaviour in a wide range of migratory and non-migratory taxa.

This article is part of the theme issue ‘Collective movement ecology’.

Effects of mis-alignment between dispersal traits and landscape structure on dispersal success in fragmented landscapes

Dispersal is fundamental to population dynamics and hence extinction risk. The dispersal success of animals depends on the biophysical structure of their environments and their biological traits; however, comparatively little is known about how evolutionary trade-offs among suites of biological traits affect dispersal potential. We developed a spatially explicit agent-based simulation model to evaluate the influence of trade-offs among a suite of biological traits on the dispersal success of vagile animals in fragmented landscapes. We specifically chose traits known to influence dispersal success: speed of movement, perceptual range, risk of predation, need to forage during dispersal, and amount of suitable habitat required for successful settlement in a patch. Using the metric of relative dispersal success rate, we assessed how the costs and benefits of evolutionary investment in these biological traits varied with landscape structure. In heterogeneous environments with low habitat availability and scattered habitat patches, individuals with more equal allocation across the trait spectrum dispersed most successfully. Our analyses suggest that the dispersal success of animals in heterogeneous environments is highly dependent on hierarchical interactions between trait trade-offs and the geometric configurations of the habitat patches in the landscapes through which they disperse. In an applied sense, our results indicate potential for ecological mis-alignment between species' evolved suites of dispersal-related traits and altered environmental conditions as a result of rapid global change. In many cases identifying the processes that shape patterns of animal dispersal, and the consequences of abiotic changes for these processes, will require consideration of complex relationships among a range of organism-specific and environmental factors.

A novel approach for estimating densities of secretive species from road-survey and spatial-movement data

Context Accurate estimates of population density are a critical component of effective wildlife conservation and management. However, many snake species are so secretive that their density cannot be determined using traditional methods such as capture–mark–recapture. Thus, the status of most terrestrial snake populations remains completely unknown. Aim We developed a novel simulation-based technique for estimating density of secretive snakes that combined behavioural observations of snake road-crossing behaviour (crossing speed), effort-corrected road-survey data, and simulations of spatial movement patterns derived from radio-telemetry, without relying on mark–recapture. Methods We used radio-telemetry data to parameterise individual-based movement models that estimate the frequency with which individual snakes cross roads and used information on survey vehicle speed and snake crossing speed to determine the probability of detecting a snake, given that it crosses the road transect during a survey. Snake encounter frequencies during systematic road surveys were then interpreted in light of detection probabilities and simulation model results to estimate snake densities and to assess various factors likely to affect abundance estimates. We demonstrated the broad applicability of this approach through a case study of the imperiled southern hognose snake (Heterodon simus) in the North Carolina (USA) Sandhills. Key results We estimated that H. simus occurs at average densities of 0.17 ha–1 in the North Carolina Sandhills and explored the sensitivity of this estimate to assumptions and variation in model parameters. Conclusions Our novel method allowed us to generate the first abundance estimates for H. simus. We found that H. simus exists at low densities relative to congeners and other mid-sized snake species, raising concern that this species may not only have declined in geographic range, but may also occur at low densities or be declining in their strongholds, such as the North Carolina Sandhills. Implications We present a framework for estimating density of species that have traditionally been considered too secretive to study at the population level. This method will greatly enhance our ability to study and manage a wide variety of snake species and could be applied to other secretive wildlife species that are most frequently encountered during road surveys.

Navigational efficiency in a biased and correlated random walk model of individual animal movement

Understanding how an individual animal is able to navigate through its environment is a key question in movement ecology that can give insight into observed movement patterns and the mechanisms behind them. Efficiency of navigation is important for behavioral processes at a range of different spatio-temporal scales, including foraging and migration. Random walk models provide a standard framework for modeling individual animal movement and navigation. Here we consider a vector-weighted biased and correlated random walk (BCRW) model for directed movement (taxis), where external navigation cues are balanced with forward persistence. We derive a mathematical approximation of the expected navigational efficiency for any BCRW of this form and confirm the model predictions using simulations. We demonstrate how the navigational efficiency is related to the weighting given to forward persistence and external navigation cues, and highlight the counter-intuitive result that for low (but realistic) levels of error on forward persistence, a higher navigational efficiency is achieved by giving more weighting to this indirect navigation cue rather than direct navigational cues. We discuss and interpret the relevance of these results for understanding animal movement and navigation strategies.

Costs and benefits of straight versus tortuous migration paths for Prairie Rattlesnakes (Crotalus viridis viridis) in seminatural and human-dominated landscapes

An individual’s migration path shape should affect its fitness, because patchily distributed features (e.g., prey) are encountered more often on straight than tortuous paths. We hypothesized that Prairie Rattlesnakes (Crotalus viridis viridis (Rafinesque, 1818)) with straighter migration paths should have better body condition, because they encounter prey patches more frequently, and higher migration mortality, because they also encounter predators and hazardous human land uses more frequently, than individuals with tortuous paths. If true, then a straighter path should be favoured when the benefit (resource acquisition) outweighs the cost (mortality risk). Humans pose a significant mortality risk for migrants; thus, the cost of straight-line movement should increase relative to the benefit in more human-dominated landscapes, favouring more tortuous movements. We tested these hypotheses using data on the body condition, mortality, and migration movements of 25 female Prairie Rattlesnakes in one human-dominated and one seminatural landscape. As hypothesized, we found better body condition and higher migration mortality for snakes with straighter migration paths, and that snakes followed more tortuous paths in the human-dominated landscape. Although selection for tortuous movements may reduce rates of migration mortality in human-dominated landscapes, this may ultimately contribute to population declines if poorer body condition reduces overwinter survival or reproductive success.

Genetics of dispersal

Dispersal is a process of central importance for the ecological and evolutionary dynamics of populations and communities, because of its diverse consequences for gene flow and demography. It is subject to evolutionary change, which begs the question, what is the genetic basis of this potentially complex trait? To address this question, we (i) review the empirical literature on the genetic basis of dispersal, (ii) explore how theoretical investigations of the evolution of dispersal have represented the genetics of dispersal, and (iii) discuss how the genetic basis of dispersal influences theoretical predictions of the evolution of dispersal and potential consequences.

Dispersal has a detectable genetic basis in many organisms, from bacteria to plants and animals. Generally, there is evidence for significant genetic variation for dispersal or dispersal‐related phenotypes or evidence for the micro‐evolution of dispersal in natural populations. Dispersal is typically the outcome of several interacting traits, and this complexity is reflected in its genetic architecture: while some genes of moderate to large effect can influence certain aspects of dispersal, dispersal traits are typically polygenic. Correlations among dispersal traits as well as between dispersal traits and other traits under selection are common, and the genetic basis of dispersal can be highly environment‐dependent.

By contrast, models have historically considered a highly simplified genetic architecture of dispersal. It is only recently that models have started to consider multiple loci influencing dispersal, as well as non‐additive effects such as dominance and epistasis, showing that the genetic basis of dispersal can influence evolutionary rates and outcomes, especially under non‐equilibrium conditions. For example, the number of loci controlling dispersal can influence projected rates of dispersal evolution during range shifts and corresponding demographic impacts. Incorporating more realism in the genetic architecture of dispersal is thus necessary to enable models to move beyond the purely theoretical towards making more useful predictions of evolutionary and ecological dynamics under current and future environmental conditions. To inform these advances, empirical studies need to answer outstanding questions concerning whether specific genes underlie dispersal variation, the genetic architecture of context‐dependent dispersal phenotypes and behaviours, and correlations among dispersal and other traits.

Individual variation changes dispersal distance and area requirements of a checkerspot butterfly

Individual variation in movement can have important consequences for spatial population dynamics. For instance, individual variation increases leptokurtosis in dispersal distance, such that more individuals move very short and very long distances relative to a homogeneous population. We quantified individual variation in movement of the Baltimore checkerspot butterfly (Euphydryas phaeton) to investigate its importance for two conservation-related metrics: the expected dispersal distance and the critical minimum patch size, or the smallest area within which a population can persist based on loss due to emigration. All movement parameters showed among-individual variation, with the greatest variation in move lengths and time spent resting. Correlations in among-individual movement parameters indicated that some butterflies were generally more mobile than others. We incorporated empirically estimated movement and demographic parameters into two individual-based models (IBMs), one with homogeneity in movement among individuals, and one with heterogeneity in movement. As expected, individual variation in movement increased the leptokurtosis of lifetime movement distance; the maximum difference in distance moved was substantial (-850 m vs. -5800 m) and is likely of significance for conservation. Individual variation also affected the critical minimum patch size, but the difference (-0.7 ha vs. -0.5 ha) is unlikely to be ecologically significant. Notably, populations with individual variation had higher growth rates in small patches and lower growth rates in large patches, a logical consequence of increased leptokurtosis. Individual variation in movement is fairly straightforward to quantify using mixed effects models and is important for spatial population dynamics, thus we encourage its inclusion in studies of other systems.

Mantled howler monkey spatial foraging decisions reflect spatial and temporal knowledge of resource distributions

An animal's ability to find and relocate food items is directly related to its survival and reproductive success. This study evaluates how mantled howler monkeys make spatial foraging decisions in the wild. Specifically, discrete choice models and agent-based simulations are used to test whether mantled howler monkeys on Barro Colorado Island, Panama, integrate spatial information in order to maximize new leaf flush and fruit gain while minimizing distance traveled. Several heuristic models of decision making are also tested as possible alternative strategies (movement to core home range areas instead of individual trees, travel along a sensory gradient, movement along arboreal pathway networks without a predetermined destination, straight-line travel in a randomly chosen direction, and random walks). Results indicate that although leaves are the single most abundant item in the mantled howler monkey diet, long-distance travel bouts target the areas with the highest concentrations of mature fruits. Observed travel patterns yielded larger estimated quantities of fruit in shorter distances traveled than all alternative foraging strategies. Thus, this study both provides novel information regarding how primates select travel paths and suggests that a highly folivorous primate integrates knowledge of spatiotemporal resource distributions in highly efficient foraging strategies.

Mapping areas of spatial-temporal overlap from wildlife tracking data

BACKGROUND

The study of inter-individual interactions (often termed spatial-temporal interactions, or dynamic interactions) from remote tracking data has focused primarily on identifying the presence of such interactions. New datasets and methods offer opportunity to answer more nuanced questions, such as where on the landscape interactions occur. In this paper, we provide a new approach for mapping areas of spatial-temporal overlap in wildlife from remote tracking data. The method, termed the joint potential path area (jPPA) builds from the time-geographic movement model, originally proposed for studying human movement patterns.

RESULTS

The jPPA approach can be used to delineate sub-areas of the home range where inter-individual interaction was possible. Maps of jPPA regions can be integrated with existing geographic data to explore landscape conditions and habitat associated with spatial temporal-interactions in wildlife. We apply the jPPA approach to simulated biased correlated random walks to demonstrate the method under known conditions. The jPPA method is then applied to three dyads, consisting of fine resolution (15 minute sampling interval) GPS tracking data of white-tailed deer (Odocoileus virginianus) collected in Oklahoma, USA. Our results demonstrate the ability of the jPPA to identify and map jPPA sub-areas of the home range. We show how jPPA maps can be used to identify habitat differences (using percent tree canopy cover as a habitat indicator) between areas of spatial-temporal overlap and the overall home range in each of the three deer dyads.

CONCLUSIONS

The value of the jPPA approach within current wildlife habitat analysis workflows is highlighted along with its simple and straightforward implementation and interpretation. Given the current emphasis on remote tracking in wildlife movement and habitat research, new approaches capable of leveraging both the spatial and temporal information content contained within these data are warranted. We make code (in the statistical software R) for implementing the jPPA approach openly available for other researchers.

The straight and narrow path: the evolution of straight-line dispersal at a cane toad invasion front

At the edge of a biological invasion, evolutionary processes (spatial sorting, natural selection) often drive increases in dispersal. Although numerous traits influence an individual's displacement (e.g. speed, stamina), one of the most important is path straightness. A straight (i.e. highly correlated) path strongly enhances overall dispersal rate relative to time and energetic cost. Thus, we predict that, if path straightness has a genetic basis, organisms in the invasion vanguard will exhibit straighter paths than those following behind. Our studies on invasive cane toads (Rhinella marina) in tropical Australia clearly support this prediction. Radio-tracking of field-collected toads at a single site showed that path straightness steadily decreased over the first 10 years post-invasion. Consistent with an evolved (genetic) basis to that behavioural shift, path straightness of toads reared under common garden conditions varied according to the location of their parents' origin. Offspring produced by toads from the invasion vanguard followed straighter paths than did those produced by parents from long-established populations. At the individual level, offspring exhibited similar path straightness to their parents. The dramatic acceleration of the cane toad invasion through tropical Australia has been driven, in part, by the evolution of a behavioural tendency towards dispersing in a straight line.

Spatial scale and movement behaviour traits control the impacts of habitat fragmentation on individual fitness

Habitat fragmentation, that is the breaking apart of habitat, can occur at multiple spatial scales at the same time, as a result of different land uses. Individuals of most species spend different amounts of times moving in different modes, during which they cover different distances and experience different fitness impacts. The scale at which fragmentation occurs interacts with the distance that individuals move in a particular mode to affect an individual's ability to find habitat. However, there is little knowledge of the fitness consequences of different scales of fragmentation for individuals with different traits of movement behaviour. This is critical to understand the mechanisms of persistence of different species in fragmented landscapes. The aim of this study was to quantify the impacts of habitat fragmentation at different scales on the fitness components (reproduction and survival) of individuals with different traits of movement behaviour. We developed a demographic model of individuals that adopt short and tortuous movements within foraging areas (foraging mode) and long and straight movements between foraging areas (searching mode). We considered individuals that adopt different movement modes with varying frequencies, inherently move different searching distances and experience different risks of mortality during searching. We then applied the model within a spatially explicit simulation framework where we varied simultaneously the degree of fragmentation within (fine scale) and between foraging areas (coarse scale). Fine-scale fragmentation had a greater impact on reproduction and survival than coarse-scale fragmentation, for those individuals with a low searching propensity. The impact of fine-scale fragmentation on reproduction and survival interacted with the impact of coarse-scale fragmentation on reproduction and survival, to affect the fitness of individuals with a high searching propensity, large inherent searching distances and high searching mortality rates. Habitat selection strongly mitigated the impact of the scale at which fragmentation occurred on individual fitness. Our findings suggest that the land use to target with conservation actions to reduce fragmentation, such as financial schemes that promote re-vegetation or retention of standing vegetation, depends on the scale at which fragmentation occurs and the movement behaviour traits of the species of conservation concern.

Robustness of optimal random searches in fragmented environments

The random search problem is a challenging and interdisciplinary topic of research in statistical physics. Realistic searches usually take place in nonuniform heterogeneous distributions of targets, e.g., patchy environments and fragmented habitats in ecological systems. Here we present a comprehensive numerical study of search efficiency in arbitrarily fragmented landscapes with unlimited visits to targets that can only be found within patches. We assume a random walker selecting uniformly distributed turning angles and step lengths from an inverse power-law tailed distribution with exponent μ. Our main finding is that for a large class of fragmented environments the optimal strategy corresponds approximately to the same value μ(opt)≈2. Moreover, this exponent is indistinguishable from the well-known exact optimal value μ(opt)=2 for the low-density limit of homogeneously distributed revisitable targets. Surprisingly, the best search strategies do not depend (or depend only weakly) on the specific details of the fragmentation. Finally, we discuss the mechanisms behind this observed robustness and comment on the relevance of our results to both the random search theory in general, as well as specifically to the foraging problem in the biological context.

Equivalence between Step Selection Functions and Biased Correlated Random Walks for Statistical Inference on Animal Movement

Animal movement has a fundamental impact on population and community structure and dynamics. Biased correlated random walks (BCRW) and step selection functions (SSF) are commonly used to study movements. Because no studies have contrasted the parameters and the statistical properties of their estimators for models constructed under these two Lagrangian approaches, it remains unclear whether or not they allow for similar inference. First, we used the Weak Law of Large Numbers to demonstrate that the log-likelihood function for estimating the parameters of BCRW models can be approximated by the log-likelihood of SSFs. Second, we illustrated the link between the two approaches by fitting BCRW with maximum likelihood and with SSF to simulated movement data in virtual environments and to the trajectory of bison (Bison bison L.) trails in natural landscapes. Using simulated and empirical data, we found that the parameters of a BCRW estimated directly from maximum likelihood and by fitting an SSF were remarkably similar. Movement analysis is increasingly used as a tool for understanding the influence of landscape properties on animal distribution. In the rapidly developing field of movement ecology, management and conservation biologists must decide which method they should implement to accurately assess the determinants of animal movement. We showed that BCRW and SSF can provide similar insights into the environmental features influencing animal movements. Both techniques have advantages. BCRW has already been extended to allow for multi-state modeling. Unlike BCRW, however, SSF can be estimated using most statistical packages, it can simultaneously evaluate habitat selection and movement biases, and can easily integrate a large number of movement taxes at multiple scales. SSF thus offers a simple, yet effective, statistical technique to identify movement taxis.

An empiricist's guide to theoretical predictions on the evolution of dispersal

Dispersal, the tendency for organisms to reproduce away from their parents, influences many evolutionary and ecological processes, from speciation and extinction events, to the coexistence of genotypes within species or biological invasions. Understanding how dispersal evolves is crucial to predict how global changes might affect species persistence and geographical distribution. The factors driving the evolution of dispersal have been well characterized from a theoretical standpoint, and predictions have been made about their respective influence on, for example, dispersal polymorphism or the emergence of dispersal syndromes. However, the experimental tests of some theories remain scarce partly because a synthetic view of theoretical advances is still lacking. Here, we review the different ingredients of models of dispersal evolution, from selective pressures and types of predictions, through mathematical and ecological assumptions, to the methods used to obtain predictions. We provide perspectives as to which predictions are easiest to test, how theories could be better exploited to provide testable predictions, what theoretical developments are needed to tackle this topic, and we place the question of the evolution of dispersal within the larger interdisciplinary framework of eco-evolutionary dynamics.

Movement ecology of amphibians: from individual migratory behaviour to spatially structured populations in heterogeneous landscapes,

Both genetic cohesion among local populations of animals and range expansion depend on the frequency of dispersers moving at an interpatch scale. Animal movement has an individual component that reflects behaviour and an ecological component that reflects the spatial organization of populations. The total movement capacity of an individual describes maximum movement distance theoretically achievable during a lifetime, whereas its variation among the members of a local population determines the magnitude of interpatch movements and thus of gene flow between neighbouring patches within metapopulation or patchy population systems. Here, I review information on dispersal and migration as components of the movement capacity of juvenile and adult pond-breeding amphibians and discuss how these components inform the spatial structure of populations. Amphibians disperse as juveniles and adults, but movement distances detected in tracking or capture–mark–recapture studies are usually far below the corresponding estimates based on molecular gene-flow data. This discrepancy reflects the constraints of available tracking methods for free-ranging individuals leading to inappropriate surrogates of annual movement capacity, but can be resolved using probabilistic approaches based on dispersal functions. There is remarkable capacity for and plasticity in movements in amphibians. Annual within-patch movements (migrations) of individuals can be large and likely represent an underestimated capacity for movement at the interpatch scale. Landscape resistance may influence the paths of dispersing amphibians, but rarely impedes interpatch movements. Juveniles emigrating unpredictably far from the natal pond and adults switching from within-patch migrations to dispersal to another patch demonstrate the plasticity of individual movement behaviour. Three basic conclusions can be drawn with respect to the linkage of individual movement behaviour and spatial or genetic structure of local amphibian populations embedded in a heterogeneous landscape: (1) individual movements or consecutive short-term series of movements are misleading surrogate measures of total movement capacity; (2) probabilistic modelling of movement capacity is the best available behavioural predictor of interpatch gene flow; (3) connectivity of local populations in heterogeneous landscapes is less affected by landscape resistance than previously expected.

Between migration load and evolutionary rescue: dispersal, adaptation and the response of spatially structured populations to environmental change

The evolutionary potential of populations is mainly determined by population size and available genetic variance. However, the adaptability of spatially structured populations may also be affected by dispersal: positively by spreading beneficial mutations across sub-populations, but negatively by moving locally adapted alleles between demes. We develop an individual-based, two-patch, allelic model to investigate the balance between these opposing effects on a population's evolutionary response to rapid climate change. Individual fitness is controlled by two polygenic traits coding for local adaptation either to the environment or to climate. Under conditions of selection that favour the evolution of a generalist phenotype (i.e. weak divergent selection between patches) dispersal has an overall positive effect on the persistence of the population. However, when selection favours locally adapted specialists, the beneficial effects of dispersal outweigh the associated increase in maladaptation for a narrow range of parameter space only (intermediate selection strength and low linkage among loci), where the spread of beneficial climate alleles is not strongly hampered by selection against non-specialists. Given that local selection across heterogeneous and fragmented landscapes is common, the complex effect of dispersal that we describe will play an important role in determining the evolutionary dynamics of many species under rapidly changing climate.

Prospecting and dispersal: their eco-evolutionary dynamics and implications for population patterns

Dispersal is not a blind process, and evidence is accumulating that individual dispersal strategies are informed in most, if not all, organisms. The acquisition and use of information are traits that may evolve across space and time as a function of the balance between costs and benefits of informed dispersal. If information is available, individuals can potentially use it in making better decisions, thereby increasing their fitness. However, prospecting for and using information probably entail costs that may constrain the evolution of informed dispersal, potentially with population-level consequences. By using individual-based, spatially explicit simulations, we detected clear coevolutionary dynamics between prospecting and dispersal movement strategies that differed in sign and magnitude depending on their respective costs. More specifically, we found that informed dispersal strategies evolve when the costs of information acquisition during prospecting are low but only if there are mortality costs associated with dispersal movements. That is, selection favours informed dispersal strategies when the acquisition and use processes themselves were not too expensive. When non-informed dispersal strategies evolve, they do so jointly with the evolution of long dispersal distance because this maximizes the sampling area. In some cases, selection produces dispersal rules different from those that would be 'optimal' (i.e. the best possible population performance--in our context quantitatively measured as population density and patch occupancy--among all possible individual movement rules) for the population. That is, on the one hand, informed dispersal strategies led to population performance below its highest possible level. On the other hand, un- and poorly informed individuals nearly optimized population performance, both in terms of density and patch occupancy.

When to be discrete: the importance of time formulation in understanding animal movement

Animal movement is essential to our understanding of population dynamics, animal behavior, and the impacts of global change. Coupled with high-resolution biotelemetry data, exciting new inferences about animal movement have been facilitated by various specifications of contemporary models. These approaches differ, but most share common themes. One key distinction is whether the underlying movement process is conceptualized in discrete or continuous time. This is perhaps the greatest source of confusion among practitioners, both in terms of implementation and biological interpretation. In general, animal movement occurs in continuous time but we observe it at fixed discrete-time intervals. Thus, continuous time is conceptually and theoretically appealing, but in practice it is perhaps more intuitive to interpret movement in discrete intervals. With an emphasis on state-space models, we explore the differences and similarities between continuous and discrete versions of mechanistic movement models, establish some common terminology, and indicate under which circumstances one form might be preferred over another. Counter to the overly simplistic view that discrete- and continuous-time conceptualizations are merely different means to the same end, we present novel mathematical results revealing hitherto unappreciated consequences of model formulation on inferences about animal movement. Notably, the speed and direction of movement are intrinsically linked in current continuous-time random walk formulations, and this can have important implications when interpreting animal behavior. We illustrate these concepts in the context of state-space models with multiple movement behavior states using northern fur seal (Callorhinus ursinus) biotelemetry data.

Evolution of predator dispersal in relation to spatio-temporal prey dynamics: how not to get stuck in the wrong place!

The eco-evolutionary dynamics of dispersal are recognised as key in determining the responses of populations to environmental changes. Here, by developing a novel modelling approach, we show that predators are likely to have evolved to emigrate more often and become more selective over their destination patch when their prey species exhibit spatio-temporally complex dynamics. We additionally demonstrate that the cost of dispersal can vary substantially across space and time. Perhaps as a consequence of current environmental change, many key prey species are currently exhibiting major shifts in their spatio-temporal dynamics. By exploring similar shifts in silico, we predict that predator populations will be most vulnerable when prey dynamics shift from stable to complex. The more sophisticated dispersal rules, and greater variance therein, that evolve under complex dynamics will enable persistence across a broader range of prey dynamics than the rules which evolve under relatively stable prey conditions.

Persistence of aquatic insects across managed landscapes: effects of landscape permeability on re-colonization and population recovery

Human practices in managed landscapes may often adversely affect aquatic biota, such as aquatic insects. Dispersal is often the limiting factor for successful re-colonization and recovery of stressed habitats. Therefore, in this study, we evaluated the effects of landscape permeability, assuming a combination of riparian vegetation (edge permeability) and other vegetation (landscape matrix permeability), and distance between waterbodies on the colonization and recovery potential of weakly flying insects. For this purpose, we developed two models, a movement and a population model of the non-biting midge, Chironomus riparius, an aquatic insect with weak flying abilities. With the movement model we predicted the outcome of dispersal in a landscape with several linear water bodies (ditches) under different assumptions regarding landscape-dependent movement. Output from the movement model constituted the probabilities of encountering another ditch and of staying in the natal ditch or perishing in the landscape matrix, and was used in the second model. With this individual-based model of midge populations, we assessed the implications for population persistence and for recovery potential after an extreme stress event. We showed that a combination of landscape attributes from the movement model determines the fate of dispersing individuals and, once extrapolated to the population level, has a big impact on the persistence and recovery of populations. Population persistence benefited from low edge permeability as it reduced the dispersal mortality which was the main factor determining population persistence and viability. However, population recovery benefited from higher edge permeability, but this was conditional on the low effective distance that ensured fewer losses in the landscape matrix. We discuss these findings with respect to possible landscape management scenarios.

Walk the line-dispersal movements of gray mouse lemurs (Microcebus murinus)

Despite the importance of dispersal for individuals and populations, little is known about the actual dispersal process in most species. We observed 90 subadult gray mouse lemurs—small, arboreal, nocturnal primates—in Kirindy Forest in western Madagascar, to determine the behavioral processes underlying natal dispersal. Twelve radio-collared males dispersed over distances between 180 and 960 m (≈1–7 home range diameters) away from their presumed natal ranges. Dispersal forays were fast and highly directed, and thus distinct from routine movements. Contrary to expectations of current hypotheses on potential differences between different types of dispersal movements, their special movement style did not prevent dispersers from interrupting forays to exploit resources they encountered during their forays. Data from a translocation experiment indicated that highly directed dispersal or search forays reflect a general strategy for large-scale exploration away from familiar sites in this species. A prolonged transfer phase was also observed, with regular commuting between old and new sites for up to 14 days, which probably served to moderate costs of unfamiliarity with a new site. In conclusion, the dispersal process of gray mouse lemurs is characterized by high intra- and interindividual consistency in movement strategies, but variation in the duration of the transfer phase. The observed dispersal movement style represents an effective strategy balancing costs of dispersal with the need to gather an appropriate level of information about potential dispersal target sites.

Mate-finding as an overlooked critical determinant of dispersal variation in sexually-reproducing animals

Dispersal is a critically important process in ecology, but robust predictive models of animal dispersal remain elusive. We identify a potentially ubiquitous component of variation in animal dispersal that has been largely overlooked until now: the influence of mate encounters on settlement probability. We use an individual-based model to simulate dispersal in sexually-reproducing organisms that follow a simple set of movement rules based on conspecific encounters, within an environment lacking spatial habitat heterogeneity. We show that dispersal distances vary dramatically with fluctuations in population density in such a model, even in the absence of variation in dispersive traits between individuals. In a simple random-walk model with promiscuous mating, dispersal distributions become increasingly 'fat-tailed' at low population densities due to the increasing scarcity of mates. Similar variation arises in models incorporating territoriality. In a model with polygynous mating, we show that patterns of sex-biased dispersal can even be reversed across a gradient of population density, despite underlying dispersal mechanisms remaining unchanged. We show that some widespread dispersal patterns found in nature (e.g. fat tailed distributions) can arise as a result of demographic variability in the absence of heterogeneity in dispersive traits across the population. This implies that models in which individual dispersal distances are considered to be fixed traits might be unrealistic, as dispersal distances vary widely under a single dispersal mechanism when settlement is influenced by mate encounters. Mechanistic models offer a promising means of advancing our understanding of dispersal in sexually-reproducing organisms.