Measuring dispersal and detecting departures from a random walk model in a grasshopper hybrid zone

Abstract. 1. The grasshopper species Chorthippus brunneus and C. jacobsi form a complex mosaic hybrid zone in northern Spain. Two mark–release–recapture studies were carried out near the centre of the zone in order to make direct estimates of lifetime dispersal.
2. A model framework based on a simple random walk in homogeneous habitat was extended to include the estimation of philopatry and flying propensity. Each model was compared with the real data, correcting for spatial and temporal biases in the data sets.
3. All four data sets (males and females at each site) deviated significantly from a random walk. Three of the data sets showed strong philopatry and three had a long dispersal tail, indicating a low propensity to move further than predicted by the random walk model.
4. Neighbourhood size estimates were 76 and 227 for the two sites. These estimates may underestimate effective population size, which could be increased by the long tail to the dispersal function. The random walk model overestimates lifetime dispersal and hence the minimum spatial scale of adaptation.
5. Best estimates of lifetime dispersal distance of 7–33 m per generation were considerably lower than a previous indirect estimate of 1344 m per generation. This discrepancy could be influenced by prezygotic isolation, an inherent by-product of mosaic hybrid zone structure.     

Integrodifference equations in patchy landscapes

We analyze integrodifference equations (IDEs) in patchy landscapes. Movement is described by a dispersal kernel that arises from a random walk model with patch dependent diffusion, settling, and mortality rates, and it incorporates individual behavior at an interface between two patch types. Growth follows a simple Beverton–Holt growth or linear decay. We obtain explicit formulae for the critical domain-size problem, and we illustrate how different individual behavior at the boundary between two patch types affects this quantity. We also study persistence conditions on an infinite, periodic, patchy landscape. We observe that if the population can persist on the landscape, the spatial profile of the invasion evolves into a discontinuous traveling periodic wave that moves with constant speed. Assuming linear determinacy, we calculate the dispersion relation and illustrate how movement behavior affects invasion speed. Numerical simulations justify our approach by showing a close correspondence between the spread rate obtained from the dispersion relation and from numerical simulations.     

Density and genetic relatedness increase dispersal distance in a subsocial organism

Although dispersal distance plays a major role in determining whether organisms will reach new habitats, empirical data on the environmental factors that affect dispersal distance are lacking. Population density and kin competition are two factors theorised to increase dispersal distance. Using the two‐spotted spider mite as a model species, we altered these two environmental conditions and measured the mean dispersal distance of individuals, as well as other attributes of the dispersal kernel. We find that both density and relatedness in the release patch increase dispersal distance. Relatedness, but not density, changes the shape of the dispersal kernel towards a more skewed and leptokurtic shape including a longer ‘fat‐tail’. This is the first experimental demonstration that kin competition can shape the whole distribution of dispersal distances in a population, and thus affect the geographical spread of dispersal phenotypes.     

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

Theoretical work exploring dispersal evolution focuses on the emigration rate of individuals and typically assumes that movement occurs either at random to any other patch or to one of the nearest‐neighbour patches. There is a lack of work exploring the process by which individuals move between patches, and how this process evolves. This is of concern because any organism that can exert control over dispersal direction can potentially evolve efficiencies in locating patches, and the process by which individuals find new patches will potentially have major effects on metapopulation dynamics and gene flow. Here, we take an initial step towards filling this knowledge gap. To do this we constructed a continuous space population model, in which individuals each carry heritable trait values that specify the characteristics of the biased correlated random walk they use to disperse from their natal patch. We explore how the evolution of the random walk depends upon the cost of dispersal, the density of patches in the landscape, and the emigration rate. The clearest result is that highly correlated walks always evolved (individuals tended to disperse in relatively straight lines from their natal patch), reflecting the efficiency of straight‐line movement. In our models, more costly dispersal resulted in walks with higher correlation between successive steps. However, the exact walk that evolved also depended upon the density of suitable habitat patches, with low density habitat evolving more biased walks (individuals which orient towards suitable habitat at quite large distances from that habitat). Thus, low density habitat will tend to develop individuals which disperse efficiently between adjacent habitat patches but which only rarely disperse to more distant patches; a result that has clear implications for metapopulation theory. Hence, an understanding of the movement behaviour of dispersing individuals is critical for robust long‐term predictions of population dynamics in fragmented landscapes.     

Density-dependent dispersal in host-parasitoid assemblages

Most spatial population models assume constant rates of dispersal. However, in a given community, dispersal may not only depend on the density of conspecifics, i.e. density‐dependent dispersal, but also on the density of other species, a phenomenon we term ‘community‐dependent dispersal’. We co‐vary the densities of both the beetle host Callosobruchus chinensis and its parasitoid wasp, Anisopteromalus calandrae, in a laboratory study and record the proportions of each species that disperse within a two‐hour period. The parasitoid in these systems exhibits community‐dependent dispersal – dispersing more frequently when parasitoid density is high and larval host density is low. This supported our prediction that individuals should disperse according to competition for available resources. However, in this study the host's dispersal was independent of density. We suggest that this may be due to less intense selection acting on host dispersal strategies than on the parasitoid. We consider some possible consequences of community‐dependent dispersal for a number of spatial population processes. A well‐known host‐parasitoid metapopulation model is expanded so that it includes a greater range of dispersal functions. When the model is parameterised with the parasitoid community‐dependent dispersal function observed in the empirical study, similar population dynamics are obtained as when fixed‐rate dispersal functions are applied. The importance of dispersal functions for invasions of both competitive and host‐parasitoid systems is also considered. The model results demonstrate that understanding how individuals disperse in response to different species’ population densities is important in determining the rate of spread of an invasion. We suggest that more empirical studies are needed to establish what determines dispersal rate and distance in a range of species, combined with theoretical studies investigating the role of the dispersal function in determining spatial population processes.     

Consequences of Dispersal Heterogeneity for Population Spread and Persistence

Dispersal heterogeneity is increasingly being observed in ecological populations and has long been suspected as an explanation for observations of non-Gaussian dispersal. Recent empirical and theoretical studies have begun to confirm this. Using an integro-difference model, we allow an individual’s diffusivity to be drawn from a trait distribution and derive a general relationship between the dispersal kernel’s moments and those of the underlying heterogeneous trait distribution. We show that dispersal heterogeneity causes dispersal kernels to appear leptokurtic, increases the population’s spread rate, and lowers the critical reproductive rate required for persistence in the face of advection. Wavespeed has been shown previously to be determined largely by the form of the dispersal kernel tail. We qualify this by showing that when reproduction is low, the precise shape of the tail is less important than the first few dispersal moments such as variance and kurtosis. If the reproductive rate is large, a dispersal kernel’s asymptotic tail has a greater influence over wavespeed, implying that estimating the prevalence of traits which correlate with long-range dispersal is critical. The presence of multiple dispersal behaviors has previously been characterized in terms of long-range versus short-range dispersal, and it has been found that rare long-range dispersal essentially determines wavespeed. We discuss this finding and place it within a general context of dispersal heterogeneity showing that the dispersal behavior with the highest average dispersal distance does not always determine wavespeed.     

Modelling larval dispersal and behaviour of coral reef fishes

Coral reef fish spend their first few weeks developing in the open ocean, where eggs and larvae appear merciless to tides and currents, before attempting to leave the pelagic zone and settle on a suitable reef. This pelagic dispersal phase is the process that determines population connectivity and allows replenishment of harvested populations across multiple coral reef habitats. Until recently this pelagic larval dispersal phase has been poorly understood and has often been referred to as the ‘black-box’ in the life-history of coral reef fishes. In this perspective article we highlight three areas where mathematical and computational approaches have been used to aid our understanding of this important ecological process. We discuss models that provide insights into the evolution of the pelagic larval phase in coral reef fish, an unresolved question which lends itself well to a modelling approach due to the difficulty in obtaining empirical data on this life history strategy. We describe how studies of fish hearing and physical sound propagation models can be used to predict the detection distance of reefs for settling larval fish, and the potential impact of anthropogenic noise. We explain how random walk models can be used to explore individual- and group-level behaviour in larval fish during the dispersal and settlement stage of their life-history. Finally, we discuss the mutual benefits that mathematical and computational approaches have brought to and gained from the field of larval behaviour and dispersal of reef fishes.     

Estimation of the diffusion rate and crossing probability for biased edge movement between two different types of habitat

One of the fundamental goals of ecology is to examine how dispersal affects the distribution and dynamics of insects across natural landscapes. These landscapes are frequently divided into patches of habitat embedded in a matrix of several non-habitat regions, and dispersal behavior could vary within each landscape element as well as the edges between elements. Reaction–diffusion models are a common way of modeling dispersal and species interactions in such landscapes, but to apply these models we also need methods of estimating the diffusion rate and any edge behavior parameters. In this paper, we present a method of estimating the diffusion rate using the mean occupancy time for a circular region. We also use mean occupancy time to estimate a parameter (the crossing probability) that governs one type of edge behavior often used in these models, a biased random walk. These new methods have some advantages over other methods of estimating these parameters, including reduced computational cost and ease of use in the field. They also provide a method of estimating the diffusion rate for a particular location in space, compared to existing methods that represent averages over large areas. We further examine the statistical properties of the new method through simulation, and discuss how mean occupancy time could be estimated in field experiments.     

Random-walk models of cell dispersal included in mechanobiological simulations of tissue differentiation

Computational models have shown that biophysical stimuli can be correlated with observed patterns of tissue differentiation, and simulations have been performed that predict the time course of tissue differentiation in, for example, long bone fracture healing. Some simulations have used a diffusion model to simulate the migration and proliferation of cells with the differentiating tissue. However, despite the convenience of the diffusion model, diffusion is not the mechanism of cell dispersal: cells disperse by crawling or proliferation, or are transported in a moving fluid. In this paper, a random-walk model (i.e., a stochastic model), with and without a preferred direction, is studied as an approach to simulate cell proliferation/migration in differentiating tissues and it is compared with the diffusion model. A simulation of tissue differentiation of gap tissue in a two-dimensional model of a bone/implant interface was performed to demonstrate the differences between diffusion vs. random walk with a preferred direction. Results of diffusion and random-walk models are similar with respect to the change in the stiffness of the gap tissue but rather different results are obtained regarding tissue patterning in the differentiating tissues; the diffusion approach predicted continuous patterns of tissue differentiation whereas the random-walk model showed a more discontinuous pattern-histological results are not available that can unequivocally establish which is most similar to experimental observation. Comparing isotropic to anisotropic random walk (preferred direction of proliferation and cell migration), a more rapid reduction of the relative displacement between implant and bone is predicted. In conclusion, we have shown how random-walk models of cell dispersal and proliferation can be implemented, and shown where differences between them exist. Further study of the random-walk model is warranted, given the importance of cell seeding and cell dispersal/proliferation in many mechanobiological problems.     

Seed Dispersal by Avian Frugivores: Non‐random Heterogeneity at Fine Scales

Seed dispersal studies have primarily examined dispersal as a function of distance from the parent tree and/or heterogeneity in dispersal due to animal use of nesting, roosting and sleeping sites. However, non‐random heterogeneity in seed dispersal is also likely to result from the post‐foraging behavior and movement of frugivores which prefer certain trees. To characterize variation in seed rain at fine scales, we studied the dispersal curve of Prunus ceylanica, a primarily bird‐dispersed species. We compared seed rain at conspecifics, heterospecific fruiting trees with similar frugivore assemblages, emergent trees, and the landscape surrounding these trees. Seed rain of P. ceylanica was found to peak globally under the canopy of conspecifics but to peak locally under the canopy and immediate neighborhood of heterospecific fruiting trees. Our results demonstrate that seed rain is highly clumped even at fine spatial scales. A large proportion of seeds are dispersed in specific, localized regions. This variation can have important implications for plant population dynamics and might significantly alter the impact of post‐dispersal processes. Seed dispersal models may need to incorporate this heterogeneity to explain manifestations of spatially explicit dynamics like mixed species ‘orchards’.     

Simultaneous estimation of mortality and dispersal rates of an artificially released population

Mark-recapture methods cannot estimate both mortality and dispersal rates of a wild population simultaneously. However, when an artificially cultured population is released into an area, the initial population size and the initial population distribution are usually known. If artificially cultured individuals are released with marks or distinguished from wild individuals or if no wild individual exists in the study area, we can estimate both the mortality and dispersal rates of the artificial population. The numbers of dispersed and dead individuals are estimated from the dispersal rate from the diffusion model and the total decreasing rate estimated from a mark-recapture data. We can estimate both the time-dependent and time-independent dispersal rates from the data. We choose the best fit model that has the smallest value of Akaike's Information Criteria. We also consider ‘concentric circles approximation” of spatial distribution, in which the cumulative and frequency distributions are analytically obtained.     

Dispersal behaviour of individuals in metapopulations of two British butterflies

Dispersal patterns are important in metapopulation ecology because they affect the dynamics and survival of populations. However, because little empirical information exists on dispersal behaviour of individuals, theoretical models usually assume random dispersal. Recent empirical evidence, by contrast, suggests that the butterfly Maniola jurtina uses a non‐random, systematic dispersal strategy, can detect and orient towards habitat from distances of 100–150 m, and prefers a familiar habitat patch over a non‐familiar one (‘homing behaviour’). The present study (1) investigated whether these results generalise to another butterfly species, Pyronia tithonus; and (2) examined the cause of the observed ‘homing behaviour’ in M. jurtina. P. tithonus used a similar non‐random, systematic dispersal strategy to M. jurtina, had a similar perceptual range for habitat detection and preferred a familiar habitat patch over a non‐familiar one. The ‘homing behaviour’ of M. jurtina was found to be context‐dependent: individual M. jurtina translocated within habitat did not return towards their capture point, whereas individuals translocated similar distances out of habitat did return to their ‘home’ patch. We conclude that butterfly ‘homing behaviour’ is not based on an inherent preference for a familiar location, but that familiarity with an area facilitates the recognition of suitable habitat, towards which individuals orient if they find themselves in unsuitable habitat. Contrary to conventional wisdom, we suggest that frequent, short ‘excursions’ over habitat patch boundaries are evolutionarily advantageous to individuals, because increased familiarity with the surrounding environment is likely to increase the ability of a straying animal to return to its natural habitat, and to reduce the rate of mortality experienced by individuals attempting to disperse between habitat patches. We discuss the implications of the non‐random dispersal for existing metapopulation models, including models of the evolution of dispersal rates.     

Flexible dispersal strategies in native and non‐native ranges: environmental quality and the ‘good–stay,bad–disperse’ rule

Dispersal strategies are one of the most important determinants of range dynamics and a surrogate for invasiveness. We tested three inter‐related hypotheses derived from demographic and ecological models: (H₁) short‐distance dispersal strategies arise at native range margins due to their demographic advantage; (H₂) in non‐native areas a high diffusion rate is favoured at the advancing range front for niche filling; (H₃) environmental deterioration can increase dispersal and lead to a ‘good–stay, bad–disperse’ strategy. Spatially and temporally explicit rates of spread and dispersal kernels of the European starling Sturnus vulgaris were generated for its native range (Britain) using ringing records from 1909 to 2008, and for a non‐native area (South Africa) using ringing data and distributional records since its introduction in 1897. There was a marked spatial and temporal variation in the rate of spread within both native and non‐native ranges. In the native range the rate of spread declined with increasing distance from the species’ European distribution (contradicting H₁). In the non‐native range the rate of spread increased with distance from the introduction locality (supporting H₂). The annual rate of spread in the native range also increased significantly when environmental conditions were deteriorating as indicated by marked population declines and relatively low abundance (H₃), providing clear evidence for flexible dispersal strategies based on a ‘good–stay, bad–disperse’ rule. Starlings’ dispersal kernel followed an inverse power law and showed strong anisotropy and significant divergence between native and invasive populations, suggesting a flexible strategy comprising a dynamic response to spatial and temporal environmental variation with implications for predicting dispersal and range dynamics arising from environmental change.     

Flow- and substratum-mediated movement by a stream insect

1. In streams subject to frequent hydrologic disturbance, the ability of benthic invertebrates to disperse within the channel is key to understanding the mechanisms of flow refugium use and population persistence. This study focuses on crawling invertebrates, the effects on movement of abiotic factors (specifically, flow near the stream bed and bed micro‐topography) and the consequences for dispersal. 2. In a large flume, we observed individual cased caddisflies, Potamophylax latipennis, moving in fully turbulent flows over a precise replica of a water‐worked surface. From maps of movement paths, we quantified crawling behaviour and entrainment, and the influence of bed micro‐topography. We manipulated discharge and tested its effect on movement, linear displacement and areal dispersal. The highest discharge treatment was a disturbance to the caddis; the lowest discharge was not. Crawling behaviours were used to parameterise random walk models and estimate population dispersal, and to test the effects of abiotic factors on movement. 3. Bed micro‐topography influenced crawling in several ways. Caddis spent most of their time at the junctions between proud particles and the adjacent plane bed. The frequency distribution of turn angles was bimodal, with modal values approximating the angle required to travel around median‐sized particles. Larvae generally crawled downstream, but crawling direction relative to the flow was skewed by bed micro‐topography and was not directly downstream, unlike drift. 4. Caddis crawled for most of the time and discharge affected almost every aspect of their movement. As discharge increased, caddis crawled less often, more slowly and over shorter distances; they also became entrained more frequently and over greater distances. With increased discharge, caddis spent proportionately less time at the junctions between proud particles and the adjacent plane bed, and more time on the tops and sides of proud clasts. This is curious as most entrainment occurred from the tops and sides of clasts and entrainment is generally considered to be disadvantageous during disturbances. 5. Linear displacement (drift and entrainment combined) was downstream, but the relation between total displacement and discharge was complex. Total displacement decreased at intermediate discharge as crawling decreased, but increased at high discharge as entrainment and drift played a greater role in movement. 6. Within‐stream dispersal via crawling contained elements of both a correlated random walk (we observed directional persistence in turn angles) and a biased random walk (we observed downstream bias in move direction angles) and was best described as a biased correlated random walk. Dispersal was inversely related to discharge, suggesting that the ability of P. latipennis to crawl into flow refugia on the streambed is reduced at high flow.     

Propagule dispersal and the scales of marine community process

Benthic marine organisms are characterized by a bipartite life history in which populations of sedentary adults are connected by oceanic transport of planktonic propagules. In contrast with the terrestrial case, where ‘long distance dispersal’ (LDD) has traditionally been viewed as a process involving rare events, this creates the possibility for large numbers of offspring to travel far relative to the spatial scale of adult populations. As a result, the concept of LDD must be examined carefully when applied in a marine context. Any measure of LDD requires reference to an explicit ‘local’ scale, often defined in terms of adult population demography, habitat patchiness, or the average dispersal distance. Terms such as ‘open’ and ‘closed’ are relative, and should be used with caution, especially when compared across different taxa and systems. We use recently synthesized data on marine propagule dispersal potential and the spread of marine invasive species to draw inferences about average and maximum effective dispersal distances for marine taxa. Foremost, our results indicate that dispersal occurs at a wide range of scales in marine communities. The nonrandom distribution of these scales among community members has implications for marine community dynamics, and for the implementation of marine conservation efforts. Second, in agreement with theoretical results, our data illustrate that average and extreme dispersal scales do not necessarily covary. This further confounds simple classifications of ‘short’ and ‘long’ dispersers, because different ecological processes (e.g. range expansion vs. population replenishment) depend on different aspects of the dispersal pattern (e.g. extremes vs. average). Our findings argue for a more rigorous quantitative view of scale in the study of marine dispersal processes, where relative terms such as ‘short’ and ‘long’, ‘open’ and ‘closed’, ‘retained’ and ‘exported’ are defined only in conjunction with explicit definitions of the scale and process of interest. This shift in perspective represents an important step towards unifying theoretical and empirical studies of dispersal processes in marine and terrestrial systems.     

From random walks to informed movement

The analysis of animal movement is a large and continuously growing field of research. Detailed knowledge about movement strategies is of crucial importance for understanding eco‐evolutionary dynamics at all scales – from individuals to (meta‐)populations. This and the availability of detailed movement and dispersal data motivated Nathan and colleagues to published their much appreciated call to base movement ecology on a more thorough mechanistic basis. So far, most movement models are based on random walks. However, even if a random walk might describe real movement patterns acceptably well, there is no reason to assume that animals move randomly. Therefore, mechanistic models of foraging strategies should be based on information use and memory in order to increase our understanding of the processes that lead to animal movement decisions. We present a mechanistic movement model of an animal with a limited perceptual range and basic information storage capacities. This ‘spatially informed forager’ constructs an internal map of its environment by using perception, memory and learned or evolutionarily acquired assumptions about landscape attributes. We analyse resulting movement patterns and search efficiencies and compare them to area restricted search strategies (ARS) and biased correlated random walks (BCRW) of omniscient individuals. We show that, in spite of their limited perceptual range, spatially informed individuals boost their foraging success and may perform much better than the best ARS. The construction of an internal map and the use of spatial information results in the emergence of a highly correlated walk between patches and a rather systematic search within resource clusters. Furthermore, the resulting movement patterns may include foray search behaviour. Our work highlights the strength of mechanistic modelling approaches and sets the stage for the development of more sophisticated models of memory use for movement decisions and dispersal.     

On evolutionary stability of carrying capacity driven dispersal in competition with regularly diffusing populations

Two competing populations in spatially heterogeneous but temporarily constant environment are investigated: one is subject to regular movements to lower density areas (random diffusion) while the dispersal of the other is in the direction of the highest per capita available resources (carrying capacity driven diffusion). The growth of both species is subject to the same general growth law which involves Gilpin–Ayala, Gompertz and some other equations as particular cases. The growth rate, carrying capacity and dispersal rate are the same for both population types, the only difference is the dispersal strategy. The main result of the paper is that the two species cannot coexist (unless the environment is spatially homogeneous), and the carrying capacity driven diffusion strategy is evolutionarily stable in the sense that the species adopting this strategy cannot be invaded by randomly diffusing population. Moreover, once the invasive species inhabits some open nonempty domain, it would spread over any available area bringing the native species diffusing randomly to extinction. One of the important technical results used in the proofs can be interpreted in the form that the limit solution of the equation with a regular diffusion leads to lower total population fitness than the ideal free distribution.     

Towards a mechanistic understanding of dispersal evolution in plants: conservation implications

Aim A species’ dispersal characteristics will play a key role in determining its likely fate during a period of environmental change. However, these characteristics are not constant within a species – instead, there is often both considerable interpopulation and interindividual variability. Also changes in selection pressures can result in the evolution of dispersal characteristics, with knock‐on consequences for a species’ population dynamics. Our aim here is to make our theoretical understanding of dispersal evolution more conservation‐relevant by moving beyond the rather abstract, phenomenological models that have dominated the literature towards a more mechanism‐based approach. Methods We introduce a continuous‐space, individual‐based model for wind‐dispersed plants where release height is determined by an individual’s ‘genotype’. A mechanistic wind dispersal model is used to simulate seed dispersal. Selection acts on variation in release height that is generated through mutation. Results We confirm that, when habitat is fragmented, both evolutionary rescue and evolutionary suicide remain possible outcomes when a mechanistic dispersal model is used. We also demonstrate the potential for what we term evolutionary entrapment. A population that under some conditions can evolve to be sufficiently dispersive that it expands rapidly across a fragmented landscape can, under different conditions, become trapped by a combination of limited dispersal and a large gap between patches. Conclusions While developing evolutionary models to be used as conservation tools is undoubtedly a challenge, we believe that, with a concerted collaborative effort linking the knowledge and methods of ecologists, evolutionary biologists and geneticists, it is an achievable aim.     

Sex, isolation and fidelity: unbiased long-distance dispersal in a terrestrial amphibian

Amphibians in general are considered poor dispersers and thus their dispersal curve should be dominated by short movements. Additionally, as male toads do not compete for females and sexual selection is by female choice, dispersal should be male-biased. Furthermore, since adults are site-loyal and polygynous, juveniles should move farther and faster than adults. We tested the hypotheses that dispersal would be limited and both sex- and age-biased in a population of Fowler's toads Bufo fowleri at Lake Erie, Ontario, Canada. Based on a mark-recapture study of 2816 toads, 1326 recaptured at least once, we found that although the toads did show high site fidelity, the dispersal curve was highly skewed with a significant "tail" where the maximum distance moved by an adult was 34 km. Dispersal was neither sex-biased nor age-biased despite clear theoretical predictions that dispersal should be biased towards males and juveniles. We conclude that the resource competition hypothesis of sex-biased dispersal does not predict dispersal tendencies as readily for amphibians as for mammals and birds. Toad dispersal only appears to be juvenile-biased because the juveniles are more abundant than the adults, not because they are the more active dispersers.     

Are dispersal and inbreeding avoidance related?

Sex differences in dispersal and inter-group transfer by birds and mammals are often considered to be evolved responses to the phenomenon of inbreeding depression. This belief is derived from ‘natural selection logic’, which holds that (1) because inbreeding depression is demonstrably costly, selection must have acted to minimize its occurrence, and (2) as sex differences in dispersal often appear to be the only thing preventing inbreeding, these sex differences must be the expected adaptations for avoiding inbreeding depression. However, although the sex differences in median dispersal distance observed among many small mammals and birds may reduce average levels of inbreeding within a population, they nevertheless leave the majority of individuals ‘at risk’ for inbreeding; such differences can be responses to inbreeding depression only in a group selection model. Furthermore, natal dispersal by both sexes occurs in many group-living species. In these species, emigration by individuals of one sex cannot easily be attributed to avoiding inbreeding because opposite-sex relatives also emigrate. Though most authors acknowledge that sexual dispersal patterns may be epiphenomenal consequences of other factors (e.g. intrasexual aggression), this point is rarely considered further. In this paper we critically review several frequently cited examples of differential dispersal, and conclude that ‘other factors’, such as intrasexual competition and territory choice, explain these observations more completely and consistently than does the inbreeding avoidance hypothesis. Observed dispersal patterns simply reflect sex differences in the balance between the advantages of philopatry and the costs of intrasexual competition.