Landscape bioacoustics allow detection of the effects of habitat patchiness on population structure

Landscape structure may affect individual dispersal abilities, thus influencing the genotypic and phenotypic composition of populations. We analyzed the interplay among landscape, behavior, and evolutionary processes by correlating habitat patchiness to the variability in vocalizations of Dupont's Lark Chersophilus duponti, one of the most habitat-selective and rare European songbirds. We tape-recorded males throughout the species distribution in Spain, analyzed the spatial patterns of territorial call variation at different scales (individuals, populations, and broad geographic areas), and related acoustic variability to patterns of isolation by geographic distance and by landscape unsuitability (calculated by building a predictive model of habitat suitability). The differentiation of spectro-temporal call features resulted from both isolation by distance and isolation by landscape unsuitability mechanisms. Landscape connectivity was often a better determinant of call differentiation than simple straight-line distance between individuals, providing the first evidence that call transmission can be limited by the presence and distribution of patches of adequate habitat, which likely mediates bird dispersal. Landscape patchiness resulted in a reduction of acoustic diversity (repertoire size) within populations, and a parallel increase in differentiation among populations. Landscape bioacoustics can represent a promising tool for estimating population structure, although the study of animal communication cannot be viewed as an alternative, but a source of complementary information to genetics, given that it provides evidence of male-male transmission and social and cultural phenomena that are currently undetectable from molecular data.     

Old models explain new observations of butterfly movement at patch edges

Understanding movement in heterogeneous environments is central to predicting how landscape changes affect animal populations. Several recent studies point out an intriguing and distinctive looping behavior by butterflies at habitat patch edges and hypothesize that this behavior requires a new framework for analyzing animal movement. We show that this looping behavior could be caused by a longstanding movement model, biased correlated random walk, with bias toward habitat patches. The ability of this longstanding model to explain recent observations reinforces the point that butterflies respond to habitat heterogeneity and do not move randomly through heterogeneous environments. We discuss the implications of different movement models for predicting butterfly responses to landscape change, and our rationale for retaining longstanding movement models, rather than developing new modeling frameworks for looping behavior at patch edges.     

Incorporating the perceptual range of animals into connectivity models

The perceptual range of an animal towards different landscape elements affects its movements through heterogeneous landscapes. However, empirical knowledge and modeling tools are lacking to assess the consequences of variation in the perceptual range for movement patterns and connectivity. In this study we tested how changes in the assumed perception of different landscape elements affect the outcomes of a connectivity model. We used an existing individual-based, spatially explicit model for the dispersal of Eurasian lynx (Lynx lynx). We systematically altered the perceptual range in which animals recognize forest fragments, water bodies or cities, as well as the probability that they respond to these landscape elements. Overall, increasing the perceptual range of the animals enhanced connectivity substantially, both qualitatively and quantitatively. An enhanced range of attraction to forests had the strongest impact, doubling immigration success; an enhanced range of attraction to rivers had a slightly lower impact; and an enhanced range of avoidance of cities had the lowest impact. Correcting the enhancement in connectivity by the abundance of each of the landscape elements in question reversed the results, indicating the potential sensitivity of connectivity models to rare landscape elements (in our case barriers such as cities). Qualitatively, the enhanced perception resulted in strong changes in movement patterns and connectivity. Furthermore, model results were highly parameter-specific and patch-specific. These results emphasize the need for further empirical research on the perceptual capabilities of different animals in different landscapes and conditions. They further indicate the usefulness of spatially explicit individual-based simulation models for recognizing consistent patterns that emerge, despite uncertainty regarding animals’ movement behavior. Altogether, this study demonstrates the need to extend the concept of ‘perceptual ranges’ beyond patch detection processes, to encompass the wide range of elements that can direct animal movements during dispersal through heterogeneous landscapes.     

Circuit-theory applications to connectivity science and conservation

Conservation practitioners have long recognized ecological connectivity as a global priority for preserving biodiversity and ecosystem function. In the early years of conservation science, ecologists extended principles of island biogeography to assess connectivity based on source patch proximity and other metrics derived from binary maps of habitat. From 2006 to 2008, the late Brad McRae introduced circuit theory as an alternative approach to model gene flow and the dispersal or movement routes of organisms. He posited concepts and metrics from electrical circuit theory as a robust way to quantify movement across multiple possible paths in a landscape, not just a single least-cost path or corridor. Circuit theory offers many theoretical, conceptual, and practical linkages to conservation science. We reviewed 459 recent studies citing circuit theory or the open-source software Circuitscape. We focused on applications of circuit theory to the science and practice of connectivity conservation, including topics in landscape and population genetics, movement and dispersal paths of organisms, anthropogenic barriers to connectivity, fire behavior, water flow, and ecosystem services. Circuit theory is likely to have an effect on conservation science and practitioners through improved insights into landscape dynamics, animal movement, and habitat-use studies and through the development of new software tools for data analysis and visualization. The influence of circuit theory on conservation comes from the theoretical basis and elegance of the approach and the powerful collaborations and active user community that have emerged. Circuit theory provides a springboard for ecological understanding and will remain an important conservation tool for researchers and practitioners around the globe.     

Inferring ecological and behavioral drivers of African elephant movement using a linear filtering approach

Understanding the environmental factors influencing animal movements is fundamental to theoretical and applied research in the field of movement ecology. Studies relating fine-scale movement paths to spatiotemporally structured landscape data, such as vegetation productivity or human activity, are particularly lacking despite the obvious importance of such information to understanding drivers of animal movement. In part, this may be because few approaches provide the sophistication to characterize the complexity of movement behavior and relate it to diverse, varying environmental stimuli. We overcame this hurdle by applying, for the first time to an ecological question, a finite impulse-response signal-filtering approach to identify human and natural environmental drivers of movements of 13 free-ranging African elephants (Loxodonta africana) from distinct social groups collected over seven years. A minimum mean-square error (MMSE) estimation criterion allowed comparison of the predictive power of landscape and ecological model inputs. We showed that a filter combining vegetation dynamics, human and physical landscape features, and previous movement outperformed simpler filter structures, indicating the importance of both dynamic and static landscape features, as well as habit, on movement decisions taken by elephants. Elephant responses to vegetation productivity indices were not uniform in time or space, indicating that elephant foraging strategies are more complex than simply gravitation toward areas of high productivity. Predictions were most frequently inaccurate outside protected area boundaries near human settlements, suggesting that human activity disrupts typical elephant movement behavior. Successful management strategies at the human-elephant interface, therefore, are likely to be context specific and dynamic. Signal processing provides a promising approach for elucidating environmental factors that drive animal movements over large time and spatial scales.     

Use of Empirically Derived Source-Destination Models to Map Regional Conservation Corridors

Abstract:  The ability of populations to be connected across large landscapes via dispersal is critical to long-term viability for many species. One means to mitigate population isolation is the protection of movement corridors among habitat patches. Nevertheless, the utility of small, narrow, linear features as habitat corridors has been hotly debated. Here, we argue that analysis of movement across continuously resistant landscapes allows a shift to a broader consideration of how landscape patterns influence connectivity at scales relevant to conservation. We further argue that this change in scale and definition of the connectivity problem improves one's ability to find solutions and may help resolve long-standing disputes regarding scale and definition of movement corridors and their importance to population connectivity. We used a new method that combines empirically derived landscape-resistance maps and least-cost path analysis between multiple source and destination locations to assess habitat isolation and identify corridors and barriers to organism movement. Specifically, we used a genetically based landscape resistance model for American black bears ( Ursus americanus ) to identify major movement corridors and barriers to population connectivity between Yellowstone National Park and the Canadian border. Even though western Montana and northern Idaho contain abundant public lands and the largest wilderness areas in the contiguous United States, moving from the Canadian border to Yellowstone Park along those paths indicated by modeled gene flow required bears to cross at least 6 potential barriers. Our methods are generic and can be applied to virtually any species for which reliable maps of landscape resistance can be developed.     

Disentangling the drivers of reduced long-distance seed dispersal by birds in an experimentally fragmented landscape

Seed dispersal is a crucial component of plant population dynamics. Human landscape modifications, such as habitat destruction and fragmentation, can alter the abundance of fruiting plants and animal dispersers, foraging rates, vector movement, and the composition of the disperser community, all of which can singly or in concert affect seed dispersal. Here, we quantify and tease apart the effects of landscape configuration, namely, fragmentation of primary forest and the composition of the surrounding forest matrix, on individual components of seed dispersal of Heliconia acuminata, an Amazonian understory herb. First we identified the effects of landscape configuration on the abundance of fruiting plants and six bird disperser species. Although highly variable in space and time, densities of fruiting plants were similar in continuous forest and fragments. However, the two largest-bodied avian dispersers were less common or absent in small fragments. Second, we determined whether fragmentation affected foraging rates. Fruit removal rates were similar and very high across the landscape, suggesting that Heliconia fruits are a key resource for small frugivores in this landscape. Third, we used radiotelemetry and statistical models to quantify how landscape configuration influences vector movement patterns. Bird dispersers flew farther and faster, and perched longer in primary relative to secondary forests. One species also altered its movement direction in response to habitat boundaries between primary and secondary forests. Finally, we parameterized a simulation model linking data on fruit density and disperser abundance and behavior with empirical estimates of seed retention times to generate seed dispersal patterns in two hypothetical landscapes. Despite clear changes in bird movement in response to landscape configuration, our simulations demonstrate that these differences had negligible effects on dispersal distances. However, small fragments had reduced densities of Turdus albicollis, the largest-bodied disperser and the only one to both regurgitate and defecate seeds. This change in Turdus abundance acted together with lower numbers of fruiting plants in small fragments to decrease the probability of long-distance dispersal events from small patches. These findings emphasize the importance of foraging style for seed dispersal and highlight the primacy of habitat size relative to spatial configuration in preserving biotic interactions.     

Changes in seed dispersal processes and the potential for between-patch connectivity for an arid land daisy

Dispersal is a major and critical process in population biology that has been particularly challenging to study. Animals can have major roles in seed dispersal even in species that do not appear specifically adapted to animal-aided dispersal. This can occur by two processes: direct movement of diaspores by animals and modification of landscape characteristics by animals in ways that greatly influence dispersal. We exploited the production of large, persistent dispersal structures (seed heads, henceforth) by Erodiophyllum elderi (Asteraceae), a daisy from arid Australia, to further understand secondary dispersal. Seed head dispersal on and off animal tracks in eight E. elderi patches was monitored for 9.5 months by periodically recording the location of marked seed heads. Sites were located inside a reserve that excludes sheep but not kangaroos, and in a nearby area with both kangaroos and sheep. The distance moved and likelihood of seed head movement was higher in areas with sheep, and especially along animal tracks. There was clear evidence that seed heads were channeled down animal tracks during large rainfall events. Seed head dispersal away from patches occurred to a limited extent via their physical contact with sheep and potentially via wind dispersal. Thus, the advantages of this study system allowed us to demonstrate the two postulated effects of herbivores on dispersal via direct movement of seed heads, and two distinct indirect effects through landscape modification by herbivores from the creation of animal tracks and the denudation of vegetation.     

An Experimental Test of Matrix Permeability and Corridor Use by an Endemic Understory Bird

Abstract:  Because of widespread habitat fragmentation, maintenance of landscape connectivity has become a major focus of conservation planning, but empirical tests of animal movement in fragmented landscapes remain scarce. We conducted a translocation experiment to test the relative permeability of three landscape elements (open habitat, shrubby secondary vegetation, and wooded corridors) to movement by the Chucao Tapaculo ( Scelorchilus rubecula ), a forest understory bird endemic to South American temperate rainforest. Forty-one radio-tagged subjects were translocated (individually) to three landscape treatments consisting of small release patches that were either entirely surrounded by open habitat (pasture), entirely surrounded by dense shrubs, or linked to other patches by wooded corridors that were otherwise surrounded by open matrix. The number of days subjects remained in release patches before dispersal (a measure of habitat resistance) was significantly longer for patches surrounded by open habitat than for patches adjoining corridors or surrounded by dense shrubs. These results indicate that open habitat significantly constrains Chucao dispersal, in accord with expectation, but dispersal occurs equally well through wooded corridors and shrub-dominated matrix. Thus, corridor protection or restoration and management of vegetation in the matrix (to encourage animal movement) may be equally feasible alternatives for maintaining connectivity.     

Consequences of ignoring dispersal variation in network models for landscape connectivity

Habitat loss and fragmentation can negatively influence population persistence and biodiversity, but the effects can be mitigated if species successfully disperse between isolated habitat patches. Network models are the primary tool for quantifying landscape connectivity, yet in practice, an overly simplistic view of species dispersal is applied. These models often ignore individual variation in dispersal ability under the assumption that all individuals move the same fixed distance with equal probability. We developed a modeling approach to address this problem. We incorporated dispersal kernels into network models to determine how individual variation in dispersal alters understanding of landscape-level connectivity and implemented our approach on a fragmented grassland landscape in Minnesota. Ignoring dispersal variation consistently overestimated a population's robustness to local extinctions and underestimated its robustness to local habitat loss. Furthermore, a simplified view of dispersal underestimated the amount of habitat substructure for small populations but overestimated habitat substructure for large populations. Our results demonstrate that considering biologically realistic dispersal alters understanding of landscape connectivity in ecological theory and conservation practice.     

How complex do models need to be to predict dispersal of threatened species through matrix habitats?

Persistence of species in fragmented landscapes depends on dispersal among suitable breeding sites, and dispersal is often influenced by the "matrix" habitats that lie between breeding sites. However, measuring effects of different matrix habitats on movement and incorporating those differences into spatially explicit models to predict dispersal is costly in terms of time and financial resources. Hence a key question for conservation managers is: Do more costly, complex movement models yield more accurate dispersal predictions? We compared the abilities of a range of movement models, from simple to complex, to predict the dispersal of an endangered butterfly, the Saint Francis' satyr (Neonympha mitchellii francisci). The value of more complex models differed depending on how value was assessed. Although the most complex model, based on detailed movement behaviors, best predicted observed dispersal rates, it was only slightly better than the simplest model, which was based solely on distance between sites. Consequently, a parsimony approach using information criteria favors the simplest model we examined. However, when we applied the models to a larger landscape that included proposed habitat restoration sites, in which the composition of the matrix was different than the matrix surrounding extant breeding sites, the simplest model failed to identify a potentially important dispersal barrier, open habitat that butterflies rarely enter, which may completely isolate some of the proposed restoration sites from other breeding sites. Finally, we found that, although the gain in predicting dispersal with increasing model complexity was small, so was the increase in financial cost. Furthermore, a greater fit continued to accrue with greater financial cost, and more complex models made substantially different predictions than simple models when applied to a novel landscape in which butterflies are to be reintroduced to bolster their populations. This suggests that more complex models might be justifiable on financial grounds. Our results caution against a pure parsimony approach to deciding how complex movement models need to be to accurately predict dispersal through the matrix, especially if the models are to be applied to novel or modified landscapes.     

Modelling dispersal with diffusion and habitat selection: Analytical results for highly fragmented landscapes

Quantifying dispersal is crucial both for understanding ecological population dynamics, and for gaining insight into factors that affect the genetic structure of populations. The role of dispersal becomes pronounced in highly fragmented landscapes inhabited by spatially structured populations. We consider a landscape consisting of a set of habitat patches surrounded by unsuitable matrix, and model dispersal by assuming that the individuals follow a random walk with parameters that may be specific to the habitat type. We allow for spatial variation in patch quality, and account for edge-mediated behavior, the latter meaning that the individuals bias their movement towards the patches when close to an edge between a patch and the matrix. We employ a diffusion approximation of the random walk model to derive analytical expressions for various characteristics of the dispersal process. For example, we derive formulae for the time that an individual is expected to spend in its current patch i, and for the time that it will spend in the matrix, both conditional on the individual hitting next a given patch j before hitting any of the other patches or dying. The analytical formulae are based on the assumptions that the landscape is infinitely large, that the patches are circularly shaped, and that the patches are small compared to interpatch distances. We evaluate the effect of these assumptions by comparing the analytical results to numerical results in a real patch network that violates all of the three assumptions. We then consider a landscape that fulfills the assumptions, and show that in this case the analytical results are in a very good agreement with the numerical results. The results obtained here allow the construction of computationally efficient dispersal models that can be used as components of metapopulation models.     

Potential Effects of the United States-Mexico Border Fence on Wildlife

Abstract:  Security infrastructure along international boundaries threatens to degrade connectivity for wildlife. To explore potential effects of a fence under construction along the U.S.–Mexico border on wildlife, we assessed movement behavior of two species with different life histories whose regional persistence may depend on transboundary movements. We used radiotelemetry to assess how vegetation and landscape structure affect flight and natal dispersal behaviors of Ferruginous Pygmy-Owls ( Glaucidium brasilianum ), and satellite telemetry, gene-flow estimates, and least-cost path models to assess movement behavior and interpopulation connectivity of desert bighorn sheep ( Ovis canadensis mexicana ). Flight height of Pygmy-Owls averaged only 1.4 m (SE 0.1) above ground, and only 23% of flights exceeded 4 m. Juvenile Pygmy-Owls dispersed at slower speeds, changed direction more, and had lower colonization success in landscapes with larger vegetation openings or higher levels of disturbance ( p ≤ 0.047), which suggests large vegetation gaps coupled with tall fences may limit transboundary movements. Female bighorn sheep crossed valleys up to 4.9 km wide, and microsatellite analyses indicated relatively high levels of gene flow and migration (95% CI for F_ST= 0.010–0.115, Nm = 1.9–24.8, M = 10.4–15.4) between populations divided by an 11-km valley. Models of gene flow based on regional topography and movement barriers suggested that nine populations of bighorn sheep in northwestern Sonora are linked by dispersal with those in neighboring Arizona. Disruption of transboundary movement corridors by impermeable fencing would isolate some populations on the Arizona side. Connectivity for other species with similar movement abilities and spatial distributions may be affected by border development, yet mitigation strategies could address needs of wildlife and humans.     

Incorporating animal behavior into seed dispersal models: implications for seed shadows

Seed dispersal fundamentally influences plant population and community dynamics but is difficult to quantify directly. Consequently, models are frequently used to describe the seed shadow (the seed deposition pattern of a plant population). For vertebrate-dispersed plants, animal behavior is known to influence seed shadows but is poorly integrated in seed dispersal models. Here, we illustrate a modeling approach that incorporates animal behavior and develop a stochastic, spatially explicit simulation model that predicts the seed shadow for a primate-dispersed tree species (Virola calophylla, Myristicaceae) at the forest stand scale. The model was parameterized from field-collected data on fruit production and seed dispersal, behaviors and movement patterns of the key disperser, the spider monkey (Ateles paniscus), densities of dispersed and non-dispersed seeds, and direct estimates of seed dispersal distances. Our model demonstrated that the spatial scale of dispersal for this V. calophylla population was large, as spider monkeys routinely dispersed seeds >100 m, a commonly used threshold for long-distance dispersal. The simulated seed shadow was heterogeneous, with high spatial variance in seed density resulting largely from behaviors and movement patterns of spider monkeys that aggregated seeds (dispersal at their sleeping sites) and that scattered seeds (dispersal during diurnal foraging and resting). The single-distribution dispersal kernels frequently used to model dispersal substantially underestimated this variance and poorly fit the simulated seed-dispersal curve, primarily because of its multimodality, and a mixture distribution always fit the simulated dispersal curve better. Both seed shadow heterogeneity and dispersal curve multimodality arose directly from these different dispersal processes generated by spider monkeys. Compared to models that did not account for disperser behavior, our modeling approach improved prediction of the seed shadow of this V. calophylla population. An important function of seed dispersal models is to use the seed shadows they predict to estimate components of plant demography, particularly seedling population dynamics and distributions. Our model demonstrated that improved seed shadow prediction for animal-dispersed plants can be accomplished by incorporating spatially explicit information on disperser behavior and movements, using scales large enough to capture routine long-distance dispersal, and using dispersal kernels, such as mixture distributions, that account for spatially aggregated dispersal.     

Modeling high-frequency position data of large herbivores with a phase-state model

Understanding the rules and factors that drive the foraging behavior of large herbivores is important to describe their interaction with the landscape at various spatial scales. Some unresolved questions refer to landscape-behavioral interactions that result in oriented or random search in seasonally changing landscapes. Remotely sensed position data indicate that herbivores select local patches of heterogeneous landscapes depending on a complex host of dynamically varying animal and environmental conditions. Since foraging paths consist in successions of relatively short steps, increasing the frequency at which position information is acquired would contribute to entangle the mechanisms resulting in herbivores’ foraging paths. We addressed the question whether herbivores would obtain information at a patch scale that would modify their distribution at a landscape scale based on directed movement or navigation ability. We considered a set of 100,000 high-frequency (1 min intervals) position data of several free-ranging sheep (Ovis aries) at a seasonal-varying range (Patagonian Monte, Argentina) and observed their movements at landscape and at single vegetation patch scales. At a landscape scale, we inspected the spatial co-variation of seasonally varying forage offer and ewes’ movement speeds. At a patch scale, we developed a phase-state (P-S) model of movement cycles based on the occurrence of behavioral phases along foraging paths, and fitted it to the observed daily time series of ewes’ movement speeds. Ewes were preferentially distributed in areas with high forage offer during periods of low forage availability and the reverse occurred during the season of high forage availability. Parameters of the model of activity cycles amenable to control by ewes (duration of speed phases, time elapsed between speed cycles) did not covariate with forage offer, but varied significantly among ewes. The shape (kurtosis) parameter of the model of movement cycles, one which is unlikely under ewes’ control, co-varied significantly with spatial forage offer but did not differ among ewes. We conclude that ewes allocated foraging time along a series of similar movement efforts irrespective of forage availability at small patches. Average forage scarcity at multi-patch level increases the ratio of searching to feeding time. This results in apparent selective time allocation to richer forage areas but does not imply evidence for oriented movement at a landscape scale. We advance a behavioral-based definition of forage patches and discuss its implications in developing foraging theory and models. The P-S model applied to high-frequency position data of large herbivores substantially improves the interpretation of the factors controlling their time allocation in space with respect to previous models of herbivore spatial behavior by discriminating among behavioral-based and environmentally induced components of their movements.     

Modeling and inference of animal movement using artificial neural networks

Movement of animals in relation to objects in their environment is important in many areas of ecology and wildlife conservation. Tools for analysis of movement data, however, still remain rather limited. In previous work, we developed nonlinear regression models for movement in relation to a single landscape feature. Here we greatly expand these previous models by using artificial neural networks. The new models add substantial flexibility and capabilities, including the ability to incorporate multiple factors and covariates. We devise a likelihood-based model fitting procedure that utilizes genetic algorithms and demonstrate the approach with movement data for red diamond rattlesnakes. The proposed methodology can be useful for global positioning system tracking data that are becoming more common in studies of animal movement behavior.     

Effects of Patch Size and Type of Coffee Matrix on Ithomiine Butterfly Diversity and Dispersal in Cloud-Forest Fragments

Abstract: Determining the permeability of different types of landscape matrices to animal movement is essential for conserving populations in fragmented landscapes. We evaluated the effects of habitat patch size and matrix type on diversity, isolation, and dispersal of ithomiine butterflies in forest fragments surrounded by coffee agroecosystems in the Colombian Andes. Because ithomiines prefer a shaded understory, we expected the highest diversity and abundance in large fragments surrounded by shade coffee and the lowest in small fragments surrounded by sun coffee. We also thought shade coffee would favor butterfly dispersal and immigration into forest patches. We marked 9675 butterflies of 39 species in 12 forest patches over a year. Microclimate conditions were more similar to the forest interior in the shade‐coffee matrix than in the sun‐coffee matrix, but patch size and matrix type did not affect species richness and abundance in forest fragments. Furthermore, age structure and temporal recruitment patterns of the butterfly community were similar in all fragments, independent of patch size or matrix type. There were no differences in the numbers of butterflies flying in the matrices at two distances from the forest patch, but their behavior differed. Flight in the sun‐coffee matrix was rapid and directional, whereas butterflies in shade‐coffee matrix flew slowly. Seven out of 130 recaptured butterflies immigrated into patches in the shade‐coffee matrix, and one immigrated into a patch surrounded by sun coffee. Although the shade‐coffee matrix facilitated movement in the landscape, sun‐coffee matrix was not impermeable to butterflies. Ithomiines exhibited behavioral plasticity in habitat use and high mobility. These traits favor their persistence in heterogeneous landscapes, opening opportunities for their conservation. Understanding the dynamics and resource requirements of different organisms in rural landscapes is critical for identifying management options that address both animals’ and farmers’ needs.     

Incorporating behaviour into simple models of dispersal using the biological control agent Dicyphus hesperus

We explored the utility of incorporating easily measured, biologically realistic movement rules into simple models of dispersal. We depart from traditional random walk models by designing an individual-based simulation model where we decompose animal movement into three separate processes: emigration, between-patch movement, and immigration behaviour. These processes were quantified using experiments on the omnivorous insect Dicyphus hesperus moving through a tomato greenhouse. We compare the predictions of the individual-based model, along with a series of biased random walk models, against an independent experimental release of D. hesperus. We find that in this system, the short-term dispersal of these insects is described well by our individual-based model, but can also be described by a 2D grid-based biased random walk model when mortality is accounted for.     

Modelling the effect of in-stream and overland dispersal on gene flow in river networks

Modelling gene flow across natural landscapes is a current challenge of population genetics. Models are essential to make clear predictions about conditions that cause genetic differentiation or maintain connectivity between populations. River networks are a special case of landscape matrix. They represent stretches of habitat connected according to a branching pattern where dispersal is usually limited to upstream or downstream movements. Because of their peculiar topology, and the increasing concern about conservation issues in hydrosystems, there has been a recent revival of interest in modelling dispersal in river networks. Network complexity has been shown to influence global population differentiation. However, geometric characteristics are likely to interact with the way individuals move across space. Studies have focused on in-stream movements. None of the work published so far took into consideration the ability of many species to disperse overland between branches of the same network though. We predicted that the relative contribution of these two dispersal modalities (in-stream and overland) would affect the overall genetic structure. We simulated dispersal in synthetic river networks using an individual-based model. We tested the effect of dispersal modalities, i.e. the ratio of overland/in-stream dispersal, and two geometric parameters, bifurcation angle between branches and network complexity. Data revealed that if geometrical parameters affected population differentiation, dispersal parameters had the strongest effect. Interestingly, we observed a quadratic relationship between p the proportion of overland dispersers and population differentiation. We interpret this U-shape pattern as a balance between isolation by distance caused by in-stream movements at low values of p and intense migrant exchanges within the same branching unit at high values of p. Our study is the first attempt to model out-of-network movements. It clearly shows that both geometric and dispersal parameters interact. Both should be taken into consideration in order to refine predictions about dispersal and gene flow in river network.