The effects of plant distribution and frugivore density on the scale and shape of dispersal kernels

For many plant species, seed dispersal is one of the most important spatial demographic processes. We used a diffusion approximation and a spatially explicit simulation model to explore the mechanisms generating seed dispersal kernels for plants dispersed by frugivores. The simulation model combined simple movement and foraging rules with seed gut passage time, plant distribution, and fruit production. A simulation experiment using plant spatial aggregation and frugivore density as factors showed that seed dispersal scale was largely determined by the degree of plant aggregation, whereas kernel shape was mostly dominated by frugivore density. Kernel shapes ranged from fat tailed to thin tailed, but most shapes were between an exponential and that of the solution of a diffusion equation. The proportion of dispersal kernels with fat tails was highest for landscapes with clumped plant distributions and increased with increasing number of dispersers. The diffusion model provides a basis for models including more behavioral details but can also be used to approximate dispersal kernels once a diffusion rate is estimated from animal movement data. Our results suggest that important characteristics of dispersal kernels will depend on the spatial pattern of plant distribution and on disperser density when frugivores mediate seed dispersal.     

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.     

The effect of patch constellation on the exchange of individuals between habitat-islands

Metapopulation models assume that inter-patch dispersal dominantly depends on distance between patches and the dispersal capability of organisms in question. We used a spatially explicit, individual-based model to investigate the potential effect of patch constellation on the exchange of individuals between patches. We simulated migration of individuals from a start- into a target-patch with both patches having the same size and shape. Simulation experiments were carried out for four patch constellations and two different movement patterns. Our results demonstrate a substantial effect of patch constellation on the exchange of individuals. They also show that the magnitude and even the direction of this effect crucially depends on their movement pattern. We conclude that particularly for highly correlated movement patterns patch shape and constellation can not readily be ignored when modelling inter-patch dispersal between habitat-islands.     

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.     

Using interview surveys and multispecies occupancy models to inform vertebrate conservation

Species distribution data are an essential biodiversity variable requiring robust monitoring to inform wildlife conservation. Yet, such data remain inherently sparse because of the logistical challenges of monitoring biodiversity across broad geographic extents. Surveys of people knowledgeable about the occurrence of wildlife provide an opportunity to evaluate species distributions and the ecology of wildlife communities across large spatial scales. We analyzed detection histories of 30 vertebrate species across the Western Ghats biodiversity hotspot in India, obtained from a large-scale interview survey of 2318 people who live and work in the forests of this region. We developed a multispecies occupancy model that simultaneously corrected for false-negative (non-detection) and false-positive (misidentification) errors that interview surveys can be prone to. Using this model, we integrated data across species in composite analyses of the responses of functional species groups (based on disturbance tolerance, diet, and body mass traits) to spatial variation in environmental variables, protection, and anthropogenic pressures. We observed a positive association between forest cover and the occurrence of species with low tolerance of human disturbance. Protected areas were associated with higher occurrence for species across different functional groups compared with unprotected lands. We also observed the occurrence of species with low disturbance tolerance, herbivores, and large-bodied species was negatively associated with developmental pressures, such as human settlements, energy production and mining, and demographic pressures, such as biological resource extraction. For the conservation of threatened vertebrates, our work underscores the importance of maintaining forest cover and reducing deforestation within and outside protected areas, respectively. In addition, mitigating a suite of pervasive human pressures is also crucial for wildlife conservation in one of the world's most densely populated biodiversity hotspots.     

Invasive species distribution modeling (iSDM): Are absence data and dispersal constraints needed to predict actual distributions?

Species distribution models (SDMs) based on statistical relationships between occurrence data and underlying environmental conditions are increasingly used to predict spatial patterns of biological invasions and prioritize locations for early detection and control of invasion outbreaks. However, invasive species distribution models (iSDMs) face special challenges because (i) they typically violate SDM's assumption that the organism is in equilibrium with its environment, and (ii) species absence data are often unavailable or believed to be too difficult to interpret. This often leads researchers to generate pseudo-absences for model training or utilize presence-only methods, and to confuse the distinction between predictions of potential vs. actual distribution. We examined the hypothesis that true-absence data, when accompanied by dispersal constraints, improve prediction accuracy and ecological understanding of iSDMs that aim to predict the actual distribution of biological invasions. We evaluated the impact of presence-only, true-absence and pseudo-absence data on model accuracy using an extensive dataset on the distribution of the invasive forest pathogen Phytophthora ramorum in California. Two traditional presence/absence models (generalized linear model and classification trees) and two alternative presence-only models (ecological niche factor analysis and maximum entropy) were developed based on 890 field plots of pathogen occurrence and several climatic, topographic, host vegetation and dispersal variables. The effects of all three possible types of occurrence data on model performance were evaluated with receiver operating characteristic (ROC) and omission/commission error rates. Results show that prediction of actual distribution was less accurate when we ignored true-absences and dispersal constraints. Presence-only models and models without dispersal information tended to over-predict the actual range of invasions. Models based on pseudo-absence data exhibited similar accuracies as presence-only models but produced spatially less feasible predictions. We suggest that true-absence data are a critical ingredient not only for accurate calibration but also for ecologically meaningful assessment of iSDMs that focus on predictions of actual distributions.     

Natal dispersal in two mice species with contrasting social systems

We compared the natal dispersal behaviour of two mice species under laboratory conditions. Natal dispersal is a movement of an animal from its birthplace to its breeding area. This behaviour is known to be influenced by the mating system. In polygamous species, males are more likely to disperse, while in most of the monogamous species, both sexes disperse. Our subjects, the house mouse (Mus musculus) and the mound-building mouse (Mus spicilegus) are two sympatric species of the genus Mus. Both are native in Hungary, but they differ in their habitat type mating system and overwintering strategy. The house mouse is a polygynous species and adapted to human environment, known for mature and reproduce early. On the contrary, the mound-building mice are monogamous, and they inhabit extensively used agricultural fields, where they spend the unfavourable winter period in nest chambers under mounds, which they construct from soil and plant material. Successful overwintering for this species demands delayed maturity and reduced dispersion during the winter. Our results showed that the natal dispersal of these two species differ; both sexes of the mound-building mice dispersed later than the house mice, where a difference between sexes also occurs; house mice males dispersed earlier than females. The mound-building mice showed no sexual dimorphism in this behaviour.     

Modeling range dynamics in heterogeneous landscapes: invasion of the hemlock woolly adelgid in eastern North America

Range expansion by native and exotic species will continue to be a major component of global change. Anticipating the potential effects of changes in species distributions requires models capable of forecasting population spread across realistic, heterogeneous landscapes and subject to spatiotemporal variability in habitat suitability. Several decades of theory and model development, as well as increased computing power and availability of fine-resolution GIS data, now make such models possible. Still unanswered, however, is the question of how well this new generation of dynamic models will anticipate range expansion. Here we develop a spatially explicit stochastic model that combines dynamic dispersal and population processes with fine-resolution maps characterizing spatiotemporal heterogeneity in climate and habitat to model range expansion of the hemlock woolly adelgid (HWA; Adelges tsugae). We parameterize this model using multiyear data sets describing population and dispersal dynamics of HWA and apply it to eastern North America over a 57-year period (1951-2008). To evaluate the model, the observed pattern of spread of HWA during this same period was compared to model predictions. Our model predicts considerable heterogeneity in the risk of HWA invasion across space and through time, and it suggests that spatiotemporal variation in winter temperature, rather than hemlock abundance, exerts a primary control on the spread of HWA. Although the simulations generally matched the observed current extent of the invasion of HWA and patterns of anisotropic spread, it did not correctly predict when HWA was observed to arrive in different geographic regions. We attribute differences between the modeled and observed dynamics to an inability to capture the timing and direction of long-distance dispersal events that substantially affected the ensuing pattern of spread.     

Linking direct and indirect data on dispersal: isolation by slope in a headwater stream salamander

There is growing recognition of the need to incorporate information on movement behavior in landscape-scale studies of dispersal. One way to do this is by using indirect indices of dispersal (e.g., genetic differentiation) to test predictions derived from direct data on movement behavior. Mark-recapture studies documented upstream-biased movement in the salamander Gyrinophilus porphyriticus (Plethodontidae). Based on this information, we hypothesized that gene flow in G. porphyriticus is affected by the slope of the stream. Specifically, because the energy required for upstream dispersal is positively related to slope, we predicted gene flow to be negatively related to change in elevation between sampling sites. Using amplified DNA fragment length polymorphisms among tissue samples from paired sites in nine streams in the Hubbard Brook Watershed, New Hampshire, USA, we found that genetic distances between downstream and upstream sites were positively related to change in elevation over standardized 1-km distances. This pattern of isolation by slope elucidates controls on population connectivity in stream networks and underscores the potential for specific behaviors to affect the genetic structure of species at the landscape scale. More broadly, our results show the value of combining direct data on movement behavior and indirect indices to assess patterns and consequences of dispersal in spatially complex ecosystems.     

Experimental manipulation of seed shadows of an Afrotropical tree determines drivers of recruitment

The loss of animals in tropical forests may alter seed dispersal patterns and reduce seedling recruitment of tree species, but direct experimental evidence is scarce. We manipulated dispersal patterns of Manilkara mabokeensis, a monkey-dispersed tree, to assess the extent to which spatial distributions of seeds drive seedling recruitment. Based on the natural seed shadow, we created seed distributions with seeds deposited under the canopy ("no dispersal"), with declining density from the tree ("natural dispersal"), and at uniform densities ("good dispersal"). These distributions mimicked dispersal patterns that could occur with the extirpation of monkeys, low levels of hunting, and high rates of seed dispersal. We monitored seedling emergence and survival for 18 months and recorded the number of leaves and damage to leaves. "Good dispersal" increased seedling survival by 26%, and "no dispersal" decreased survival by 78%, relative to "natural dispersal." Using a mixed-effects survival model, we decoupled the distance and density components of the seed shadow: seedling survival depended on the seed density, but not on the distance from the tree. Although community seedling diversity tended to decrease with longer dispersal distances, we found no conclusive evidence that patterns of seed dispersal influence the diversity of the seedling community. Local seed dispersal does affect seedling recruitment and survival, with better dispersal resulting in higher seedling recruitment; hence the loss of dispersal services that comes with the reduction or extirpation of seed dispersers will decrease regeneration of some tree species.     

The Role of Roadsides in Plant Invasions: a Demographic Approach

Abstract:  Non-native plant species are common along roadsides, but presence does not necessarily indicate spread along the road axis. Roadsides may serve merely as habitat for a species spreading independently of roads. The potential conduit function of roads depends on the habitat specificity of the spreading species, its dispersal range relative to the spacing of roads in the landscape, and the relative importance of long- and short-range dispersal. We describe a demographic model of the road × species interaction and suggest methods of assessing conduit function in the field based on the model results. A species limited to roadside habitat will be constrained to spread along the road axis unless its long-range dispersal is sufficient to carry it across the intervening unfavorable area to another road. It will propagate along a road corridor at a rate determined by the scale of short-range dispersal. Effective management of an invasion requires distinguishing between the habitat and conduit functions, a distinction difficult to make with only snapshot data. Invasions can be reconstructed by several methods, but none is totally satisfactory. We suggest comparing stem distributions on transects parallel and perpendicular to the road axis, and beside the road, and away from it, with an idealized Gaussian curve. Such comparisons would allow discrimination between pattern determined by habitat suitability and pattern reflecting random and facilitated dispersal.     

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.     

Including Spatial Heterogeneity and Animal Dispersal When Evaluating Hunting: a Model Analysis and an Empirical Assessment in an Amazonian Community

Abstract:  Hunting in tropical forests is typically most intense near human settlements, and this creates gradients of decreasing animal densities toward those settlements. Within the context of this spatial pattern, we evaluated the status of game in the hunting grounds of an indigenous community in eastern Ecuador. We constructed a spatially explicit model of hunter-prey interactions that mimicked the hunting in the village and included realistic animal-dispersal rules. We compared predictions from the model with distributions of animal harvest rates and catch per unit effort of 12 game species. Six species were overharvested in part or all of the area, and two other species were probably being overharvested, although high dispersal rates complicated the interpretation. We then compared our method with methods that have been used previously. We argue that because our method provides information about the spatial extent of overharvesting, it could be particularly useful in informing decision makers about where to establish no-take areas and could therefore aid in improving the sustainability of hunting in tropical forests.     

Modeling leaf dispersal in mixed hardwood forests using a ballistic approach

In mixed-species stands, modeling leaf litter dispersal is important to predict the physical and chemical characteristics of the forest floor, which plays a major role in nutrient cycling and in plant population dynamics. In this study, a spatially explicit model of leaf litterfall was developed and compared with two other models. These three models were calibrated for a mixed forest of oak and beech using litterfall data from mapped forest plots. All models assumed that an allometric equation described individual leaf litter production, but they strongly differed in the modeling of the probability density of leaf shedding with distance from source trees. Two models used a negative exponential function to account for leaf dispersal with distance, and this function was allowed to vary according to wind direction in one of them. In contrast, our approach was based on a simple ballistic equation considering release height, wind speed, wind direction, and leaf fall velocity; the distributions of wind speeds and wind directions were modeled according to a Weibull and a Von Mises distribution, respectively. Using an independent validation data set, all three models provided predictions well correlated to measurements (r > 0.83); however, the two models with a direction-dependent component were slightly more accurate. In addition, parameter estimates of the ballistic model were in close agreement with a foliar litter production equation derived from the literature for beech and with wind characteristics measured during leaf litterfall for both species. Because of its mechanistic background, such a spatially explicit model might be incorporated as a litterfall module in larger models (nutrient cycling, plant population dynamics) or used to determine the manner in which patch size in mixed-species stands influences litter mixture.     

Microsite-limited recruitment controls fern colonization of post-agricultural forests

Assessing the relative roles of dispersal limitation and environmental effects in population dynamics and community assembly is fundamental to understanding patterns of species distribution and diversity. In forests growing on abandoned agricultural lands, both legacies of vegetation disturbance and changes in the abiotic environment shape the diversity and composition of recovering communities. Here I specify how interactions among historical, environmental, and biological factors influence species distributions, focusing on three fern species with contrasting distributions across forests of different history in central New York, USA: Dryopteris carthusiana, Dryopteris intermedia, and Polystichum acrostichoides. Using population surveys, spore-trap and spore-bank studies, and a three-year field experiment, I compare demographic rates among species and between forest types to determine which life history stages limit colonization and which traits explain species distributions. Adult plants of all three species were larger and more likely to produce spores in post-agricultural forests than in adjacent, uncleared stands. Though lower population densities led to fewer spores in post-agricultural soils, spore availability still exceeded recruitment by four to five orders of magnitude. Sowing additional spores had relatively little effect, while microhabitat conditions had the greatest impact on establishment rates. Given similar microsites, the two forest types had equal rates of establishment, but some forest-floor features preferentially occupied by juvenile plants were less frequent in post-agricultural stands. The availability of suitable sites for establishment, created by small-scale heterogeneity on forest floors, thus limits both the growth of fern populations and the colonization of new habitats. In fact, reduced microtopographic variation in post-agricultural forests may represent a greater hindrance to plant establishment than changes in mean environmental conditions. Among the three fern species, establishment rates differed as species distributions would predict, with the strongest colonizer consistently having the highest rates and the slowest colonizer the lowest. Rather than random or trait-mediated dispersal, the different distributions of these species reflect life history traits that determine establishment rates and thus colonization ability. This case study demonstrates that ecological interactions based on the unique life histories of individual species can override dispersal in determining species distributions.     

An individual-based stochastic hazard model of eastern king prawn (Melicertus plebejus) migration with spatially and temporally varying fishing effort

This paper describes an individual-based stochastic model of eastern king prawn migration along the eastern Australian coast. Migration is treated as one-dimensional diffusion with drift. Capture of a prawn is seen as a failure event driven by movement through a spatially and temporally variable fishing mortality hazard. This hazard is combined with a uniform natural mortality hazard. We use a Monte Carlo method to estimate parameters by comparing expected numbers of tag-returns predicted from the model with previously published tag-release data. As the previous study used a discrete compartmental model, with compartments corresponding to zones of constant fishing effort, we used the same zones and fishing effort in our comparison. The marginal distribution of yield in each zone per single recruit is determined, providing more information compared with the deterministic approach to yield-per-recruit. Using our model we also derive the constant fishing mortality rate equivalent to a spatially variable fishing mortality rate in its impact on the proportion of prawns surviving the migration to reach spawning grounds. Determination of this proportion could contribute significantly to a sustainability assessment of the fishery. It is demonstrated using the AIC that better fits to the data of the previous study and greater parsimony are obtained using our model than were found in the deterministic compartmental analysis of that study. This improvement results from the ability of our model to account separately for average speed of movement and average dispersal rate, whereas in the previous deterministic compartmental model, movement is governed by just one parameter. Our individual-based model includes a parameter that explicitly accounts for dispersal of prawns in migration, so it can distinguish between speed effects and dispersal effects in the data. It also models both types of mortality as processes distinct from those of movement. This enables it to better separate movement and mortality effects compared to the compartmental approach, in which movement and mortality are treated as similar departure processes from a compartment. This separation reduces confounding of movement and mortality effects when parameters are estimated.     

Defining and Evaluating the Umbrella Species Concept for Conserving and Restoring Landscape Connectivity

Conserving or restoring landscape connectivity between patches of breeding habitat is a common strategy to protect threatened species from habitat fragmentation. By managing connectivity for some species, usually charismatic vertebrates, it is often assumed that these species will serve as conservation umbrellas for other species. We tested this assumption by developing a quantitative method to measure overlap in dispersal habitat of 3 threatened species—a bird (the umbrella), a butterfly, and a frog—inhabiting the same fragmented landscape. Dispersal habitat was determined with Circuitscape, which was parameterized with movement data collected for each species. Despite differences in natural history and breeding habitat, we found substantial overlap in the spatial distributions of areas important for dispersal of this suite of taxa. However, the intuitive umbrella species (the bird) did not have the highest overlap with other species in terms of the areas that supported connectivity. Nevertheless, we contend that when there are no irreconcilable differences between the dispersal habitats of species that cohabitate on the landscape, managing for umbrella species can help conserve or restore connectivity simultaneously for multiple threatened species with different habitat requirements. Definición y Evaluación del Concepto de Especie Paraguas para Conservar y Restaurar la Conectividad de Paisajes     

Connectivity Planning to Address Climate Change

As the climate changes, human land use may impede species from tracking areas with suitable climates. Maintaining connectivity between areas of different temperatures could allow organisms to move along temperature gradients and allow species to continue to occupy the same temperature space as the climate warms. We used a coarse‐filter approach to identify broad corridors for movement between areas where human influence is low while simultaneously routing the corridors along present‐day spatial gradients of temperature. We modified a cost–distance algorithm to model these corridors and tested the model with data on current land‐use and climate patterns in the Pacific Northwest of the United States. The resulting maps identified a network of patches and corridors across which species may move as climates change. The corridors are likely to be robust to uncertainty in the magnitude and direction of future climate change because they are derived from gradients and land‐use patterns. The assumptions we applied in our model simplified the stability of temperature gradients and species responses to climate change and land use, but the model is flexible enough to be tailored to specific regions by incorporating other climate variables or movement costs. When used at appropriate resolutions, our approach may be of value to local, regional, and continental conservation initiatives seeking to promote species movements in a changing climate. Planificación de Conectividad para Atender el Cambio Climático     

A dispersal-constrained habitat suitability model for predicting invasion of alpine vegetation

Developing tools to predict the location of new biological invasions is essential if exotic species are to be controlled before they become widespread. Currently, alpine areas in Australia are largely free of exotic plant species but face increasing pressure from invasive species due to global warming and intensified human use. To predict the potential spread of highly invasive orange hawkweed (Hieracium aurantiacum) from existing founder populations on the Bogong High Plains in southern Australia, we developed an expert-based, spatially explicit, dispersal-constrained, habitat suitability model. The model combines a habitat suitability index, developed from disturbance, site wetness, and vegetation community parameters, with a phenomenological dispersal kernel that uses wind direction and observed dispersal distances. After generating risk maps that defined the relative suitability of H. aurantiacum establishment across the study area, we intensively searched several locations to evaluate the model. The highest relative suitability for H. aurantiacum establishment was southeast from the initial infestations. Native tussock grasslands and disturbed areas had high suitability for H. aurantiacum establishment. Extensive field searches failed to detect new populations. Time-step evaluation using the location of populations known in 1998-2000, accurately assigned high relative suitability for locations where H. aurantiacum had established post-2003 (AUC [area under curve] = 0.855 +/- 0.035). This suggests our model has good predictive power and will improve the ability to detect populations and prioritize areas for ongoing monitoring.     

Grassy field margins as potential corridors for butterflies in agricultural landscapes: A simulation study

Over the last decades, agricultural intensification has caused a dramatic reduction of grassy habitats. This habitat loss has had a strong negative effect on many meadow-living insect populations, including butterflies. As a part of the cross-compliance measures of the Common Agricultural Policy of the European Union, subsidies for creation and maintenance of grassy field margins (GFM) have been launched. Among other environmental issues, they may serve as corridors for movement of various meadow-living species between individual meadows. Their role as corridors has, however, not yet been demonstrated at the landscape scale and their characteristics that most significantly increase landscape connectivity are unknown. Empirical data for such studies are missing, as the GFM subsidies were launched only 3 years ago. One possibility to get some predictions of their outcomes is provided by simulation models. Here we present our simulation results, using an extension of the model developed by Kindlmann et al. (2004) for the Meadow Brown butterfly, Maniola jurtina. The extension includes the probability to cross a boundary (Conradt and Roper, 2006) that negatively influences dispersal rates but increases sensitivity to the corridor effect. Our simulations show that GFMs increase the dispersal rates between habitat patches and we predict the optimal combinations of width and number of GFMs in the landscape. This way we provide a decision-making tool for increasing landscape connectivity for M. jurtina and similar species. Although our simulations are based on a particular species, they may be generalized because this species shows dispersal rates that are typical of butterfly metapopulations (Conradt et al., 2000), and a potentially widespread dispersal kernel (i.e. “foray search”) that has been reported in a wide variety of species (see Conradt et al., 2003 for a review).