Unveiling human-assisted dispersal mechanisms in invasive alien insects: Integration of spatial stochastic simulation and phenology models

Capturing the spread of biological invasions in heterogeneous landscapes is a complex modelling task where information on both dispersal and population dynamics needs to be integrated. Spatial stochastic simulation and phenology models have rarely been combined to assist in the study of human-assisted long-distance dispersal events.Here we develop a process-based spatially explicit landscape-extent simulation model that considers the spread and detection of invasive insects. Natural and human-assisted dispersal mechanisms are modelled with an individual-based approach using negative exponential and negative power law dispersal kernels and gravity models. The model incorporates a phenology sub-model that uses daily temperature grids for the prediction and timing of the population dynamics in each habitat patch. The model was applied to the study of the invasion by the important maize pest western corn rootworm (WCR) Diabrotica virgifera ssp. virgifera in Europe. We parameterized and validated the model using maximum likelihood and simulation methods from the historical invasion of WCR in Austria.WCR was found to follow stratified dispersal where international transport networks in the Danube basin played a key role in the occurrence of long-distance dispersal events. Detection measures were found to be effective and altitude had a significant effect on limiting the spread of WCR. Spatial stochastic simulation combined with phenology models, maximum likelihood methods and predicted versus observed regression showed a high degree of flexibility that captured the salient features of WCR spread in Austria. This modelling approach is useful because it allows to fully exploit and the often limited and heterogeneous information available regarding the population dynamics and dispersal of alien invasive insects.     

Exploitative competition between invasive herbivores benefits a native host plant

Although biological invasions are of considerable concern to ecologists, relatively little attention has been paid to the potential for and consequences of indirect interactions between invasive species. Such interactions are generally thought to enhance invasives' spread and impact (i.e., the "invasional meltdown" hypothesis); however, exotic species might also act indirectly to slow the spread or blunt the impact of other invasives. On the east coast of the United States, the invasive hemlock woolly adelgid (Adelges tsugae, HWA) and elongate hemlock scale (Fiorinia externa, EHS) both feed on eastern hemlock (Tsuga canadensis). Of the two insects, HWA is considered far more damaging and disproportionately responsible for hemlock mortality. We describe research assessing the interaction between HWA and EHS, and the consequences of this interaction for eastern hemlock. We conducted an experiment in which uninfested hemlock branches were experimentally infested with herbivores in a 2 x 2 factorial design (either, both, or neither herbivore species). Over the 2.5-year course of the experiment, each herbivore's density was approximately 30% lower in mixed- vs. single-species treatments. Intriguingly, however, interspecific competition weakened rather than enhanced plant damage: growth was lower in the HWA-only treatment than in the HWA + EHS, EHS-only, or control treatments. Our results suggest that, for HWA-infested hemlocks, the benefit of co-occurring EHS infestations (reduced HWA density) may outweigh the cost (increased resource depletion).     

The ecology of energy and nutrient fluxes in hemlock forests invaded by hemlock woolly adelgid

The hemlock woolly adelgid (HWA, Adelges tsugae Annand) is currently causing a severe decline in vitality and survival of eastern hemlock in North American forests. We analyzed the effects of light HWA infestation on vertical energy and nutrient fluxes from the canopy to the forest floor. Canopy throughfall, litter lysimeters, and laboratory litter microcosms were used to examine the effects of HWA-affected and unaffected throughfall on litter type, leachate, and litter chemistry. Early in the season adelgid infestation caused higher dissolved organic carbon (DOC; +24.6%), dissolved organic nitrogen (DON; +28.5%), and K (+39.3%) fluxes and lower inorganic nitrogen fluxes (-39.8%) in throughfall and in adjacent litter solutions collected beneath infested compared to uninfested trees. Needle litter collected beneath uninfested hemlock had significantly lower N concentrations compared to needles collected beneath infested trees, while no difference in N concentrations was found in birch litter. Bacteria were significantly more abundant on hemlock and birch litter beneath infested trees, while yeasts and filamentous fungi showed no consistent response to HWA throughfall. Litter microcosms showed that less DOC was leaching from birch than from hemlock needles when exposed to HWA throughfall. Overall, NH4-N and DON leachate concentrations were higher from birch than from hemlock litter. Thus, HWA-affected throughfall leads to qualitative and quantitative differences in nitrogen export from the litter layer. The N concentration of hemlock litter did not change with time, but the N concentration in birch litter increased significantly during the course of the experiment, especially when HWA-affected throughfall was applied. We suggest a nonlinear conceptual model for the temporal and vertical transition of energy and nutrient fluxes relative to progressing HWA infestation from a pure hemlock to a birch/maple-dominated forest. Progressive needle loss and changes in needle chemistry are likely to produce a humped-shaped DOC curve, while N fluxes initially decrease as infestation continues but rise eventually with hemlock decline and immigration of hardwood species. These findings suggest that it is necessary to understand the biology and specific physiological/trophic effects of exotic pests on their hosts and associated ecosystem processes in order to decipher the temporal dynamics, direction of change, and functional consequences.     

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.     

Heterogeneity shapes invasion: host size and environment influence susceptibility to a nonnative pathogen.

Theoretical study of invasion dynamics has suggested that spatial heterogeneity should strongly influence the rate and extent of spreading organisms. However, empirical support for this prediction is scant, and the importance of understanding heterogeneity for real-world systems has remained ambiguous. This study quantified the influence of host and environmental heterogeneity on the dynamics of a 19-year disease invasion by the exotic and fatal pathogen, Phytophthora lateralis, within a stream population of its host tree, Port Orford cedar (Chamaecyparis lawsoniana). Using dendrochronology, we reconstructed the invasion history along a 1350-m length of infected stream, which serves as the only route of pathogen dispersal. Contrary to theoretical predictions, the temporal progression of the disease invasion was not related to a host's downstream spatial position, but instead was determined by two sources of heterogeneity: host size and proximity to the stream channel. These sources of heterogeneity influenced both the epidemic and endemic dynamics of this pathogen invasion. This analysis provides empirical support for the influence of heterogeneity on the invasion dynamics of a commercially important forest pathogen and highlights the need to incorporate such natural variability into both invasion theory and methods aimed at controlling future spread.     

Continuous versus binary representations of landscape heterogeneity in spatially-explicit models of mobile populations

How a landscape is represented is an important structural assumption in spatially-explicit simulation models. Simple models tend to specify just habitat and non-habitat (binary), while more complex models may use multiple levels or a continuum of habitat quality (continuous). How these different representations influence model projections is unclear. To assess the influence of landscape representation on population models, I developed a general, individual-based model with local dispersal and examined population persistence across binary and continuous landscapes varying in the amount and fragmentation of habitat. In binary and continuous landscapes habitat and non-habitat were assigned a unique mean suitability. In continuous landscapes, suitability of each individual site was then drawn from a normal distribution with fixed variance. Populations went extinct less often and abundances were higher in continuous landscapes. Production in habitat and non-habitat was higher in continuous landscapes, because the range of habitat suitability sampled by randomly dispersing individuals was higher than the overall mean habitat suitability. Increasing mortality, dispersal distance, and spatial heterogeneity all increased the discrepancy between continuous and binary landscapes. The effect of spatial structure on the probability of extinction was greater in binary landscapes. These results show that, under certain circumstances, model projections are influenced by how variation in suitability within a landscape is represented. Care should be taken to assess how a given species actually perceives the landscape when conducting population viability analyses or empirical validation of theory.     

Genes and song: genetic and social connections in fragmented habitat in a woodland bird with limited dispersal

Understanding the processes leading to population declines in fragmented landscapes is essential for successful conservation management. However, isolating the influence of disparate processes, and dispersal in particular, is challenging. The Grey Shrike-thrush, Colluricincla harmonica, is a sedentary woodland-dependent songbird, with learned vocalizations whose incidence in suitable habitat patches falls disproportionally with decline in tree cover in the landscape. Although it has been suggested that gaps in tree cover might act as barriers to its dispersal, the species remains in many remnants of native vegetation in agricultural landscapes, suggesting that it may have responded to habitat removal and fragmentation by maintaining or even increasing dispersal distances. We quantified population connectivity of the Grey Shrike-thrush in a system fragmented over more than 120 years using genetic (microsatellites) and acoustic (song types) data. First, we tested for population genetic and acoustic structure at regional and local scales in search of barriers to dispersal or gene flow and signals of local spatial structuring indicative of restricted dispersal or localized acoustic similarity. Then we tested for effects of habitat loss and fragmentation on genetic and acoustic connectivity by fitting alternative models of mobility (isolation-by-distance [the null model] and reduced and increased movement models) across treeless vs. treed areas. Birds within -5 km of each other had more similar genotypes and song types than those farther away, suggesting that dispersal and song matching are limited in the region. Despite restricted dispersal detected for females (but not males), populations appeared to be connected by gene flow and displayed some cultural (acoustic) connectivity across the region. Fragmentation did not appear to impact greatly the dispersal of the Grey Shrike-thrush: none of the mobility models fit the genetic distances of males, whereas for females, an isolation-by-distance model could not be rejected in favor of the models of reduced or increased movement through treeless gaps. However, dissimilarities of the song types were more consistent with the model of reduced cultural connectivity through treeless areas, suggesting that fragmentation impedes song type sharing in the Grey Shrike-thrush. Our paper demonstrates that habitat fragmentation hinders important population processes in an Australian woodland bird even though its dispersal is not detectably impacted.     

Effects of density-dependent dispersal behaviours on the speed and spatial patterns of range expansion in predator-prey metapopulations

Dispersal can strongly affect the spatiotemporal dynamics of a species (its spread, spatial distribution and persistence). We investigated how two dispersal behaviours, namely prey evasion (PE) and predator pursuit (PP), affect the dynamics of a predator-prey system. PE portrays the tendency of prey avoiding predators by dispersing into adjacent patches with fewer predators, while PP describes the tendency of predators to pursue the prey by moving into patches with more prey. Based on the Beddington predation model, a spatially explicit metapopulation model was built to incorporate PE and PP. Numerical simulations were run to investigate the effects of PE and PP on the rate of spread, spatial synchrony and the persistence of populations. Results show that both PE and PP can alter spatial synchrony although PP has a weaker desynchronising effect than PE. The predator-prey system without PE and PP expanded in circular waves. The effect of PE can push the prey to distribute in a circular ring front, whereas the effect of PP can change the circular waves to anisotropic expansion. Furthermore, weak PE and PP can accelerate the spread of prey while strong and disproportionate intensities slow down the range expansion. The effects of PE and PP further enhance the population size, break down the spatial synchrony and promote the persistence of populations.     

Extinction Dynamics in the American Marten (Martes americana)

We constructed a model of marten population dynamics and used it to investigate extinction processes across a wide range of parameter values. The model was based on rules governing the behavior and physiology of individual martens and focused on energy balance. Spatial dynamics and demographic and environmental stochasticity were incorporated. The outcome was the probability of extinction and quasiextinction (20 females remaining) over 500 years. Three qualitative forms of extinction were delineated. The first was deterministic extinction, associated with those parameter combinations leading to a negative population growth rate. The second was probabilistic extinction in systems with a strong positive growth rate but restricted population size due to habitat constraint. The transition from 100% persistence to 100% quasiextinction, as the input habitat size was decreased, was abrupt. The final form of extinction was in systems with a growth rate of approximately zero. Prey availability maintained an upper limit on these populations, but otherwise fluctuations in population size were essentially random, leading to nontrivial probabilities of extinction in even relatively large populations. A number of issues requiring further empirical research were identified. These included the relationship between habitat quality and marten reproduction, dispersal patterns and dispersal mortality, the effect of habitat edge on marten reproduction and mortality, and the characterization of the severity and frequency of catastrophic mortality as experienced by marten populations.     

Evaluating the effect of corridors and landscape heterogeneity on dispersal probability: a comparison of three spatially explicit modelling approaches

Spatially explicit simulation models of varying degree of complexity are increasingly used in landscape and species management and conservation. The choice as to which type of model to employ in a particular situation, is however, far too often governed by logistic constraints and the personal preferences of the modeller, rather than by a critical evaluation of model performance. We present a comparison of three common spatial simulation approaches (patch-based incidence-function model (IFM), individual-based movement model (IBMM), individual-based population model including detailed behaviour and demographics (IBPM)). The IBPM was analysed in two versions (IBPM_st and IBPM_dyn). Both assumed spatial heterogeneity of the matrix, but the IBPM_dyn in addition included temporal matrix dynamics. The models were developed with a shared minimum objective, namely to predict dynamics of individuals or populations in space given a specific configuration of habitat patches. We evaluated how the choice of model influenced predictions regarding the effect of patch and corridor configuration on dispersal probabilities and the number of successful immigrants of a simulated small mammal. Model results were analysed both at the level of the entire habitat network and at the level of individual patches.All models produced similar rankings of alternative habitat networks, but large discrepancies existed between absolute estimates of dispersal probabilities and the number of successful immigrants predicted by the different models. Generally, predicted dispersal probabilities were highest in the IBMM, intermediate in the IFM and the IBPM_st and lowest in the IBPM_dyn. Observed differences were due both to differences in implementation (e.g. raster versus vector-based movement algorithms), the chosen level of detail in landscape representation (e.g. matrix complexity) and the degree of behavioural realism included in the models (e.g. demography, differentiated mortality).The advantages and disadvantages of the three modelling approaches are discussed, as are the implications of the results for the recommended use of the three types of models in practical management.     

Dispersal in Spatially Explicit Population Models

Abstract: Ruckelshaus et al. (1997) outlined a simulation model of dispersal between patches in a fragmented landscape. They showed that dispersal success—the proportion of dispersers successfully locating a patch—was particularly sensitive to errors in dispersal mortality and concluded that this limits the utility of spatially explicit population models in conservation biology. I contend that, although they explored error propagation in a simple dispersal model, they did not explore how errors are propagated in spatially explicit population models, as no consideration of population processes was included. I developed a simple simulation model to investigate the effect of varying dispersal success on predictions of patch occupancy and population viability, the conventional outputs of spatially explicit population models. The model simulates births and deaths within habitat patches and dispersal as the transfer of individuals between them. Model predictions were sensitive to changes in dispersal success across a restricted range of within-patch growth rates, which depended on the dispersal initiation mechanism, patch carrying capacities, and number of generations simulated. Predictions of persistence and patch occupancy were generally more sensitive to changes in dispersal success (1) under presaturation rather than saturation dispersal; (2) at lower patch carrying capacities; and (3) over longer time periods. The framework I present provides a means of assessing, quantitatively, the regions of parameter space for which differences in dispersal success are likely to have a large effect on population model outputs. Investigating the effect of the representation of dispersal behavior within the demographic and landscape context provides a more useful assessment of whether our lack of knowledge is likely to cause unacceptable uncertainty in the predictions of spatially explicit population models.     

Dispersal, competition, and shifting patterns of diversity in a degraded oak savanna

Diversity is a balance between processes that add and limit species (e.g., dispersal vs. competition), but reconciling their contributions remains a challenge. Recruit-ment-based models predict that dispersal barriers are most limiting for diversity, while competition-based models predict that dispersal matters only when competition is minimized. Testing these models is difficult because their influence varies with scale and site productivity. In a degraded oak savanna, we used plot-level (seed additions, burning) and site-level (proportions of regional functional groups found locally) analyses in areas with variable soil depth to examine how dispersal and competition influence diversity. At the plot level, added species persisted where they were formerly absent, but few established naturally despite fire-induced resource enrichment and nearby populations, revealing the importance of dispersal limitation for diversity. This result did not vary with soil depth or standing crop. Although competition could not prevent establishment in unburned plots, it significantly lowered survival, indicating that resource limitations exacerbate dispersal inefficiencies. At the site level, the concordance between regional and local diversity for native species was associated with soil depth heterogeneity, not dispersal or competition. This suggests that persistence is determined primarily by the influence of the environment on population demographics. Given that the formation of new populations is unlikely, those remaining appear to be confined to optimal habitat where they resist competitive or stochastic displacement, possibly explaining why species loss is rare despite substantial habitat loss and invasion. For exotics, there was no relationship between diversity and soil depth heterogeneity. Annuals with presumed dispersal capabilities were significantly overrepresented in all sites while perennial forbs, the largest regional functional group, were significantly underrepresented. We interpret the native-exotic discrepancies as reflecting the recent arrival of exotics (150 years ago), suggesting that local establishment occurs slowly even for species with regional prevalence. The accumulation lag may be explained by the need for founder populations to be demographically stable; otherwise persistence requires continual immigration favoring overrepresentation by dispersers. Our findings support the view that dispersal limitation restricts diversity within plant communities, but suggests that the impacts of environment on demographic performance ultimately determine the pattern and rate of community assembly.     

Spatiotemporal dynamics in variable population interactions with density-dependent interaction coefficients

In this article, I present a two-patch metapopulation model with locally explicit dynamics to study the effect of spatial heterogeneity and dispersal upon population interactions with variable or conditional outcomes. These are interactions that may be either detrimental or beneficial for each species depending on the balance of the density-dependent costs and benefits involved. The local dynamics respond to density-dependent α-interaction functions that may change sign, thus yielding a diversity of possible local outcomes for the association in terms of type of interaction and in the number of stable solutions. The spatiotemporal model predicts that the fragmentation of space and dispersal between patches may cause further variation in these outcomes. First, the demographic performance of a species in the association is enhanced if migrations cause a proportional increase of individuals of its own species; being so, a victim may become a mutualist or an exploiter, an excluded species may invade, and a good competitor may overcome its own carrying capacity: the ‘enhancement effect of dispersal’; a sort of rescue effect in source-sink dynamics. The underlying mechanisms involve an interplay between density-dependent effects of dispersal per se and the relative local and global average α-interaction functions, which involve costs and benefits at both the local and regional level that may either counteract or reinforce each other; thus, localities and/or populations may change dynamically their sink or source role in the spatial dynamics. A significant insight arises herewith: in the context of variable or conditional interactions the concept of the role of a species does not make strict sense; it becomes a spatiotemporal dynamic quality. Second, regardless of which species disperses, bifurcation of equilibria may occur in those patches that receive the migrating individuals, and annihilation of equilibria in those from where migration leaves; thus, the number of equilibria increases or decreases accordingly.     

Controlling range expansion in habitat networks by adaptively targeting source populations

Controlling the spread of invasive species, pests, and pathogens is often logistically limited to interventions that target specific locations at specific periods. However, in complex, highly connected systems, such as marine environments connected by ocean currents, populations spread dynamically in both space and time via transient connectivity links. This results in nondeterministic future distributions of species in which local populations emerge dynamically and concurrently over a large area. The challenge, therefore, is to choose intervention locations that will maximize the effectiveness of the control efforts. We propose a novel method to manage dynamic species invasions and outbreaks that identifies the intervention locations most likely to curtail population expansion by selectively targeting local populations most likely to expand their future range. Critically, at any point during the development of the invasion or outbreak, the method identifies the local intervention that maximizes the long‐term benefit across the ecosystem by restricting species’ potential to spread. In so doing, the method adaptively selects the intervention targets under dynamically changing circumstances. To illustrate the effectiveness of the method we applied it to controlling the spread of crown‐of‐thorns starfish (Acanthaster sp.) outbreaks across Australia's Great Barrier Reef. Application of our method resulted in an 18‐fold relative improvement in management outcomes compared with a random targeting of reefs in putative starfish control scenarios. Although we focused on applying the method to reducing the spread of an unwanted species, it can also be used to facilitate the spread of desirable species through connectivity networks. For example, the method could be used to select those fragments of habitat most likely to rebuild a population if they were sufficiently well protected.     

Do source-sink dynamics promote the spread of an invasive grass into a novel habitat?

Models of source-sink and other spatial patch dynamics have generated a number of ideas and predictions about species range expansion, the evolution of local adaptation, and the factors influencing population persistence, but relatively few empirical studies have applied these ideas due to the difficulty of measuring both patch-specific demography and movement rates. In this study, I used a combination of mark-recapture experiments, model fitting, and demographic approaches to ask how habitat-specific differences in population growth and dispersal affect spread of the invasive grass Aegilops triuncialis into serpentine environments. A. triuncialis germinated at lower rates but exhibited equivalent survival and greater growth in edge (extreme serpentine) than in core populations, even accounting for density differences between habitats. Estimated growth rates (lambda) for four of five edge subpopulations were strongly positive, ranging from lambda = 1.32 to 2.09 without propagule input from adjacent habitat. Local dispersal was best described by an exponential kernel, with a mean dispersal distance about twice as long on the edge (0.24-0.40 m) as in the core (0.18 m). Twenty-five percent of marked spikes in the edge were not relocated within the patch, suggesting greater rates of either seed predation or long-distance dispersal that reduced population growth. These results suggest that A. triuncialis can successfully spread into extreme serpentine habitats without sustained propagule input from adjacent populations. Further, asymmetric dispersal that may be both habitat- and density-dependent could slow growth rates on the edge. This pattern may also increase the importance of harsh edge patches as a source of long-distance dispersers.     

Influence of host migration between woodland and pasture on the population dynamics of the tick Ixodes ricinus: A modelling approach

Ticks act as vectors of pathogens that can be harmful to animals and/or humans. Epidemiological models can be useful tools to investigate the potential effects of control strategies on diseases such as tick-borne diseases. The modelling of tick population dynamics is a prerequisite to simulating tick-borne diseases and the corresponding spread of the pathogen. We have developed a dynamic model to simulate changes in tick density at different stages (egg, larva, nymph and adult) under the influence of temperature. We have focused on the tick Ixodes ricinus, which is widespread in Europe. The main processes governing the biological cycles of ticks were taken into account: egg laying, hatching, development, host (small, mainly rodents, or large, like deer and cattle, mammals) questing, feeding and mortality. This model was first applied to a homogeneous habitat, where simulations showed the ability of the model to reproduce the general patterns of tick population dynamics. We considered thereafter a multi-habitat model, where three different habitats (woodland, ecotone and meadow) were connected through host migration. Based on this second application, it appears that migration from woodland, via the ecotone, is necessary to sustain the presence of ticks in the meadow. Woodland can therefore be considered as a source of ticks for the meadow, which in turn can be regarded as a sink. The influence of woodland on surrounding tick densities increases in line with the area of this habitat before reaching a plateau. A sensitivity analysis to parameter values was carried out and demonstrated that demographic parameters (sex ratio, development, mortality during feeding and questing, host finding) played a crucial role in the determination of questing nymph densities. This type of modelling approach provides insight into the influence of spatial heterogeneity on tick population dynamics.     

Temporal limits to simulating the future spread pattern of invasive species: Buddleja davidii in Europe and New Zealand

The spread of invasive species is a major ecological and economic problem. Dynamic spread modelling is a potentially valuable tool to assist regional and central government authorities to monitor and control invasive species. To date a lack of suitable data has meant that most broad scale dispersal models have not been validated with independent datasets, and so their predictive ability and reliability has remained unscrutinised. A dynamic, stochastic dispersal model of the widely invasive plant Buddleja davidii was calibrated on European spread data and then used to project the temporal progression of B. davidii's distribution in New Zealand, starting from several different historical distributions. To assess the model's performance, we constructed an occupancy map based on the average number of simulation realisations that have a population present. The application of Receiver Operating Characteristic (ROC) curves to occupancy maps is introduced, but with specificity substituted by the proportion of available area used in a realisation. A derivative measure, the partial area under these curves when assessed through time (pAUC), is introduced and used to assess overall performance of the spread model. The model was able to attain a high level of model sensitivity, encompassing all of the known locations within the occupancy envelope. However, attempting to simulate the spread of this invasive species beyond a decade had very low model specificity. This is due to several factors, including the exponential process of spread (the further a population spreads the more sites exist from which it can spread stochastically), and the Markovian chain property of the stochastic system whereby differences between realisations compound through time. These features are seen in many reports of spread models, without being explicitly acknowledged. Our measure of pAUC through time allows a model's temporal performance and its specificity to be simultaneously assessed. While the rapid deterioration in model performance limits the utility of this type of modelling for forecasting long-term broad-scale strategic management of biological invasions, it does not necessarily limit its attractiveness for informing smaller scale and shorter term invasion management activities such as surveillance, containment and local eradication.     

Demographic stochasticity reduces the synchronizing effect of dispersal in predator-prey metapopulations

Dispersal may affect predator-prey metapopulations by rescuing local sink populations from extinction or by synchronizing population dynamics across the metapopulation, increasing the risk of regional extinction. Dispersal is likely influenced by demographic stochasticity, however, particularly because dispersal rates are often very low in metapopulations. Yet the effects of demographic stochasticity on predator-prey metapopulations are not well known. To that end, I constructed three models of a two-patch predator-prey system. The models constitute a hierarchy of complexity, allowing direct comparisons. Two models included demographic stochasticity (pure jump process [PJP] and stochastic differential equations [SDE]), and the third was deterministic (ordinary differential equations [ODE]). One stochastic model (PJP) treated population sizes as discrete, while the other (SDE) allowed population sizes to change continuously. Both stochastic models only produced synchronized predator-prey dynamics when dispersal was high for both trophic levels. Frequent dispersal by only predators or prey in the PJP and SDE spatially decoupled the trophic interaction, reducing synchrony of the non-dispersive species. Conversely, the ODE generated synchronized predator-prey dynamics across all dispersal rates, except when initial conditions produced anti-phase transients. These results indicate that demographic stochasticity strongly reduces the synchronizing effect of dispersal, which is ironic because demographic stochasticity is often invoked post hoc as a driver of extinctions in synchronized metapopulations.     

Fire and forest landscapes in the Georgia Piedmont: an assessment of spatial modeling assumptions

Landscape simulation models are widely used to study the behavior of ecological systems. As computing power has increased, these models have become more complex and incorporated more realistic spatial representations of landscape patterns and ecological processes. The goal of this research was to examine the sensitivity of simulated landscape patterns to fundamental spatial modeling assumptions. The LANDIS simulator was parameterized for forests of the Georgia Piedmont and used to model landscape-scale community dynamics at fire return intervals from 20 to 100 years. A base scenario incorporating localized seed dispersal along with landform-related variation in species establishment rates and disturbance regimes was contrasted with three alternative scenarios. The uniform habitat scenario applied the same set of species establishment coefficients across all landforms. The uniform dispersal scenario removed the effects of seed source abundance and pattern on species establishment. The uniform disturbance scenario assumed identical disturbance regimes on all landforms.At the shortest fire return intervals, fire severities were low and the stand age distribution was dominated by older forests. At longer fire return intervals, fire severities were high and the stand age distribution was skewed toward younger forests. Species composition generally followed a gradient from fire-resistant species at short fire return intervals to fire-sensitive species at longer fire return intervals. However, some species exhibited bimodal distributions with high abundances at both short and long fire return intervals. Landscape responses to fire were similar in the uniform habitat scenario and the base scenario. Communities were less sensitive to fire return interval and had more fire-sensitive species in the uniform dispersal scenario than in the base scenario. Species composition in the uniform disturbance scenario was similar to the base scenario for the longest fire-intervals, but was more sensitive to changes in the fire regime at shorter fire return intervals. In models of Piedmont forest landscapes, accurate spatial representations of dispersal and fire regime heterogeneity are essential for predicting landscape-scale species composition under changing fire regimes. In contrast, the precise spatial representation of species–habitat relationships may be considerably less important.     

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.