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.     

Spatially mixed crops to control the stratified dispersal of airborne fungal diseases

Intraspecific crop diversification is thought to be a possible solution to the disease susceptibility of monocultured crops. We modelled the stratified dispersal of an airborne pathogen population in order to identify the spatial patterns of cultivar mixtures that could slow epidemic spread driven by dual dispersal mechanisms acting over both short and long distances. We developed a model to simulate the propagation of a fungal disease in a 2D field, including a reaction-diffusion model for short-distance disease dispersal, and a stochastic model for long-distance dispersal. The model was fitted to data for the spatio-temporal spread of faba bean rust (caused by Uromyces viciae-fabae) through a discontinuous field. The model was used to compare the effectiveness of eight different planting patterns of cultivar mixtures against a disease spread by short-distance and stratified dispersal. Our combined modelling approach provides a reasonably good fit with the observed data for the spread of faba bean rust. Similar predictive power could be expected for the management of resource-mediated invasions by other airborne fungi. If a disease spreads by short-distance dispersal, random mixtures can be used to slow the epidemic spread, since their spatial irregularity creates a natural barrier to the progression of a smooth epidemic wave. In the context of stratified dispersal, heterogeneous patterns should be used that include a minimum distance between susceptible units, which decreases the probability of infection by long-distance spore dispersal. We provide a simple framework for modelling the stratified dispersal of disease in a diversified crop. The model suggests that the spatial arrangement of components in cultivar mixtures has to accord with the dispersal characteristics of the pathogen in order to increase the efficiency of diversification strategies in agro-ecosystems and forestry. It can be applied in low input agriculture to manage pathogen invasion by intercropping and cultivar mixtures, and to design sustainable systems of land use.     

A process-based population dynamics model to explore target and non-target impacts of a biological control agent

The risks and benefits associated with efforts to control invasive alien species using classical biological control are being subjected to increasing scrutiny. A process-based population dynamics model was developed to explore the interactions between a folivorous biological control agent, Cleopus japonicus, and its plant host Buddleja davidii. The model revealed that climate could have a significant impact upon the interactions between B. davidii and C. japonicus. At the coolest sites, the impact of C. japonicus on B. davidii was slowed, but it was still eventually capable of controlling populations of B. davidii. At the warmer sites where both B. davidii and C. japonicus grew faster, B. davidii succumbed rapidly to weevil damage. We hypothesise that barring an encounter with a natural enemy, C. japonicus will eventually be able to provide sustained control B. davidii throughout the North Island of New Zealand. The model scenarios illustrate the potential for the C. japonicus population to attain high densities rapidly, and to defoliate patches of B. davidii, creating the potential for spill-over feeding on non-target plants. The potential magnitude of this threat will depend partly on the climate suitability for C. japonicus, the pattern by which it migrates in response to a reduction in the available leaf resource, and the suitability of non-target plants as hosts. In all migration scenarios considered, the pattern of population growth and resource consumption by C. japonicus was exponential, with a strong tendency toward complete utilisation of resource patches more quickly at the warmer compared to colder sites. In addition to providing some useful hypotheses about the effects of climate on the biological control system, and the non-target risks, it also provides some insight into the mechanisms by which climate affects the system.     

Dispersal potential of invasive algae: the determinants of buoyancy in <Emphasis Type="Italic">Codium fragile</Emphasis> ssp. <Emphasis Type="Italic">fragile</Emphasis>

The capacity for long-distance dispersal is an important factor in determining the spread of invasive species. For algae, positive buoyancy generally is correlated with increased dispersal potential, and the light environment has been previously identified as a possible determinant of buoyancy in several species. We examined the effect of light intensity on the buoyancy of fragments of the invasive green alga Codium fragile ssp. fragile. Under natural and controlled conditions, the buoyancy of samples taken from the thallus tip was higher than those from near the holdfast. Both laboratory and field experiments also showed that buoyancy was dynamic and switched from positive to negative under reduced light intensity, but this change required several days. We also observed seasonal changes in buoyancy, presumably due to natural variations in light intensity, with the buoyancy of fragments washed up on the shore highest in mid-summer. These results show that buoyancy is a dynamic property of the C. fragile ssp. fragile thallus and suggest that buoyant fragments contribute to long-range dispersal and accelerated regional spread of this invader. This finding suggests that dispersal is more likely during conditions of high light intensity and illustrates the need to understand how variations in the natural environment can affect the dispersal potential of invasive species.     

Local population dynamics of an invasive tree species with a complex life-history cycle: A stochastic matrix model

Biological invasions are widely accepted as having a major impact on ecosystem functioning worldwide, giving urgency to a better understanding of the factors that control their spread. Modelling tools have been developed for this purpose but are often discrete-space, discrete-time spatial-mechanistic models that adopt a computer simulation approach and resist mathematical analysis. We constructed a simple demographic matrix model to explore the local population dynamics of an invasive species with a complex life history and whose invasive success depends on resource availability, which occurs stochastically. As a case study we focused on the American black cherry (Prunus serotina Ehrh.), a gap-dependent tree able both to constitute a long-living seedling bank under unfavourable light conditions and to resprout vigorously once cut-down, which is invading European temperate forests. The model used was a stage-classified matrix population model (i.e., Lefkovitch matrix), integrating environmental stochasticity. Stochastic matrix projection analysis was combined with elasticity analysis and stochastic simulations to search for the species’ ‘Achille heel’. As expected, the population growth rate (i.e., Lyapunov exponent), which measures the risk of P. serotina invasion at the stand scale, increased with light frequency. There was a critical value above which the population of P. serotina explodes and below which it locally goes extinct. The resprouting capacity usually speed up the invasion but appeared to play a minor role. The mean duration of stand invasion was measured and important life stage transitions that mostly contribute to the local stochastic growth rate were identified. Some relevant management implications are discussed and the interest of such models for the understanding of demographic characteristics of invasive species is stressed.     

Assessing biodegradation benefits from dispersal networks

The performance of biodegradation of organic pollutants in soil often depends on abiotic conditions and the bioavailability of these pollutants to degrading bacteria. In this context, bacterial dispersal is an essential aspect. Recent studies on the potential promotion of bacterial dispersal by fungal hyphae raised the idea of specifically applying fungal networks to accelerate bacterial degradation processes in situ. Our objective is to investigate these processes and their performance via simulation modelling and address the following questions: (1) Under what abiotic conditions can dispersal networks significantly improve bacterial degradation? and (2) To what extent does the spatial configuration of the networks influence the degradation performance? To answer these questions, we developed a spatially explicit bacterial colony model, which is applied to controlled laboratory experiments with Pseudomonas putida G7 organisms as a case study. Using this model, we analyzed degradation performance in response to different environmental scenarios and showed that conditions of limited bacterial dispersal also limit degradation performance. Under such conditions, dispersal networks have the highest potential for improving the bioavailability of pollutants to bacteria. We also found that degradation performance significantly varies with the spatial configuration of the dispersal networks applied and the time horizon over which performance is assessed. Regarding future practical applications, our results suggest that (1) fungal networks may dramatically improve initially adverse conditions for biodegradation of pollutants in soil, and (2) the network's spatial structure and accessibility are decisive for the success of such tasks.     

Social network properties within a fish assemblage invaded by non-native sunbleak Leucaspius delineatus

Network theory is commonly used to reveal social interactions and the organisation of interconnected nodes—but has not yet been applied to animal invasions. Non-native species invasions are now considered one of the foremost threats to natural ecosystems and biodiversity. This is the first attempt to assess social network properties within a freshwater fish assemblage invaded by a non-native fish species. We show that invasive sunbleak Leucaspius delineatus is socially more strongly interconnected with native species than the native species with each other. The social networks also reveal characteristics of a ‘small world’ such as low clustering coefficients C and short path lengths L. The findings may indicate potential traits of successful invaders and the implication for the spread of pathogens between individuals within a group of animals that contain a non-native invasive species. The success of establishment and subsequent invasion may be highlighted not only by the capacity of the new species to adapt to the new environment, but also in its capacity to penetrate the social circle of the native community.     

A robust-design formulation of the incidence function model of metapopulation dynamics applied to two species of rails

The incidence function model (IFM) uses area and connectivity to predict metapopulation dynamics. However, false absences and missing data can lead to underestimates of the number of sites contributing to connectivity, resulting in overestimates of dispersal ability and turnovers (extinctions plus colonizations). We extend estimation methods for the IFM by using a hierarchical Bayesian model to account both for false absences due to imperfect detection and for missing data due to sites not surveyed in some years. We compare parameter estimates, measures of metapopulation dynamics, and forecasts using stochastic patch occupancy models (SPOMs) among three IFM models: (1) a Bayesian formulation assuming no false absences and omitting site-year combinations with missing data; (2) a hierarchical Bayesian formulation assuming no false absences but incorporating missing data; and (3) a hierarchical Bayesian formulation allowing for imperfect detection and incorporating missing data. We fit the models to multiyear data sets of occupancy for two bird species that differ in body size and presumed dispersal ability but inhabit the same network of sites: the small Black Rail (Laterallus jamaicensis) and the medium-sized Virginia Rail (Rallus limicola). Incorporating missing data affected colonization parameters and led to lower estimates of dispersal ability for the Black Rail. Detection rates were high for the Black Rail in most years but moderate for the Virginia Rail. Incorporating imperfect detection resulted in higher occupancy and lower turnover rates for both species, with largest effects for the Virginia Rail. Forecasts using SPOMs were sensitive to both missing data and false absences; persistence in models assuming no false absences was more optimistic than from robust models. Our results suggest that incorporating false absences and missing data into the IFM can improve (1) estimates of dispersal ability and the effect of connectivity on colonization, (2) the scaling of extinction risk with patch area, and (3) forecasts of occupancy and turnover rates.     

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.     

Stochastic gravity models for modeling lake invasions

Freshwater aquatic systems in North America are being invaded by many different species, ranging from fish, mollusks, cladocerans to various bacteria and viruses. These invasions have serious ecological and economic impacts. Human activities such as recreational boating are an important pathway for dispersal. Gravity models are used to quantify the dispersal effect of human activity. Gravity models currently used in ecology are deterministic. This paper proposes the use of stochastic gravity models in ecology, which provides new capabilities both in model building and in potential model applications. These models allow us to use standard statistical inference tools such as maximum likelihood estimation and model selection based on information criteria. To facilitate prediction, we use only those covariates that are easily available from common data sources and can be forecasted in future. This is important for forecasting the spread of invasive species in geographical and temporal domain. The proposed model is portable, that is it can be used for estimating relative boater traffic and hence relative propagule pressure for the lakes not covered by current boater surveys. This makes our results broadly applicable to various invasion prediction and management models.     

Epidemiological risk assessment using linked network and grid based modelling: Phytophthora ramorum and Phytophthora kernoviae in the UK

We developed a stochastic simulation model incorporating most processes likely to be important in the spread of Phytophthora ramorum and similar diseases across the British landscape (covering Rhododendron ponticum in woodland and nurseries, and Vaccinium myrtillus in heathland). The simulation allows for movements of diseased plants within a realistically modelled trade network and long-distance natural dispersal. A series of simulation experiments were run with the model, representing an experiment varying the epidemic pressure and linkage between natural vegetation and horticultural trade, with or without disease spread in commercial trade, and with or without inspections-with-eradication, to give a 2 × 2 × 2 × 2 factorial started at 10 arbitrary locations spread across England. Fifty replicate simulations were made at each set of parameter values. Individual epidemics varied dramatically in size due to stochastic effects throughout the model. Across a range of epidemic pressures, the size of the epidemic was 5–13 times larger when commercial movement of plants was included. A key unknown factor in the system is the area of susceptible habitat outside the nursery system. Inspections, with a probability of detection and efficiency of infected-plant removal of 80% and made at 90-day intervals, reduced the size of epidemics by about 60% across the three sectors with a density of 1% susceptible plants in broadleaf woodland and heathland. Reducing this density to 0.1% largely isolated the trade network, so that inspections reduced the final epidemic size by over 90%, and most epidemics ended without escape into nature. Even in this case, however, major wild epidemics developed in a few percent of cases. Provided the number of new introductions remains low, the current inspection policy will control most epidemics. However, as the rate of introduction increases, it can overwhelm any reasonable inspection regime, largely due to spread prior to detection.     

A two-dimensional stochastic model of downy mildew of radish

A two-dimensional stochastic model that simulates the spread of disease over space and time was recently proposed by Xu and Ridout [Xu, X.M., Ridout, M.S., 1998. Effects of initial epidemic conditions, sporulation rate, and spore dispersal gradient on the spatio-temporal dynamics of plant disease epidemics. Phytopathology 88, 1000–1012]. In a theoretical study, the authors showed the ability of their model to generate a broad range of disease patterns and disease progress rates. The objective of our study was to test if this theoretical approach was able to describe disease progress and the disease pattern of a specific disease, downy mildew (Peronospora parasitica) of radish (Raphanus sativus L.). Two field experiments with artificial inoculation were carried out and disease incidence and spatial pattern were assessed twice a week until disease incidence was greater than 0.25. Four model parameters were estimated by an algorithm that uses a least square regression together with an evolutionary optimisation strategy. Moran's I indices of spatial autocorrelation calculated both for measured und simulated data were significantly correlated (α = 0.05, r = 0.61). Also observed variances in measurements and in simulations were closely and significantly correlated (α = 0.05, r = 0.95). Thus, disease pattern (as assessed in terms of variance inflation and spatial autocorrelation) was well described by the model. The model accounted for 94% of the variation in the disease incidence data. It has, therefore, the potential to be developed into a forecast model for risk analysis and for decision support in plant protection. However, in the specific case of downy mildew on radish more experimental data are required for model validation and to parameterise the effects of environment on infection, sporulation and spore dispersal.     

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.     

SPAnDX: a process-based population dynamics model to explore management and climate change impacts on an invasive alien plant,Acacia nilotica

This paper describes a process-based metapopulation dynamics and phenology model of prickly acacia, Acacia nilotica, an invasive alien species in Australia. The model, SPAnDX, describes the interactions between riparian and upland sub-populations of A. nilotica within livestock paddocks, including the effects of extrinsic factors such as temperature, soil moisture availability and atmospheric concentrations of carbon dioxide. The model includes the effects of management events such as changing the livestock species or stocking rate, applying fire, and herbicide application. The predicted population behaviour of A. nilotica was sensitive to climate. Using 35 years daily weather datasets for five representative sites spanning the range of conditions that A. nilotica is found in Australia, the model predicted biomass levels that closely accord with expected values at each site. SPAnDX can be used as a decision-support tool in integrated weed management, and to explore the sensitivity of cultural management practices to climate change throughout the range of A. nilotica. The cohort-based DYMEX modelling package used to build and run SPAnDX provided several advantages over more traditional population modelling approaches (e.g. an appropriate specific formalism (discrete time, cohort-based, process-oriented), user-friendly graphical environment, extensible library of reusable components, and useful and flexible input/output support framework).     

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.     

Predicting regional spread of non-native species using oceanographic models: validation and identification of gaps

Predicting spread is a central goal of invasion ecology. Within marine systems, researchers have increasingly made use of oceanographic circulation models to estimate currents and track species dispersal. However, the accuracy of these models for predicting biological patterns, particularly for non-native species, has generally not been validated. Particularly, we wished to examine the ability of models to predict physical and biological processes, which jointly determine the spread of marine larval organisms. We conducted two empirical studies—a recruitment study and a drift card study—along the coast of New England, USA, focusing on two invaders of concern—the European green crab (Carcinus maenas) and the Asian shore crab (Hemigrapsus sanguineus), to explicitly evaluate the ability of oceanographic models to predict patterns of spread. We used data from the large-scale drift card study to validate our ability to capture dispersal patterns driven purely by physical processes. Next, we conducted a recruitment study to evaluate our ability to reproduce patterns of biological dispersal. We were generally capable of reproducing drift cards patterns—suggesting that the physical mechanics in the model were predictive. However, predicted biological patterns were inconsistent—we were able to predict dispersal patterns for H. sanguineus but not for C. maenas. Our results highlight the importance of validating models and suggest that more work is necessary before we can reliably use oceanographic models to predict biological spread of intertidal organisms.     

Population growth versus population spread of an ant-dispersed neotropical herb with a mixed reproductive strategy

In plants that produce seeds with contrasting genetic background (selfed versus outcrossed), the question arises whether the ecological function of the two types of progeny differ. This paper addresses this issue for the ant-dispersed Calathea micans by introducing a novel application of the Neubert–Caswell model for analysis of wave speed for structured populations. Because dispersal as well as vital rates are structured, the model allows for distinct dispersal kernels for different types of progeny and thus permits comparisons of the sensitivity to changes in demographic and dispersal parameters of in situ population growth rate versus population spread across space. The study site was a lowland, evergreen tropical rain forest at La Selva Biological station, Costa Rica, where the species is commonly found throughout the forest. In C. micans, seeds produced by open flowers (potentially outcrossed) or by closed flowers (selfed) bear oily arils and are dispersed by ants. Five life-history stages were used to characterize the population: seedlings originating from seeds produced by open flowers, seedlings originating from seeds produced by closed flowers, juvenile vegetative plants, reproductive plants without new shoots and reproductive plants with new shoots. Demography varied seasonally. Transitions were estimated from marking and following the fate of plants (N = 400) in a natural population over a dry and a wet season. The population dynamics was described by a 10 × 10 matrix, with five life-history stages and two habitat states. The habitat states cycle repeatedly, dry–wet–dry–wet. To estimate dispersal kernels for each seed type, individual seeds (N = 225 and 306 seeds produced by open and closed flowers, respectively) were color-coded and placed in depots, allowing the ants to redistribute them. Five months later, seedlings with an attached seed coat bearing the intact color-coding, were surveyed around the depots. Radial distances and angles were recorded for each seedling (N = 67 and 81 seedlings arising from open and closed flowers, respectively). The results of the model give an asymptotic growth rate of 1.06 per season and an asymptotic rate of spread of 8.36 cm per season. There is a high correlation (r = 0.99) between elasticity of growth rate and elasticity of rate of spread of the population. Both rates are most sensitive to changes in stasis of juveniles during the dry season. However, most interesting is the analysis that revealed that population spread is more sensitive than in situ population growth to demographic rates of seedlings arising from open flowers. The analysis suggests a new way of thinking about ecological functions of multiple modes of reproduction.     

Effect of Rotational Shepherding on Demographic and Genetic Connectivity of Calcareous Grassland Plants

Response to habitat fragmentation may not be generalized among species, in particular for plant communities with a variety of dispersal traits. Calcareous grasslands are one of the most species‐rich habitats in Central Europe, but abandonment of traditional management has caused a dramatic decline of calcareous grassland species. In the Southern Franconian Alb in Germany, reintroduction of rotational shepherding in previously abandoned grasslands has restored species diversity, and it has been suggested that sheep support seed dispersal among grasslands. We tested the effect of rotational shepherding on demographic and genetic connectivity of calcareous grassland specialist plants and whether the response of plant populations to shepherding was limited to species dispersed by animals (zoochory). Specifically, we tested competing dispersal models and source and focal patch properties to explain landscape connectivity with patch‐occupancy data of 31 species. We fitted the same connectivity models to patch occupancy and nuclear microsatellite data for the herb Dianthus carthusianorum (Carthusian pink). For 27 species, patch connectivity was explained by dispersal by rotational shepherding regardless of adaptations to zoochory, whereas population size (16% species) and patch area (0% species) of source patches were not important predictors of patch occupancy in most species. [Correction made after online publication, February 25, 2014: Population size and patch area percentages were mistakenly inverted, and have now been fixed.] Microsite diversity of focal patches significantly increased the model variance explained by patch occupancy in 90% of the species. For D. carthusianorum, patch connectivity through rotational shepherding explained both patch occupancy and population genetic diversity. Our results suggest shepherding provides dispersal for multiple plant species regardless of their dispersal adaptations and thus offers a useful approach to restore plant diversity in fragmented calcareous grasslands. Efectos del Pastoreo Rotacional sobre la Conectividad Genética y Demográfica de Plantas de Pastizales Calcáreos     

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.     

The spread of marine non-indigenous species via recreational boating: A conceptual model for risk assessment based on fault tree analysis

Recreational vessel movements are increasingly recognised as an important pathway for the spread of non-indigenous species (NIS) in marine environments. Research on risks posed by recreational vessels has focused on external hull fouling, yet a number of studies reveal the potential for NIS to also be transferred by a range of other vessel components. This paper uses fault tree analysis as a framework for incorporating input from a panel of international experts, to elucidate the consecutive steps that must occur for NIS to be introduced from different components of recreational boats. Our conceptual model reveals the complexity of the invasion process even when only the ‘release’ phase is considered (i.e. the release of NIS from an infected vessel into a new area). The model highlights that, in addition to external fouling of the ‘hull’ (hull, rudder and propeller), important vessel components may also include fouling, sediment or water released from the deck, internal spaces, anchors and fishing/diving gear. The extent to which these components are important is situation-specific, and depends on attributes of the vessel, location and NIS present. Hence, the comprehensive model described here could be modified or simplified to reflect the attributes that are relevant to particular circumstances. We demonstrate this principle using examples of three NIS: the colonial tunicate Didemnum vexillum and the Asian kelp Undaria pinnatifida that both have established in Port Nelson New Zealand after vessel-mediated spread, and the clubbed tunicate Styela clava that was detected on a vessel hull in the port but is not known to have established. Although the modelling and assessment of some of the events identified in the fault trees would be difficult or unrealistic, it is important to acknowledge them in order to provide a comprehensive risk assessment tool. Even where risks are largely unknown, difficult to quantify, or reflect stochastic events, this does not necessarily preclude management intervention.