Genetic Diversity of Invasive Species in the Great Lakes Versus Their Eurasian Source Populations: Insights for Risk Analysis

Combining DNA variation data and risk assessment procedures offers important diagnostic and monitoring tools for evaluating the relative success of exotic species invasions. Risk assessment may allow us to understand how the numbers of founding individuals, genetic variants, population sources, and introduction events affect successful establishment and spread. This is particularly important in habitats that are "hotbeds" for invasive species--such as the North American Great Lakes. This study compares genetic variability and its application to risk assessment within and among three Eurasian groups and five species that successfully invaded the Great Lakes during the mid 1980s through early 1990s; including zebra and quagga mussels, round and tubenose gobies, and the ruffe. DNA sequences are compared from exotic and native populations in order to evaluate the role of genetic diversity in invasions. Close relatives are also examined, since they often invade in concert and several are saline tolerant and are likely to spread to North American estuaries. Results show that very high genetic diversity characterizes the invasions of all five species, indicating that they were founded by very large numbers of propagules and underwent no founder effects. Genetic evidence points to multiple invasion sources for both dreissenid and goby species, which appears related to especially rapid spread and widespread colonization success in a variety of habitats. In contrast, results show that the ruffe population in the Great Lakes originated from a single founding population source from the Elbe River drainage. Both the Great Lakes and the Elbe River populations of ruffe have similar genetic diversity levels--showing no founder effect, as in the other invasive species. In conclusion, high genetic variability, large numbers of founders, and multiple founding sources likely significantly contribute to the risk of an exotic species introduction's success and persistence.     

Ensemble Habitat Mapping of Invasive Plant Species

Ensemble species distribution models combine the strengths of several species environmental matching models, while minimizing the weakness of any one model. Ensemble models may be particularly useful in risk analysis of recently arrived, harmful invasive species because species may not yet have spread to all suitable habitats, leaving species‐environment relationships difficult to determine. We tested five individual models (logistic regression, boosted regression trees, random forest, multivariate adaptive regression splines (MARS), and maximum entropy model or Maxent) and ensemble modeling for selected nonnative plant species in Yellowstone and Grand Teton National Parks, Wyoming; Sequoia and Kings Canyon National Parks, California, and areas of interior Alaska. The models are based on field data provided by the park staffs, combined with topographic, climatic, and vegetation predictors derived from satellite data. For the four invasive plant species tested, ensemble models were the only models that ranked in the top three models for both field validation and test data. Ensemble models may be more robust than individual species‐environment matching models for risk analysis.     

Assessing the Risk of Invasive Spread in Fragmented Landscapes

Little theoretical work has investigated how landscape structure affects invasive spread, even though broad-scale disturbances caused by habitat loss and fragmentation are believed to facilitate the spread of exotic species. Neutral landscape models (NLMs), derived from percolation theory in the field of landscape ecology, provide a tool for assessing the risk of invasive spread in fragmented landscapes. A percolation-based analysis of the potential for invasive spread in fragmented landscapes predicts that invasive spread may be enormously enhanced beyond some threshold level of habitat loss, which depends upon the species' dispersal abilities and the degree of habitat fragmentation. Assuming that invasive species spread primarily through disturbed areas of the landscape, poor dispersers may spread better in landscapes in which disturbances are concentrated in space, whereas good dispersers are predicted to spread better in landscapes where disturbances are small and dispersed (i.e., fragmented landscape). Assessing the risk of invasive spread in fragmented landscapes ultimately requires understanding the relative effects of landscape structure on processes that contribute to invasive spread--dispersal (successful colonization) and demography (successful establishment). Colonization success is predicted to be highest when >20% of the landscape has been disturbed, particularly if disturbances are large or aggregated in space, because propagules are more likely to encounter sites suitable for colonization and establishment. However, landscape pattern becomes less important for predicting colonization success if species are capable of occasional long-distance dispersal events. Invasive species are also more likely to persist and achieve positive population growth rates (successful establishment) in landscapes with clumped disturbance patterns, which can then function as population sources that produce immigrants that invade other landscapes. Finally, the invasibility of communities may be greatest in landscapes with a concentrated pattern of disturbance, especially below some critical threshold of biodiversity. Below the critical biodiversity threshold, the introduction of a single species can trigger a cascade of extinctions among indigenous species. The application of NLMs may thus offer new insights and opportunities for the management and restoration of landscapes so as to slow the spread of invasive species.     

Risk Analysis for Biological Hazards: What We Need to Know about Invasive Species

Risk analysis for biological invasions is similar to other types of natural and human hazards. For example, risk analysis for chemical spills requires the evaluation of basic information on where a spill occurs; exposure level and toxicity of the chemical agent; knowledge of the physical processes involved in its rate and direction of spread; and potential impacts to the environment, economy, and human health relative to containment costs. Unlike typical chemical spills, biological invasions can have long lag times from introduction and establishment to successful invasion, they reproduce, and they can spread rapidly by physical and biological processes. We use a risk analysis framework to suggest a general strategy for risk analysis for invasive species and invaded habitats. It requires: (1) problem formation (scoping the problem, defining assessment endpoints); (2) analysis (information on species traits, matching species traits to suitable habitats, estimating exposure, surveys of current distribution and abundance); (3) risk characterization (understanding of data completeness, estimates of the "potential" distribution and abundance; estimates of the potential rate of spread; and probable risks, impacts, and costs); and (4) risk management (containment potential, costs, and opportunity costs; legal mandates and social considerations and information science and technology needs).     

Modeling the Risks of Nonindigenous Species Introductions Using a Patch-Dynamics Approach Incorporating Contaminant Effects as a Disturbance

The establishment and spread of invasive or nonindigenous species has caused concern from stakeholders in affected areas, and has prompted many field and modeling studies. We used stochastic two species, circular three patch dynamic models to investigate the patterns of invasion and impacts upon the affected species. Both persistent and degradable toxicants were incorporated as parts of the model system to act as disturbance regimens. There is a clear series of patterns that result from these simulations. Competition increases population variability, but decreases the number of distinct outcomes possible from the same initial conditions. Isolation of the patch of the introduction was the main determinant of successful establishment through a process we call the beachhead effect. Coexistence of species was often possible in local patches, contrary to the analytical solutions of Lotka-Volterra equations and numerous modeling studies. Contaminants and their resultant disturbances are important as contributors to the stochastic nature of models. The stochasticity leads to a variety of outcomes from some sets of initial conditions. Different outcomes have different probabilities of occurrence and are dependent upon the specific initial conditions of the simulation. A clear pattern that is apparent is the "beachhead effect," where the invasive establishes a population within a relatively remote patch before migrating to the remainder of the landscape. We make predictions and provide specific research hypotheses as to the causes and effects of invasive species establishment, spread, and impacts.     

Knowledge-Based Risk Assessment Under Uncertainty for Species Invasion

Management of invasive species depends on developing prevention and control strategies through comprehensive risk assessment frameworks that need a thorough analysis of exposure to invasive species. However, accurate exposure analysis of invasive species can be a daunting task because of the inherent uncertainty in invasion processes. Risk assessment of invasive species under uncertainty requires potential integration of expert judgment with empirical information, which often can be incomplete, imprecise, and fragmentary. The representation of knowledge in classical risk models depends on the formulation of a precise probabilistic value or well-defined joint distribution of unknown parameters. However, expert knowledge and judgments are often represented in value-laden terms or preference-ordered criteria. We offer a novel approach to risk assessment by using a dominance-based rough set approach to account for preference order in the domains of attributes in the set of risk classes. The model is illustrated with an example showing how a knowledge-centric risk model can be integrated with the dominance-based principle of rough set to derive minimal covering "if ... , then...," decision rules to reason over a set of possible invasion scenarios. The inconsistency and ambiguity in the data set is modeled using the rough set concept of boundary region adjoining lower and upper approximation of risk classes. Finally, we present an extension of rough set to evidence a theoretic interpretation of risk measures of invasive species in a spatial context. In this approach, the multispecies interactions in an invasion risk are approximated with imprecise probability measures through a combination of spatial neighborhood information of risk estimation in terms of belief and plausibility.     

Ecological Risk Assessment Conceptual Model Formulation for Nonindigenous Species

This article addresses the application of ecological risk assessment at the regional scale to the prediction of impacts due to invasive or nonindigenous species (NIS). The first section describes risk assessment, the decision-making process, and introduces regional risk assessment. A general conceptual model for the risk assessment of NIS is then presented based upon the regional risk assessment approach. Two diverse examples of the application of this approach are presented. The first example is based upon the dynamics of introduced plasmids into bacteria populations. The second example is the application risk assessment approach to the invasion of a coastal marine site of Cherry Point, Washington, USA by the European green crab. The lessons learned from the two examples demonstrate that assessment of the risks of invasion of NIS will have to incorporate not only the characteristics of the invasive species, but also the other stresses and impacts affecting the region of interest.     

First Application of FISK,the Freshwater Fish Invasiveness Screening Kit,in Northern Europe: Example of Southern Finland

The climatic conditions of north temperate countries pose unique influences on the rates of invasion and the potential adverse impacts of non‐native species. Methods are needed to evaluate these risks, beginning with the pre‐screening of non‐native species for potential invasives. Recent improvements to the Fish Invasiveness Scoring Kit (FISK) have provided a means (i.e., FISK v2) of identifying potentially invasive non‐native freshwater fishes in virtually all climate zones. In this study, FISK is applied for the first time in a north temperate country, southern Finland, and calibrated to determine the appropriate threshold score for fish species that are likely to pose a high risk of being invasive in this risk assessment area. The threshold between “medium” and “high” risk was determined to be 22.5, which is slightly higher than the original threshold for the United Kingdom (i.e., 19) and that determined for a FISK application in southern Japan (19.8). This underlines the need to calibrate such decision‐support tools for the different areas where they are employed. The results are evaluated in the context of current management strategies in Finland regarding non‐native fishes.     

Risk analysis of fast spreading species in a Kashmir Himalayan National Park (Dachigam) for better monitoring and management

Huge economic costs and ecological impacts of invasive alien species (IAS) in the protected areas (PAs) worldwide make their timely prediction and potential risk assessment of central importance for effective management. While the preborder weed risk assessment framework has been extensively evaluated and implemented, the postborder species risk assessment framework has not been subjected to the same degree of scrutiny. Here we used a rather more realistic modified version of the Australian Weed Risk framework (AWRM) for Dachigam National Park (DNP) in Kashmir Himalaya against 84 plant species, including 55 alien species and 29 fast spreading native species, for risk analysis. We found two very high-risk species, three high-risk species, 10 medium-risk species, 29 low-risk species, and 40 negligible-risk species in the DNP. The containment scores accordingly ranged from 14.4 to 293.5 comprising of 27 species that can be contained with very high feasibility, 23 species with high feasibility, 14 species with medium feasibility, and 12 species which cannot be contained easily thereby having low feasibility of containment (FOC) score. However, eight species which have a negligible FOC score are difficult to contain within their infestation sites. Our results demonstrate the merit of the AWRM with a caution that the necessary region-specific modifications may help in its better implementation. Overall, these results provide quite a promising tool in the hands of protected area managers to timely and effectively deal with the problem of plant invasions.     

Evaluating Potential Distribution of High‐Risk Aquatic Invasive Species in the Water Garden and Aquarium Trade at a Global Scale Based on Current Established Populations

Aquatic non‐native invasive species are commonly traded in the worldwide water garden and aquarium markets, and some of these species pose major threats to the economy, the environment, and human health. Understanding the potential suitable habitat for these species at a global scale and at regional scales can inform risk assessments and predict future potential establishment. Typically, global habitat suitability models are fit for freshwater species with only climate variables, which provides little information about suitable terrestrial conditions for aquatic species. Remotely sensed data including topography and land cover data have the potential to improve our understanding of suitable habitat for aquatic species. In this study, we fit species distribution models using five different model algorithms for three non‐native aquatic invasive species with bioclimatic, topographic, and remotely sensed covariates to evaluate potential suitable habitat beyond simple climate matches. The species examined included a frog (Xenopus laevis), toad (Bombina orientalis), and snail (Pomacea spp.). Using a unique modeling approach for each species including background point selection based on known established populations resulted in robust ensemble habitat suitability models. All models for all species had test area under the receiver operating characteristic curve values greater than 0.70 and percent correctly classified values greater than 0.65. Importantly, we employed multivariate environmental similarity surface maps to evaluate potential extrapolation beyond observed conditions when applying models globally. These global models provide necessary forecasts of where these aquatic invasive species have the potential for establishment outside their native range, a key component in risk analyses.     

Establishment Risks for Invasive Species

This article presents a quantitative methodology for evaluating the probability of invasive pest species establishing persistent populations. The estimation of pest establishment relies on data and information describing the biology and ecology of the pest and its interactions with potential host species and the regional environment. This information is developed using a model construct borrowed from theoretical population ecology. The methodology for estimating the probability of pest establishment is part of an overall framework that explores the implications of reductions in pest invasions on subsequent establishment. The risk reduction framework integrates the engineering aspects of different technologies for reducing pest entry, the biology and ecology of pest species, the suitability of potentially susceptible hosts, and the quality of available habitats. The methodology for estimating the risk of establishment is presented using an example pest, the Asian longhorned beetle ( Anoplophora glabripennis ), which has been introduced into the United States via solid wood packing materials (SWPM) used in international commerce. Uncertainties inherent to the estimation of model parameters that determine the risk of establishment are defined, quantified, and propagated through the population model. Advantages and limitations of the proposed methodology are discussed along with recommendations to make the approach more useful in the management of risks posed by the establishment of pest populations.     

Risk Analysis for Invasive Species: General Framework and Research Needs

A joint workshop was convened by the Society for Risk Analysis Ecological Risk Assessment Specialty Group and the Ecological Society of America Theoretical Ecology Section to provide independent scientific input into the formulation of methods and processes for risk assessment of invasive species. In breakout sessions on (1) the effects of invasive species on human health, (2) effects on plants and animals, (3) risk analysis issues and research needs related to entry and establishment of invasive species, and (4) risk analysis issues and research needs related to the spread and impacts of invasive species, workshop participants discussed an overall approach to risk assessment for invasive species. Workshop participants agreed on the need for empirical research on areas in which data are lacking, including potential invasive species, native species and habitats that may be impacted by invasive species, important biological processes and phenomena such as dispersal, and pathways of entry and spread for invasive species. Participants agreed that theoretical ecology can inform the process of risk assessment for invasive species by providing guidelines and conceptual models, and can contribute to improved decision making by providing a firm biological basis for risk assessments.     

What Can Decision Analysis Do for Invasive Species Management?

Decisions about management of invasive species are difficult for all the reasons typically addressed by multiattribute decision analysis: uncertain outcomes, multiple and conflicting objectives, and many interested parties with differing views on both facts and values. This article illustrates how the tools of multiattribute analysis can improve management of invasive species, with an emphasis on making explicit the social values and preferences that must inform invasive species management. Risk assessment protocols developed previously for invasive species management typically suffer from two interacting flaws: (1) separating risk assessment from risk management, thus disrupting essential connections between the social values at stake in invasive species decisions and the scientific knowledge necessary to predict the likely impacts of management actions, and (2) relying on expert judgment about risk framed in qualitative and value-laden terms, inadvertently mixing the expert's judgment about what is likely to happen with personal preferences. Using the values structuring and probability-modeling elements of formal decision analysis can remedy these difficulties and make invasive species management responsive to both good science and public values. The management of feral pigs in Hawaiian ecosystems illustrates the need for such an integrated approach.     

Effectiveness of FISK,an Invasiveness Screening Tool for Non‐Native Freshwater Fishes,to Perform Risk Identification Assessments in the Iberian Peninsula

Risk assessments are crucial for identifying and mitigating impacts from biological invasions. The Fish Invasiveness Scoring Kit (FISK) is a risk identification (screening) tool for freshwater fishes consisting of two subject areas: biogeography/history and biology/ecology. According to the outcomes, species can be classified under particular risk categories. The aim of this study was to apply FISK to the Iberian Peninsula, a Mediterranean climate region highly important for freshwater fish conservation due to a high level of endemism. In total, 89 fish species were assessed by three independent assessors. Results from receiver operating characteristic analysis showed that FISK can discriminate reliably between noninvasive and invasive fishes for Iberia, with a threshold of 20.25, similar to those obtained in several regions around the world. Based on mean scores, no species was categorized as “low risk,” 50 species as “medium risk,” 17 as “moderately high risk,” 11 as “high risk,” and 11 as “very high risk.” The highest scoring species was goldfish Carassius auratus. Mean certainty in response was above the category “mostly certain,” ranging from tinfoil barb Barbonymus schwanenfeldii with the lowest certainty to eastern mosquitofish Gambusia holbrooki with the highest level. Pair‐wise comparison showed significant differences between one assessor and the other two on mean certainty, with these two assessors showing a high coincidence rate for the species categorization. Overall, the results suggest that FISK is a useful and viable tool for assessing risks posed by non‐native fish in the Iberian Peninsula and contributes to a “watch list” in this region.     

Risk Assessment for Invasive Species

Although estimates vary, there is a broad agreement that invasive species impose major costs on the U.S. economy, as well as posing risks to nonmarket environmental goods and services and to public health. The domestic effort to manage risks associated with invasive species is coordinated by the National Invasive Species Council (NISC), which is charged with developing a science-based process to evaluate risks associated with the introduction and spread of invasive species. Various international agreements have also elevated invasive species issues onto the international policy agenda. The World Trade Organization (WTO) Sanitary and Phytosanitary (SPS) Agreement establishes rights and obligations to adhere to the discipline of scientific risk assessment to ensure that SPS measures are applied only to the extent required to protect human, animal, and plant health, and do not constitute arbitrary or unjustifiable technical barriers to trade. Currently, however, the field of risk assessment for invasive species is in its infancy. Therefore, there is a pressing need to formulate scientifically sound methods and approaches in this emerging field, while acknowledging that the demand for situation-specific empirical evidence is likely to persistently outstrip supply. To begin addressing this need, the Society for Risk Analysis Ecological Risk Assessment Specialty Group and the Ecological Society of America Theoretical Ecology Section convened a joint workshop to provide independent scientific input into the formulation of methods and processes for risk assessment of invasive species to ensure that the analytic processes used domestically and internationally will be firmly rooted in sound scientific principles.     

Robustness of Risk Maps and Survey Networks to Knowledge Gaps About a New Invasive Pest

In pest risk assessment it is frequently necessary to make management decisions regarding emerging threats under severe uncertainty. Although risk maps provide useful decision support for invasive alien species, they rarely address knowledge gaps associated with the underlying risk model or how they may change the risk estimates. Failure to recognize uncertainty leads to risk‐ignorant decisions and miscalculation of expected impacts as well as the costs required to minimize these impacts. Here we use the information gap concept to evaluate the robustness of risk maps to uncertainties in key assumptions about an invading organism. We generate risk maps with a spatial model of invasion that simulates potential entries of an invasive pest via international marine shipments, their spread through a landscape, and establishment on a susceptible host. In particular, we focus on the question of how much uncertainty in risk model assumptions can be tolerated before the risk map loses its value. We outline this approach with an example of a forest pest recently detected in North America, Sirex noctilio Fabricius. The results provide a spatial representation of the robustness of predictions of S. noctilio invasion risk to uncertainty and show major geographic hotspots where the consideration of uncertainty in model parameters may change management decisions about a new invasive pest. We then illustrate how the dependency between the extent of uncertainties and the degree of robustness of a risk map can be used to select a surveillance network design that is most robust to knowledge gaps about the pest.     

Evaluating Critical Uncertainty Thresholds in a Spatial Model of Forest Pest Invasion Risk

Pest risk maps can provide useful decision support in invasive species management, but most do not adequately consider the uncertainty associated with predicted risk values. This study explores how increased uncertainty in a risk model's numeric assumptions might affect the resultant risk map. We used a spatial stochastic model, integrating components for entry, establishment, and spread, to estimate the risks of invasion and their variation across a two-dimensional landscape for Sirex noctilio , a nonnative woodwasp recently detected in the United States and Canada. Here, we present a sensitivity analysis of the mapped risk estimates to variation in key model parameters. The tested parameter values were sampled from symmetric uniform distributions defined by a series of nested bounds (±5%, … , ±40%) around the parameters' initial values. The results suggest that the maximum annual spread distance, which governs long-distance dispersal, was by far the most sensitive parameter. At ±15% or larger variability bound increments for this parameter, there were noteworthy shifts in map risk values, but no other parameter had a major effect, even at wider bounds of variation. The methodology presented here is generic and can be used to assess the impact of uncertainties on the stability of pest risk maps as well as to identify geographic areas for which management decisions can be made confidently, regardless of uncertainty.     

Optimal Strategies for Interception,Detection, and Eradication in Plant Biosecurity

The introduction of invasive species causes damages from the economic and ecological point of view. Interception of plant pests and eradication of the established populations are two management options to prevent or limit the risk posed by an invasive species. Management options generate costs related to the interception at the point of entry, and the detection and eradication of established field populations. Risk managers have to decide how to allocate resources between interception, field detection, containment, and eradication minimizing the expected total costs. In this work is considered an optimization problem aiming at determining the optimal allocation of resources to minimize the expected total costs of the introduction of Bemisia tabaci‐transmitted viruses in Europe. The optimization problem takes into account a probabilistic model for the estimation of the percentage of viruliferous insect populations arriving through the trade of commodities, and a population dynamics model describing the process of the vector populations' establishment and spread. The time of field detection of viruliferous insect populations is considered as a random variable. The solution of the optimization problem allows to determine the optimal allocation of the search effort between interception and detection/eradication. The behavior of the search effort as a function of efficacy or search in interception and in detection is then analyzed. The importance of the vector population growth rate and the probability of virus establishment are also considered in the analysis of the optimization problem.     

Managing Invasive Species in the Presence of Endogenous Technological Change with Uncertainty

This research incorporates the development and adoption of an induced technology under uncertainty into a conceptual dynamic model to more broadly examine efficient policies for mitigating invasive species infestations. We find that under optimal policy, marginal costs of adopting conventional control measures are equal to the sum of the marginal benefits from development and adoption of new technology, as well as the use of conventional control measures. This result implies that a resource allocation designed for controlling invasive species is not adequate when an induced technology is not considered. Our results also reveal that the shadow values associated with the probabilities of developing and then adopting an induced technology increase as the shadow values associated with the stock of an invasive species population increase.     

Projecting Rates of Spread for Invasive Species

All else being equal, the faster an invading species spreads, the more dangerous its invasion. The projection of spread rate therefore ought to be a central part of the determination of invasion risk. Originally formulated in the 1970s to describe the spatial spread of advantageous alleles, integrodifference equation (IDE) models have since been co-opted by population biologists to describe the spread of populations. More recently, they have been modified to include population structure and environmental variability. We review how IDE models are formulated, how they are parameterized, and how they can be analyzed to project spread rates and the sensitivity of those rates to changes in model parameters. For illustrative purposes, we apply these models to Cytisus scoparius, a large shrub in the legume family that is considered a noxious invasive species in eastern and western North America, Chile, Australia, and New Zealand.