Invasive Species Risk Research Articles

New pasture plants intensify invasive species risk.

Agricultural intensification is critical to meet global food demand, but intensification threatens native species and degrades ecosystems. Sustainable intensification (SI) is heralded as a new approach for enabling growth in agriculture while minimizing environmental impacts. However, the SI literature has overlooked a major environmental risk. Using data from eight countries on six continents, we show that few governments regulate conventionally bred pasture taxa to limit threats to natural areas, even though most agribusinesses promote taxa with substantial weed risk. New pasture taxa (including species, subspecies, varieties, cultivars, and plant-endophyte combinations) are bred with characteristics typical of invasive species and environmental weeds. By introducing novel genetic and endophyte variation, pasture taxa are imbued with additional capacity for invasion and environmental impact. New strategies to prevent future problems are urgently needed. We highlight opportunities for researchers, agribusiness, and consumers to reduce environmental risks associated with new pasture taxa. We also emphasize four main approaches that governments could consider as they build new policies to limit weed risks, including (i) national lists of taxa that are prohibited based on environmental risk; (ii) a weed risk assessment for all new taxa; (iii) a program to rapidly detect and control new taxa that invade natural areas; and (iv) the polluter-pays principle, so that if a taxon becomes an environmental weed, industry pays for its management. There is mounting pressure to increase livestock production. With foresight and planning, growth in agriculture can be achieved sustainably provided that the scope of SI expands to encompass environmental weed risks.

The Invasive Species Risk Assessment and Prediction System Based on GIS

With the international economic and trade exchanges, biological invasion has become an important factor in the threat of biological diversity and ecological environment. In order to prevent and control exotic species invasion, using of GIS-based geospatial technology to the potential distribution of invasive species risk assessment can provide the basis for ecological management of invasive alien species better, thus reducing the economic losses due to invasive alien species caused to our country. To this point, the study had done a secondary development based on ArcGIS Engine component. It used niche model to analysis and study potential suitable distribution of alien pests in China, conduct a risk assessment to them. The receiver operating characteristic curve was applied to access the prediction accuracy Analyzed the impact of the distribution of invasive alien species` main environmental variables. It provided a theoretical basis for ecological management of invasive alien species.

A simple, rapid methodology for developing invasive species watch lists

Biosecurity schemes aim to prevent the introduction of species with a high invasion potential, without unduly restricting personal freedom and commercial activities. But invasive species risk assessments are time consuming, data intensive and expensive. Consequently, resource poor nations cannot implement these schemes. Here we develop a method for creating watch lists using the consistent predictors of invasion success—history of invasion, environmental suitability, and propagule pressure (measured respectively using the Global Invasive Species Database (GISD), environmental modelling, and tourism and trade data). We tested the approach for South Africa, at a national level for various taxa and at a provincial level for plants. Of 884 alien species listed in the GISD, 400 were potential invaders, with most occurring in high risk regions. When alien species in South Africa were evaluated there were many false-negatives (sensitivity of 32% for terrestrial and 40% for marine species), because the GISD is not comprehensive, but few false positives (specificity of 91% for terrestrial and 89% for marine species). The methodology was easy to apply at different political levels, but we found substantial overlaps between the national and provincial watch lists of plants. This simple technique is rapid, easily repeatable, flexible, transparent, works across taxa, and does not require substantial financial or scientific input. It can be used in any region of the world and at various political levels as an initial assessment of key threats. As such it may be an important step in developing biosecurity schemes for resource poor regions.

Minimizing Risks of Invasive Alien Plant Species in Tropical Production Forest Management

Timber production is the most pervasive human impact on tropical forests, but studies of logging impacts have largely focused on timber species and vertebrates. This review focuses on the risk from invasive alien plant species, which has been frequently neglected in production forest management in the tropics. Our literature search resulted in 114 publications with relevant information, including books, book chapters, reports and papers. Examples of both invasions by aliens into tropical production forests and plantation forests as sources of invasions are presented. We discuss species traits and processes affecting spread and invasion, and silvicultural practices that favor invasions. We also highlight potential impacts of invasive plant species and discuss options for managing them in production forests. We suggest that future forestry practices need to reduce the risks of plant invasions by conducting surveillance for invasive species; minimizing canopy opening during harvesting; encouraging rapid canopy closure in plantations; minimizing the width of access roads; and ensuring that vehicles and other equipment are not transporting seeds of invasive species. Potential invasive species should not be planted within dispersal range of production forests. In invasive species management, forewarned is forearmed.

Explaining the rank order of invasive plants by stakeholder groups

Debates surrounding the use of policies to avoid further spread of invasive species highlight the need to establish priorities in public resource allocations. We explore the consistency or discrepancy among stakeholder groups involved in the risk and control management of invasive species to identify the extent to which different factors influence stakeholder choices of major relevant plant invaders. Based on stakeholder ranking of invasive plants, we explore the reasons behind stakeholders' support for policy management. Data were collected in Galicia, Spain. A national catalogue of prohibited entry and trade of invasive species has been recently approved. We estimate a rank ordered logit model using information from semi-structured interviews conducted with respondents from four stakeholder groups: public administration sector, ornamental sector, research and social groups. The characteristics of plant invaders that provoke stakeholders to rank a species more highly are wide distribution of plant invaders, existence of public control programmes, use and sale of species in the ornamental sector and media coverage. The influence these aspects have in the selection of top-ranked invaders varies across different stakeholder groups and with stakeholders' level of knowledge, awareness and attitudes towards different potential policy measures. A small group of invaders are perceived as top rated by all stakeholder groups.

Risk aversion and adaptive management: Insights from a multi-armed bandit model of invasive species risk

This article explores adaptive management (AM) for decision-making under environmental uncertainty. In the context of targeting invasive species inspections of agricultural imports, I find that risk aversion increases the relative value of AM and can increase the rate of exploratory action. While calls for AM in natural resource management are common, many analyses have identified modest gains from this approach. I analytically and numerically examine the distribution of outcomes from AM under risk neutrality and risk aversion. The inspection decision is framed as a multi-armed bandit problem and solved using the Lagrangian decomposition method. Results show that even when expected gains are modest, asymmetry in the distribution of outcomes has important implications. Notably, AM can serve to buffer against large losses, even if the most likely outcome is a small loss.

Variability in Compensatory Ability and Relative Invasive Potential in Ornamental Cleomes

Tolerance to herbivory is an important trait influencing invasive potential of exotic plant species. However, though many invasive plant species have been introduced as ornamentals, tolerance to herbivory has not been evaluated among cultivars of ornamental crops to assess relative invasive potential. A greenhouse study was performed to compare tolerance to simulated herbivory in five Cleome cultivars (Sparkler White, Sparkler Rose, Queen White, Queen Rose and Solo). The herbivory treatments simulated deer, rabbit and invertebrate herbivore damage by clipping the main stem, removing leaves, or punching out leaf pieces, respectively. Data were collected for flowering time, vegetative and reproductive biomass, ratio of reproductive: vegetative biomass (reproductive effort), number of flowering and vegetative shoots, ratio of number of flowering: total shoots (reproductive allocation), and number of ovules/flower. Cultivars showed different norms of tolerance ranging from under compensation to overcompensation with differences among cultivars within series. The response differed among patterns of simulated herbivory with stem clipping having the most dramatic and negative effect on plant growth and reproduction relative to whole leaf and partial leaf defoliation. The response also varied depending on cultivar and trait. For example, compensation in vegetative, but not reproductive, biomass, was observed across most cultivars after clipping. Significant interactions of herbivory treatment x cultivar were detected for total shoot number and the ratio of flowering: total shoots in the stem clipping experiment, indicating shifts in relative cultivar ranks. The implication of variation in tolerance to herbivory is discussed in relation to ornamental crop development and invasive species risk assessment.

Visualising continuous intra-landscape isolation with uncertainty using least-cost modelling based catchment areas: common brushtail possums in the Auckland isthmus

Invasive species have become a major stressor in many ecosystems. Therefore, public-policy decision-makers desire ecologically informed risk assessments that characterise the likelihood and severity of potential adverse effects from invasive species. These risk assessments often take the form of maps, but risk maps have generally ignored uncertainty and avoided incorporating processes such as the risk of spread. One method that has been proposed to map risk of spread is a least-cost modelling based catchment area approach. In summary, using a raster cost-surface that represents the difficulty associated with traversing different parts of a landscape, least-cost catchments are calculated for all cells in a landscape, and the catchments’ areas are then visualised as a map of intra-landscape isolation. However, there are challenges with parameterising least-cost modelling in an ecological context which means it is particularly important that any estimates of isolation are coupled with associated estimates of uncertainty. Using an example of the common brushtail possum (Trichosurus vulpecula) on the Auckland isthmus (New Zealand), we provide a demonstration of how the least-cost modelling based catchment area approach to mapping isolation can be applied to estimate isolation with uncertainty. We use a Python geoprocessing and geovisualisation framework to quantify isolation for four least-cost modelling based possum dispersal scenarios in order to produce a bivariate colour-by-alpha map that simultaneously visualises predicted isolation with associated uncertainty. The bivariate colour-by-alpha map clearly reinforces the need to consider uncertainty when producing catchment area isolation maps. While the overall pattern in isolation was a relatively simple function of the different isolation maps, the associated uncertainty had a complex spatial structure that would be difficult to understand without representing it explicitly. Providing policy decision-makers with bivariate maps that simultaneously include isolation and uncertainty will help support more robust invasive species risk assessments.

Global approaches to addressing biofuel‐related invasive species risks and incorporation into U.S. laws and policies

Biofuels are being pursued for their potential greenhouse gas (GHG) emissions benefits, among other reasons. In order to maximize productivity, avoid food–fuel conflicts, and minimize GHG emissions, many advanced biofuel feedstock crops, such as those desired by the aviation community, are under consideration based on traits, such as high biomass and/or seed production, tolerance of marginal cultivation conditions, and short generation times, that may also be predictors of potential invasiveness risk. Biofuel‐related invasion risks can be mitigated through careful feedstock crop selection and cultivation techniques developed from the invasion science literature. Existing voluntary best practices and some state and federal regulatory requirements in the United States recommend and/or require the use of such risk mitigation strategies. However, other policies and programs allow or provide incentives for biofuel production without conditions requiring the use of these strategies. We have synthesized information on the scientific knowledge of invasive species predictors and their use (or absence) in voluntary codes and U.S. regulatory frameworks and incentive programs. We highlight the existing tools and approaches for assessing invasion risk and avoiding the introduction and spread of invasive species as a result of biofuel feedstock cultivation. A well‐coordinated combination of species restrictions, biosecurity requirements, and incentives for selection of less risky biofuel crops may effectively balance the desire for increased biofuel production while minimizing invasion risk.

Spatial analysis facilitates invasive species risk assessment

Regional scale quantitative invasion risk analyses are needed to allow early detection and rapid response in order to effectively control the spread of exotic invasion. Most of the current invasion risk analyses are qualitative and ad hoc based. In this study, we used a spatial statistics based framework to assess the invasion risks of hemlock woolly adelgid (Adelges tsugae) with the following major steps: (1) invasion probability was first predicted by two widely used spatial statistics tools, maximum entropy (Maxent) and Mahalanobis distance (MD), based on known adelgid infestation locations and a set of environmental and anthropogenic related factors; (2) an ensemble of the above two models and a multi-threshold approach were employed to reduce prediction uncertainties; and (3) a spatial hotspot analysis were applied to enhance invasion prevention and management decision making. Among the factors investigated, variables representing corridors (e.g., trails and railroads) that are inadvertently spreading adelgid were important for the prediction of adelgid invasion. Large portion of the hemlock forests in the study area had a high adelgid invasion probability. The hotspot analysis based on the ensemble model showed three major clustered areas with high adelgid infestation probability. Our study demonstrated the feasibility of regional-scale quantitative invasion risk assessment with the application of a spatial statistics based framework, which can be used for effective and proactive invasion prevention and management.

Toxicity of a Traditional Molluscicide to Asian Clam Veligers

Abstract Aquaculture and hatchery industries are in need of effective control methods to reduce the risk of spreading aquatic invasive species, such as the Asian clam Corbicula fluminea, through aquaculture and hatchery activities. The planktonic nature of Asian clam veligers enables this life stage to enter water-based infrastructure undetected, including hatchery trucks used to stock fish. Once in hatchery trucks, veligers can disperse overland and establish in previously uninvaded habitats. As a result, there is a need to develop techniques that result in veliger mortality but do not harm fish. In September 2012, we conducted laboratory trials to determine if a molluscicide (750 mg/L potassium chloride and 25 mg/L formalin) commonly used to kill zebra mussel (Dreissena polymorpha) veligers in hatchery trucks can also effectively kill Asian clam veligers. We exposed Asian clam veligers to this molluscicide for 1, 3, and 5 h in each of two water types: deionized water and filtered lake water. We found <20% mortality at the 1-h exposure period and 100% mortality at both the 3-h and 5-h exposure periods, regardless of water type. This laboratory study represents an important step toward reducing the spread of Asian clams by aquaculture facilities.

A street tree survey for Canadian communities: Protocol and early results

This paper describes early results from a survey that was developed to allow rapid, yet reasonably accurate, estimates of street tree composition in Canadian communities. To carry out surveys, participants walk (or drive) a number of 0.5-km routes, identifying all trees within 10 m of the road edge. The number of survey routes in each community was determined such that tree densities could be estimated within reasonable error bounds: ±5 trees/km for common species and ±1 tree/km for uncommon species. Information from this initiative has already supported invasive species risk assessments and urban forest management activities. Full details are available at http://gmaps.nrcan.gc.ca/uts/index.php .

Understanding trade pathways to target biosecurity surveillance

Increasing trends in global trade make it extremely difficult to prevent the entry of all potential invasive species (IS). Establishing early detection strategies thus becomes an important part of the continuum used to reduce the introduction of invasive species. One part necessary to ensure the success of these strategies is the determination of priority survey areas based on invasion pressure. We used a pathway-centred conceptual model of pest invasion to address these questions: what role does global trade play in invasion pressure of plant ecosystems and how could an understanding of this role be used to enhance early detection strategies? We concluded that the relative level of invasion pressure for destination ecosystems can be influenced by the intensity of pathway usage (import volume and frequency), the number and type of pathways with a similar destination, and the number of different ecological regions that serve as the source for imports to the same destination. As these factors increase, pressure typically intensifies because of increasing a) propagule pressure, b) likelihood of transporting pests with higher intrinsic invasion potential, and c) likelihood of transporting pests into ecosystems with higher invasibility. We used maritime containerized imports of live plants into the contiguous U.S. as a case study to illustrate the practical implications of the model to determine hotspot areas of relative invasion pressure for agricultural and forest ecosystems (two ecosystems with high potential invasibility). Our results illustrated the importance of how a pathway-centred model could be used to highlight potential target areas for early detection strategies for IS. Many of the hotspots in agricultural and forest ecosystems were within major U.S. metropolitan areas. Invasion ecologists can utilize pathway-centred conceptual models to a) better understand the role of human-mediated pathways in pest establishment, b) enhance current methodologies for IS risk analysis, and c) develop strategies for IS early detection-rapid response programs.

Prioritizing the risk of plant pests by clustering methods; self-organising maps, k-means and hierarchical clustering

For greater preparedness, pest risk assessors are required to prioritise long lists of pest species with potential to establish and cause significant impact in an endangered area. Such prioritization is often qualitative, subjective, and sometimes biased, relying mostly on expert and stakeholder consultation. In recent years, cluster based analyses have been used to investigate regional pest species assemblages or pest profiles to indicate the risk of new organism establishment. Such an approach is based on the premise that the co-occurrence of well-known global invasive pest species in a region is not random, and that the pest species profile or assemblage integrates complex functional relationships that are difficult to tease apart. In other words, the assemblage can help identify and prioritise species that pose a threat in a target region. A computational intelligence method called a Kohonen self-organizing map (SOM), a type of artificial neural network, was the first clustering method applied to analyse assemblages of invasive pests. The SOM is a well known dimension reduction and visualization method especially useful for high dimensional data that more conventional clustering methods may not analyse suitably. Like all clustering algorithms, the SOM can give details of clusters that identify regions with similar pest assemblages, possible donor and recipient regions. More important, however SOM connection weights that result from the analysis can be used to rank the strength of association of each species within each regional assemblage. Species with high weights that are not already established in the target region are identified as high risk. However, the SOM analysis is only the first step in a process to assess risk to be used alongside or incorporated within other measures. Here we illustrate the application of SOM analyses in a range of contexts in invasive species risk assessment, and discuss other clustering methods such as k-means, hierarchical clustering and the incorporation of the SOM analysis into criteria based approaches to assess pest risk.

Addressing a critique of the TEASI framework for invasive species risk assessment

We address criticism that the Transport, Establishment, Abundance, Spread, Impact (TEASI) framework does not facilitate objective mapping of risk assessment methods nor defines best practice. We explain why TEASI is appropriate for mapping, despite inherent challenges, and how TEASI offers considerations for best practices, rather than suggesting one best practice.

Mapping ecological risks with a portfolio‐based technique: incorporating uncertainty and decision‐making preferences

AbstractAimGeographic mapping of risks is a useful analytical step in ecological risk assessments and in particular, in analyses aimed to estimate risks associated with introductions of invasive organisms. In this paper, we approach invasive species risk mapping as a portfolio allocation problem and apply techniques from decision theory to build an invasion risk map that combines risk and uncertainty in a single map product.LocationCanada.MethodsWe divide the study area into a set of spatial domains and treat each domain as an individual ‘portfolio’ with a unique distribution of the expected impacts of invasion. The risk of invasion is then mapped by finding nested ‘efficient’ portfolio sets that identify the geographic areas exhibiting the worst combinations of the estimated risk of invasion and the uncertainty in that estimate. For Canadian municipalities, we apply the approach to quantify the risk that a given location will receive invasive forest pests with commercial freight transported via the North American road network. We compare risk allocation techniques that employ the concepts of nested mean‐variance (M‐V) frontiers and second‐degree stochastic dominance.ResultsWhile both methods based on M‐V and the stochastic dominance principles identified similar areas of highest risk, they differed in how they demarcated moderate‐risk areas. Furthermore, they address uncertainty in different ways, treating it as a risk premium (in the case of nested M‐V frontiers) or producing risk‐averse delineations (in the case of stochastic dominance).Main conclusionsThe portfolio‐based approach offers a viable strategy for dealing with the typically wide variability in risk estimates caused by a lack of knowledge about a new invader. The methodology also provides a tractable way of incorporating decision‐making preferences into the final risk estimates and thus better aligns risk assessments with particular decision‐making scenarios about the organism of concern.

Closing the Gap between Risk Estimation and Decision Making: Efficient Management of Trade-Related Invasive Species Risk

This paper examines the implications of a binary action, binary outcome decision problem for estimating risk. We use data on the invasiveness of biological imports to develop the first comparison of two classical methods—maximum likelihood and Bayesian—against a third, the recently developed maximum utility (MU) approach. MU estimation uniquely takes advantage of the structure of the decision problem, which depends on a local rather than global fit to the model. Extending methods to account for an endogenously stratified sample, we show that the MU approach is less sensitive to specification error and can offer significant economic gains under model uncertainty.

Optimal Border Policies for Invasive Species Under Asymmetric Information

This paper analyzes the problem faced by a border protection agency if endogenous exporter abatement activities affect invasive species risk, allowing for unobservable differences in abatement cost. We show how the optimal inspection/penalty regime differs from the symmetric information case. Departing from previous literature, we allow for technical assistance, a policy instrument specifically permitted and commonly employed under Article 9 of the World Trade Organization Sanitary and Phytosanitary Agreement. We find the information asymmetry can make it optimal for the importing country to provide technical assistance grants for exporter risk abatement, even if it would otherwise be inefficient. Further, we show that fungibility of technical assistance with inputs in other sectors of the exporting economy affects the qualitative nature of optimal policy. If technical assistance has no outside value in the exporter’s country, optimal policy is characterized by a menu of contracts balancing higher tariffs with lower penalties for being caught with an invasive. If technical assistance can be used in other sectors of the exporter’s economy, it can introduce countervailing incentives making a uniform tariff/penalty combination optimal.

A New Multicriteria Risk Mapping Approach Based on a Multiattribute Frontier Concept

Invasive species risk maps provide broad guidance on where to allocate resources for pest monitoring and regulation, but they often present individual risk components (such as climatic suitability, host abundance, or introduction potential) as independent entities. These independent risk components are integrated using various multicriteria analysis techniques that typically require prior knowledge of the risk components' importance. Such information is often nonexistent for many invasive pests. This study proposes a new approach for building integrated risk maps using the principle of a multiattribute efficient frontier and analyzing the partial order of elements of a risk map as distributed in multidimensional criteria space. The integrated risks are estimated as subsequent multiattribute frontiers in dimensions of individual risk criteria. We demonstrate the approach with the example of Agrilus biguttatus Fabricius, a high-risk pest that may threaten North American oak forests in the near future. Drawing on U.S. and Canadian data, we compare the performance of the multiattribute ranking against a multicriteria linear weighted averaging technique in the presence of uncertainties, using the concept of robustness from info-gap decision theory. The results show major geographic hotspots where the consideration of tradeoffs between multiple risk components changes integrated risk rankings. Both methods delineate similar geographical regions of high and low risks. Overall, aggregation based on a delineation of multiattribute efficient frontiers can be a useful tool to prioritize risks for anticipated invasive pests, which usually have an extremely poor prior knowledge base.

Invasive Plant Species in the National Parks of Vietnam

The impact of invasive plant species in national parks and forests in Vietnam is undocumented and management plans have yet to be developed. Ten national parks, ranging from uncut to degraded forests located throughout Vietnam, were surveyed for invasive plant species. Transects were set up along roads, trails where local people access park areas, and also tracks through natural forest. Of 134 exotic weeds, 25 were classified as invasive species and the number of invasive species ranged from 8 to 15 per park. An assessment of the risk of invasive species was made for three national parks based on an invasive species assessment protocol. Examples of highly invasive species were Chromolaena odorata and Mimosa diplotricha in Cat Ba National Park (island evergreen secondary forest over limestone); Mimosa pigra, Panicum repens and Eichhornia crassipes in Tram Chim National Park (lowland wetland forest dominated by melaleuca); and C. odorata, Mikania micrantha and M. diplotricha in Son Tra Nature Conservation area (peninsula evergreen secondary forest). Strategies to monitor and manage invasive weeds in forests and national parks in Vietnam are outlined.