Detection capacity,information gaps and the design of surveillance programs for invasive forest pests

Integrated pest risk maps and their underlying assessments provide broad guidance for establishing surveillance programs for invasive species, but they rarely account for knowledge gaps regarding the pest of interest or how these can be reduced. In this study we demonstrate how the somewhat competing notions of robustness to uncertainty and potential knowledge gains could be used in prioritizing large-scale surveillance activities. We illustrate this approach with the example of an invasive pest recently detected in North America, Sirex noctilio Fabricius. First, we formulate existing knowledge about the pest into a stochastic model and use the model to estimate the expected utility of surveillance efforts across the landscape. The expected utility accounts for the distribution, abundance and susceptibility of the host resource as well as the value of timely S. noctilio detections. Next, we make use of the info-gap decision theory framework to explore two alternative pest surveillance strategies. The first strategy aims for timely, certain detections and attempts to maximize the robustness to uncertainty about S. noctilio behavior; the second strategy aims to maximize the potential knowledge gain about the pest via unanticipated (i.e., opportune) detections. The results include a set of spatial outputs for each strategy that can be used independently to prioritize surveillance efforts. However, we demonstrate an alternative approach in which these outputs are combined via the Pareto ranking technique into a single priority map that outlines the survey regions with the best trade-offs between both surveillance strategies.     

Info-Gap Decision Theory for Assessing the Management of Catchments for Timber Production and Urban Water Supply

While previous studies have examined how forest management is influenced by the risk of fire, they rely on probabilistic estimates of the occurrence and impacts of fire. However, nonprobabilistic approaches are required for assessing the importance of fire risk when data are poor but risks are appreciable. We explore impacts of fire risk on forest management using as a case study a water catchment in the Australian Capital Territory (ACT) (southeastern Australia). In this forested area, urban water supply and timber yields from exotic plantations are potential joint but also competing land uses. Our analyses were stimulated by extensive wildfires in early 2003 that burned much of the existing exotic pine plantation estate in the water catchment and the resulting need to explore the relative economic benefits of revegetating the catchment with exotic plantations or native vegetation. The current mean fire interval in the ACT is approximately 40 years, making the establishment of a pine plantation economically marginal at a 4% discount rate. However, the relative impact on water yield of revegetation with native species and pines is very uncertain, as is the risk of fire under climate change. We use info-gap decision theory to account for these nonprobabilistic sources of uncertainty, demonstrating that the decision that is most robust to uncertainty is highly sensitive to the cost of native revegetation. If costs of native revegetation are sufficiently small, this option is more robust to uncertainty than revegetation with a commercial pine plantation.     

A Risk-Based Predictive Tool to Prevent Accidental Introductions of Nonindigenous Marine Species

Preventing the introduction of nonindigenous species (NIS) is the most efficient way to avoid the costs and impacts of biological invasions. The transport of fouling species on ship hulls is an important vector for the introduction of marine NIS. We use quantitative risk screening techniques to develop a predictive tool of the abundance and variety of organisms being transported by ocean-going yachts. We developed and calibrated an ordinal rank scale of the abundance of fouling assemblages on the hulls of international yacht hulls arriving in New Zealand. Fouling ranks were allocated to 783 international yachts that arrived in New Zealand between 2002 and 2004. Classification tree analysis was used to identify relationships between the fouling ranks and predictor variables that described the maintenance and travel history of the yachts. The fouling ranks provided reliable indications of the actual abundance and variety of fouling assemblages on the yachts and identified most (60%) yachts that had fouling on their hulls. However, classification tree models explained comparatively little of the variation in the distribution of fouling ranks (22.1%), had high misclassification rates (∼43%), and low predictive power. In agreement with other studies, the best model selected the age of the toxic antifouling paint on yacht hulls as the principal risk factor for hull fouling. Our study shows that the transport probability of fouling organisms is the result of a complex suite of interacting factors and that large sample sizes will be needed for calibration of robust risk models.     

What Lies Beneath? An Evaluation of Rapid Assessment Tools for Management of Hull Fouling

Despite an increased understanding of marine invasions, non-indigenous species (NIS) continue to be redistributed at both global and regional scales. Since prevention is an important element of NIS programs, monitoring vectors responsible for NIS introductions and spread, such as hull fouling, has become a priority and methods should be selected carefully to balance accuracy, time, and cost. Two common fouling assessment tools for the marine recreational boating vector were evaluated for accuracy using a traditional underwater SCUBA survey in coastal British Columbia: a dockside level of fouling assessment and a behavioral questionnaire model. Results showed that although rapid, dockside assessments did not provide an accurate assessment of fouling present below the surface, at least not in this region. In contrast, a questionnaire-based model using four easily obtained variables (boat type, age of antifouling paint, storage type, and occurrence of long distance trips) reliably identified boats carrying macrofouling species, a proxy for risk of NIS transport. Once validated, this fouling model tool could be applied in border inspection or quarantine situations where decisions must be made quickly. Further development and refinement of rapid assessment tools would improve our ability to prevent new introductions and manage spread of existing invasive species.     

Price-based vs. quantity-based environmental regulation under Knightian uncertainty: an info-gap robust satisficing perspective

Conventional wisdom among environmental economists is that the relative slopes of the marginal social benefit and marginal social cost functions determine whether a price-based or quantity-based environmental regulation leads to higher expected social welfare. We revisit the choice between price-based vs. quantity-based environmental regulation under Knightian uncertainty; that is, when uncertainty cannot be modeled with known moments of probability distributions. Under these circumstances, the policy objective cannot be to maximize the expected net benefits of emissions control. Instead, we evaluate an emissions tax and an aggregate abatement standard in terms of maximizing the range of uncertainty under which the welfare loss from error in the estimates of the marginal benefits and costs of emissions control can be limited. The main result of our work is that the same criterion involving the relative slopes of the marginal benefit and cost functions determines whether price-based or quantity-based control is more robust to unstructured uncertainty. Hence, not only does the relative slopes criterion lead to the policy that maximizes the expected net benefits of control under structured uncertainty, it also leads to the policy that maximizes robustness to unstructured uncertainty.     

Ecological Impact Assessment in Data-Poor Systems: A Case Study on Metapopulation Persistence

Legislation on the protection of biodiversity (e.g., European Union Habitat and Bird Directives) increasingly requires ecological impact assessment of human activities. However, knowledge and understanding of relevant ecological processes and species responses to different types of impact are often incomplete. In this paper we demonstrate with a case study how impact assessment can be carried out for situations where data are scarce but some expert knowledge is available. The case study involves two amphibian species, the great crested newt (Triturus cristatus) and the natterjack toad (Bufo calamita) in the nature reserve the Meinweg in the Netherlands, for which plans are being developed to reopen an old railway track called the Iron Rhine. We assess the effects of this railway track and its proposed alternatives (scenarios) on the metapopulation extinction time and the occupancy times of the patches for both species using a discrete-time stochastic metapopulation model. We quantify the model parameters using expert knowledge and extrapolated data. Because of our uncertainty about these parameter values, we perform a Monte Carlo uncertainty analysis. This yields an estimate of the probability distribution of the model predictions and insight into the contribution of each distinguished source of uncertainty to this probability distribution. We show that with a simple metapopulation model and an extensive uncertainty analysis it is possible to detect the least harmful scenario. The ranking of the different scenarios is consistent. Thus, uncertainty analysis can enhance the role of ecological impact assessment in decision making by making explicit to what extent incomplete knowledge affects predictions.     

GROUND WATER SOLUTE TRANSPORT,OPTIMAL REMEDIATION PLANNING,AND DECISION MAKING UNDER UNCERTAINTY1

ABSTRACT: A groundwater quality modeling advisory system has been developed for the U.S. Air Force for use in investigating remediation alternatives for the cleanup of subsurface contamination. The system is capable of accounting for uncertainty, not only in the prediction of solute transport but also in the optimization of the remediation scheme through chance constraints. The system guides users in the selection of appropriate transport models through an algorithm independently tested with machine learning codes. An application to Hill Air Force Base, Utah, is presented for which different pump-and-treat strategies are considered: the results are evaluated in terms of the cumulative distribution of the contaminant concentration for each case and the tradeoff relationship between the cost of remediation and the probability that the remediation strategy exceeds an established maximum allowable contaminant concentration.     

Socioeconomic Factors Affecting Local Support for Black Bear Recovery Strategies

There is global interest in recovering locally extirpated carnivore species. Successful efforts to recover Louisiana black bear in Louisiana have prompted interest in recovery throughout the species’ historical range. We evaluated support for three potential black bear recovery strategies prior to public release of a black bear conservation and management plan for eastern Texas, United States. Data were collected from 1,006 residents living in proximity to potential recovery locations, particularly Big Thicket National Preserve. In addition to traditional logistic regression analysis, we used conditional probability analysis to statistically and visually evaluate probabilities of public support for potential black bear recovery strategies based on socioeconomic characteristics. Allowing black bears to repopulate the region on their own (i.e., without active reintroduction) was the recovery strategy with the greatest probability of acceptance. Recovery strategy acceptance was influenced by many socioeconomic factors. Older and long-time local residents were most likely to want to exclude black bears from the area. Concern about the problems that black bears may cause was the only variable significantly related to support or non-support across all strategies. Lack of personal knowledge about black bears was the most frequent reason for uncertainty about preferred strategy. In order to reduce local uncertainty about possible recovery strategies, we suggest that wildlife managers focus outreach efforts on providing local residents with general information about black bears, as well as information pertinent to minimizing the potential for human–black bear conflict.     

A harvest failure approach to assess the threat from an invasive species

We present the idea of using potential infringements on annual allowable harvest targets as an approach to estimate threats from invasive species to the forest products sector. The approach uses present-day harvest levels as a reference level to estimate when and where the impact of a nonnative forest pest could become economically damaging. We use a generic model that simulates spread and damage by nonnative invasive species, basic harvest and forest growth through time. The concept is illustrated with a case study of a new nonnative invasive pest, Sirex noctilio Fabricius on pine resources in eastern Canada. Impacts of invasion on wood supply, in particular, the point at which present-day harvest levels are not attainable, were identified for 77 non-overlapping geographical regions that delimit the primary wood supply areas around large mills and wood processing facilities in eastern Canada. The results identify the minimum area of a pest outbreak that could trigger harvest shortages (approximately 12.5–14 M ha of pine forests in Ontario and Quebec). Beyond this level, the amount of host resource available for harvesting in any given year declines rapidly. The failure to sustain broad-scale harvest targets may be an attractive and intuitive indicator for policy makers and regulators interested in developing control and “slow-the-spread” programs for non-native forest pests.     

Simulated climate adaptation in stormwater systems: evaluating the efficiency of adaptation strategies

Adaptations in infrastructure may be necessitated by changes in temperature and precipitation patterns to avoid losses and maintain expected levels of service. A roster of adaptation strategies has emerged in the climate change literature, especially with regard to timing: anticipatory, concurrent, or reactive. Significant progress has been made in studying climate change adaptation decision making that incorporates uncertainty, but less work has examined how strategies interact with existing infrastructure characteristics to influence adaptability. We use a virtual testbed of highway drainage crossings configured with a selection of actual culvert emplacements in Colorado, USA, to examine the effect of adaptation strategy and culvert characteristics on cost efficiency and service level under varying rates of climate change. A meta-model approach with multinomial regression is used to compare the value of better climate change predictions with better knowledge of existing crossing characteristics. We find that, for a distributed system of infrastructural units like culverts, knowing more about existing characteristics can improve the efficacy of adaptation strategies more than better projections of climate change. Transportation departments choosing climate adaptation strategies often lack detailed data on culverts, and gathering that data could improve the efficiency of adaptation despite climate uncertainty.     

Uncertainty Analysis In Dissolved Oxygen Modeling in Streams

Uncertainty analysis in surface water quality modeling is an important issue. This paper presents a method based on the first-order reliability method (FORM) to assess the exceedance probability of a target dissolved oxygen concentration in a stream, using a Streeter–Phelps prototype model. Basic uncertainty in the input parameters is considered by representing them as random variables with prescribed probability distributions. Results obtained from FORM analysis compared well with those of the Monte Carlo simulation method. The analysis also presents the stochastic sensitivity of the probabilistic outcome in the form of uncertainty importance factors, and shows how they change with changing simulation time. Furthermore, a parametric sensitivity analysis was conducted to show the effect of selection of different probability distribution functions for the three most important parameters on the design point, exceedance probability, and importance factors. Note: This version was published online in June 2005 with the cover date of August 2004.     

Robust detection protocols for uncertain introductions of invasive species

Two important features of real-world port inspections of shipping containers for invasive species are the general absence of underlying economic considerations and the climate of severe uncertainty that surrounds the likelihood of invasive species introductions. In this article we propose and illustrate a method for determining inspection protocols that address both of these issues. We seek inspection protocols that are robust in the sense that they maximize the range of uncertainty over which the expected loss from the introduction of an invasive species plus the costs of inspections do not exceed some critical value. These inspection strategies are practical and provide ready alternatives to existing protocols.     

Science and Management of the Introduced Seagrass Zostera japonica in North America

Healthy seagrass is considered a prime indicator of estuarine ecosystem function. On the Pacific coast of North America, at least two congeners of Zostera occur: native Zostera marina, and introduced, Zostera japonica. Z. japonica is considered “invasive” and therefore, ecologically and economically harmful by some, while others consider it benign or perhaps beneficial. Z. japonica does not appear on the Federal or the Oregon invasive species or noxious weed lists. However, the State of California lists it as both an invasive and noxious weed; Washington State recently listed it as a noxious weed. We describe the management dynamics in North America with respect to these congener species and highlight the science and policies behind these decisions. In recent years, management strategies at the state level have ranged from historical protection of Z. japonica as a priority habitat in Washington to eradication in California. Oregon and British Columbia, Canada appear to have no specific policies with regard to Z. japonica. This fractured management approach contradicts efforts to conserve and protect seagrass in other regions of the US and around the world. Science must play a critical role in the assessment of Z. japonica ecology and the immediate and long-term effects of management actions. The information and recommendations provided here can serve as a basis for providing scientific data in order to develop better informed management decisions and aid in defining a uniform management strategy for Z. japonica.     

Optimal renewable resource management in the presence of endogenous risk of invasion

In this paper we examine the optimal management of a renewable resource that is at risk from alien species invasion. The objective of this paper is to derive implications for optimal management of a resource when options exist for both preventing the arrival of an invasive species and mitigating the impact of that arrival. Uncertainty about the timing and nature of an invasion can have important implications for the choice of management strategy, and a key feature of this analysis is an explicit treatment of that uncertainty.     

Assessing and communicating data quality in policy-relevant research

The quality of scientific information in policy-relevant fields of research is difficult to assess, and quality control in these important areas is correspondingly difficult to maintain. Frequently there are insufficient high-quality measurements for the presentation of the statistical uncertainty in the numerical estimates that are crucial to policy decisions. We propose and develop a grading system for numerical estimates that can deal with the full range of data quality—from statistically valid estimates to informed guesses. By analyzing the underlying quality of numerical estimates, summarized as spread and grade, we are able to provide simple rules whereby input data can be coded for quality, and these codings carried through arithmetical calculations for assessing the quality of model results. For this we use the NUSAP (numeral, unit, spread, assessment, pedigree) notational system. It allows the more quantitative and the more qualitative aspects of data uncertainty to be managed separately. By way of example, we apply the system to an ecosystem valuation study that used several different models and data of widely varying quality to arrive at a single estimate of the economic value of wetlands. The NUSAP approach illustrates the major sources of uncertainty in this study and can guide new research aimed at the improvement of the quality of outputs and the efficiency of the procedures.     

Learning-by-catching: uncertain invasive-species populations and the value of information

This paper develops a model of invasive species control when the species’ population size is unknown. In the face of an uncertain population size, a resource manager's species-control efforts provide two potential benefits: (1) a direct benefit of possibly reducing the population of invasive species, and (2) an indirect benefit of information acquisition (due to learning about the population size, which reduces uncertainty). We provide a methodology that takes into account both of these benefits, and show how optimal management decisions are altered in the presence of the indirect benefit of learning. We then apply this methodology to the case of controlling the Brown Treesnake (Boiga irregularis) on the island of Saipan. We find that the indirect benefit—the value of information to reduce uncertainty—is likely to be quite large.     

A Technicoeconomic Approach for the Selection of a Site Remediation Strategy—Part A: Theory

A technicoeconomic model is developed to select an optimal strategy for the remediation of a contaminated site and to determine the value of this remediation strategy. The model is an extension of actual cost–benefit analysis, with consideration of “irreversible” remediation technology choices, technology effectiveness, and uncertainty on the site's level of contamination. The model considers the possibility of reducing uncertainty by both acquiring more and better information on the level of contamination and by offering the decision-maker the opportunity to reevaluate his decision and switch to a more appropriate technology. It is believed that this model will help decision-makers in the selection of a remediation strategy by presenting all potentially feasible strategies, and how uncertainty on the site's level of contamination affects these strategies.     

Using Risk-Based Analysis and Geographic Information Systems to Assess Flooding Problems in an Urban Watershed in Rhode Island

This article provides an overview of the use of risk-based analysis (RBA) in flood damage assessment, and it illustrates the use of Geographic Information Systems (GIS) in identifying flood-prone areas, which can aid in flood-mitigation planning assistance. We use RBA to calculate expected annual flood damages in an urban watershed in the state of Rhode Island, USA. The method accounts for the uncertainty in the three primary relationships used in computing flood damage: (1) the probability that a given flood will produce a given amount of floodwater, (2) the probability that a given amount of floodwater will reach a certain stage or height, and (3) the probability that a certain stage of floodwater will produce a given amount of damage. A greater than 50% increase in expected annual flood damage is estimated for the future if previous development patterns continue and flood-mitigation measures are not taken. GIS is then used to create a map that shows where and how often floods might occur in the future, which can help (1) identify priority areas for flood-mitigation planning assistance and (2) disseminate information to public officials and other decision-makers.     

Toward Consensus-Based Actions that Balance Invasive Plant Management and Conservation of At-Risk Fauna

Limiting the spread of invasive plants has become a high priority among natural resource managers. Yet in some regions, invasive plants are providing important habitat components to native animals that are at risk of local or regional extirpation. In these situations, removing invasive plants may decrease short-term survival of the at-risk taxa. At the same time, there may be a reluctance to expand invaded habitats to benefit at-risk species because such actions may increase the distribution of invasive plants. Such a dilemma can result in “management paralysis,” where no action is taken either to reduce invasive plants or to expand habitats for at-risk species. A pragmatic solution to this dilemma may be to develop an approach that considers site-specific circumstances. We constructed a “discussion tree” as a means of initiating conversations among various stakeholders involved with managing habitats in the northeastern USA to benefit several at-risk taxa, including New England cottontails (Sylvilagus transitionalis). Major components of this approach include recognition that expanding some invaded habitats may be essential to prevent extirpation of at-risk species, and the effective control of invasive plants is dependent on knowledge of the status of invasives on managed lands and within the surrounding landscape. By acknowledging that management of invasive plants is a complex issue without a single solution, we may be successful in limiting their spread while still addressing critical habitat needs.     

Integrating drivers influencing the detection of plant pests carried in the international cut flower trade

This paper analyses the cut flower market as an example of an invasion pathway along which species of non-indigenous plant pests can travel to reach new areas. The paper examines the probability of pest detection by assessing information on pest detection and detection effort associated with the import of cut flowers. We test the link between the probability of plant pest arrivals, as a precursor to potential invasion, and volume of traded flowers using count data regression models. The analysis is applied to the UK import of specific genera of cut flowers from Kenya between 1996 and 2004.There is a link between pest detection and the Genus of cut flower imported. Hence, pest detection efforts should focus on identifying and targeting those imported plants with a high risk of carrying pest species. For most of the plants studied, efforts allocated to inspection have a significant influence on the probability of pest detection. However, by better targeting inspection efforts, it is shown that plant inspection effort could be reduced without increasing the risk of pest entry. Similarly, for most of the plants analysed, an increase in volume traded will not necessarily lead to an increase in the number of pests entering the UK. For some species, such as Carthamus and Veronica, the volume of flowers traded has a significant and positive impact on the likelihood of pest detection. We conclude that analysis at the rank of plant Genus is important both to understand the effectiveness of plant pest detection efforts and consequently to manage the risk of introduction of non-indigenous species.