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.     

Rapid Assessment of Risks to a Mobile Marine Mammal in an Ecosystem-Scale Marine Protected Area

Abstract:  Ecosystem-scale networks of marine protected areas (MPAs) are important conservation tools, but their effectiveness is difficult to quantify in a time frame appropriate to species conservation because of uncertainties in the data available. The dugong ( Dugong dugon ) is a mobile marine species that occurs in shallow inshore waters of an ecosystem-scale network of MPAs (the Great Barrier Reef World Heritage Area [GBRWHA]). We developed a rapid approach to assess risk to dugongs in the region and evaluate options to ameliorate that risk. We used expert opinion and a Delphi technique to identify and rank 5 human factors with the potential to adversely affect dugongs and their sea grass habitats: netting, indigenous hunting, trawling, vessel traffic, and poor-quality terrestrial runoff. We then quantified and compared the distribution of these factors with a spatially explicit model of dugong distribution. We estimated that approximately 96% of habitat of high conservation value for dugongs in the GBRWHA is at low risk from human activities. Using a sensitivity analysis, we found that to decrease risk, commercial netting or indigenous hunting had to be reduced in remote areas and the effects of vessel traffic, terrestrial runoff, and commercial netting had to be reduced in urban areas. This approach enabled us to compare and rank risks so as to identify the most severe risks and locate specific sites that require further management attention.     

Assessment of uncertainties in expert knowledge, illustrated in fuzzy rule-based models

The coherence between different aspects in the environmental system leads to a demand for comprehensive models of this system to explore the effects of different management alternatives. Fuzzy logic has been suggested as a means to extend the application domain of environmental modelling from physical relations to expert knowledge. In such applications the expert describes the system in terms of fuzzy variables and inference rules. The result of the fuzzy reasoning process is a numerical output value. In such a model, as in any other, the model context, structure, technical aspects, parameters and inputs may contribute uncertainties to the model output. Analysis of these contributions in a simplified model for agriculture suitability shows how important information about the accuracy of the expert knowledge in relation to the other uncertainties can be provided. A method for the extensive assessment of uncertainties in compositional fuzzy rule-based models is proposed, combining the evaluation of model structure, input and parameter uncertainties. In an example model, each of these three appear to have the potential to dominate aggregated uncertainty, supporting the relevance of an ample uncertainty approach.     

Simultaneous estimation of jointly dependent recreation participation function

The purpose of this paper is to develop and estimate a simultaneous model of recreation participation. The logic of the model is that participation in one activity (for example, boating) is influenced by and influences participation in other activities (for example, fishing). For the empirical part of our paper we have used the simultaneous logit model developed by P. Schmidt and R. P. Strauss (Econometrics43, 745–755, 1975). For the application, we have applied the simultaneous logit model to participation in summer recreational activities in Rhode Island. Our results show that simultaneous equation models tend to forecast better, but that the specification bias from excluding the endogenous variables tends to be small.     

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.     

Implementation of a marine reserve has a rapid but short-lived effect on recreational angler use

Changes in human behavior are a precursor to measurable impacts of no-take marine reserves. We investigated changes in recreational fishing site selection in response to the 2005 announcement of enforcement in a marine reserve in the Gulf of California, Mexico. We used a novel data set of daily self-reported boating destinations from emergency rescue logbooks for a recreational angling community from 2000 to 2008. Because the reserve system has no experimental control, we modeled the data two ways to test for robustness to model specification. We tested for changes in human fishing behavior with regression and fit a fleet-level discrete choice model to project a. counterfactual scenario. The counterfactual is the statistically constructed ex post expectation of the human behavior we would have observed if the reserve never existed. We included month and year fixed effects in our models to account for seasonal and interannual fluctuations in fishing behavior and catch rates. We detected a decrease in reserve use compared to the counterfactual, indicating that the reserve rapidly experienced a decrease in visitation. However, the reserve's effect to reduce trips diminished with time. These results indicate that the reserve is unlikely to meet its ecological goals without institutional changes that enhance compliance. This illustrates the value of human use data to understanding the processes underlying marine reserve function. We suggest that managers should consider human use with the same frequency, rigor, and tools as they do fishery stocks. Marine reserves directly affect people, and understanding human behavioral responses to marine reserves is an important step in marine reserve management.     

Nonindigenous biota on artificial structures: could habitat creation facilitate biological invasions?

We identified different distributions of marine nonindigenous species (NIS) and native species on some artificial structures versus natural reefs and using experimental manipulations, revealed some possible causal mechanisms. In well-established subtidal assemblages, numbers of NIS were 1.5–2.5 times greater on pontoons or pilings than on rocky reefs, despite the local species pool of natives being up to 2.5 times greater than that of NIS. Conversely, on reefs and seawalls, numbers of native species were up to three times greater than numbers of NIS. Differential recruitment to different positions and types of surfaces appeared to influence distribution patterns. NIS recruited well to most surfaces, particularly concrete surfaces near the surface of the water, whilst natives occurred infrequently on wooden surfaces. The position of rocky reefs and seawalls close to the shore and to the seabed appeared to make them favourable for the recruitment of natives, but this positioning alone does not hinder the recruitment of NIS. We argue that pontoons and pilings represent beachheads (i.e. entry points for invasion) for many nonindigenous epibiota and so enhance the spread and establishment of NIS in estuaries. Habitat creation in estuaries may, therefore, be a serious threat to native biodiversity. Electronic supplementary material Supplementary material is available in the online version of this article at and is accessible for authorized users.     

An Adaptive‐Management Framework for Optimal Control of Hiking Near Golden Eagle Nests in Denali National Park

Abstract: Unintended effects of recreational activities in protected areas are of growing concern. We used an adaptive‐management framework to develop guidelines for optimally managing hiking activities to maintain desired levels of territory occupancy and reproductive success of Golden Eagles (Aquila chrysaetos) in Denali National Park (Alaska, U.S.A.). The management decision was to restrict human access (hikers) to particular nesting territories to reduce disturbance. The management objective was to minimize restrictions on hikers while maintaining reproductive performance of eagles above some specified level. We based our decision analysis on predictive models of site occupancy of eagles developed using a combination of expert opinion and data collected from 93 eagle territories over 20 years. The best predictive model showed that restricting human access to eagle territories had little effect on occupancy dynamics. However, when considering important sources of uncertainty in the models, including environmental stochasticity, imperfect detection of hares on which eagles prey, and model uncertainty, restricting access of territories to hikers improved eagle reproduction substantially. An adaptive management framework such as ours may help reduce uncertainty of the effects of hiking activities on Golden Eagles.     

Use of structured expert judgment to forecast invasions by bighead and silver carp in Lake Erie

Identifying which nonindigenous species will become invasive and forecasting the damage they will cause is difficult and presents a significant problem for natural resource management. Often, the data or resources necessary for ecological risk assessment are incomplete or absent, leaving environmental decision makers ill equipped to effectively manage valuable natural resources. Structured expert judgment (SEJ) is a mathematical and performance‐based method of eliciting, weighting, and aggregating expert judgments. In contrast to other methods of eliciting and aggregating expert judgments (where, for example, equal weights may be assigned to experts), SEJ weights each expert on the basis of his or her statistical accuracy and informativeness through performance measurement on a set of calibration variables. We used SEJ to forecast impacts of nonindigenous Asian carp (Hypophthalmichthys spp.) in Lake Erie, where it is believed not to be established. Experts quantified Asian carp biomass, production, and consumption and their impact on 4 fish species if Asian carp were to become established. According to experts, in Lake Erie Asian carp have the potential to achieve biomass levels that are similar to the sum of biomasses for several fishes that are harvested commercially or recreationally. However, the impact of Asian carp on the biomass of these fishes was estimated by experts to be small, relative to long term average biomasses, with little uncertainty. Impacts of Asian carp in tributaries and on recreational activities, water quality, or other species were not addressed. SEJ can be used to quantify key uncertainties of invasion biology and also provide a decision‐support tool when the necessary information for natural resource management and policy is not available. El Uso de Juicio Experto Estructurado para Predecir Invasiones de Carpas Asiáticas en el Lago Erie     

Uncertainty in invasive alien species listing

Lists of invasive alien species (IAS) are essential for preventing, controlling, and reporting on the state of biological invasions. However, these lists suffer from a range of errors, with serious consequences for their use in science, policy, and management. Here we (1) collated and classified errors in IAS listing using a taxonomy of uncertainty; and (2) estimated the size of these errors using data from a completed listing exercise, with the purpose of better understanding, communicating, and dealing with them. Ten errors were identified. Most result from a lack of knowledge or measurement error (epistemic uncertainty), although two were a result of context dependence and vagueness (linguistic uncertainty). Estimates of the size of the effects of these errors were substantial in a number of cases and unknown in others. Most errors, and those with the largest estimated effect, result in underestimates of IAS numbers. However, there are a number of errors where the size and direction of the effect remains poorly understood. The effect of differences in opinion between specialists is potentially large, particularly for data-poor taxa and regions, and does not have a clearly directional or consistent effect on the size and composition of IAS lists. Five tactics emerged as important for reducing uncertainty in IAS lists, and while uncertainty will never be removed entirely, these approaches will significantly improve the transparency, repeatability, and comparability of IAS lists. Understanding the errors and uncertainties that occur during the process of listing invasive species, as well as the potential size and nature of their effects on IAS lists, is key to improving the value of these lists for governments, management agencies, and conservationists. Such understanding is increasingly important given positive trends in biological invasion and the associated risks to biodiversity and biosecurity.     

Incorporating Climate and Ocean Change into Extinction Risk Assessments for 82 Coral Species

Many marine invertebrate species facing potential extinction have uncertain taxonomies and poorly known demographic and ecological traits. Uncertainties are compounded when potential extinction drivers are climate and ocean changes whose effects on even widespread and abundant species are only partially understood. The U.S. Endangered Species Act mandates conservation management decisions founded on the extinction risk to species based on the best available science at the time of consideration—requiring prompt action rather than awaiting better information. We developed an expert‐opinion threat‐based approach that entails a structured voting system to assess extinction risk from climate and ocean changes and other threats to 82 coral species for which population status and threat response information was limited. Such methods are urgently needed because constrained budgets and manpower will continue to hinder the availability of desired data for many potentially vulnerable marine species. Significant species‐specific information gaps and uncertainties precluded quantitative assessments of habitat loss or population declines and necessitated increased reliance on demographic characteristics and threat vulnerabilities at genus or family levels. Adapting some methods (e.g., a structured voting system) used during other assessments and developing some new approaches (e.g., integrated assessment of threats and demographic characteristics), we rated the importance of threats contributing to coral extinction risk and assessed those threats against population status and trend information to evaluate each species’ extinction risk over the 21st century. This qualitative assessment resulted in a ranking with an uncertainty range for each species according to their estimated likelihood of extinction. We offer guidance on approaches for future biological extinction risk assessments, especially in cases of data‐limited species likely to be affected by global‐scale threats. Incorporación del Cambio Climático y Oceánico en Estudios de Riesgo de Extinción para 82 Especies de Coral     

Aktive Stoffe als Handlungsoption gegen die Verschleppung von Organismen durch Seeschiffe?

Background and Scope

The marine shipping lanes have become the most important path for the invasion of foreign aquatic organisms. The increasing global trade results in an increase in the number of marine vessels. Without any protective measures, with every ship carrying foreign organisms the risk of biological invasions will rise.

Results

The International Martime Organization (IMO) of the United Nations developed a convention to reduce the transfer of organisms with ballast water. After the entry-into-force of this convention the fleet of the world has to be equipped with effective ballast water management technology before 2016. This article discusses potential options for action. To comply with the limit values of the ballast water convention, the current state of the art demands the use of active substances. Any decision on the approval of active substances used for ballast water treatment and the environmental impact assessment lies with the IMO. Proposed to day are UV-radiation, active chlorine, active oxygen, the creation of biocides through electrolysis and a change in gases contained in the ballast water. The technologies and the potential risks are presented.

Conclusions

Despite the introduction of an approval procedure by IMO any reliable assessment of the real risks involved in the use of biocides is impossible, as the risk assessment approaches have still to be developed. On the regulatory level, the main focus in data requirements for the risk assessment is on a comprehensive testing of the toxic potential of the biocides proposed. Strategies for the identification and evaluation of the chemical resulting from the treatment of limnic, marine and brackish water are not fully developed. An integrating assessment of risks involved in the introduction of foreign organisms versus the toxic effects of the substances used or created during treatment is still missing.     

Assessing model structure uncertainty through an analysis of system feedback and Bayesian networks.

Ecological predictions and management strategies are sensitive to variability in model parameters as well as uncertainty in model structure. Systematic analysis of the effect of alternative model structures, however, is often beyond the resources typically available to ecologists, ecological risk practitioners, and natural resource managers. Many of these practitioners are also using Bayesian belief networks based on expert opinion to fill gaps in empirical information. The practical application of this approach can be limited by the need to populate large conditional probability tables and the complexity associated with ecological feedback cycles. In this paper, we describe a modeling approach that helps solve these problems by embedding a qualitative analysis of sign directed graphs into the probabilistic framework of a Bayesian belief network. Our approach incorporates the effects of feedback on the model's response to a sustained change in one or more of its parameters, provides an efficient means to explore the effect of alternative model structures, mitigates the cognitive bias in expert opinion, and is amenable to stakeholder input. We demonstrate our approach by examining two published case studies: a host-parasitoid community centered on a nonnative, agricultural pest of citrus cultivars and the response of an experimental lake mesocosm to nutrient input. Observations drawn from these case studies are used to diagnose alternative model structures and to predict the system's response following management intervention.     

外来鱼类入侵风险评估体系及方法

根据中国外来鱼类的入侵现状,分析了建立外来鱼类入侵风险评估体系的蕈要性、必要性和应用前景.在现状调查、文献分析和专家咨询的基础上,构建了一套包含5个一级指标、12个二级指标、44个三级指标的可定量化的外来鱼类入侵风险评估指标体系,确定了各指标权重,并举例说明了该评估体系的应用.     

Evaluating and Ranking the Vulnerability of Global Marine Ecosystems to Anthropogenic Threats

Abstract:  Marine ecosystems are threatened by a suite of anthropogenic stressors. Mitigating multiple threats is a daunting task, particularly when funding constraints limit the number of threats that can be addressed. Threats are typically assessed and prioritized via expert opinion workshops that often leave no record of the rationale for decisions, making it difficult to update recommendations with new information. We devised a transparent, repeatable, and modifiable method for collecting expert opinion that describes and documents how threats affect marine ecosystems. Experts were asked to assess the functional impact, scale, and frequency of a threat to an ecosystem; the resistance and recovery time of an ecosystem to a threat; and the certainty of these estimates. To quantify impacts of 38 distinct anthropogenic threats on 23 marine ecosystems, we surveyed 135 experts from 19 different countries. Survey results showed that all ecosystems are threatened by at least nine threats and that nine ecosystems are threatened by > 90% of existing threats. The greatest threats (highest impact scores) were increasing sea temperature, demersal destructive fishing, and point-source organic pollution. Rocky reef, coral reef, hard-shelf, mangrove, and offshore epipelagic ecosystems were identified as the most threatened. These general results, however, may be partly influenced by the specific expertise and geography of respondents, and should be interpreted with caution. This approach to threat analysis can identify the greatest threats (globally or locally), most widespread threats, most (or least) sensitive ecosystems, most (or least) threatened ecosystems, and other metrics of conservation value. Additionally, it can be easily modified, updated as new data become available, and scaled to local or regional settings, which would facilitate informed and transparent conservation priority setting.     

Evaluating and managing wildlife impacts of climate change under uncertainty

Wildlife managers face the daunting task of managing wildlife in light of uncertainty about the nature and extent of future climate change and variability and its potential adverse impacts on wildlife. A conceptual framework is developed for managing wildlife under such uncertainty. The framework uses fuzzy logic to test hypotheses about the extent of the wildlife impacts of past climate change and variability, and fuzzy multiple attribute evaluation to determine best compensatory management actions for adaptively managing the potential adverse impacts of future climate change and variability on wildlife. A compensatory management action is one that can offset some of the potential adverse impacts of climate change and variability on wildlife. Implementation of the proposed framework requires wildlife managers to: (1) select climate impact states, hypotheses about climate impact states, possible management actions for alleviating adverse wildlife impacts of climate change and variability, and future climate change scenarios; (2) choose biological attributes or indicators of species integrity; (3) adjust those attributes for changes in non-climatic variables; (4) define linguistic variables and associated triangular fuzzy numbers for rating both the acceptability of biological conditions under alternative management actions and the relative importance of biological attributes; (5) select minimum or maximum acceptable levels of the attributes and reliability levels for chance constraints on the biological attributes; and (6) define fuzzy sets on the extent of species integrity and biological conditions and select a fuzzy relation between species integrity and biological conditions. A constructed example is used to illustrate a hypothetical application of the framework by a wildlife management team. An overall best compensatory management action across all climate change scenarios is determined using the minimax regret criterion, which is appropriate when the management team cannot assign or is unwilling to assign probabilities to the future climate change scenarios. Application of the framework can be simplified and expedited by incorporating it in a web-based, interactive, decision support tool.     

Unintended biological invasions: Does risk vary by trading partner?

International trade is the primary conduit for unintentional and damaging species introductions. But biogeographic heterogeneity, and differences in historical trade exposure across trade partners suggest that not all imports are equally risky. We develop an analytical model linking exotic species introductions and discoveries to trade volumes. The model is estimated using a novel historical data set on global trade and species introductions by region. Our estimates support theoretical predictions that trade from different regions poses different risks and that the cumulative number of introductions from a region is a concave function of imports. For each trade region we then calculate the marginal and cumulative invasion risk from additional trade. Simple volume restrictions on imports to reduce NIS introductions are not advisable based on coarse cost–benefit calculations.     

Translating habitat class to land cover to map area of habitat of terrestrial vertebrates

Area of habitat (AOH) is defined as the “habitat available to a species, that is, habitat within its range” and is calculated by subtracting areas of unsuitable land cover and elevation from the range. The International Union for the Conservation of Nature (IUCN) Habitats Classification Scheme provides information on species habitat associations, and typically unvalidated expert opinion is used to match habitat to land-cover classes, which generates a source of uncertainty in AOH maps. We developed a data-driven method to translate IUCN habitat classes to land cover based on point locality data for 6986 species of terrestrial mammals, birds, amphibians, and reptiles. We extracted the land-cover class at each point locality and matched it to the IUCN habitat class or classes assigned to each species occurring there. Then, we modeled each land-cover class as a function of IUCN habitat with (SSG, using) logistic regression models. The resulting odds ratios were used to assess the strength of the association between each habitat and land-cover class. We then compared the performance of our data-driven model with those from a published translation table based on expert knowledge. We calculated the association between habitat classes and land-cover classes as a continuous variable, but to map AOH as binary presence or absence, it was necessary to apply a threshold of association. This threshold can be chosen by the user according to the required balance between omission and commission errors. Some habitats (e.g., forest and desert) were assigned to land-cover classes with more confidence than others (e.g., wetlands and artificial). The data-driven translation model and expert knowledge performed equally well, but the model provided greater standardization, objectivity, and repeatability. Furthermore, our approach allowed greater flexibility in the use of the results and uncertainty to be quantified. Our model can be modified for regional examinations and different taxonomic groups.     

An integrated optimization and simulation approach for air pollution control under uncertainty in open-pit metal mine

Air Pollution Control model is developed for open-pit metal mines. Model will aid decision makers to select a cost-effective solution. Open-pit metal mines contribute toward air pollution and without effective control techniques manifests the risk of violation of environmental guidelines. This paper establishes a stochastic approach to conceptualize the air pollution control model to attain a sustainable solution. The model is formulated for decision makers to select the least costly treatment method using linear programming with a defined objective function and multi-constraints. Furthermore, an integrated fuzzy based risk assessment approach is applied to examine uncertainties and evaluate an ambient air quality systematically. The applicability of the optimized model is explored through an open-pit metal mine case study, in North America. This method also incorporates the meteorological data as input to accommodate the local conditions. The uncertainties in the inputs, and predicted concentration are accomplished by probabilistic analysis using Monte Carlo simulation method. The output results are obtained to select the cost-effective pollution control technologies for PM_2.5, PM₁₀, NO_x, SO₂ and greenhouse gases. The risk level is divided into three types (loose, medium and strict) using a triangular fuzzy membership approach based on different environmental guidelines. Fuzzy logic is then used to identify environmental risk through stochastic simulated cumulative distribution functions of pollutant concentration. Thus, an integrated modeling approach can be used as a decision tool for decision makers to select the cost-effective technology to control air pollution.     

Using Expert Opinion Surveys to Rank Threats to Endangered Species: A Case Study with Sea Turtles

Abstract: Little is known about how specific anthropogenic hazards affect the biology of organisms. Quantifying the effect of regional hazards is particularly challenging for species such as sea turtles because they are migratory, difficult to study, long lived, and face multiple anthropogenic threats. Expert elicitation, a technique used to synthesize opinions of experts while assessing uncertainty around those views, has been in use for several decades in the social science and risk assessment sectors. We conducted an internet‐based survey to quantify expert opinion on the relative magnitude of anthropogenic hazards to sea turtle populations at the regional level. Fisheries bycatch and coastal development were most often ranked as the top hazards to sea turtle species in a geographic region. Nest predation and direct take followed as the second and third greatest threats, respectively. Survey results suggest most experts believe sea turtles are threatened by multiple factors, including substantial at‐sea threats such as fisheries bycatch. Resources invested by the sea turtle community, however, appear biased toward terrestrial‐based impacts. Results from the survey are useful for conservation planning because they provide estimates of relative impacts of hazards on sea turtles and a measure of consensus on the magnitude of those impacts among researchers and practitioners. Our survey results also revealed patterns of expert bias, which we controlled for in our analysis. Respondents with no experience with respect to a sea turtle species tended to rank hazards affecting that sea turtle species higher than respondents with experience. A more‐striking pattern was with hazard‐based expertise: the more experience a respondent had with a specific hazard, the higher the respondent scored the impact of that hazard on sea turtle populations. Bias‐controlled expert opinion surveys focused on threatened species and their hazards can help guide and expedite species recovery plans.