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Prioritizing Invasive Plant Management with Multi-Criteria Decision Analysis

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Abstract

Prioritizing management of invasive plants is important for large land management entities, such as federal and state public land stewards, because management resources are limited and multiple land uses and management objectives are differentially impacted. Management decisions also have important consequences for the likelihood of success and ultimate cost of control efforts. We applied multi-criteria decision analysis methods in a geographic information system using natural resource and land use data from Fort Bragg, North Carolina. Landscape-scale prioritization was based on a hierarchical model designed to increase invasive plant management efficiencies and reduce the risk of impacts to key installation management goals, such as training-land management and protected species conservation. We also applied spatial sensitivity analyses to evaluate the robustness of the prioritization to perturbations of the model weights, which were used to describe the relative importance of different elements of the hierarchical model. Based on stakeholders' need for confidence in making management investments, we incorporated the results of the sensitivity analysis into the decision-making process. We identified high-priority sites that were minimally affected by the weight perturbations as being suitable for up-front management and evaluated how adopting this strategy affected management area, locations, and costs. We found that incorporating the results of the sensitivity analysis led to a reduced management area, different target locations, and lower costs for an equal area managed. Finally, we confirmed the distinctiveness of the approach by comparing this same subset of prioritized sites with locations representing species-centric strategies for three invasive plants and their aggregate distribution. By supplying pragmatic information about the localized effects of weighting uncertainty, spatial sensitivity analyses enhanced the invasive plant management decision-making process and increased stakeholder confidence.

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... Various approaches have been developed in the last decade to guide the prioritization of IAPs in complex landscapes (e.g. Forsyth et al. 2012;Hohmann et al. 2013;Nielsen and Fei 2015). This study builds on these methods and introduces novel ways of approaching IAP management at a landscape and local scale. ...
... Experience has shown that successful IAP management requires well established priorities, clear time-based goals, adequate resources to achieve the desired level of control, and support from multiple stakeholders (e.g., JanuchowskiHartley et al. 2011;Forsyth et al. 2012;Hohmann et al. 2013). Efficient management of IAPs in urban landscapes is especially complicated, because of the multiple interacting environmental and socio-economic factors. ...
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The original version of the article unfortunately contained an error with the figure captions. The appropriate captions for Fig. 3-6 are published accordingly. The original article has been corrected.
... Various approaches have been developed in the last decade to guide the prioritization of IAPs in complex landscapes (e.g. Forsyth et al. 2012;Hohmann et al. 2013;Nielsen and Fei 2015). This study builds on these methods and introduces novel ways of approaching IAP management at a landscape and local scale. ...
... Experience has shown that successful IAP management requires well established priorities, clear time-based goals, adequate resources to achieve the desired level of control, and support from multiple stakeholders (e.g., Januchowski-Hartley et al. 2011;Forsyth et al. 2012;Hohmann et al. 2013). Efficient management of IAPs in urban landscapes is especially complicated, because of the multiple interacting environmental and socio-economic factors. ...
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Alien plant invasions in urban areas can have considerable impact on biodiversity and ecosystem services (ES). Managing urban plant invasions is particularly challenging given the complex interactions between ecological, economic and social elements that exist in the urban milieu. Strategic landscape-scale insights are crucial for guiding management, as are tactical site-scale perspectives to plan and coordinate control efforts on the ground. Integrating these requirements to enhance management efficiency is a major challenge. Decision-support models have considerable potential for guiding and informing management strategies when problems are complex. This study uses multi-criteria decision tools to develop a prioritization framework for managing invasive alien plants (IAPs) in urban areas at landscape and local scales. We used the Analytic Hierarchy Process (AHP; a multi-criteria decision support model) to develop and rank criteria for prioritising IAP management in the City of Cape Town (CoCT), South Africa. Located within a global biodiversity hotspot, Cape Town has a long history of alien plant introductions and a complex socio-political make-up, creating a useful system to explore the challenges associated with managing urban plant invasions. To guide the prioritization of areas for IAP management across the CoCT, a stakeholder workshop was held to identify a goal and criteria for consideration, and to assess the relative importance given to each criterion in IAP management. Workshop attendees were drawn from multiple disciplines involved with different aspects of IAP research and management: government departments, scientists and researchers, and managers with a diverse set of skills and interests. We selected spatial datasets and applied our multi-criteria decision analysis in a Geographic Information System (GIS) to develop a landscape-scale prioritization map. To address issues relevant in an urban setting, we also modified an existing IAP management framework to develop a tactical (site-level) prioritization scheme for guiding on-the-ground control operations. High-priority sites for IAP management were identified at landscape-and local scales across the study area. Factors related to safety and security emerged as pivotal features for setting spatially-explicit priorities for management. The approach applied in this study can be useful for managers in all urban settings to guide the selection and prioritization of areas for IAP management.
... In other cases where finding a near-optimal solution is more feasible, researchers may compare heuristic strategies [17,18], genetic algorithms [37,55], simulated annealing [2]. Depending on the modeling approach, other methods such as optimal control theory [49] and multi-criteria decision analysis [36] may be more appropriate. ...
... Modelers have incorporated stochasticity into initial detection probability [27], probability of survival [14], spread dynamics [57], and management effectiveness [21]. There are numerous methods for optimizing under uncertainty, ranging from sensitivity analysis [36] to stochastic dynamic programming [41,44] and information-gap decision theory [45]. ...
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Invasive species pose a significant threat to global biodiversity. Managing invasive species often involves modeling the species’ spread pattern, estimating control costs and damage costs due to the invasion, designing control efforts, and accounting for uncertainties in model parameters. Dealing with uncertainty is arguably the most important part of the process, since biological, environmental, and economic factors can cause parameter values to vary greatly. Managers need decision tools that are robust to such limited or variable information. Here, we present a robust spatial optimization model to select treatment sites in a way that maximally reduces the size of an invasive population, given a constraint on financial resources. We develop an integer programming model that includes population dynamics and management costs over space and time. The model incorporates uncertainty in the available budget and the invasive spread rate as sets of discrete scenarios to determine a robust, cost-effective management plan in a novel way.
... However, there has been limited use of AHP for invasive plant management. Existing applications of AHP in invasion management are often region or species-specific (e.g., Roura-Pascual et al. 2009, Forsyth et al. 2012, Hohmann et al. 2013. Moreover, these studies do not directly demonstrate to managers that the AHP tool is adaptable to their specific management scenarios. ...
... While the management tool was not demonstrated by multiple user groups we believe that our results show that AHP is capable of producing flexible outputs for prioritizing management. Our assessment of AHP flexibility, along with other region and species-specific AHP frameworks (e.g., Skurka Darin et al. 2011, Hohmann et al. 2013, Robison et al. 2013) will greatly enrich managers options in invasive species management decision making. ...
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Decision tools have been advocated to assist the prioritization of management areas for preventing and mitigating exotic invasions into native ecosystems. Currently, most tools have been created for specific invaders/regions and are thus often not sufficient to address the complex range of invasion scenarios that managers encounter. As exotic invasions continue to be a major issue, science-based, information-driven tools are pressingly needed. In this study, we explore the potential of utilizing the Analytic Hierarchy Process (AHP), one of the information-driven tools, to flexibly prioritize various invasion scenarios by incorporating a broad spectrum of management data. We tested the flexibility of the AHP management tool with two distinct invasion-stage-specific prioritizations for Amur honeysuckle (Lonicera maackii). The AHP tool successfully created two management prioritizations from contrasting invasion scenarios of established Amur honeysuckle invasion versus a hypothetical scenario of newly invading populations. The flexibility of AHP allowed users to alter input based on the stage of invasion in each scenario. In the established scenario, management priority was assigned to removing Amur honeysuckle from the most ecologically significant areas. For the new invasion scenario, priority was shifted to removing the invader from areas of most recent invasions. The two contrasting prioritizations demonstrate the flexibility of AHP as a management tool. We conclude that the flexible AHP tool could be useful for prioritizing management of exotic plant invasions.
... The various ecological mechanisms involved (Catford et al. 2009) and the ecological impacts (Simberloff et al. 2013) of invasive species are widely studied. The management of widespread and well-established invasive species is difficult and needs to prioritize and optimize control efforts (Epanchin-Niell and Hastings 2010;Giljohann et al. 2011;Hohmann et al. 2013) according to ecological, economic, and social criteria, including perceived benefits and impacts of the species (Gaertner et al. 2017). Moreover, different value systems of stakeholders may even lead to some conflicts about Communicated by: Matthias Waltert Electronic supplementary material The online version of this article (https://doi.org/10.1007/s00114-018-1592-7) ...
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Choices have to be made to manage invasive species because eradication often is not possible. Both ecological and social factors have to be considered to improve the efficiency of management plans. We conducted a social study on Fallopia spp., a major invasive plant taxon in Europe, including (1) a survey on the perception of a landscape containing Fallopia spp. using a photoquestionnaire and (2) an analysis of the social representations of Fallopia spp. of managers and users in one highly invaded area and one less invaded area. The respondents to the photoquestionnaire survey appreciated the esthetics of the landscapes less when tall Fallopia spp. were present. Few people were able to identify and name the plant, and this knowledge negatively affected the appreciation of the photos containing Fallopia spp. The central core of the social representation of Fallopia spp. was composed of the invasive status of the plant, its density, and its ecological impacts. The peripheral elements of the representation depended on the people surveyed. The users highlighted the natural aspect whereas the managers identified the need for control. In the invaded area, the managers qualified the species as “unmanageable,” whereas the species was qualified as “foreign” in the less invaded area. Those results provide insights that have to be included when objectives of management plans of these species are selected.
... We studied six avian-dispersed, non-native woody species that are generally considered invasive in the southeastern USA: Elaeagnus umbellata Thunb., Ligustrum sinense Lour., Melia azedarach L., Nandina domestica Thunb., Pyrus calleryana Dcn., and Triadica sebifera (L.) Small (Table 1; nomenclature follows USDA NRCS (2016)). These species have been documented to occur in longleaf pine landscapes in both xeric and mesic communities (Drew et al., 1998;Herring and Judd, 1995;Hohmann et al., 2013;Jenkins and McMillan, 2009;Noss, 2012;Renne et al., 2002). Moreover, each of these non-native species have been found at Fort Bragg, with the greatest abundances in residential and urban areas, where fire is suppressed and some species have been planted ornamentally. ...
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... Hohmann et al. [97] used one method of Multi-Criteria Decision Analysis, Analytic Hierarchy Process (AHP) with spatial sensitivity analysis, to prioritize invasive plant management across a complex landscape in North Carolina, USA. Interestingly, less than 8% of the aggregate area that would have been targeted in a species-centric strategy was identified by the integrated AHP process. ...
... Hohmann et al. [97] used one method of Multi-Criteria Decision Analysis, Analytic Hierarchy Process (AHP) with spatial sensitivity analysis, to prioritize invasive plant management across a complex landscape in North Carolina, USA. Interestingly, less than 8% of the aggregate area that would have been targeted in a species-centric strategy was identified by the integrated AHP process. ...
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PRELIMINARIES. Geographical Data, Information, and Decision Making. Introduction to GIS. Introduction to Multicriteria Decision Analysis. SPATIAL MULTICRITERIA DECISION ANALYSIS. Evaluation Criteria. Decision Alternatives and Constraints. Criterion Weighing. Decision Rules. Sensitivity Analysis. MULTICRITERIA-SPATIAL DECISION SUPPORT SYSTEMS. Spatial Decision Support Systems. MC-SDSS: Case Studies. Glossary. Selected Bibliography. Indexes.
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Conservation programme planning involves allocating a limited budget amongst different potential conservation projects. The selection of projects for funding is subject to a high degree of uncertainty and a number of competing objectives such as ecological protection, recreation and community relations. The purposes of this paper are to summarize the quantitative methods currently used in deciding which conservation projects to fund and to present a general methodology based on decision analysis that can be used for making conservation programme planning decisions. The methodology directly links the proposed contributions of projects to the objectives of the conservation agency, and it includes an explicit consideration of uncertainty and a conversion of ordinal scores into utilities. The methodology is a rational way of making decisions in conservation situations that are characterized by high degrees of uncertainty and subjective information. An application of decision analysis with staff from the New Zealand Department of Conservation is described. Some of the difficulties with using this methodology in practice are discussed in both the New Zealand and broader contexts. The conclusions are that conservation programme planning is currently based on managerial experience and relatively simple scoring procedures, but that a more rational approach based on decision analysis is possible, and additional research would reduce the amount of effort required to use decision analysis for conservation programme planning.
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Biological invasions are widespread phenomena that threaten the integrity and functioning of natural ecosystems. In this paper we develop a model that is designed to be a decision-making tool for planning and managing alien plant control operations. Most decision tools adopt a static approach; in this application we integrate a dynamic simulation model of alien plant spread with decision-making tools commonly used for reserve design. The model is a landscape-scale implementation of a fine-grained individual- based spread model. We first describe the scaling up of the fine-scaled model into a landscape extent model. Comparisons between the fine-grained local-scale and coarse-grained land- scape-scale model show that the scaling-up process did not introduce significant artifacts into the behavior of the model. The landscape model is used to explore a range of strategies and funding schedules for clearing alien plants. These strategies are evaluated in terms of the cost of the clearing operation, the time it takes to eradicate the plants, and the impact the plants have on three components of native plant diversity (all species, rare and threatened species, endemic species). Clearing strategies that prioritize low-density sites dominated by juvenile alien plants proved to be the most cost effective. Strategies that used information on the distribution of plant diversity were not much more expensive than the most cost- effective strategy, and they substantially reduced the threat to native plant diversity. De- laying the initiation of clearing operations had a strong effect on both the eventual costs of the clearing operation and the threat to native plant diversity. We conclude that the integration of dynamic modeling with decision-making tools, as illustrated here, will be useful for the management of biodiversity under global change.
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SUMMARY (I) We evaluated through simulation the spatial growth of an invading terrestrial plant population and various strategies for its control. The initial population comprised a single large expanding focus but had the potential for the continual establishment of new foci. (2) We compared the area occupied through the establishment and expansion of these "satellite" foci to the area occupied by the initially large or main focus under varying regimens of repeated control, in which either the area of the main focus was reduced or some satellites were destroyed, or both. (3) Whether varying growth rates for the foci, rates of satellite establishment, the level of reduction of the main focus or the intensity of satellite detection and destruction, the overall effectiveness of control measures was greatly improved by destroying even 30% of the satellites. (4) These predictions contrast with much current practice in the control of alien plants, where large or otherwise conspicuous infestations are often treated at the expense of eradicating isolated populations while they still remain small. As supported by empirical precedents, consistent implementation of the general strategy suggested by our model should improve the control of alien plants.
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1. A key problem facing invasive species management is how best to allocate surveillance and control effort. Models of the establishment and spread of invasive species are widely used to predict species’ occurrence across space and inform resource prioritization. However, the way they should be used to direct control effort is less clear. Managers could exhaustively search and treat the few highest priority locations or apply less thorough effort more broadly. The choice between these options is a question of balancing resources to maximize local success while minimizing further spread.
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Invasive alien trees and shrubs pose significant threats to biodiversity and ecosystem services in South African fynbos ecosystems. An ambitious initiative, the Working for Water program, commenced in 1995 to reduce the extent and impact of plant invasions. Despite substantial progress, the problem remains immense, and innovative ways of improving the efficiency of control operations are urgently needed. This study sought to develop a robust conceptual framework for effective management of the most important invasive alien plant (IAP) species. Two methods were applied in exploring the complexity of problems, thereby identifying appropriate response strategies. The DPSIR (Driving forces-Pressure-State-Impacts-Responses) framework and the Analytic Hierarchy Process (AHP) tool were used to design a strategy for prioritizing management actions. This strategy considers explicitly the most influential factors that determine the distribution, abundance, spread and impacts of IAPs. Efficient management of IAPs is constrained by multiple interacting environmental and socio-economic factors. Factors related to the fire-prone nature of the ecosystem and the characteristics of the invasive stands emerged as pivotal features for setting spatially-explicit priorities for management. Results of the analyses provide an objective and quantifiable perspective for improving the management efficiency. We conclude that considerable progress in controlling the spread of IAPs in fynbos ecosystems could be achieved by better coordination of management practices and by improving the quality of species distribution data.
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Patterns in the spatial arrangement of invasive plant populations can provide opportunity for strategic placement of control efforts. Smooth cordgrass (Spartina alterniflora) is rapidly invading the intertidal mudflats of Pacific Coast estuaries. Its pattern of spread is distinctive. Seedlings establish in open mud and then grow vegetatively to form expanding circular patches, which dot the mudflats and eventually coalesce into a contiguous monospecific meadow. The invasion typically begins in the upper tide zone and then moves down the tidal gradient. A spatially explicit model was used to simulate the spread of S. alterniflora and compare various strategies for control in a situation where only a fraction of the total infestation could be controlled each year. A strategy of killing outlying patches first and then attacking the dense meadows (moving up the tidal gradient) led to eradication with up to 44% less time and effort than a strategy of attacking the dense meadows first and outlying patches second (moving down the tidal gradient). In the control of contiguous meadows located adjacent to the shoreline, the best strategy was to approach one end of the infestation, moving across the meadow to the other end. Suppression of seeds was not an effective control strategy. In general, effective control strategies were those that first eliminate the plant in areas where current or future vegetative growth is greatest. Application of these results in control programs for S. alterniflora and similar invasive species could greatly reduce the costs of control work and improve the likelihood of local or complete eradication.
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This paper describes a methodological approach based on the integrated use of Geographical Information Systems (GIS) and Decision Support Systems (DSS) to identify nature conservation priorities among the remnant ecosystems within an alpine valley. The ecosystems are first assessed by means of landscape ecological indicators, and then ranked by using multicriteria analysis (MCA) techniques. Several conservation scenarios are generated so as to simulate different evaluation perspectives. The scenarios are then compared to highlight the most conflicting sites and to propose a conservation strategy for the area under evaluation. The paper aims at exemplifying and discussing the effectiveness of spatial decision-support techniques in land-use planning for nature conservation.
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The behavior of several landscape pattern metrics were tested against various pattern scenarios generated by neutral landscape models, including number of classes, scale-map extent, scale-resolution, class proportion, aggregation level—RULE, and aggregation level—SimMap. The results demonstrate that most of the metrics are sensitive to certain pattern scenarios, yet are not sensitive to others; therefore, none of them is appropriate for all aspects of a landscape pattern. Despite these limitations, some of these metrics are recommended for future use, which include total number of patches, average patch size, total edge density, double-logged fractal, contagion, and aggregation index. Special attention should be paid to the relationships between metric values and ecological processes rather than the numbers themselves.
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In this paper, a comprehensive algorithm is developed to analyze the sensitivity of hierarchical decision models (HDM), including the analytic hierarchy process and its variants, to single and multiple changes in the local contribution matrices at any level of the decision hierarchy. The algorithm is applicable to all HDM that use an additive function to derive the overall contribution vector. It is independent of pairwise comparison scales, judgment quantification techniques and group opinion combining methods. The allowable range/region of perturbations, contribution tolerance, operating point sensitivity coefficient, total sensitivity coefficient and the most critical decision element at a certain level are identified in the HDM SA algorithm. An example is given to demonstrate the application of the algorithm and show that HDM SA can reveal information more significant and useful than simply knowing the rank order of the decision alternatives.
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Invading alien species in the United States cause major environmental damages and losses adding up to almost $120 billion per year. There are approximately 50,000 foreign species and the number is increasing. About 42% of the species on the Threatened or Endangered species lists are at risk primarily because of alien-invasive species.
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Scientists have argued that invasive species can be managed most cost effectively with greater investments in prevention. Further, under ideas like the precautionary principle it is reasonable to expect that a cautious manager would use more prevention relative to control because it keeps more invaders out. Yet, this is not typically done. In many cases, private and public resources are invested primarily to control existing invaders rather than to prevent new invasions. Managers frequently wait until after invaders have arrived and then scramble to limit the damages. We believe these paradoxical decisions can be understood by recognizing the link between typical human preferences for risk bearing and the technology of risk reduction. We demonstrate quantitatively how managers perceived to be cautious or averse to risk tend to shy away from prevention relative to control. This counterintuitive result arises because control is a safer choice than prevention because its productivity is relatively less risky: it works to remove existing invaders from the system. In contrast, the productivity of prevention is more uncertain because prevention only reduces the chance of invasion, it does not eliminate it, and invasion may not occur even in the absence of prevention. Managers' averse to risk will inherently avoid as much uncertainty as possible, whether the source of uncertainty regards ecological outcomes or economic productivity. Implications for environmental decision making are clear. In invasive species management, if managers act as though they are risk averse, their caution can backfire when it leads to more control rather than prevention. The social consequences of this choice are a greater probability of future invasions and lower social welfare. Our results suggest that social welfare is highest when managers were willing to “take a risk” with prevention.
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When a weed invasion is first discovered a decision has to be made on whether to attempt to eradicate it, contain it or do nothing. Ideally, these decisions should be based on a complete benefit-cost analysis, but this is often not possible. A partial analysis, combining knowledge of the rate of spread, seedbank longevity, costs of control and techniques of economic analysis, can assist in making a good decision. This paper presents a decision model to determine when immediate eradication of a weed should be attempted, or more generally whether weed control should be attempted at all. The technique is based on identifying two ‘switching points’: the invasion size at which it is no longer optimal to attempt eradication but where containment may be an option; and the invasion size at which it becomes optimal to apply no form of control at all. The model is applied to a woody perennial weed in a natural environment. The results show that seedbank longevity is the main constraint on the maximum eradicable area and spread rate is the main constraint on the maximum containment area. Stochastic simulations are undertaken to derive probability distributions of costs which are than used to evaluate the effect of budget constraints on areas that can be eradicated. We find that, in the absence of a budget constraint, it may be desirable to eradicate invasions from areas as large as 8000 ha, but when budget constraints typical of those faced by agencies in Australia are introduced, feasible eradicable areas are less than 1000 ha.
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The purpose of this paper is to investigate a method of scaling ratios using the principal eigenvector of a positive pairwise comparison matrix. Consistency of the matrix data is defined and measured by an expression involving the average of the nonprincipal eigenvalues. We show that λmax = n is a necessary and sufficient condition for consistency. We also show that twice this measure is the variance in judgmental errors. A scale of numbers from 1 to 9 is introduced together with a discussion of how it compares with other scales. To illustrate the theory, it is then applied to some examples for which the answer is known, offering the opportunity for validating the approach. The discussion is then extended to multiple criterion decision making by formally introducing the notion of a hierarchy, investigating some properties of hierarchies, and applying the eigenvalue approach to scaling complex problems structured hierarchically to obtain a unidimensional composite vector for scaling the elements falling in any single level of the hierarchy. A brief discussion is also included regarding how the hierarchy serves as a useful tool for decomposing a large-scale problem, in order to make measurement possible despite the now-classical observation that the mind is limited to 7 ± 2 factors for simultaneous comparison.
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The increasing importance and complexity of land and natural resource management are creating a need for ecosystem-based management (EBM). Multiple criteria decision analysis (MCDA) combined with geographic information systems (GIS) can integrate factors related to the triple bottom line of ecological, economic, and social perspectives required by EBM. However, GIS-based MCDA is limited in this role because (i) it rarely integrates or encourages an exploration phase in preparation for structured evaluation and (ii) inexperienced users may find MCDA methods and GIS software difficult to use. This paper presents a novel approach for (i) supporting an exploration phase to help structure a problem and (ii) integrating the exploration and evaluation phases in an easy-to-use software system. The approach was validated through a land-management case study in a forest-dominated landscape with a variety of stakeholders. Case-study participants used the approach to rate areas within a timber harvest plan based on their potential for conflict with conservation values. The case-study decision analysis determined that between 1.3% and 6.6% of the harvest plan area had a conservation rating of 0.30 or higher on a scale of 0-1. The system was made available to the forest industry and other stakeholders to support harvest plan adjustments, demonstrating how such tools can be used to improve and integrate our knowledge of forest ecology and management. Assessment of participant feedback reveals that an exploration phase is effective in helping understand a problem and prepare for multiple criteria evaluation (MCE). Crown Copyright (C) 2010 Published by Elsevier B.V. All rights reserved.
Article
The integration of GIS and multicriteria decision analysis has attracted significant interest over the last 15 years or so. This paper surveys the GIS-based multicriteria decision analysis (GIS-MCDA) approaches using a literature review and classification of articles from 1990 to 2004. An electronic search indicated that over 300 articles appeared in refereed journals. The paper provides taxonomy of those articles and identifies trends and developments in GIS-MCDA.
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Large geographic areas can have numerous incipient invasive plant populations that necessitate eradication. However, resources are often deficient to address every infestation. Within the United States, weed lists (either state-level or smaller unit) generally guide the prioritization of eradication of each listed species uniformly across the focus region. This strategy has several limitations that can compromise overall effectiveness, which include spending limited resources on 1) low impact populations, 2) difficult to access populations, or 3) missing high impact populations of low priority species. Therefore, we developed a novel science-based, transparent, analytical ranking tool to prioritize weed populations, instead of species, for eradication and tested it on a group of noxious weeds in California. For outreach purposes, we named the tool WHIPPET (Weed Heuristics: Invasive Population Prioritization for Eradication Tool). Using the Analytic Hierarchy Process that included expert opinion, we developed three major criteria, four sub-criteria, and four sub-sub-criteria, taking into account both species and population characteristics. Subject matter experts weighted and scored these criteria to assess the relative impact, potential spread, and feasibility of eradication (major criteria) for 100 total populations of 19 species. Species-wide population scores indicated that conspecific populations do not necessarily group together in the final ranked output. Thus, priority lists based solely on species-level characteristics are less effective compared to a blended prioritization based on both species attributes and individual population and site parameters. WHIPPET should facilitate a more efficacious decision-making process allocating limited resources to target invasive plant infestations with the greatest predicted impacts to the region under consideration.
Article
Ecology Letters (2010) 13: 528–541 We review studies that address economically optimal control of established invasive species. We describe three important components for determining optimal invasion management: invasion dynamics, costs of control efforts and a monetary measure of invasion damages. We find that a management objective that explicitly considers both costs and damages is most appropriate for determining economically optimal strategies, but also leads to large challenges due to uncertainty in components of the management problem. To address uncertainty, some studies have included stochasticity in their models; others have quantified the value of information or focused on decision-making with limited information. Our synthesis shows how invasion characteristics, such as costs, damages, pattern of spread and invasion and landscape size, affect optimal control strategies and goals in systematic ways. We find that even for simple questions, such as whether control should be applied at the centre of an invasion or to satellite patches, the answer depends on the details of a particular invasion. Future work should seek to better quantify key components of this problem, determine best management in the face of limited information, improve understanding of spatial aspects of invasion control and design approaches to improve the feasibility of achieving regional control goals.
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The unique band structure of graphene allows reconfigurable electric-field control of carrier type and density, making graphene an ideal candidate for bipolar nanoelectronics. We report the realization of a single-layer graphene p-n junction in which carrier type and density in two adjacent regions are locally controlled by electrostatic gating. Transport measurements in the quantum Hall regime reveal new plateaus of two-terminal conductance across the junction at 1 and times the quantum of conductance, e2/h, consistent with recent theory. Beyond enabling investigations in condensed-matter physics, the demonstrated local-gating technique sets the foundation for a future graphene-based bipolar technology.