Delineating protected wildlife corridors with multi‐objective programming

Protected wildlife corridors can help counteract habitat fragmentation and link isolated reserve “islands” into connected reserve systems. The need for wildlife corridors will grow as expanding human populations place increasing pressure on remaining undeveloped land. A two‐objective zero–one programming model is formulated for the problem of selecting land for a system of wildlife corridors that must connect a known set of existing reserves or critical habitat areas. This problem is modeled as a network Steiner tree problem, under the objectives of minimizing corridor land costs and minimizing the amount of unsuitable land within the corridor system. Linear programming is used to find exact solutions with little or no branching and bounding, and the multi‐objective weighting method is used to generate non‐inferior alternatives. Two hypothetical examples demonstrate the model and solution procedure. Results can help inform planning and decision making for protected area land acquisition and habitat restoration.     

A Simulation Framework for Assessing Physical and Wildlife Impacts of Oil and Gas Development Scenarios in Southwestern Wyoming

Foreseeable natural gas development in southwestern Wyoming has the potential to increase sagebrush fragmentation and risks to resident wildlife species. The ability to balance future development with conservation goals, however, is enhanced by advances in directional-drilling technologies that use multiple wells per pad and produce less surface disturbance than conventional drilling methods. To evaluate the conservation potential of this technology, I developed an energy footprint model that simulates well, pad, and road patterns for oil and gas recovery options that vary in well types (vertical and directional) and number of wells per pad and use simulation results to quantify physical and wildlife-habitat impacts. I applied the model to assess tradeoffs among 10 conventional and directional-drilling scenarios in a natural gas field in southwestern Wyoming. Scenarios spanned a gradient in the number of vertical and directional wells, and in number of pads (2000 to 250), but all extracted the same amount of gas over a 15-year period. Reducing pad numbers with directional-drilling technology reduced surface disturbance area and impacts on spatially extensive habitats (48–96% of study area) such as sagebrush-obligate songbird habitat, elk winter range, and sagebrush core area. Impacts declined for spatially restricted mule deer migration corridors (24% of study area) and greater sage-grouse leks until energy infrastructure densities within corridors and near leks were similar to the initial landscape. Scenario simulations and tradeoff assessments such as illustrated in this study are intended to help decision-makers identify development designs that best achieve both energy and conservation goals.     

A Spatial Analysis of the Economic and Ecological Efficacy of Land Retirement

This paper uses a cellular automata simulation model of a hypothetical landscape to investigate the role of location as it relates to the efficacy of land retirement in achieving two environmental goals: hydrological improvement and habitat improvement. Statistical analysis of simulation results is used to show how absolute and relative location relate to achievement of these objectives. Linear and nonlinear compromise programming frameworks then combine these two environmental objectives and a cost minimization objective into a measure that allows decision-makers to rank the desirability of different retirement strategies. These frameworks are explored to determine what each implies about the tradeoffs that must be made among objectives and among the spatial land parcel characteristics that contribute to those objectives.     

DMSP-IEES: A Stochastic Programming Model Based on Dual-Interval and Multi-Stage Scenarios Modeling Approaches for Energy Systems Management and GHG Emissions Control

Energy-related activities contribute a major portion of anthropogenic greenhouse gas (GHG) emissions into the atmosphere. In this study, a dual-interval multi-stage stochastic programming model for the planning of integrated energy-environment systems (DMSP-IEES) model is developed for integrated energy-environment systems management, in which issues of GHG-emission mitigation can be reflected throughout the process of energy systems planning. By integrating methodologies of interval linear programming (when numbers are described as interval values without distribution information), dual-interval programming (when lower and upper bounds of interval values are not available as deterministic values but as discrete intervals), and multi-stage stochastic programming, the DMSP-IEES model is capable of dealing with uncertainties expressed as discrete intervals, dual intervals, and probability distributions within a multi-stage context. Decision alternatives can also be generated through analysis of the single- and dual-interval solutions according to projected applicable conditions. A case study is provided for demonstrating the applicability of the developed methodology. The results indicate that the developed model can tackle the dual uncertainties and the dynamic complexities in the energy-environment management systems through a multi-layer scenario tree. In addition, it can reflect the interactions among multiple system components and the associated trade-offs.     

Integrating Land Market Feedbacks into Conservation Planning—A Mathematical Programming Approach

Nature reserves are often designated ad hoc. Despite increasing conservation efforts, loss of biodiversity is still accelerating. Considering land scarcity and demand for alternative uses, efficiency in conservation strongly correlates with efficiency in land allocation. Systematic conservation planning can effectively prioritize conservation activities. Previous studies minimize opportunity costs for given conservation targets. However, these studies assume constant marginal costs of habitat protection. We extend this cost minimization approach by also considering a dynamic representation of marginal costs. The more land is allocated to nature reserves, the higher are opportunity costs, i.e., costs of forgone agricultural production. This increase in costs results from changes in the prices of agricultural commodities. We employ a deterministic, spatially explicit mathematical optimization model to allocate species habitats by minimizing opportunity costs for setting aside land for conservation purposes. The model is designed as a mixed integer programming problem and solved with GAMS/CPLEX. Our results show the need for integrating land market feedbacks into conservation planning. We find that ignoring land rent adjustments can lead to highly cost-ineffective solutions in reserve selection.     

Regulation of pesticide discharge into surface and groundwater under uncertainty: A model for environmental risk‐profitability tradeoffs and policy selection

The presence of contaminants in environmental media as well as the desire to maintain a high level of economic activity has led to an important and difficult decision‐making problem for both public policy decision makers and the general public. In one sense, all of the interested parties are likely to be concerned about the potential health risks posed by the presence of contaminants in environmental media and the need to design/implement policies for their mitigation and/or removal. At the same time, however, there also appear to be concerns about the cost of these policies. These costs could be measured in terms of the potential losses in economic activity that are likely to occur when a policy is adopted. The policy can be selected from a range of alternatives, with the choice being driven in part by the stakeholders represented in the policy decision problem. In this case, two general goals might be considered: minimizing environmental risk and minimizing the economic impact of the policy considered. These two objectives are likely to be viewed as conflicting goals, and the nature of the tradeoffs between them must be taken into account in the policy selection process. This paper presents the development of a zero–one weighted goal programming model that can be used to select a preferred policy that minimizes surface and groundwater contamination as well as the economic costs of environmental policy selection. A safety rule model is developed first and then extended to the zero–one weighted goal programming formulation. The stochastic aspects of these structures are emphasized throughout. The paper also addresses a number of issues related to implementation of the model.     

Land classification and ecosystem classification

Earth, the ecosphere, is a unified functional ecosystem. Ecological land classification (ELC) and regionalization divides and categorizes this unity into similar and dissimilar pieces-sectoral ecosystems - at various scales, in the interests of admiration and understanding. The recognition of land/water ecosystems in a hierarchy of sizes provides a rational base for the many-scaled problems of protection and careful exploitation in the fields of agriculture, forestry, wildlife and recreation. In forested terrain the protection of biodiversity, old growth forests, watersheds and wildlife habitat depends on spatial-temporal planning of forestry operations to maintain a preferred mosaic structure of local ecosystems within each ecological region. Without ecological understanding and a good ELC, this is impossible. Conceiving the world as comprising nested land/water ecosystems that are the source of life, elevates the role of Earth-as-context, an antidote to destructive anthropocentrism.     

Interval-Parameter Conditional Value-at-Risk Two-Stage Stochastic Programming Model for Management of End-of-Life Vehicles

The management of end-of-life vehicles conserves natural resources, provides economic benefits, and reduces water, air, and soil pollution. Sound management of end-of-life vehicles is vitally important worldwide thus requiring sophisticated decision-making tools for optimizing its efficiency and reducing system risk. This paper proposes an interval-parameter conditional value-at-risk two-stage stochastic programming model for management of end-of-life vehicles. A case study is conducted in order to demonstrate the usefulness of the developed model. The model is able to provide the trade-offs between the expected profit and system risk. It can effectively control risk at extremely disadvantageous availability levels of end-of-life vehicles. The formulated model can produce optimal solutions under predetermined decision-making risk preferences and confidence levels. It can simultaneously determine the optimal long-term allocation targets of end-of-life vehicles and reusable parts as well as capital investment, production planning, and logistics management decisions within a multi-period planning horizon. The proposed model can efficiently handle uncertainties expressed as interval values and probability distributions. It is able to provide valuable insights into the effects of uncertainties. Compared to the available models, the resulting solutions are far more robust.

     

A Blending Problem in Copper Production

Well-known mathematical models related to blending problem are extended and adjusted to the specific blending problem in copper production. Certain constraints are deduced from the process of making copper as well as from the ecological aspects of the production process. The models are applied to the production experience at the copper-smelting plant RTB Bor. The implementation of introduced models was made in the programming package MATHEMATICA. Numerical results corresponding to the introduced mathematical model were compared with results obtained by implementing the classical mathematical models.     

Assessing the wildlife habitat value of New England salt marshes: II. Model testing and validation

We tested a previously described model to assess the wildlife habitat value of New England salt marshes by comparing modeled habitat values and scores with bird abundance and species richness at sixteen salt marshes in Narragansett Bay, Rhode Island USA. As a group, wildlife habitat value assessment scores for the marshes ranged from 307-509, or 31-67% of the maximum attainable score. We recorded 6 species of wading birds (Ardeidae; herons, egrets, and bitterns) at the sites during biweekly survey. Species richness (r (2)=0.24, F=4.53, p=0.05) and abundance (r (2)=0.26, F=5.00, p=0.04) of wading birds significantly increased with increasing assessment score. We optimized our assessment model for wading birds by using Akaike information criteria (AIC) to compare a series of models comprised of specific components and categories of our model that best reflect their habitat use. The model incorporating pre-classification, wading bird habitat categories, and natural land surrounding the sites was substantially supported by AIC analysis as the best model. The abundance of wading birds significantly increased with increasing assessment scores generated with the optimized model (r (2)=0.48, F=12.5, p=0.003), demonstrating that optimizing models can be helpful in improving the accuracy of the assessment for a given species or species assemblage. In addition to validating the assessment model, our results show that in spite of their urban setting our study marshes provide substantial wildlife habitat value. This suggests that even small wetlands in highly urbanized coastal settings can provide important wildlife habitat value if key habitat attributes (e.g., natural buffers, habitat heterogeneity) are present.     

Assessing the impact of alternative land-use zoning policies on future ecosystem services

Land use conversions rank among the most significant drivers of change in ecosystem services worldwide, affecting human wellbeing and threatening the survival of other species. Hence, predicting the effects of land use decisions on ecosystem services has emerged as a crucial need in spatial planning, and in the associated Strategic Environmental Assessment (SEA) practice. The paper presents a case-study research aimed at empirically exploring how the implementation of different land-use zoning policies affect the future provision of a set of ecosystem services (water purification, soil conservation, habitat for species, carbon sequestration and timber production). The study area is located in The Araucanía, one of Chile's Administrative Regions. The first part of the methods consisted in the construction of land-use scenarios associated to different policies. Subsequently, the effects of the land-use scenarios on the provision of the selected ecosystem services were assessed in a spatially explicit way, by using modeling tools. Finally, a set of metrics was developed to compare scenarios, and trade-offs in the provision of different ecosystem services were made explicit through trade-off curves. The results indicate that, for this case study, spatial configuration of land uses is as an important factor as their size. This suggests that the analysis of land-use patterns deserves attention, and that this information should be included in scenario exercises aimed to support spatial planning. The paper concludes by discussing the potential contribution of the approach to support SEA of spatial plans.     

Assessing the wildlife habitat value of New England salt marshes: I. Model and application

We developed an assessment model to quantify the wildlife habitat value of New England salt marshes based on marsh characteristics and the presence of habitat types that influence habitat use by terrestrial wildlife. Applying the model to 12 salt marshes located in Narragansett Bay, RI resulted in assessment scores that ranged over a factor of 1.5 from lowest to highest. Pre-classifying the results based on marsh size and morphology helped to compare assessment scores between marshes, and demonstrated that even the lower ranking marshes had substantial habitat value. Stepwise multiple regression analysis of assessment scores and model components demonstrated that salt marsh morphology, the degree of anthropogenic modification, and salt marsh vegetative heterogeneity were significant variables and accounted for 91.3% of the variability in component scores. Our results suggest that targeting these components for restoration may lead to improved assessment scores for our study marshes. We also examined the use of lower resolution remote sensing data in the assessment in order to minimize the time and effort required to complete the model. Scores obtained using smaller-scale, lower resolution data were significantly lower than those obtained using larger-scale, higher resolution data (df = 11; t = 2.2; p < 0.001). The difference was significantly positively correlated with the portion of the assessment score that could be attributed to trees, pools, and pannes and marsh size (r (2) =0.50, F = 4.6, p = 0.04), and could indicate a bias against smaller, more heterogeneous marshes. We conclude that potential differences need to be weighed against the time benefit of using this type of data, bearing in mind the marsh size and the goals of the assessment. Overall, our assessment can provide information to aid in prioritizing marshes for protection and restoration, identify marshes that may harbor significant biodiversity, or help monitor changes in habitat value over time.     

A Regional Assessment of Windbreak Habitat Suitability

The Environmental Monitoring and Assessment Programwas initiated in 1989 by the United StatesEnvironmental Protection Agency to collect, analyze,and report quantitative, statistically unbiasedinformation about the state of the nation'senvironment on a regional basis. During a pilotprogram in Nebraska we measured a habitat suitabilityindex for a probability sample of 40 windbreaks andexpanded the results to estimate the potential valueof windbreaks as wildlife habitat in Nebraska. Theindex estimates the suitability of a windbreak ashabitat for wildlife including breeding birds, smallmammals, and deer. Index values range from zero toone, where a value of one indicates maximal habitatvalue. We estimated that 50% (±13% at 90%confidence) of windbreaks in Nebraska have a habitatsuitability index of 0.25 or less and that nowindbreaks have a suitability index greater than 0.6. Our results indicate that increasing the area ofindividual windbreaks is the most effective way toimprove their value as wildlife habitat. Monitoringwindbreak condition over time would alert wildlifemanagers to changes in the resource that might affectwildlife populations. Because our data were highlyvariable, the power to detect change in habitatcondition between two measurement periods was low. Amuch larger sample would be required to detect smallchanges in habitat condition. Variability may bereduced, and power increased, by carefully andconsistently constructing the sampling frame, keepingdata collection as simple as possible, appropriatelystratifying sample selection, and using a small numberof well-trained data collection teams. However, wesuggest adapting the index for use with aerialphotography in future efforts to evaluate windbreaksas wildlife habitat in extensive areas.     

An alternative approach for delineating eco-sensitive zones around a wildlife sanctuary applying geospatial techniques

The dynamics, degradation, and conservation of forest ecosystems are matters of prime concerns worldwide at the present. Proper planning and management of a forest area are essentially needed to protect it from the grasp of burgeoning pressure of urban-industrial sprawl. Establishment of eco-sensitive zones (ESZs), which act as buffer areas around the core forests, is one of the key approaches towards achieving this goal. This paper deals with the applicability of geospatial techniques to identify the ESZ around an Indian wildlife sanctuary following the different rules and acts prescribed by the Government of India. Gumti Wildlife Sanctuary, located in the northeastern state of Tripura in India, has been selected here as a case study. Collected pieces of information on the distribution of biodiversity and human population in the area were also used to make the approach more holistic. As inferred from this study, remote sensing and geographical information systems were found to be easily implementable and time as well as cost-effective tools for this purpose with a distinct advantage of spatial as well as temporal accuracy in identifying the existing land use and land cover patterns in pilot assessments. However, the results indicated that only appropriate hybridization of field-based information on the biodiversity and ecological aspects of the forest as well as patterns of human interferences with the remote sensing and GIS-based data could make this approach more relevant in actual implementations.     

Maryland's Green Infrastructure—Using Landscape Assessment Tools to Identify a Regional Conservation Strategy

Maryland is growing at a very rapid pace. Compounding the problems associated with rapid growth is the scattered pattern of development that consumes an excessive amount of land and fragments the landscape. As land use changes, wildlife habitat and migration corridors are lost and normal ecosystem functions are disturbed or destroyed. While land use planners and developers are attempting to minimize such impacts, they do not always know where key natural lands and corridors are situated. The Green Infrastructure Assessment (GIA) provides this information and can be used to identify a greenway network that will protect the most critical lands in the state before they are gone foreover. Using GIS and principles of landscape ecology, the Maryland Department of Natural Resources is identifying an interconnected network of "hubs" and "corridors" that are now the focus of state and local agency deliberations and revisions. Elements of the network are being prioritized for conservation and restoration activities based on ecological parameters (e.g., sensitive species, important wetlands or riparian zones, etc.) and threat parameters (e.g., protection status, development pressure, etc.). The goal of GIA is to help identify an ecologically sound open space network, and ultimately, to incorporate the agreed upon network into state and local land conservation planning.     

A practical wind farm siting framework integrating ecosystem services — A case study of coastal China

Deploying renewable energy (RE) technologies has been acknowledged as an effective way of mitigating the pressure from increasing energy-related carbon emissions. However, evidence shows that RE deployment frequently leads to the loss and degradation of multiple ecosystem services (ES). Therefore, a sustainable RE deployment scheme should proactively identify and manage the potential trade-offs between RE production and ES provisioning. This study proposed a practical RE siting framework that integrates ES considerations (named as IES framework), and formulated a novel method that integrates Geographic Information Systems, fuzzy Analytic Hierarchy Process and Weighted Slacks-based Measure to implement this framework. Then, the suitability of wind farm sites in coastal China was evaluated and mapped using the IES framework. Results show that the suitable locations for wind farms in this region were mainly distributed in the provinces of Shandong, Hebei, Liaoning, and Jiangsu. Avian habitat and cultural ES were identified as the two services most vulnerable to wind farm deployment. A suitability map of wind farm siting in coastal China was created. Results prove that the proposed IES framework and the corresponding integrated method can effectively evaluate the trade-offs between RE production and ES provisioning and can be easily extended to guide the site selection for other REs, such as biomass, photovoltaic, and hydroelectric energy.     

Designing a conservation reserve network with minimal fragmentation: A linear integer programming approach

In the biological conservation literature, the optimum reserve site selection problem has often been addressed by using the prototype set covering and maximal covering formulations, assuming that representation of species is the only criterion in site selection. This approach usually results in a small but highly fragmented reserve, which is not useful for practical conservation planning. To improve the chances of species' persistence, it may be desirable to reduce habitat fragmentation. This paper presents a linear integer programming formulation to minimize spatial gaps between selected sites in a reserve network, which is applied to a data set on breeding birds. The authors express their willingness to share the database used in this study. Those readers who wish to have access to the data may contact Robert A. Briers at r.briers@napier.ac.uk.     

Efficiency,costs and trade-offs in marine reserve system design

With marine biodiversity conservation the primary goal for reserve planning initiatives, a site's conservation potential is typically evaluated on the basis of the biological and physical features it contains. By comparison, socio-economic information is seldom a formal consideration of the reserve system design problem and generally limited to an assessment of threats, vulnerability or compatibility with surrounding uses. This is perhaps surprising given broad recognition that the success of reserve establishment is highly dependent on widespread stakeholder and community support. Using information on the spatial distribution and intensity of commercial rock lobster catch in South Australia, we demonstrate the capacity of mathematical reserve selection procedures to integrate socio-economic and biophysical information for marine reserve system design. Analyses of trade-offs highlight the opportunities to design representative, efficient and practical marine reserve systems that minimise potential loss to commercial users. We found that the objective of minimising the areal extent of the reserve system was barely compromised by incorporating economic design constraints. With a small increase in area (<3%) and boundary length (<10%), the economic impact of marine reserves on the commercial rock lobster fishery was reduced by more than a third. We considered also how a reserve planner might prioritise conservation areas using information on a planning units selection frequency. We found that selection frequencies alone were not a reliable guide for the selection of marine reserve systems, but could be used with approaches such as summed irreplaceability to direct conservation effort for efficient marine reserve design.     

A habitat-based microscale forest classification system for zoning wood production areas to conserve a rare species threatened by logging operations in south-eastern Australia

The production of timber from native forests is presently one of the most controversial land management issues in Australia. Part of this controversy results from the potential impacts of forestry practices on forest-dependent fauna, particularly those that are rare and endangered, such as Leadbeater's Possum Gymnobelideus leadbeateri McCoy, in the forests of central Victoria, south-eastern Australia. A significant proportion of the highly limited distribution of this species overlaps with some of the most valuable wood production forests in Australia within which extensive clearfelling operations are employed to produce timber and pulpwood. These operations can destroy the habitat of G. leadbeateri. The Victoria government agency that is responsible for forest and wildlife management has devised a forest zoning system as part of the management strategies to conserve G. leadbeateri within timber production areas. This is designed to partition the forest into three types of areas: (1) where the conservation of G. leadbeateri is a priority, (2) where wood production is a priority, and, (3) where both land uses are a joint priority. The classification of areas of forest where the conservation of G. leadbeateri is the primary land use is based on an understanding of the habitat requirements of the species. The results of recent field studies, where statistical models of the habitat requirements of G. leadbeateri have been developed and their performance subsequently tested using a new dataset, highlights the need for a new basis to guide the classification of areas for the conservation of the species within wood production forests. We describe a method for devising a forest management zoning system that is based on a statistical model of the habitat requirements of G. leadbeateri and which will better integrate wood production and the conservation of the species. This procedure accounts for the uncertainty in the statistical model and, in turn, reduces the risk that areas where G. leadbeateri occurs are logged, whilst ensuring that other areas are not unnecessarily excluded from timber harvesting.     

Optimizing the removal of small fish passage barriers

Removing small artificial barriers that hinder upstream migrations of fish is a major problem in riparian habitat restoration. Because of budgetary limitations, it is necessary to prioritize barrier removal and repair decisions. These have usually been based on scoring and ranking procedures, which, although simple to use, can be very inefficient in terms of increasing the amount of accessible instream habitat. We develop a novel decision-making approach, based on integer programming techniques, which optimizes repair and removal decisions. Results show based on real datasets of barrier culverts located in Washington State that scoring and ranking is over 25% below the optimum on average and a full 100% below in the worst case, producing no net habitat gain whatsoever. This is compared to a dynamic programming method that was able to find optimal solutions in less than a second, even for problems with up to several hundred variables, and a heuristic method, which found solutions with less than a 1% average optimality gap in even less time.