Maximizing Species Representation under Limited Resources: A New and Efficient Heuristic

The maximal covering species problem (MCSP) is becoming an accepted method for selecting networks of reserves for the preservation of species and their habitats. Drawing on experience with the MC location P (MCLP), we expect that the objective function in the region of the optimum is quite flat. This implies many equal-optimal and near-optimal solutions for any particular problem. We propose a new type of heuristic for the MCSP: an interchange heuristic which frequently provides a better solution than greedy adding heuristics now commonly used. The proposed interchange heuristic, with multiple random starts, gives one a range of alternative sets of sites rather than a single mathematically selected solution, from which a final satisfactory solution can be chosen.     

Novel operations research methods for efficiently determining irreplaceable sites for conservation

We examine the irreplaceability of sites in the context of the species set covering problem and the maximal covering species problem. We show that a succession of 0-1 programming problems can be solved to quickly determine the set of irreplaceable sites. For the widely available Oregon data set, we find a general lack of trend in the number of irreplaceable sites with the number of sites available for selection used. Moreover, we observe that irreplaceability at one level of resource may not be a predictor of irreplaceability at a higher or a lower level of resource. Finally, we investigate the economic value of irreplaceable sites by trial removals of those sites. This paper is dedicated to the memory of Dr. Charles S. ReVelle.     

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.     

Representational success: A new paradigm for achieving species protection by reserve site selection

Models for designing habitat reserve networks have focused on minimizing the number of sites necessary to cover each species one or more times. A solution to this problem is usually one from among a large number of alternative optimal configurations of sites. This paper develops an iterative method for building reserve networks that produces an optimal solution to the species set covering problem (SSCP) and also maximizes the number of species covered two or more times, three or more times, and so on, conditional on the solution to the previous iteration. We refer to this as representational success. Thus, a pareto optimal species set covering is achieved that is preferable to an arbitrary optimal solution to the SSCP.     

The SITES reserve selection system: A critical review

Numerous models have been put forth to help with the growing demand for the establishment of biodiversity reserves. One site selection model that has been used in several recent studies is SITES [S.J. Andelman, I. Ball, F.W. Davis and D.M. Stoms, SITES V 1.0: an analytical toolbox for designing ecoregional conservation portfolios, Unpublished manual prepared for the nature conservancy, 1999, 1–43. (available at )]. SITES includes two heuristic solvers: based on Greedy and Simulated Annealing. We discuss the formulation of the SITES model, present a new formulation for that problem, and solve a number of test problems optimally using off-the-shelf software. We compared our optimal results with the SITES Simulated Annealing heuristic and found that SITES frequently returns significantly suboptimal solutions. Our results add further support to the argument, started by Underhill [L.G. Underhill, Optimal and suboptimal reserve selection algorithms, Biol. Conserv. 70 (1994) 85–87], continuing through Rodrigues and Gaston [A.S.L. Rodrigues and K.J. Gaston, Optimization in reserve selection procedures – why not?, Biol. Conserv. 107 (2002) 123–129], for greater integration of optimal methods in the reserve design/selection literature.     

A combined hydrologic simulation and landscape design model to prioritize sites for wetlands restoration

Most landscape design models have been applied to the problem of maximizing species richness in a network of nature reserves. This paper describes a combined hydrologic simulation and landscape design model designed to prioritize sites for wetlands restoration, where the objective is to maximize the amount of nutrients in non-point-source runoff attenuated in the restored wetlands. Targeted site selection in four small watersheds in the Central Valley resulted in predicted levels of nitrogen attenuation two to eight times greater than that from maximizing wetland area without consideration of the location of the restoration sites. Disclaimer  The views expressed in this paper are those of the author and do not necessarily represent those of the US Environmental Protection Agency. No official Agency endorsement should be inferred.     

Integrated response plot designs for indicators of desertification

The improvement of land management practices on lands susceptible to desertification requires information on the status and condition of the existing resources as well as any change occurring in the resource condition over time. The Environmental Monitoring and Assessment Program (EMAP) of the U.S. Environmental Protection Agency has developed a statistical survey design for monitoring the condition of ecological resources on large spatial scales. EMAP-Rangelands used a uniformity sampling study in 1993 to evaluate response plot designs for three categories of indicators (soils, vegetation, and spectral reflectance) to be used for monitoring ecological condition of a site. The response plot design study was developed to integrate on-site measurements for the three indicator categories. The study was conducted on the Colorado Plateau in southern Utah in three rangeland resource classes (grassland, desertscrub, and conifer woodland) of differing productivity levels in an attempt to develop a common plot design for all three resource classes. Basic measurement units were developed to facilitate integration of data collection. Preliminary spatial analysis of the sampling study found considerable differences in variation patterns among the study sites and measurement categories for the indicator classes used by EMAP-Rangelands. Evidence of substantial trends in the indicator measurements on monitoring sites relative to regional trends leads to the conclusion that nonstationary spatial models for biological processes on a monitoring site may be needed to fulfill the requirements for developing plot designs and indicator criteria.The U.S. Environmental Protection Agency, through the Office of Research and Development, funded the research described here. This paper has been subjected to the Agency's peer and administrative review and has been approved as an EPA publication. The U.S. Government has the right to retain a nonexclusive, royalty-free license in and to any copyright covering this article.     

Reserve Design to Maximize Species Persistence

We develop a reserve design strategy to maximize the probability of species persistence predicted by a stochastic, individual-based, metapopulation model. Because the population model does not fit exact optimization procedures, our strategy involves deriving promising solutions from theory, obtaining promising solutions from a simulation optimization heuristic, and determining the best of the promising solutions using a multiple-comparison statistical test. We use the strategy to address a problem of allocating limited resources to new and existing reserves. The best reserve design depends on emigration, dispersal mortality, and probabilities of movement between reserves. When movement probabilities are symmetric, the best design is to expand a subset of reserves to equal size to exhaust the habitat budget. When movement probabilities are not symmetric, the best design does not expand reserves to equal size and is strongly affected by movement probabilities and emigration rates. We use commercial simulation software to obtain our results.     

Linking Water Science to Policy: Results from a Series of National Workshops on Water

To ensure science better informs the decision-making process, researchers and policy/program managers need to understand and respect each other's way of working, culture and operational timelines. However, there is little practical guidance on how this should be done and even less documented experience with specific mechanisms that better link these two groups. The published literature on information transfer has largely emphasized the dissemination of standard packages of information to ill-defined constituencies whose needs for scientific information are not well understood. Environment Canada's National Water Research Institute, on behalf of the Canadian Council of Ministers of the Environment, led a series of “Linking Water Science to Policy Workshops” as one such mechanism by which recent science could be delivered to practitioners, and practitioners could identify their research needs to scientists and research managers. There is a pressing need to explore and share experiences using creative mechanisms for sustained dialogue and networking between scientists and policy and program managers. The lessons learned from the workshop series and the need for science to continually inform the decision-making process has particular relevance for Canada's Ecosystem Initiatives given their integrated, place-based focus on long-term restoration and protection, and the challenge of continually changing ecosystems.The Canadian Crown reserves the right to retain a non-exclusive, royalty free licence in and to any copyright.     

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.     

Models for preserving species diversity with backup coverage

The problem of selecting land for preservation of species has been a rich and active area of research over the past two decades. Typically, reserve selection models have tried to maximize species diversity by preserving areas that contain the greatest number of species. However, several studies have shown that seldom do these species-rich areas contain the rarest species most in need of protection. Most reserve selection models seek to maximize diversity by choosing parcels so that all species are covered by or represented in at least one parcel. This approach would usually be expected to result in coverage by a single parcel for the rarest species, especially for those that do not coincide with more abundant species. It is precisely these rare species, however, that would be lost or whose survivability would be most challenged, if the single parcels in which they are represented became unavailable due to some unforeseen event. In this paper, we introduce to reserve selection models the concept of secondary, or backup, coverage of species. Briefly stated, a species is said to have backup representation in the system of reserves if it is covered by, or represented in, two or more parcels. Having backup coverage guarantees that every species is still covered in the event that a natural or man-made catastrophe makes a given parcel uninhabitable. The results show that backup coverage can be obtained at little additional cost (as expressed by the number of parcels selected). Bi-objective formulations that trade-off primary with backup coverage show that backup coverage can be guaranteed for larger numbers of species with little reduction in primary coverage.     

Landsat 8卫星OLI遥感影像在生态环境监测中的应用研究

利用美国2013年2月发射的Landsat 8卫星上运营性陆地成像仪OLI获取的太湖流域遥感影像数据,开展了其在大气能见度、蓝藻水华及建设用地等生态环境监测领域中的应用研究。研究表明,Landsat 8卫星向未来延续了Landsat系列的长时期对地观测能力,且观测性能有所优化,适合对区域能见度、湖泊蓝藻水华、生态系统格局等生态环境问题进行反演和分析,是生态环境监测的重要遥感信息源。     

Applying mathematical programming to reserve selection

During the last 10–15 years heuristic methods have been developed for problems in optimal reserve selection. Unfortunately, there is no guarantee that heuristics will find optimal solutions. In recognizing this limitation, analysts have formulated reserve selection problems as set covering problems, for which matrix reduction and integer (0/1) programming can be used to find optimal solutions. In this paper we restate the set covering formulation and review solution techniques. A new 0/1 programming model, which is a generalization of the set covering model, is then presented and applied to a hypothetical reserve selection problem. Objectives of minimizing the number of sites selected and maximizing the number of species represented are addressed. Solutions which characterize the tradeoffs between these objectives provide a rich set of information for planners and decision makers. Applications of mathematical programming to related problems in land use planning and forestry are also discussed.     

Spatial attributes and reserve design models: A review

A variety of decision models have been formulated for the optimal selection of nature reserve sites to represent a diversity of species or other conservation features. Unfortunately, many of these models tend to select scattered sites and do not take into account important spatial attributes such as reserve shape and connectivity. These attributes are likely to affect not only the persistence of species but also the general ecological functioning of reserves and the ability to effectively manage them. In response, researchers have begun formulating reserve design models that improve spatial coherence by controlling spatial attributes. We review the spatial attributes that are thought to be important in reserve design and also review reserve design models that incorporate one or more of these attributes. Spatial modeling issues, computational issues, and the trade-offs among competing optimization objectives are discussed. Directions for future research are identified. Ultimately, an argument is made for the development of models that capture the dynamic interdependencies among sites and species populations and thus incorporate the reasons why spatial attributes are important.     

Mapping the Spatial Variability of Plant Diversity in a Tropical Forest: Comparison of Spatial Interpolation Methods

Knowledge of the spatial distribution of plant species is essential to conservation and forest managers in order to identify high priority areas such as vulnerable species and habitats, and designate areas for reserves, refuges and other protected areas. A reliable map of the diversity of plant species over the landscape is an invaluable tool for such purposes. In this study, the number of species, the exponent Shannon and the reciprocal Simpson indices, calculated from 141 quadrat sites sampled in a tropical forest were used to compare the performance of several spatial interpolation techniques used to prepare a map of plant diversity, starting from sample (point) data over the landscape. Means of mapped classes, inverse distance functions, kriging and co-kriging, both, applied over the entire studied landscape and also applied within vegetation classes, were the procedures compared. Significant differences in plant diversity indices between classes demonstrated the usefulness of boundaries between vegetation types, mapped through satellite image classification, in stratifying the variability of plant diversity over the landscape. These mapped classes, improved the accuracy of the interpolation methods when they were used as prior information for stratification of the area. Spatial interpolation by co-kriging performed among the poorest interpolators due to the poor correlation between the plant diversity variables and vegetation indices computed by remote sensing and used as covariables. This indicated that the latter are not suitable covariates of plant diversity indices. Finally, a within-class kriging interpolator yielded the most accurate estimates of plant diversity values. This interpolator not only provided the most accurate estimates by accounting for the indices' intra-class variability, but also provided additional useful interpretations of the structure of spatial variability of diversity values through the interpretation of their semi-variograms. This additional role was found very useful in aiding decisions in conservation planning.     

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.     

Land Cover Changes as a Result of Environmental Restrictions on Nitrate Leaching in Dairy Farming

Nitrate leaching forms an important environmental problem because it causes pollution of groundwater and surface water, and adds to already problematic eutrophication. This study analyses the impact of reductions in nitrate leaching on land cover decisions of dairy farms, of which the activities make an important contribution to nitrate leaching. As the level of nitrate leaching depends on groundwater depth as well as on the supply of nitrogen, spatial variation in groundwater levels will cause a spatial variation in land cover under restrictions on nitrate leaching. A non-linear partial optimisation model for the economic and ecological aspects of the problem were used to show how land cover and dairy farms' financial balances change when nitrate losses are reduced. The model is spatially explicit, and describes nitrate leakage and yields of maize and grass as a function of groundwater depth, including the effects of various grazing systems. The model analyses the decisions of a risk neutral agent who minimises costs under the following constraints: (i) production, feed requirements and mass balances for fodder; (ii) constraints for nitrate leaching. Economic costs are attributed to increased costs of fodder and processing of manure when nitrate restrictions are tightened. An important result of the study is the variation in compliance costs and land cover for maize and grass production brought about by spatial variation in groundwater depth. While the effects are negligible for some shallow groundwater classes, it is extremely difficult in other classes – if not impossible – to obtain the EU standard of maximum admissible losses of 34 kg N ha^–1 at low costs. The study shows an important reduction in land cover by maize.     

An Approach to Reaeration Coefficient Modeling in Local Surface Water Quality Monitoring

Reaeration coefficient (k ₂) for River Atuwara, Ogun State, Nigeria was calculated from dissolved oxygen and biochemical oxygen demand data collected over period of 3 months covering the two prevailing climatic seasons in the country. Both the Akaike and Bayesian information criteria were used in the selection and analysis of ten models to identify the most suitable reaeration coefficient (k ₂) model for Atuwara River. Models that passed the confidence limit were subjected to model evaluation using measures of agreement between observed and predicted data such as percent bias, Nash–Sutcliffe efficiency, and root mean square observation standard deviation ratio. The used approach yield better results than empirical models developed for local conditions while it is also useful in conserving scarce resources.     

山东省省级自然保护区人类活动遥感监测与评价

基于2018年高分系列遥感影像数据,提取山东省省级自然保护区人类土地利用活动信息,探讨人类活动对山东省省级自然保护区的影响。结果表明,自然保护区人类活动总面积占保护区总面积的22.2%,人类活动影响指数介于0~0.01368。不同类型的自然保护区人类活动面积不同,主要影响因子差异明显,森林生态类保护区以农业用地为主,内陆湿地类保护区以养殖场为主。内陆湿地类保护区是受到人类干扰程度最为严重的保护区类型,野生动物类保护区受到人类影响最小。