Locating and protecting critical reserve sites to minimize expected and worst-case losses

There has been much recent interest in the development of systematic reserve selection methods that are capable of incorporating uncertainty associated with site destruction. This paper makes a contribution to this line of research by presenting two different optimization models for minimizing species losses within a planning region. Given limited acquisition budgets, the first minimizes expected species losses over all possible site loss patterns outside the reserve network while the second minimizes maximum species losses following the worst-case loss of a restricted subset of nonreserve sites. By incorporating the uncertainty of site destruction directly into the decision planning process, these models allow a conservation planner to take a less defensive and more strategic view of reserve selection that seeks to minimize species losses through the targeted acquisition of high-value/high-risk sites. We compare both of these methods to a more standard approach, which simply maximizes within reserve representation without regard for the varied level of threat faced by different sites and species. Results on a realistic dataset show that significant reductions in species losses can be achieved using either of these more intelligent modeling frameworks.     

First-best, second-best, and heuristic solutions in conservation reserve site selection

Previous studies which dealt with the conservation reserve site selection problem used either optimization methods, specifically linear integer programming (IP), or heuristic algorithms. The trade-off between computational efficiency versus optimality has been discussed in some articles and conflicting messages were signaled. Although the problem of suboptimality was acknowledged, some authors argued that heuristics may be preferable to exact optimization because IP models are computationally complex and may not be solvable when too many reserve sites are involved. On the other hand, some studies reported that fairly large problems could be solved easily. This paper shows that although the computational complexity argument can be valid for large reserve selection problems, by properly guiding the solver and exploiting the problem structure, formal optimization can deliver second-best (near-optimal) solutions that dominate the greedy heuristic solutions.     

Methods for reserve selection: Interior point search

Spatial reserve design concerns the planning of biological reserves for conservation. Typical reserve selection formulations operate on a large set of landscape elements, which could be grid cells or irregular sites, and selection algorithms aim to select the set of sites that achieves biodiversity target levels with minimum cost. This study presents a completely different optimization approach to reserve design. The reserve selection problem can be considerably simplified given the reasonable assumptions that: (i) maximum reserve cost is known; (ii) the approximate number of new reserves to be established is known; (iii) individual reserves need to be spatially contiguous. Further assuming the ability to construct a set of reserves in an efficient and close to optimal manner around designated reserve locations, the reserve selection problem can be turned into a search for a single interior point and area for each reserve. The utility of the proposed method is demonstrated for a data set of seven indicator species living in an conservation priority area in Southern Australia consisting of ca 73,000 selection units, with up to 10,000 cells chosen for inclusion in a reserve network. Requirements (ii) and (iii) above make interior point search computationally very efficient, allowing use with landscapes in the order of millions of elements. The method could also be used with non-linear species distribution models.     

The importance of in situ site loss in nature reserve selection: Balancing notions of complementarity and robustness

Because the threat of habitat destruction can never be entirely eliminated, there is a legitimate concern that some reserve networks, especially highly complementary ones with minimal species overlap, may be predisposed to severe losses in species representation if one or more core reserve sites are destroyed. In order to address this problem in a systematic way, we propose the use of two different optimization models for designing complementary reserve networks that are also highly robust to possible site losses. Given limited budgets, the first maximizes expected species representation over all possible site loss patterns while the second maximizes a combination of representation given all sites and remaining representation following the worst-case loss of a restricted subset of reserve sites. By incorporating reserve loss in fundamentally different ways, these two models provide a range of options in terms of information requirements, assumptions about risk aversion, and structural complexity. We compare both of these methods to a more standard approach, which completely ignores the inherent risk posed by reserve site loss. Results confirm that significantly more robust solutions can be obtained for a marginal decrease in initial species representation within the reserve system.     

Accounting for habitat loss rates in sequential reserve selection: Simple methods for large problems

We develop reserve selection methods for maximizing either species retention in the landscape or species representation in reserve areas. These methods are developed in the context of sequential reserve selection, where site acquisition is done over a number of years, yearly budgets are limited and habitat loss may cause some sites to become unavailable during the planning period. The main methodological development of this study is what we call a site-ordering algorithm, which maximizes representation within selected sites at the end of the planning period, while accounting for habitat loss rates in optimization. Like stochastic dynamic programming, which is an approach that guarantees a globally optimal solution, the ordering algorithm generates a sequence in which sites are ideally acquired. As a distinction from stochastic dynamic programming, the ordering is generated via a relatively fast approximate process, which involves hierarchic application of the principle of maximization of marginal gain. In our comparisons, the ordering algorithm emerges a clear winner, it does well in terms of retention and is superior to simple heuristics in terms of representation within reserves. Unlike stochastic dynamic programming, the ordering algorithm is applicable to relatively large problem sizes, with reasonable computation times expected for problems involving thousands of sites.     

Optimal reserve selection in a dynamic world

In this paper we present a novel expansion of the problem of optimal reserve site selection over time. We explore a case where areas with valuable biodiversity cannot all be protected immediately due to budget restrictions and there is a probability of species extinction on reserved as well as non-reserved sites. Add to this the risk of land-use conversion facing all non-reserved areas. We furthermore introduce a new type of control by making the planning authorities have the option to sell reserved land on which biodiversity value has decreased. We formulate and solve this problem through stochastic dynamic integer-programming. The current study shows that, due to the dynamic and stochastic nature of biodiversity evolution, the inclusion of a swapping option may increase overall efficiency. Finally, we test a number of decision criteria (heuristics) to investigate alternatives to the cumbersome task of determining the true optimum.     

Within-site habitat configuration in reserve design: A case study with a peatland bird

This study assesses the effects of considering within-site habitat configuration when designing reserve networks. This attribute takes all its importance in situations where the long-term integrity of (within-site) habitat patches cannot be preserved without protecting their surrounding environment. We addressed this issue through the concrete problem of selecting a reserve network of natural peatlands in southern Québec, Canada. We used a reserve-selection algorithm that minimized the total number of peatlands to include within networks. The algorithm was constrained to include peatlands containing habitat patches that met specific size thresholds. Five habitat-clustering thresholds were used to set the eligibility of each site to the selection process. The resulting reserve networks were evaluated according to their representation efficiency and to the expected consequences for the Palm Warbler (Dendroica palmarum), an area and isolation-sensitive bird restricted to peatlands in southern Québec.Constraining the algorithm to include peatlands showing increasingly larger patches of habitats led to larger networks, both in terms of area and number of sites, and to networks composed of smaller sites. These effects increased with the representation target (i.e., the % of each habitat preserved). With respect to the Palm Warbler, selecting peatlands with larger patches of habitats had only an indirect effect on its site-occupancy pattern. Indeed, despite the fact that the probability of occurrence of the warbler was negatively correlated with the size of habitat patches, the habitat-clustering threshold influenced the incidence of the warbler mainly via its effect on the physical attributes of the selected networks - including the area, isolation level, and the number of selected sites. Because increasing the habitat-clustering threshold led indirectly to a greater regional availability of prime breeding habitats for the Palm Warbler, it mitigated the severe negative impact of an hypothetical alteration or destruction of non-selected peatlands. Our study thus emphasizes the importance of determining how the different factors describing within-site configuration are correlated with other intrinsic characteristics of the sites available to the selection process before opting for a site-selection strategy.     

基于多目标粒子群的土地整理项目选址模型

土地整理项目选址实质上是一个多目标空间优化问题,将传统选址方法用于解决多目标土地整理项目选址存在明显不足。该文提出了一种基于多目标粒子群的土地整理项目选址模型,归纳了土地整理项目选址的选址规则,提取3个能够体现土地整理项目选址目的及意义的目标函数,即新增耕地潜力最高、空间分区集中连片、土地适宜性评价指数最高,同时考虑了土地整理项目最小新增耕地率、实施规模2类约束条件,并详细阐述了算法的核心思想、矢量编码策略、状态更新机制等内容,最后选取湖北省嘉鱼县为试验区,验证了模型的可行性和有效性,结果表明通过对目标的权重调控可以得到不同目标偏好的土地整理项目选址方案,该文所构建模型在土地整理实践中具有可操作性,提供的选址方案科学合理,为土地利用规划和土地利用调控管理提供支持。     

青藏高原雪灾高风险区饲草料储备库选址分析

为了更好的发挥饲草料储备库在灾害风险管理中的应用,提高高原牧区灾害韧性。该研究将雪灾高风险区与实际多年雪灾发生区相结合,采用P-中值模型提出了饲草料储备库的选址分析方法,并利用贪婪取走启发式算法对模型求解。以青海省雪灾高风险区为例,选址分析得出治多、玛沁、都兰3座饲草料储备库和麻多、扎朵、秋智等13座饲草料储备点的分布位置与储备规模。其中治多储备规模为21.0万t;玛沁储备规模为13.2万t;都兰储备规模为13.5万t。布局上形成了以储备库为中心,储备点为外围的二元结构,验证了分析方法的合理性和可行性。从而为高原牧区饲草料储备库的选址提供参考性理论依据和可操作性方法。     

Heuristic algorithms vs. linear programs for designing efficient conservation reserve networks: Evaluation of solution optimality and processing time

Systematic approaches to efficient reserve network design often make use of one of two types of site selection algorithm; linear programs or heuristic algorithms. Unlike with linear programs, heuristic algorithms have been demonstrated to yield suboptimal networks in that more sites are selected in order to meet conservation goals than may be necessary or fewer features are captured than is possible. Although the degree of suboptimality is not known when using heuristics, some researchers have suggested that it is not significant in most cases and that heuristics are preferred since they are more flexible and can yield a solution more quickly. Using eight binary datasets, we demonstrate that suboptimality of numbers of sites selected and biodiversity features protected can occur to various degrees depending on the dataset, the model design, and the type of heuristic applied, and that processing time is not dramatically different between optimal and heuristic algorithms. In choosing an algorithm, the degree of suboptimality may not always be as important to planners as the perception that optimal solvers have feasibility issues, and therefore heuristic algorithms might continue to be a popular tool for conservation planning. We conclude that for many datasets, feasibility of optimal algorithms should not be a concern and that the value of heuristic results can be greatly improved by using optimal algorithms to determine the degree of suboptimality of the results.     

基于改进粒子群算法的车辆转向梯形机构优化

通过对车辆转向机构的尺寸和定位参数进行优化,能有效减小车辆转向机构的实际运动轨迹和理论运动轨迹间误差,进而有效改善车辆的操纵性能和提高转向安全性。该文研究了转向梯形机构的工作原理及其对车辆转向性能的影响,建立了转向梯形机构的非线性优化模型;然后引入越界检测函数改进传统粒子群优化算法,并给出了求解转向梯形机构非线性优化模型的方法;编制了改进粒子群算法的实现程序,并对3款不同车型的转向梯形机构进行了优化设计;最后选取3种不同智能算法分别对途乐GRX转向梯形机构进行多组优化试验。试验结果表明,改进粒子群算法的收敛速度快于传统粒子群算法和基于模拟退火的粒子群算法,求解精度略逊于基于模拟退火的粒子群算法,但仍能保证求解精度。     

Optimizing reserve expansion for disjunct populations of San Joaquin kit fox

Expanding habitat protection is a common strategy for species conservation. We present a model to optimize the expansion of reserves for disjunct populations of an endangered species. The objective is to maximize the expected number of surviving populations subject to budget and habitat constraints. The model accounts for benefits of reserve expansion in terms of likelihood of persistence of each population and monetary cost. Solving the model with incrementally higher budgets helps prioritize sites for expansion and produces a cost curve showing funds required for incremental increases in the objective. We applied the model to the problem of allocating funds among eight reserves for the endangered San Joaquin kit fox (Vulpes macrotis mutica) in California, USA. The priorities for reserve expansion were related to land cost and amount of already-protected habitat at each site. Western Kern and Ciervo-Panoche sites received highest priority because land costs were low and moderate amounts of already-protected habitat resulted in large reductions in extinction risk for small increments of habitat protection. The sensitivity analysis focused on the impacts of kit fox reproductive success and home range in non-native grassland sites. If grassland habitat is lower quality than brushland habitat resulting in higher annual variation in reproductive success or larger home ranges, then protecting habitat at the best grassland site (Ciervo-Panoche) is not cost-efficient relative to shrubland sites (Western Kern, Antelope Plain, Carrizo Plain). Finally, results suggested that lowest priority should be given to three relatively high-cost grassland sites (Camp Roberts, Contra Costa, and Western Madera) because protecting habitat at those sites would be expensive and have little effect on the expected number of surviving kit fox populations.     

Designing spatially-explicit reserve networks in the presence of mandatory sites

In the selection of reserve networks there are special sites whose ecologic, strategic or morphologic values dictate their inclusion. The existence of regional rare or confined-distribution species is one among other reasons that often determines the existence of such mandatory sites. Moreover, quite often these mandatory sites are located far apart. Although several methods have been proposed to accommodate structural connectivity in reserve selection, they were not devised to deal specifically with such mandatory sites. Those that encourage aggregation of sites by means of criteria incorporated in the objective function do not seem suitable to acquire consistent connectivity levels in the presence of mandatory sites. Methods that enforce “full connectivity” tend to produce long and narrow solutions, which results in efficiency deficits and biological unsuitability, as they force the selection of more sites of less quality to ensure connectivity. Hence specific methods to select ecological reserves when mandatory sites exist are needed. Here we discuss and propose a 0-1 linear programming model to deal with this issue. The model was applied in two data sets of forest breeding birds and butterflies. Its solutions and computational performances are discussed.     

Hindsight in marine protected area selection: A comparison of ecological representation arising from opportunistic and systematic approaches

Systematic approaches to site selection for marine protected areas (MPAs) are often favored over opportunistic approaches as a means to meet conservation objectives efficiently. In this study, we compared analytically the conservation value of these two approaches. We locate this study in Danajon Bank, central Philippines, where many MPAs were established opportunistically based on community preference, with few if any contributions from biophysical data. We began by identifying the biophysical data that would have been available when the first MPA was created in Danajon Bank (1995). We next used these data with the reserve selection software Marxan to identify MPAs that covered the same area as is protected under the current set of MPAs (0.32% of the total study area) and that would protect the greatest number of conservation targets at the lowest cost. We finally compared the conservation value of the current MPAs to the value of those selected by Marxan. Because of the dearth of biophysical data available in 1995 and the small area currently under protection, Marxan identified multiple configurations of MPAs that would protect the same percentage of conservation targets, with little differentiation among sites. Further, we discovered that the costs of obtaining and analyzing these data to be used for conservation planning would have been large relative to resources typically available to conservation planners in developing countries. Finally, we found that the current set of MPAs protected more ecological features than would be expected by chance, although not as many as could be protected using a systematic approach. Our results suggest that an opportunistic approach can be a valuable component of conservation planning, especially when biophysical data are sparse and community acceptance is a critical factor affecting the success of an MPA.     

Reserve selection with minimum contiguous area restrictions: An application to open space protection planning in suburban Chicago

Conservation efforts often require site or parcel selection strategies that lead to spatially cohesive reserves. Although habitat contiguity is thought to be conducive to the persistence of many sensitive species, availability of funding and suitable land may restrict the extent to which this spatial attribute can be pursued in land management or conservation. Using optimization modeling, we explore the economic and spatial tradeoffs of retaining or restoring grassland habitat in contiguous patches of various sizes near the Chicago metropolitan area. The underlying mathematical construct is the first exact, generalized formulation that directly models spatial contiguity in optimal reserve selection. The construct allows conservation planners to analyze and weigh different minimum contiguous habitat size requirements that are to be used in specific land acquisition or retention projects.     

集成"适宜性-集聚性-稳定性"的永久基本农田储备区划定

永久基本农田储备区是永久基本农田的直接补划来源，划定并建设永久基本农田储备区对于稳定永久基本农田保护区格局，保障国家粮食安全具有重要意义。该研究从适宜性、集聚性、稳定性三个维度构建永久基本农田储备区评价体系，在一般耕地区开展综合质量评价基础上划定永久基本农田储备区；进一步结合三维魔方空间分类方法，制定了永久基本农田储备区的整治分区方案，并以江苏省常州市金坛区开展了方法实证。结果表明：1）从约束准则和评价准则两方面构建永久基本农田储备区划定准则，有利于提高永久基本农田储备区筛选的科学性和合理性；2）研究区基于耕地适宜性、集聚性、稳定性指标综合评价，在研究区划定了永久基本农田储备区7 307.8 hm2；3）结合耕地综合质量和空间分类方法可将永久基本农田储备区划分为综合利用潜力区、生产改善潜力区、发展提升潜力区、生产改善-发展提升潜力区等4种类型，针对不同类型区实施相应的整治措施，可进一步提升永久基本农田储备区的质量，为后续永久基本农田补划提供了坚实的基础。     

基于生态服务价值的潮白河上游土地利用优化

生态环境安全和人类发展息息相关,以潮白河上游森林生态服务价值和生态服务总价值为目标,以约束函数和转化规则为条件,利用灰参数线性规划理论和CLUE-S模型对该区2008年土地利用现状进行了数量结构优化和空间格局配置。结果表明：优化配置后的林地面积和森林生态服务价值较2008年均有显著增加,且后者增加幅度大于前者,说明森林单位面积生态服务价值提高,林地结构得到改善;随着草地和未利用地向林地和居民工矿用地转化,生态服务总价值有所增加,重点表现在调节服务和支持服务两方面价值上。该区域近年来经济利益驱动的发展模式给首都可持续发展带来巨大压力,土地退化和环境破坏须通过资源优化得以控制和改善。     

Replacement cost: A practical measure of site value for cost-effective reserve planning

Conservation needs are often in direct competition with other forms of land-use, and therefore protection of biodiversity must be cost-efficient. While common reserve selection algorithms address this problem, quantitative planning tools often suggest an optimal set of sites that is not necessarily convenient for practical conservation. Besides cost-effective solutions we require flexibility if land-use conflicts are to be effectively resolved. We introduce a novel concept for site value in quantitative reserve planning. Replacement cost refers to the loss in solution value given that the optimal cost-efficient solution cannot be protected and alternative solutions, with particular sites forcibly included or excluded, are needed. This cost can be defined either in terms of loss of biological value or in terms of extra economic cost, and it has clear mathematical definitions in the context of benefit-function-based reserve planning. A main difference with the much-used concept of irreplaceability is that the latter tells about the likelihood of needing a site for achieving a particular conservation target. Instead, replacement cost tells us at what cost (biological or economic) can we exclude (or include) a site from the reserve network. Here, we illustrate the concept with hypothetical examples and show that replacement-cost analysis should prove useful in an interactive planning process, improving our understanding of the importance of a site for cost-efficient conservation.     

黄河三角洲自然保护区土地利用格局空间优化模拟

空间优化模型能够实现多管理目标下的土地利用格局空间优化,为管理者制定保护政策提供参考。该文以黄河三角洲自然保护区为研究区域,基于保护区的多目标管理需求,设计了3种用于协调丹顶鹤生境保护和社区可持续发展的情景模式,并采用土地利用空间优化(land use pattern optimization,LUPO)模型,模拟实现了不同情景模式下的保护区土地利用格局空间优化配置。模拟结果表明:情景A通过将光滩和芦苇滩等转为丹顶鹤喜好的翅碱蓬滩涂和柽柳-翅碱蓬滩涂,实现使丹顶鹤适宜生境面积增加30%的生态效益目标,但年经济收益增幅仅为11%;情景B通过将农田、芦苇滩和光滩等转为年经济效益更高的虾池,使区域年经济效益增长54%,但丹顶鹤适宜生境面积变化较小,生境更为破碎化;情景C通过将光滩等转为翅碱蓬滩涂,将农田等转为虾池,分别使丹顶鹤适宜生境面积增加24%和区域年经济效益增长41.3%,是一种双赢方案。研究结果表明,该模型可用于保护区土地利用格局空间优化,协调物种保护和经济发展之间的平衡关系,但需对模型结构和参数进一步优化设计。     

采用SCS-CN水文模型和GIS确定雨水集蓄工程的位置

针对北京西部清水河上游山区生产生活用水日趋紧张的问题,该文应用遥感与地理信息系统软件处理TM影像、土壤和质地图及数字高程模型等基础数据,结合soil conservation service(SCS)曲线数法计算径流量,根据雨水集蓄工程技术规范构建了雨水集蓄工程位置选择约束集。在此基础上,运用地理信息系统软件对坡度、径流潜力及集水路径的空间及属性数据进行叠加和邻域分析,得到适宜的雨水集蓄工程位置。主要结果如下:适宜修建蓄水坑塘的面积4.24km2、蓄水池位置46处、拦水坝位置50处、大口井位置53处、适宜庭院集雨区的面积4.95km2。结果可为合理开发利用雨水资源及工程建设提供理论支撑和科学指导。