最优化设计连续的自然保护区

生境破碎是导致生物多样性损失的重要原因之一,避免生境破碎的一个有效方式是建立连续的自然保护区使物种可在保护区内自由移动。不加选择地把大片土地都转为保护区是实现连续的一个途径,但资源是有限的,应当以最优的方式分配。如何最优化设计生态上和经济上都有效的保护区成为生物保护领域一个重要议题。从一组备选地块中选择一部分组成自然保护区,这样的问题主要有两种解法:启发式方法和最优化方法。启发式方法虽然灵活且运算速度快但不能保证最优解因而可能导致稀缺资源的浪费,最优化方法保证得到的解是最优的但建模和运算存在困难。建立一个线性整数规划模型用于设计一个最小的连续保护区,用Dantzig剪切法消除循环确保形成一个连续的树,对应一个连续的保护区,检验了模型的计算效率。结果显示,模型可在合理时间内解决一个包含100个备选地块和30个物种的连续保护区设计问题,计算效率显著优于同类目的的其它方法。以美国伊利诺伊州Cache河流域11种濒危鸟类的保护区设计为例说明了该方法的应用,设计了两种情况下连续的保护区。讨论了模型的局限和数据问题。     

自然保护区空间特征和地块最优化选择方法

自然保护区是保护物种和生态系统的有效方式,用于建立自然保护区的资源却是稀缺的,这就提出这样的问题：1)自然保护区在空间上应具有什么特征才是有效的;2)如何从许多备选地块中选择一部分组成自然保护区对稀缺资源进行最优化分配。为促进物种生存繁衍,在地块选择时应考虑保护区空间特征。这篇文章综述了该领域最近的研究进展,重点介绍了结合各种空间特征的保护区地块最优化选择模型。介绍了4个主要的空间特征：1)连续,2)间隔和距离,3)边界和集约,4)面积以及核心区和缓冲区。以前用启发式算法求解这些问题,但研究已显示该法不能保证资源的最优化分配。空间特征也可用线性整数规划模拟,用最优化软件求得最优解。目前的线性整数规划模型和软件还不能有效解决大型的保护区地块选择问题,计算效率易成为实际应用的瓶颈。文章概括了我国目前自然保护区设计领域的研究状况和面临的问题,最后讨论了该领域新的研究方向。     

自然保护区气候变化风险及其评估——以达里诺尔国家级自然保护区为例

从基于风险管理应对气候变化的基本理论框架和气候变化对我国自然保护区管理的挑战出发,明确了自然保护区气候变化风险的涵义,并以达里诺尔自然保护区鸟类及其赖以生存的水体、草地、林地、沼泽地生境为研究对象,对达里诺尔自然保护区气候变化风险及其变化趋势进行评估和预测.结果表明: 1997—2010年,达里诺尔自然保护区及其水体、草地、林地、沼泽地生境的气候变化风险均呈明显的波动性变化趋势,1999、2001、2005、2008年保护区及其4类生境和2002、2004年沼泽地生境均处于风险状态;与2010年相比,情景A、B、C下2020、2030年保护区及其4类生境的气候变化风险均有所增强;各类生境的气候变化风险存在显著差异,其中,沼泽地生境的气候变化风险较为突出,与其对气候变化的敏感性和丰富的鸟类分布密切相关;人类对水资源、草地资源的过度利用会加剧气候变化对自然保护区的不利影响及其对应的生态风险.总体上,气候变化风险在达里诺尔自然保护区已经显现,气候变化风险管理有助于保持并增强自然保护区的生物多样性保护功能.     

保护区的大小和数量效果的模拟研究*

对一个既包含局域种群动态,又包含集合种群侵占率的模型进行了计算机模拟,结果表明:(1)集合种群的存活时间随着保护区数目的增大先增大而后减小,即保护区的数目维持在中等大小时最有利于种群在集合种群水平上的存活。(2)这个最优值与保护区的总面积密切相关。这意味着在自然保护区的设置中,如果保护区的总面积一定,那么最佳决策不是保留一个大的完整的自然保护区,而是建立一个由数目相对较多而面积相对较小的保护区组成的网络。这对于自然保护区的设置有着重要的意义。     

基于空间生态集合覆盖模型的自学习禁忌搜索算法在保护区空间选址中的应用——以戴云山为例

自然保护区规划是保护生物多样性的有效方式.传统保护区规划方法只能识别物种保护的重点区域,无法科学确定保护区的适宜面积.地块选择方法基于数学模型,从规划区域中选择部分地块组成自然保护区,保护特定物种或生态系统,是缓解生态保护与开发利用矛盾的重要手段.现有地块选择法未考虑各单元生态差异,且最优化算法存在计算效率的瓶颈.本文首先构建适用于森林生态系统的生态值赋分评价体系,据此计算戴云山生态值并绘制其分布图;然后,结合生态值建立生态集合覆盖模型(ESCP),并基于ESCP嵌入空间紧凑性提出空间生态集合覆盖模型(SSCP);最后,利用寻优性能良好的自学习禁忌搜索算法(STS)搜索各保护目标下的近似最优选址方案,给出福建省戴云山现有建成区优化方案.结果表明: 戴云山生态值计算结果在空间分布上存在明显差异;ESCP比原集合覆盖模型(SCP)能产生生态值更高的选址方案;SSCP在ESCP基础上对生态值较高区域有聚集作用,且周长权重越大,聚集效果越明显;建议现保护区可向外拓展136 km²,并将西北向分布长苞铁杉的地块纳入保护区范围.研究结果为实现戴云山保护区可持续发展及土地资源优化配置提供了优化方案,也可为我国森林生态系统类型的自然保护区设计提供新思路.     

滇西南四个自然保护区鱼类多样性及评价指标探究

为了解滇西南怒江水系的南滚河自然保护区、南捧河自然保护区、永德大雪山自然保护区及澜沧江水系的澜沧江自然保护区鱼类多样性和变化趋势, 探讨其差异和变化的原因, 本文采用β多样性指数分析了4个保护区的鱼类多样性, 并比较了鱼类分类阶元的特有性、单型性和古老成分的有无等多项指标。结果显示, 4个自然保护区共有土著鱼类85种, 隶属于6目13科45属。在中国仅见于怒江水系的4个特有属有异鲴属(Aspidoparia)和新条鳅属(Neonoemacheilus)分布于这3个保护区中; 18种特有种中, 仅分布在这3个保护区的狭域特有种5种。在中国仅分布于澜沧江水系的属有31个, 但仅安巴沙鳅属(Ambastaia)分布于澜沧江保护区; 在澜沧江保护区分布着中国仅见于澜沧江水系的特有种20种, 其中狭域特有种3种。怒江水系的3个保护区分布有1个单型属, 即鳗鲡属(Anguilla), 但没有单型种; 澜沧江自然保护区无单型属与单型种分布。4个保护区中的鱼类均系晚第三纪和第四纪形成的种类或类群, 没有古老或孑遗种类。β多样性结果显示, 在4个保护区中澜沧江自然保护区的鱼类多样性最丰富, 而南滚河自然保护区的丰富程度最低, 但是怒江水系3个自然保护区鱼类多样性的代表性及保护地位比澜沧江自然保护区的要高。而特有阶元和单型性阶元的存在体现出怒江水系3个自然保护区的保护价值及保护意义比澜沧江保护区高。地理范围跨度大小、生境空间异质性高低、保护区面积大小及支流多少等是影响鱼类多样性的主要因素。因此, 规划和设计保护区时, 如果能在水系的上、中、下游分别规划1条一级支流作为保护区, 可使该水系的绝大多数鱼类得到保护。     

江苏省3个自然保护区外来入侵植物的调查及分析

选择位于江苏省内不同生物气候带的连云港云台山森林自然保护区、南京紫金山风景名胜区和宜兴龙池山森林自然保护区为调查区域,采用线路调查、样方调查与走访调查相结合的方法对这3个自然保护区内外来入侵植物的种类及分布现状进行了调查分析.结果显示,云台山森林自然保护区、龙池山森林自然保护区和紫金山风景名胜区内的外来入侵植物分别有13、19和23种,3个保护区总计有外来入侵植物25种,其中共有种11种;在25种外来入侵植物中,菊科(Compositae)种类最多(12种),占总种数的48%;苋科(Amaranthaceae)和玄参科(Scrophulariaceae)种类各有2种;80%的入侵种类来源于美洲,入侵途径以无意传播为主.一年蓬[Erigeron annuus (L. ) Pers. ]的频度最高,达到51.6%;小飞蓬[Conyza canadensis (L. ) Cronq. ]和野茼蒿[Crassocephalum crepidioides (Benth. ) S. Moore]的频度也较高,均在10%以上.部分外来入侵植物已在保护区内建立稳定的繁殖种群,对自然保护区生态环境造成危害,严重威胁着保护区的生物多样性.此外,根据3个保护区内外来入侵植物的分布现状和生态影响,提出了对保护区内外来入侵植物管理与防治的对策和建议.     

自然保护区减缓和适应气候变化的管理有效性评估: 以广西12个典型自然保护区为例

建立自然保护区是生物多样性保护的根本措施, 而且自然保护区对减缓和适应气候变化具有重要的作用。生物多样性保护的压力在气候变化的胁迫下不断加剧, 因此, 有效的自然保护区管理必须考虑气候变化的影响。发展应对气候变化威胁的适应性管理技术以提高自然保护区管理有效性是自然保护区管理的迫切需求。但目前全球范围内还没有针对减缓和适应气候变化的自然保护区管理有效性评估工具。近半个世纪来广西气温持续升高且极端气候事件频次增加, 对广西各类生物生境产生了重要的影响。本文基于世界自然保护联盟(IUCN)的自然保护区减缓和适应气候变化管理框架和管理有效性评估框架, 在管理有效性跟踪工具(mangement effectiveness tracking tool, METT)基础上提出了自然保护区减缓和适应气候变化管理有效性评估工具(management effectiveness assessment tool of mitigation and adaptation on climate change, MEATMACC), 并使用该工具和METT对广西12个典型自然保护区进行了调查分析。结果表明: 国家级自然保护区的METT得分、MEATMACC得分分别比非国家级自然保护区高28.98%和43.91%; 国家级与非国家级自然保护区的METT得分无显著差异, 但MEATMACC得分差异极显著; 两个管理有效性评估工具得分率呈线性相关但差异不显著; 两个评估工具中背景、规划与影响3个要素得分率存在极显著差异。研究结果表明, 对于自然保护区减缓和适应气候变化的政策和技术支持仍需加强。     

豚鼠脑干听觉诱发反应的分析及建模初探

本文运用系统建模的方法,在时域和频域中分析了听觉脑干诱发反应(ABR)和听觉频率跟随反应(FFR)的实验数据,讨论了此两种反应之间即相联系又相独立的关系,及两种反应对刺激信号的线性和非线性关系。用单纯型最优化方法,对其参数进行辨识,建立一个线性传递函数和非线性函数及脉冲函数组合的模型。 整个模型在计算机上进行模拟,模拟的结果与FFR和ABR记录的数据相符。     

基于系统保护规划法的长江中下游鱼类保护区网络规划

以长江中下游为例,采用系统保护规划法来开展鱼类保护区网络的顶层规划,选择了栖息于长江中下游的153种鱼类,其中,142种鱼类的分布信息来自物种分布建模和后续相关处理,11种鱼类的分布信息来自于人为指定.以这些鱼类的分布信息为基础,采用Marxan保护规划软件来执行保护规划.为了同时考虑保护区网络的代表性、维持性和高效性,在规划过程中考虑了已建立湿地自然保护区、人类干扰、保护区间的水文连通性等因素,并为各鱼类设定了适当的代表性目标.通过运行Marxan,得到了每个规划单元的选择频率和一个最优解.规划单元选择频率表示一个规划单元的保护重要性,而最优解是一个理想的鱼类保护区网络.结果显示,无论是选择频率高的规划单元还是最优解都仅有少部分位于现有的湿地自然保护区网络内,这说明长江中下游鱼类存在着明显的保护空缺.本研究得到的最优解可以作为构建长江中下游鱼类保护区网络的参考.解中的规划单元在一定程度上可以用其他的规划单元来替代,这一灵活性使得在现实中执行本规划方案时可以灵活避开意外的阻碍.最后,建议在遵循一个淡水管理框架的基础上来执行本规划方案.     

Designing connected nature reserve networks using a graph theory approach

Habitat fragmentation has been cited as one of the critical reasons for biodiversity loss. Establishing connected nature reserve networks is an effective way to reduce habit fragmentation. However, the resources devoted to nature reserves have always been scarce. Therefore it is important to allocate our scarce resources in an optimal way. The optimal design of a reserve network which is effective both ecologically and economically has become an important research topic in the reserve design literature. The problem of optimal selection of a subset from a larger group of potential habitat sites is solved using either heuristic or formal optimization methods. The heuristic methods, although flexible and computationally fast, can not guarantee the solution is optimal therefore may lead to scarce resources being used in an ineffective way. The formal optimization methods, on the other hand, guarantees the solution is optimal, but it has been argued that it would be difficult to model site selection process using optimization models, especially when spatial attributes of the reserve have to be taken into account. This paper presents a linear integer programming model for the design of a minimal connected reserve network using a graph theory approach. A connected tree is determined corresponding to a connected reserve. Computational performance of the model is tested using datasets randomly generated by the software GAMS. Results show that the model can solve a connected reserve design problem which includes 100 potential sites and 30 species in a reasonable period of time. As an empirical application, the model is applied to the protection of endangered and threatened bird species in the Cache River basin area in Illinois, US. Two connected reserve networks are determined for 13 bird species.     

Designing connected nature reserve networks using a graph theory approach

Habitat fragmentation has been cited as one of the critical reasons for biodiversity loss. Establishing connected nature reserve networks is an effective way to reduce habit fragmentation. However, the resources devoted to nature reserves have always been scarce. Therefore it is important to allocate our scarce resources in an optimal way. The optimal design of a reserve network which is effective both ecologically and economically has become an important research topic in the reserve design literature. The problem of optimal selection of a subset from a larger group of potential habitat sites is solved using either heuristic or formal optimization methods. The heuristic methods, although flexible and computationally fast, can not guarantee the solution is optimal therefore may lead to scarce resources being used in an ineffective way. The formal optimization methods, on the other hand, guarantees the solution is optimal, but it has been argued that it would be difficult to model site selection process using optimization models, especially when spatial attributes of the reserve have to be taken into account. This paper presents a linear integer programming model for the design of a minimal connected reserve network using a graph theory approach. A connected tree is determined corresponding to a connected reserve. Computational performance of the model is tested using datasets randomly generated by the software GAMS. Results show that the model can solve a connected reserve design problem which includes 100 potential sites and 30 species in a reasonable period of time. As an empirical application, the model is applied to the protection of endangered and threatened bird species in the Cache River basin area in Illinois, US. Two connected reserve networks are determined for 13 bird species.     

Robust optimization of total joint replacements incorporating environmental variables.

Direct search techniques for the optimal design of biomechanical devices are computationally intensive requiring many iterations before converging to a global solution. This, along with the incorporation of environmental variables such as multiple loading conditions and bone properties, makes direct search techniques infeasible. In this study, we introduced new methods that are based on the statistical design and analysis of computer experiments to account efficiently for environmental variables. Using data collected at a relatively small set of training sites, the method employs a computationally inexpensive predictor of the structural response that is statistically motivated. By using this predictor in place of the simulator (e.g., finite element model), a sufficient number of iterations can be performed to facilitate the optimization of the complex system. The applicability of these methods was demonstrated through the design of a femoral component for total hip arthroplasty incorporating variations in joint force orientation and cancellous bone properties. Beams on elastic foundation (BOEF) finite element models were developed to simulate the structural response. These simple models were chosen for their short computation time. This allowed us to represent the actual structural response surface by an exhaustive enumeration of the design and environmental variable space, and provided a means by which to validate the statistical predictor. We were able to predict the structural response and the optimal design accurately using only 16 runs of the computer code. The general trends predicted by the BOEF models were in agreement with previous three-dimensional finite element computer simulations, and experimental and clinical results, which demonstrated that the important features of intramedullary fixation systems were captured. These results indicate that the statistically based optimization methods are appropriate for optimization studies using computationally demanding models.     

Design of Nature Reserve System for Red-Crowned Crane in China

A system of nature reserves is a necessary component of an integrated conservation strategy. The basic problem in the design of a nature reserve system is to select the smallest number of sites from a region for some conservation objectives. There are 33 nature reserves intended for the conservation of Red-Crowned Crane (Grus japonensis), totalling 3.1 million ha. Other habitats of Red-Crowned Crane are facing severe problems due to economic development and other human activities. GIS, iterative methods and the integer programming approach were employed to design the nature reserve system for Red-Crowned Crane, with conservation goals to protect 70 and 60% areas of highly and moderately suitable wetlands, respectively. The results indicated the need to designate six new nature reserves in Wulagai marsh, Duluhe River, Tumen River, Rizhao, Gaoyou Lake and Hongze Lake, and showed a protection zone in Songnen Plain (between Heilongjiang Province and Jilin Province) and three clusters of nature reserves in Sanjing Plain, which, will be used as reference for the designation of new nature reserves, or enlargement and adjustment of existing nature reserves. The iterative method and integer programming approaches were feasible for design of nature reserve system.     

Optimal multiple testing and design in clinical trials

A central goal in designing clinical trials is to find the test that maximizes power (or equivalently minimizes required sample size) for finding a false null hypothesis subject to the constraint of type I error. When there is more than one test, such as in clinical trials with multiple endpoints, the issues of optimal design and optimal procedures become more complex. In this paper, we address the question of how such optimal tests should be defined and how they can be found. We review different notions of power and how they relate to study goals, and also consider the requirements of type I error control and the nature of the procedures. This leads us to an explicit optimization problem with objective and constraints that describe its specific desiderata. We present a complete solution for deriving optimal procedures for two hypotheses, which have desired monotonicity properties, and are computationally simple. For some of the optimization formulations this yields optimal procedures that are identical to existing procedures, such as Hommel's procedure or the procedure of Bittman et al. (2009), while for other cases it yields completely novel and more powerful procedures than existing ones. We demonstrate the nature of our novel procedures and their improved power extensively in a simulation and on the APEX study (Cohen et al., 2016).     

Using an optimization algorithm to establish a network of video surveillance for the protection of Golden Camellia

The natural environment is facing increasing human disturbance. Many species of flora are extinct or endangered. To improve the efficiency of ecological management and monitoring, this study proposed to establish a video monitoring network to protect a world-famous rare flora: Golden Camellia, in Fangcheng nature reserve, Guangxi Province, China. Based on the model of LSCP (location set covering problem), we attempted to establish full monitoring coverage of camellias while minimizing the number of video cameras. The model was solved by integer programming. In case of multiple solutions, this study proposed two additional criteria, maximize monitoring area and maximize overlapping count, to eliminate suboptimal solutions. Both of the two optimal solutions included 80 cameras covering a monitoring area of over 55 km². Together, these cameras are able to monitor 97.2% of golden camellia in the reserve. The findings of this study suggest that this location optimization model can be used to improve the conservation effectiveness of rare species.     

Heuristic and optimal solutions for set-covering problems in conservation biology

Area-selection methods have recently gained prominence in conservation biology. A typical problem is to identify the minimum number of areas required to represent all species over some geographic region. Iterative heuristic methods have been developed by conservation scientists to solve these problems, although the solutions cannot be guaranteed to be optimal. Although optimal solutions can often be found, heuristics continue to be popular as they are perceived to be faster and more transparent as they are intuitively easy to understand. We used distributional data for 1921 bird species, 939 mammal species, 405 snake species, and 617 amphibian species compiled at the Zoological Museum, Univ. of Copenhagen for all 1° cells of mainland sub-Saharan Africa to compare the quality of the solutions found using two heuristic methods (simple-greedy algorithm and a progressive-rarity algorithm) with optimal solutions. We found that the heuristic methods considered here often provide solutions as good as optimal solutions. Even in those cases where the optimal solutions were better the difference was relatively small, with the heuristics providing solutions requiring a 2–10% increase in area selected compared with the optimal solution, which importantly, represented an increase of <1% of the total area. Our study also suggests that the heuristic algorithms performed least well for datasets with few single cell endemics and taxa that tend to have larger range sizes. Despite the good quality of solutions using heuristics there was no time penalty associated with finding optimal solutions for the problems considered here, suggesting that the major obstacle to their use is making optimal methods accessible to conservation biologists. We encourage conservation biologists to work with operations researchers and so gain the benefit of their expertise and experience in solving these kinds of problems.     

Semi-Markov models for brownian dynamics permeation in biological ion channels

Constructing accurate computational models that explain how ions permeate through a biological ion channel is an important problem in biophysics and drug design. Brownian dynamics simulations are large-scale interacting particle computer simulations for modeling ion channel permeation but can be computationally prohibitive. In this paper, we show the somewhat surprising result that a small-dimensional semi-Markov model can generate events (such as conduction events and dwell times at binding sites in the protein) that are statistically indistinguishable from brownian dynamics computer simulation. This approach enables the use of extrapolation techniques to predict channel conduction when performing the actual brownian dynamics simulation that is computationally intractable. Numerical studies on the simulation of gramicidin A ion channels are presented.