水-粮食贸易:虚拟水研究进展

虚拟水思想强调的是水资源贡献，量化计算是其深入研究的基本，而是否选择虚拟水作为战略政策，应该考虑由不同国家的资源贡献和生产技术决定的比较利益。社会调适能力要求社会针对资源的第一性缺乏做相应调适并谋求解决手段，以提高资源管理能力。为此，需要结合我国的水和粮食安全问题，提出用虚拟水贸易解决我国水资源和粮食问题，提高我国对水资源缺乏的调适能力。     

甘肃河西内陆河流域社会化水资源稀缺评价

水资源稀缺是我国经济社会发展所面临的严重制约因素。水资源稀缺评价是水资源管理中最基础性的工作。借助Karshenas模型对资源利用同经济发展之间的关系进行了诠释；在界定水资源管理阶段的基础上。引入社会适应性能力概念。着重论述了其内在结构及其度量指标。从而将水资源稀缺问题拓展到了社会经济领域。强调社会资源在水资源稀缺评价中的作用。同时。建立社会化水资源稀缺指数。并以甘肃省河西内陆河流域五市为例进行了实证研究．结果表明：嘉峪关市由于相对较高的社会适应性能力。其社会化水资源稀缺程度指数的相对排序得到改善；而武威市则因相对较低的社会适应性能力。社会化水资源稀缺指数的排序有所降低；金昌市和张掖市尽管社会化水资源稀缺指数的相对排序没有变化。但由于考虑了社会适应性能力。水资源稀缺程度得到有效的缓解。社会化水资源稀缺指数更能如实反映水资源状况。社会适应性能力是一种重要的资源。对缓解水资源紧缺程度具有重要的作用。     

经济快速发展地区土地利用结构的时空演变——以苏锡常地区为例

利用1996～2007年苏锡常地区土地利用变更数据，从土地利用变化幅度、动态度、变化强度、相对变化率及景观生态学角度，对区域土地利用结构的动态变化及区域差异进行分析。研究结果表明：近十多年来，由于区域经济快速发展，工业用地扩展迅猛，城镇加速蔓延，从而导致区内耕地面积锐减，居民点及工矿用地、交通用地所占比例则逐年上升，交通用地的变化幅度及动态度最大；各用地类型的变化强度在此期间呈一定波动，除牧草地外，交通用地历年的变化强度之和最大，其次为园地、居民点及工矿用地、水利设施用地、耕地、其他农用地、林地、未利用地；区域土地利用结构逐渐向均衡状态发展，用地结构的均质性逐渐增强，地区土地利用结构渐趋稳定；各市耕地、居民点及工矿用地、其他农用地的变化幅度及相对变化率差别不大，而园地、林地、牧草地、交通用地、水利设施用地及未利用地的变化幅度及相对变化率区域差异较大，且三市园地、牧草地及未利用地的变化方向不一致。     

城市区域土地利用变化及驱动机制研究 --以长江三角洲地区为例

以正处于一个新的成长期的城市群——长江三角洲地区为例,分析其工业化、城市化进程中的城市区域土地利用变化态势及内在驱动机理。通过对长江三角洲地区城市区域各地类面积比例的动态分析,发现研究区土地利用变化的主要方面是建设用地比例的增加以及耕地和水域面积比例的减少。在此基础上建立驱动因素体系,利用相关分析和主因子分析方法,并构建城市区域土地利用变化驱动力模型,得出长江三角洲城市区域土地利用变化的主要驱动因素是人口的增长和非农化、经济总量的增加以及劳动力的非农化。但是不同的时期,主要驱动力随着社会经济发展的特点和土地利用的特点不断变化：人口的非农化(城市化率)的作用不断增强;经济总量增长的作用明显的减弱;第三产业的发展对建设用地比例增加的驱动作用越来越强。     

昆山市生态系统服务价值变化研究

在Constanza的生态系统服务价值理论的基础上,计算了1994－2002年昆山市生态系统服务价值的变化。建设用地对耕地和水域面积的占用,引起了昆山市的生态系统服务价值逐渐下降： 9年间生态系统服务价值（ESV）总量下降了8.9%,人均占有量（Ave(ESV)）下降了13.0%。各种土地利用方式的生态系统服务价值的弹性系数都小于1。水域面积的变化则对生态系统服务价值变化起到放大作用。耕地面积的变化主要是影响昆山市的粮食安全问题,而水域的变化则在更大程度上影响生态系统服务功能方面。     

三峡库区雷暴气候变化特征分析

利用长江三峡库区及其周边地区38个气象站1961～2001年的逐日雷暴资料,统计、分析了三峡库区雷暴日数及其初、终日的时空分布特征。结果表明：41年来,长江三峡库区年平均雷暴日数较多,一般为34～45 d,其中库区西北部和中南部为多雷区;年际变化大,最多年比最少年一般偏多27～61 d;整个库区年雷暴日数的变化均存在不同程度的减少趋势,气候倾向率为 1～7 d/10 a;雷暴出现的季节变化很明显,4～8月为多发时段;雷暴初日库区东部早于西部,终日东西段差别不大;雷暴持续期普遍在195～239 d之间,其中西部持续时间短,东部长;大部地区雷暴初日有推后的变化趋势,推迟速率约2～6 d/10 a;终日有提前的变化趋势,且提前速率为2～4 d/10 a;库区大部雷暴期呈缩短的变化趋势,缩短速率为2～8 d/10 a。     

Learning and climate feedbacks: Optimal climate insurance and fat tails

We study the effect of potentially severe climate change on optimal climate change policy, accounting for learning and uncertainty in the climate system. In particular, we test how fat upper tailed uncertainty over the temperature change from a doubling of greenhouse gases (the climate sensitivity), affects economic growth and emissions policy. In addition, we examine whether and how fast uncertainties could be diminished through Bayesian learning. Our results indicate that while overall learning is slow, the mass of the fat tail diminishes quickly, since observations near the mean provide evidence against fat tails. We denote as “tail learning” the case where the planner rejects high values of the climate sensitivity with high confidence, even though significant uncertainty remains. Fat tailed uncertainty without learning reduces current emissions by 38% relative to certainty, indicating significant climate insurance, or paying to limit emissions today to reduce the risk of very high temperature changes, is optimal. However, learning reduces climate insurance by about 50%. The optimal abatement policy is strongly influenced by the current state of knowledge, even though greenhouse gas (GHG) emissions are difficult to reverse. Once the mass of the fat tail diminishes, the remaining uncertainty is largely irrelevant for optimal emissions policy.     

The potential for biodiversity offsetting to fund effective invasive species control

Compensating for biodiversity losses in 1 location by conserving or restoring biodiversity elsewhere (i.e., biodiversity offsetting) is being used increasingly to compensate for biodiversity losses resulting from development. We considered whether a form of biodiversity offsetting, enhancement offsetting (i.e., enhancing the quality of degraded natural habitats through intensive ecological management), can realistically secure additional funding to control biological invaders at a scale and duration that results in enhanced biodiversity outcomes. We suggest that biodiversity offsetting has the potential to enhance biodiversity values through funding of invasive species control, but it needs to meet 7 key conditions: be technically possible to reduce invasive species to levels that enhance native biodiversity; be affordable; be sufficiently large to compensate for the impact; be adaptable to accommodate new strategic and tactical developments while not compromising biodiversity outcomes; acknowledge uncertainties associated with managing pests; be based on an explicit risk assessment that identifies the cost of not achieving target outcomes; and include financial mechanisms to provide for in‐perpetuity funding. The challenge then for conservation practitioners, advocates, and policy makers is to develop frameworks that allow for durable and effective partnerships with developers to realize the full potential of enhancement offsets, which will require a shift away from traditional preservation‐focused approaches to biodiversity management. El Potencial de la Compensación de la Biodiversidad para Financiar Controles Efectivos de Especies Invasoras     

Assessing the components of adaptive capacity to improve conservation and management efforts under global change

Natural‐resource managers and other conservation practitioners are under unprecedented pressure to categorize and quantify the vulnerability of natural systems based on assessment of the exposure, sensitivity, and adaptive capacity of species to climate change. Despite the urgent need for these assessments, neither the theoretical basis of adaptive capacity nor the practical issues underlying its quantification has been articulated in a manner that is directly applicable to natural‐resource management. Both are critical for researchers, managers, and other conservation practitioners to develop reliable strategies for assessing adaptive capacity. Drawing from principles of classical and contemporary research and examples from terrestrial, marine, plant, and animal systems, we examined broadly the theory behind the concept of adaptive capacity. We then considered how interdisciplinary, trait‐ and triage‐based approaches encompassing the oft‐overlooked interactions among components of adaptive capacity can be used to identify species and populations likely to have higher (or lower) adaptive capacity. We identified the challenges and value of such endeavors and argue for a concerted interdisciplinary research approach that combines ecology, ecological genetics, and eco‐physiology to reflect the interacting components of adaptive capacity. We aimed to provide a basis for constructive discussion between natural‐resource managers and researchers, discussions urgently needed to identify research directions that will deliver answers to real‐world questions facing resource managers, other conservation practitioners, and policy makers. Directing research to both seek general patterns and identify ways to facilitate adaptive capacity of key species and populations within species, will enable conservation ecologists and resource managers to maximize returns on research and management investment and arrive at novel and dynamic management and policy decisions.     

Progress in the ecology and conservation of giant pandas

Giant panda (Ailuropoda melanoleuca) conservation is a possible success story in the making. If extinction of this iconic endangered species can be avoided, the species will become a showcase program for the Chinese government and its collaborators. We reviewed the major advancements in ecological science for the giant panda, examining how these advancements have contributed to panda conservation. Pandas’ morphological and behavioral adaptations to a diet of bamboo, which bear strong influence on movement ecology, have been well studied, providing knowledge to guide management actions ranging from reserve design to climate change mitigation. Foraging ecology has also provided essential information used in the creation of landscape models of panda habitat. Because habitat loss and fragmentation are major drivers of the panda population decline, efforts have been made to help identify core habitat areas, establish where habitat corridors are needed, and prioritize areas for protection and restoration. Thus, habitat models have provided guidance for the Chinese governments’ creation of 67 protected areas. Behavioral research has revealed a complex and efficient communication system and documented the need for protection of habitat that serves as a communication platform for bringing the sexes together for mating. Further research shows that den sites in old‐growth forests may be a limiting resource, indicating potential value in providing alternative den sites for rearing offspring. Advancements in molecular ecology have been revolutionary and have been applied to population census, determining population structure and genetic diversity, evaluating connectivity following habitat fragmentation, and understanding dispersal patterns. These advancements form a foundation for increasing the application of adaptive management approaches to move panda conservation forward more rapidly. Although the Chinese government has made great progress in setting aside protected areas, future emphasis will be improved management of pandas and their habitat.