基于变权-物元分析模型的老工业基地区域生态安全动态预警研究——以吉林省为例

生态安全预警是生态安全研究的重要内容,对维护区域生态安全具有重要的意义。老工业基地区域生态安全预警研究具有一定的特殊性和典型性,选取吉林省为研究区,基于压力、状态、响应(P-S-R)和生态、环境、经济、社会(E-E-E-S)框架模型构建生态安全预警指标体系,运用变权-物元分析模型对1991—2011年吉林省区域生态安全的预警等级进行了测度,并结合灰色系统GM(1,1)预测模型对2015年、2020年区域生态安全态势进行预测预警。研究结果表明:(1)1991—2011年,吉林省生态安全总体水平呈逐步上升的趋势,区域生态安全预警等级从"巨警"上升为"轻警",指示灯由"红色预警"逐步变为"蓝色预警";(2)2015年,吉林省的生态安全预警等级属于"轻警",指示灯为"蓝色预警",到2020年,吉林省的生态安全预警等级属于"无警",指示灯为"绿色预警",但具有向"轻警"变化的态势;(3)制约吉林省生态安全水平提升的主要因素包括单位面积耕地化肥负荷量、城镇化、人均水资源量、GDP增长率、第一产业占GDP比重等,这些因素应是今后生态环境保护调控的重点,本研究为吉林省经济-生态-社会可持续发展提供参考。     

基于FMT-AHP的海南农垦花岗岩类多雨区橡胶园地力评价

海南农垦是中国最大的天然橡胶生产基地,自第二次全国土壤普查以来橡胶园养分状况已发生了很大变化,但具体情况如何尚不清楚。运用耕地地力评价方法对海南农垦主要橡胶园的地力进行了系统评价,以期为橡胶园地力提升和天然橡胶的可持续发展提供理论支持。以土壤母质类型和降雨量为依据,首次将海南农垦橡胶园划分为8个类型区,并选取占海南农垦橡胶园总面积56.97%的花岗岩类多雨区作为评价区域,采集7204个0—20 cm层的土壤样品,运用特尔菲法、模糊数学理论和层次分析法确定11个评价指标及其权重,将评价区橡胶园地力划分为5等。研究结果发现:评价区以中间地力水平的二等、三等、四等橡胶园为主,占评价区橡胶园总面积的85.85%,它们广泛分布于琼中、屯昌、澄迈、儋州、万宁、保亭、乐东、三亚、陵水、定安、琼海、五指山、昌江、文昌和东方15个县市;一等地面积很小且分散,五等地相对集中面积也很小。相关分析表明土壤pH、有机质、有效磷和速效钾含量是影响评价区橡胶园地力水平的重要因素。评价区橡胶园土壤pH适宜橡胶树正常生长,但该区域土壤有机质和有效磷含量不能满足橡胶树正常生长的需要,而该区域一、二等地土壤速效钾含量能满足橡胶树正常生长,其三、四等地土壤速效钾含量仅达到橡胶树正常生长所需水平,随着地力下降到五等其土壤速效钾含量已不适宜橡胶树正常生长。根据上述研究结果,笔者建议橡胶园应大力间作绿肥,在增施有机质的基础上补氮、补钾、施用钙镁磷肥,同时加强养分管理,提高肥料利用率。     

Modelling land use changes for landscape connectivity: The role of plantation forestry and highways

Landscape connectivity is a key aspect for the maintenance of biodiversity and ecosystem viability. Nowadays, the competition between economic development and nature conservation is intense. In most territories natural vegetation is being replaced by exotic tree plantations, which have a better performance in terms of timber productivity but often, a lower ecological value. We evaluated potential natural forest connectivity improvement in the Cantabria region (Northern Spain) through two main actions: protection of environmentally valuable forest areas, and reforestation with indigenous species of those patches of exotic plantation trees with a particularly important role for the connectivity of the forest network. We established a variety of scenarios to calculate least cost paths, considering the presence or absence of plantation forestry and highways to examine connectivity. Then, we applied two habitat availability indices (integral index of connectivity and probability of connectivity) attending to different dispersal distances. Our analyses show a great potential for improving connectivity using plantation forests in the natural forest network, and a dramatic impact of the highway in the north–south connectivity of the study area. Based on these results, we identified those patches of plantation forest and natural forest that are more important for the maintenance of overall landscape connectivity, and propose their protection or conversion through reforestation. The final proposed network constitutes a larger and better connected natural forested landscape than the existing one.     

纳米混悬药物传递系统研究进展

在新药研发过程中,约有40%的药物存在溶解性差的问题,限制了药物的开发与应用。纳米混悬剂是20世纪末发展起来的一种纳米药物传递系统,可增加难溶性药物的溶解度和溶出速率、改变药物的体内药物动力学特征、提高口服生物利用度、安全性和有效性。纳米混悬剂不但适用于水溶性差的药物,而且适用于水溶性、脂溶性均较差的药物,其制备方法主要包括"bottom up"和"top down"两种。本文从纳米混悬剂的特点、理论基础、专利技术及应用等方面对纳米混悬剂的研究进展进行了综述。纳米混悬剂对改善难溶性药物的溶出、吸收,提高难溶性药物的有效性、安全性等方面具有显著优势,且适合工业化生产,已有越来越多的产品问世。纳米混悬技术是未来药物传递系统的发展方向之一,将具有良好的应用前景。     

Local competition sparks concerns for fairness in the ultimatum game

Humans reject uneven divisions of resources, even at personal cost. This is observed in countless experiments using the ultimatum game, where a proposer offers to divide a resource with a responder who either accepts the division or rejects it (whereupon both earn zero). Researchers debate why humans evolved a psychology that is so averse to inequity within partnerships. We suggest that the scale of competition is crucial: under local competition with few competitors, individuals reject low offers, because they cannot afford to be disadvantaged relative to competitors. If one competes against the broader population (i.e. global competition), then it pays to accept low offers to increase one''s absolute pay-off. We support this intuition with an illustrative game-theoretical model. We also conducted ultimatum games where participants received prizes based on pay-offs relative to immediate partners (local competition) versus a larger group (global competition). Participants demanded higher offers under local competition, suggesting that local competition increases people''s demands for fairness and aversion to inequality.     

Decision science for effective management of populations subject to stochasticity and imperfect knowledge

Many species are threatened by human activity through processes such as habitat modification, water management, hunting, and introduction of invasive species. These anthropogenic threats must be mitigated as efficiently as possible because both time and money available for mitigation are limited. For example, it is essential to address the type and degree of uncertainties present to derive effective management strategies for managed populations. Decision science provides the tools required to produce effective management strategies that can maximize or minimize the desired objective(s) based on imperfect knowledge, taking into account stochasticity. Of particular importance are questions such as how much of available budgets should be invested in reducing uncertainty and which uncertainties should be reduced. In such instances, decision science can help select efficient environmental management actions that may be subject to stochasticity and imperfect knowledge. Here, we review the use of decision science in environmental management to demonstrate the utility of the decision science framework. Our points are illustrated using examples from the literature. We conclude that collaboration between theoreticians and practitioners is crucial to maximize the benefits of decision science’s rational approach to dealing with uncertainty.     

Ecology drives intragenomic conflict over menopause

Menopause is the transition from reproductive to non‐reproductive life well before natural death. Rather than involving a smooth, rapid change, it is normally preceded by a long period of erratic hormonal fluctuation that is accompanied by a plethora of unpleasant symptoms. Here, we (1) suggest that this turbulent period owes to conflict, between a woman's maternally inherited (MI) and paternally inherited (PI) genes, over the trade‐off between reproduction and communal care; (2) perform a theoretical analysis to show that this conflict is resolved either through silencing or fluctuating expression of one of the genes; (3) highlight which of the symptoms preceding menopause may result from antagonistic co‐evolution of MI and PI genes; (4) argue that ecological differences between ancestral human populations may explain the variability in menopause among different ethnic groups; (5) discuss how these insights may be used to inform family planning and cancer risk assessment based on a woman's ancestral background.     

Cooperative investment in public goods is kin directed in communal nests of social birds

The tragedy of the commons predicts social collapse when public goods are jointly exploited by individuals attempting to maximize their fitness at the expense of other social group members. However, animal societies have evolved many times despite this vulnerability to exploitation by selfish individuals. Kin selection offers a solution to this social dilemma, but in large social groups mean relatedness is often low. Sociable weavers (Philetairus socius) live in large colonies that share the benefits of a massive communal nest, which requires individual investment for construction and maintenance. Here, we show that despite low mean kinship within colonies, relatives are spatially and socially clustered and that nest‐building males have higher local relatedness to other colony members than do non‐building males. Alternative hypotheses received little support, so we conclude that the benefits of the public good are shared with kin and that cooperative investment is, despite the large size and low relatedness of these communities, kin directed.     

Sensitivity analysis of coexistence in ecological communities: theory and application

Sensitivity analysis, the study of how ecological variables of interest respond to changes in external conditions, is a theoretically well‐developed and widely applied approach in population ecology. Though the application of sensitivity analysis to predicting the response of species‐rich communities to disturbances also has a long history, derivation of a mathematical framework for understanding the factors leading to robust coexistence has only been a recent undertaking. Here we suggest that this development opens up a new perspective, providing advances ranging from the applied to the theoretical. First, it yields a framework to be applied in specific cases for assessing the extinction risk of community modules in the face of environmental change. Second, it can be used to determine trait combinations allowing for coexistence that is robust to environmental variation, and limits to diversity in the presence of environmental variation, for specific community types. Third, it offers general insights into the nature of communities that are robust to environmental variation. We apply recent community‐level extensions of mathematical sensitivity analysis to example models for illustration. We discuss the advantages and limitations of the method, and some of the empirical questions the theoretical framework could help answer.     

Infusing considerations of trophic dependencies into species distribution modelling

Community ecology involves studying the interdependence of species with each other and their environment to predict their geographical distribution and abundance. Modern species distribution analyses characterise species‐environment dependency well, but offer only crude approximations of species interdependency. Typically, the dependency between focal species and other species is characterised using other species’ point occurrences as spatial covariates to constrain the focal species’ predicted range. This implicitly assumes that the strength of interdependency is homogeneous across space, which is not generally supported by analyses of species interactions. This discrepancy has an important bearing on the accuracy of inferences about habitat suitability for species. We introduce a framework that integrates principles from consumer–resource analyses, resource selection theory and species distribution modelling to enhance quantitative prediction of species geographical distributions. We show how to apply the framework using a case study of lynx and snowshoe hare interactions with each other and their environment. The analysis shows how the framework offers a spatially refined understanding of species distribution that is sensitive to nuances in biophysical attributes of the environment that determine the location and strength of species interactions.