Assessing the current state of ecological connectivity in a large marine protected area system

The establishment of marine protected areas (MPAs) is a critical step in ensuring the continued persistence of marine biodiversity. Although the area protected in MPAs is growing, the movement of individuals (or larvae) among MPAs, termed connectivity, has only recently been included as an objective of many MPAs. As such, assessing connectivity is often neglected or oversimplified in the planning process. For promoting population persistence, it is important to ensure that protected areas in a system are functionally connected through dispersal or adult movement. We devised a multi-species model of larval dispersal for the Australian marine environment to evaluate how much local scale connectivity is protected in MPAs and determine whether the extensive system of MPAs truly functions as a network. We focused on non-migratory species with simplified larval behaviors (i.e., passive larval dispersal) (e.g., no explicit vertical migration) as an illustration. Of all the MPAs analyzed (approximately 2.7 million km²), outside the Great Barrier Reef and Ningaloo Reef, <50% of MPAs (46-80% of total MPA area depending on the species considered) were functionally connected. Our results suggest that Australia's MPA system cannot be referred to as a single network, but rather a collection of numerous smaller networks delineated by natural breaks in the connectivity of reef habitat. Depending on the dispersal capacity of the taxa of interest, there may be between 25 and 47 individual ecological networks distributed across the Australian marine environment. The need to first assess the underlying natural connectivity of a study system prior to implementing new MPAs represents a key research priority for strategically enlarging MPA networks. Our findings highlight the benefits of integrating multi-species connectivity into conservation planning to identify opportunities to better incorporate connectivity into the design of MPA systems and thus to increase their capacity to support long-term, sustainable biodiversity outcomes.     

乡村振兴背景下社区居民旅游创业意愿研究——基于分布式认识理论

在乡村振兴背景下,选择兰州市榆中县浪街村社区为研究对象,依托分布式认知理论,构建了居民旅游创业意愿和影响因素模型。结果发现:(1)个人力因素不是形成创业意愿的决定性因素。(2)在地域力方面,大部分居民参与旅游创业的资源条件有限。(3)在文化力方面,领导和以领导为核心的社会关系网是旅游创业意愿形成和转变的决定性因素,并且能够将这种创业意愿转化为创业行为。在研究基础上,提出对策建议:注意培育旅游创业主体,增强现存社区创业能力,争取外部专家与辅助者的支持,以增强乡村旅游发展的可持续性。     

资源环境承载力研究方法综述

资源环境承载力是区域发展战略决策的基础,对指导区域可持续发展和服务国家战略需求具有重要意义。本文系统梳理了资源环境承载力评价从土地资源承载力向水资源承载力、环境承载力和生态承载力发展,再到近年来以土地开发强度为特征,以及基于供给能力的资源环境承载力评价兴起的历程。资源环境承载力评价从单一资源走向各类主要自然资源、环境要素及综合要素的承载力评价,研究方法不断完善。但目前资源环境承载力研究仍存在更多地关注承载的极限容量,对发展容量的关注不足;缺乏具有普适性、可推广的资源环境承载力评价理论及方法体系等问题,其研究仍面临严峻的挑战。未来资源环境承载力研究仍需在承载力从极限容量向发展容量转变,形成具有广泛指导意义的资源环境承载力评价方法体系,强化以空间开发利用为特征的资源环境承载力评价等方面的研究,以此深化资源环境承载力理论及实践应用研究,为区域可持续发展及服务国家战略提供支撑。     

基于动态毒性负荷的人员疏散安全评估方法

毒气泄漏事故在高含硫气田及化工园区频繁发生,一旦发生事故,周边公众迅速进行疏散是应急的首要任务。我国很多地区制定了疏散方案,但是如何评估疏散的安全性和可行性,是亟待解决的问题。分析了我国泄漏事故特点和周边居民情况,对以往评估方法缺陷进行了剖析,提出基于动态毒性负荷分析的安全疏散评估方法。该方法在毒气扩散的精确3d模拟及疏散模拟的基础上,用差分法对人员行走过程中的毒性负荷Pc进行的计算,最终得出相应的致死概率Pr,并通过一个实例验证该方法的可行性。结果表明,运用该方法能够详尽、准确规划疏散区域、搬迁区域和避难区域。     

基于比奥动力固结理论的尾矿坝地震响应分析

上游法尾矿坝坝体密实度低,饱和区域大,地震作用下极易发生液化进而引起溃坝等重大事故,基于比奥动力固结理论和广义塑性模型,采用有效应力有限单元法对上游法尾矿坝的地震动力响应进行了非线性时程动力计算分析。结果表明坝体地震加速度响应、残余变形、超静孔压等计算结果符合一般规律,其中坝顶下部的超静孔压比值最大,从尾矿坝底部到顶部,加速度放大系数先稍微减弱后显著变大,呈明显的鞭梢效应,说明上游法尾矿坝坝顶部位是地震作用下最为危险的区域,采用弹塑性本构模型对尾矿坝进行非线性动力固结分析是可行的。     

基于贝叶斯网络的基本农田划定方法

基本农田划定是落实耕地保护、保证粮食安全的关键问题。目前,基本农田划定的相关研究多基于对耕地适宜性条件的评价,而未涉及对耕地历史变化过程的考虑,因而不能保证划定结果适应实际区域的耕地变化趋势,导致基本农田易被占用,补划与调整频繁。论文综合考虑耕地适宜性条件与历史动态变化状况,提出了一种基于贝叶斯网络模型的基本农田划定方法。以湖北省大冶市这一典型资源型城市为实验区进行了实例研究,划定结果表明,该划定方法能在保证基本农田划定数量与质量的同时,提高其农业用途的稳定性,促进基本农田保护与经济建设、生态保护间协调发展,是一种有效的划定模型。     

基于空间拟合和神经网络的机场噪声预测集成模型

将集成学习方法引入到机场噪声预测中,提出一种基于空间拟合和神经网络的机场噪声预测集成模型.该模型采用空间拟合算法和BP神经网络算法构建基学习器,然后通过所提出的基于观察学习的异构集成算法将基学习器集成起来,获得集成的机场噪声预测结果.该模型通过集成多个异构机场噪声预测基学习器,能够有效提升预测准确率.实验结果表明,本文所提出的基于观察学习的异构集成算法,较之其他异构集成算法,在解决机场噪声预测问题上准确性更高、容错性更强.     

人工神经网络在矿井多水源识别中的应用

以焦作矿区水化数据为例,选用Na++K+、Ca2+、Mg2+、Cl-、SO2-4、HCO-36种水化离子浓度作为识别矿井水源的依据,运用Matlab软件分别建立BP神经网络与Elman神经网络的矿井多水源识别模型。应用结果表明:与静态的BP神经网络相比,在结构上增加承接层的Elman神经网络在训练和仿真中拟合能力更强,识别精度更高和泛化能力更好;矿井地下水随着地下开采与扰动具有动态性,将具有非线性动态特征的Elman神经网络应用于矿井多水源的识别,对准确判断突水来源和分析地下水运移规律具有一定的辅助和指导意义。     

城市纳污河流有色溶解有机物时空演变特征

利用平行因子分析和主成分分析方法,结合紫外吸收光谱与三维荧光光谱技术,研究了典型城市纳污河流-河北洨河水体有色溶解有机物(CDOM)的来源及随季节和空间变化特征,探讨了水体CDOM与水质指标间关系.结果表明:洨河水体CDOM主要为新近微生物源产生,受人类活动影响较大.CDOM浓度在时间变化上表现为春夏(2、5月)低,而秋冬(8、11月)高,从上游至下游呈现先升高再降低变化特征.荧光鉴别出的4种组分:组分1(类富里酸),组分2(类腐殖酸)及组分3(类胡敏酸)为类腐殖质,组分4为类蛋白物质.不同季节各组分来源及分布存在差异,除夏季外其他季节水体类蛋白与类腐殖质来源相似,尤其与类胡敏酸组分;类蛋白组分在各季节分布变化显著,冬春含量相对较高.洨河水体荧光物质与氨氮、亚硝氮具有共同来源,其中类腐殖质对COD贡献较为明显.采用光谱分析法并结合平行因子、主成分分析及聚类分析方法可识别污染源空间分布,揭示河体CDOM随季节变化规律.     

Bibliometric analysis of ecosystem monitoring-related research in Africa: implications for ecological stewardship and scientific collaboration

Regional ecosystem monitoring is a central form of knowledge sharing and collaboration amongst scientists and decision makers on environmental health, land use change, and science-policy development. Despite the proliferation of such research networks on long-term monitoring on many continents, little has been achieved in Africa. This study aims to assess and examine the spatiotemporal trend and categorical patterns in ecosystem monitoring-related research in Africa for the benefits of conserving biodiversity and sustaining natural resource sectors for well-being and livelihood security, environmental planning, and ecological stewardship. A systematic review was conducted using bibliometric tools. Based on a set of search terms and peer-reviewed publications retrieved from various ecosystem monitoring networks and journal databases, further analysis was conducted using social network approaches, mapping tools, and content analysis. About 1442 scientific publications on ecosystem monitoring and related research were documented from 1987 to 2014 mostly published in English. The number of publication increased progressively since 1992 after the Convention on Biodiversity was signed and this trend peaked till 2008. South African Journal of Science was the most leading journal and Nature the most cited. Internationally coauthored and collaborative articles represented majority of the findings with the United Kingdom at the central position in the research network due to colonial relationships. Regional collaboration amongst countries is limited owing to language barriers and other institutional constraints such as funding and short-term projects. These findings have implication for prioritizing national and regional policies toward biodiversity science and its contribution to human well-being, food security, and global change responses.