社会-生态系统适应性治理研究进展与展望

社会—生态系统（SES）由社会子系统、生态子系统及两者的交互作用构成,具有不同于社会系统或生态系统单独具有的结构、功能和复杂特征。社会—生态系统适应性治理旨在通过适应性的社会权利分配与行为决策机制,使社会—生态系统能够在动态条件下可持续地保障人类福祉。适应性治理理论的形成受到“公共池塘资源管理”“韧性”和“治理”3方面理论的影响,并为“转型治理”与“协作治理”提供了建构基础。该理论具有以下3个主要目的：① 理解和应对社会—生态系统多稳态、非线性、不确定性、整体性以及复杂性;② 建立非对抗性的社会结构、权利分配制度以及行为决策体系,匹配社会子系统与自然子系统;③ 通过综合方法管理生态系统,使其可持续提供生态系统服务。因此,面对人类行为主导地表过程的“人类世”,实现适应性治理有助于应对社会—生态系统的复杂性与不确定性。鉴于中国的生态环境正处于迅速变化时期,且中国与世界各国间的相互影响日益复杂,未来研究可重点关注以下3个方面：① 理解耦合系统的多元互动过程,增强适应能力;② 强调社会—生态系统的整体性研究;③ 提高环境变化背景下理解和预测系统动态的能力。     

Effect of slow-solvent-vapour treatment on performance of polymer photovoltaic devices

In this work, enhanced poly(3-hexylthiophene):[6,6]-phenyl-C61-butyric acid methyl ester (P3HT:PCBM) bulk-heterojunction photovoltaic devices are achieved via slow-solvent-vapour treatment. The correlations between the morphology of the active layer and the photovoltaic performance of polymer-based solar cell are investigated. The active layers are characterized by atomic force microscopy and optical absorption. The results show that slow-solvent-vapour treatment can induce P3HT self-organization into an ordered structure, leading to the enhanced absorption and efficient charge transport.     

基于ART理论的自组织神经网络模型在水资源分类中的应用

BP和RBF神经网络技术以其强大的学习功能应用于水资源分类 ,取得了很好的效果。但当不具备已知样本时 ,以上技术很难应用。提出了可塑性较强、无监督的A -K网络模型 ,阐述了其基本原理和算法 ,并将其用于水文水资源研究领域中。实例表明 ,该方法能较理想地解决已知样本的分类问题 ,具有良好的应用前景     

斜压大气中双涡自组织与台风形成的初步研究

从数值研究和个例分析两个方面讨论了斜压大气中双涡自组织与台风形成的关系.首先,利用PSU/NCAR 第五代数值天气预报模式(MM5),设计了6个弱环境流场下的理想试验,研究斜压大气中双涡自组织对台风形成的影响,结果表明:斜压大气中双涡自组织存在一个临界距离dc,其值在380 km左右.当双涡间距d≤dc时,双涡可以自组织形成台风环流,当d>dc时,自组织现象不能发生.其次,选取一个对我国有重要影响典型台风个例,分析双涡自组织对其形成的影响,结果表明双涡自组织过程是对我国有重要影响台风形成的典型方式之一.     

Some Investigations on Early Organization of Karst System

Karstsystemsaredynamicsystemsinspontaneoussuc-cessiveevolutionarisenfromtheinteractionbetweenwaterflowandsolub1emedium-Thecircu1ationofwaterprogres-sivelyandcontinuouslymodifiesthestructureofmediumfield,consequentlymodifyingthehydraulicbehaviorofthesystemitself'Someauthors(e.g.,FordandWilliams,l989)believedthatmostcarbonaterockswillbecomeconduitaquifersifsurficialerosionisnegligibleorsufficienttimeisgiven.Karstsystemsfailtodevelopconnectedconduiteitherduetoincompleteextension(becauseinsuffici…     

Estuarine biofilm patterns: Modern analogues for Precambrian self-organization

This field and laboratory study examines whether regularly patterned biofilms on present-day intertidal flats are equivalent to microbially induced bedforms found in geological records dating back to the onset of life on Earth. Algal mats of filamentous Vaucheria species, functionally similar to microbial biofilms, cover the topographic highs of regularly spaced ridge–runnel bedforms. As regular patterning is typically associated with self-organization processes, indicators of self-organization are tested and found to support this hypothesis. The measurements suggest that biofilm-induced sediment trapping and biostabilization enhance bedform relief, strength and multi-year persistence. This demonstrates the importance of primitive organisms for sedimentary landscape development. Algal-covered ridges consist of wavy-crinkly laminated sedimentary deposits that resemble the layered structure of fossil stromatolites and microbially induced sedimentary structures. In addition to layering, both the morphological pattern and the suggested formation mechanism of the recent bedforms are strikingly similar to microbialite strata found in rock records from the Precambrian onwards. This implies that self-organization was an important morphological process in times when biofilms were the predominant sessile ecosystem. These findings furthermore emphasize that self-organization dynamics, such as critical transitions invoking ecosystem emergence or collapse, might have been captured in fossil microbialites, influencing their laminae. This notion may be important for paleoenvironmental reconstructions based on such strata. © 2019 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd     

Ecohydrologic feedbacks controlling sizes of cypress wetlands in a patterned karst landscape

Many landforms on Earth are profoundly influenced by biota. In particular, biota play a significant role in creating karst biogeomorphology, through biogenic CO₂ accelerating calcite weathering. In this study, we explore the ecohydrologic feedback mechanisms that have created isolated depressional wetlands on exposed limestone bedrock in South Florida – Big Cypress National Preserve –as a case study for karst biogeomorphic processes giving rise to regularly patterned landscapes. Specifically, we are interested in: (1) whether cypress depressions on the landscape have reached (or will reach) equilibrium size; (2) if so, what feedback mechanisms stabilize the size of depressions; and (3) what distal interactions among depressions give rise to the even distribution of depressions in the landscape. We hypothesize three feedback mechanisms controlling the evolution of depressions and build a numerical model to evaluate the relative importance of each mechanism. We show that a soil cover feedback (i.e. a smaller fraction of CO₂ reaches the bedrock surface for weathering as soil cover thickens) is the major feedback stabilizing depressions, followed by a biomass feedback (i.e. inhibited biomass growth with deepening standing water and extended inundation period as depressions expand in volume). Strong local positive feedback between the volume of depressions and rate of volume expansion and distal negative feedback between depressions competing for water likely lead to the regular patterning at the landscape scale. The individual depressions, however, are not yet in steady state but would be in ~0.2–0.4 million years. This represents the first study to demonstrate the decoupling of landscape-scale self-organization and the self-organization of its constituent agents. © 2018 John Wiley & Sons, Ltd.     

基于SOFM神经网络的边坡稳定性评价

针对边坡工程稳定性分析中参数的不确定性,在分析自组织特征映射神经网络（SOFM）基本学习算法的基础上,从提高算法收敛速度和性能出发,将自组织特征映射神经网络基本学习算法加以改进,据此建立了评价边坡稳定状态的SOFM神经网络模型。然后用收集到的边坡稳定工程实例作为样本,对该模型进行训练和检验,并与BP神经网络判别结果对比。结果表明,SOFM神经网络性能良好、预测精度高,是边坡稳定性评价的一种有效方法。     

某些矿物中同心层状鲕(豆)粒的自组织成因

本文首先综述了矿物中同心层状鲕(豆)粒的基本特征,接着提出该鲕状结构的二阶段成因模式(早期胶团从沉积物中的快速形成和晚期胶团在自催化反馈机制的作用下的有序化)。最后,用自组织(耗散结掏) 理论和动力学分析方法揭示出如下结论:①自催化反馈机理是胶团中杂质元素的催化结晶;②胶团在有序化过程中能形成时-空有序的自组织结构即鲕粒同心层;③胶团中凝胶浓度和杂质元素浓度在相空间内为一极限环,定态胶团失稳后将沿着极限环闭轨演化并最终形成同心层状矿物鲕粒。寻找有序结构和自反馈机制是研究自组织结构的有效方法     

露天铁矿禀赋优势等级划分和合理矿业税费的研究

利用自组织神经网络，对我国主要露天铁矿进行了禀赋优势等级划分。权利金大小的确定，应以铁矿资源的资产评估为基础，资产评估时合理成本的取值应是评估矿山所在同一等级矿山的平均成本。矿产资源的原有价值是权利金征收的对象。最后以歪头山为实例，计算了铁矿资源的原有价值和权利金。结果表明，目前对歪头山铁矿征收的税费仍然偏高。