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。     

区域经济发展动力系统的构建与运行机制研究

区域经济发展需要动力,解决动力问题一直是区域经济学、经济地理学、发展经济学等学科长期研究的重点领域。单一动力对区域经济发展能够产生一定的功效,但缺乏系统动力是区域经济发展中一个普遍存在的问题。在科学发展观背景下,通过对区域经济发展要素的分类与综合分析,提出了"合动力网络"的概念,以自组织结构动力、技术创新动力、制度创新动力和文化动力为子系统,初步构建了区域经济发展的动力系统,并分析了动力系统及其子系统的相互作用关系和运行机制。     

Typhoon Vortex Self-Organization in a Baroclinic Environment

Self-organization of typhoon vortex in a baroclinic environment is studied based on eight numerical experiments with the fifth-generation Pennsylvania State University/National Center for Atmospheric Research （PSU/NCAR） Mesoscale Model （MM5）. The results show that, when there are only two 400-km-away mesoscale axisymmetric vortices with a radius of 500 km in the initial field, the two vortices move away from each other during co-rotating till the distance between them greater than a critical distance named co-rotating critical distance. Then, they stop co-rotating. The situation is changed when a small vortex with a radius of 80 kin is introduced in between the two vortices in the initial field, with the two initially separated vortices approaching each other during their co-rotation, and finally self-organizing into a typhoon-like vortex consisting of an inner core and spiral bands. This result supports both Zhou Xiuji＇s view in 1994 and the studies in the barotropic framework concerning the interactions between the same and different scales of vortices. Six other experiments are carried out to study the effects of the initial vortex parameters, including the initial position of the small-scale vortex, the distance and intensity of the initially axisymmetric binary mesoscale vortices. It is found that the distance between the initial axisymmetrie mesoscale vortices is the most important parameter that influences the self-organizing process of the final typhoon-like vortex. This conclusion is similar to that obtained from barotropical model experiments.