人类承载力研究面临的困境与原因

建立在自然生物种群数量动态基础之上的承载力理论,当其应用于人类生态系统的研究时,遇到了极大的挑战和困惑.总结了人类承载力研究在理论基础、调控机理和估算方法3个方面存在的关键问题与困境,指出在理论基础方面人类承载力的客观性一直是生态学界和经济学界争论的焦点;在调控机理方面,现有的承载力研究尚不能解释人类经济社会增长不符合Logistic增长规律的因素和机理;在估算方法方面,现有的人类承载力估算方法还不能为人类经济社会的实践提供切实可行的决策依据.通过广泛收集和吸纳生态科学、地球科学、物理科学、环境考古学等诸多领域的最新研究成果,指出地球生态系统的复杂性、人类承载力的社会属性和承载力研究思路上存在的偏差是承载力研究困境产生的主要原因,在此基础上提出了解决承载力研究困境的研究思路和未来研究重点.     

Estimation of human carrying capacity in rainforest areas

Tropical rainiorest areas are rapidly being settled as a result of continued growth of local populations, spontaneous migration from non-rainiorest areas and planned settlement projects undertaken by governments. National decision makers frequently view rainiorest settlement as a solution to the problems of other regions undergoing population growth, land tenure concentration, environmental degradation, agricultural mechanization and population displacement by development projects. Natural habitats are replaced by settlements that often cannot support the density of population expected of them. Inappropriate assumptions can lead to estimates that are orders of magnitude too high, such as an FAO calculation that Brazil could support over seven billion people if Amazonia were converted to intensive agriculture. Inadequate information on human carrying capacity allows planners to foster unrealistic expectations.     

Novelties that change carrying capacity

Comparative developmental studies have revealed a rich array of details about the patterns and processes of morphological change in animals and increasingly in plants. But, applying these insights to the study of major episodes of evolutionary innovation requires understanding how these novel morphologies become established and sufficiently abundant (either as individuals within a species or as a clade of species) to be preserved in the fossil record, and, in many cases, to influence ecological processes. Evolutionary novelties may: (1) disappear without changing the species; (2) be associated with the generation (through selection or drift) of a new species; and if the latter (3) may or may not become ecologically significant. Only the latter are commonly preserved in the fossil record. These alternatives mirror the distinction among historians of technology between innovation and invention. Here, I argue that specific sorts of evolutionary inventions drive ecological transformation, essentially constructing an environment for themselves and ancillary organisms through ecological spillover effects, increasing the "carrying capacity" of an ecosystem.     

The carrying capacity of ecosystems

We analyse the concept of carrying capacity (CC), from populations to the biosphere, and offer a definition suitable for any level. For communities and ecosystems, the CC evokes density‐dependence assumptions analogous to those of population dynamics. At the biosphere level, human CC is uncertain and dynamic, leading to apprehensive rather than practical conclusions. The term CC is widely used among ecological disciplines but remains vague and elusive. We propose the following definition: the CC is ‘the limit of growth or development of each and all hierarchical levels of biological integration, beginning with the population, and shaped by processes and interdependent relationships between finite resources and the consumers of those resources’. The restrictions of the concept relate to the hierarchical approach. Emergent properties arise at each level, and environmental heterogeneity restrains the measurement and application of the CC. Because the CC entails a myriad of interrelated, ever‐changing biotic and abiotic factors, it must not be assumed constant, if we are to derive more effective and realistic management schemes. At the ecosystem level, stability and resilience are dynamic components of the CC. Historical processes that help shape global biodiversity (e.g. continental drift, glaciations) are likely drivers of large‐scale changes in the earth's CC. Finally, world population growth and consumption of resources by humanity will necessitate modifications to the paradigm of sustainable development, and demand a clear and fundamental understanding of how CC operates across all biological levels.     

生态承载力研究进展

基于生态承载力的概念发展,介绍了常用的生态承载力研究方法,包括生态足迹法、人类净初级生产力占用法、状态空间法、综合评价法、系统模型法和生态系统服务消耗评价法,并客观评述了这些方法的优缺点,指出了目前生态承载力研究中存在的薄弱环节。未来生态承载力研究需要完善理论体系,深入研究承载力过程机理与承载机制,将生态系统服务的空间流动因素纳入评估体系,构建完善的评价指标体系,加强生态承载力时空动态评估。最终将生态承载力作为解决生态脆弱区资源环境问题的抓手,建立区域资源环境监测预警机制,并落实到主体功能规划和生态安全建设上,为生态文明建设提供有力的科学依据。     

基于生态系统净化与人为调控耦合作用的水环境承载力评估

针对目前水环境承载力相关研究中未突显生态系统净化作用和人为调控作用的问题,从生态系统污染净化功能和人为调控污染削减功能两个角度,提出基于生态系统净化-人为调控耦合作用的水环境承载力概念,并构建流域环境承载力评估模型。以滇池流域为例,计算了2015年滇池流域水环境承载力。研究结果表明:滇池流域2015年水环境承载力综合指数为1.16,处于超载状态;流域环境承载力分布呈现北高南低,北部限制因子化学需氧量,南部为总磷;调水工程调入水量出境携带污染物约为流域水环境承载力的16%,对流域水环境改善十分重要;人为调控污染削减能力在流域水环境承载力中所占比例已超过50%,成为不可忽视的一部分。     

环境承载力研究进展

进行环境承载力理论与量化方法的研究,对于指导人类社会经济活动,协调人类发展与环境的关系,具有十分重要而迫切的现实意义.本文论述了环境承载力概念的发展过程,并从“容量”、“阈值”和“能力”三方面介绍了环境承载力定义,指出了环境承载力具有客观性和主观性、区域性和时间性、动态性和可调控性的主要特征.在此基础上,对目前国内外用于环境承载力定量化研究的指数评价法、承载率评价法、系统动力学方法和多目标模型最优化等方法进行了分析,最后对环境承载力研究的发展趋势进行了讨论.     

Bivalve carrying capacity in coastal ecosystems

The carrying capacity of suspension feeding bivalvesin 11 coastal and estuarine ecosystems is examined. Bivalve carrying capacity is defined in terms of watermass residence time, primary production time andbivalve clearance time. Turnover times for the 11ecosystems are compared both two and threedimensionally. Fast systems, e.g., Sylt and NorthInlet, have turnover times of days or less, while,slow systems, e.g., Delaware Bay, have turnover timesof months and years. Some systems,Marennes-Oléron, South San Francisco Bay and NorthInlet, require a net influx of phytoplankton in orderto support their bivalve populations. Three systems,Carlingford Lough, Chesapeake Bay and Delaware Bay,have very long bivalve clearance times due to small orreduced bivalve filter feeder populations. Carlingford Lough stands out because it is a naturallyplanktonic system now being converted to bivalveculture with an adherently stronger benthic-pelagiccoupling. Existing models of bivalve carrying capacity arereviewed. The Herman model is utilized as anappropriate ecosystem level model to examine carryingcapacity because it includes the three major turnovertime elements of water mass residence time, primaryproduction time and bivalve filter feeder clearancetime. The graphical analysis suggests that massive andsuccessful bivalve filter feeder populations are foundin systems with relatively short residence times(<40 days) and short primary production times (<4days) in order to sustain a high bivalve biomass withits associated rapid clearance times. Outliersystems are constrained by long water mass residencetimes, extended primary production times, and longclearance times. This revised version was published online in August 2006 with corrections to the Cover Date.     

The carrying capacity for species richness

The idea that the number of species within an area is limited by a specific capacity of that area to host species is old yet controversial. Here, we show that the concept of carrying capacity for species richness can be as useful as the analogous concept in population biology. Many lines of empirical evidence indicate the existence of limits of species richness, at least at large spatial and phylogenetic scales. However, available evidence does not support the idea of diversity limits based on limited niche space; instead, carrying capacity should be understood as a stable equilibrium of biodiversity dynamics driven by diversity‐dependent processes of extinction, speciation and/or colonization. We argue that such stable equilibria exist even if not all resources are used and if increasing species richness increases the ability of a community to use resources. Evaluating the various theoretical approaches to modelling diversity dynamics, we conclude that a fruitful approach for macroecology and biodiversity science is to develop theory that assumes that the key mechanism leading to stable diversity equilibria is the negative diversity dependence of per‐species extinction rates, driven by the fact that population sizes of species must decrease with an increasing number of species owing to limited energy availability. The recently proposed equilibrium theory of biodiversity dynamics is an example of such a theory, which predicts that equilibrium species richness (i.e., carrying capacity) is determined by the interplay of the total amount of available resources, the ability of communities to use those resources, environmental stability that affects extinction rates, and the factors that affect speciation and colonization rates. We argue that the diversity equilibria resulting from these biodiversity dynamics are first‐order drivers of large‐scale biodiversity patterns, such as the latitudinal diversity gradient.     

城市生态系统承载力理论与评价方法

城市作为一个复杂的人工生态系统,其承载力的意义与生态学中的种群承载力意义有了很大差别。定义了城市生态系统承载力,强调其对维系城市生态系统健康的能动性特征,并在比较生物免疫力与城市生态系统承载力的相似性的基础上,构建了“城市生态系统承载力免疫学模型”作为其理论模型。在理论模型基础上设计其计量模型,分为天然承载力和获得性承载力两部分。并通过承载力与压力的相对变化趋势表达城市生态系统维系其健康水平的能力。以广州市为例,计算了广州市城市生态系统承载力与压力,获得二者的动态关系。结果表明,自1992年以来,广州市基本上处于一种经济发展与城市生态系统支持力同步发展的良性状态,所采取的发展模式具有可持续性     

生态承载力研究和应用进展

生态承载力研究是解决资源-环境矛盾、实现区域可持续发展的重要基础,也是地理学、生态学和经济学关注的热点与前沿领域.本文在综述国内外相关研究成果的基础上,阐述了生态承载力的概念内涵,即对复合生态系统支持力和压力的表征;评述了常用的研究方法,即净初级生产力估测法、生态足迹法、供需平衡法、综合指标评价法和系统模型法;介绍了目前较为关注的流域、生态脆弱区、城市、农业区和旅游区生态承载力的研究进展;总结了目前生态承载力研究存在的缺乏科学完整的研究体系、阈值的生态学指示意义不明确、动态演化与预测研究不够深入、空间尺度与格局分异涉足较少等问题;并据此提出未来应在作用机理、模型构建和实践应用方面加强研究.     

生态承载力与崇明岛生态建设

概述了崇明岛的生态建设目标及历史背景,分析了崇明岛生态经济现状和制约因素,阐明了崇明岛生态建设要解决的科学问题.据此提出,崇明生态岛建设科学研究应从生态承载力研究着手,紧密结合崇明岛的区域特点,研究借鉴国内外生态岛资源节约型可持续发展模式,从系统和动态的观点出发,综合研究崇明岛生态承载力现状和发展动态,提出操作性强的提升崇明岛生态承载力的对策,制定与区域生态承载力相适应的新型产业结构、人口规模调整和优化布局方案,构建崇明岛有效的生态安全预警调控系统,为崇明生态岛经济发展和环境资源可持续利用提供建议和战略决策依据.     

A stochastic model for estimating human carrying capacity in Brazil's Transamazon Highway colonization area

Human carrying capacity for tropical agricultural populations can be estimated with a computer simulation of the agroecosystem. A stochastic model is developed for estimating carrying capacity in one of the government-directed small farmer settlement projects along Brazil's Transamazon Highway. Carrying capacity is operationally defined in terms of an empirically computed relationship between population density and probability of colonist failure with respect to various criteria. When high population density leads failure probability to exceed a maximum acceptable level, population can be considered to be above carrying capacity. Colonist failure probabilities are those that are sustainable over a long period of simulated years. High variability in crop yields appears to have a strong effect on failure probability based on comparison of deterministic and stochastic runs of the simulations. Failure probabilities are raised by variability at low population densities, but are lowered at extremely high densities where most colonists would fail in an average year. Effects can be tested for colonists with different backgrounds or with differing agricultural practices such as fallow times. Failure probabilities in standard runs are higher than those considered acceptable to government planners at all population densities simulated in the present study's stochastic runs (lowest density 24 persons/km²), thus lending support to the informal impression of many that the carrying capacity of most of Amazonia's uplands is low.Funds have come from National Science Foundation dissertation improvement grant GS-42869, to Dr. Daniel H. Janzen, a Resources for the Future predoctoral fellowship, two fellowships from the Institute for Environmental Quality, the University of Michigan, and two grants from the Programa de Trópico Úmido of the Conselho Nacional de Desenvolvimento Científico e Technológico.     

Minimum requirements for modelling bivalve carrying capacity

The concept of carrying capacity of an ecosystem fornatural populations is derived from the logisticgrowth curve in population ecology, and defined as themaximum standing stock that can be supported by agiven ecosystem for a given time. This definitionneeds to be modified for the exploitation ofecosystems. Carrying capacity for exploitation isdefined as the standing stock at which the annualproduction of a marketable cohort is maximized. Forbivalve suspension feeders, the dominant factordetermining the exploitation carrying capacity at theecosystem scale is primary production. At a localscale carrying capacity depends on physicalconstraints such as substrate, shelter and food supplyby tidal currents.We evaluate critically some existing models ofexploited ecosystems for shellfish cultivation inorder to formulate the minimum requirements of ageneric carrying capacity model. Generic models canbe developed for both the ecosystem scale and thelocal scale, depending on the aim of the modelling.Transport processes, sediment dynamics and submodelsfor organism and population level processes areminimum requirements for carrying capacity modelling. This revised version was published online in August 2006 with corrections to the Cover Date.     

The respiratory gas carrying capacity of ascidian blood

• 1.1. The respiratory function of ascidian blood as an oxygen carrier is marginal and equal to sea-water.
• 2.2. The main gas flux is by diffusion.

     

Predator-prey systems with a perturbed periodic carrying capacity

In this paper we perturb the constant carrying capacity of a predatorprey model. Non-critical cases and critical cases are investigated for existence and stability of periodic solutions.     

基于生态承载力的城市生态调控

城市生态系统承载力反映了城市生态支持系统对城市发展的支撑功能,它是供给与需求的统一体,社会经济发展的无限需求与生态支持系统的有限供给之间的矛盾决定了城市生态系统承载力的阈限必然存在。引入生态承载力理论,结合其阈限性,解析了导致城市生态危机的生态承载力供需失衡根源。而生态承载力的阈限特征通常在少数瓶颈要素上表现出来,因此城市生态调控最终落脚到调节生态承载力瓶颈要素的供需上。针对瓶颈要素,给出了城市生态调控的层次、方法和蓝图,即从自然、功能和人文3个层次,根据具体情况采取调节供给或需求的措施进行生态调控,最终实现稳定的、持续的城市发展。     

Estimating the home range and carrying capacity for takahe (

Predator-free offshore islands play an important role in the conservation of many of New Zealand's endemic species. Takahe (Porphyrio mantelli) have small populations established on four offshore islands and although hatching success is lower than that of the wild mainland population in Fiordland, juvenile and adult survival is high and populations are growing exponentially. Accurate estimates of home range size and potential carrying capacities are therefore essential for the future management of the population as a whole. The mean home range size of takahe pairs in one study population on Mana Island (217 ha) was 2.8 ± 1.9 ha. The island was assessed for current and maximum available area for takahe and the potential carrying capacity was estimated at 22—53 pairs. Current and maximum available areas were also used to calculate carrying capacities on each of three other islands using two different estimates of mean home range size for Maud Island (7—34 pairs) and Kapiti Island (5—33 pairs) and one estimate of home range size for Tiritiri Matangi Island (25 pairs). A model of the population growth of takahe on islands predicted that estimated carrying capacities would be reached between 1997 and 2009. The urgency of planning to make use of the considerable potential of island populations of takahe is stressed.     

Microbial carrying capacity and carbon biomass of plastic marine debris

Trillions of plastic debris fragments are floating at sea, presenting a substantial surface area for microbial colonization. Numerous cultivation-independent surveys have characterized plastic-associated microbial biofilms, however, quantitative studies addressing microbial carbon biomass are lacking. Our confocal laser scanning microscopy data show that early biofilm development on polyethylene, polypropylene, polystyrene, and glass substrates displayed variable cell size, abundance, and carbon biomass, whereas these parameters stabilized in mature biofilms. Unexpectedly, plastic substrates presented lower volume proportions of photosynthetic cells after 8 weeks, compared to glass. Early biofilms displayed the highest proportions of diatoms, which could influence the vertical transport of plastic debris. In total, conservative estimates suggest 2.1 × 10²¹ to 3.4 × 10²¹ cells, corresponding to about 1% of the microbial cells in the ocean surface microlayer (1.5 × 10³ to 1.1 × 10⁴ tons of carbon biomass), inhabit plastic debris globally. As an unnatural addition to sea surface waters, the large quantity of cells and biomass carried by plastic debris has the potential to impact biodiversity, autochthonous ecological functions, and biogeochemical cycles within the ocean.Subject terms: Microbial ecology, Environmental sciences