The use of structural dynamic models to explain successes and failures of biomanipulation

A development of a structural dynamic model, i.e. a model with current change of the most important parameters according to a goal function, is presented with the aim to explain the structural changes observed in lakes, when the nutrient concentration is increased or decreased. This type of models may be important in lake management as it may be possible qualitatively to predict the success or failure of biomanipulation. The answer to the crucial question: àt which phosphorus level will the success of biomanipulation be most probable?' will probably require the development of model which takes into account site specific processes and properties, i.e., a more complicated model. As goal function is proposed the thermodynamic function, exergy, which is defined as the work content of the system (model) compared with the system at thermodynamic equilibrium. It is shown that the structural dynamic modelling approach has been able to explain the shift from large to small zooplankton species at a certain level of phosphorus concentration, accompanied by a shifts from a dominance of zooplankton, and predatory fish to a system dominated by planktivorous fish and phytoplankton. The shift in zooplankton species cannot be explained by application of catastrophe theoretical models, which have been used to explain the hysteresis reaction. The results show that the shift should be expected at approximately 0.12 mg P l-1 and that a typical hysteresis reaction occurs at this concentration in accordance with the expectations. These results are consistent with many observations but should be interpreted with great caution, as the model is simple and general and don't account for a number of processes which may influence the results significantly in specific lake studies. The structural dynamic approach has previously been used in ten case studies with good agreement with the observations, but more case studies are needed before a general recommendation of the use of this type of models can be given. The results from this study point toward to apply this type of models for lake management where biomanipulation is involved, although it should be recommended to improve the presented general model with introduction of site specific properties for a considered lake study.     

Ecosystem engineering in space and time

The ecosystem engineering concept focuses on how organisms physically change the abiotic environment and how this feeds back to the biota. While the concept was formally introduced a little more than 10 years ago, the underpinning of the concept can be traced back to more than a century to the early work of Darwin. The formal application of the idea is yielding new insights into the role of species in ecosystems and many other areas of basic and applied ecology. Here we focus on how temporal, spatial and organizational scales usefully inform the roles played by ecosystem engineers and their incorporation into broader ecological contexts. Two particular, distinguishing features of ecosystem engineers are that they affect the physical space in which other species live and their direct effects can last longer than the lifetime of the organism – engineering can in essence outlive the engineer. Together, these factors identify critical considerations that need to be included in models, experimental and observational work. The ecosystem engineering concept holds particular promise in the area of ecological applications, where influence over abiotic variables and their consequent effects on biotic communities may facilitate ecological restoration and counterbalance anthropogenic influences.     

The Urban Funnel Model and the Spatially Heterogeneous Ecological Footprint

Urban ecological systems are characterized by complex interactions between the natural environment and humans at multiple scales; for an individual urban ecosystem, the strongest interactions may occur at the local or regional spatial scale. At the regional scale, external ecosystems produce resources that are acquired and transported by humans to urban areas, where they are processed and consumed. The assimilation of diffuse human wastes and pollutants also occurs at the regional scale, with much of this process occurring external to the urban system. We developed the urban funnel model to conceptualize the integration of humans into their ecological context. The model captures this pattern and process of resource appropriation and waste generation by urban ecosystems at various spatial scales. This model is applied to individual cities using a modification of traditional ecological footprint (EF) analysis that is spatially explicit; the incorporation of spatial heterogeneity in calculating the EF greatly improves its accuracy. The method for EF analysis can be further modified to ensure that a certain proportion of potential ecosystem services are left for in situ processes. Combining EF models of human appropriation with ecosystem process models would help us to learn more about the effects of ecosystem service appropriation. By comparing the results for food and water, we were able to identify some of the potentially limiting ecological factors for cities. A comparison of the EFs for the 20 largest US cities showed the importance of urban location and interurban competition for ecosystem services. This study underscores the need to take multiple scales and spatial heterogeneity into consideration to expand our current understanding of human–ecosystem interactions. The urban funnel model and the spatially heterogeneous EF provide an effective means of achieving this goal. Received 17 October 2000; accepted 31 May 2001.     

湖泊水库结构生态动态模型

综述了湖泊水库结构生态动态模型的研究进展及其在湖泊水库环境生态模拟中的应用。结果表明,热力学理论为获取湖泊水库生态系统的特性提供了一条整体性的途径,热力学概念“Ｙｏｎｇ”可将生态学理论（达尔文理论）和热力学理论（最大Ｙｏｎｇ原理）很好地联系起来。引入Ｙｏｎｇ后,许多重要模型参数的目标函数可根据最大Ｙｏｎｇ原理获得,达尔文“达者生存”理论可被定量为一个生态约束条件用于发展湖泊水库结构生态结构模型,从     

森林生态系统发展和植物种群变化的热力学过程

随着生态学的发展,人们对自然生态系统的认识逐渐从对自然现象的记录、描述,发展为对机制的系统认识。热力学定律为人们提供了认识系统发展规律的理论基础,但在生态系统中的应用还处于起步阶段。基于前人关于生态系统可用能的研究。探讨了森林生态系统和植物种群变化的热力学过程。在生态系统水平上,把可用能耗散分为了植物耗散和环境耗散两个部分,并探讨了这两个过程之间的关系。第一次明确地提出蒸散是植物耗散的主要部分。在植物种群水平上,“可用能储存”与“可用能耗散”是决定植物竞争力的关键因子,在同一区域相同条件下,拥有更大可用能耗散能力的物种应当被优先选择。因此,群落中的优势物种应当比同层次的伴生种具有相对高的生长速度和更强的蒸腾能力。研究试图在热力学理论体系与实际生态系统的生理生态过程之间建立了纽带和桥梁,为开展森林生态系统的健康评估、深刻认识植物与环境的关系、以及评价物种竞争能力提供新的理论视野。     

Bayesian networks as a novel tool to enhance interpretability and predictive power of ecological models

In today's world, it is becoming increasingly important to have the tools to understand, and ultimately to predict, the response of ecosystems to disturbance. However, understanding such dynamics is not simple. Ecosystems are a complex network of species interactions, and therefore any change to a population of one species will have some degree of community level effect. In recent years, the use of Bayesian networks (BNs) has seen successful applications in molecular biology and ecology, where they were able to recover plausible links in the respective systems they were applied to. The recovered network also comes with a quantifiable metric of interaction strength between variables. While the latter is an invaluable piece of information in ecology, an unexplored application of BNs would be using them as a novel variable selection tool in the training of predictive models. To this end, we evaluate the potential usefulness of BNs in two aspects: (1) we apply BN inference on species abundance data from a rocky shore ecosystem, a system with well documented links, to test the ecological validity of the revealed network; and (2) we evaluate BNs as a novel variable selection method to guide the training of an artificial neural network (ANN). Here, we demonstrate that not only was this approach able to recover meaningful species interactions networks from ecological data, but it also served as a meaningful tool to inform the training of predictive models, where there was an improvement in predictive performance in models with BN variable selection. Combining these results, we demonstrate the potential of this novel application of BNs in enhancing the interpretability and predictive power of ecological models; this has general applicability beyond the studied system, to ecosystems where existing relationships between species and other functional components are unknown.     

Assessement and management of environmental quality conditions in marine sandy beaches for its sustainable use—Virtues of the population based approach

Sandy beaches constitute high natural value ecosystems which have been worldwide a target for growing human activities and ensuing pressures in the last decades, which caused ecological damages on these environments and led to its environmental quality decline. However, little is known about the responses of these ecosystems to distinct stressors and pressures, and holistic and integrated coastal management actions that protect beach environments and their ecological processes are yet to be developed. The aim of this viewpoint article is to present and discuss the utility of using a population approach to macrofaunal key species as a helpful tool for the assessment, management, and sustainable use of sandy beaches. The role of macrofaunal key species as indicators of environmental changes and of ecological quality condition is discussed and illustrated by some practical examples from the literature. The population is presented as a highly relevant ecological unit in management and one of the easiest ones to use, responding more rapidly to disturbances in the ecosystem than the most complex units. In this context, bio-ecology and population dynamics models are presented as tools and their potential, to improve the way we assess and manage ecological quality conditions of beach ecosystems aiming at its sustainable use, are discussed. Also, the advantages and drawbacks of the use of these tools in the population approach are evaluated. Monitoring, assessment and management practices focusing on beach key species bio-ecology as ecological indicator hold large potential in nowadays fast changing scenario, and should be encouraged as a function of their identifiable responses to manmade and natural disturbances.     

Mediterranean vegetation dynamics: modelling problems and functional types

Gap models have been applied to a wide range of ecosystems, mainly temperate and boreal forests, but rarely have such models been applied to Mediterranean ecosystems. In the present review we address some problems of gap models for predicting the long-term dynamics of Mediterranean ecosystems, and we suggest plant functional types suitable for modelling based on responses to disturbance. Most gap models do not take into account different life forms, interactions with fire (e.g., resprouting and stimulation of the germination), and underground structures. Long term human impact on Mediterranean ecosystems has made a significant impact on the current landscapes. That intense land use, involving long-lived slow-growing species, has had long-term consequences. It is not possible to understand Mediterranean vegetation and to validate any model without considering these factors. The lack of data for Mediterranean species may be overcome by taking into account correlations of traits and trade-offs between different functional types. A simple disturbance-based functional group system is discussed.     

Stoichiometric flexibility as a regulator of carbon and nutrient cycling in terrestrial ecosystems under change

Ecosystems across the biosphere are subject to rapid changes in elemental balance and climatic regimes. A major force structuring ecological responses to these perturbations lies in the stoichiometric flexibility of systems - the ability to adjust their elemental balance whilst maintaining function. The potential for stoichiometric flexibility underscores the utility of the application of a framework highlighting the constraints and consequences of elemental mass balance and energy cycling in biological systems to address global change phenomena. Improvement in the modeling of ecological responses to disturbance requires the consideration of the stoichiometric flexibility of systems within and across relevant scales. Although a multitude of global change studies over various spatial and temporal scales exist, the explicit consideration of the role played by stoichiometric flexibility in linking micro-scale to macro-scale biogeochemical processes in terrestrial ecosystems remains relatively unexplored. Focusing on terrestrial systems under change, we discuss the mechanisms by which stoichiometric flexibility might be expressed and connected from organisms to ecosystems. We suggest that the transition from the expression of stoichiometric flexibility within individuals to the community and ecosystem scales is a key mechanism regulating the extent to which environmental perturbation may alter ecosystem carbon and nutrient cycling dynamics.     

Functional responses and scaling in predator-prey interactions of marine fishes: contemporary issues and emerging concepts

Predator-prey interactions are a primary structuring force vital to the resilience of marine communities and sustainability of the world's oceans. Human influences on marine ecosystems mediate changes in species interactions. This generality is evinced by the cascading effects of overharvesting top predators on the structure and function of marine ecosystems. It follows that ecological forecasting, ecosystem management, and marine spatial planning require a better understanding of food web relationships. Characterising and scaling predator-prey interactions for use in tactical and strategic tools (i.e. multi-species management and ecosystem models) are paramount in this effort. Here, we explore what issues are involved and must be considered to advance the use of predator-prey theory in the context of marine fisheries science. We address pertinent contemporary ecological issues including (1) the approaches and complexities of evaluating predator responses in marine systems; (2) the 'scaling up' of predator-prey interactions to the population, community, and ecosystem level; (3) the role of predator-prey theory in contemporary fisheries and ecosystem modelling approaches; and (4) directions for the future. Our intent is to point out needed research directions that will improve our understanding of predator-prey interactions in the context of the sustainable marine fisheries and ecosystem management.     

Spatial modelling of succession-disturbance dynamics in forest ecosystems: Concepts and examples

Over the last few decades it has become increasingly obvious that disturbance, whether natural or anthropogenic in origin, is ubiquitous in ecosystems. Disturbance-related processes are now considered to be important determinants of the composition, structure and function of ecological systems. However, because disturbance and succession processes occur across a wide range of spatio-temporal scales their empirical investigation is difficult. To counter these difficulties much use has been made of spatial modelling to explore the response of ecological systems to disturbance(s) occurring at spatial scales from the individual to the landscape and above, and temporal scales from minutes to centuries. Here we consider such models by contrasting two alternative motivations for their development and use: prediction and exploration, with a focus on forested ecosystems. We consider the two approaches to be complementary rather than competing. Predictive modelling aims to combine knowledge (understanding and data) with the goal of predicting system dynamics; conversely, exploratory models focus on developing understanding in systems where uncertainty is high. Examples of exploratory modelling include model-based explorations of generic issues of criticality in ecological systems, whereas predictive models tend to be more heavily data-driven (e.g. species distribution models). By considering predictive and exploratory modelling alongside each other, we aim to illustrate the range of methods used to model succession and disturbance dynamics and the challenges involved in the model-building and evaluation processes in this arena.     

Considering ecological dynamics in resource selection functions

1.  Describing distribution and abundance is requisite to exploring interactions between organisms and their environment. Recently, the resource selection function (RSF) has emerged to replace many of the statistical procedures used to quantify resource selection by animals.
2.  A RSF is defined by characteristics measured on resource units such that its value for a unit is proportional to the probability of that unit being used by an organism. It is solved using a variety of techniques, particularly the binomial generalized linear model.
3.  Observing dynamics in a RSF – obtaining substantially different functions at different times or places for the same species – alerts us to the varying ecological processes that underlie resource selection.
4.  We believe that there is a need for us to reacquaint ourselves with ecological theory when interpreting RSF models. We outline a suite of factors likely to govern ecologically based variation in a RSF. In particular, we draw attention to competition and density-dependent habitat selection, the role of predation, longitudinal changes in resource availability and functional responses in resource use.
5.  How best to incorporate governing factors in a RSF is currently in a state of development; however, we see promise in the inclusion of random as well as fixed effects in resource selection models, and matched case–control logistic regression.
6.  Investigating the basis of ecological dynamics in a RSF will allow us to develop more robust models when applied to forecasting the spatial distribution of animals. It may also further our understanding of the relative importance of ecological interactions on the distribution and abundance of species.     

基于生态流方法的土地整治项目对农田生态系统的影响研究

将土地整治活动作为外界对农田生态系统(项目区)集中性的外部激励,以陕西关中凤翔县典型土地整治项目为例,分析了项目实施前后生态流(物质流、能量流、信息流)变化状况,建立了土地整治生态影响概念性模型,明确了相应生态流的流向与路径关系,使用可用能法和能值法测算项目区外部输入及生态产品输出,应用生态流分析法,对土地整治项目生态流和系统效率进行了定量计算。根据设定的土地整治工程使用年限,评估了项目实施后区域净生态价值、自然资源依赖度、可更新资源依赖度、生态产出率、生态承载力和生态可持续度等指标的时间变化过程。得到以下研究结果:(1)可用能法和能值法测算出的系统生态效益均呈现由项目建设初期陡降为负值,而后指数增加,再趋于平稳的过程;(2)可用能法测算出项目实施后的第29年,生态效益由亏转盈,体现出系统从被扰乱后恢复自然平衡状态的过程;(3)能值法测算出项目实施后的第4年,生态系统趋于平衡状态;(4)研究区土地整治项目的经济效益为负,于项目实施3a后趋于平稳,总投资中农业生产年投入占资金总额的78.35%。通过可用能和能值方法的结合,可以定量计算系统稳定性,为土地整治项目的物质、劳动力和资金投资选择等提供借鉴。     

种群生存力分析研究进展和趋势

种群生存力分析（PVA）是正在迅速发展的新方法,已成为保护生物学研究的热点。它主要研究随机干扰对小种群绝灭的影响,其目的是制定最小可存活种群（MVP）,把绝灭减少到可接受的水平。随机干扰可分四类;统计随机性,环境随机性,自然灾害和遗传随机性。确定MVP的方法有三种：理论模型,模拟模型,模拟模型和岛屿生物地理学方法。理论模型主要研究理想或特定条件下随机因素对种群的影响;模拟模型是利用计算机模拟种群绝灭过程;岛屿生物地理学方法主要分析岛屿物种的分布和存活,证实分析模型和模拟模型。已有大量的文献研究统计随机性,环境随机性和自然灾害的行为特征,但遗传因素与种群生存力之间的关系还不清楚。建立包括四种随机性的综合性模型,广泛地检验PVA模型,系统地研制目标种的遗传和生态特性以及MVP的实际应用是PVA的发展趋势。     

国家公园生态系统健康测度模型构建及黄山实证研究

国家公园是中国生态文明建设的重要制度实践,其生态系统健康的科学评估是国家公园分区管理、空间管制、生态保护的基础。国家公园生态系统具有特殊性和复合性,区别于城市、流域、湿地等生态系统,亟需建立一套适合国家公园生态系统的生态系统健康测度模型。基于国家公园生态系统的特殊性和生态系统健康概念的多维性,探讨了现有模型存在的问题和不足,从生态系统与人类活动交互的视角,建立了"VSR"(生态活力Vigor、服务能力Service、抗干扰力Resilience)国家公园生态系统健康测度模型。此外,将"VSR"模型应用到黄山国家公园生态系统健康的测度中,可视化了黄山国家公园生态系统健康的时空过程和格局,通过随机森林回归模型和增强回归树模型验证了"VSR"模型的有效性和稳定性。"VSR"国家公园生态系统健康测度模型有效量化了国家公园生态系统健康的时空差异性和时空动态性,为国家公园空间管制、生态保护等目标实施提供了科学支撑。     

Estimating co-extinction threats in terrestrial ecosystems

The biosphere is changing rapidly due to human endeavour. Because ecological communities underlie networks of interacting species, changes that directly affect some species can have indirect effects on others. Accurate tools to predict these direct and indirect effects are therefore required to guide conservation strategies. However, most extinction-risk studies only consider the direct effects of global change—such as predicting which species will breach their thermal limits under different warming scenarios—with predictions of trophic cascades and co-extinction risks remaining mostly speculative. To predict the potential indirect effects of primary extinctions, data describing community interactions and network modelling can estimate how extinctions cascade through communities. While theoretical studies have demonstrated the usefulness of models in predicting how communities react to threats like climate change, few have applied such methods to real-world communities. This gap partly reflects challenges in constructing trophic network models of real-world food webs, highlighting the need to develop approaches for quantifying co-extinction risk more accurately. We propose a framework for constructing ecological network models representing real-world food webs in terrestrial ecosystems and subjecting these models to co-extinction scenarios triggered by probable future environmental perturbations. Adopting our framework will improve estimates of how environmental perturbations affect whole ecological communities. Identifying species at risk of co-extinction (or those that might trigger co-extinctions) will also guide conservation interventions aiming to reduce the probability of co-extinction cascades and additional species losses.     

湖泊富营养化模型研究进展

自多湖泊富营养化引起人类注意以来,科学家们就设法通过使用数学模型来模拟湖泊富营养化的发生,预测湖泊对不同管理措施的响应,以便批出合理的治理措施。总的来说,湖泊富营养化模型大概经历了以下三个发展阶段：（1）单限制因子模型,如磷模型;（2）多限制因子模型,如浮游植物初级生产力估测模型;（3）生态－动力学模型,它是目前也是以后发展的主不充。随着人们对湖泊生态系统认识的提高和计算机技术的发展,生态与水动力耦合模型、面向对象模型和神经网络模型等具有良好的发展前景。     

Developing approaches for linear mixed modeling in landscape genetics through landscape‐directed dispersal simulations

Dispersal can impact population dynamics and geographic variation, and thus, genetic approaches that can establish which landscape factors influence population connectivity have ecological and evolutionary importance. Mixed models that account for the error structure of pairwise datasets are increasingly used to compare models relating genetic differentiation to pairwise measures of landscape resistance. A model selection framework based on information criteria metrics or explained variance may help disentangle the ecological and landscape factors influencing genetic structure, yet there are currently no consensus for the best protocols. Here, we develop landscape‐directed simulations and test a series of replicates that emulate independent empirical datasets of two species with different life history characteristics (greater sage‐grouse; eastern foxsnake). We determined that in our simulated scenarios, AIC and BIC were the best model selection indices and that marginal R² values were biased toward more complex models. The model coefficients for landscape variables generally reflected the underlying dispersal model with confidence intervals that did not overlap with zero across the entire model set. When we controlled for geographic distance, variables not in the underlying dispersal models (i.e., nontrue) typically overlapped zero. Our study helps establish methods for using linear mixed models to identify the features underlying patterns of dispersal across a variety of landscapes.     

Using multilevel models to quantify heterogeneity in resource selection

Models of resource selection are being used increasingly to predict or model the effects of management actions rather than simply quantifying habitat selection. Multilevel, or hierarchical, models are an increasingly popular method to analyze animal resource selection because they impose a relatively weak stochastic constraint to model heterogeneity in habitat use and also account for unequal sample sizes among individuals. However, few studies have used multilevel models to model coefficients as a function of predictors that may influence habitat use at different scales or quantify differences in resource selection among groups. We used an example with white-tailed deer (Odocoileus virginianus) to illustrate how to model resource use as a function of distance to road that varies among deer by road density at the home range scale. We found that deer avoidance of roads decreased as road density increased. Also, we used multilevel models with sika deer (Cervus nippon) and white-tailed deer to examine whether resource selection differed between species. We failed to detect differences in resource use between these two species and showed how information-theoretic and graphical measures can be used to assess how resource use may have differed. Multilevel models can improve our understanding of how resource selection varies among individuals and provides an objective, quantifiable approach to assess differences or changes in resource selection. © 2011 The Wildlife Society.