Lags in the response of mountain plant communities to climate change

Rapid climatic changes and increasing human influence at high elevations around the world will have profound impacts on mountain biodiversity. However, forecasts from statistical models (e.g. species distribution models) rarely consider that plant community changes could substantially lag behind climatic changes, hindering our ability to make temporally realistic projections for the coming century. Indeed, the magnitudes of lags, and the relative importance of the different factors giving rise to them, remain poorly understood. We review evidence for three types of lag: “dispersal lags” affecting plant species’ spread along elevational gradients, “establishment lags” following their arrival in recipient communities, and “extinction lags” of resident species. Variation in lags is explained by variation among species in physiological and demographic responses, by effects of altered biotic interactions, and by aspects of the physical environment. Of these, altered biotic interactions could contribute substantially to establishment and extinction lags, yet impacts of biotic interactions on range dynamics are poorly understood. We develop a mechanistic community model to illustrate how species turnover in future communities might lag behind simple expectations based on species’ range shifts with unlimited dispersal. The model shows a combined contribution of altered biotic interactions and dispersal lags to plant community turnover along an elevational gradient following climate warming. Our review and simulation support the view that accounting for disequilibrium range dynamics will be essential for realistic forecasts of patterns of biodiversity under climate change, with implications for the conservation of mountain species and the ecosystem functions they provide.     

大尺度陆地生态系统动态变化与空间变异的过程模型及模拟系统

当代生态系统科学研究更加关注区域生态环境及生态系统状态变化的监测、评估、预测、预警及生态环境可持续管理。在深入理解陆地生态系统的要素、过程、功能、格局及其相互作用机理基础上,发展生态系统定量化描述方法和数值模拟技术,集成构建大陆尺度的“多过程耦合-多技术集成-多目标应用”的陆地生态系统数值模拟器已成为生态系统与全球变化及其资源、环境和灾害效应科学研究的重要科技任务。本研究围绕宏观生态系统模拟分析方法问题,在回顾陆地生态系统模型研究现状和发展趋势的基础上,深入讨论开发大尺度陆地生态系统动态变化和空间变异及其资源环境效应模拟系统的理念,以及模拟系统的功能定位、结构设计等基本问题,为构造中国陆地生态系统数值模拟器提供参考。     

The Value of Animal Behavior in Evaluations of Restoration Success

Animals are key members of ecosystems, contributing to processes like pollination, seed dispersal, and herbivory. Incorporating measures of animal behavior into evaluations of restoration success will provide critical information that is not available from animal species composition and richness estimates derived from the documentation of species presence and absence. Behavioral studies will (1) allow comparisons of the habitat quality of target and reference sites based on behaviors that have fitness consequences for organisms; (2) provide valuable information about reasons for differences in habitat quality; (3) identify critical resources that make a site suitable or not for particular species; and/or (4) provide information on the mechanisms through which species contribute to ecosystem functions. When resources for the evaluation of restoration success are available, practitioners should carefully consider the costs and benefits of the different variables they could quantify. In some cases, it may be more important to compare the behavior of one or a few critical animal species that contribute to ecosystem function rather than try to document the presence or absence of all species.     

Coordinated approaches to quantify long‐term ecosystem dynamics in response to global change

Many serious ecosystem consequences of climate change will take decades or even centuries to emerge. Long‐term ecological responses to global change are strongly regulated by slow processes, such as changes in species composition, carbon dynamics in soil and by long‐lived plants, and accumulation of nutrient capitals. Understanding and predicting these processes require experiments on decadal time scales. But decadal experiments by themselves may not be adequate because many of the slow processes have characteristic time scales much longer than experiments can be maintained. This article promotes a coordinated approach that combines long‐term, large‐scale global change experiments with process studies and modeling. Long‐term global change manipulative experiments, especially in high‐priority ecosystems such as tropical forests and high‐latitude regions, are essential to maximize information gain concerning future states of the earth system. The long‐term experiments should be conducted in tandem with complementary process studies, such as those using model ecosystems, species replacements, laboratory incubations, isotope tracers, and greenhouse facilities. Models are essential to assimilate data from long‐term experiments and process studies together with information from long‐term observations, surveys, and space‐for‐time studies along environmental and biological gradients. Future research programs with coordinated long‐term experiments, process studies, and modeling have the potential to be the most effective strategy to gain the best information on long‐term ecosystem dynamics in response to global change.     

The role of wildlife science in wetland ecosystem restoration: Lessons from the Everglades

There has been little discussion of how and when to integrate wildlife science into ecological restoration projects. The recent emergence of wetland ecosystem restoration offers an opportunity to use wildlife science to increase the probability of a project being successful. This paper traces the evolution of wetland ecosystem restoration in North America and proposes three roles for wildlife science in wetland ecosystem restoration: (1) contribute to conceptual ecosystem models, (2) develop quantitative performance measures and restoration targets that track the progress of restoration, and (3) achieve social feasibility by sustaining long-term public support for a project. The extensive knowledge base for many species of wildlife makes them especially useful for contributing to conceptual ecosystem models. Wildlife species are often the subject of long-term monitoring and research because they have commercial value, are conspicuous, or have aesthetic appeal. Wildlife parameters can be good performance measures for large-scale restoration projects because some species integrate information over large spatial scales and are long-lived. Parameters associated with threatened or endangered wildlife species should get special consideration as performance measures because the information will meet multiple needs rather than just those of the conceptual ecosystem model. Finally, wetland ecosystem restoration projects need to sustain funding over decades to ensure the restored system is self-sustaining. Wildlife are a valued resource that can help achieve the social feasibility of a project by providing a way to communicate complex science in terms that society understands and values.     

The Ecological Role of the Vaquita, Phocoena sinus, in the Ecosystem of the Northern Gulf of California

From an ecosystem management perspective, analysis of the functional roles of species is a challenge. It is valuable to determine which species are irreplaceable within a given community based on their contribution to the system’s organization. This study relates the emergent functional and structural indices of biological groups estimated from a trophic model of the Northern Gulf of California to identify the roles of these groups in the ecosystem context, with a particular focus on the role of the vaquita, an endemic porpoise in critically endangered status. The simulation of removing each group allowed the analysis of the removal’s functional effect on the ecosystem’s global attributes and organization (based on Ulanowicz’s ascendency concept). Groups from lower trophic levels (TL) were more related to complexity indicators, suggesting their contribution to the organization and structure of energy flows in the food web. Groups from intermediate TL had higher values of structural indexes, indicating their function in the control of flows throughout the network. The vaquita along with other marine mammals, aquatic birds, and some species of fish with a high TL contribute in a similar way to the order (for example, ascendency/capacity-of-development ratio) of the system, showing a relatively high value of ascendency (contribution of the group to the organization inherent to the ecosystem) and the change in ecosystem ascendency when they were removed. The vaquita, like marine and coastal birds, plays a small role in the ecosystem. But like them, it does contribute substantially to ecosystem organization. This study thus provides information potentially useful for management in understanding the species’ role and in reducing uncertainty in decision-making.     

气候变化和土地利用变化驱动下的生物多样性系统分析新框架

尽管目前已有大量关于生物多样性评估的研究,但同时考虑生物多样性多维评估、多驱动因素对生物多样性变化的影响评估及生物多样性变化中长期动态模拟预测等研究仍相对缺乏,这会引起对生物多样性不同维度变化水平的片面理解,导致生物多样性保护工程管理决策失误。基于此,综述现有生物多样性评估维度、驱动因素及历史评估的研究进展,并基于现有研究存在的局限性提出生物多样性多维评估方法与人地耦合系统下生物多样性模拟模型构建思路,基于此提出气候变化和土地利用变化驱动下的生物多样性系统分析新框架。该框架包括:①生物多样性"潜力-贡献-重要性"多维评估理论与方法构建;②人地耦合系统下生物多样性模拟模型构建;③人地耦合系统下生物多样性预测及生物多样性保护工程效果仿真与管理。该框架可为生物多样性保护工程管理及可持续开展提供科学建议。     

Bivalve aquaculture‐environment interactions in the context of climate change

Coastal embayments are at risk of impacts by climate change drivers such as ocean warming, sea level rise and alteration in precipitation regimes. The response of the ecosystem to these drivers is highly dependent on their magnitude of change, but also on physical characteristics such as bay morphology and river discharge, which play key roles in water residence time and hence estuarine functioning. These considerations are especially relevant for bivalve aquaculture sites, where the cultured biomass can alter ecosystem dynamics. The combination of climate change, physical and aquaculture drivers can result in synergistic/antagonistic and nonlinear processes. A spatially explicit model was constructed to explore effects of the physical environment (bay geomorphic type, freshwater inputs), climate change drivers (sea level, temperature, precipitation) and aquaculture (bivalve species, stock) on ecosystem functioning. A factorial design led to 336 scenarios (48 hydrodynamic × 7 management). Model outcomes suggest that the physical environment controls estuarine functioning given its influence on primary productivity (bottom‐up control dominated by riverine nutrients) and horizontal advection with the open ocean (dominated by bay geomorphic type). The intensity of bivalve aquaculture ultimately determines the bivalve–phytoplankton trophic interaction, which can range from a bottom‐up control triggered by ammonia excretion to a top‐down control via feeding. Results also suggest that temperature is the strongest climate change driver due to its influence on the metabolism of poikilothermic organisms (e.g. zooplankton and bivalves), which ultimately causes a concomitant increase of top‐down pressure on phytoplankton. Given the different thermal tolerance of cultured species, temperature is also critical to sort winners from losers, benefiting Crassostrea virginica over Mytilus edulis under the specific conditions tested in this numerical exercise. In general, it is predicted that bays with large rivers and high exchange with the open ocean will be more resilient under climate change when bivalve aquaculture is present.     

Single species dynamics under climate change

We propose a general mathematical model describing the growth and dispersal of a single species living in a 1-D spatially discrete array of habitat patches affected by a sustained and directional change in climate. Our model accounts for two important characteristics of the climate change phenomenon: (1) Scale dependency: different species may perceive the change in the environment as occurring at different rates because they perceive the environment at different scales, and (2) measure dependency: different species measure the environment differently in the sense that they may be sensible to or cue in on different aspects of it (e.g., maximum temperature, minimum temperature, accumulated temperature) which is associated with their physiological, ecological, and life history attributes, which renders some characteristics of the environment more biologically relevant than others. We show that the deterioration in the quality of habitable patches as a consequence of climate change drives the species to extinction when dispersal is not possible; otherwise, we proof and provide a numerical example that, depending on the velocity of climate change, the scale at which a species measures it, and the particular attribute of the environment that is more biologically relevant to the species under analysis, there is always a migration strategy that allows the persistence of the species such that it tracks its niche conditions through space, thus shifting its geographic range. Our mathematical analysis provides a general framework to analyze species’ responses to climate change as a relational property of a given species in interaction with a change in climate. In particular, we can analyze the persistence of species by taking into account the ways in which they measure and filter the environment. Indeed, one of our main conclusions is that there is not a single climate change but many, as it depends on the interaction between a particular species and climate. Thus, the problem is more complex than assumed by analytically tractable models of species responses to climate change.     

Global change alters the stability of food webs

Recent research has generally shown that a small change in the number of species in a food web can have consequences both for community structure and ecosystem processes. However ‘change’ is not limited to just the number of species in a community, but might include an alteration to such properties as precipitation, nutrient cycling and temperature. How such changes might affect species interactions is important, not just through the presence or absence of interactions, but also because the patterning of interaction strengths among species is intimately associated with community stability. Interaction strengths encompass such properties as feeding rates and assimilation efficiencies, and encapsulate functionally important information with regard to ecosystem processes. Interaction strengths represent the pathways and transfer of energy through an ecosystem. We review the best empirical data available detailing the frequency distribution of interaction strengths in communities. We present the underlying (but consistent) pattern of species interactions and discuss the implications of this patterning. We then examine how such a basic pattern might be affected given various scenarios of ‘change’ and discuss the consequences for community stability and ecosystem functioning.     

Winter climate change,plant traits and nutrient and carbon cycling in cold biomes

It is essential that scientists be able to predict how strong climate warming, including profound changes to winter climate, will affect the ecosystem services of alpine, arctic and boreal areas, and how these services are driven by vegetation–soil feedbacks. One fruitful avenue for studying such changing feedbacks is through plant functional traits, as an understanding of these traits may help us to understand and synthesise (1) responses of vegetation (through ‘response traits’ and ‘specific response functions’ of each species) to winter climate and (2) the effects of changing vegetation composition (through ‘effect traits’ and ‘specific effect functions’ of each species) on soil functions. It is the relative correspondence of variation in response and effect traits that will provide useful data on the impacts of winter climate change on carbon and nutrient cycling processes. Here we discuss several examples of how the trait-based, response–effect framework can help scientists to better understand the effects of winter warming on key ecosystem functions in cold biomes. These examples support the view that measuring species for their response and effect traits, and how these traits are linked across species through correspondence of variation in specific response and effects functions, may be a useful approach for teasing out the contribution of changing vegetation composition to winter warming effects on ecosystem functions. This approach will be particularly useful when linked with ecosystem-level measurements of vegetation and process responses to winter warming along natural gradients, over medium time scales in given sites or in response to experimental climate manipulations.     

农田生态系统种群结构多样性与系统微环境的关系——对几种多样性农田生态系统的分析评价

农田生物与其环境因素之间关系问题是农业生态系统研究的一个重点问题 ,生物与其所处环境因素之间关系的好坏 ,对生物的生长发育起着重要作用 ,进而影响着农田生态系统的功能发挥。单一生物与其环境因素之间的关系 ,通常是农田生态系统研究的重点。由多种生物组成的生物群落与其环境因素之间的关系 ,由于对农田生态系统的良好发育更起着关键制约作用 ,因而 ,也越来越多地受到研究人员的关注。对农田生态系统生物种群多样性 ,与多种生态环境因子之间关系的研究 ,也由于人们对多样化系统关注程度的提高而显得尤为重要。本文在对已有研究资料系…     

Quantitative measures of organization for multiagent systems

A set of "information theoretic" measures has been developed to quantify the degree of constraint inherent in the organization of a multiagent system. Separate measures can be provided to quantify spatial organization, trophic organization and, more generally, the overall structure of interactions. The additive character of these quantities allows them to be distributed in various fashions among species and places in a way that allows one to assign an "Importance Index" to those taxa and places. In addition, a measure to gauge the degree of adaptation of a species to a particular environment is proffered. The proposed measures allow one to formulate the following hypotheses in quantitative fashion: (1). that any disturbance of an ecosystem at a location associated with a high spatial Importance Index will exert a greater impact on the population dynamics than will a similar disturbance aimed at a place where the values of these indexes are lower; (2). that any disturbance in an ecosystem affecting a particular species with high individual Importance Indexes will cause a greater impact on the overall population dynamics than will a disturbance aimed at a species with a lower values of these indexes; (3). that the ascendancy of evolving system has a propensity to increase. The precise quantitative formulation of these hypothesis would permit them to be tested via multiagent simulation. Estimating the probablities pertaining to these hypotheses presents a number of problems that merit discussion.     

Non-Deterministic Modelling of Food-Web Dynamics

A novel approach to model food-web dynamics, based on a combination of chance (randomness) and necessity (system constraints), was presented by Mullon et al. in 2009. Based on simulations for the Benguela ecosystem, they concluded that observed patterns of ecosystem variability may simply result from basic structural constraints within which the ecosystem functions. To date, and despite the importance of these conclusions, this work has received little attention. The objective of the present paper is to replicate this original model and evaluate the conclusions that were derived from its simulations. For this purpose, we revisit the equations and input parameters that form the structure of the original model and implement a comparable simulation model. We restate the model principles and provide a detailed account of the model structure, equations, and parameters. Our model can reproduce several ecosystem dynamic patterns: pseudo-cycles, variation and volatility, diet, stock-recruitment relationships, and correlations between species biomass series. The original conclusions are supported to a large extent by the current replication of the model. Model parameterisation and computational aspects remain difficult and these need to be investigated further. Hopefully, the present contribution will make this approach available to a larger research community and will promote the use of non-deterministic-network-dynamics models as ‘null models of food-webs’ as originally advocated.     

Environmental forcing and Southern Ocean marine predator populations: effects of climate change and variability

The Southern Ocean is a major component within the global ocean and climate system and potentially the location where the most rapid climate change is most likely to happen, particularly in the high-latitude polar regions. In these regions, even small temperature changes can potentially lead to major environmental perturbations. Climate change is likely to be regional and may be expressed in various ways, including alterations to climate and weather patterns across a variety of time-scales that include changes to the long interdecadal background signals such as the development of the El Niño–Southern Oscillation (ENSO). Oscillating climate signals such as ENSO potentially provide a unique opportunity to explore how biological communities respond to change. This approach is based on the premise that biological responses to shorter-term sub-decadal climate variability signals are potentially the best predictor of biological responses over longer time-scales. Around the Southern Ocean, marine predator populations show periodicity in breeding performance and productivity, with relationships with the environment driven by physical forcing from the ENSO region in the Pacific. Wherever examined, these relationships are congruent with mid-trophic-level processes that are also correlated with environmental variability. The short-term changes to ecosystem structure and function observed during ENSO events herald potential long-term changes that may ensue following regional climate change. For example, in the South Atlantic, failure of Antarctic krill recruitment will inevitably foreshadow recruitment failures in a range of higher trophic-level marine predators. Where predator species are not able to accommodate by switching to other prey species, population-level changes will follow. The Southern Ocean, though oceanographically interconnected, is not a single ecosystem and different areas are dominated by different food webs. Where species occupy different positions in different regional food webs, there is the potential to make predictions about future change scenarios.     

生物多样性与生态系统服务情景模拟研究进展

生物多样性和生态系统服务情景模拟是指对未来生物多样性和生态系统服务变化轨迹的定量估计,二者相互关联并为长期、稳定的保护和恢复生态系统提供了重要科学依据。梳理生物多样性以及生态系统服务预测情景的核心观点,讨论基于生物多样性和生态系统服务情景模拟的保护决策支持途径,以期服务于我国生物多样性与生态系统服务预测研究的发展和深化。研究凝练结果如下:物种分布模型需要进行更规范的评价以明晰其对具体对象的适用性,生态系统预测模型亟待在关系结构的基础上嵌入更多的生态系统过程和社会经济过程,生态系统服务评估模型有必要强化对生物多样性、生态系统服务、人类福祉级联特征的刻画;全球气候变化驱动了未来区域生物多样性的大幅改变;土地利用则是陆地生态系统服务预测中的核心驱动变量。生态区划与区域尺度情景模拟、景观尺度下的生态安全格局构建、基于社会生态网络的社区适应三点重要展望方向将对基于情景模拟的我国生态系统保护决策提供重要的理论和实践支持。     

考虑气候因子变化的湖泊富营养化模型研究进展

气候因子是影响湖泊营养状态和进程的主要自然因素.在全球气候变化的趋势下,将气候因子的变化纳入湖泊富营养化模型中,可以为湖泊演化趋势分析和环境管理决策提供技术支持.本文首先分析了气温、降水、光照和大气等气候因子对湖泊富营养化的影响,进而对考虑气候因子变化的数理统计与分析模型、生态动力学模型、系统生态学模型及智能算法等的研究进行了综述.在此基础上,对完善气候因子变化下湖泊营养状态变化的模型研究进行了展望：1)加强气候因子作用于湖泊营养状态的机理研究;2)选择合适的气候模拟模型,合理设置气候变化情景,在不同模型嵌套时保证时空尺度的匹配;3)以水动力学模型为基础,耦合生态模型及智能算法等,并结合良好的气候模拟模型,以精确模拟预测气候变化下湖泊富营养化的演化过程和趋势.     

生态系统服务与景观格局集成研究综述

生态系统服务是综合科学和政策应用的有效工具,可用于应对人类干扰下的景观和生态系统服务的快速退化等复杂生态环境问题。综述生态系统服务与景观格局集成的学科发展、基础理论和模型开发的进展与存在的问题,建立可用的集成建模框架,并提出知识集成的概念框架:1)在要素层,"政策-决策—景观—生态系统服务—社会经济系统"的跨学科知识反馈环是集成理论基础; 2)在模型层,结构化、多层次的集成模拟模型是核心方法; 3)在数据层,多源数据集成是模拟模型的数据基础。集成生态系统服务与景观格局为区域生态环境治理实践提供了科学参考,能更好地应对生态系统服务科学与应用的挑战。     

Predicting the geographical distribution of plant communities in complex terrain – a case study in Fushian Experimental Forest, northeastern Taiwan

Ecosystem management and biodiversity conservation are usually implemented using information of several targeted species or cover-types and usually do not include information about communities. This is not because community-level information is unimportant for management purposes, but because the detailed fieldwork required for gathering community-level information at the scale for ecosystem management is usually impractical. We propose two methods to estimate the geographical distribution of plant communities with the objectives of covering large areas with minimal field efforts. The first method estimates the geographical distribution of plant communities by combining clustering methods with vegetation modeling, and the second extrapolates the geographical distribution of gradients in plant communities by combining gradient analysis with vegetation modeling. Vegetation modeling with clustering methods can be used to allocate sites with potentially higher alpha diversity, with the benefit of having a list of species associated with the clustered type. Vegetation modeling with gradient analysis can be used to identify regions with potentially the highest beta diversity by means of selecting regions with the widest range or highest variability in major DCA axes scores, and thereby help to preserve the scope of environmental conditions that lead to diversity in species assemblages. This is especially important because biological entities such as species, communities, or even ecosystems may cease to exist in the long run, and the preservation of processes that lead to biodiversity will eventually become more meaningful. We conclude that new methods to study and manage the processes that contribute to biodiversity at all scales should be and can be developed.