Ecosystem Model Skill Assessment. Yes We Can!

Need to Assess the Skill of Ecosystem Models

Accelerated changes to global ecosystems call for holistic and integrated analyses of past, present and future states under various pressures to adequately understand current and projected future system states. Ecosystem models can inform management of human activities in a complex and changing environment, but are these models reliable? Ensuring that models are reliable for addressing management questions requires evaluating their skill in representing real-world processes and dynamics. Skill has been evaluated for just a limited set of some biophysical models. A range of skill assessment methods have been reviewed but skill assessment of full marine ecosystem models has not yet been attempted.

Northeast US Atlantis Marine Ecosystem Model

We assessed the skill of the Northeast U.S. (NEUS) Atlantis marine ecosystem model by comparing 10-year model forecasts with observed data. Model forecast performance was compared to that obtained from a 40-year hindcast. Multiple metrics (average absolute error, root mean squared error, modeling efficiency, and Spearman rank correlation), and a suite of time-series (species biomass, fisheries landings, and ecosystem indicators) were used to adequately measure model skill. Overall, the NEUS model performed above average and thus better than expected for the key species that had been the focus of the model tuning. Model forecast skill was comparable to the hindcast skill, showing that model performance does not degenerate in a 10-year forecast mode, an important characteristic for an end-to-end ecosystem model to be useful for strategic management purposes.

Skill Assessment Is Both Possible and Advisable

We identify best-practice approaches for end-to-end ecosystem model skill assessment that would improve both operational use of other ecosystem models and future model development. We show that it is possible to not only assess the skill of a complicated marine ecosystem model, but that it is necessary do so to instill confidence in model results and encourage their use for strategic management. Our methods are applicable to any type of predictive model, and should be considered for use in fields outside ecology (e.g. economics, climate change, and risk assessment).     

Spatio-temporal development of forests – current trends in field methods and models

We present a critical review of current trends in research of spatio-temporal development of forests. The paper addresses (1) field methods for the development of spatially-explicit models of forest dynamics and their integration in models of forest dynamics, (2) strengths and limitations of traditional patch models versus spatially-explicit, individual-based models, and (3) the potential for moment-based methods in the analysis of forest dynamics. These topics are discussed with reference to their potential for solving open questions in the studies of forest dynamics. The study of spatio-temporal processes provides a link between pattern and process in plant communities, and plays a crucial role in understanding ecosystem dynamics. In the last decade, the development of spatially-explicit, individual-based models shifted the focus of forest dynamics modelling from the dynamics of discrete patches to the interactions among individual organisms, thus encapsulating the theory of “neighbourhood” dynamics. In turn, the stochastic properties and the complexity of spatially-explicit, individual-based models gave rise to the development of a new suite of so-called moment-based models. These new models describe the dynamics of individuals and of pairs of individuals in terms of their densities, thus directly capturing second-order information on spatial structure. So far, this approach has not been applied to forests; we indicate extensions needed for such applications. Moment-based models may be an important complement to spatially explicit individual-based models in developing a general spatial theory of forest dynamics. However, both kinds of models currently focus on fine scales, whereas a critical issue in forest dynamics is to understand the interaction of fine-scale processes with coarser-scale disturbances. To obtain a more complete picture of forest dynamics, the relevant links and interactions between fine-, intermediate-, and coarse-scale processes ought to be identified. Intensive links between modelling work and field studies designed across different scales are a promising means to create a new perspective on forest dynamics.     

Controlling chaos in ecology: From deterministic to individual-based models

The possibility of chaos control in biological systems has been stimulated by recent advances in the study of heart and brain tissue dynamics. More recently, some authors have conjectured that such a method might be applied to population dynamics and even play a nontrivial evolutionary role in ecology. In this paper we explore this idea by means of both mathematical and individual-based simulation models. Because of the intrinsic noise linked to individual behavior, controlling a noisy system becomes more difficult but, as shown here, it is a feasible task allowed to be experimentally tested.     

McComedy: A user-friendly tool for next-generation individual-based modeling of microbial consumer-resource systems

Individual-based modeling is widely applied to investigate the ecological mechanisms driving microbial community dynamics. In such models, the population or community dynamics emerge from the behavior and interplay of individual entities, which are simulated according to a predefined set of rules. If the rules that govern the behavior of individuals are based on generic and mechanistically sound principles, the models are referred to as next-generation individual-based models. These models perform particularly well in recapitulating actual ecological dynamics. However, implementation of such models is time-consuming and requires proficiency in programming or in using specific software, which likely hinders a broader application of this powerful method. Here we present McComedy, a modeling tool designed to facilitate the development of next-generation individual-based models of microbial consumer-resource systems. This tool allows flexibly combining pre-implemented building blocks that represent physical and biological processes. The ability of McComedy to capture the essential dynamics of microbial consumer-resource systems is demonstrated by reproducing and furthermore adding to the results of two distinct studies from the literature. With this article, we provide a versatile tool for developing next-generation individual-based models that can foster understanding of microbial ecology in both research and education.     

Linking biodiversity and ecosystems: towards a unifying ecological theory

Community ecology and ecosystem ecology provide two perspectives on complex ecological systems that have largely complementary strengths and weaknesses. Merging the two perspectives is necessary both to ensure continued scientific progress and to provide society with the scientific means to face growing environmental challenges. Recent research on biodiversity and ecosystem functioning has contributed to this goal in several ways. By addressing a new question of high relevance for both science and society, by challenging existing paradigms, by tightly linking theory and experiments, by building scientific consensus beyond differences in opinion, by integrating fragmented disciplines and research fields, by connecting itself to other disciplines and management issues, it has helped transform ecology not only in content, but also in form. Creating a genuine evolutionary ecosystem ecology that links the evolution of species traits at the individual level, the dynamics of species interactions, and the overall functioning of ecosystems would give new impetus to this much-needed process of unification across ecological disciplines. Recent community evolution models are a promising step in that direction.     

基于智能体模型的土地利用动态模拟研究进展

土地利用动态变化是全球变化和可持续发展研究的基础,对区域水循环、大气循环、环境质量、气候变化及陆地生态系统生产力等具有重要影响,也是造成生物多样性衰减的最主要原因.目前,建立于复杂性科学基础上的的智能体模型(ABM)成为土地利用动态模拟的重要方法.智能体模型能模拟个体或群体的行为及决策模式,从而能将政府、城市规划、房地产开发商、住户等社会群体及个人对土地利用产生的影响进行模拟,同时能对不同社会经济政策对土地动态影响进行模拟.智能体模型在元胞自动机基础上,加入了人为因素的智能体概念,从而能更好地模拟土地动态.在分析总结了智能体模型的相关概念和组织结构,并分析了其在土地利用动态、城市动态模拟及生态过程模拟等方面的应用与元胞自动机的关系,比较了常用的智能体模型的主要软件,最后概括了智能体模型优点、发展趋势及存在的主要问题.     

Coupled map lattice approximations for spatially explicit individual-based models of ecology

Spatially explicit individual-based models are widely used in ecology but they are often difficult to treat analytically. Despite their intractability they often exhibit clear temporal and spatial patterning. We demonstrate how a spatially explicit individual-based model of scramble competition with local dispersal can be approximated by a stochastic coupled map lattice. The approximation disentangles the deterministic and stochastic element of local interaction and dispersal. We are thus able to understand the individual-based model through a simplified set of equations. In particular, we demonstrate that demographic noise leads to increased stability in the dynamics of locally dispersing single-species populations. The coupled map lattice approximation has general application to a range of spatially explicit individual-based models. It provides a new alternative to current approximation techniques, such as the method of moments and reaction-diffusion approximation, that captures both stochastic effects and large-scale patterning arising in individual-based models.     

Rewilding the Scottish Highlands: Do Wild Boar,Sus scrofa,Use a Suitable Foraging Strategy to be Effective Ecosystem Engineers?

Ecosystem engineers are increasingly being reintroduced to restore ecological processes in restoration and rewilding projects. To predict and adaptively manage the impact of such species their behavioral ecology must be understood and quantified. Rooting behavior by wild boar qualifies them as ecosystem engineers due to their impact on vegetation disturbance regimes. The behavioral foraging ecology of wild boar was quantified in a fenced area in the Scottish Highlands in order to provide some of the understanding necessary to predict their ability to affect ecosystem restoration. Five wild boar were monitored within a 125 ha fenced area using Global Positioning System (GPS) collars and behavioral monitoring over a 12‐month period. Their activity budget, the relationship between foraging behavior and vegetation communities, and how these relationships vary between seasons was investigated. The results indicate that wild boar invested approximately four more hours daily to rooting during the autumn and winter than the spring and summer. During the spring and summer, grazing was the dominant foraging behavior (approximately 28% of foraging period) while rooting dominated in autumn and winter (approximately 76% of foraging period). Deep rooting behavior is particularly associated with bracken‐dominated communities. Associations between rooting, vegetation community, and season will have a strong influence on the spatial and temporal distribution of rooting behavior. This variation could have important implications for the impacts of boar on vegetation community dynamics. These results detail some of wild boar's ecosystem engineering behaviors; however, further research is required to consider the wider impacts of a full reintroduction.     

Application of network methods for understanding evolutionary dynamics in discrete habitats

In populations occupying discrete habitat patches, gene flow between habitat patches may form an intricate population structure. In such structures, the evolutionary dynamics resulting from interaction of gene‐flow patterns with other evolutionary forces may be exceedingly complex. Several models describing gene flow between discrete habitat patches have been presented in the population‐genetics literature; however, these models have usually addressed relatively simple settings of habitable patches and have stopped short of providing general methodologies for addressing nontrivial gene‐flow patterns. In the last decades, network theory – a branch of discrete mathematics concerned with complex interactions between discrete elements – has been applied to address several problems in population genetics by modelling gene flow between habitat patches using networks. Here, we present the idea and concepts of modelling complex gene flows in discrete habitats using networks. Our goal is to raise awareness to existing network theory applications in molecular ecology studies, as well as to outline the current and potential contribution of network methods to the understanding of evolutionary dynamics in discrete habitats. We review the main branches of network theory that have been, or that we believe potentially could be, applied to population genetics and molecular ecology research. We address applications to theoretical modelling and to empirical population‐genetic studies, and we highlight future directions for extending the integration of network science with molecular ecology.     

区域生态学的特点、学科定位及其与相邻学科的关系

区域生态学作为生态学的一门重要分支学科,起源于20世纪70年代的区域综合科学考察和环境污染调查,旨在研究区域生态环境问题形成背景和驱动因子,探讨区域生态环境问题解决的思路和方法。基于前人研究成果和文献综述,系统分析了区域生态学研究的特点,剖析了区域生态学的性质和学科定位。在此基础上进一步比较了区域生态学与景观生态学、生态系统生态学、区域自然地理学和宏观生态学的共性与差异。认为:(1)区域生态学研究对象是具有特定生态环境属性的区域生态综合体,既具有特定要素主导下的空间均质性,也具有多种要素耦合作用下的空间异质性特征,是一门问题导向的应用性基础学科;(2)区域生态学研究需要具有多元综合、问题导向和系统集成的思维,从多层次、多视角探讨区域生态环境问题的解决方案;(3)区域生态学属于宏观生态学研究的范畴,处于分子生态学、个体生态学、种群生态学、群落生态学、生态系统生态学、景观生态学、区域生态学和全球生态学这个生态学学科体系的较高层次。     

Geographical and Temporal Body Size Variation in a Reptile: Roles of Sex,Ecology, Phylogeny and Ecology Structured in Phylogeny

Geographical body size variation has long interested evolutionary biologists, and a range of mechanisms have been proposed to explain the observed patterns. It is considered to be more puzzling in ectotherms than in endotherms, and integrative approaches are necessary for testing non-exclusive alternative mechanisms. Using lacertid lizards as a model, we adopted an integrative approach, testing different hypotheses for both sexes while incorporating temporal, spatial, and phylogenetic autocorrelation at the individual level. We used data on the Spanish Sand Racer species group from a field survey to disentangle different sources of body size variation through environmental and individual genetic data, while accounting for temporal and spatial autocorrelation. A variation partitioning method was applied to separate independent and shared components of ecology and phylogeny, and estimated their significance. Then, we fed-back our models by controlling for relevant independent components. The pattern was consistent with the geographical Bergmann''s cline and the experimental temperature-size rule: adults were larger at lower temperatures (and/or higher elevations). This result was confirmed with additional multi-year independent data-set derived from the literature. Variation partitioning showed no sex differences in phylogenetic inertia but showed sex differences in the independent component of ecology; primarily due to growth differences. Interestingly, only after controlling for independent components did primary productivity also emerge as an important predictor explaining size variation in both sexes. This study highlights the importance of integrating individual-based genetic information, relevant ecological parameters, and temporal and spatial autocorrelation in sex-specific models to detect potentially important hidden effects. Our individual-based approach devoted to extract and control for independent components was useful to reveal hidden effects linked with alternative non-exclusive hypothesis, such as those of primary productivity. Also, including measurement date allowed disentangling and controlling for short-term temporal autocorrelation reflecting sex-specific growth plasticity.     

Stoichiometric distribution models: ecological stoichiometry at the landscape extent

Human activities are altering the fundamental geography of biogeochemicals. Yet we lack an understanding of how the spatial patterns in organismal stoichiometry affect biogeochemical processes and the tools to predict the impacts of global changes on biogeochemical processes. In this contribution we develop stoichiometric distribution models (StDMs), which allow us to map spatial structure in resource elemental composition across a landscape and evaluate spatial responses of consumers. We parameterise StDMs for a consumer‐resource (moose‐white birch) system and demonstrate that we can develop predictive models of resource stoichiometry across a landscape and that such models could improve our predictions of consumer space use. With results from our study system application, we argue that explicit consideration of the spatial patterns in organismal elemental composition may uncover emergent individual, population, community and ecosystem properties that are not revealed at the local extents routinely used in ecological stoichiometry. We discuss perspectives for further developments and application of StDMs to advance three emerging frameworks for spatial ecosystem ecology in an era of global change; meta‐ecosystem theory, macroecological stoichiometry and remotely sensed biogeochemistry. Progress on these emerging frameworks will allow for the integration of ecological stoichiometry and individual space use and fitness.     

Scaling from optimal behavior to population dynamics and ecosystem function

While behavioral responses of individual organisms can be predicted with optimal foraging theory, the theory of how individual behavior feeds back to population and ecosystem dynamics has not been fully explored. Ecological models of trophic interactions incorporating behavior of entire populations commonly assume either that populations act as one when making decisions, that behavior is slowly varying or that non-linear effects are negligible in behavioral choices at the population scale. Here, we scale from individual optimal behavior to ecosystem structure in a classic tri-trophic chain where both prey and predators adapt their behavior in response to food availability and predation risk. Behavior is modeled as playing the field, with both consumers and predators behaving optimally at every instant basing their choices on the average population behavior. We establish uniqueness of the Nash equilibrium, and find it numerically. By modeling the interactions as playing the field, we can perform instantaneous optimization at the individual level while taking the entire population into account. We find that optimal behavior essentially removes the effect of top-down forcing at the population level, while drastically changing the behavior. Bottom-up forcing is found to increase populations at all trophic levels. These phenomena both appear to be driven by an emerging constant consumption rate, corresponding to a partial satiation. In addition, we find that a Type III functional response arises from a Type II response for both predators and consumers when their behavior follows the Nash equilibrium, showing that this is a general phenomenon. Our approach is general and computationally efficient and can be used to account for behavior in population dynamics with fast behavioral responses.     

景观空间动态模型研究现状和应重点解决的问题

分析了景观空间动态模型研究的现状及今后的重点发展方向。论文重点介绍了随机景观模型、邻域规则模型和景观过程模型(包括渗透模型、个体行为模型和空间生态系统模型)3类景观空间模型的发展现状、存在的主要问题以及对这些模型途径进行完善的有关工作,并从确证性分析、有效性分析与敏感性分析等3个方面阐述了模型检验技术的发展现状。最后,总结了未来景观空间动态模型发展中应重点解决的主要问题,即模型算法的优化、尺度转换、模型的复杂化与简化、模型检验与评价,通用模型的建立以及传统模型与社会经济因素衔接问题。     

展望数学生态学与生态模型的未来

首先简要回顾了２０世纪数学生态学发展的历史,特别是半２个世纪以来在中国的发展。然后指出了生物学的进步为数学生态学的发展提供了机遇。作者列出了当前数学生态学和生态模型研究的几个热点：⑴非线性动力学;⑵种群的时空动态：包括异质种群动态,源－汇理论以及种群对时、空变化的响应等;⑶多样性和稳定性的关系;⑷行为的动态模型;⑸基于个体的模型。最后指出,生态学中混沌现象,可能表明多年来理论生态学家寻找的种群动态     

Individual variability and population regulation: a model of the significance of within-generation density dependence

Most models of theoretical population ecology consider population density as a state variable and thus ignore the fact that populations are composed not of identical average individuals but of individuals which are usually different. However, this individual variability may be important for population regulation. We therefore analysed an individual-based population model which explicitly describes within-generation processes, i.e. individual growth, starvation, and resource dynamics. The results show that if population dynamics are dominated by slow changes in resource level, the population size in the model undergoes wide oscillation, often leading to extinction. If, on the other hand, fast within-generation processes predominate, such as starvation and sudden drops in resource levels, the population fluctuates to a limited extent around an average. Within-generation density dependence may thus be an important mechanism which is largely ignored in classic time-discrete state-variable models. We conclude that the individual-based approach provides important insights into the hierarchical organization of population dynamics, i.e. the relationship between fast processes at the individual level and slower processes at the population level.     

Biological soil crusts (biocrusts) as a model system in community,landscape and ecosystem ecology

Model systems have had a profound influence on the development of ecological theory and general principles. Compared to alternatives, the most effective models share some combination of the following characteristics: simpler, smaller, faster, general, idiosyncratic or manipulable. We argue that biological soil crusts (biocrusts) have unique combinations of these features that should be more widely exploited in community, landscape and ecosystem ecology. In community ecology, biocrusts are elucidating the importance of biodiversity and spatial pattern for maintaining ecosystem multifunctionality due to their manipulability in experiments. Due to idiosyncrasies in their modes of facilitation and competition, biocrusts have led to new models on the interplay between environmental stress and biotic interactions and on the maintenance of biodiversity by competitive processes. Biocrusts are perhaps one of the best examples of micro-landscapes—real landscapes that are small in size. Although they exhibit varying patch heterogeneity, aggregation, connectivity and fragmentation, like macro-landscapes, they are also compatible with well-replicated experiments (unlike macro-landscapes). In ecosystem ecology, a number of studies are imposing small-scale, low cost manipulations of global change or state factors in biocrust micro-landscapes. The versatility of biocrusts to inform such disparate lines of inquiry suggests that they are an especially useful model system that can enable researchers to see ecological principles more clearly and quickly.     

Research on fish ecology in Japan: a brief history and selected review

Fish play an important role in the culture of Japan, supplying the primary source of food protein. Research on fish ecology in Japan began developing about 1955, and paralleled that in North America and Europe, but has a number of unique differences. Two main research foci, stream fish ecology and ecology of Lake Biwa, were founded by H. Kawanabe and his colleagues while graduate students in D. Miyadi's laboratory at Kyoto University in the 1950s. The focus on studies of individual differences in ecology, life history, and behavior by direct observation that were developed in this laboratory had a pervasive influence on research that has continued to the present. In the 1980s, Kawanabe, who had succeeded Miyadi as laboratory head, also co-organized a major research project on the complex communities of cichlid fishes in Lake Tanganyika, which has involved nearly every major Japanese investigator in fish ecology since. A review of research conducted by Japanese investigators in stream fish ecology, ecology of fishes in lakes Biwa and Tanganyika, and marine reef fish ecology revealed a wealth of literature of which most English-speaking fish ecologists are unaware. The most striking difference between Western and Japanese research is the focus on detailed observations and experiments in natural habitats of individual differences in behavior, life history, and ecology, and how these ultimately affect processes at the population and community level, as amply demonstrated by Kawanabe's early work on ayu, Plecoglossus altivelis. This approach predated by 20–30 years the current interest in individual differences and individual-based models in North America and Europe.