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Ecological network analysis (ENA) is a modeling approach increasingly being used to examine food webs. However, most studies do not replicate networks, and a statistical evaluation of ENA is lacking. The major objectives of this study, therefore, were to evaluate statistically the effectiveness of ENA in detecting differences in food web properties and to compare ENA output with established community level indices. Quantitative trophic networks (n = 12) representing four high salt marsh ponds during three times (corresponding to low stress, high stress, and post-disturbance) were constructed from an extensive field sampling program augmented by literature values. Food webs of salt marsh ponds were used because these systems contain relatively simple food webs, have well defined boundaries, and allow for adequate replication. A null hypothesis was tested to determine how values of 12 indices from ENA output differed among the three stress/disturbance conditions (H o: low stress = high stress = post-disturbance). Results of both ANOVA and Friedman’s tests indicated most ENA indices were significantly different among the three stress/disturbance conditions. The amount of covariance among the indices was relatively low (7 of 66 were significant). Results were compared to differences in community indices (richness, evenness, and diversity) among the three stress/disturbance conditions. ENA output identified differences beyond those recognized by the community indices. Overall, networks were unique enough under different environmental conditions to provide statistically significant differences in ENA results. Our findings are supportive of the use of carefully constructed networks in food web analysis and for decision making in ecosystem-based management. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.  相似文献
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Energy (biomass) and energy flows (production, inputs, transfers and losses) were calculated for eight and twelve compartment systems (phytoplankton, benthic primary producers (macroalgae, microphytobenthos), zooplankton, benthos (meiofauna, suspensivores, deposivores and predators), fish, birds and particulate organic matter (POM) in sediment and suspended particulate matter (SPM)) both balanced and unbalanced of Dublin Bay and the Baie de Somme. The resultant models were analysed with the Scientific Committee on Oceanic Research (SCOR) network analysis package. While the two systems share many properties such as the dominant biosedimentary facies, there are fundamental differences in both structuring and responses of the systems. The network analysis suggested that the Baie de Somme was far more productive, notably in terms of water column productivity, and was the more mature system. The high organic SPM input to Dublin Bay greatly elevated the degree of detritivory such that the analysis generated metrics indicative of a mature system but which rather reflected the degree of anthropogenic stress on the system. However, the analysis of both systems displayed varying degrees of maturity. Increasing the number of compartments greatly increased the calculated throughput (T) of the system and other associated metrics such as capacity (C), ascendancy (A) and redundancy (R). In the case of Dublin Bay, a higher number of compartments increased the various measures of system maturity, but this was much less marked for the Baie de Somme. Balancing the systems also increased T, C, A and R, and, to a lesser extent but not invariably, the system maturity metrics. The ratios of the comparative system metrics such as comparative ascendancy (A/C) were much less changed by the different methodologies and as such are recommended as robust measures for intercomparison of system performance.  相似文献
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Trophic interactions and community structure in the upwelling system off Central Chile (USCCh) (33-39°S) are analyzed using biological and ecological data concerning the main trophic groups and the Ecopath with Ecosim software version 5.0 (EwE). The model encompasses the fisheries, cetaceans, sea lion, marine birds, cephalopods, large-sized pelagic fish (sword fish), medium-sized pelagic fish (horse mackerel, hoki), small-sized pelagic fish (anchovy, common sardine), demersal fish (e.g. Chilean hake, black conger-eel), benthic invertebrates (red squat lobster, yellow squat lobster) and other groups such as zooplankton, phytoplankton and detritus. Input data was gathered from published and unpublished reports and our own estimates. Trophic interactions, system indicators and food web attributes are calculated using network analysis routines included in EwE. Results indicate that trophic groups are aligned around four trophic levels (TL) with phytoplankton and detritus at the TL=1, while large-sized pelagic fish and cetaceans are top predators (TL>4.0). The fishery is located at an intermediate to low trophic level (TL=2.97), removing about 15% of the calculated system primary production. The pelagic realm dominates the system, with medium-sized pelagic fish as the main fish component in biomass, while small-sized pelagic fish dominate total landings. Chilean hake is by far the main demersal fish component in both, biomass and yield. Predators consume the greater part of the production of the most important fishery resources, particularly juvenile stages of Chilean hake. Consequently, mortality by predation is an important component of total mortality. However, fishery also removes a large fraction of common sardine, anchovy, horse mackerel, and Chilean hake. The analysis of direct and indirect trophic impacts reveals that Chilean hake is a highly cannibalistic species. Chilean hake is also an important predator on anchovy, common sardine, benthic invertebrates, and demersal fish. The fisheries heavily impact on Chilean hake, common sardine, anchovy, and horse mackerel. Total system biomass (B=476 t km−2 year−1) and throughput (T=89454 t km−2 year−1) estimated in the USCCh model are in accordance with models of comparable systems. Considering system attributes derived from network analysis, the USCCh can be characterized as an immature system, with short trophic chains and low trophic transfer efficiency. Finally, we suggest that trophic interactions should be considered in stock assessment and management programs in USCCh. In addition, future research programs should be carried out in order to understand the ecosystem effects of fishing and trophic control in this highly productive food web.  相似文献
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Large-scale structural patterns commonly occur in network models of complex systems including a skewed node degree distribution and small-world topology. These patterns suggest common organizational constraints and similar functional consequences. Here, we investigate a structural pattern termed pathway proliferation. Previous research enumerating pathways that link species determined that as pathway length increases, the number of pathways tends to increase without bound. We hypothesize that this pathway proliferation influences the flow of energy, matter, and information in ecosystems. In this paper, we clarify the pathway proliferation concept, introduce a measure of the node-node proliferation rate, describe factors influencing the rate, and characterize it in 17 large empirical food-webs. During this investigation, we uncovered a modular organization within these systems. Over half of the food-webs were composed of one or more subgroups that were strongly connected internally, but weakly connected to the rest of the system. Further, these modules had distinct proliferation rates. We conclude that pathway proliferation in ecological networks reveals subgroups of species that will be functionally integrated through cyclic indirect effects.  相似文献
5.
李中才  徐俊艳  吴昌友  张漪 《生态学报》2011,31(18):5396-5405
生态网络分析方法是分析生态系统作用关系、辨识系统内在、整体属性的一种有效的系统分析方法。总结了生态网络分析方法的主要研究成果:网络结构特性、网络稳定性、网络上升性、网络效能等;介绍了构建生态网络模型过程和群落构建规则;以德国西部城市诺伊斯河口氮循环为例,介绍David K是如何运用生态网络分析方法来揭示网络中的微动力流循环规律。生态网络分析方法的主要贡献:(1)对人们凭经验感知的生态系统分室间的关联关系,采用了严密的数学模型和推导进行了描述和证明;(2)为生态系统的微动力流循环的研究提供了方法,对生态系统中物质流的间接循环作用进行了科学论证;(3)不仅为分析生态系统提供了一种科学的数学方法,而且,它为探索生态系统提供了不同与牛顿世界观的崭新的认识论。总结与回顾生态网络分析方法,有益于该方法的运用和进一步完善。  相似文献
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