Evaluating the ecological state of Chinese Lake Baiyangdian (BYD) based on Ecological Network Analysis

The Bay of Seine (Normandy coast of the English Channel) is a highly impacted ecosystem concerned by numerous human activities. It is subjected to heavy historic anthropogenic pressures and the emergence of new human activities: fishing, harbour extension, aggregate extraction, deposition of dredged sediment, and offshore wind farms. By contrast, this area shows a high level of protection of its natural heritage, mainly owing to the Natural Reserve and Natura 2000 sites. Moreover, an accumulation of research projects has ensured the acquisition of a high level of scientific knowledge and high-quality ecological data in this area. However, there is a lack of a systematic approach taking into account the available data. By building maps of benthic habitats, food-web modelling and calculating ecological indicators, we are able to take the first steps towards an ecosystem-based management. These integrative approaches allow us to assess the ecological quality status of the Bay of Seine and the Seine estuary. Trophic models based on the quantification of energy and matter fluxes in ecosystems, as well as indices derived from ecological network analysis, are used to describe the interaction between species across all trophic levels. When applied to spatial models, ecological functioning and ecosystem health can be assessed in different areas of the ecosystem. In the Bay of Seine, benthic habitats display high resilience while pelagic, fish and bird compartments have been shown to be highly modified, due to hydrological and climatic changes. The North Channel and the Navigation Channel of the Seine estuary appear to be far more intensely stressed, while the South Channel and marine areas of the Bay show a more mature functioning. Our conclusions reveal the need to consider the influence of human pressures on the functioning of complex ecosystems, thus providing an integrated approach that can be used to study a social-ecological system affected by global changes and investigate the cumulative impacts of human activities.

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.

Ultra high voltage (UHV) power transmission construction project is a high-tech power grid construction project which faces many risks and uncertainty. Identifying the risk of UHV power transmission construction project can help mitigate the risk loss and promote the smooth construction. The risk evaluation on “Zhejiang-Fuzhou” UHV power transmission construction project was performed based on analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE) method in this paper. After the risk evaluation index system was built, the AHP was used to determine the weights of risk indicators, and the FCE method was to perform the risk evaluation. The evaluation result shows that (1) “Zhejiang-Fuzhou” UHV power transmission construction project has moderate risk, which indicates the occurrence probability of project risk is medium and the risk occurrence will cause general loss for project, (2) “society risk” has the highest level, and the next is “policy and law risk,” “technique risk,” “natural environmental risk,” and “Management risk,” respectively, and it should keep main eye on the social risk, policy and law risk, and technique risk. Finally, according to the risk evaluation result, the specific risk control recommendations were proposed for the smooth construction of this project.

Ecological threshold of phosphorus load in Baiyangdian Lake based on a PCLake model and ecological network analysis

Vitamine ENA: A framework for the development of ecosystem-based indicators for decision makers

Ecological communities are constantly changing as a response to environmental and anthropogenic pressures. Yet, how changes in community composition influence the structure of food webs over time and space remains elusive. Using ecological network analysis, we assessed how food web structure changed across six distinct areas of the North Sea over a sixteen‐year time‐period. We used multivariate analyses to disentangle and compare spatio‐temporal dynamics in community composition (i.e. changes in species abundances) and food web structure (i.e. changes in network properties). Specifically, we assessed how changes in community composition were reflected in food web structure. Our results revealed a strong spatial coupling between community composition and food web structure along a south–north gradient. However, the temporal covariation between community composition and food web structure depended on the spatial scale. We observed a temporal mismatch at regional scale, but a strong coupling at local scale. In particular, we found that community composition can be influenced by hydro‐climatic events over large areas, with diverse effects manifesting in local food web structure. Our proposed methodological framework quantified and compared spatio‐temporal changes in community composition and food web structure, providing key information to support effective management strategies aimed at conserving the structure and functioning of ecological communities in times of environmental change.

The water resources carrying capacity (WRCC) shows remarkable fuzziness and randomness, which causes the uncertainty and instability of the WRCC assessment (WRCCA). In order to solve these problems, we proposed a novel hybrid approach for WRCCA, in which the fuzzy comprehensive evaluation (FCE) and analytical hierarchy process (AHP) methods were integrated with the cloud model (CM). Firstly, an evaluation indicator system of WRCC was constructed. Secondly, the AHP and FCE methods were subsequently improved with the CM. The CM was used to scale the relative importance and aggregate the judgment matrices, where the weights of the clouds were obtained. These integrations of AHP and CM greatly reduced the randomness in the weight calculation; the CM was used to describe the comment sets, calculate the membership degree matrices and determine the assignment clouds, the evaluation sets and the WRCCA index clouds were obtained. These integrations of FCE and CM effectively blurred the boundary fuzziness and gave more intuitive results. Finally, the hybrid FCE-AHP-CM approach was applied to a case study. It was concluded that the novel approach has particular advantages in dealing with the fuzziness and randomness comprehensively, and therefore could assess the WRCC and enhance the robustness and intuition of WRCCA results.

Ecological network analyses and their use for establishing reference domain in functional assessment of an estuary

Optimal study of the rural house space heating systems employing the AHP and FCE methods

The determination of food web structures using Ecological Network Analysis (ENA) is a helpful tool to get insight into complex ecosystem processes. The intertidal area of the Wadden Sea is structured into diverse habitat types which differ in their ecological functioning. In the present study, six different intertidal habitats (i.e. cockle field, razor clam field, mud flat, mussel bank, sand flat and seagrass meadow) were analyzed using ENA to determine similarities and characteristic differences in the food web structure of the systems. All six systems were well balanced between their degree of organization and their robustness. However, they differed in their detailed features. The cockle field and the mussel bank exhibited a strong dependency on external imports. The razor clam field appeared to be a rather small system with low energy transfer. In the mud flat microphytobenthos was used as a main food source and the system appeared to be sensitive to perturbations. Bird predation was the most pronounced in the sand flat and the seagrass meadow and led to an increase in energy transfer and parallel trophic cycles in these habitats. Habitat diversity appears to be an important trait for the Wadden Sea as each subsystem seems to have a specific role in the overall functioning of the entire ecosystem.

Network analysis indices reflect extreme hydrodynamic conditions in a shallow estuarine lake (Lake St Lucia), South Africa

A hybrid fuzzy method for performance evaluation of fusion algorithms for integrated navigation system

With the gradual popularization of hydrogen fuel cell vehicles (HFCVs), the construction and planning of hydrogen refueling stations (HRSs) are increasingly important. Taking operational HRSs in China’s coastal and major cities as examples, we consider the main factors affecting the site selection of HRSs in China from the three aspects of economy, technology and society to establish a site selection evaluation system for hydrogen refueling stations and determine the weight of each index through the analytic hierarchy process (AHP). Then, combined with fuzzy comprehensive evaluation (FCE) method and artificial neural network model (ANN), FCE method is used to evaluate HRS in operation in China’s coastal areas and major cities, and we used the resulting data obtained from the comprehensive evaluation as the training data to train the neural network. So, an intelligent site selection model for HRSs based on fuzzy comprehensive evaluation and artificial neural network model (FCE-ANN) is proposed. The planned HRSs in Shanghai are evaluated, and an optimal site selection of the HRS is obtained. The results show that the optimal HRSs site selected by the FCE-ANN model is consistent with the site selection obtained by the FCE method, and the accuracy of the FCE-ANN model is verified. The findings of this study may provide some guidelines for policy makers in planning the hydrogen refueling stations.

Graph theory (GT) is extensively applied in the ecological network analysis. This review study aimed to examine GT in the field of ecological network analysis based on the following questions: In what areas are the articles focused?, what indexes or graph-based indicators have been thus far utilized in ecological network analysis?, and what aspects of ecological network analysis have been less considered in terms of the use of the GT indicators? To address these questions, a systematic literature review was conducted and the results showed that most of the articles in this field had been fulfilled in China, the United States, and France. This theory could have implications for more research on plants and mammals. In addition, 118 indicators were identified in the field of GT in the ecological network analysis. Among these indicators, the probability of connectivity (PC) and an integral index of connectivity (IIC) had been consistently exploited in most articles. Moreover, the results revealed the increasing trend of introducing the new indicators of GT to ecological network analysis, suggesting the applicability of GT in this context. Despite the importance of ecological network resilience, it has been less reflected from the GT perspective while it can be useful and efficient in analyzing the sustainability of ecological networks within this framework. The current trend of exploiting the GT indicators delineates three future lines of development, viz. (1) the GT use more widely in ecological network analysis, (2) emerging new and more precise indexes, and (3) new concerns mainly examining ecological network resilience.

An approach towards quantification of ecosystem trophic status and health through ecological network analysis applied in Hooghly-Matla estuarine system, India