15 research outputs found
Aquatic Terrestrial Linkages Along a Braided-River: Riparian Arthropods Feeding on Aquatic Insects
Rivers can provide important sources of energy for riparian biota. Stable isotope analysis (δ13C, δ15N) together with linear mixing models, were used to quantify the importance of aquatic insects as a food source for a riparian arthropod assemblage inhabiting the shore of the braided Tagliamento River (NE Italy). Proportional aquatic prey contributions to riparian arthropod diets differed considerable among taxa. Carabid beetles of the genus Bembidion and Nebria picicornis fed entirely on aquatic insects. Aquatic insects made up 80% of the diet of the dominant staphylinid beetle Paederidus rubrothoracicus. The diets of the dominant lycosid spiders Arctosa cinerea and Pardosa wagleri consisted of 56 and 48% aquatic insects, respectively. In contrast, the ant Manica rubida fed mainly on terrestrial sources. The proportion of aquatic insects in the diet of lycosid spiders changed seasonally, being related to the seasonal abundance of lycosid spiders along the stream edge. The degree of spatial and seasonal aggregation of riparian arthropods at the river edge coincided with their proportional use of aquatic subsidies. The results suggest that predation by riparian arthropods is a quantitatively important process in the transfer of aquatic secondary production to the riparian food we
Effects of riparian arthropod predation on the biomass and abundance of aquatic insect emergence
Abstract. Adult aquatic insects are important energy subsidies for terrestrial predators, but the effects of terrestrial predators on emerged aquatic insects have been widely neglected. We compared emergence of aquatic insects from predator-free exclosures and open cages to test the hypothesis that riparian arthropod predators can reduce the abundances of emerged aquatic insects. We used emergence traps over the aquatic and terrestrial sides of the shoreline to collect insects that emerged from the water or crawled onto land to emerge. The abundances and taxonomic composition of emerged aquatic insects and riparian arthropod predators changed seasonally. Riparian arthropods consumed 45% of emerged aquatic insect biomass from terrestrial traps in spring and 45% from aquatic traps in summer. The dominant riparian predator at the time of emergence determined the specific predation effect. Stoneflies that emerged into terrestrial traps were significantly reduced when ground beetles were the most abundant predators; caddisflies that emerged into aquatic traps were significantly reduced when spiders were the most abundant predators. Thus, taxon-specific predation by riparian arthropods can affect the taxonomic composition of emerged aquatic insects
Effects of riparian arthropod predation on the biomass and abundance of aquatic insect emergence
The macro-ecological model:making sense of the conflicts in integrated catchment management
Bringing diverse knowledge sources together:a meta-model for supporting integrated catchment management
Integrated catchment management (ICM), as promoted by recent legislation such as the European Water Framework Directive, presents difficult challenges to planners and decision-makers. To support decision-making in the face of high complexity and uncertainty, tools are required that can integrate the evidence base required to evaluate alternative management scenarios and promote communication and social learning. In this paper we present a pragmatic approach for developing an integrated decision-support tool, where the available sources of information are very diverse and a tight model coupling is not possible. In the first instance, a loosely coupled model is developed which includes numerical sub-models and knowledge-based sub-models. However, such a model is not easy for decision-makers and stakeholders to operate without modelling skills. Therefore, we derive from it a meta-model based on a Bayesian Network approach which is a decision-support tool tailored to the needs of the decision-makers and is fast and easy to operate. The meta-model can be derived at different levels of detail and complexity according to the requirements of the decision-makers. In our case, the meta-model was designed for high-level decisionmakers to explore conflicts and synergies between management actions at the catchment scale. As prediction uncertainties are propagated and explicitly represented in the model outcomes, important knowledge gaps can be identified and an evidence base for robust decision-making is provided. The framework seeks to promote the development of modelling tools that can support ICM both by providing an integrated scientific evidence base and by facilitating communication and learning processes
Appendix A. Additional details about study sites, methods, and results.
Additional details about study sites, methods, and results
Bayesian networks for a multi-objective evaluation of River Basin Management Plans
The European Water Framework Directive (WFD) sets out an integrated perspective to water management in river catchments and river basin districts and is a key driver in the movement towards Integrated River Basin Management. Integrated river basin management must deliver objectives related to the WFD in the wider context of various other stakeholder interests, for example related to flooding, water resources, employment and cost. In managing such complex systems, a specific objective can be achieved through different management actions. Likewise, a specific management action can have implications for multiple objectives. Synergies or conflicts between specific objectives and between specific actions are likely to occur, and need careful consideration in order to increase the efficiency of planned management actions. However, such integrated decision making is a very difficult and highly complex task, which cannot easily be accomplished by either single or groups of planners. Integrated modelling tools to facilitate and enhance communication within a group of decision-makers and inform a more objective and evidence-based multi-criteria decision-making process are required. The scope for the development of such an integrated tool is being tested by the Catchment Science Centre (CSC) at The University of Sheffield. The CSC and the Environment Agency are jointly developing a tool termed the Macro-Ecological Model (MEM). The MEM is developed as a consistent framework for the integration of knowledge and information about environmental, social and economic processes and process-interactions that are affected by management actions and have impacts on multiple management objectives. The MEM enables knowledge from various different resources to be integrated, including empirical data, model results and even expert knowledge using a Bayesian Belief Network (BBN) approach. BBNs have the advantage of representing system understanding in an intuitive, graphical format. Furthermore, the approach provides the ability to explicitly account for uncertainties in model predictions. Therefore, the model framework provides a good tool for visualising system understanding and communicating uncertainties. Applied in a participatory process, it can support robust decision making in river basin management. The conceptual model framework is illustrated with examples from the prototyping study. The prototype model captures the process interactions affecting the management objectives "Ecological Status" (composed of both Biological Quality and Physico-chemical Quality) and "Flood Risk". It is planned to be later extended to incorporate further environmental, and also social and economic objectives
A consistent framework for knowledge integration to support Integrated Catchment Management
The European Water Framework Directive (WFD) sets out an integrated perspective to water management in river catchments and river basin districts and is a key driver in the movement towards Integrated River Basin Management. Integrated river basin management must deliver objectives related to the WFD in the wider context of various other stakeholder interests, for example related to flooding, water resources, employment and cost. In managing such complex systems, a specific objective can be achieved through different management actions. Likewise, a specific management action can have implications for multiple objectives. Synergies or conflicts between specific objectives and between specific actions are likely to occur, and need careful consideration in order to increase the efficiency of planned management actions. However, such integrated decision making is a very difficult and highly complex task, which cannot easily be accomplished by either single or groups of planners. Integrated modelling tools to facilitate and enhance communication within a group of decision-makers and inform a more objective and evidence-based multi-criteria decision-making process are required. The scope for the development of such an integrated tool is being tested by the Catchment Science Centre (CSC) at The University of Sheffield. The CSC and the Environment Agency are jointly developing a tool termed the Macro-Ecological Model (MEM). The MEM is developed as a consistent framework for the integration of knowledge and information about environmental, social and economic processes and process-interactions that are affected by management actions and have impacts on multiple management objectives. The MEM enables knowledge from various different resources to be integrated, including empirical data, model results and even expert knowledge using a Bayesian Belief Network (BBN) approach. BBNs have the advantage of representing system understanding in an intuitive, graphical format. Furthermore, the approach provides the ability to explicitly account for uncertainties in model predictions. Therefore, the model framework provides a good tool for visualising system understanding and communicating uncertainties. Applied in a participatory process, it can support robust decision making in river basin management. The conceptual model framework is illustrated with examples from the prototyping study. The prototype model captures the process interactions affecting the management objectives “Ecological Status” (composed of both Biological Quality and Physico-chemical Quality) and “Flood Risk”. It is planned to be later extended to incorporate further environmental, and also social and economic objectives