ISFREM · Improved spatial Frameworks for river environment management
FP6 — Marie Curie Actions (Human Resources and Mobility)
- Duration
- 2006-10-02 → 2008-10-01
- EU contribution
- €216,291
- Participants
- 1
- Scheme
- IIF
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Results in brief
Final Activity Report Summary - ISFREM (Improved spatial frameworks for river environment management)
This project undertook research of environmental classifications derived for use as spatial frameworks for river environmental management. Environmental classifications are spatially explicit (i.e. mapped) surrogates for patterns in ecological characteristics of interest to resource and conservation managers (such as environmental regimes and species composition). The first project compared the performance (i.e. the degree to which classes discriminate areas with similar ecological character) of two classifications of the rivers of France; a conventional geographic regionalisation ('hydro-ecoregions') developed in accordance with the European Water Framework Directive and a numerical classification of segments of a digital river network. Both classifications were derived from a common dataset describing climate, topography and geology of France and were tested with independent water chemistry, invertebrate and hydrological data. The test results showed that there was little difference in the performance of the two classifications. The subsequent studies attempted to increase performance of network and other numerical classifications using statistical modelling. A classification of natural flow regimes of France was defined by first classifying gauging stations based on their flow records. Statistical modelling was used to predict class membership for all segments of a digital river network based on environmental variables. Tests of this spatial framework indicated that it had significantly better predictive performance than the hydro-ecoregions. However, despite strong scientific support for concept of the natural flow regime as the 'master variable' controlling ecological patterns in rivers, tests showed that flow regime classes had very weak relationships with fish assemblages observed at 297 sites throughout France. This result did not support the use of flow regime classifications as spatial frameworks for managing river flows. Four subsequent projects applied various forms of statistical modelling to the definition of environmental classifications for terrestrial regions in Switzerland and rivers in Spain and New Zealand. These studies showed that statistical modelling (i.e. using a small dataset to 'train' a classification) can produce significant increases in performance of classifications. Thus, the research developed a progression from subjective to more objective techniques to define classifications for both river and terrestrial environments and demonstrated the potential performance gains in a variety of environmental contexts. Seven papers were generated and a software library comprising various functions to test and define classifications.
Data: CORDIS, © European Union
Project objective
European Water Framework Directives such as reaching a 'good ecological status' require that achievable conditions be assessed, and restoration targets are set, over large areas. In this context, spatial frameworks (delineation of ecological pattern) are used to predict ecological potential over large scales and to implement harmonious ecological objectives. We propose to undertake management-oriented research to develop new spatial frameworks for river management.Methods, developed by the researcher in New Zealand, provide high spatial resolution ecological classifications of rivers and use advances in Geographic Information System and classification methods. In contrast with existing regionalisation approaches (subdividing landscapes into large regions), they classify individual segments of digital representations of river networks using functionally important ecological attributes (of the segment or inherited from the river's catchment through the network structure).Our first and second objectives are to define new classifications and compare them with existing regionalisations. Tests will be based on taxonomic and functional descriptions (e.g., biological traits) of river ecosystems. Objective three is to use the classifications to extrapolate existing general ecological models to entire river systems (e.g., models of ecological responses to flow modifications). The work will be based on available databases, models and tools. Tests using functional descriptors are uncommon and can demonstrate the generality of our approach. Spatial extrapolation of ecological models will increase their value as management and research tools. The researcher will work in an environment with a strong background in ecological research, modelling and spatial framework development. The project will benefit international and national research projects that use spatial frameworks and ecological models.
Original text from CORDIS.
Participants
- CENTRE NATIONAL DU MACHINISME AGRICOLE, DU GÉNIE RURAL DES EAUX ET DES FORÊTS · ANTONYCoordinatorCity levelFrance
Links
Data: CORDIS, © European Union