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Riverine landscape dynamics and ecological risk assessment


Dr Rob S. E. W. Leuven, Department of Environmental Studies, Faculty of Science, Mathematics and Computing Science, University of Nijmegen, PO Box 9010, 6500 GL Nijmegen, The Netherlands. E-mail:


1. The aim of ecological risk assessments is to evaluate the likelihood that ecosystems are adversely affected by human-induced disturbance that brings the ecosystem into a new dynamic equilibrium with a simpler structure and lower potential energy. The risk probability depends on the threshold capacity of the system (resistance) and on the capacity of the system to return to a state of equilibrium (resilience).

2. There are two complementary approaches to assessing ecological risks of riverine landscape dynamics. The reductionist approach aims at identifying risk to the ecosystem on the basis of accumulated data on simple stressor–effect relationships. The holistic approach aims at taking the whole ecosystem performance into account, which implies meso-scale analysis.

3. Landscape patterns and their dynamics represent the physical framework of processes determining the ecosystem's equilibrium. Assessing risks of landscape dynamics to riverine ecosystems implies addressing complex interactions of system components (e.g. population dynamics and biogeochemical cycles) occurring at multiple scales of space and time.

4. One of the most important steps in ecological risk assessment is to establish clear assessment endpoints (e.g. vital ecosystem and landscape attributes). Their formulation must recognise that riverine ecosystems are dynamic, structurally complex and composed of both deterministic and stochastic components.

5. Remote sensing (geo)statistics and geographical information systems are primary tools for quantifying spatial and temporal components of riverine ecosystem and landscape attributes.

6. The difficulty to experiment at the riverine landscape level means that ecological risk management is heavily dependent on models. Current models are targeted towards simulating ecological risk at levels ranging from single species to habitats, food webs and meta-populations to ecosystems and entire riverine landscapes, with some including socio-economic considerations.

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