Sustainability is a key concept in resource management and environmental issues, but implementation is fraught with difficulty due to lack of agreement as to what it means. Because of the ubiquity of disturbance, ecosystem sustainability inevitably involves change. We define stand-level biophysical sustainability as non-declining patterns of change over at least three cycles of disturbance, and landscape-level sustainability as a shifting mosaic of non-declining stand change, the overall character of which remains within acceptable limits over time. Simple empirical assessment (i.e., monitoring) of this concept of sustainability is generally not practical in forestry because of the long time and large spatial scales involved. Adaptive management (AM), another key resource management concept, involves monitoring to assess the consequences of management actions. It requires forecasts of expected change in sustainably managed, post-disturbance ecosystems against which to assess monitoring data. Without these forecasts, which constitute temporal fingerprints of sustainable change, short-term monitoring data cannot be used reliably as a basis from which to assess longer-term sustainability. A comprehensive monitoring system to address biophysical sustainability locally and at the landscape scale for a large management unit over a rotation-length time scale would involve the key elements of ecosystem structure and function and the effects thereon of management and climate change. This would be prohibitively expensive and demanding of human resources and the results would not be available until the end of the rotation. A strategy that honours the intent of AM is an intimate linkage between predictive monitoring and process-based ecosystem management decision support systems—ecosystem process-based monitoring—the emphasis of which is on temporal patterns of indicator change rather than comparisons between static indicators and audits of current ecosystem conditions (the certification approach). It involves a combination of monitoring and ecosystem management modeling that reduces the long-term cost of monitoring and increases the utility of the data collected for the assessment of sustainability and for the design of policy and adaptive practice in forestry. Key words: prediction, process-based monitoring, sustainability, forest ecosystems, biophysical indicators, temporal fingerprints, adaptive management, ecosystem management models
DECISION SUPPORT SYSTEMS FOR WATER RESOURCE MANAGEMENT APPLIED TO ANDEAN SUPPLY MICRO-BASINS