Linking the multiple types of monitoring to the adaptive management cycle to support environmental flows.

Abstract

With accelerated declines in ecosystems, targeted and effective environmental management programs are increasingly important. These programs always operate under some degree of uncertainty, and adaptive management is often used as an iterative learning process to assist decision making under uncertainty. Monitoring plays a critical role in adaptive management as knowledge is gathered to evaluate the effectiveness of the interventions to resolve uncertainty and improve decisions. While there is extensive literature on improving adaptive management, little has focused specifically on monitoring. In this paper, we examine the role that different types of monitoring play in supporting adaptive management and how monitoring programs are conceived and evolve over time. We propose a novel double-loop framework that facilitates identification of critical uncertainties and iterative adjustment of the investment in monitoring to support management. It foreshadows a shift in monitoring resources away from filling knowledge gaps as understanding of ecosystem processes improves, towards other knowledge gaps or fundamental environmental outcomes. We demonstrate the framework through a case study on golden perch responses to environmental flows in the Goulburn River, Australia. After 8 years of monitoring, an initial knowledge gap regarding the flow-spawning relationship for golden perch has been filled, and we recommend now reducing monitoring effort in this area to redirect resources to other critical uncertainties. This framework is broadly applicable across various fields. It has the potential to enhance the efficiency and effectiveness of environmental management programs and strengthen purposeful learning within the adaptive management cycle.