The process of setting objectives for biodiversity monitoring is an exercise in research prioritization that should seek to identify the management practices or threatening processes whose evaluation would make the greatest contribution towards improving opportunities for biodiversity conservation.

Research priorities are commonly selected on a relatively ad hoc basis that is strongly influenced by the nature of funding opportunities, as well as differences in the personal interest of the researchers involved. Adopting a more systematic approach that compares alternative objectives with regard to their ability to generate real and practically relevant learning, could greatly increase the efficiency and cost-effectiveness of research.

The first step in a more systematic approach to identifying research priorities is to identify a suite of existing and/or potential management practices or ‘management control variables’ that are candidates for evaluation. This review process can be aided by a series of assessments to summarize information on current management practices, the structure and composition of the study landscape, and the characteristics of reference sites.

The second step is to employ a selection framework for identifying priority objectives from this candidate set. The three types of motivation that drive decisions about research priorities are: the opportunity to learn – what management practices are feasible to evaluate and monitor?; the necessity to learn – what management practices are associated with the greatest level of uncertainty regarding their implications for biodiversity conservation?; and the value of learning – what management practices, if adjusted or newly implemented, are likely to deliver the greatest benefits for biodiversity?

The value of learning is determined not only by the estimated impact of management on biodiversity (e.g. as determined by a formal risk assessment), but also by the extent to which any findings can be extended to other landscapes and related management systems, and the likelihood with which any findings from monitoring will translate into policy change.