At the global scale, biodiversity indicators are typically used to monitor general trends, but are rarely implemented with specific purpose or linked directly to decision making. Some indicators are better suited to predicting future change, others are more appropriate for evaluating past actions, but this is seldom made explicit. We developed a conceptual model for assigning biodiversity indicators to appropriate functions based on a common approach used in economics. Using the model, indicators can be classified as leading (indicators that change before the subject of interest, informing preventative actions), coincident (indicators that measure the subject of interest), or lagging (indicators that change after the subject of interest has changed and thus can be used to evaluate past actions). We classified indicators based on ecological theory on biodiversity response times and management objectives in 2 case studies: global species extinction and marine ecosystem collapse. For global species extinctions, indicators of abundance (eg, the Living Planet Index or biodiversity intactness index) were most likely to respond first, as leading indicators that inform preventative action, while extinction indicators were expected to respond slowly, acting as lagging indicators flagging the need for evaluation. For marine ecosystem collapse, indicators of direct responses to fishing were expected to be leading, while those measuring ecosystem collapse could be lagging. Classification defines an active role for indicators within the policy cycle, creates an explicit link to preventative decision-making, and supports preventative action.

Item Type:	Refereed Article
Keywords:	Aichi Targets, biodiversity indicators, Convention on Biological Diversity, ecosystem based fisheries management, extinction, IUCN red list index, population dynamics, sustainable development goals
Research Division:	Environmental Sciences
Research Group:	Environmental management
Research Field:	Conservation and biodiversity
Objective Division:	Environmental Management
Objective Group:	Coastal and estuarine systems and management
Objective Field:	Rehabilitation or conservation of coastal or estuarine environments
UTAS Author:	Fulton, EA (Dr Elizabeth Fulton)
ID Code:	143235
Year Published:	2020
Web of Science® Times Cited:	11
Deposited By:	Ecology and Biodiversity
Deposited On:	2021-03-06
Last Modified:	2021-05-04
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