Management thresholds are a useful tool to inform decision-makers when management intervention is required to address undesirable environmental changes. These tools have had widespread application in natural resource management like fisheries and water quality management, but less so in conservation.

My colleagues, Kelly de Bie and Libby Rumpff, and I found ourselves in need of an approach to develop conservation management thresholds for the following situation, where management thresholds: (1) must be set for environmental indicators in the face of multiple competing objectives; (2) need to incorporate scientific understanding and value judgments; and, (3) involve participants in the process with limited modelling experience. As no approaches existed to address our situation, we devised a new participatory modelling approach for setting management thresholds.

The approach that we devised follows the steps of structured decision-making, which is very useful in supporting multi-objective conservation decision-making. Structured decision-making also enables the incorporation of scientific knowledge and value judgments into decision-making, and promotes the involvement of decision makers, stakeholders, and experts (collectively participants) in the decision-making process. Our approach draws on a unique combination of modelling techniques within each step of structured decision-making, which have not been used to set conservation management thresholds to date (Figure 1).

The steps of the participatory modelling process and recommended techniques to set management thresholds.
Figure 1. The steps of the participatory modelling process and recommended techniques to set management thresholds.

In our recent Conservation Biology paper, we describe this participatory modelling approach to set management thresholds, and illustrate its application using a case study where management thresholds were set for a mat-forming brown alga, Hormosira banksii (Figure 2), in an Australian marine protected area.

Figure 2. A rocky intertidal reef in Victoria, Australia, with a close up of the brown alga, Hormosira banksii.
Figure 2. A rocky intertidal reef in Victoria, Australia, with a close up of the brown alga, Hormosira banksii.

Participants, including management staff and scientists, were involved in a workshop to test the approach, and set management thresholds to address the threat of trampling by visitors to an intertidal rocky reef. The approach involved trading off the environmental objective, to maintain the condition of intertidal reef communities, with social and economic objectives to ensure management intervention did not ruin visitor experience and was cost-effective.

Ecological scenarios, developed using scenario planning, were a key feature of this approach that provided the foundation for where to set management thresholds. The four scenarios developed represented the current condition, and plausible declines in percent cover of H. banksii that may occur under increased threatening processes in the future (Figure 3).

The ecological scenarios developed using scenario planning, representing the current condition (70% cover), and plausible declines in percent cover of H. banksii (42%, 30% and 15% cover) that may occur under increased threatening processes in the future. Monitoring data showing the current condition of H. banksii (solid black line: mean percentage cover [SE]) at the intertidal reef is also displayed.
Figure 3. The ecological scenarios developed using scenario planning, representing the current condition (70% cover), and plausible declines in percent cover of Hormosira (42%, 30% and 15% cover) that may occur under increased threatening processes in the future. Monitoring data showing the current condition of Hormosira (solid black line: mean percentage cover [SE]) at the intertidal reef is also displayed.
Participants defined four discrete management alternatives to address the threat of trampling and estimated the consequence of these alternatives on the objectives under each ecological scenario. A weighted additive model was used to aggregate participants’ consequence estimates. Model outputs (decision scores) clearly expressed uncertainty (Figure 4), which can be considered by decision- makers and used to inform where to set management thresholds (Figure 5).

Figure 4. The performance of the 4 management alternatives under the ecological scenarios representing the current condition (70% cover) and 3 plausible states of reduced cover of Hormosira (42%, 30%, and 15% cover).
Figure 4. The performance of the 4 management alternatives under the ecological scenarios representing the current condition (70% cover) and 3 plausible states of reduced cover of Hormosira (42%, 30%, and 15% cover).

Figure 5. The medium protection management threshold implementation range (amber shading) for Hormosira informed by decision scores in Figure 3. The current condition of Hormosira (solid black line: mean percentage cover [SE]) at the intertidal reef is shown from 2004 to 2013, and the ecological scenarios are represented by the four horizontal lines (as presented in Figure 2).
Figure 4. The medium protection management threshold implementation range (amber shading) for Hormosira informed by decision scores in Figure 3. The current condition of Hormosira (solid black line: mean percentage cover [SE]) at the intertidal reef is shown from 2004 to 2013, and the ecological scenarios are represented by the four horizontal lines (as presented in Figure 2).
Why set conservation management thresholds?

Setting management thresholds remains a challenging task in conservation. We believe this novel participatory modelling approach provides an accessible and effective method to set conservation management thresholds.

One single approach to setting management thresholds will not be suitable for all contexts, as conservation decisions often involve different circumstances that will require different modelling approaches. We propose this participatory modelling approach as one in a toolbox of available approaches to assist with setting management thresholds.

Most importantly this participatory modelling approach encourages a proactive form of conservation management, where management thresholds and associated management actions are defined a priori for ecological indictors, rather than reacting to unexpected future ecosystem changes.

Want to find out more about this research?

Please feel free to download our open access Conservation Biology paper.

For those attending the International Congress for Conservation Biology in Marseille, France, please come along to my presentation in the Adaptive Management and Monitoring session on Tuesday 4th of August, 8.30-10.00, room Sully 1.

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