Are we missing the boat?

Using long-term monitoring data in managing marine protected areas

Long-term biological monitoring data are becoming increasingly available to inform conservation efforts around the world. These data are rich sources of scientific evidence that offer insights into the natural variability of ecosystems and species through time, as well as revealing information about the effectiveness of conservation efforts. However, there are many occasions where long-term monitoring data, like other forms of scientific evidence, have been of little use to conservation management. So, how are we going in Australia when it comes to using long-term monitoring data to inform management decisions? You often hear that conservation management agencies fail to use scientific evidence to inform management but our investigation suggests this is not the case – though there is room for improvement.

We recently explored how long-term biological monitoring data are used to inform the management of Australian marine protected areas (MPAs). We focussed on long-term monitoring programs from Australian MPAs, as these include some of the world’s longest running marine monitoring programs. Part of their value is the contribution they make to our understanding of the biological effects of MPAs. They also generate rich data sources that are available to inform the ongoing management of MPAs.

The first goal of MEE (to enable environmental accountability and reporting) is being achieved, but the second goal of facilitating evidence-based management is not.” 

We conducted interviews with MPA managers and scientists from Australian management agencies to document a national perspective of how long-term biological monitoring data are used to inform evidence-based management of Australian MPAs (Addison et al., 2015).

We asked MPA managers and scientists about seven long-term biological monitoring programs that occur within five networks of MPAs in Australian state and Commonwealth waters. These MPAs are some of the oldest in Australia having been established for an average of 20.3 years (ranging from 11 to 39 years) and have some of longest running monitoring programs, undertaken for an average of 18.7 years (ranging from 12 to 27 years, with some commencing before the MPA was established). All of the monitoring programs involved sampling both inside and outside of no-take zones, and occur in either a single MPA or are replicated in several MPAs across a network.

Figure 2: Management decisions made in Australian MPAs in response to the seven long-term biological monitoring programs. The different colours represent different monitoring programs (de-identified to avoid direct comparison).

Figure 2: Management decisions made in Australian MPAs in response
to the seven long-term biological monitoring programs. The different
colours represent different monitoring programs (de-identified to avoid
direct comparison).

As with protected area management agencies around the globe, Australian agencies responsible for managing MPAs commonly use management effectiveness evaluation (MEE) to better understand, learn from and improve conservation outcomes (see the box on MEE in MPAs). These evaluations are being used to judge the effectiveness of management in many Australian MPAs, however this process is in its infancy, with only one or two evaluation cycles having occurred in most cases.

Our research revealed that many long-term biological monitoring programs are used to inform qualitative condition assessments of biological indicators (under the ‘outcomes’ stage of a MEE cycle), where published monitoring results are interpreted using expert judgment in most cases. This means that available quantitative biological monitoring data are not yet used to provide maximum value in formal quantitative condition assessments for MEE.

While not yet fully utilized in MEE, we found substantial evidence that long-term monitoring data are informing the evidence-based management of MPAs (Figure 2) – contrary to the common criticism that conservation management agencies fail to use scientific evidence to inform management.

Many management agencies use monitoring results to justify the continued need for scientific research and monitoring in MPAs to resolve key uncertainties and identified knowledge gaps. Long-term monitoring results have also been valuable in supporting planning decisions, such as re-zoning MPAs based on an improved understanding of the distribution of marine habitats. Long-term monitoring results have also informed a variety of routine management decisions, such as the development of educational programs, compliance efforts, introduced species control and infrastructure development in MPAs.

Despite the goal of MEEs to enable evidence-based management of protected areas, we found that MEE is rarely the only mechanism that facilitates the knowledge transfer of science to management action. ‘Closing the loop’ of MEE to ensure evidence-based management remains a challenge for many management agencies around the globe.

How might we meet this challenge? In our paper, we provide several recommendations on how to improve the use of long-term monitoring data in MEE for evidence-based management. These include:

  • Ensuring internal MEE frameworks reflect MEE theory, to determine where breaks in the information chain may be preventing the use of monitoring data in evidence-based management.
  • Implementing quantitative condition assessment of long-term monitoring data to ensure more objective, repeatable and transparent use of monitoring data in MEE.
  • Invest in targeted long-term monitoring to support outcome assessments.
  • Increase the frequency of evaluation to ensure MEE enables evidence-based management.

On this last point, a shorter evaluation timeframe, more frequent than the common 5–10 year cycle, should improve the alignment of MEE with evidence-based management. More frequent in-house evaluation will ensure evidence-based management becomes the main driver of MEE, rather than public accountability through associated public reporting.

During our interviews, most informants indicated a willingness to move towards using monitoring results in quantitative condition assessment and to forge a stronger link between MEE and evidence-based management. All of which bodes well for the future of our unique network of marine protected areas.


Management effectiveness evaluation (MEE) has gained global recognition as an important framework to promote the continual improvement of conservation efforts in protected areas. It involves an assessment of the complete management process: beginning with clearly defining the management context, through to measuring conservation outcomes to determine whether management objectives are being achieved (see Figure 1).

In response to the growing societal demand for environmental accountability, there is a focus on publicly reporting MEE results to demonstrate the value for money of conservation efforts. But, ultimately, MEE is designed to facilitate evidence-based management to ensure the best conservation outcomes for protected areas.

MEE should draw on the best available evidence, using both qualitative and quantitative data to support assessments. Whilst qualitative data are most appropriate for some aspects of management (eg, measuring stakeholder engagement), other aspects (eg, measuring ecological condition) should ideally be based on quantitative data sourced from monitoring or research. A lack of quantitative data often necessitates reliance on qualitative information, such as expert judgment, in MEE.

Outcome assessment is the final stage of MEE, where the condition of important environmental attributes is assessed to determine whether management objectives have been achieved or if management should be adapted. This requires an assessment of the condition of indicators, such as the abundance of a threatened species.

When monitoring data are available, these should be assessed against condition categories that have been defined numerically. Quantitative condition categories are commonly based on an acceptable range of natural variation of an indicator. For example, the United States National Parks Service uses historic long-term monitoring data to define quantitative condition categories for average forest patch size to reflect landscape fragmentation due to anthropogenic stressors, as: Good (>50 ha); Caution (10–50 ha); and Significant Concern (<10 ha). Quantitative condition assessments can enable more transparent and repeatable integration of monitoring data into MEE, and when condition categories represent thresholds that trigger management action promotes evidence-based management. In addition, condition rating scales can help simplify complex information about natural systems for public reporting.

Figure 1: The management effectiveness evaluation cycle. The cycle is designed to enable an assessment of the complete management process and facilitate evidence-based management. (Adapted from Hocking et al., 2006)

Figure 1: The management effectiveness evaluation cycle. The cycle is designed to enable an assessment of the complete management process and facilitate evidence-based management. (Adapted from Hocking et al., 2006)

Australian MPAs

Monitoring in the Great Barrier Reef Marine Park (Photo by Juergen Freund, AIMS)

Monitoring in the Great Barrier Reef Marine Park
(Photo by Juergen Freund, AIMS)

Australia’s marine protected areas (MPAs) are established for biodiversity conservation and many were gazetted more than ten years ago. These MPAs fall under either state or federal jurisdiction and all management agencies aspire to regularly monitor, evaluate and report on their management effectiveness. Like other parts of the world, long-term monitoring programs in Australian MPAs predominantly assess the effect of protection on subtidal coral and rocky reef communities.

More info: Prue Addison; 

Note: This research was part of Prue Addison’s PhD at the University of Melbourne. She is now a postdoc at AIMS. 


Hockings M, S Stolton, F Leverington, N Dudley & J. Courrau (2006). Evaluating Effectiveness: a Framework for Assessing Management Effectiveness of Protected Areas (second ed.) IUCN, Gland, Switzerland/Cambridge, UK (2006), p. 105.

Addison PFE, LB Flander & CN Cook (2015). Are we missing the boat? Current uses of long-term biological monitoring data in the evaluation and management of marine protected areas. Journal of Environmental Management 149: 148-156. 

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