Moorinya National Park, Queensland
Photo © Megan Barnes

Assessing the effectiveness of protected areas for biodiversity conservation.

Megan Barnes, PhD candidate, University of Queensland.

As part of her research project, Megan is conducting a case study in Queensland and looking to identify population estimates for fauna species in Queensland. The project and data request is outlined below. If anyone has any information that may assist with her research, please email Megan.

The Project

Protected areas are key tools in biodiversity conservation and over the past decade we have also made great advances in understanding issues of protected area management effectiveness. However, there is surprisingly little data available at a global level on outcomes in general and more specifically, on long-term biodiversity conservation outcomes from protected areas. In particular, there are large gaps in understanding of the relative effectiveness of different management approaches and governance models within protected areas as they relate to biodiversity outcomes. Our current research project intends to use partial, full and complementary datasets from protected sites and their surrounding area globally to assemble a meta data-set to determine whether protected areas have been successful in maintaining their biodiversity values.

As part of this study I am conducting a case study in Queensland. I am looking to identify population estimates for fauna species in Queensland. Time series are required for this analysis, but individual (one-off) estimates are still of interest as they could potentially be updated. For the same reason, and in order to be comprehensive, data does not need to be up to date, just to quantitatively estimate population abundance or a proxy thereof.

Existing data sets will be used from protected areas around the world to assess long-term conservation success.

Data checklist

Basic Trend Data (within a protected area)

• At least 2 separate years
• Information on date of collection must be available (at least year)
• Some estimate of population abundance of proxy thereof – e.g. nest counts, density etc.
• Information available on data collection methods, units of measurement and geographic location
• Consistent data collection methods through time or methods indexed
• Consistent geographic locations used throughout for any one set of data

If you have data which you feel is close to meeting these criteria, or may be able to be matched with other data to meet the criteria, we are also happy to accept it. Please contact us if you have any doubts.

Ideal Trend Data

• Long term trend data for species, communities, habitats or ecosystems within protected areas. 
• At least two data points are essential for data to be useful, separated by a meaningful time period –e.g. spanning  at least 5 years, optimally ten years or more.
• Ideally data would be repeated periodically over an extended period of time – the longer the better, but at least 5 years of data is necessary to make an adequate assessment of change through time. 
• Ideally data would include trends within PA’s and outside them in comparable areas although trend data without external comparison is still useful
• Ideally both regional and PA trend data would be available and comparable
• Ideally data for the same variable both inside and outside parks obtained using similar methods in comparable areas would be available.
• Ideally there would be some sort of historical baseline to which we can compare results, for example, from prior to PA establishment
• Ideally data would pertain to functionally important species or guilds, representative groups and/or indicator species.

The data used in this analysis will be reported at a broad spatial scale and combined with many other data sources. All sources will be fully acknowledged and credited appropriately. Data agreements will be entered into with parties providing data as necessary.

If you think you or someone you know has data that fits any of the specified criteria, we would really like to discuss its inclusion in the study. Please contact Megan Barnes or Marc Hockings

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