Protected Area Representativeness Index
The Protected Area Representativeness Index estimates the extent to which terrestrial biodiversity is included in protected areas. It integrates information from a global protected areas database with modeled fine-scaled spatial variation in biodiversity composition.
This indicator ranges from 0-1, with values closer to 1 indicating fully protected biodiversity and values closer to 0 representing no biodiversity protection. An increase in the Protected Area Representativeness Index reflects an increase in that region's (and adjacent region's) protection of biodiversity.
The Protected Area Representativeness Index is derived by combining ecological uniqueness with protected areas for the year of interest. Protected-area boundaries were used from the World Database on Protected Areas (UNEP-WCMC 2016; WDPA), while ecological uniqueness is calculated as the inverse of the summed ecological similarity of a given 'focal cell' to surrounding cells (see Table 1 for details on the ecological similarity model). The Protected Area Representativeness Index score assigned to a given 'focal cell' is therefore calculated as the proportional protection of all ecologically-similar cells, with the contribution any other cell makes to this calculation weighted according to its predicted level of similarity with the focal cell (Ferrier et al. 2004; Allnutt et al. 2008; Williams et al. 2016). The Protected Area Representativeness Index for any given spatial reporting unit (e.g. basin, country) is then derived as a weighted geometric mean (Buckland et al. 2005) of the scores obtained for all cells within that unit, with the contribution of each cell weighted according to its ecological uniqueness - i.e. the inverse of the summed ecological similarity of this cell to all other cells (for further details see Ferrier et al. 2004, Allnutt et al. 2008, Williams et al. 2016). This aggregate score indicates the extent to which protected areas represent the full range of biological diversity occurring within a given reporting unit.
Table 1. Ecological similarity models (Ferrier et al. 2007; Allnutt et al. 2008; Williams et al. 2016).
The fitted generalized dissimilarity models (GDMs) represent spatial turnover in species composition as a function of environmental variables, the geographical distance between records, and the identity of WWF ecoregions within which they occur. "Ecological similarity" equals the predicted proportional overlap in species composition between any given pair of locations (grid cells) - i.e. the mean proportion of species occurring at one of the locations that would be expected to also occur at the other location (in the absence of habitat degradation at both locations).
|Abiotic Environmental Surfaces||Min Monthly Min Temperature|
|Max Monthly Max Temperature|
|Max Diurnal Temperature Range|
|Min Monthly Water Deficit|
|Max Monthly Water Deficit|
|Soil Clay Proportion|
|Soil Silt Proportion|
|Soil Bulk Density|
|Topographic Wetlands Index|
|Global Occurrence Records for Terrestrial Species||Amphibians, Birds, Mammals||Map of Life|
|Vascular plants, Reptiles, Ants, Bees, Beetles, Bugs, Butterflies, Centipedes, Dragonflies, Flies, Grasshoppers, Millipedes, Snails, Moths, Spiders, Termites, Wasps||Global Biodiversity Information Facility (GBIF)|
Use of the GDM modelling approach to the turnover of biodiversity provides a more nuanced perspective on representativeness than a simple areal approach (e.g. the proportion of an ecoregion covered by reserves). This allows several key aspects of biodiversity to be considered. A region may have no protected areas, but some of its species may be protected by reserves in other regions. Conversely, a region with a high proportion of protected areas may have large parts of the ranges of those species in unprotected areas.
Protected areas are often sited in terrain unsuitable for development, so flatter lowland ecosystems may be disproportionately impacted, and steeper upland systems disproportionately protected. The interaction of these factors (which are not considered in a simple areal approach) in the Protected Area Representativeness Index means that the proportional representation values of the two metrics are not directly comparable. As a rule of thumb the Protected Area Representativeness Index will give a lower score than the areal approach for regions with medium to high areal protection and a higher score than the areal approach for regions with very low areal protection.
More information and further resources are available in the indicator factsheet here.
Allnutt, T.F., Ferrier, S., Manion, G., Powell, G.V.N., Ricketts, T.H., Fisher, B.L., Harper, G.J., Kremen, C., Labat, J., Lees, D.C., Pearce, T.A., Irwin, M.E. and Rakotondrainibe, F. (2008). Quantifying biodiversity loss in Madagascar from a 50-year record of deforestation. Conservation Letters, 1, 173-181.
Buckland, S. T., Magurran, a E., Green, R. E., Fewster, R. M. (2005). Monitoring change in biodiversity through composite indices. Philosophical Transaction: Biological Sciences, 360(1454), 243-254.
Ferrier, S., Powell, G. V. N., Richardson, K., Manion, G., Overton, J. M., Allnutt, T. F., Cameron, S.E., Mantle, K., Burgess, N.D., Faith, D.P., Lamoreux, J.F., Kier, G., Hijmans, R.J.,
Funk, V.A., Cassis, G.A., Fisher, B.L., Flemons, P., Lees, D., Lovett, J.C., van Rompaey, R. S. A. R. (2004). Mapping More of Terrestrial Biodiversity for Global Conservation Assessment. BioScience, 54(12), 1101-1109.
Ferrier, S., Manion, G., Elith, J. and Richardson, K. (2007) Using generalised dissimilarity modelling to analyse and predict patterns of beta-diversity in regional biodiversity assessment. Diversity and Distributions, 13, 252-264.
UNEP-WCMC (2016). World Database on Protected Areas User Manual 1.3. UNEP-WCMC: Cambridge, UK. Available at: http://wcmc.io/WDPA_Manual
Williams, K.J., Harwood, T.D., Ferrier, S. (2016). Assessing the ecological representativeness of Australia's terrestrial National Reserve System: A community-level modelling approach. Publication Number EP163634. CSIRO Land and Water, Canberra, Australia. https://publications.csiro.au/rpr/pub?pid=csiro:EP163634.