Reduced survey intensity and its consequences for marine reserve selection

There has been much interest in the potential of short-cuts in biodiversity surveys (e.g. physical surrogates, indicator groups, and lower taxonomic resolution) in systematic processes to select networks of representative marine reserves. This study tested the consequences for reserve selection of reducing survey intensity in intertidal rocky shores in southeast Australia. Using a reference data set of species' distributions based on surveys of two replicate sites in each of 15 locations, a reduction in survey intensity was simulated by randomly eliminating the data from one of the replicate sites in each location. A complementarity-based reserve selection algorithm was used to determine the number of locations required to represent all species once in a reserve network and the irreplaceability value of locations. A reduction in survey intensity led to increases in: the size of reserve networks (of between 8 and 17%); the irreplaceability value of locations; and the number of irreplaceable locations. These changes were caused by a reduction in the observed range sizes of species in the data sets simulating a reduced survey intensity.

[1]  M. Chapman,et al.  Spatial analyses of intertidal assemblages on sheltered rocky shores , 1998 .

[2]  R. Pressey,et al.  Effectiveness of using vascular plants to select reserves for bryophytes and lichens , 2000 .

[3]  A. O. Nicholls,et al.  SELECTING MARINE RESERVES USING HABITATS AND SPECIES ASSEMBLAGES AS SURROGATES FOR BIOLOGICAL DIVERSITY , 1999 .

[4]  Georgina M. Mace,et al.  Threatened Status, Rarity, and Diversity as Alternative Selection Measures for Protected Areas: A Test Using Afrotropical Antelopes , 1995 .

[5]  W. Gladstone,et al.  Sustainable use of renewable resources and conservation in the Red Sea and Gulf of Aden: issues, needs and strategic actions , 1999 .

[6]  Simon Ferrier,et al.  A new predictor of the irreplaceability of areas for achieving a conservation goal, its application to real-world planning, and a research agenda for further refinement , 2000 .

[7]  Mansell,et al.  Biodiversity assessment and conservation strategies , 1998, Science.

[8]  S. Sarkar,et al.  Systematic conservation planning , 2000, Nature.

[9]  A. V. van Jaarsveld,et al.  Sensitivity of selection procedures for priority conservation areas to survey extent, survey intensity and taxonomic knowledge , 1998, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[10]  K. McGuinness Explaining patterns in abundances of organisms on boulders: the failure of 'natural experiments' , 1988 .

[11]  Randall T Ryti,et al.  Effect of the Focal Taxon on the Selection of Nature Reserves. , 1992, Ecological applications : a publication of the Ecological Society of America.

[12]  Hugh P. Possingham,et al.  Effects of data characteristics on the results of reserve selection algorithms , 1999 .

[13]  A. Balmford,et al.  Using higher-taxon richness as a surrogate for species richness: II. Local applications , 1996, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[14]  T. Ward,et al.  Use of assemblages derived from different taxonomic levels to select areas for conserving marine biodiversity , 1998 .

[15]  K. Wessels,et al.  The use of land facets as biodiversity surrogates during reserve selection at a local scale , 1999 .

[16]  P. Archambault,et al.  Scales of coastal heterogeneity and benthic intertidal species richness, diversity and abundance , 1996 .

[17]  A. Balmford,et al.  Testing the higher-taxon approach to conservation planning in a megadiverse group: the macrofungi. , 2000 .

[18]  Hugh M. Caffey,et al.  No effect of naturally-occurring rock types on settlement or survival in the intertidal barnacle, Tesseropora rosea (Krauss) , 1982 .

[19]  G. Quinn,et al.  Geographic variation in interactions between size classes of the limpet Cellana tramoserica , 1997 .

[20]  Amanda T. Lombard,et al.  Reserve systems for limestone endemic flora of the Cape Lowland Fynbos: Iterative versus linear programming , 1996 .

[21]  Kevin J. Gaston,et al.  How large do reserve networks need to be , 2001 .

[22]  Manuela M. P. Huso,et al.  A comparison of reserve selection algorithms using data on terrestrial vertebrates in Oregon , 1997 .

[23]  A. V. Jaarsveld,et al.  Complementarity as a biodiversity indicator strategy , 2000, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[24]  M. Chapman,et al.  Variation in algal assemblages on wave-exposed rocky shores in New South Wales , 1998 .

[25]  Andrew Balmford,et al.  Complementarity and the use of indicator groups for reserve selection in Uganda , 1998, Nature.

[26]  Graeme Kelleher,et al.  A Global representative system of marine protected areas , 1995 .

[27]  A. O. Nicholls,et al.  Selecting networks of reserves to maximise biological diversity , 1988 .

[28]  A. Magurran Ecological Diversity and Its Measurement , 1988, Springer Netherlands.

[29]  W. Gladstone The potential value of indicator groups in the selection of marine reserves , 2002 .

[30]  K. Astles Patterns of abundance and distribution of species in intertidal rock pools , 1993, Journal of the Marine Biological Association of the United Kingdom.

[31]  R. L. Pressey,et al.  Reserve selection in the Succulent Karoo, South Africa: coping with high compositional turnover , 1999, Plant Ecology.

[32]  I. R. Johnson,et al.  Shades of irreplaceability: towards a measure of the contribution of sites to a reservation goal , 1994, Biodiversity & Conservation.

[33]  J. Travis,et al.  Flexibility and the use of indicator taxa in the selection of sites for nature reserves , 2001, Biodiversity & Conservation.

[34]  T. O’hara Consistency of faunal and floral assemblages within temperate subtidal rocky reef habitats , 2001 .