Environmental diversity: on the best-possible use of surrogate data for assessing the relative biodiversity of sets of areas

The conservation goal of representation of biodiversity (in the broad sense of all species) in protected areas requires best-possible use of available surrogate information. One standard approach is based on ‘indicator’ groups of taxa. A minimum set of areas having at least one representation of each indicator species is taken to be representative of other organisms. This same minimum-set approach is adapted to other ‘attributes’ of biodiversity, for example, derived environmental clusters. A weakness of these approaches is that useful information is lost; for example, for environmental clusters, there is no distinction made either among or within clusters. A more powerful surrogate approach can use some expression of environmental and/or biotic pattern so that variation among areas is seen as part of a continuum rather than partitioned into arbitrary clusters/attributes. The challenge in using pattern effectively is to adopt a robust model for the relationship between pattern and the underlying units of biodiversity, i.e. species. An environmental space (a continuum or ordination pattern), combined with the standard ecological continuum model relating species to environmental space, has advantages over other patterns based on hierarchy or distance matrices. Because an environmental space can be estimated either directly (observed environmental data) or indirectly (data on indicator groups), the corresponding surrogate-measure of biodiversity, ‘environmental diversity’ (ED) makes best-possible use of either kind of data. We conclude that the arbitrariness of the ‘attribute’ approach can be replaced by a robust surrogate ‘pattern’ approach that is flexible and avoids unwarranted assumptions.

[1]  D. Faith,et al.  Compositional dissimilarity as a robust measure of ecological distance , 1987, Vegetatio.

[2]  R. G. Wright,et al.  GAP ANALYSIS: A GEOGRAPHIC APPROACH TO PROTECTION OF BIOLOGICAL DIVERSITY , 1993 .

[3]  M. Brandeau,et al.  An overview of representative problems in location research , 1989 .

[4]  Lee Belbin Comparing two sets of community data: A method for testing reserve adequacy , 1992 .

[5]  P. A. Walker,et al.  DIVERSITY: a software package for sampling phylogenetic and environmental diversity. Reference and user's guide. v. 2.1. , 1994 .

[6]  R L Pressey,et al.  Beyond opportunism: Key principles for systematic reserve selection. , 1993, Trends in ecology & evolution.

[7]  David A. Keith,et al.  A new approach for selecting fully representative reserve networks: addressing efficiency, reserve design and land suitability with an iterative analysis , 1992 .

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

[9]  Ian J. Kitching,et al.  Cladistics: A Practical Course in Systematics , 1992 .

[10]  Claire Kremen,et al.  Assessing the Indicator Properties of Species Assemblages for Natural Areas Monitoring. , 1992, Ecological applications : a publication of the Ecological Society of America.

[11]  G. Orians,et al.  Endangered at What Level? , 1993, Ecological applications : a publication of the Ecological Society of America.

[12]  E. Erkut The discrete p-dispersion problem , 1990 .

[13]  D. P. Faith,et al.  Integrating conservation and development: effective trade-offs between biodiversity and cost in the selection of protected areas , 1996, Biodiversity & Conservation.

[14]  Daniel P. Faith,et al.  Correlation of environmental variables with patterns of distribution and abundance of common and rare freshwater macroinvertebrates , 1989 .

[15]  H. J. B. Birks,et al.  Assessing the representativeness of nature reserves using multivariate analysis: Vascular plants and breeding birds in deciduous forests, western Norway , 1993 .

[16]  Hugh G. Gauch,et al.  Multivariate analysis in community ecology , 1984 .

[17]  A. O. Nicholls,et al.  An upgraded reserve selection algorithm , 1993 .

[18]  Robert L. Pressey,et al.  Level of geographical subdivision and its effects on assessments of reserve coverage: a review of regional studies , 1994 .

[19]  D P Faith,et al.  Phylogenetic pattern and the quantification of organismal biodiversity. , 1994, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[20]  C. Margules,et al.  Conservation evaluation in practice , 1986 .

[21]  Timothy J. Lowe,et al.  Location on Networks: A Survey. Part I: The p-Center and p-Median Problems , 1983 .

[22]  John B. Taggart,et al.  Ordination as an aid in determining priorities for plant community protection , 1994 .

[23]  D. P. Faith,et al.  Integrating conservation and development: incorporating vulnerability into biodiversity-assessment of areas , 1996, Biodiversity & Conservation.

[24]  A. Solow,et al.  On the measurement of biological diversity , 1993 .

[25]  George O. Wesolowsky,et al.  FACILITIES LOCATION: MODELS AND METHODS , 1988 .

[26]  Robert K. Colwell,et al.  Estimating terrestrial biodiversity through extrapolation. , 1994, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[27]  Lee Belbin,et al.  Environmental representativeness: Regional partitioning and reserve selection , 1993 .

[28]  G. W. Milligan,et al.  A Comparison of Two Approaches to Beta-Flexible Clustering. , 1992, Multivariate behavioral research.

[29]  Robert L. Pressey,et al.  Land classifications are necessary for conservation planning but what do they tell us about fauna , 1994 .

[30]  Gabriel Y. Handler,et al.  The continuous m-center problem on a network , 1985, Networks.

[31]  Daniel P. Faith,et al.  Compositional dissimilarity as a robust measure of ecological distance , 1987, Vegetatio.

[32]  G. Park,et al.  Gradient Analysis in Nature Reserve Design: A New Zealand Example , 1988 .

[33]  D. Faith Conservation evaluation and phylogenetic diversity , 1992 .

[34]  Gordon Taylor,et al.  Discussion of the implications of the report on Biological Conservation of the South East Forests , 1990 .