Conservation planning and biodiversity: assembling the best data for the job

Pressey, R.L. (2004) Conservation planning and biodiversity: assembling the best data for the job. Conservation Biology, 18 (6). pp. 1677-1681.

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Abstract

Readers of the note by Brooks et al. (2004) will, I hope, be persuaded of the urgent need for more comprehensive data on species. It would be unfortunate, though, if readers formed the impression that biodiversity processes cannot be seriously considered by conservation planners because "Techniques for mapping and measuring ecological and evolutionary processes are in their infancy." More unfortunate would be the impression that "broad-scale biodiversity attributes" (Brooks et al. 2004), hereafter "land types" (such as vegetation units or land systems) are alternatives to data on species. Most conservation planners would agree with Brooks et al. that different biodiversity currencies have different advantages and problems. From that starting point, divergent courses can be plotted.

Brooks et al. recommend species data as a more promising option than relying on land types and call for an end to "armchair environmental classification." Others have taken a different course. Since the early 1990s, many regional conservation plans have been shaped by a mixture of biodiversity surrogates, selected from a list of potential types (Table 1) and assembled into composite data sets (Noss 1993; Davis et al. 1999; Groves et al. 2000; Cowling et al. 2003). The rationale is straightforward: all surrogates are limited idiosyncratically in their depictions of biodiversity pattern and process, so a more comprehensive array of surrogates gives a better picture.

Item ID: 10038
Item Type: Article (Refereed Research - C1)
ISSN: 1523-1739
Date Deposited: 15 Apr 2010 05:43
FoR Codes: 05 ENVIRONMENTAL SCIENCES > 0502 Environmental Science and Management > 050205 Environmental Management @ 100%
SEO Codes: 96 ENVIRONMENT > 9606 Environmental and Natural Resource Evaluation > 960605 Institutional Arrangements for Environmental Protection @ 100%
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