Complementarity analysis: Mapping the performance of surrogates for biodiversity

Complementarity analysis: Mapping the performance of surrogates for biodiversity Efficient planning for biodiversity conservation requires a consideration of complementarity when assessing the value of adding new areas for management. Unfortunately, complementarity in biodiversity across all groups cannot usually be measured directly, so methods are needed to choose good surrogates (or ‘indicators’) for predicting this overall complementarity. Previous attempts at assessment of biological surrogates have measured dissimilarity among biotas, or congruence between sets of selected areas, or species representation within a set of selected areas, all of which can seriously misrepresent the strength of a surrogate relationship across all areas. Therefore, we propose a new approach to complementarity analysis. We show that the pattern of complementarity among all biotas can be assessed in terms of the frequency of false high and false low predictions by the surrogates. We also show how the spatial pattern in these false predictions can be mapped and discuss their usefulness. On the one hand, areas on these maps associated with many false high predictions are overvalued and would be an inefficient investment for scarce conservation resources. On the other hand, areas associated with many false low predictions are undervalued and unlikely to attract conservation action, so we need to know whether they are particularly likely to be highly threatened. These geographical patterns can be used to identify habitat-associated biases in the performance of surrogate groups. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Biological Conservation Elsevier

Complementarity analysis: Mapping the performance of surrogates for biodiversity

Loading next page...
 
/lp/elsevier/complementarity-analysis-mapping-the-performance-of-surrogates-for-1miamLimte
Publisher
Elsevier
Copyright
Copyright © 2005 Elsevier Ltd
ISSN
0006-3207
D.O.I.
10.1016/j.biocon.2005.09.047
Publisher site
See Article on Publisher Site

Abstract

Efficient planning for biodiversity conservation requires a consideration of complementarity when assessing the value of adding new areas for management. Unfortunately, complementarity in biodiversity across all groups cannot usually be measured directly, so methods are needed to choose good surrogates (or ‘indicators’) for predicting this overall complementarity. Previous attempts at assessment of biological surrogates have measured dissimilarity among biotas, or congruence between sets of selected areas, or species representation within a set of selected areas, all of which can seriously misrepresent the strength of a surrogate relationship across all areas. Therefore, we propose a new approach to complementarity analysis. We show that the pattern of complementarity among all biotas can be assessed in terms of the frequency of false high and false low predictions by the surrogates. We also show how the spatial pattern in these false predictions can be mapped and discuss their usefulness. On the one hand, areas on these maps associated with many false high predictions are overvalued and would be an inefficient investment for scarce conservation resources. On the other hand, areas associated with many false low predictions are undervalued and unlikely to attract conservation action, so we need to know whether they are particularly likely to be highly threatened. These geographical patterns can be used to identify habitat-associated biases in the performance of surrogate groups.

Journal

Biological ConservationElsevier

Published: Mar 1, 2006

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create folders to
organize your research

Export folders, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off