Uncertainty Analysis for Regional‐Scale Reserve Selection

Uncertainty Analysis for Regional‐Scale Reserve Selection Abstract: Methods for reserve selection and conservation planning often ignore uncertainty. For example, presence‐absence observations and predictions of habitat models are used as inputs but commonly assumed to be without error. We applied information‐gap decision theory to develop uncertainty analysis methods for reserve selection. Our proposed method seeks a solution that is robust in achieving a given conservation target, despite uncertainty in the data. We maximized robustness in reserve selection through a novel method, “distribution discounting,” in which the site‐ and species‐specific measure of conservation value (related to species‐specific occupancy probabilities) was penalized by an error measure (in our study, related to accuracy of statistical prediction). Because distribution discounting can be implemented as a modification of input files, it is a computationally efficient solution for implementing uncertainty analysis into reserve selection. Thus, the method is particularly useful for high‐dimensional decision problems characteristic of regional conservation assessment. We implemented distribution discounting in the zonation reserve‐selection algorithm that produces a hierarchy of conservation priorities throughout the landscape. We applied it to reserve selection for seven priority fauna in a landscape in New South Wales, Australia. The distribution discounting method can be easily adapted for use with different kinds of data (e.g., probability of occurrence or abundance) and different landscape descriptions (grid or patch based) and incorporated into other reserve‐selection algorithms and software. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Conservation Biology Wiley

Uncertainty Analysis for Regional‐Scale Reserve Selection

Loading next page...
 
/lp/wiley/uncertainty-analysis-for-regional-scale-reserve-selection-8bRYajWcaN
Publisher
Wiley
Copyright
Copyright © 2006 Wiley Subscription Services, Inc., A Wiley Company
ISSN
0888-8892
eISSN
1523-1739
D.O.I.
10.1111/j.1523-1739.2006.00560.x
Publisher site
See Article on Publisher Site

Abstract

Abstract: Methods for reserve selection and conservation planning often ignore uncertainty. For example, presence‐absence observations and predictions of habitat models are used as inputs but commonly assumed to be without error. We applied information‐gap decision theory to develop uncertainty analysis methods for reserve selection. Our proposed method seeks a solution that is robust in achieving a given conservation target, despite uncertainty in the data. We maximized robustness in reserve selection through a novel method, “distribution discounting,” in which the site‐ and species‐specific measure of conservation value (related to species‐specific occupancy probabilities) was penalized by an error measure (in our study, related to accuracy of statistical prediction). Because distribution discounting can be implemented as a modification of input files, it is a computationally efficient solution for implementing uncertainty analysis into reserve selection. Thus, the method is particularly useful for high‐dimensional decision problems characteristic of regional conservation assessment. We implemented distribution discounting in the zonation reserve‐selection algorithm that produces a hierarchy of conservation priorities throughout the landscape. We applied it to reserve selection for seven priority fauna in a landscape in New South Wales, Australia. The distribution discounting method can be easily adapted for use with different kinds of data (e.g., probability of occurrence or abundance) and different landscape descriptions (grid or patch based) and incorporated into other reserve‐selection algorithms and software.

Journal

Conservation BiologyWiley

Published: Dec 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