Rarity-weighted richness

A simple and reliable alternative to integer programming and heuristic algorithms for minimum set and maximum coverage problems in conservation planning

Fabio Albuquerque, Paul Beier

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

Here we report that prioritizing sites in order of rarity-weighted richness (RWR) is a simple, reliable way to identify sites that represent all species in the fewest number of sites (minimum set problem) or to identify sites that represent the largest number of species within a given number of sites (maximum coverage problem). We compared the number of species represented in sites prioritized by RWR to numbers of species represented in sites prioritized by the Zonation software package for 11 datasets in which the size of individual planning units (sites) ranged from <1 ha to 2,500 km2. On average, RWR solutions were more efficient than Zonation solutions. Integer programming remains the only guaranteed way find an optimal solution, and heuristic algorithms remain superior for conservation prioritizations that consider compactness and multiple near-optimal solutions in addition to species representation. But because RWR can be implemented easily and quickly in R or a spreadsheet, it is an attractive alternative to integer programming or heuristic algorithms in some conservation prioritization contexts.

Original languageEnglish (US)
Article numbere0119905
JournalPLoS One
Volume10
Issue number3
DOIs
StatePublished - Mar 17 2015

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prioritization
Integer programming
Heuristic algorithms
Conservation
planning
Planning
Spreadsheets
Software packages
Software
Heuristics
Datasets

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

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