Dynamic Reserve Selection: Optimal Land Retention with Land-Price Feedbacks

Urban growth compromises open space and ecosystem functions. To mitigate the negative effects, some agencies use reserve selection models to identify conservation sites for purchase or retention. Existing models assume that conservation has no impact on nearby land prices. We propose a new integer p...

Full description

Saved in:
Bibliographic Details
Published inOperations research Vol. 59; no. 5; pp. 1059 - 1078
Main Authors Tóth, Sándor F., Haight, Robert G., Rogers, Luke W.
Format Journal Article
LanguageEnglish
Published Hanover, MD INFORMS 01.09.2011
Institute for Operations Research and the Management Sciences
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Urban growth compromises open space and ecosystem functions. To mitigate the negative effects, some agencies use reserve selection models to identify conservation sites for purchase or retention. Existing models assume that conservation has no impact on nearby land prices. We propose a new integer program that relaxes this assumption via adaptive cost coefficients. Our model accounts for the two key land price feedbacks that arise in markets where conservation competes with development: the amenity premium and price increases driven by shifts in market equilibriums. We illustrate the mechanics of the proposed model in a real land retention context. The results suggest that in competitive land markets, the optimal conservation strategy during the initial phase of the retention effort might be to use available dollars to buy fewer parcels with smaller total area that are under high risk of development. We show that failure to capture the land-price feedbacks can lead to significant losses in biological conservation. The present study is the first to create a reserve selection model that captures the economic theory of competitive land markets in a dynamic framework, produces tangible, parcel-level conservation recommendations, and works on problems with thousands of potential site selection decisions and several planning periods.
ISSN:0030-364X
1526-5463
DOI:10.1287/opre.1110.0961