Wildlife corridors as a connected subgraph problem

Wildlife corridors connect areas of biological significance to mitigate the negative ecological impacts of habitat fragmentation. In this article we formalize the optimal corridor design as a connected subgraph problem, which maximizes the amount of suitable habitat in a fully connected parcel netwo...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of environmental economics and management Jg. 63; H. 1; S. 1 - 18
Hauptverfasser: Conrad, Jon M., Gomes, Carla P., van Hoeve, Willem-Jan, Sabharwal, Ashish, Suter, Jordan F.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Elsevier Inc 2012
Elsevier Science Publishing Company, Inc
Schlagworte:
Algorithms
Bears
biological corridors
Computation
Computational methods
Computational sustainability
Corridors
Ecological analysis
Economics
environmental impact
Environmental management
Graph algorithms
Grizzly bears
Habitat fragmentation
Habitats
Integer programming
Mixed integer programming
Network analysis
Optimization
Parcels
Rocky Mountain region
Segmentation
Social networks
Studies
U.S.A
United States
Ursus arctos
Wildlife
Wildlife conservation
Wildlife corridors
Wildlife management
United States > US
United States
Rocky Mountain region
USA
Habitat fragmentation
Mixed integer programming
Wildlife corridors
Computational sustainability
Optimization
ISSN:0095-0696, 1096-0449
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Wildlife corridors connect areas of biological significance to mitigate the negative ecological impacts of habitat fragmentation. In this article we formalize the optimal corridor design as a connected subgraph problem, which maximizes the amount of suitable habitat in a fully connected parcel network linking core habitat areas, subject to a constraint on the funds available for land acquisition. To solve this challenging computational problem, we propose a hybrid approach that combines graph algorithms with Mixed Integer Programming-based optimization. We apply this technique to the design of corridors for grizzly bears in the U.S. Northern Rockies, illustrating the underlying computational complexities by varying the granularity of the parcels available for acquisition. The approach that is introduced is general and can be applied to other species or other similar problems, such as those occurring in social networks.
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-1
ObjectType-Feature-2
content type line 23
ObjectType-Article-2
ISSN:0095-0696
1096-0449
DOI:10.1016/j.jeem.2011.08.001