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Identifying landscape species for ecological planning
- Source :
- Ecological Indicators. 99:140-148
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- The global extent of habitat degradation and accelerated rate of diversity loss requires conservation managers to quickly develop conservation plans within political, financial and time constraints. Despite the important role of surrogate species for structuring site-based conservation, these species have often been selected using unsupervised approaches. We aimed to incorporate the strengths of several surrogate species approaches within a new single species selection framework in order to select a suite of ecologically and culturally suitable landscape species as a complement to the network of current protected areas (PAs) for conservation of central Iranian deserts. Using carnivores, we utilised multiple decision making criteria, combining decision making trial and evaluation laboratory (DEMATEL) with analytic network process (ANP) methods, to rank the most important criteria in selecting landscape species. We then applied weighted criteria, ecological niche modelling, experts’ information, and attitudes of local communities to score ten candidate species based on the thirteen criteria. Finally we identified a suite of complementary landscape species for ecological planning of the landscape. This framework is as an effective approach for selecting landscape species especially in habitats where there are few data on candidate species.
- Subjects :
- 0106 biological sciences
Ecological niche
Ecology
business.industry
Analytic network process
Suite
Environmental resource management
General Decision Sciences
010501 environmental sciences
010603 evolutionary biology
01 natural sciences
Structuring
Habitat destruction
Geography
Habitat
Ecological planning
business
Ecology, Evolution, Behavior and Systematics
Selection (genetic algorithm)
0105 earth and related environmental sciences
Subjects
Details
- ISSN :
- 1470160X
- Volume :
- 99
- Database :
- OpenAIRE
- Journal :
- Ecological Indicators
- Accession number :
- edsair.doi...........e202f841fefce73cb8171d9bf49d8b25
- Full Text :
- https://doi.org/10.1016/j.ecolind.2018.12.010