000			02673nam a2200289ui 4500
001			UK0418913967
003			OSt
008			100705s2010 uk a f 001 0 eng d
020			_a978-0-521-70002-3
040			_aUCA-CYT _cUCA
100	1		_aFranklin, Janet
245	1	0	_aMapping species distributions : _bspatial inference and prediction / _cJanet Franklin ; with contributions by Jennifer A. Miller
260			_aCambridge : _bCambridge University Press, _c2009
300			_aXVIII, 320 p. : _bil. ; _c24 cm
490	0	0	_aEcology, biodiversity and conservation
520			_aMaps of species' distributions or habitat suitability are required for many aspects of environmental research, resource management and conservation planning. These include biodiversity assessment, reserve design, habitat management and restoration, species and habitat conservation plans and predicting the effects of environmental change on species and ecosystems. The proliferation of methods and uncertainty regarding their effectiveness can be daunting to researchers, resource managers and conservation planners alike. Franklin summarises the methods used in species distribution modeling (also called niche modeling) and presents a framework for spatial prediction of species distributions based on the attributes (space, time, scale) of the data and questions being asked. The framework links theoretical ecological models of species distributions to spatial data on species and environment, and statistical models used for spatial prediction. Providing practical guidelines to students, researchers and practitioners in a broad range of environmental sciences including ecology, geography, conservation biology, and natural resources management.
520			_aÍndice: Part I. History and Ecological Basis of Species' Distribution Modeling: 1. Species distribution modeling; 2. Why do we need species' distribution models?; 3. Ecological understanding of species' distributions; Part II. The Data Needed for Modeling Species' Distributions; 4. Data for species' distribution models: the biological data; 5. Data for species' distribution models: the environmental data; Part III. An Overview of the Modeling Methods: 6. Statistical models - modern regression; 7. Machine learning methods; 8. Classification, similarity and other methods for presence-only data; Part IV. Model Evalua... Etc.
650	0	4	_aEcología _94229
650	0	4	_aBiodiversidad _94228
650	0	4	_aBiodiversidad _xConservación _911506
650	0	4	_aEcosistemas. _913177
909			_bcyt _c-
942			_n0
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