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Mapping species distributions : spatial inference and prediction / Janet Franklin ; with contributions by Jennifer A. Miller.

By: Contributor(s): Material type: TextTextSeries: Ecology, biodiversity and conservationPublication details: Cambridge ; New York : Cambridge University Press, 2009.Description: xviii, 320 p. : ill., maps (some col.) ; 24 cmISBN:
  • 9780521876353 (cased)
  • 0521876354 (cased)
  • 9780521700023 (pbk.)
  • 0521700027 (pbk.)
Subject(s): DDC classification:
  • 578.09 22
LOC classification:
  • QH84 .F73 2009
Contents:
PART I. HISTORY AND ECOLOGICAL BASIS OF SPECIES DISTRIBUTION MODELING: Species distribution modeling -- Why do we need species' distribution models? -- Ecological understanding of species' distributions -- PART II. THE DATA NEEDED FOR MODELING SPECIES DISTRIBUTIONS: Data for species' distribution models: the biological data -- Data for species' distribution models: the environmental data -- PART III. AN OVERVIEW OF THE MODELING METHODS: Statistical models - modern regression -- Machine learning methods -- Classification, similarity and other methods for presence-only data -- PART IV. MODEL EVALUATION AND IMPLEMENTATION: Model evaluation -- Implementation of species' distribution models.
Scope and content: "Maps 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." --NHBS Environment Bookstore.
Holdings
Item type Current library Collection Call number Status Date due Barcode
Book Book Research Library Stacks Non-fiction QH84 .F73 2009 (Browse shelf(Opens below)) Available 14662

Includes bibliographical references and index.

PART I. HISTORY AND ECOLOGICAL BASIS OF SPECIES DISTRIBUTION MODELING: Species distribution modeling -- Why do we need species' distribution models? -- Ecological understanding of species' distributions -- PART II. THE DATA NEEDED FOR MODELING SPECIES DISTRIBUTIONS: Data for species' distribution models: the biological data -- Data for species' distribution models: the environmental data -- PART III. AN OVERVIEW OF THE MODELING METHODS: Statistical models - modern regression -- Machine learning methods -- Classification, similarity and other methods for presence-only data -- PART IV. MODEL EVALUATION AND IMPLEMENTATION: Model evaluation -- Implementation of species' distribution models.

"Maps 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." --NHBS Environment Bookstore.

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