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Large ungulates in tropical forests are among the most threatened
taxa of mammals. Excessive hunting, degradation of and
encroachments on their natural habitats by humans have contributed
to drastic reductions in wild ungulate populations in recent
decades. As such, reliable assessments of ungulate-habitat
relationships and the spatial dynamics of their populations are
urgently needed to provide a scientific basis for conservation
efforts. However, such rigorous assessments are methodologically
complex and logistically difficult, and consequently many commonly
used ungulate population survey methods do not address key
problems. As a result of such deficiencies, key parameters related
to population distribution, abundance, habitat ecology and
management of tropical forest ungulates remain poorly understood.
This book addresses this critical knowledge gap by examining how
population abundance patterns in five threatened species of large
ungulates vary across space in the tropical forests of the
Nagarahole-Bandipur reserves in southwestern India. It also
explains the development and application of an innovative
methodology - spatially explicit line transect sampling - based on
an advanced hierarchical modelling under the Bayesian inferential
framework, which overcomes common methodological deficiencies in
current ungulate surveys. The methods and results presented provide
valuable reference material for researchers and professionals
involved in studying and managing wild ungulate populations around
the globe.
"Spatial Capture-Recapture" provides a comprehensive how-to
manual with detailed examples of spatial capture-recapture models
based on current technology and knowledge. "Spatial
Capture-Recapture" provides you with an extensive step-by-step
analysis of many data sets using different software
implementations. The authors' approach is practical it embraces
Bayesian and classical inference strategies to give the reader
different options to get the job done. In addition, "Spatial
Capture-Recapture" provides data sets, sample code and computing
scripts in anR package.
Comprehensive reference on revolutionary new methods in ecology
makes this the first and only book on the topicEvery methodological
element has a detailed worked example with a code template,
allowing you to learn by exampleIncludes an R package that contains
all computer code and data sets on companion website"
Large ungulates in tropical forests are among the most threatened
taxa of mammals. Excessive hunting, degradation of and
encroachments on their natural habitats by humans have contributed
to drastic reductions in wild ungulate populations in recent
decades. As such, reliable assessments of ungulate-habitat
relationships and the spatial dynamics of their populations are
urgently needed to provide a scientific basis for conservation
efforts. However, such rigorous assessments are methodologically
complex and logistically difficult, and consequently many commonly
used ungulate population survey methods do not address key
problems. As a result of such deficiencies, key parameters related
to population distribution, abundance, habitat ecology and
management of tropical forest ungulates remain poorly understood.
This book addresses this critical knowledge gap by examining how
population abundance patterns in five threatened species of large
ungulates vary across space in the tropical forests of the
Nagarahole-Bandipur reserves in southwestern India. It also
explains the development and application of an innovative
methodology - spatially explicit line transect sampling - based on
an advanced hierarchical modelling under the Bayesian inferential
framework, which overcomes common methodological deficiencies in
current ungulate surveys. The methods and results presented provide
valuable reference material for researchers and professionals
involved in studying and managing wild ungulate populations around
the globe.
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