Beth Gardner – författare
1 233 kr
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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 an�R package.
Comprehensive reference on revolutionary new methods in ecology makes this the first and only book on the topic Every methodological element has a detailed worked example with a code template, allowing you to learn by example Includes an R package that contains all computer code and data sets on companion website1 206 kr
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1 073 kr
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1 379 kr
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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 spacein 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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