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Modeling Demographic Processes in Marked Populations

Editat de David L Thomson, Evan G Cooch, Michael J Conroy
en Limba Engleză Hardback – 2 dec 2008

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Specificații

ISBN-13: 9780387781501
ISBN-10: 0387781501
Pagini: 1132
Ilustrații: XXIV, 1132 p.
Dimensiuni: 157 x 234 x 56 mm
Greutate: 1.7 kg
Ediția:2009 edition
Editura: Springer Us
Locul publicării:New York, NY, United States

Public țintă

Research

Cuprins

Population Dynamics – Growth, Density-Dependence and Decomposing ?.- Evolutionary Ecology.- Abundance Estimation – Direct Methods, Proxies, Occupancy Models and Point Count Data.- Dispersal, Movement and Migration – Methods and Multi-State Models.- Wildlife and Conservation Management.- Combing Sources of Information – Kalman Filters, Matrix Methods and Joint Likelihoods.- Bayesian Applications - Advances, Random Effects and Hierarchical Models.- The Robust Design – Sampling, Applications and Advances.- State Uncertainty – Assignmant Error and Unobservable States.- New Software Developments for Modeling Demographic Processes.- Open Forum.

Textul de pe ultima copertă

Much of biology can be understood in terms of demography. It is the demographic processes of birth and death which govern rates of population growth and the rates at which gene frequencies change. The analysis of demographic processes in free-living organisms is, however, far from simple. Scientists from diverse fields in biology and statistics have united to address the challenges by developing mark-recapture methods and other approaches. Progress has been rapid, and this volume represents a snapshot of the emerging field. It has eleven sections in total, covering the most important biological and statistical frontiers, new software developments, and an open forum. It covers the latest approaches in modeling population dynamics, evolutionary ecology and wildlife biology. It addresses issues in the estimation of abundance and movement, and it covers new statistical approaches in the combination of information, Bayesian statistics, Robust Designs and the modeling of state-uncertainty.

Caracteristici

Brings together the latest and best work in this rapidly developing field Provides a cohesive overview of current best-practice and provides stimulus and impetus to the development of the field over the coming years Principal software developments of the last three years are presented