This book introduces a minimal set of principles and numerical techniques for spatio-temporal statistics that can be used to implement a wide range of real-world ecological analyses regarding animal movement, population dynamics, community composition, causal attribution, and spatial dynamics.
This book introduces a minimal set of principles and numerical techniques for spatio-temporal statistics that can be used to implement a wide range of real-world ecological analyses regarding animal movement, population dynamics, community composition, causal attribution, and spatial dynamics.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
James Thorson is a statistical ecologist at the Alaska Fisheries Science Center within the National Marine Fisheries Service. His research interests include population dynamics, life-history theory, and methods for the sustainable management of natural resources. He has taught graduate-level courses in hierarchical modelling and spatio-temporal statistics at University of Washington. Kasper Kristensen is a Senior Researcher at Danish Technical University. His research interests include spatio-temporal statistics and computational methods. He developed the R-package TMB, which is seeing increased use throughout ecology. For example, TMB is the computational backend for R-package glmmTMB, which has been cited over 3000 times from 2017-2022.
Inhaltsangabe
Part 1: Introductory 1. Statistical models for individual-based processes 2. Hierarchical models and Laplace approximation Part 2: Basic 3. Population dynamics and state-space models 4. Individual movement 5. Spatial models 6. Spatial sampling designs and analysis 7. Covariates affecting densities and detectability Part 3: Advanced 8. Spatio-temporal models with seasonal or multi-year dynamics 9. Ecological teleconnections 10. Population movement and habitat selection 11. Multispecies models for community diversity and biogeography 12. A decadal forecast for spatio-temporal models A. Acknowledgements B. Appendices
Part 1: Introductory 1. Statistical models for individual-based processes 2. Hierarchical models and Laplace approximation Part 2: Basic 3. Population dynamics and state-space models 4. Individual movement 5. Spatial models 6. Spatial sampling designs and analysis 7. Covariates affecting densities and detectability Part 3: Advanced 8. Spatio-temporal models with seasonal or multi-year dynamics 9. Ecological teleconnections 10. Population movement and habitat selection 11. Multispecies models for community diversity and biogeography 12. A decadal forecast for spatio-temporal models A. Acknowledgements B. Appendices
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