Spatio-Temporal Models for Ecologists

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.

About the author

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.

Summary

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.

Product details

• Authors: James Kristensen Thorson, James Thorson, Kasper Kristensen
• Publisher: Taylor & Francis Ltd.
• Content: Book
• Product form: Hardback
• Publication date: 27.02.2024
• Subject: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematica
• EAN: 9781032531014
• ISBN: 978-1-0-3253101-4
• Pages: 276
• Series: Chapman & Hall/CRC Applied Environmental Statistics
• Subjects: SCIENCE / Life Sciences / Ecology, MATHEMATICS / Probability & Statistics / General, SCIENCE / Earth Sciences / Geology, Ecological science, the Biosphere, Probability & statistics, Geochemistry, Probability and statistics, State-space estimation, Ecological forecasting, R statistical computing, advanced spatio-temporal ecological methods, habitat selection analysis, animal population modelling, community diversity metrics