Product Description
by James Thorson (Author), Kasper Kristensen (Author)
Ecological dynamics are tremendously complicated and are studied at a variety of spatial and temporal scales. Ecologists often simplify analysis by describing changes in density of individuals across a landscape, and statistical methods are advancing rapidly for studying spatio-temporal dynamics. However, spatio-temporal statistics is often presented using a set of principles that may seem very distant from ecological theory or practice. This book seeks to introduce 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. We provide a step-by-step illustration of techniques that combine core spatial-analysis packages in R with low-level computation using Template Model Builder. Techniques are showcased using real-world data from varied ecological systems, providing a toolset for hierarchical modelling of spatio-temporal processes. Spatio-Temporal Models for Ecologists is meant for graduate level students, alongside applied and academic ecologists.
Key Features:
- Foundational ecological principles and analyses
- Thoughtful and thorough ecological examples
- Analyses conducted using a minimal toolbox and fast computation
- Code using R and TMB included in the book and available online
Author Biography
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.
