Uncovering ecological state dynamics with hidden Markov models

Brett T. McClintock, Roland Langrock, Olivier Gimenez, Emmanuelle Cam, David L. Borchers, Richard Glennie, Toby A. Patterson

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)
2 Downloads (Pure)

Abstract

Ecological systems can often be characterised by changes among a finite set of underlying states pertaining to individuals, populations, communities or entire ecosystems through time. Owing to the inherent difficulty of empirical field studies, ecological state dynamics operating at any level of this hierarchy can often be unobservable or ?hidden?. Ecologists must therefore often contend with incomplete or indirect observations that are somehow related to these underlying processes. By formally disentangling state and observation processes based on simple yet powerful mathematical properties that can be used to describe many ecological phenomena, hidden Markov models (HMMs) can facilitate inferences about complex system state dynamics that might otherwise be intractable. However, HMMs have only recently begun to gain traction within the broader ecological community. We provide a gentle introduction to HMMs, establish some common terminology, review the immense scope of HMMs for applied ecological research and provide a tutorial on implementation and interpretation. By illustrating how practitioners can use a simple conceptual template to customise HMMs for their specific systems of interest, revealing methodological links between existing applications, and highlighting some practical considerations and limitations of these approaches, our goal is to help establish HMMs as a fundamental inferential tool for ecologists.
Original languageEnglish
Number of pages26
JournalEcology Letters
VolumeEarly View
Early online date19 Oct 2020
DOIs
Publication statusPublished - 19 Oct 2020

Keywords

  • Behavioural ecology
  • community ecology
  • ecosystem ecology
  • hierarchical model
  • movement ecology
  • observation error
  • population ecology
  • state-space model
  • time series
  • INDIVIDUAL ANIMAL MOVEMENT
  • ESTIMATING POPULATION-SIZE
  • ESTIMATING SITE OCCUPANCY
  • CAPTURE-RECAPTURE MODELS
  • IMPERFECT DETECTION
  • REGIME SHIFTS
  • SPACE MODELS
  • TRANSITION-PROBABILITIES
  • METAPOPULATION DYNAMICS
  • DEMOGRAPHIC PARAMETERS

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