Oecologia

, 167:599

A primer for data assimilation with ecological models using Markov Chain Monte Carlo (MCMC)

  • J. M. Zobitz
  • A. R. Desai
  • D. J. P. Moore
  • M. A. Chadwick
Concepts, Reviews and Syntheses

DOI: 10.1007/s00442-011-2107-9

Cite this article as:
Zobitz, J.M., Desai, A.R., Moore, D.J.P. et al. Oecologia (2011) 167: 599. doi:10.1007/s00442-011-2107-9

Abstract

Data assimilation, or the fusion of a mathematical model with ecological data, is rapidly expanding knowledge of ecological systems across multiple spatial and temporal scales. As the amount of ecological data available to a broader audience increases, quantitative proficiency with data assimilation tools and techniques will be an essential skill for ecological analysis in this data-rich era. We provide a data assimilation primer for the novice user by (1) reviewing data assimilation terminology and methodology, (2) showcasing a variety of data assimilation studies across the ecological, environmental, and atmospheric sciences with the aim of gaining an understanding of potential applications of data assimilation, and (3) applying data assimilation in specific ecological examples to determine the components of net ecosystem carbon uptake in a forest and also the population dynamics of the mayfly (Hexagenia limbata, Serville). The review and examples are then used to provide guiding principles to newly proficient data assimilation practitioners.

Keywords

Data assimilation Markov Chain Monte Carlo NEE Aquatic insects Ecological models 

Supplementary material

442_2011_2107_MOESM1_ESM.pdf (526 kb)
Supplementary material 1 (PDF 287 kb)

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • J. M. Zobitz
    • 1
  • A. R. Desai
    • 2
  • D. J. P. Moore
    • 3
    • 4
  • M. A. Chadwick
    • 3
  1. 1.Department of MathematicsAugsburg CollegeMinneapolisUSA
  2. 2.Department of Atmospheric and Oceanic SciencesUniversity of Wisconsin-MadisonMadisonUSA
  3. 3.Department of GeographyKing’s College LondonLondonUK
  4. 4.School of Natural Resources and EnvironmentUniversity of ArizonaTucsonUSA