Statistical ecology comes of age

Olivier Gimenez, Stephen Terrence Buckland, Byron J. T. Morgan, Nicolas Bez, Sophie Bertrand, Remi Choquet, Stephane Dray, Marie-Pierre Etienne, Rachel Fewster, Frederic Gosselin, Bastien Merigot, Pascal Monestiez, Juan M. Morales, Frederic Mortier, Francois Munoz, Otso Ovaskainen, Sandrine Pavoine, Roger Pradel, Frank M. Schurr, Len ThomasWilfried Thuiller, Verena Trenkel, Perry de Valpine, Eric Rexstad

Research output: Contribution to journalArticlepeer-review

25 Citations (Scopus)
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Abstract

The desire to predict the consequences of global environmental change has
been the driver towards more realistic models embracing the variability and
uncertainties inherent in ecology. Statistical ecology has gelled over the past
decade as a discipline that moves away from describing patterns towards
modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1 –4 July 2014) in
Montpellier, France, we analyse current trends in statistical ecology. Important
advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the
increasing use of hierarchical and hidden process models. Exciting research
perspectives include the development of methods to interpret citizen science
data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data.
Original languageEnglish
Article number20140698
Number of pages4
JournalBiology Letters
Volume10
DOIs
Publication statusPublished - 24 Dec 2014

Keywords

  • Citizen science
  • Hidden Markov model
  • Hierarchical model
  • Movement ecology
  • Software package

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