Statistical ecology comes of age
Author(s) -
Olivier Giménez,
S. T. Buckland,
Byron J. T. Morgan,
Nicolas Bez,
Sophie Bertrand,
Rémi Choquet,
Stéphane Dray,
MariePierre Étienne,
Rachel M. Fewster,
Frédéric Gosselin,
Bastien Mérigot,
Pascal Monestiez,
Juan M. Morales,
Frédéric Mortier,
François Munoz,
Otso Ovaskainen,
Sandrine Pavoine,
Roger Pradel,
Frank M. Schurr,
Len Thomas,
Wilfried Thuiller,
Verena M. Trenkel,
Perry de Valpine,
Eric A. Rexstad
Publication year - 2014
Publication title -
biology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.596
H-Index - 110
eISSN - 1744-957X
pISSN - 1744-9561
DOI - 10.1098/rsbl.2014.0698
Subject(s) - ecology , population ecology , theoretical ecology , biology , statistical model , process (computing) , population , computer science , artificial intelligence , sociology , demography , operating system
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.
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