Statistical ecology comes of age

Gimenez, Olivier, Buckland, Stephen T., Morgan, Byron J. T., Bertrand, Sophie, Choquet, Rémi, Dray, Stéphane, Etienne, Marie-Pierre, Fewster, Rachel, Gosselin, Frédéric, Mérigot, Bastien, and others. (2014) Statistical ecology comes of age. Biology Letters, 10 (11). ISSN 1744-9561. (doi:10.1098/rsbl.2014.0698) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:48965)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL: http://dx.doi.org/10.1098/rsbl.2014.0698

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. Impor-

tant 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. Stat-

istical ecology has come of age: it now provides a general and mathematically

rigorous framework linking ecological theory and empirical data.

Item Type:	Article
DOI/Identification number:	10.1098/rsbl.2014.0698
Subjects:	Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics Q Science > QH Natural history > QH541 Ecology
Divisions:	Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User:	Byron Morgan
Date Deposited:	09 Jun 2015 13:09 UTC
Last Modified:	17 Aug 2022 10:58 UTC
Resource URI:	https://kar.kent.ac.uk/id/eprint/48965 (The current URI for this page, for reference purposes)

Depositors only (login required):

Altmetric