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dc.contributor.authorGimenez, Olivier
dc.contributor.authorBuckland, Stephen Terrence
dc.contributor.authorMorgan, Byron J. T.
dc.contributor.authorBez, Nicolas
dc.contributor.authorBertrand, Sophie
dc.contributor.authorChoquet, Remi
dc.contributor.authorDray, Stephane
dc.contributor.authorEtienne, Marie-Pierre
dc.contributor.authorFewster, Rachel
dc.contributor.authorGosselin, Frederic
dc.contributor.authorMerigot, Bastien
dc.contributor.authorMonestiez, Pascal
dc.contributor.authorMorales, Juan M.
dc.contributor.authorMortier, Frederic
dc.contributor.authorMunoz, Francois
dc.contributor.authorOvaskainen, Otso
dc.contributor.authorPavoine, Sandrine
dc.contributor.authorPradel, Roger
dc.contributor.authorSchurr, Frank M.
dc.contributor.authorThomas, Len
dc.contributor.authorThuiller, Wilfried
dc.contributor.authorTrenkel, Verena
dc.contributor.authorde Valpine, Perry
dc.contributor.authorRexstad, Eric
dc.date.accessioned2015-02-20T14:31:01Z
dc.date.available2015-02-20T14:31:01Z
dc.date.issued2014-12-24
dc.identifier169367761
dc.identifier829aea79-6e6a-4d4d-97d0-ac76dfed26e8
dc.identifier84953641166
dc.identifier000361337600002
dc.identifier.citationGimenez , O , Buckland , S T , Morgan , B J T , Bez , N , Bertrand , S , Choquet , R , Dray , S , Etienne , M-P , Fewster , R , Gosselin , F , Merigot , B , Monestiez , P , Morales , J M , Mortier , F , Munoz , F , Ovaskainen , O , Pavoine , S , Pradel , R , Schurr , F M , Thomas , L , Thuiller , W , Trenkel , V , de Valpine , P & Rexstad , E 2014 , ' Statistical ecology comes of age ' , Biology Letters , vol. 10 , 20140698 . https://doi.org/10.1098/rsbl.2014.0698en
dc.identifier.issn1744-9561
dc.identifier.otherORCID: /0000-0002-7436-067X/work/29591676
dc.identifier.otherORCID: /0000-0002-4323-8161/work/29574861
dc.identifier.otherORCID: /0000-0002-9939-709X/work/73701018
dc.identifier.urihttps://hdl.handle.net/10023/6128
dc.description.abstractThe 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.
dc.format.extent4
dc.format.extent283824
dc.language.isoeng
dc.relation.ispartofBiology Lettersen
dc.subjectCitizen scienceen
dc.subjectHidden Markov modelen
dc.subjectHierarchical modelen
dc.subjectMovement ecologyen
dc.subjectSoftware packageen
dc.subjectGE Environmental Sciencesen
dc.subjectQA Mathematicsen
dc.subject.lccGEen
dc.subject.lccQAen
dc.titleStatistical ecology comes of ageen
dc.typeJournal articleen
dc.contributor.sponsorEPSRCen
dc.contributor.institutionUniversity of St Andrews. School of Mathematics and Statisticsen
dc.contributor.institutionUniversity of St Andrews. Marine Alliance for Science & Technology Scotlanden
dc.contributor.institutionUniversity of St Andrews. Scottish Oceans Instituteen
dc.contributor.institutionUniversity of St Andrews. St Andrews Sustainability Instituteen
dc.contributor.institutionUniversity of St Andrews. Centre for Research into Ecological & Environmental Modellingen
dc.contributor.institutionUniversity of St Andrews. Statisticsen
dc.identifier.doi10.1098/rsbl.2014.0698
dc.description.statusPeer revieweden
dc.identifier.grantnumberEP/I000917/1en


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