FN Archimer Export Format
PT J
TI Statistical ecology comes of age
BT 
AF GIMENEZ, Olivier
   BUCKLAND, Stephen T.
   MORGAN, Byron J. T.
   BEZ, Nicolas
   BERTRAND, Sophie
   CHOQUET, Remi
   DRAY, Stephane
   ETIENNE, Marie-Pierre
   FEWSTER, Rachel
   GOSSELIN, Frederic
   MERIGOT, Bastien
   MONESTIEZ, Pascal
   MORALES, Juan M.
   MORTIER, Frederic
   MUNOZ, Francois
   OVASKAINEN, Otso
   PAVOINE, Sandrine
   PRADEL, Roger
   SCHURR, Frank M.
   THOMAS, Len
   THUILLER, Wilfried
   TRENKEL, Verena
   DE VALPINE, Perry
   REXSTAD, Eric
AS 1:1;2:2;3:3;4:4;5:4;6:1;7:5,6,7;8:8;9:9;10:10;11:11;12:12;13:13;14:14;15:15;16:16;17:17,18;18:1;19:19;20:2;21:20;22:21;23:22;24:2;
FF 1:;2:;3:;4:;5:;6:;7:;8:;9:;10:;11:;12:;13:;14:;15:;16:;17:;18:;19:;20:;21:;22:PDG-RBE-EMH;23:;24:;
C1 Univ Montpellier 3, CNRS, CEFE UMR 5175, EPHE, F-34293 Montpellier 5, France.
   Univ St Andrews, Ctr Res Ecol & Environm Modelling, St Andrews KY16 9LZ, Fife, Scotland.
   Univ Kent, Sch Math Stat & Actuarial Sci, Canterbury CT2 7NF, Kent, England.
   IRD, UMR EME 212, Sete, France.
   Univ Lyon, F-69000 Lyon, France.
   Univ Lyon 1, F-69622 Villeurbanne, France.
   CNRS, UMR5558, Lab Biometrie & Biol Evolut 18, F-69622 Villeurbanne, France.
   AgroParisTech, UMR MIA 518, Paris, France.
   Univ Auckland, Dept Stat, Auckland 1, New Zealand.
   Irstea, UR EFNO, Ctr Nogent Sur Vernisson, F-45290 Nogent Sur Marne, France.
   Univ Montpellier 2, UMR EME 212, Sete, France.
   INRA, BioSP, Avignon, France.
   Consejo Nacl Invest Cient & Tecn, INIBIOMA, CRUB, Lab Ecotono, San Carlos De Bariloche, Rio Negro, Argentina.
   CIRAD, UPR Bsef, Montpellier, France.
   UMR AMAP, UM2, F-34398 Montpellier 5, France.
   Univ Helsinki, Dept Biosci, Helsinki, Finland.
   Museum Natl Hist Nat, Ctr Ecol & Conservat Sci, UMR CNRS UPMC 7204, F-75005 Paris, France.
   Univ Oxford, Dept Zool, Math Ecol Res Grp, Oxford OX1 3PS, England.
   Univ Hohenheim, Inst Landscape & Plant Ecol, D-70593 Stuttgart, Germany.
   Univ Grenoble 1, UMR CNRS 5553, Lab Ecol Alpine, F-38041 Grenoble 9, France.
   IFREMER, F-44311 Nantes 3, France.
   Univ Calif Berkeley, Environm Sci Policy & Management, Berkeley, CA 94720 USA.
C2 UNIV MONTPELLIER, FRANCE
   UNIV ST ANDREWS, UK
   UNIV KENT, UK
   IRD, FRANCE
   UNIV LYON, FRANCE
   UNIV LYON, FRANCE
   CNRS, FRANCE
   AGROPARISTECH, FRANCE
   UNIV AUCKLAND, NEW ZEALAND
   IRSTEA, FRANCE
   UNIV MONTPELLIER, FRANCE
   INRA, FRANCE
   CONSEJO NACL INVEST CIENT & TECN, ARGENTINA
   CIRAD, FRANCE
   UNIV MONTPELLIER, FRANCE
   UNIV HELSINKI, FINLAND
   MNHN, FRANCE
   UNIV OXFORD, UK
   UNIV HOHENHEIM, GERMANY
   UNIV GRENOBLE, FRANCE
   IFREMER, FRANCE
   UNIV CALIF BERKELEY, USA
SI NANTES
SE PDG-RBE-EMH
IN WOS Ifremer jusqu'en 2018
   copubli-france
   copubli-p187
   copubli-europe
   copubli-univ-france
   copubli-int-hors-europe
   copubli-sud
IF 3.248
TC 35
UR https://archimer.ifremer.fr/doc/00249/36026/35298.pdf
LA English
DT Article
DE ;citizen science;hidden Markov model;hierarchical model;movement ecology;software package;spatially explicit capture-recapture;species distribution modelling;state-space model
AB 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.
PY 2014
PD DEC
SO Biology Letters
SN 1744-9561
PU Royal Soc
VL 10
IS 12
UT 000361337600002
DI 10.1098/rsbl.2014.0698
ID 36026
ER

EF