FN Archimer Export Format
PT J
TI A HMM-based model to geolocate pelagic fish from high-resolution individual temperature and depth histories: European sea bass as a case study
BT 
AF WOILLEZ, Mathieu
   FABLET, Ronan
   LALIRE, Maxime
   LAZURE, Pascal
   DE PONTUAL, Helene
AS 1:1;2:2;3:1,3;4:1,4;5:5;6:1;
FF 1:PDG-RBE-STH-LBH;2:;3:;4:;5:PDG-ODE-LOPS-OC;6:PDG-RBE-STH-LBH;
C1 IFREMER, Sci & Technol Halieut, CS 10070, F-29280 Plouzane, France.
   Inst Telecom Telecom Bretagne, LabSTICC, UMR 6285, CS 83818, F-29238 Brest 3, France.
   Univ Strasbourg, ICube, UMR 7357, BP 10413, F-67412 Illkirch Graffenstaden, France.
   CLS, Space Oceanog Div, 8-10 Rue Hermes, F-31520 Ramonville St Agne, France.
   IFREMER, Lab Phys Hydrodynam & Sedimentaire, CS 10070, F-29280 Plouzane, France.
C2 IFREMER, FRANCE
   TELECOM BRETAGNE, FRANCE
   UNIV STRASBOURG, FRANCE
   CLS, FRANCE
   IFREMER, FRANCE
SI BREST
SE PDG-RBE-STH-LBH
   PDG-ODE-LOPS-OC
UM LOPS
IN WOS Ifremer jusqu'en 2018
   copubli-france
   copubli-univ-france
IF 2.363
TC 25
UR https://archimer.ifremer.fr/doc/00300/41097/40270.pdf
LA English
DT Article
DE ;Fish movement;Archival tagging;Migration;Population structure;Hidden Markov Model (HMM);State-space model
AB Numerous methods have been developed to geolocate fish from data storage tags. Whereas demersal species have been tracked using tide-driven geolocation models, pelagic species which undertake extensive migrations have been mainly tracked using light-based models. Here, we present a new HMM-based model that infers pelagic fish positions from the sole use of high-resolution temperature and depth histories. A key contribution of our framework lies in model parameter inference (diffusion coefficient and noise parameters with respect to the reference geophysical fields—satellite SST and temperatures derived from the MARS3D hydrodynamic model), which improves model robustness. As a case study, we consider long time series of data storage tags (DSTs) deployed on European sea bass for which individual migration tracks are reconstructed for the first time. We performed a sensitivity analysis on synthetic and real data in order to assess the robustness of the reconstructed tracks with respect to model parameters, chosen reference geophysical fields and the knowledge of fish recapture position. Model assumptions and future directions are discussed. Finally, our model opens new avenues for the reconstruction and analysis of migratory patterns of many other pelagic species in relatively contrasted geophysical environments
PY 2016
PD FEB
SO Ecological Modelling
SN 0304-3800
PU Elsevier Science Bv
VL 321
UT 000368866600002
BP 10
EP 22
DI 10.1016/j.ecolmodel.2015.10.024
ID 41097
ER

EF