FN Archimer Export Format
PT J
TI Metrics for describing dyadic movement: a review
BT 
AF JOO, Rocio
   ETIENNE, Marie-Pierre
   BEZ, Nicolas
   MAHEVAS, Stephanie
AS 1:1,2;2:3;3:4;4:2;
FF 1:;2:;3:;4:PDG-RBE-EMH;
C1 Univ Florida, Dept Wildlife Ecol & Conservat, Ft Lauderdale Res & Educ Ctr, 3205 Coll Ave, Davie, FL 33314 USA.
   Ecol & Modeles Halieut, IFREMER, BP 21105, F-44311 Nantes 03, France.
   Univ Rennes, CNRS, Agrocampus Ouest, IRMAR,UMR 6625, F-35000 Rennes, France.
   Univ Montpellier, CNRS, MARBEC, IRD,Ifremer, Sete, France.
C2 UNIV FLORIDA, USA
   IFREMER, FRANCE
   UNIV RENNES, FRANCE
   IRD, FRANCE
SI NANTES
SE PDG-RBE-EMH
UM MARBEC
IN WOS Ifremer jusqu'en 2018
   DOAJ
   copubli-france
   copubli-p187
   copubli-univ-france
   copubli-int-hors-europe
IF 3.745
TC 18
UR https://archimer.ifremer.fr/doc/00475/58657/61156.pdf
   https://archimer.ifremer.fr/doc/00475/58657/61157.pdf
   https://archimer.ifremer.fr/doc/00475/58657/61158.pdf
   https://archimer.ifremer.fr/doc/00475/58657/61159.pdf
   https://archimer.ifremer.fr/doc/00475/58657/61160.pdf
   https://archimer.ifremer.fr/doc/00475/58657/61161.pdf
   https://archimer.ifremer.fr/doc/00475/58657/61162.pdf
   https://archimer.ifremer.fr/doc/00475/58657/61163.pdf
   https://archimer.ifremer.fr/doc/00475/58657/61164.pdf
LA English
DT Article
DE ;Collective behaviour;Dyadic movement;Indices;Movement ecology;Spatio-temporal dynamics;Trajectories
AB In movement ecology, the few works that have taken collective behaviour into account are data-driven and rely on simplistic theoretical assumptions, relying in metrics that may or may not be measuring what is intended. In the present paper, we focus on pairwise joint-movement behaviour, where individuals move together during at least a segment of their path. We investigate the adequacy of twelve metrics introduced in previous works for assessing joint movement by analysing their theoretical properties and confronting them with contrasting case scenarios. Two criteria are taken into account for review of those metrics: 1) practical use, and 2) dependence on parameters and underlying assumptions. When analysing the similarities between the metrics as defined, we show how some of them can be expressed using general mathematical forms. In addition, we evaluate the ability of each metric to assess specific aspects of joint-movement behaviour: proximity (closeness in space-time) and coordination (synchrony) in direction and speed. We found that some metrics are better suited to assess proximity and others are more sensitive to coordination. To help readers choose metrics, we elaborate a graphical representation of the metrics in the coordination and proximity space based on our results, and give a few examples of proximity and coordination focus in different movement studies. 
PY 2018
PD DEC
SO Movement Ecology
SN 2051-3933
PU Bmc
VL 6
IS 26
UT 000454431900001
DI 10.1186/s40462-018-0144-2
ID 58657
ER

EF