2024-03-28T12:42:20Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/1865422020-09-25T01:14:48Zcom_10261_88com_10261_8com_10261_63617col_10261_341col_10261_63619
00925njm 22002777a 4500
dc
Aspillaga, Eneko
author
Safi, Kamran
author
Hereu, Bernat
author
Bartumeus, Frederic
author
2019-09
1. Passive acoustic telemetry provides the opportunity to monitor and contextualize
the movements of diverse aquatic animals. Despite depth being an essential
dimension along which many processes are organized, the Eulerian structure of
the acoustic telemetry data (movements perceived from fixed locations) and the
consequences of sound propagation in water hinders the incorporation of the vertical
dimension into animal’s space use analyses.
2. Here, we propose a new data‐driven quantitative method to estimate 3D space use
from telemetry networks. The methodology is based on simulating large numbers of
stochastic synthetic paths, accommodating the detection probability around receivers
and the depth information from transmitters and integrating the local topography.
3. The methodological protocol is explained in detail and tested with acoustic telemetry
data from the common dentex Dentex dentex in a Mediterranean marine
protected area. We present 3D space use estimations for the tagged individuals
and compare them with other 3D and 2D estimations derived with existing probabilistic
methods.
4. 3D space use estimations that incorporate topography provided a more comprehensive
view of the movement ecology of tracked individuals, with relevant pieces
being missed by 2D representations. Our method generated realistic representations
of the actual spatial co‐occurrence of individuals, including the spatio‐temporal
identification of relevant aggregation areas.
Methods in Ecology and Evolution 10(9): 1551-1557 (2019)
http://hdl.handle.net/10261/186542
2041-210X
Acoustic telemetry
Utilization distribution
3D
Aquatic ecology
Movement ecology
Space use
Telemetry networks
Topography
Modelling the three‐dimensional space use of aquatic animals combining topography and Eulerian telemetry data