An individual-based model of skipjack tuna (Katsuwonus pelamis) movement in the tropical Pacific ocean
Authored by Patrick Lehodey, Sebille Erik van, Joe Scutt Phillips, Gupta Alex Sen, Inna Senina, Michael Lange, John Hampton, Simon Nicol
Date Published: 2018
DOI: 10.1016/j.pocean.2018.04.007
Sponsors:
European Union
European Research Council (ERC)
Australian Research Council (ARC)
United Kingdom Engineering and Physical Sciences Research Council (EPSRC)
Platforms:
No platforms listed
Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
Model code not found
Abstract
The distribution of marine species is often modeled using Eulerian
approaches, in which changes to population density or abundance are
calculated at fixed locations in space. Conversely, Lagrangian, or
individual-based, models simulate the movement of individual particles
moving in continuous space, with broader-scale patterns such as
distribution being an emergent property of many, potentially adaptive,
individuals. These models offer advantages in examining dynamics across
spatiotemporal scales and making comparisons with observations from
individual-scale data.
Here, we introduce and describe such a model, the Individual-based
Kinesis, Advection and Movement of Ocean ANimAls model (Ikamoana), which
we use to replicate the movement processes of an existing Eulerian model
for marine predators (the Spatial Ecosystem and Population Dynamics
Model, SEAPODYM). Ikamoana simulates the movement of either individual
or groups of animals by physical ocean currents, habitat-dependent
stochastic movements (kinesis), and taxis movements representing active
searching behaviours.
Applying our model to Pacific skipjack tuna (Katsuwonus pelamis), we
show that it accurately replicates the evolution of density distribution
simulated by SEAPODYM with low time-mean error and a spatial correlation
of density that exceeds 0.96 at all times. We demonstrate how the
Lagrangian approach permits easy tracking of individuals' trajectories
for examining connectivity between different regions, and show how the
model can provide independent estimates of transfer rates between
commonly used assessment regions. In particular, we find that retention
rates in most assessment regions are considerably smaller (up to a
factor of 2) than those estimated by this population of skipjack's
primary assessment model. Moreover, these rates are sensitive to ocean
state (e.g. El Nino vs La Nina) and so assuming fixed transfer rates
between regions may lead to spurious stock estimates. A novel feature of
the Lagrangian approach is that individual schools can be tracked
through time, and we demonstrate that movement between two assessment
regions at broad temporal scales includes extended transits through
other regions at finer-scales.
Finally, we discuss the utility of this modeling framework for the
management of marine reserves, designing effective monitoring
programmes, and exploring hypotheses regarding the behaviour of
hard-to-observe oceanic animals.
Tags
behavior
Animal behavior
population
Ecosystem
fisheries
Dynamics model
Tracking
Indian-ocean
Western
Yellowfin tuna
Thunnus-obesus
Hidden markov-models
Advection-diffusion
Genetic-analysis
Western
pacific
Yellowfin
tuna