A probabilistic cellular automata approach for predator-prey interactions of arrowtooth flounder (Atheresthes stomias) and walleye pollock (Theragra chalcogramma) in the eastern Bering Sea
Authored by Kun Chen, Kung-Sik Chan, Kevin M Bailey, Kerim Aydin, Lorenzo Ciannelli
Date Published: 2012
DOI: 10.1139/f2011-160
Sponsors:
Oceans and Human Health Initiative (NOAA)
United States National Science Foundation (NSF)
Platforms:
No platforms listed
Model Documentation:
Other Narrative
Flow charts
Mathematical description
Model Code URLs:
Model code not found
Abstract
We developed a hybrid cellular automata (CA) modelling approach to
explore the dynamics of a key predator-prey interaction in a marine
system; our study is motivated by the quest for better understanding of
the scale and heterogeneity-related effects on the arrowtooth flounder
(Atheresthes stomias) and walleye pollock (Theragra chalcogramma)
dynamics during the summer feeding season in the eastern Bering Sea
(EBS), but can be readily extended to other systems. The spatially
explicit and probabilistic CA model incorporates individual behaviours
and strategies and local interactions among species, as well as spatial
and temporal heterogeneity due to geographical and (or) environmental
changes in the physical environment. The model is hybridized, with an
individual-based model (IBM) approach for increasing its capacity and
continuum and for balancing between computational efficiency and model
validity, which makes it suitable for simulating predator-prey dynamics
in a large, complex ecological environment. We focus on the functional
and aggregative responses of predators to prey density at different
spatial scales, the effects of individual behaviours, and the impacts of
systematic heterogeneity. Simulations from the model with suitable
parameter values share qualitatively similar features found in field
observations, e. g., local aggregations around hydrographical features.
Spatial heterogeneity is an important aspect of whether local-scale
functional and aggregative responses reflect those operating over large, or global, scales.
Tags
systems
Recruitment
Population-dynamics
Temperature
Functional-response
Scaling-up
Single-species models