**2.1 Agent based modelling (ABM)**

As described above the movement of an oil spill particle model mainly governed by the underlying hydrodynamics, wind forcing and weathering process. The seabird movement is the outcome of a complex agent-based model (ABM) describing the movement, feeding and internal states based on a set of input factors (forcing) and sub-models as outlined in **Figure 1** and **Table 1**. The model template used is the CBIRD ABM module in DHI's MIKE ABM Lab framework [4].

One of the main challenges related to agent-based modelling of the behaviour of individual sea-birds is to strike a balance between realistic parameterisation and heuristic representativeness of the model.

The CBIRD ABM model is described in detail in [5]. The description is repeated in brief below. It largely follows the ODD protocol for describing individual- and agent-based models [6, 7]. The ODD protocol consists of seven elements: the first three elements (purpose, entities, overview) provide an overview, the fourth element (design concepts) explains general concepts underlying the model's design, and the remaining three elements (calibration, parameterisation, validation) provide details.

*Combining Predicted Seabird Movements and Oil Drift Using Lagrangian Agent-Based Model… DOI: http://dx.doi.org/10.5772/intechopen.106956*

#### **Figure 1.**

*Conceptual diagram of the various parameters/sub-modules affecting movement mode decisions in the envisioned seabird ABM. Green box variables denote Eulerian spatiotemporal model forcings, while blue boxes indicate Lagrangian variables/processes. Red arrows indicate two-way feedback mechanisms.*


#### **Table 1.** *Overview of CBIRD modules.*

The purpose of the CBIRD model is to predict the dynamic spatiotemporal distribution of seabirds like the Common Guillemot in the Barents Sea by combining several individual movement and feeding behaviours as a function of explicitly modelled bioenergetics with the included effect of physical environmental forcings, such as ocean currents, wind drag, habitat suitability and ice cover.

The model tracks the horizontal position and internal state of individual seabird agents (the Lagrangian entity) inside the spatially explicit model domain. Each agent represents multiple individuals and can thus be considered a 'super-individual' [8]. The memory of previously visited habitat locations (x, y coordinates) is stored as attributes of the entity, while the strength of the habitat memory is described by a reference memory (dimensionless) to the previously visited habitat versus a satiation memory (dimensionless) relating to the perceived habitat utility (dimensionless) of staying in the current habitat. The time attribute, time since the last food encounter (minutes), controls the magnitude of swimming activity of migrating birds relative to drag forces imposed on agents by wind and currents.

All model calculations of state variables and updates of environmental forcings occur at a discrete time step over the simulation period. At the beginning of each model time step, the following sequential order is applied:

