Table 1.

Schematic summary of the characteristics of the modelling approaches considered, which may assist in identifying the appropriate modelling approach for a specific research problem (see also Fig. 2).

	Simple analytical models (SAM)	Game-theoretic models (GT)	Dynamic optimisation models (SDP)	Individual-based models (incl. Physical transport models) (IBM, PTM)	Evolutionary programming models (EP)
Model questions typically aim at …	explaining general migration patterns, incl. differences between species or populations	explaining (coexistence of) behavioural strategies in groups	identifying optimal (individual) behaviours	explaining & predicting individual behaviour and interactions and resulting population dynamics	explaining & predicting individual behaviour and interactions and resulting population dynamics, additionally includes “evolutionary” selection of optimal behavioural decisions
Parameter richness & complexity*	low	low	medium	medium - high	high
Representation of space (environment)	implicit, simple	none or implicit	explicit, static & simple	explicit, dynamic & detailed	explicit, dynamic & detailed
Temporal dynamics considered?	no	no	yes	yes	yes
Basic organismal unit	any	any	individual	individual	individual
Characterisation of organismal units by	a limited set of variables	their strategy	a set of state variables	a set of state variables	a set of state variables
Behavioural repertoire (migration in context of annual routine or other life-history activities)	restricted; usually looks at specific aspects of migration only	restricted; but includes migration and one or few other competing activities	restricted; typically includes movement & foraging, can detect knock-on effects	rich; can include movement, foraging, reproduction, territory acquisition and many more activities	rich; can include movement, foraging, reproduction, territory acquisition and many more activities
Fundamental tenet	specific currency is optimized, e.g. time, energy or predation-risk	behaviour of specific player depends on behaviour of all others	evolution has shaped behaviour such that it maximises fitness	emergent properties arise from behaviour & interaction of individuals	evolution of individual behaviour towards optimality
Population dynamics	no	no	implicit	explicit; many levels of detail possible	explicit; many levels of detail possible
Empirical data required for model parameterisation	few but possibly challenging parameters	cost & pay-offs of behavioural alternatives	costs of activities, expected fitness as dependent on state variables	set of rules for behaviour of individuals and their energetic consequences	in addition to parameters of “usual” IBM, selection criteria for evolutionary modeling process required
Empirical data required for scrutinizing model predictions	general migration patterns	strategies in populations/ subgroups	individual migration routes & schedules, constraints of activities	individual migration routes & schedules, other population level patterns, e.g. spatial distributions	individual migration routes & schedules, other population level patterns, e.g. spatial distributions

^*This includes the number of parameters and the level of detail with which processes are considered but is also inversely related to the ease with which model output can be understood, interpreted and scrutinized.