Using individual based models to understand blue whale migration – published today from Steph Dodson!

A GRIP fellow from our group, Dr. Steph Dodson has published her work with us in Ecological modeling today, titled “Disentangling the biotic and abiotic drivers of emergent migratory behavior using individual-based models.” Using published info on blue whale movement and fine scale models of krill distribution, Steph was able to test whether an IBM could recreate observed movement timing and extent. Interested in more, please read below!

Figure 2Fig. 2. (a) Model algorithm in pictorial form. The acronym ARS stands for area restricted search. (b) Behavioral states for each model. Arrows indicate possible transitions. (c) Step length and turning angle distributions for all transiting and foraging states. These distributions have been scaled from Bailey et al. (2009) to account for the 6 h time step used in the IBM. A turning angle of 0 corresponds to straight in all behavioral states except of the north-south model, where instead 0 is due south.

Dodson, B. Abrahms, S.J. Bograd, J. Fiechter, and E.L. Hazen. 2020. Disentangling the biotic and abiotic drivers of emergent migratory behavior using individual-based models. Ecological Modeling. DOI: 10.1016/j.ecolmodel.2020.109225.


Understanding the drivers of movement, migration and distribution of individuals is important for insight into how species will respond to changing environmental conditions. Both abiotic and biotic factors are thought to influence migratory behavior, but their relative roles are difficult to disentangle. For migratory marine predators, both temperature and prey availability have been shown to be significant predictors of space use, though often researchers rely on physical proxies due to the lack of data on dynamic prey fields. We generated spatially explicit individual-based movement models to evaluate the relative roles of abiotic (sea surface temperature; SST) and biotic (prey availability) factors in driving blue whale (Balaenoptera musculus) movement decisions and migratory behavior in the eastern North Pacific. Using output from a lower trophic ecosystem model coupled with a regional ocean circulation model, we parameterized a blue whale movement model that explicitly incorporates prey fields in addition to physical proxies. A model using both SST and prey data reproduced blue whale foraging behavior including realistic timing of latitudinal migrations. SST- and prey-only population models demonstrated important independent effects of each variable. In particular, the SST-only model revealed that warm temperatures limited krill foraging opportunities but failed to drive seasonal foraging patterns, whereas the prey-only model revealed more realistic seasonal and interannual differences in foraging behavior. Our individual-based movement model helps elucidate the mechanisms underlying migration and demonstrates how fine-scale individual decision-making can lead to emergent migratory behavior at the population level. Moreover, determining the relative effects of the physical environment and prey availability on the movement decisions of threatened species is critical to understand how they may respond to changing ocean conditions.

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