Collective decision strategies in the presence of spatio-temporal correlations

Winklmayr, Claudia; Kao, Albert B.; Bak-Coleman, Joseph; Romanczuk, Pawel

doi:10.1177/26339137221148675

Cited by 4 publications

(5 citation statements)

References 44 publications

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“…Social information enhances the range of nonlocal information, but the information acquired personally by information-sharing individuals is often highly correlated 66 . Such homogeneous personal information among individuals can limit the value of social information and the ability of groups to collectively sense broad-scale ecosystem gradients or changes 25 .…”

Section: Discussionmentioning

confidence: 99%

Long-distance communication can enable collective migration in a dynamic seascape

Dodson,

Oestreich,

Savoca

et al. 2024

Sci Rep

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Social information is predicted to enhance the quality of animals’ migratory decisions in dynamic ecosystems, but the relative benefits of social information in the long-range movements of marine megafauna are unknown. In particular, whether and how migrants use nonlocal information gained through social communication at the large spatial scale of oceanic ecosystems remains unclear. Here we test hypotheses about the cues underlying timing of blue whales’ breeding migration in the Northeast Pacific via individual-based models parameterized by empirical behavioral data. Comparing emergent patterns from individual-based models to individual and population-level empirical metrics of migration timing, we find that individual whales likely rely on both personal and social sources of information about forage availability in deciding when to depart from their vast and dynamic foraging habitat and initiate breeding migration. Empirical patterns of migratory phenology can only be reproduced by models in which individuals use long-distance social information about conspecifics’ behavioral state, which is known to be encoded in the patterning of their widely propagating songs. Further, social communication improves pre-migration seasonal foraging performance by over 60% relative to asocial movement mechanisms. Our results suggest that long-range communication enhances the perceptual ranges of migrating whales beyond that of any individual, resulting in increased foraging performance and more collective migration timing. These findings indicate the value of nonlocal social information in an oceanic migrant and suggest the importance of long-distance acoustic communication in the collective migration of wide-ranging marine megafauna.

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Section: Discussionmentioning

confidence: 99%

Long-distance communication can enable collective migration in a dynamic seascape

Dodson,

Oestreich,

Savoca

et al. 2024

Sci Rep

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show abstract

“…Social information enhances the range of nonlocal information, but the information acquired personally by information-sharing individuals is often highly-correlated (Winklmayr et al 2023). Such homogeneous personal information among individuals can limit the value of social information and the ability of groups to collectively sense broad-scale ecosystem gradients or changes (Kao & Couzin 2014).…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Long-distance communication can enable collective migration in a dynamic seascape

Dodson,

Oestreich,

Savoca

et al. 2023

Preprint

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Social information is predicted to enhance migratory performance, but the relative benefits of social information in the long-range movements of marine megafauna are unknown. In particular, whether and how migrants use nonlocal information gained through social communication at the extreme spatial scale of oceanic ecosystems remains unclear. Here we combine long-term acoustic recordings of foraging and migratory blue whales, oceanographic and prey data, and individual-based modeling to discern the cues underlying timing of blue whales’ breeding migration in the Northeast Pacific. We find that individual whales rely on both personal and social sources of information about forage availability in deciding when to depart from their vast and dynamic foraging habitat and initiate breeding migration. Empirical patterns of migratory phenology can only be reproduced by models in which individuals use long-distance social information about conspecifics’ behavioral state, which is known to be encoded in the patterning of their widely-propagating songs. Further, social communication improves pre-migration seasonal foraging performance by over 60% relative to asocial movement mechanisms. Our results suggest that long-range communication enhances the perceptual ranges of migrating whales beyond that of any individual, resulting in increased foraging performance. These findings indicate the value of nonlocal social information in an oceanic migrant and highlight the importance of long-distance acoustic communication in the collective migration of wide-ranging marine megafauna.

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“…Accordingly, equation ( 7) is the Hamiltonian of a system of spins in random local magnetic fields h i , equation (12). The fields are functions of random variables ω i that attain values {ω + , ω 0 , ω − } with given distribution functions, equation (6).…”

Section: Spins In a Social Field (Sf-model)mentioning

confidence: 99%

“…There have been significant advances in our understanding of collective decision making in recent decades, providing insights, for example, into the role of different interaction networks [10,11], correlated information [12] or agent heterogeneity [13]; however, many fundamental questions remain open. On the theoretical side, idealized physics-inspired models provide a very valuable tool to investigate universal properties of collective decision making in very large systems and at large time-scales, where the microscopic details of the individual deliberation process and the interactions between agents can be ignored.…”

Section: Introductionmentioning

confidence: 99%

Individual bias and fluctuations in collective decision making: from algorithms to Hamiltonians

et al. 2023

Self Cite

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In this paper, we reconsider the spin model suggested recently to understand some features of collective decision making among higher organisms [A.T. Hartnett et al., Phys. Rev. Lett. 116 (2016) 038701]. Within the model, the state of an agent i is described by the pair of variables corresponding to its opinion Si = ±1 and a bias ωitowards any of the opposing values of Si. Collective decision making is interpreted as an approach to the equilibrium state within the non-linear voter model subject to a social pressure and a probabilistic algorithm. Here, we push such physical analogy further and give the statistical physics interpretation of the model, describing it in terms of the Hamiltonian of interaction and looking for the equilibrium state via explicit calculation of its partition function. We show that depending on the assumptions about the nature of social interactions two diﬀerent Hamiltonians can be formulated, which can be solved with diﬀerent methods. In such an interpretation the temperature serves as a measure of ﬂuctuations, not considered before in the original model. We ﬁnd exact solutions for the thermodynamics of the model on the complete graph. The general analytical predictions are conﬁrmed using individualbased simulations. The simulations allow us also to study the impact of system size and initial conditions in the collective decision making in ﬁnite-sized systems, in particular with respect to convergence to metastable states.

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Collective decision strategies in the presence of spatio-temporal correlations

Cited by 4 publications

References 44 publications

Long-distance communication can enable collective migration in a dynamic seascape

Long-distance communication can enable collective migration in a dynamic seascape

Long-distance communication can enable collective migration in a dynamic seascape

Individual bias and fluctuations in collective decision making: from algorithms to Hamiltonians

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