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Sumpter, David J. T.ORCID iD iconorcid.org/0000-0002-1436-9103
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Publications (10 of 59) Show all publications
Blomqvist, B. R. H., Sumpter, D. J. T. & Mann, R. P. (2019). Inferring the dynamics of rising radical right-wing party support using Gaussian processes. Philosophical Transactions. Series A: Mathematical, physical, and engineering science, 377(2160), Article ID 20190145.
Open this publication in new window or tab >>Inferring the dynamics of rising radical right-wing party support using Gaussian processes
2019 (English)In: Philosophical Transactions. Series A: Mathematical, physical, and engineering science, ISSN 1364-503X, E-ISSN 1471-2962, Vol. 377, no 2160, article id 20190145Article in journal (Refereed) Published
Abstract [en]

The use of classical regression techniques in social science can prevent the discovery of complex, nonlinear mechanisms and often relies too heavily on both the expertise and prior expectations of the data analyst. In this paper, we present a regression methodology that combines the interpretability of traditional, well used, statistical methods with the full predictability and flexibility of Bayesian statistics techniques. Our modelling approach allows us to find and explain the mechanisms behind the rise of Radical Right-wing Populist parties (RRPs) that we would have been unable to find using traditional methods. Using Swedish municipality-level data (2002-2018), we find no evidence that the proportion of foreign-born residents is predictive of increases in RRP support. Instead, education levels and population density are the significant variables that impact the change in support for the RRP, in addition to spatial and temporal control variables. We argue that our methodology, which produces models with considerably better fit of the complexity and nonlinearities often found in social systems, provides a better tool for hypothesis testing and exploration of theories about RRPs and other social movements. This article is part of the theme issue 'Coupling functions: dynamical interaction mechanisms in the physical, biological and social sciences'.

Place, publisher, year, edition, pages
ROYAL SOC, 2019
Keywords
Gaussian processes, coupling functions, Radical Right-wing parties, Bayesian statistics
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:uu:diva-406505 (URN)10.1098/rsta.2019.0145 (DOI)000511612600013 ()31656139 (PubMedID)
Available from: 2020-03-10 Created: 2020-03-10 Last updated: 2020-03-10Bibliographically approved
Dussutour, A., Ma, Q. & Sumpter, D. J. T. (2019). Phenotypic variability predicts decision accuracy in unicellular organisms. Proceedings of the Royal Society of London. Biological Sciences, 286(1896), Article ID 20182825.
Open this publication in new window or tab >>Phenotypic variability predicts decision accuracy in unicellular organisms
2019 (English)In: Proceedings of the Royal Society of London. Biological Sciences, ISSN 0962-8452, E-ISSN 1471-2954, Vol. 286, no 1896, article id 20182825Article in journal (Refereed) Published
Abstract [en]

When deciding between different options, animals including humans face the dilemma that fast decisions tend to be erroneous, whereas accurate decisions tend to be relatively slow. Recently, it has been suggested that differences in the efficacy with which animals make a decision relate closely to individual behavioural differences. In this paper, we tested this hypothesis in a unique unicellular organism, the slime mould Physarum polycephalum. We first confirmed that slime moulds differed consistently in their exploratory behaviour from 'fast' to 'slow' explorers. Second, we showed that slow explorers made more accurate decisions than fast explorers. Third, we demonstrated that slime moulds integrated food cues in time and achieved higher accuracy when sampling time was longer. Lastly, we showed that in a competition context, fast explorers excelled when a single food source was offered, while slow explorers excelled when two food sources varying in quality were offered. Our results revealed that individual differences in accuracy were partly driven by differences in exploratory behaviour. These findings support the hypothesis that decision-making abilities are associated with behavioural types, even in unicellular organisms.

Keywords
speed - accuracy trade-off, individual differences, decision-making, slime moulds, Physarum polycephalum, drift-diffusion model
National Category
Evolutionary Biology
Identifiers
urn:nbn:se:uu:diva-383888 (URN)10.1098/rspb.2018.2825 (DOI)000465431000021 ()30963918 (PubMedID)
Funder
EU, European Research Council, IDCAB 220/104702003
Available from: 2019-05-29 Created: 2019-05-29 Last updated: 2019-05-29Bibliographically approved
Szorkovszky, A., Kotrschal, A., Herbert-Read, J. E., Buechel, S. D., Romensky, M., Rosén, E., . . . Sumpter, D. J. T. (2018). Assortative interactions revealed by sorting of animal groups. Animal Behaviour, 142, 165-179
Open this publication in new window or tab >>Assortative interactions revealed by sorting of animal groups
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2018 (English)In: Animal Behaviour, ISSN 0003-3472, E-ISSN 1095-8282, Vol. 142, p. 165-179Article in journal (Refereed) Published
Abstract [en]

Animals living in groups can show substantial variation in social traits and this affects their social organization. However, as the specific mechanisms driving this organization are difficult to identify in already organized groups typically found in the wild, the contribution of interindividual variation to group level behaviour remains enigmatic. Here, we present results of an experiment to create and compare groups that vary in social organization, and study how individual behaviour varies between these groups. We iteratively sorted individuals between groups of guppies, Poecilia reticulata, by ranking the groups according to their directional alignment and then mixing similar groups. Over the rounds of sorting the consistency of the group rankings increased, producing groups that varied significantly in key social behaviours such as collective activity and group cohesion. The repeatability of the underlying individual behaviour was then estimated by comparing the experimental data to simulations. At the level of basic locomotion, individuals in more coordinated groups displayed stronger interactions with the centre of the group, and weaker interactions with their nearest neighbours. We propose that this provides the basis for a passive phenotypic assortment mechanism that may explain the structures of social networks in the wild.

Place, publisher, year, edition, pages
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD, 2018
Keywords
collective behaviour, repeatability, sociability
National Category
Behavioral Sciences Biology
Identifiers
urn:nbn:se:uu:diva-362701 (URN)10.1016/j.anbehav.2018.06.005 (DOI)000441515500019 ()
Funder
Knut and Alice Wallenberg Foundation, 102 2013.0072
Available from: 2018-10-10 Created: 2018-10-10 Last updated: 2018-10-10Bibliographically approved
Kotrschal, A., Szorkovszky, A., Romenskyy, M., Perna, A., Buechel, S. D., Zeng, H.-L., . . . Kolm, N. (2018). Brain size does not impact shoaling dynamics in unfamiliar groups of guppies (Poecilia reticulata). Behavioural Processes, 147, 13-20
Open this publication in new window or tab >>Brain size does not impact shoaling dynamics in unfamiliar groups of guppies (Poecilia reticulata)
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2018 (English)In: Behavioural Processes, ISSN 0376-6357, E-ISSN 1872-8308, Vol. 147, p. 13-20Article in journal (Refereed) Published
Abstract [en]

Collective movement is achieved when individuals adopt local rules to interact with their neighbours. How the brain processes information about neighbours' positions and movements may affect how individuals interact in groups. As brain size can determine such information processing it should impact collective animal movement. Here we investigate whether brain size affects the structure and organisation of newly forming fish shoals by quantifying the collective movement of guppies (Poecilia reticulata) from large- and small-brained selection lines, with known differences in learning and memory. We used automated tracking software to determine shoaling behaviour of single-sex groups of eight or two fish and found no evidence that brain size affected the speed, group size, or spatial and directional organisation of fish shoals. Our results suggest that brain size does not play an important role in how fish interact with each other in these types of moving groups of unfamiliar individuals. Based on these results, we propose that shoal dynamics are likely to be governed by relatively basic cognitive processes that do not differ in these brain size selected lines of guppies.

Keywords
Brain size, Collective behaviour, Cognition, Fish shoal, Guppy
National Category
Zoology
Identifiers
urn:nbn:se:uu:diva-386327 (URN)10.1016/j.beproc.2017.12.006 (DOI)000423645400003 ()29248747 (PubMedID)
Funder
Knut and Alice Wallenberg Foundation, 102 2013.0072
Available from: 2019-06-24 Created: 2019-06-24 Last updated: 2019-06-24Bibliographically approved
Mann, R. P., Spaiser, V., Bergström, L. & Sumpter, D. J. T. (2018). Choice modelling with Gaussian processes in the social sciences: A case study of neighbourhood choice in Stockholm. PLoS ONE, 13(11), Article ID e0206687.
Open this publication in new window or tab >>Choice modelling with Gaussian processes in the social sciences: A case study of neighbourhood choice in Stockholm
2018 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 13, no 11, article id e0206687Article in journal (Refereed) Published
Abstract [en]

We present a non parametric extension of the conditional logit model, using Gaussian process priors. The conditional logit model is used in quantitative social science for inferring interaction effects between personal features and choice characteristics from observations of individual multinomial decisions, such as where to live, which car to buy or which school to choose. The classic, parametric model presupposes a latent utility function that is a linear combination of choice characteristics and their interactions with personal features. This imposes strong and unrealistic constraints on the form of individuals' preferences. Extensions using non-linear basis functions derived from the original features can ameliorate this problem but at the cost of high model complexity and increased reliance on the user in model specification. In this paper we develop a non-parametric conditional logit model based on Gaussian process logit models. We demonstrate its application on housing choice data from over 50,000 moving households from the Stockholm area over a two year period to reveal complex homophilic patterns in income, ethnicity and parental status.

Place, publisher, year, edition, pages
PUBLIC LIBRARY SCIENCE, 2018
National Category
Human Geography
Identifiers
urn:nbn:se:uu:diva-371507 (URN)10.1371/journal.pone.0206687 (DOI)000449291400041 ()30395626 (PubMedID)
Funder
Riksbankens Jubileumsfond, 516 M12-0301: 1EU, European Research Council, 615159
Available from: 2018-12-21 Created: 2018-12-21 Last updated: 2019-01-07Bibliographically approved
Spaiser, V., Hedström, P., Ranganathan, S., Jansson, K., Nordvik, M. K. & Sumpter, D. J. T. (2018). Identifying Complex Dynamics in Social Systems: A New Methodological Approach Applied to Study School Segregation. Sociological Methods & Research, 47(2), 103-135
Open this publication in new window or tab >>Identifying Complex Dynamics in Social Systems: A New Methodological Approach Applied to Study School Segregation
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2018 (English)In: Sociological Methods & Research, ISSN 0049-1241, E-ISSN 1552-8294, Vol. 47, no 2, p. 103-135Article in journal (Refereed) Published
Abstract [en]

It is widely recognized that segregation processes are often the result of complex nonlinear dynamics. Empirical analyses of complex dynamics are however rare, because there is a lack of appropriate empirical modeling techniques that are capable of capturing complex patterns and nonlinearities. At the same time, we know that many social phenomena display nonlinearities. In this article, we introduce a new modeling tool in order to partly fill this void in the literature. Using data of all secondary schools in Stockholm county during the years 1990 to 2002, we demonstrate how the methodology can be applied to identify complex dynamic patterns like tipping points and multiple phase transitions with respect to segregation. We establish critical thresholds in schools' ethnic compositions, in general, and in relation to various factors such as school quality and parents' income, at which the schools are likely to tip and become increasingly segregated.

Place, publisher, year, edition, pages
SAGE PUBLICATIONS INC, 2018
Keywords
dynamical systems, tipping points, nonlinearities, social systems, segregation, school segregation
National Category
Human Geography Mathematical Analysis
Identifiers
urn:nbn:se:uu:diva-352981 (URN)10.1177/0049124116626174 (DOI)000429944800001 ()
Available from: 2018-07-18 Created: 2018-07-18 Last updated: 2018-07-18Bibliographically approved
Liu, Y. & Sumpter, D. J. T. (2018). Is the golden ratio a universal constant for self-replication?. PLoS ONE, 13(7), Article ID e0200601.
Open this publication in new window or tab >>Is the golden ratio a universal constant for self-replication?
2018 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 13, no 7, article id e0200601Article in journal (Other academic) Published
Abstract [en]

The golden ratio, ϕ = 1.61803..., has often been found in connection with biological phenomena, ranging from spirals in sunflowers to gene frequency. One example where the golden ratio often arises is in self-replication, having its mathematical origins in Fibonacci's sequence for "rabbit reproduction". Recently, it has been claimed that ϕ determines the ratio between the number of different nucleobases in human genome. Such empirical examples continue to give credence to the idea that the golden ratio is a universal constant, not only in mathematics but also for biology. In this paper, we employ a general framework for chemically realistic self-replicating reaction systems and investigate whether the ratio of chemical species population follows "universal constants". We find that many self-replicating systems can be characterised by an algebraic number, which, in some cases, is the golden ratio. However, many other algebraic numbers arise from these systems, and some of them—such as and 1.22074... which is also known as the 3rd lower golden ratio—arise more frequently in self-replicating systems than the golden ratio. The "universal constants" in these systems arise as roots of a limited number of distinct characteristic equations. In addition, these "universal constants" are transient behaviours of self-replicating systems, corresponding to the scenario that the resource inside the system is infinite, which is not always the case in practice. Therefore, we argue that the golden ratio should not be considered as a special universal constant in self-replicating systems, and that the ratios between different chemical species only go to certain numbers under some idealised scenarios.

Keywords
Golden ratio, Fibonacci sequence, Self-replication, Fibonacci rabbit, Universal constant
National Category
Other Mathematics
Identifiers
urn:nbn:se:uu:diva-339888 (URN)10.1371/journal.pone.0200601 (DOI)000438829800032 ()30011316 (PubMedID)
Available from: 2018-01-23 Created: 2018-01-23 Last updated: 2018-09-27Bibliographically approved
Liu, Y. & Sumpter, D. J. T. (2018). Mathematical modeling reveals spontaneous emergence of self-replication in chemical reaction systems. Journal of Biological Chemistry, 293(49), 18854-18863
Open this publication in new window or tab >>Mathematical modeling reveals spontaneous emergence of self-replication in chemical reaction systems
2018 (English)In: Journal of Biological Chemistry, ISSN 0021-9258, E-ISSN 1083-351X, Vol. 293, no 49, p. 18854-18863Article in journal (Refereed) Published
Abstract [en]

Explaining the origin of life requires us to elucidate how self-replication arises. To be specific, how can a self-replicating entity develop spontaneously from a chemical reaction system in which no reaction is self-replicating? Previously proposed mathematical models either supply an explicit framework for a minimal living system or consider only catalyzed reactions, and thus fail to provide a comprehensive theory. Here, we set up a general mathematical model for chemical reaction systems that properly accounts for energetics, kinetics, and the conservation law. We found that 1) some systems are collectively catalytic, a mode whereby reactants are transformed into end products with the assistance of intermediates (as in the citric acid cycle), whereas some others are self-replicating, that is, different parts replicate each other and the system self-replicates as a whole (as in the formose reaction, in which sugar is replicated from form-aldehyde); 2) side reactions do not always inhibit such systems; 3) randomly chosen chemical universes (namely random artificial chemistries) often contain one or more such systems; 4) it is possible to construct a self-replicating system in which the entropy of some parts spontaneously decreases, in a manner similar to that discussed by Schrodinger; and 5) complex self-replicating molecules can emerge spontaneously and relatively easily from simple chemical reaction systems through a sequence of transitions. Together, these results start to explain the origins of prebiotic evolution.

Place, publisher, year, edition, pages
American Society for Biochemistry and Molecular Biology, 2018
National Category
Other Mathematics
Identifiers
urn:nbn:se:uu:diva-377982 (URN)10.1074/jbc.RA118.003795 (DOI)000458467400004 ()30282809 (PubMedID)
Available from: 2019-03-04 Created: 2019-03-04 Last updated: 2019-03-04Bibliographically approved
Sumpter, D. J. T., Szorkovszky, A., Kotrschal, A., Kolm, N. & Herbert-Read, J. E. (2018). Using activity and sociability to characterize collective motion. Philosophical Transactions of the Royal Society of London. Biological Sciences, 373(1746), Article ID 20170015.
Open this publication in new window or tab >>Using activity and sociability to characterize collective motion
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2018 (English)In: Philosophical Transactions of the Royal Society of London. Biological Sciences, ISSN 0962-8436, E-ISSN 1471-2970, Vol. 373, no 1746, article id 20170015Article, review/survey (Refereed) Published
Abstract [en]

A wide range of measurements can be made on the collective motion of groups, and the movement of individuals within them. These include, but are not limited to: group size, polarization, speed, turning speed, speed or directional correlations, and distances to near neighbours. From an ecological and evolutionary perspective, we would like to know which of these measurements capture biologically meaningful aspects of an animal's behaviour and contribute to its survival chances. Previous simulation studies have emphasized two main factors shaping individuals' behaviour in groups; attraction and alignment. Alignment responses appear to be important in transferring information between group members and providing synergistic benefits to group members. Likewise, attraction to conspecifics is thought to provide benefits through, for example, selfish herding. Here, we use a factor analysis on a wide range of simple measurements to identify two main axes of collective motion in guppies (Poecilia reticulata): (i) sociability, which corresponds to attraction (and to a lesser degree alignment) to neighbours, and (ii) activity, which combines alignment with directed movement. We show that for guppies, predation in a natural environment produces higher degrees of sociability and (in females) lower degrees of activity, while female guppies sorted for higher degrees of collective alignment have higher degrees of both sociability and activity. We suggest that the activity and sociability axes provide a useful framework for measuring the behaviour of animals in groups, allowing the comparison of individual and collective behaviours within and between species.

Place, publisher, year, edition, pages
ROYAL SOC, 2018
Keywords
collective behaviour, factor analysis, fish, Poecilia reticulata, personality
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:uu:diva-356886 (URN)10.1098/rstb.2017.0015 (DOI)000428370800012 ()29581400 (PubMedID)
Funder
Knut and Alice Wallenberg Foundation, 102 2013.0072
Available from: 2018-08-09 Created: 2018-08-09 Last updated: 2018-08-09Bibliographically approved
Blomqvist, B. R. H., Mann, R. P. & Sumpter, D. J. T. (2018). Using Bayesian dynamical systems, model averaging and neural networks to determine interactions between socio-economic indicators. PLoS ONE, 13(5), Article ID e0196355.
Open this publication in new window or tab >>Using Bayesian dynamical systems, model averaging and neural networks to determine interactions between socio-economic indicators
2018 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 13, no 5, article id e0196355Article in journal (Refereed) Published
Abstract [en]

Social and economic systems produce complex and nonlinear relationships in the indicator variables that describe them. We present a Bayesian methodology to analyze the dynamical relationships between indicator variables by identifying the nonlinear functions that best describe their interactions. We search for the 'best' explicit functions by fitting data using Bayesian linear regression on a vast number of models and then comparing their Bayes factors. The model with the highest Bayes factor, having the best trade-off between explanatory power and interpretability, is chosen as the 'best' model. To be able to compare a vast number of models, we use conjugate priors, resulting in fast computation times. We check the robustness of our approach by comparison with more prediction oriented approaches such as model averaging and neural networks. Our modelling approach is illustrated using the classical example of how democracy and economic growth relate to each other. We find that the best dynamical model for democracy suggests that long term democratic increase is only possible if the economic situation gets better. No robust model explaining economic development using these two variables was found.

Place, publisher, year, edition, pages
PUBLIC LIBRARY SCIENCE, 2018
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:uu:diva-359665 (URN)10.1371/journal.pone.0196355 (DOI)000431757400027 ()29742126 (PubMedID)
Available from: 2018-09-05 Created: 2018-09-05 Last updated: 2018-10-30Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0002-1436-9103

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