1
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Vanadzina K, Street SE, Healy SD, Laland KN, Sheard C. Global drivers of variation in cup nest size in passerine birds. J Anim Ecol 2023; 92:338-351. [PMID: 36134498 PMCID: PMC10092846 DOI: 10.1111/1365-2656.13815] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 09/15/2022] [Indexed: 11/30/2022]
Abstract
The size of a bird's nest can play a key role in ensuring reproductive success and is determined by a variety of factors. The primary function of the nest is to protect offspring from the environment and predators. Field studies in a number of passerine species have indicated that higher-latitude populations in colder habitats build larger nests with thicker walls compared to lower-latitude populations, but that these larger nests are more vulnerable to predation. Increases in nest size can also be driven by sexual selection, as nest size can act as a signal of parental quality and prompt differential investment in other aspects of care. It is unknown, however, how these microevolutionary patterns translate to a macroevolutionary scale. Here, we investigate potential drivers of variation in the outer and inner volume of open cup nests using a large dataset of nest measurements from 1117 species of passerines breeding in a diverse range of environments. Our dataset is sourced primarily from the nest specimens at the Natural History Museum (UK), complemented with information from ornithological handbooks and online databases. We use phylogenetic comparative methods to test long-standing hypotheses about potential macroevolutionary correlates of nest size, namely nest location, clutch size and variables relating to parental care, together with environmental and geographical factors such as temperature, rainfall, latitude and insularity. After controlling for phylogeny and parental body size, we demonstrate that the outer volume of the nest is greater in colder climates, in island-dwelling species and in species that nest on cliffs or rocks. By contrast, the inner cup volume is associated solely with average clutch size, increasing with the number of chicks raised in the nest. We do not find evidence that nest size is related to the length of parental care for nestlings. Our study reveals that the average temperature in the breeding range, along with several key life-history traits and proxies of predation threat, shapes the global interspecific variation in passerine cup nest size. We also showcase the utility of museum nest collections-a historically underused resource-for large-scale studies of trait evolution.
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Affiliation(s)
| | - Sally E Street
- Department of Anthropology, Durham University, Durham, UK
| | - Susan D Healy
- School of Biology, University of St Andrews, St Andrews, UK
| | - Kevin N Laland
- School of Biology, University of St Andrews, St Andrews, UK
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2
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Webster MM, Laland KN. No evidence for individual recognition in threespine or ninespine sticklebacks ( Gasterosteus aculeatus or Pungitius pungitius). R Soc Open Sci 2020; 7:191703. [PMID: 32874600 PMCID: PMC7428269 DOI: 10.1098/rsos.191703] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Accepted: 06/17/2020] [Indexed: 06/11/2023]
Abstract
Recognition plays an important role in the formation and organization of animal groups. Many animals are capable of class-level recognition, discriminating, for example, on the basis of species, kinship or familiarity. Individual recognition requires that animals recognize distinct cues, and learn to associate these with the specific individual from which they are derived. In this study, we asked whether sticklebacks (Gasterosteus aculeatus and Pungitius pungitius) were capable of learning to recognize individual conspecifics. We have used these fish as model organisms for studying selective social learning, and demonstrating a capacity for individual recognition in these species would provide an exciting opportunity for studying how biases for copying specific individuals shape the dynamics of information transmission. To test for individual recognition, we trained subjects to associate green illumination with the provision of a food reward close to one of two conspecifics, and, for comparison, one of two physical landmarks. Both species were capable of recognizing the rewarded landmark, but neither showed a preference for associating with the rewarded conspecific. Our study provides no evidence for individual recognition in either species. We speculate that the fission-fusion structure of their social groups may not favour a capacity for individual recognition.
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Affiliation(s)
- Mike M. Webster
- Centre for Biological Diversity, School of Biology, University of St Andrews, St Andrews, Fife KY16 9TF, UK
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3
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Miu E, Gulley N, Laland KN, Rendell L. Flexible learning, rather than inveterate innovation or copying, drives cumulative knowledge gain. Sci Adv 2020; 6:eaaz0286. [PMID: 32548255 PMCID: PMC7274806 DOI: 10.1126/sciadv.aaz0286] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/06/2019] [Accepted: 04/15/2020] [Indexed: 06/11/2023]
Abstract
Human technology is characterized by cumulative cultural knowledge gain, yet researchers have limited knowledge of the mix of copying and innovation that maximizes progress. Here, we analyze a unique large-scale dataset originating from collaborative online programming competitions to investigate, in a setting of real-world complexity, how individual differences in innovation, social-information use, and performance generate technological progress. We find that cumulative knowledge gain is primarily driven by pragmatists, willing to copy, innovate, explore, and take risks flexibly, rather than by pure innovators or habitual copiers. Our study also reveals a key role for prestige in information transfer.
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Affiliation(s)
- Elena Miu
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St Andrews, St Andrews KY16 9TH, UK
- School of Human Evolution and Social Change and Institute of Human Origins, Arizona State University, Tempe, AZ 85287, USA
| | | | - Kevin N. Laland
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St Andrews, St Andrews KY16 9TH, UK
| | - Luke Rendell
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St Andrews, St Andrews KY16 9TH, UK
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4
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Milham M, Petkov CI, Margulies DS, Schroeder CE, Basso MA, Belin P, Fair DA, Fox A, Kastner S, Mars RB, Messinger A, Poirier C, Vanduffel W, Van Essen DC, Alvand A, Becker Y, Ben Hamed S, Benn A, Bodin C, Boretius S, Cagna B, Coulon O, El-Gohary SH, Evrard H, Forkel SJ, Friedrich P, Froudist-Walsh S, Garza-Villarreal EA, Gao Y, Gozzi A, Grigis A, Hartig R, Hayashi T, Heuer K, Howells H, Ardesch DJ, Jarraya B, Jarrett W, Jedema HP, Kagan I, Kelly C, Kennedy H, Klink PC, Kwok SC, Leech R, Liu X, Madan C, Madushanka W, Majka P, Mallon AM, Marche K, Meguerditchian A, Menon RS, Merchant H, Mitchell A, Nenning KH, Nikolaidis A, Ortiz-Rios M, Pagani M, Pareek V, Prescott M, Procyk E, Rajimehr R, Rautu IS, Raz A, Roe AW, Rossi-Pool R, Roumazeilles L, Sakai T, Sallet J, García-Saldivar P, Sato C, Sawiak S, Schiffer M, Schwiedrzik CM, Seidlitz J, Sein J, Shen ZM, Shmuel A, Silva AC, Simone L, Sirmpilatze N, Sliwa J, Smallwood J, Tasserie J, Thiebaut de Schotten M, Toro R, Trapeau R, Uhrig L, Vezoli J, Wang Z, Wells S, Williams B, Xu T, Xu AG, Yacoub E, Zhan M, Ai L, Amiez C, Balezeau F, Baxter MG, Blezer EL, Brochier T, Chen A, Croxson PL, Damatac CG, Dehaene S, Everling S, Fleysher L, Freiwald W, Griffiths TD, Guedj C, Hadj-Bouziane F, Harel N, Hiba B, Jung B, Koo B, Laland KN, Leopold DA, Lindenfors P, Meunier M, Mok K, Morrison JH, Nacef J, Nagy J, Pinsk M, Reader SM, Roelfsema PR, Rudko DA, Rushworth MF, Russ BE, Schmid MC, Sullivan EL, Thiele A, Todorov OS, Tsao D, Ungerleider L, Wilson CR, Ye FQ, Zarco W, Zhou YD. Accelerating the Evolution of Nonhuman Primate Neuroimaging. Neuron 2020; 105:600-603. [PMID: 32078795 PMCID: PMC7610430 DOI: 10.1016/j.neuron.2019.12.023] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Revised: 12/13/2019] [Accepted: 12/17/2019] [Indexed: 11/17/2022]
Abstract
Nonhuman primate neuroimaging is on the cusp of a transformation, much in the same way its human counterpart was in 2010, when the Human Connectome Project was launched to accelerate progress. Inspired by an open data-sharing initiative, the global community recently met and, in this article, breaks through obstacles to define its ambitions.
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5
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Abstract
As a form of adaptive plasticity that allows organisms to shift their phenotype toward the optimum, learning is inherently a source of developmental bias. Learning may be of particular significance to the evolutionary biology community because it allows animals to generate adaptively biased novel behavior tuned to the environment and, through social learning, to propagate behavioral traits to other individuals, also in an adaptively biased manner. We describe several types of developmental bias manifest in learning, including an adaptive bias, historical bias, origination bias, and transmission bias, stressing that these can influence evolutionary dynamics through generating nonrandom phenotypic variation and/or nonrandom environmental states. Theoretical models and empirical data have established that learning can impose direction on adaptive evolution, affect evolutionary rates (both speeding up and slowing down responses to selection under different conditions) and outcomes, influence the probability of populations reaching global optimum, and affect evolvability. Learning is characterized by highly specific, path-dependent interactions with the (social and physical) environment, often resulting in new phenotypic outcomes. Consequently, learning regularly introduces novelty into phenotype space. These considerations imply that learning may commonly generate plasticity first evolution.
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Affiliation(s)
- Kevin N Laland
- School of Biology, University of St. Andrews, St. Andrews, UK
| | - Wataru Toyokawa
- School of Biology, University of St. Andrews, St. Andrews, UK.,Department of Evolutionary Studies of Biosystems, SOKENDAI (The Graduate University for Advanced Studies), Hayama, Kanagawa, Japan
| | - Thomas Oudman
- School of Biology, University of St. Andrews, St. Andrews, UK.,Department of Coastal Systems, NIOZ Royal Netherlands Institute for Sea Research, Utrecht University, Utrecht, The Netherlands
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6
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Abstract
Culture (behaviour based on socially transmitted information) is present in diverse animal species, yet how it interacts with genetic evolution remains largely unexplored. Here, we review the evidence for gene-culture coevolution in animals, especially birds, cetaceans and primates. We describe how culture can relax or intensify selection under different circumstances, create new selection pressures by changing ecology or behaviour, and favour adaptations, including in other species. Finally, we illustrate how, through culturally mediated migration and assortative mating, culture can shape population genetic structure and diversity. This evidence suggests strongly that animal culture plays an important evolutionary role, and we encourage explicit analyses of gene-culture coevolution in nature.
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Affiliation(s)
- Hal Whitehead
- Department of Biology, Dalhousie University, Halifax, B3H 4R2, Canada.
| | - Kevin N Laland
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St Andrews, St Andrews, KY16 9TF, United Kingdom
| | - Luke Rendell
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St Andrews, St Andrews, KY16 9TF, United Kingdom
| | - Rose Thorogood
- Department of Zoology, University of Cambridge, Cambridge, CB2 3EJ, United Kingdom
- Helsinki Institute of Life Science, University of Helsinki, Helsinki, 00014, Finland
- Faculty of Biological and Environmental Sciences (Research Program in Organismal & Evolutionary Biology), University of Helsinki, Helsinki, 00014, Finland
| | - Andrew Whiten
- Centre for Social Learning and Cognitive Evolution, School of Psychology and Neuroscience, University of St Andrews, St Andrews, KY16 9JP, United Kingdom
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7
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Webster MM, Chouinard-Thuly L, Herczeg G, Kitano J, Riley R, Rogers S, Shapiro MD, Shikano T, Laland KN. A four-questions perspective on public information use in sticklebacks (Gasterosteidae). R Soc Open Sci 2019; 6:181735. [PMID: 30891285 PMCID: PMC6408396 DOI: 10.1098/rsos.181735] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Accepted: 01/08/2019] [Indexed: 06/09/2023]
Abstract
Whether learning primarily reflects general processes or species-specific challenges is a long-standing matter of dispute. Here, we present a comprehensive analysis of public information use (PI-use) in sticklebacks (Gasterosteidae). PI-use is a form of social learning by which animals are able to assess the relative quality of resources, here prey patches, by observing the behaviour of others. PI-use was highly specific with only Pungitius and their closest relative Culaea inconstans showing evidence of PI-use. We saw no effects of ontogenetic experience upon PI-use in Pungitius pungitius. Experiments with live demonstrators and animated fish revealed that heightened activity and feeding strikes by foraging conspecifics are important cues in the transmission of PI. Finally, PI-use was the only form of learning in which P. pungitius and another stickleback, Gasterosteus aculeatus differed. PI-use in sticklebacks is species-specific and may represent an 'ecological specialization' for social foraging. Whether this reflects selection on perception, attentional or cognitive processes remains to be determined.
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Affiliation(s)
- Mike M. Webster
- Centre for Biological Diversity, School of Biology, University of St Andrews, St Andrews, Fife KY16 9TF, UK
| | - Laura Chouinard-Thuly
- Centre for Biological Diversity, School of Biology, University of St Andrews, St Andrews, Fife KY16 9TF, UK
- Department of Biology, McGill University, 1205 Docteur Penfield, Montréal, Quebec, Canada H3A 1B1
| | - Gabor Herczeg
- Ecological Genetics Research Group, Department of Biosciences, University of Helsinki, Finland
- Behavioural Ecology Group, Department of Systematic Zoology and Ecology, Eötvös Loránd University, Hungary
| | - Jun Kitano
- Division of Ecological Genetics, National Institute of Genetics, Mishima, Japan
| | - Riva Riley
- Centre for Biological Diversity, School of Biology, University of St Andrews, St Andrews, Fife KY16 9TF, UK
- Department of Zoology, University of Cambridge, UK
| | - Sean Rogers
- Ecology and Evolutionary Biology, Calgary, Canada
| | - Michael D. Shapiro
- Department of Biology, University of Utah, Salt Lake City, UT 84112, USA
| | - Takahito Shikano
- Ecological Genetics Research Group, Department of Biosciences, University of Helsinki, Finland
| | - Kevin N. Laland
- Centre for Biological Diversity, School of Biology, University of St Andrews, St Andrews, Fife KY16 9TF, UK
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8
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9
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Troisi CA, Hoppitt WJE, Ruiz-Miranda CR, Laland KN. Food-Offering Calls in Wild Golden Lion Tamarins ( Leontopithecus rosalia): Evidence for Teaching Behavior? INT J PRIMATOL 2018; 39:1105-1123. [PMID: 30613117 PMCID: PMC6300579 DOI: 10.1007/s10764-018-0069-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Accepted: 08/07/2018] [Indexed: 11/27/2022]
Abstract
Many animals emit calls in the presence of food, but researchers do not always know the function of these calls. Evidence suggests that adult golden lion tamarins (Leontopithecus rosalia) use food-offering calls to teach juveniles which substrate (i.e., microhabitat) to forage on, or in, for food. However, we do not yet know whether juveniles learn from this aspect of the adults' behavior. Here we examine whether juveniles learn to associate food-offering calls with a foraging substrate, as a step toward assessing whether these calls qualify as teaching behavior. We compared the performance of four wild juvenile golden lion tamarins that were introduced to a novel substrate while exposed to playbacks of food-offering calls (experimental condition) to the performance of three juveniles that were exposed to the novel substrate without the presence of food-offering playbacks (control condition). We varied the location of the novel substrate between trials. We found that food-offering calls had an immediate effect on juveniles' interactions with the novel substrate, whether they inserted their hands into the substrate and their eating behavior, and a long-term effect on eating behavior at the substrate. The findings imply that juvenile golden lion tamarins can learn through food-offering calls about the availability of food at a substrate, which is consistent with (but does not prove) teaching in golden lion tamarins through stimulus enhancement. Our findings support the hypothesis that teaching might be more likely to evolve in cooperatively breeding species with complex ecological niches.
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Affiliation(s)
- Camille A. Troisi
- School of Biology, University of St Andrews, St Andrews, KY16 9TH UK
- Present Address: Department of Psychology, University of Cambridge, Cambridge, CB2 3EB UK
| | - Will J. E. Hoppitt
- School of Biology, University of Leeds, Leeds, LS2 9JT UK
- Present Address: School of Biological Sciences, Royal Holloway, University of London, Egham, UK
| | - Carlos R. Ruiz-Miranda
- Laboratory of Environmental Sciences, Universidade Estadual do Norte Fluminense, Campos dos Goytacazes, Rio de Janeiro, Brazil
| | - Kevin N. Laland
- School of Biology, University of St Andrews, St Andrews, KY16 9TH UK
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10
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Milham MP, Ai L, Koo B, Xu T, Amiez C, Balezeau F, Baxter MG, Blezer ELA, Brochier T, Chen A, Croxson PL, Damatac CG, Dehaene S, Everling S, Fair DA, Fleysher L, Freiwald W, Froudist-Walsh S, Griffiths TD, Guedj C, Hadj-Bouziane F, Ben Hamed S, Harel N, Hiba B, Jarraya B, Jung B, Kastner S, Klink PC, Kwok SC, Laland KN, Leopold DA, Lindenfors P, Mars RB, Menon RS, Messinger A, Meunier M, Mok K, Morrison JH, Nacef J, Nagy J, Rios MO, Petkov CI, Pinsk M, Poirier C, Procyk E, Rajimehr R, Reader SM, Roelfsema PR, Rudko DA, Rushworth MFS, Russ BE, Sallet J, Schmid MC, Schwiedrzik CM, Seidlitz J, Sein J, Shmuel A, Sullivan EL, Ungerleider L, Thiele A, Todorov OS, Tsao D, Wang Z, Wilson CRE, Yacoub E, Ye FQ, Zarco W, Zhou YD, Margulies DS, Schroeder CE. An Open Resource for Non-human Primate Imaging. Neuron 2018; 100:61-74.e2. [PMID: 30269990 PMCID: PMC6231397 DOI: 10.1016/j.neuron.2018.08.039] [Citation(s) in RCA: 126] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2018] [Revised: 03/02/2018] [Accepted: 08/30/2018] [Indexed: 01/11/2023]
Abstract
Non-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience. Unfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMatE Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design, and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 25 independent data collections aggregated across 22 sites (total = 217 non-human primates). We also outline the unique pitfalls and challenges that should be considered in the analysis of non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets.
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Affiliation(s)
- Michael P Milham
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA; Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA.
| | - Lei Ai
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA
| | - Bonhwang Koo
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA
| | - Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA
| | - Céline Amiez
- University of Lyon, Université Claude Bernard Lyon 1, INSERM, Stem Cell and Brain Research Institute U1208, Lyon, France
| | - Fabien Balezeau
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Mark G Baxter
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Erwin L A Blezer
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Thomas Brochier
- Institut de Neurosciences de la Timone, CNRS & Aix-Marseille Université, UMR 7289, Marseille, France
| | - Aihua Chen
- Key Laboratory of Brain Functional Genomics (Ministry of Education & Science and Technology Commission of Shanghai Municipality), School of Life Sciences, East China Normal University, Shanghai 200062, China
| | - Paula L Croxson
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Christienne G Damatac
- Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, 6525 EN Nijmegen, Netherlands
| | - Stanislas Dehaene
- NeuroSpin, CEA, INSERM U992, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
| | - Stefan Everling
- Centre for Functional and Metabolic Mapping, The University of Western Ontario, London, ON N6A 3K7, Canada
| | - Damian A Fair
- Department of Behavior Neuroscience, Department of Psychiatry, Advanced Imaging Research Center, Oregon Health and Science University, Portland, OR, USA
| | - Lazar Fleysher
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Winrich Freiwald
- Laboratory of Neural Systems, The Rockefeller University, New York, NY, USA
| | | | - Timothy D Griffiths
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Carole Guedj
- INSERM, U1028, CNRS UMR5292, Lyon Neuroscience Research Center, Lyon, France
| | | | - Suliann Ben Hamed
- Institut des Sciences Cognitives - Marc Jeannerod, UMR5229, CNRS-Université de Lyon, Lyon, France
| | - Noam Harel
- Center for Magnetic Resonance Research, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - Bassem Hiba
- Institut des Sciences Cognitives - Marc Jeannerod, UMR5229, CNRS-Université de Lyon, Lyon, France
| | - Bechir Jarraya
- NeuroSpin, CEA, INSERM U992, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
| | - Benjamin Jung
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Sabine Kastner
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540, USA
| | - P Christiaan Klink
- Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, 1105 BA Amsterdam, the Netherlands; Department of Psychiatry, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, the Netherlands
| | - Sze Chai Kwok
- Shanghai Key Laboratory of Brain Functional Genomics, School of Psychology and Cognitive Science, Key Laboratory of Brain Functional Genomics (Ministry of Education), East China Normal University, Shanghai 200062, China; Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai 200062, China; NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai, Shanghai 200062, China
| | - Kevin N Laland
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St. Andrews, St. Andrews, UK
| | - David A Leopold
- Section on Cognitive Neurophysiology and Imaging, National Institute of Mental Health, Bethesda, MD 20892, USA; Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, Bethesda, MD 20892, USA
| | - Patrik Lindenfors
- Institute for Future Studies, Stockholm, Sweden; Centre for Cultural Evolution & Department of Zoology, Stockholm University, Stockholm, Sweden
| | - Rogier B Mars
- Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, 6525 EN Nijmegen, Netherlands; Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK
| | - Ravi S Menon
- Centre for Functional and Metabolic Mapping, The University of Western Ontario, London, ON N6A 3K7, Canada
| | - Adam Messinger
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Martine Meunier
- INSERM, U1028, CNRS UMR5292, Lyon Neuroscience Research Center, Lyon, France
| | - Kelvin Mok
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Departments of Neurology, Neurosurgery, and Biomedical Engineering, McGill University, Montreal, QC H3A 0G4, Canada
| | - John H Morrison
- California National Primate Research Center, Davis, CA 95616, USA; Department of Neurology, School of Medicine, University of California, Davis, CA 95616, USA
| | - Jennifer Nacef
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Jamie Nagy
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Michael Ortiz Rios
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Christopher I Petkov
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Mark Pinsk
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540, USA
| | - Colline Poirier
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Emmanuel Procyk
- University of Lyon, Université Claude Bernard Lyon 1, INSERM, Stem Cell and Brain Research Institute U1208, Lyon, France
| | - Reza Rajimehr
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Simon M Reader
- Department of Biology and Helmholtz Institute, Utrecht University, 35 84 CH Utrecht, The Netherlands; Department of Biology, McGill University, Montreal, QC H3A 1BA, Canada
| | - Pieter R Roelfsema
- Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, 1105 BA Amsterdam, the Netherlands; Department of Psychiatry, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, the Netherlands; Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit, 1081 HV Amsterdam, the Netherlands
| | - David A Rudko
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Departments of Neurology, Neurosurgery, and Biomedical Engineering, McGill University, Montreal, QC H3A 0G4, Canada
| | - Matthew F S Rushworth
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK; Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford OX1 3AQ, UK
| | - Brian E Russ
- Section on Cognitive Neurophysiology and Imaging, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Jerome Sallet
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford OX1 3AQ, UK
| | | | | | - Jakob Seidlitz
- Developmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, MD 20892, USA; Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK
| | - Julien Sein
- Institut de Neurosciences de la Timone, CNRS & Aix-Marseille Université, UMR 7289, Marseille, France
| | - Amir Shmuel
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Departments of Neurology, Neurosurgery, and Biomedical Engineering, McGill University, Montreal, QC H3A 0G4, Canada
| | - Elinor L Sullivan
- Divisions of Neuroscience and Cardiometabolic Health, Oregon National Primate Research Center, Beaverton, OR, USA; Department of Human Physiology, University of Oregon, Eugene, OR, USA
| | - Leslie Ungerleider
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Alexander Thiele
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Orlin S Todorov
- Department of Biology and Helmholtz Institute, Utrecht University, 35 84 CH Utrecht, The Netherlands
| | - Doris Tsao
- Department of Computation and Neural Systems, California Institute of Technology, Pasadena, CA 91125, USA
| | - Zheng Wang
- Institute of Neuroscience, Key Laboratory of Primate Neurobiology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Charles R E Wilson
- University of Lyon, Université Claude Bernard Lyon 1, INSERM, Stem Cell and Brain Research Institute U1208, Lyon, France
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - Frank Q Ye
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, Bethesda, MD 20892, USA
| | - Wilbert Zarco
- Laboratory of Neural Systems, The Rockefeller University, New York, NY, USA
| | - Yong-di Zhou
- Krieger Mind/Brain Institute, Department of Neurosurgery, Johns Hopkins University, Baltimore, MD 21287, USA
| | - Daniel S Margulies
- Max Planck Research Group for Neuroanatomy and Connectivity, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany; Centre national de la recherche scientifique, CNRS UMR 7225, Institut du Cerveau et de la Moelle épinière, 75013 Paris, France
| | - Charles E Schroeder
- Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA; Department of Neurological Surgery, Columbia University College of Physicians and Surgeons, New York, NY 10032, USA; Department of Psychiatry, Columbia University College of Physicians and Surgeons, New York, NY 10032, USA
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11
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Laland KN. Beyond epigenetics
Extended Heredity: A New Understanding of Inheritance and Evolution
Russell Bonduriansky and Troy Day
Princeton University Press, 2018. 302 pp. Science 2018. [DOI: 10.1126/science.aau1392] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Kevin N. Laland
- The reviewer is at the Centre for Biological Diversity, University of St. Andrews, St. Andrews, Fife KY16 9TH, UK
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12
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Navarrete AF, Blezer ELA, Pagnotta M, de Viet ESM, Todorov OS, Lindenfors P, Laland KN, Reader SM. Primate Brain Anatomy: New Volumetric MRI Measurements for Neuroanatomical Studies. Brain Behav Evol 2018; 91:109-117. [PMID: 29894995 DOI: 10.1159/000488136] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Accepted: 03/05/2018] [Indexed: 12/20/2022]
Abstract
Since the publication of the primate brain volumetric dataset of Stephan and colleagues in the early 1980s, no major new comparative datasets covering multiple brain regions and a large number of primate species have become available. However, technological and other advances in the last two decades, particularly magnetic resonance imaging (MRI) and the creation of institutions devoted to the collection and preservation of rare brain specimens, provide opportunities to rectify this situation. Here, we present a new dataset including brain region volumetric measurements of 39 species, including 20 species not previously available in the literature, with measurements of 16 brain areas. These volumes were extracted from MRI of 46 brains of 38 species from the Netherlands Institute of Neuroscience Primate Brain Bank, scanned at high resolution with a 9.4-T scanner, plus a further 7 donated MRI of 4 primate species. Partial measurements were made on an additional 8 brains of 5 species. We make the dataset and MRI scans available online in the hope that they will be of value to researchers conducting comparative studies of primate evolution.
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Affiliation(s)
- Ana F Navarrete
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St. Andrews, St. Andrews, United Kingdom.,Department of Biology and Helmholtz Institute, Utrecht University, Utrecht, the Netherlands
| | - Erwin L A Blezer
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Murillo Pagnotta
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St. Andrews, St. Andrews, United Kingdom
| | - Elizabeth S M de Viet
- Department of Biology and Helmholtz Institute, Utrecht University, Utrecht, the Netherlands
| | - Orlin S Todorov
- Department of Biology and Helmholtz Institute, Utrecht University, Utrecht, the Netherlands
| | - Patrik Lindenfors
- Institute for Future Studies, Stockholm, Sweden.,Centre for Cultural Evolution & Department of Zoology, Stockholm University, Stockholm, Sweden
| | - Kevin N Laland
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St. Andrews, St. Andrews, United Kingdom
| | - Simon M Reader
- Department of Biology and Helmholtz Institute, Utrecht University, Utrecht, the Netherlands.,Department of Biology, McGill University, Montreal, Québec, Canada
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13
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Kendal RL, Boogert NJ, Rendell L, Laland KN, Webster M, Jones PL. Social Learning Strategies: Bridge-Building between Fields. Trends Cogn Sci 2018; 22:651-665. [PMID: 29759889 DOI: 10.1016/j.tics.2018.04.003] [Citation(s) in RCA: 219] [Impact Index Per Article: 36.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2017] [Revised: 04/06/2018] [Accepted: 04/12/2018] [Indexed: 01/13/2023]
Abstract
While social learning is widespread, indiscriminate copying of others is rarely beneficial. Theory suggests that individuals should be selective in what, when, and whom they copy, by following 'social learning strategies' (SLSs). The SLS concept has stimulated extensive experimental work, integrated theory, and empirical findings, and created impetus to the social learning and cultural evolution fields. However, the SLS concept needs updating to accommodate recent findings that individuals switch between strategies flexibly, that multiple strategies are deployed simultaneously, and that there is no one-to-one correspondence between psychological heuristics deployed and resulting population-level patterns. The field would also benefit from the simultaneous study of mechanism and function. SLSs provide a useful vehicle for bridge-building between cognitive psychology, neuroscience, and evolutionary biology.
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Affiliation(s)
- Rachel L Kendal
- Centre for Coevolution of Biology & Culture, Durham University, Anthropology Department, Durham, DH1 3LE, UK.
| | - Neeltje J Boogert
- Centre for Ecology and Conservation, College of Life and Environmental Sciences, University of Exeter, Penryn Campus, Cornwall, TR10 9EZ, UK
| | - Luke Rendell
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St Andrews, St Andrews, KY16 9TS, UK
| | - Kevin N Laland
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St Andrews, St Andrews, KY16 9TS, UK
| | - Mike Webster
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St Andrews, St Andrews, KY16 9TS, UK
| | - Patricia L Jones
- Department of Biology, Bowdoin College, Brunswick, ME 04011, USA
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14
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Street SE, Morgan TJH, Thornton A, Brown GR, Laland KN, Cross CP. Human mate-choice copying is domain-general social learning. Sci Rep 2018; 8:1715. [PMID: 29379046 PMCID: PMC5788917 DOI: 10.1038/s41598-018-19770-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2017] [Accepted: 01/09/2018] [Indexed: 11/11/2022] Open
Abstract
Women appear to copy other women’s preferences for men’s faces. This ‘mate-choice copying’ is often taken as evidence of psychological adaptations for processing social information related to mate choice, for which facial information is assumed to be particularly salient. No experiment, however, has directly investigated whether women preferentially copy each other’s face preferences more than other preferences. Further, because prior experimental studies used artificial social information, the effect of real social information on attractiveness preferences is unknown. We collected attractiveness ratings of pictures of men’s faces, men’s hands, and abstract art given by heterosexual women, before and after they saw genuine social information gathered in real time from their peers. Ratings of faces were influenced by social information, but no more or less than were images of hands and abstract art. Our results suggest that evidence for domain-specific social learning mechanisms in humans is weaker than previously suggested.
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Affiliation(s)
- Sally E Street
- School of Biology, Sir Harold Mitchell Building, University of St Andrews, Greenside Place, St Andrews, KY16 9TJ, Fife, UK.,Department of Anthropology, Durham University, South Road, Durham, DH1 3LE, Country Durham, UK
| | - Thomas J H Morgan
- School of Human Evolution and Social Change, Arizona State University, South Cady Mall, Tempe, 85281, Arizona, USA
| | - Alex Thornton
- Centre for Ecology and Conservation, University of Exeter, Penryn Campus, Penryn, TR10 9FE, Cornwall, UK
| | - Gillian R Brown
- School of Psychology and Neuroscience, University of St Andrews, Westburn Lane, St Andrews, KY16 9JP, Fife, UK
| | - Kevin N Laland
- School of Biology, Sir Harold Mitchell Building, University of St Andrews, Greenside Place, St Andrews, KY16 9TJ, Fife, UK
| | - Catharine P Cross
- School of Psychology and Neuroscience, University of St Andrews, Westburn Lane, St Andrews, KY16 9JP, Fife, UK.
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15
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Evans CL, Laland KN, Carpenter M, Kendal RL. Selective copying of the majority suggests children are broadly “optimal-” rather than “over-” imitators. Dev Sci 2017; 21:e12637. [DOI: 10.1111/desc.12637] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2016] [Accepted: 10/05/2017] [Indexed: 11/30/2022]
Affiliation(s)
- Cara L. Evans
- School of Biology; University of St Andrews; St Andrews UK
- Department of Linguistic and Cultural Evolution; Max Planck Institute for the Science of Human History; Jena Germany
| | | | - Malinda Carpenter
- School of Psychology & Neuroscience; University of St Andrews; St Andrews UK
- Department of Developmental and Comparative Psychology; Max Planck Institute for Evolutionary Anthropology; Leipzig Germany
| | - Rachel L. Kendal
- Centre for Coevolution of Biology & Culture, Anthropology Department; Durham University; UK
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16
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17
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18
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Affiliation(s)
- Andrew Whiten
- Centre for Social Learning and Cognitive Evolution, School of Psychology and Neuroscience, University of St. Andrews, St. Andrews KY16 9JP, United Kingdom;
| | - Francisco J Ayala
- Department of Ecology and Evolutionary Biology, University of California, Irvine, CA 92697
| | | | - Kevin N Laland
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St. Andrews, St. Andrews KY16 9JP, United Kingdom
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19
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Affiliation(s)
- Kevin N. Laland
- Department of Integrative Biology; University of California; Berkeley California 94720
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20
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Abstract
There is a tension between the conception of cognition as a central nervous system (CNS) process and a view of cognition as extending towards the body or the contiguous environment. The centralised conception requires large or complex nervous systems to cope with complex environments. Conversely, the extended conception involves the outsourcing of information processing to the body or environment, thus making fewer demands on the processing power of the CNS. The evolution of extended cognition should be particularly favoured among small, generalist predators such as spiders, and here, we review the literature to evaluate the fit of empirical data with these contrasting models of cognition. Spiders do not seem to be cognitively limited, displaying a large diversity of learning processes, from habituation to contextual learning, including a sense of numerosity. To tease apart the central from the extended cognition, we apply the mutual manipulability criterion, testing the existence of reciprocal causal links between the putative elements of the system. We conclude that the web threads and configurations are integral parts of the cognitive systems. The extension of cognition to the web helps to explain some puzzling features of spider behaviour and seems to promote evolvability within the group, enhancing innovation through cognitive connectivity to variable habitat features. Graded changes in relative brain size could also be explained by outsourcing information processing to environmental features. More generally, niche-constructed structures emerge as prime candidates for extending animal cognition, generating the selective pressures that help to shape the evolving cognitive system.
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Affiliation(s)
- Hilton F Japyassú
- Biology Institute, Federal University of Bahia, Rua Barão de Jeremoabo s/n, Campus de Ondina, Salvador, Bahia, 40170-115, Brazil.
- Centre for Biodiversity, School of Biology, University of St Andrews, Harold Mitchell Building, St Andrews, Fife, UK, KY16 9TH.
| | - Kevin N Laland
- Centre for Biodiversity, School of Biology, University of St Andrews, Harold Mitchell Building, St Andrews, Fife, UK, KY16 9TH
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21
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Webster MM, Whalen A, Laland KN. Fish pool their experience to solve problems collectively. Nat Ecol Evol 2017; 1:135. [DOI: 10.1038/s41559-017-0135] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2016] [Accepted: 03/09/2017] [Indexed: 11/09/2022]
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Abstract
November 7-9, 2016 witnessed a joint discussion meeting of the Royal Society and the British Academy (the UK national academies for the sciences and social sciences, respectively) entitled 'New Trends in Evolutionary Biology: Biological, Philosophical and Social Science Perspectives'. The meeting, anticipated with a mix of feverish enthusiasm and dread, sold out months in advance, the eager audience perhaps expecting radical and traditional evolutionists to go toe to toe, rather than the constructive dialogue among biologists, social scientists, and researchers in the humanities that the academies advertised. One issue under discussion was whether or not the explanatory core of evolutionary biology requires updating in the light on recent advances in evo-devo, epigenetics, ecosystem ecology, and elsewhere.
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Affiliation(s)
- Kevin N Laland
- Centre for Biological Diversity, School of Biology, University of St Andrews, Fife, UK.
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23
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van der Post DJ, Franz M, Laland KN. The evolution of social learning mechanisms and cultural phenomena in group foragers. BMC Evol Biol 2017; 17:49. [PMID: 28187705 PMCID: PMC5303232 DOI: 10.1186/s12862-017-0889-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2016] [Accepted: 01/18/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Advanced cognitive abilities are widely thought to underpin cultural traditions and cumulative cultural change. In contrast, recent simulation models have found that basic social influences on learning suffice to support both cultural phenomena. In the present study we test the predictions of these models in the context of skill learning, in a model with stochastic demographics, variable group sizes, and evolved parameter values, exploring the cultural ramifications of three different social learning mechanisms. RESULTS Our results show that that simple forms of social learning such as local enhancement, can generate traditional differences in the context of skill learning. In contrast, we find cumulative cultural change is supported by observational learning, but not local or stimulus enhancement, which supports the idea that advanced cognitive abilities are important for generating this cultural phenomenon in the context of skill learning. CONCLUSIONS Our results help to explain the observation that animal cultures are widespread, but cumulative cultural change might be rare.
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Affiliation(s)
- Daniel J van der Post
- Center for Social Learning and Cognitive Evolution, School of Biology, St Andrews University, Harold Mitchell Building, St Andrews, KY16 9TH, UK.
| | - Mathias Franz
- Leibniz Institute for Zoo and Wildlife Research, Alfred-Kowalke-Straße 17, Berlin, 10315, Germany
| | - Kevin N Laland
- Center for Social Learning and Cognitive Evolution, School of Biology, St Andrews University, Harold Mitchell Building, St Andrews, KY16 9TH, UK
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24
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Abstract
Innovative behaviour in animals, ranging from invertebrates to humans, is increasingly recognized as an important topic for investigation by behavioural researchers. However, what constitutes an innovation remains controversial, and difficult to quantify. Drawing on a broad definition whereby any behaviour with a new component to it is an innovation, we propose a quantitative measure, which we call the magnitude of innovation, to describe the extent to which an innovative behaviour is novel. This allows us to distinguish between innovations that are a slight change to existing behaviours (low magnitude), and innovations that are substantially different (high magnitude). Using mathematical modelling and evolutionary computer simulations, we explored how aspects of social interaction, cognition and natural selection affect the frequency and magnitude of innovation. We show that high-magnitude innovations are likely to arise regularly even if the frequency of innovation is low, as long as this frequency is relatively constant, and that the selectivity of social learning and the existence of social rewards, such as prestige and royalties, are crucial for innovative behaviour to evolve. We suggest that consideration of the magnitude of innovation may prove a useful tool in the study of the evolution of cognition and of culture.
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Affiliation(s)
- Michal Arbilly
- Department of Biology, Emory University, Atlanta, GA 30322, USA
| | - Kevin N Laland
- School of Biology, University of St Andrews, Harold Mitchell Building, St Andrews, Fife KY16 9TH, UK
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25
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Abstract
I introduce seven criteria for determining the validity of competing theories for the original function of language. I go on to present a novel explanation that meets all the criteria: language originally evolved to teach kin. I suggest that the use of symbols subsequently generated evolutionary feedback at two levels, in the form of self-modified selection pressures that favored structures in the mind that functioned to manipulate and use symbols with efficiency, and cultural selection on languages for learnability.
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Affiliation(s)
- Kevin N Laland
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St Andrews, Harold Mitchell Building, St Andrews, Fife, KY16 9TH, Scotland, UK.
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26
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Templeton CN, Philp K, Guillette LM, Laland KN, Benson-Amram S. Sex and pairing status impact how zebra finches use social information in foraging. Behav Processes 2016; 139:38-42. [PMID: 28013062 DOI: 10.1016/j.beproc.2016.12.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2016] [Revised: 12/15/2016] [Accepted: 12/19/2016] [Indexed: 10/20/2022]
Abstract
Many factors, including the demonstrator's sex, status, and familiarity, shape the nature and magnitude of social learning. Given the important role of pair bonds in socially-monogamous animals, we predicted that these intimate relationships would promote the use of social information, and tested this hypothesis in zebra finches (Taeniopygia guttata). Observer birds witnessed either their mate or another familiar, opposite-sex bird eat from one, but not a second novel food source, before being allowed to feed from both food sources themselves. Birds used social information to make foraging decisions, but not all individuals used this information in the same way. While most individuals copied the foraging choice of the demonstrator as predicted, paired males did not, instead avoiding the feeder demonstrated by their mate. Our findings reveal that sex and pairing status interact to influence the use of social information and suggest that paired males might use social information to avoid competing with their mate.
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Affiliation(s)
- Christopher N Templeton
- School of Biology, University of St Andrews, St Andrews, Fife, KY169TH, UK; Biology Department, Pacific University, Forest Grove, OR, 97116, USA.
| | - Katharine Philp
- School of Biology, University of St Andrews, St Andrews, Fife, KY169TH, UK
| | - Lauren M Guillette
- School of Biology, University of St Andrews, St Andrews, Fife, KY169TH, UK
| | - Kevin N Laland
- School of Biology, University of St Andrews, St Andrews, Fife, KY169TH, UK
| | - Sarah Benson-Amram
- School of Biology, University of St Andrews, St Andrews, Fife, KY169TH, UK; Department of Zoology and Physiology and Program in Ecology, University of Wyoming, Laramie, WY, 82071, USA
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27
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Cross CP, Brown GR, Morgan TJH, Laland KN. Sex differences in confidence influence patterns of conformity. Br J Psychol 2016; 108:655-667. [DOI: 10.1111/bjop.12232] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2016] [Revised: 10/12/2016] [Indexed: 10/20/2022]
Affiliation(s)
- Catharine P. Cross
- School of Psychology & Neuroscience; University of St Andrews; UK
- Centre for Social Learning and Cognitive Evolution; School of Biology; University of St Andrews; UK
| | - Gillian R. Brown
- School of Psychology & Neuroscience; University of St Andrews; UK
| | - Thomas J. H. Morgan
- Centre for Social Learning and Cognitive Evolution; School of Biology; University of St Andrews; UK
- Department of Psychology; University of California; Berkeley California USA
| | - Kevin N. Laland
- Centre for Social Learning and Cognitive Evolution; School of Biology; University of St Andrews; UK
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28
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Abstract
Background Social learning is potentially advantageous, but evolutionary theory predicts that (i) its benefits may be self-limiting because social learning can lead to information parasitism, and (ii) these limitations can be mitigated via forms of selective copying. However, these findings arise from a functional approach in which learning mechanisms are not specified, and which assumes that social learning avoids the costs of asocial learning but does not produce information about the environment. Whether these findings generalize to all kinds of social learning remains to be established. Using a detailed multi-scale evolutionary model, we investigate the payoffs and information production processes of specific social learning mechanisms (including local enhancement, stimulus enhancement and observational learning) and their evolutionary consequences in the context of skill learning in foraging groups. Results We find that local enhancement does not benefit foraging success, but could evolve as a side-effect of grouping. In contrast, stimulus enhancement and observational learning can be beneficial across a wide range of environmental conditions because they generate opportunities for new learning outcomes. Conclusions In contrast to much existing theory, we find that the functional outcomes of social learning are mechanism specific. Social learning nearly always produces information about the environment, and does not always avoid the costs of asocial learning or support information parasitism. Our study supports work emphasizing the value of incorporating mechanistic detail in functional analyses. Electronic supplementary material The online version of this article (doi:10.1186/s12862-016-0742-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Daniel J van der Post
- Center for Social Learning and Cognitive Evolution, School of Biology, St Andrews University, Harold Mitchell Building, St Andrews, KY16 9TH, UK.
| | - Mathias Franz
- Leibniz Institute for Zoo and Wildlife Research, Alfred-Kowalke-Straße 17, Berlin, 10315, Germany
| | - Kevin N Laland
- Center for Social Learning and Cognitive Evolution, School of Biology, St Andrews University, Harold Mitchell Building, St Andrews, KY16 9TH, UK
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29
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Laland KN, Uller T, Feldman MW, Sterelny K, Müller GB, Moczek A, Jablonka E, Odling-Smee J. The extended evolutionary synthesis: its structure, assumptions and predictions. Proc Biol Sci 2016; 282:20151019. [PMID: 26246559 DOI: 10.1098/rspb.2015.1019] [Citation(s) in RCA: 331] [Impact Index Per Article: 41.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Scientific activities take place within the structured sets of ideas and assumptions that define a field and its practices. The conceptual framework of evolutionary biology emerged with the Modern Synthesis in the early twentieth century and has since expanded into a highly successful research program to explore the processes of diversification and adaptation. Nonetheless, the ability of that framework satisfactorily to accommodate the rapid advances in developmental biology, genomics and ecology has been questioned. We review some of these arguments, focusing on literatures (evo-devo, developmental plasticity, inclusive inheritance and niche construction) whose implications for evolution can be interpreted in two ways—one that preserves the internal structure of contemporary evolutionary theory and one that points towards an alternative conceptual framework. The latter, which we label the 'extended evolutionary synthesis' (EES), retains the fundaments of evolutionary theory, but differs in its emphasis on the role of constructive processes in development and evolution, and reciprocal portrayals of causation. In the EES, developmental processes, operating through developmental bias, inclusive inheritance and niche construction, share responsibility for the direction and rate of evolution, the origin of character variation and organism-environment complementarity. We spell out the structure, core assumptions and novel predictions of the EES, and show how it can be deployed to stimulate and advance research in those fields that study or use evolutionary biology.
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Affiliation(s)
- Kevin N Laland
- School of Biology, University of St Andrews, St Andrews, Fife, UK
| | - Tobias Uller
- Edward Grey Institute, Department of Zoology, University of Oxford, Oxford, UK Department of Biology, University of Lund, Lund, Sweden
| | - Marcus W Feldman
- Department of Biology, Stanford University, Herrin Hall, Stanford, CA 94305, USA
| | - Kim Sterelny
- School of Philosophy, Australian National University, Canberra, Australia School of History, Philosophy, Political Science and International Relations, Victoria University of Wellington, Wellington, New Zealand
| | - Gerd B Müller
- Department of Theoretical Biology, University of Vienna, Vienna, Austria
| | - Armin Moczek
- Department of Biology, Indiana University, Bloomington, IN 47405-7107, USA
| | - Eva Jablonka
- Cohn Institute for the History of Philosophy of Science and Ideas, Tel Aviv University, Tel Aviv, Israel
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30
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Navarrete AF, Reader SM, Street SE, Whalen A, Laland KN. The coevolution of innovation and technical intelligence in primates. Philos Trans R Soc Lond B Biol Sci 2016; 371:20150186. [PMID: 26926276 PMCID: PMC4780528 DOI: 10.1098/rstb.2015.0186] [Citation(s) in RCA: 69] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/23/2015] [Indexed: 01/04/2023] Open
Abstract
In birds and primates, the frequency of behavioural innovation has been shown to covary with absolute and relative brain size, leading to the suggestion that large brains allow animals to innovate, and/or that selection for innovativeness, together with social learning, may have driven brain enlargement. We examined the relationship between primate brain size and both technical (i.e. tool using) and non-technical innovation, deploying a combination of phylogenetically informed regression and exploratory causal graph analyses. Regression analyses revealed that absolute and relative brain size correlated positively with technical innovation, and exhibited consistently weaker, but still positive, relationships with non-technical innovation. These findings mirror similar results in birds. Our exploratory causal graph analyses suggested that technical innovation shares strong direct relationships with brain size, body size, social learning rate and social group size, whereas non-technical innovation did not exhibit a direct relationship with brain size. Nonetheless, non-technical innovation was linked to brain size indirectly via diet and life-history variables. Our findings support 'technical intelligence' hypotheses in linking technical innovation to encephalization in the restricted set of primate lineages where technical innovation has been reported. Our findings also provide support for a broad co-evolving complex of brain, behaviour, life-history, social and dietary variables, providing secondary support for social and ecological intelligence hypotheses. The ability to gain access to difficult-to-extract, but potentially nutrient-rich, resources through tool use may have conferred on some primates adaptive advantages, leading to selection for brain circuitry that underlies technical proficiency.
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Affiliation(s)
- Ana F Navarrete
- School of Biology, University of St Andrews, St Andrews, Fife KY16 9TS, UK
| | - Simon M Reader
- Department of Biology, McGill University, 1205 Doctor Penfield Avenue, Montreal, Quebec H3A 1B1, Canada
| | - Sally E Street
- School of Biology, University of St Andrews, St Andrews, Fife KY16 9TS, UK School of Biological, Biomedical and Environmental Sciences, University of Hull, Cottingham Road, Kingston upon Hull, Yorkshire HU6 7RX, UK
| | - Andrew Whalen
- School of Biology, University of St Andrews, St Andrews, Fife KY16 9TS, UK
| | - Kevin N Laland
- School of Biology, University of St Andrews, St Andrews, Fife KY16 9TS, UK
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31
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Nightingale GF, Laland KN, Hoppitt W, Nightingale P. Bayesian Spatial NBDA for Diffusion Data with Home-Base Coordinates. PLoS One 2015; 10:e0130326. [PMID: 26135317 PMCID: PMC4489808 DOI: 10.1371/journal.pone.0130326] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2014] [Accepted: 05/19/2015] [Indexed: 11/18/2022] Open
Abstract
Network-based diffusion analysis (NBDA) is a statistical method that allows the researcher to identify and quantify a social influence on the spread of behaviour through a population. Hitherto, NBDA analyses have not directly modelled spatial population structure. Here we present a spatial extension of NBDA, applicable to diffusion data where the spatial locations of individuals in the population, or of their home bases or nest sites, are available. The method is based on the estimation of inter-individual associations (for association matrix construction) from the mean inter-point distances as represented on a spatial point pattern of individuals, nests or home bases. We illustrate the method using a simulated dataset, and show how environmental covariates (such as that obtained from a satellite image, or from direct observations in the study area) can also be included in the analysis. The analysis is conducted in a Bayesian framework, which has the advantage that prior knowledge of the rate at which the individuals acquire a given task can be incorporated into the analysis. This method is especially valuable for studies for which detailed spatially structured data, but no other association data, is available. Technological advances are making the collection of such data in the wild more feasible: for example, bio-logging facilitates the collection of a wide range of variables from animal populations in the wild. We provide an R package, spatialnbda, which is hosted on the Comprehensive R Archive Network (CRAN). This package facilitates the construction of association matrices with the spatial x and y coordinates as the input arguments, and spatial NBDA analyses.
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Affiliation(s)
- Glenna F. Nightingale
- School of Geography and Geosciences, University of St. Andrews, St. Andrews, Scotland, United Kingdom
- * E-mail:
| | - Kevin N. Laland
- School of Biology, University of St. Andrews, St. Andrews, Scotland, United Kingdom
| | - William Hoppitt
- School of Life Sciences, Anglia Ruskin University, Cambridge, England, United Kingdom
| | - Peter Nightingale
- School of Computer Science, University of St. Andrews, St. Andrews, Scotland, United Kingdom
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Atton N, Galef BJ, Hoppitt W, Webster MM, Laland KN. Familiarity affects social network structure and discovery of prey patch locations in foraging stickleback shoals. Proc Biol Sci 2015; 281:20140579. [PMID: 25009061 PMCID: PMC4100505 DOI: 10.1098/rspb.2014.0579] [Citation(s) in RCA: 59] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Numerous factors affect the fine-scale social structure of animal groups, but it is unclear how important such factors are in determining how individuals encounter resources. Familiarity affects shoal choice and structure in many social fishes. Here, we show that familiarity between shoal members of sticklebacks (Gasterosteus aculeatus) affects both fine-scale social organization and the discovery of resources. Social network analysis revealed that sticklebacks remained closer to familiar than to unfamiliar individuals within the same shoal. Network-based diffusion analysis revealed that there was a strong untransmitted social effect on patch discovery, with individuals tending to discover a task sooner if a familiar individual from their group had previously done so than if an unfamiliar fish had done so. However, in contrast to the effect of familiarity, the frequency with which individuals had previously associated with one another had no effect upon the likelihood of prey patch discovery. This may have been due to the influence of fish on one another's movements; the effect of familiarity on discovery of an empty ‘control’ patch was as strong as for discovery of an actual prey patch. Our results demonstrate that factors affecting fine-scale social interactions can also influence how individuals encounter and exploit resources.
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Affiliation(s)
- N Atton
- School of Biology, University of St Andrews, Harold Mitchell Building, Fife KY16 9TH, UK
| | - B J Galef
- Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, Ontario, Canada L8S 4K1
| | - W Hoppitt
- Animal and Environment Research Group, Anglia Ruskin University, Cambridge CB1 1PT, UK
| | - M M Webster
- School of Biology, University of St Andrews, Harold Mitchell Building, Fife KY16 9TH, UK
| | - K N Laland
- School of Biology, University of St Andrews, Harold Mitchell Building, Fife KY16 9TH, UK
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Morgan TJ, Laland KN, Harris PL. The development of adaptive conformity in young children: effects of uncertainty and consensus. Dev Sci 2014; 18:511-24. [DOI: 10.1111/desc.12231] [Citation(s) in RCA: 68] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2013] [Accepted: 07/10/2014] [Indexed: 11/28/2022]
Affiliation(s)
- Thomas J.H. Morgan
- Centre for Social Learning and Cognitive Evolution; School of Biology; University of St Andrews; UK
- Department of Psychology; University of California; Berkeley USA
| | - Kevin N. Laland
- Centre for Social Learning and Cognitive Evolution; School of Biology; University of St Andrews; UK
| | - Paul L. Harris
- Harvard Graduate School of Education; Harvard University; USA
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Boogert NJ, Nightingale GF, Hoppitt W, Laland KN. Perching but not foraging networks predict the spread of novel foraging skills in starlings. Behav Processes 2014; 109 Pt B:135-44. [PMID: 25178191 DOI: 10.1016/j.beproc.2014.08.016] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2014] [Revised: 08/01/2014] [Accepted: 08/19/2014] [Indexed: 11/16/2022]
Abstract
The directed social learning hypothesis suggests that information does not spread evenly through animal groups, but rather individual characteristics and patterns of physical proximity guide the social transmission of information along specific pathways. Network-based diffusion analysis (NBDA) allows researchers to test whether information spreads following a social network. However, the explanatory power of different social networks has rarely been compared, and current models do not easily accommodate random effects (e.g. allowing for individuals within groups to correlate in their asocial solving rates). We tested whether the spread of two novel foraging skills through captive starling groups was affected by individual- and group-level random and fixed effects (i.e. sex, age, body condition, dominance rank and demonstrator status) and perching or foraging networks. We extended NBDA to include random effects and conducted model discrimination in a Bayesian context. We found that social learning increased the rate at which birds acquired the novel foraging task solutions by 6.67 times, and acquiring one of the two novel foraging task solutions facilitated the asocial acquisition of the other. Surprisingly, the spread of task solutions followed the perching rather than the foraging social network. Upon acquiring a task solution, foraging performance was facilitated by the presence of group mates. Our results highlight the importance of considering more than one social network when predicting the spread of information through animal groups. This article is part of a Special Issue entitled: Cognition in the wild.
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Affiliation(s)
- Neeltje J Boogert
- School of Psychology and Neuroscience, University of St. Andrews, St Andrews, UK.
| | | | - William Hoppitt
- Department of Life Sciences, Anglia Ruskin University, Cambridge, UK
| | - Kevin N Laland
- School of Biology, University of St. Andrews, St Andrews, UK
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Abstract
In this essay I consider how biologists understand 'causation' and 'evolutionary process', drawing attention to some idiosyncrasies in the use of these terms. I suggest that research within the evolutionary sciences has been channeled in certain directions and not others by scientific conventions, many of which have now become counterproductive. These include the views (i) that evolutionary processes are restricted to those phenomena that directly change gene frequencies, (ii) that understanding the causes of both ecological change and ontogeny is beyond the remit of evolutionary biology, and (iii) that biological causation can be understood by a dichotomous proximate-ultimate distinction, with developmental processes perceived as solely relevant to proximate causation. I argue that the notion of evolutionary process needs to be broadened to accommodate phenomena such as developmental bias and niche construction that bias the course of evolution, but do not directly change gene frequencies, and that causation in biological systems is fundamentally reciprocal in nature. This article is part of a Special Issue entitled: In Honor of Jerry Hogan.
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Affiliation(s)
- Kevin N Laland
- School of Biology, University of St Andrews, United Kingdom.
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36
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Laland KN, Plotkin HC. Further experimental analysis of the social learning and transmission of foraging information amongst Norway rats. Behav Processes 2014; 27:53-64. [PMID: 24896467 DOI: 10.1016/0376-6357(92)90040-k] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/06/1992] [Indexed: 11/18/2022]
Abstract
Adult male Norway rats were tested to see if their foraging efficiency could be improved by social learning and to investigate whether foraging information could be socially transmitted along a chain of animals. In Experiment 1, 'observers' were placed in one of four conditions, distinguished by the nature of their experience during an observation phase, in which they either observed: (1) a trained conspecific unearthing buried carrot; (2) a trained conspecific digging; (3) carrot pieces only; or (4) an empty enclosure (the control group). When tested 24 h later it was found that subjects in group 1 alone exhibited a significantly elevated foraging ability relative to the control group, being more active, and unearthing more carrot pieces in total. The results show that perception of a trained demonstrator conspecific successfully foraging for food is necessary for social learning of foraging information to occur, probably by a local enhancement mechanism. In Experiment 2, chains of transmission were established by allowing each observer to act 24 h later as the demonstrator for the next observer. In one of two transmission groups subjects were given an extra period of individual foraging experience in the test enclosure, with no demonstrator present. Enhanced levels of foraging efficiency were maintained across eight transmission episodes for both transmission groups relative to a no-transmission control. Subjects in the group with the additional experience unearthed significantly more buried food than subjects in the other transmission group. The experiments extend our standard transmission group was upheld. The superior performance of demonstrators in this group, as reflected in their higher level of carrot digging, suggests that the extra period of experience did indeed enhance their ability to act as effective demonstrators. The elevated performance of subjects in this group is attributed to a combination of social and individual learning. This finding suggests that the stability of social transmission may, under some circumstances, be bolstered by individual reinforcement of socially learned and enhanced patterns of behaviour. It also lends support to the hypothesis, proposed to account for the findings of our earlier study, that motivational factors such as fatigue, may detract from subjects' performance as demonstrators when this demonstration follows closely after the additional period of individual experience, but that a 24 h period is sufficient to allow such motivational factors to decay. If individual experience can buttress socially learned traits then this interaction may act so as to prolong the period of time that a socially transmitted trait remains in a population. It is conceivable that an additional period of foraging longer than 10 min may further enhance subjects' subsequent performance as demonstrators. The complex relationship between individual and social learning has received little attention. It is not clear how, if at all, social learning is different from other forms of learning (Plotkin, 1988), apart from the obvious requirement that another animal somehow be involved in the social learning process. Boyd and Richerson (1985) argue that social and individual learning are, at least in humans, alternative ways of acquiring a particular behavioural variant. Most recent studies of animal social learning, on the other hand, tend to emphasize the stimulus enhancing role of the demonstrator animal (Galef, 1988a), thereby suggesting that social learning is a sub-category of individual learning. This study shows that individual learning can reinforce the acquisition and expression of socially acquired behavioural variants.
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Affiliation(s)
- K N Laland
- Department of Psychology, University College London, Gower Street, London, UK
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Scott-Phillips TC, Laland KN, Shuker DM, Dickins TE, West SA. The niche construction perspective: a critical appraisal. Evolution 2014; 68:1231-43. [PMID: 24325256 PMCID: PMC4261998 DOI: 10.1111/evo.12332] [Citation(s) in RCA: 89] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2013] [Accepted: 11/27/2013] [Indexed: 12/05/2022]
Abstract
Niche construction refers to the activities of organisms that bring about changes in their environments, many of which are evolutionarily and ecologically consequential. Advocates of niche construction theory (NCT) believe that standard evolutionary theory fails to recognize the full importance of niche construction, and consequently propose a novel view of evolution, in which niche construction and its legacy over time (ecological inheritance) are described as evolutionary processes, equivalent in importance to natural selection. Here, we subject NCT to critical evaluation, in the form of a collaboration between one prominent advocate of NCT, and a team of skeptics. We discuss whether niche construction is an evolutionary process, whether NCT obscures or clarifies how natural selection leads to organismal adaptation, and whether niche construction and natural selection are of equivalent explanatory importance. We also consider whether the literature that promotes NCT overstates the significance of niche construction, whether it is internally coherent, and whether it accurately portrays standard evolutionary theory. Our disagreements reflect a wider dispute within evolutionary theory over whether the neo-Darwinian synthesis is in need of reformulation, as well as different usages of some key terms (e.g., evolutionary process).
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Abstract
Humans have a form of externalised memory. They are able to transmit information across generations in the form of learned cultural traditions and preserve this knowledge in artefacts. How this capability evolved from the simpler traditions of other animals is an active area of research.
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Affiliation(s)
- Kevin N Laland
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St Andrews, UK.
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40
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Bateson P, Laland KN. On current utility and adaptive significance: a response to Nesse. Trends Ecol Evol 2013; 28:682-3. [DOI: 10.1016/j.tree.2013.10.009] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2013] [Revised: 10/18/2013] [Accepted: 10/18/2013] [Indexed: 10/26/2022]
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Bateson P, Laland KN. Tinbergen's four questions: an appreciation and an update. Trends Ecol Evol 2013; 28:712-8. [PMID: 24144467 DOI: 10.1016/j.tree.2013.09.013] [Citation(s) in RCA: 166] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2013] [Revised: 09/16/2013] [Accepted: 09/20/2013] [Indexed: 01/01/2023]
Abstract
This year is the 50th anniversary of Tinbergen's (1963) article 'On aims and methods of ethology', where he first outlined the four 'major problems of biology'. The classification of the four problems, or questions, is one of Tinbergen's most enduring legacies, and it remains as valuable today as 50 years ago in highlighting the value of a comprehensive, multifaceted understanding of a characteristic, with answers to each question providing complementary insights. Nonetheless, much has changed in the intervening years, and new data call for a more nuanced application of Tinbergen's framework. The anniversary would seem a suitable opportunity to reflect on the four questions and evaluate the scientific work that they encourage.
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Affiliation(s)
- Patrick Bateson
- Subdepartment of Animal Behaviour, University of Cambridge, Madingley, Cambridge, CB23 8AA, UK
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42
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Dean LG, Vale GL, Laland KN, Flynn E, Kendal RL. Human cumulative culture: a comparative perspective. Biol Rev Camb Philos Soc 2013; 89:284-301. [PMID: 24033987 DOI: 10.1111/brv.12053] [Citation(s) in RCA: 172] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2012] [Revised: 06/24/2012] [Accepted: 07/30/2013] [Indexed: 11/27/2022]
Abstract
Many animals exhibit social learning and behavioural traditions, but human culture exhibits unparalleled complexity and diversity, and is unambiguously cumulative in character. These similarities and differences have spawned a debate over whether animal traditions and human culture are reliant on homologous or analogous psychological processes. Human cumulative culture combines high-fidelity transmission of cultural knowledge with beneficial modifications to generate a 'ratcheting' in technological complexity, leading to the development of traits far more complex than one individual could invent alone. Claims have been made for cumulative culture in several species of animals, including chimpanzees, orangutans and New Caledonian crows, but these remain contentious. Whilst initial work on the topic of cumulative culture was largely theoretical, employing mathematical methods developed by population biologists, in recent years researchers from a wide range of disciplines, including psychology, biology, economics, biological anthropology, linguistics and archaeology, have turned their attention to the experimental investigation of cumulative culture. We review this literature, highlighting advances made in understanding the underlying processes of cumulative culture and emphasising areas of agreement and disagreement amongst investigators in separate fields.
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Affiliation(s)
- Lewis G Dean
- School of Biology, Centre for Social Learning and Cognitive Evolution, University of St. Andrews, Queen's Terrace, St. Andrews, Fife, KY16 9TS, U.K
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Odling-Smee J, Erwin DH, Palkovacs EP, Feldman MW, Laland KN. Niche construction theory: a practical guide for ecologists. Q Rev Biol 2013; 88:4-28. [PMID: 23653966 DOI: 10.1086/669266] [Citation(s) in RCA: 269] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Niche construction theory (NCT) explicitly recognizes environmental modication by organisms ("niche construction") and their legacy overtime ("ecological inheritance") to be evolutionary processes in their own right. Here we illustrate how niche construction theory provides usedl conceptual tools and theoretical insights for integrating ecosystem ecology and evolutionary theory. We begin by briefly describing NCT, and illustrating how it deifers from conventional evolutionary approaches. We then distinguish between two aspects ofniche construction--environment alteration and subsequent evolution in response to constructed environments--equating the first of these with "ecosystem engineering." We describe some of the ecological and evolutionary impacts on ecosystems of niche construction, ecosystem engineering and ecological inheritance, and illustrate how these processes trigger ecological and evolutionary feedbacks and leave detectable ecological signatures that are open to investigation. FIinally, we provide a practical guide to how NCT could be deployed by ecologists and evolutionary biologists to aeplore ecoeoolutionay dynamics. We suggest that, by highlighting the ecological and evolutionay ramifications of changes that organisms bring about in ecosystems, NCT helps link ecosystem ecology to evolutionary biology, potentially leading to a deeper understanding of how ecosystems change over time.
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Laland KN, Odling-Smee J, Hoppitt W, Uller T. More on how and why: a response to commentaries. Biol Philos 2013; 28:793-810. [PMID: 23970808 DOI: 10.1007/s10539-012-9335-1] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2013] [Accepted: 04/24/2013] [Indexed: 05/28/2023]
Abstract
We are grateful to the commentators for taking the time to respond to our article. Too many interesting and important points have been raised for us to tackle them all in this response, and so in the below we have sought to draw out the major themes. These include problems with both the term 'ultimate causation' and the proximate-ultimate causation dichotomy more generally, clarification of the meaning of reciprocal causation, discussion of issues related to the nature of development and phenotypic plasticity and their roles in evolution, and consideration of the need for an extended evolutionary synthesis.
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Affiliation(s)
- Kevin N Laland
- School of Biology, University of St Andrews, St Andrews, UK
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45
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Laland KN, Odling-Smee J, Hoppitt W, Uller T. More on how and why: a response to commentaries. Biol Philos 2013; 28:793-810. [PMID: 23970808 PMCID: PMC3745615 DOI: 10.1007/s10539-013-9380-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2013] [Accepted: 04/24/2013] [Indexed: 06/02/2023]
Abstract
We are grateful to the commentators for taking the time to respond to our article. Too many interesting and important points have been raised for us to tackle them all in this response, and so in the below we have sought to draw out the major themes. These include problems with both the term 'ultimate causation' and the proximate-ultimate causation dichotomy more generally, clarification of the meaning of reciprocal causation, discussion of issues related to the nature of development and phenotypic plasticity and their roles in evolution, and consideration of the need for an extended evolutionary synthesis.
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Affiliation(s)
| | | | - William Hoppitt
- Department of Life Sciences, Anglia Ruskin University, Cambridge, UK
| | - Tobias Uller
- Department of Zoology, Edward Grey Institute, University of Oxford, Oxford, UK
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Flynn EG, Laland KN, Kendal RL, Kendal JR. Target Article with Commentaries: Developmental niche construction. Dev Sci 2013; 16:296-313. [DOI: 10.1111/desc.12030] [Citation(s) in RCA: 102] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2012] [Accepted: 07/31/2012] [Indexed: 01/09/2023]
Affiliation(s)
- Emma G. Flynn
- Centre for the Coevolution of Biology and Culture, Department of Psychology; Durham University; UK
| | | | - Rachel L. Kendal
- Centre for the Coevolution of Biology and Culture, Department of Anthropology; Durham University; UK
| | - Jeremy R. Kendal
- Centre for the Coevolution of Biology and Culture, Department of Anthropology; Durham University; UK
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Webster MM, Atton N, Hoppitt WJE, Laland KN. Environmental complexity influences association network structure and network-based diffusion of foraging information in fish shoals. Am Nat 2013; 181:235-44. [PMID: 23348777 DOI: 10.1086/668825] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Socially transmitted information can significantly affect the ways in which animals interact with their environments. We used network-based diffusion analysis, a novel and powerful tool for exploring information transmission, to model the rate at which sticklebacks (Gasterosteus aculeatus) discovered prey patches, comparing shoals foraging in open and structured environments. We found that for groups in the open environment, individuals tended to recruit to both the prey patch and empty comparison patches at similar times, suggesting that patch discovery was not greatly affected by direct social transmission. In contrast, in structured environments we found strong evidence that information about prey patch location was socially transmitted and moreover that the pathway of information transmission followed the shoals' association network structures. Our findings highlight the importance of considering habitat structure when investigating the diffusion of information through populations and imply that association networks take on greater ecological significance in structured than open environments.
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Affiliation(s)
- Mike M Webster
- School of Biology, University of St. Andrews, St. Andrews, Fife KY16 9TF, United Kingdom.
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48
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Abstract
Many animals have socially transmitted behavioural traditions, but human culture appears unique in that it is cumulative, i.e. human cultural traits increase in diversity and complexity over time. It is often suggested that high-fidelity cultural transmission is necessary for cumulative culture to occur through refinement, a process known as 'ratcheting', but this hypothesis has never been formally evaluated. We discuss processes of information transmission and loss of traits from a cognitive viewpoint alongside other cultural processes of novel invention (generation of entirely new traits), modification (refinement of existing traits) and combination (bringing together two established traits to generate a new trait). We develop a simple cultural transmission model that does not assume major evolutionary changes (e.g. in brain architecture) and show that small changes in the fidelity with which information is passed between individuals can lead to cumulative culture. In comparison, modification and combination have a lesser influence on, and novel invention appears unimportant to, the ratcheting process. Our findings support the idea that high-fidelity transmission is the key driver of human cumulative culture, and that progress in cumulative culture depends more on trait combination than novel invention or trait modification.
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Affiliation(s)
- Hannah M Lewis
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St Andrews, Bute Medical Building, Queen's Terrace, St Andrews, Fife KY16 9TS, UK.
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Atton N, Hoppitt W, Webster MM, Galef BG, Laland KN. Information flow through threespine stickleback networks without social transmission. Proc Biol Sci 2012; 279:4272-8. [PMID: 22896644 DOI: 10.1098/rspb.2012.1462] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Social networks can result in directed social transmission of learned information, thus influencing how innovations spread through populations. Here we presented shoals of threespine sticklebacks (Gasterosteous aculeatus) with two identical foraging tasks and applied network-based diffusion analysis (NBDA) to determine whether the order in which individuals in a social group contacted and solved the tasks was affected by the group's network structure. We found strong evidence for a social effect on discovery of the foraging tasks with individuals tending to discover a task sooner when others in their group had previously done so, and with the spread of discovery of the foraging tasks influenced by groups' social networks. However, the same patterns of association did not reliably predict spread of solution to the tasks, suggesting that social interactions affected the time at which the tasks were discovered, but not the latency to its solution following discovery. The present analysis, one of the first applications of NBDA to a natural animal system, illustrates how NBDA can lead to insight into the mechanisms supporting behaviour acquisition that more conventional statistical approaches might miss. Importantly, we provide the first compelling evidence that the spread of novel behaviours can result from social learning in the absence of social transmission, a phenomenon that we refer to as an untransmitted social effect on learning.
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Affiliation(s)
- N Atton
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St Andrews, Queen's Terrace, St Andrews KY16 9TS, UK.
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50
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Abstract
Vigorous debates as to the evolutionary origins of culture remain unresolved due to an absence of methods for identifying learning mechanisms in natural populations. While laboratory experiments on captive animals have revealed evidence for a number of mechanisms, these may not necessarily reflect the processes typically operating in nature. We developed a novel method that allows social and asocial learning mechanisms to be determined in animal groups from the patterns of interaction with, and solving of, a task. We deployed it to analyse learning in groups of wild meerkats (Suricata suricatta) presented with a novel foraging apparatus. We identify nine separate learning processes underlying the meerkats’ foraging behaviour, in each case precisely quantifying their strength and duration, including local enhancement, emulation, and a hitherto unrecognized form of social learning, which we term ‘observational perseverance’. Our analysis suggests a key factor underlying the stability of behavioural traditions is a high ratio of specific to generalized social learning effects. The approach has widespread potential as an ecologically valid tool to investigate learning mechanisms in natural groups of animals, including humans.
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Affiliation(s)
- Will Hoppitt
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St. Andrews, St. Andrews, Fife, United Kingdom
- * E-mail:
| | - Jamie Samson
- Kalahari Meerkat Project, Kuruman River Reserve, Van Zylsrus, Northern Cape, South Africa
| | - Kevin N. Laland
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St. Andrews, St. Andrews, Fife, United Kingdom
| | - Alex Thornton
- Department of Zoology, University of Cambridge, Cambridge, United Kingdom
- Department of Experimental Psychology, University of Cambridge, Cambridge, United Kingdom
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