Data-Driven Inference Reveals Distinct and Conserved Dynamic Pathways of Tool Use Emergence across Animal Taxa
Summary: Tool use is a striking aspect of animal behavior, but it is hard to infer how the capacity for different types of tool use emerged across animal taxa. Here we address this question with HyperTraPS, a statistical approach that uses contemporary observations to infer the likely orderings in w...
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2020-06-01
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Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004220304314 |
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doaj-b0fbb6a4eb6f41e5b49d4d0937c59aa42020-11-25T03:11:36ZengElsevieriScience2589-00422020-06-01236101245Data-Driven Inference Reveals Distinct and Conserved Dynamic Pathways of Tool Use Emergence across Animal TaxaIain G. Johnston0Ellen C. Røyrvik1Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Bergen, Bergen, Norway; Alan Turing Institute, London, UK; Corresponding authorDepartment of Clinical Sciences, University of Bergen, Bergen, NorwaySummary: Tool use is a striking aspect of animal behavior, but it is hard to infer how the capacity for different types of tool use emerged across animal taxa. Here we address this question with HyperTraPS, a statistical approach that uses contemporary observations to infer the likely orderings in which different types of tool use (digging, reaching, and more) were historically acquired. Strikingly, despite differences linked to environment and family, many similarities in these appear across animal taxa, suggesting some universality in the process of tool use acquisition across different animals and environments. Four broad classes of tool use are supported, progressing from simple object manipulations (acquired relatively early) to more complex interactions and abstractions (acquired relatively late or not at all). This data-driven, comparative approach supports existing and suggests new mechanistic hypotheses, predicts future and possible unobserved behaviors, and sheds light on patterns of tool use emergence across animals.http://www.sciencedirect.com/science/article/pii/S2589004220304314Biocomputational MethodBioinformaticsEthologyEvolutionary Biology |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Iain G. Johnston Ellen C. Røyrvik |
spellingShingle |
Iain G. Johnston Ellen C. Røyrvik Data-Driven Inference Reveals Distinct and Conserved Dynamic Pathways of Tool Use Emergence across Animal Taxa iScience Biocomputational Method Bioinformatics Ethology Evolutionary Biology |
author_facet |
Iain G. Johnston Ellen C. Røyrvik |
author_sort |
Iain G. Johnston |
title |
Data-Driven Inference Reveals Distinct and Conserved Dynamic Pathways of Tool Use Emergence across Animal Taxa |
title_short |
Data-Driven Inference Reveals Distinct and Conserved Dynamic Pathways of Tool Use Emergence across Animal Taxa |
title_full |
Data-Driven Inference Reveals Distinct and Conserved Dynamic Pathways of Tool Use Emergence across Animal Taxa |
title_fullStr |
Data-Driven Inference Reveals Distinct and Conserved Dynamic Pathways of Tool Use Emergence across Animal Taxa |
title_full_unstemmed |
Data-Driven Inference Reveals Distinct and Conserved Dynamic Pathways of Tool Use Emergence across Animal Taxa |
title_sort |
data-driven inference reveals distinct and conserved dynamic pathways of tool use emergence across animal taxa |
publisher |
Elsevier |
series |
iScience |
issn |
2589-0042 |
publishDate |
2020-06-01 |
description |
Summary: Tool use is a striking aspect of animal behavior, but it is hard to infer how the capacity for different types of tool use emerged across animal taxa. Here we address this question with HyperTraPS, a statistical approach that uses contemporary observations to infer the likely orderings in which different types of tool use (digging, reaching, and more) were historically acquired. Strikingly, despite differences linked to environment and family, many similarities in these appear across animal taxa, suggesting some universality in the process of tool use acquisition across different animals and environments. Four broad classes of tool use are supported, progressing from simple object manipulations (acquired relatively early) to more complex interactions and abstractions (acquired relatively late or not at all). This data-driven, comparative approach supports existing and suggests new mechanistic hypotheses, predicts future and possible unobserved behaviors, and sheds light on patterns of tool use emergence across animals. |
topic |
Biocomputational Method Bioinformatics Ethology Evolutionary Biology |
url |
http://www.sciencedirect.com/science/article/pii/S2589004220304314 |
work_keys_str_mv |
AT iaingjohnston datadriveninferencerevealsdistinctandconserveddynamicpathwaysoftooluseemergenceacrossanimaltaxa AT ellencrøyrvik datadriveninferencerevealsdistinctandconserveddynamicpathwaysoftooluseemergenceacrossanimaltaxa |
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