A semi-automatic approach to study population dynamics based on population pyramids
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arXiv
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| Format: | Preprint |
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2025
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| author | Hahn-Klimroth, Max Meireles, João Pedro Lackey, Laurie Bingaman Bertelsen, Nick van Eeuwijk Mads F. Dierkes, Paul W. Clauss, Marcus |
| author_facet | Hahn-Klimroth, Max Meireles, João Pedro Lackey, Laurie Bingaman Bertelsen, Nick van Eeuwijk Mads F. Dierkes, Paul W. Clauss, Marcus |
| contents | The depiction of populations - of humans or animals - as "population pyramids" is a useful tool for the assessment of various characteristics of populations at a glance. Although these visualisations are well-known objects in various communities, formalised and algorithmic approaches to gain information from these data are less present. Here, we present an algorithm-based classification of population data into "pyramids" of different shapes ([normal and inverted] pyramid / plunger / bell, [lower / middle / upper] diamond, column, hourglass) that are linked to specific characteristics of the population. To develop the algorithmic approach, we used data describing global zoo populations of mammals from 1970-2024. This algorithm-based approach delivers plausible classifications, in particular with respect to changes in population size linked to specific series of, and transitions between, different "pyramid" shapes. We believe this approach might become a useful tool for analysing and communicating historical population developments in multiple contexts and is of broad interest. Moreover, it might be useful for animal population management strategies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_03788 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A semi-automatic approach to study population dynamics based on population pyramids Hahn-Klimroth, Max Meireles, João Pedro Lackey, Laurie Bingaman Bertelsen, Nick van Eeuwijk Mads F. Dierkes, Paul W. Clauss, Marcus Populations and Evolution Machine Learning Applications 62P25, 62P10 I.2.1 The depiction of populations - of humans or animals - as "population pyramids" is a useful tool for the assessment of various characteristics of populations at a glance. Although these visualisations are well-known objects in various communities, formalised and algorithmic approaches to gain information from these data are less present. Here, we present an algorithm-based classification of population data into "pyramids" of different shapes ([normal and inverted] pyramid / plunger / bell, [lower / middle / upper] diamond, column, hourglass) that are linked to specific characteristics of the population. To develop the algorithmic approach, we used data describing global zoo populations of mammals from 1970-2024. This algorithm-based approach delivers plausible classifications, in particular with respect to changes in population size linked to specific series of, and transitions between, different "pyramid" shapes. We believe this approach might become a useful tool for analysing and communicating historical population developments in multiple contexts and is of broad interest. Moreover, it might be useful for animal population management strategies. |
| title | A semi-automatic approach to study population dynamics based on population pyramids |
| topic | Populations and Evolution Machine Learning Applications 62P25, 62P10 I.2.1 |
| url | https://arxiv.org/abs/2508.03788 |