A semi-automatic approach to study population dynamics based on population pyramids
This provides a semi-automatic tool for analyzing and communicating historical population developments, potentially useful for animal population management, but it is incremental as it formalizes existing visual concepts algorithmically.
The authors tackled the problem of analyzing population dynamics by developing an algorithm to classify population data into specific pyramid shapes linked to population characteristics, using global zoo mammal data from 1970-2024, and found it delivers plausible classifications for changes in population size.
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.