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Updated: May 16, 2025

Methodology for Developing Life Tables for Sessile Insects in the Field Using the Whitefly, Bemisia tabaci, in Cotton As a Model System
Published on: November 1, 2017
Life tables data collection in entomology: an overview on the differential and the integral representation and
Luca Rossini1, Arthur Lots1, Grégoire Noël2
1Service d'Automatique et d'Analyse des Systèmes, Université Libre de Bruxelles, Brussels, Belgium.
Abstract:
Life tables allow the exploration of insects' and terrestrial arthropods' biology, and how they respond to external factors. Data collection process has been partially standardized, but the presentation of results mainly depends on the purpose of the study. Two different data representations can be obtained from the raw dataset: the differential representation provides the distribution of the stage-development times, while the integral representation provides the number of individuals into the different life stages, over time. The representations provide relevant biological information, but they lead to a loss of information with respect to the raw dataset. To date, a conceptual explanation of how the two representations can be obtained from the raw data, and of their respective properties, is still missing; moreover, providing the raw dataset as supporting information of the published papers is still not customary. This paper highlights three main points: (i) how the two representations are obtained from life tables raw dataset; (ii) without raw data, it is not possible to switch between the two representations, with a subsequent loss of information; and (iii) why there is the need for a data collection standard. The conceptual explanation is further completed by an electronic file that could support data collection and sharing, and that automatically transform the data in the two representations. We believe that this study is a first step toward a more efficient diffusion of the information among the scientific community, maximizing the efforts made by scholars during the experimental and data analysis process.
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