Modelling daily weight variation in honey bee hives.
A quantitative understanding of the dynamics of bee colonies is important to support global efforts to improve bee health and enhance pollination services. Traditional approaches focus either on theoretical models or data-centred statistical analyses. Here we argue that the combination of these two...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2023-03-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1010880 |
| _version_ | 1811158360364417024 |
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| author | Karina Arias-Calluari Theotime Colin Tanya Latty Mary Myerscough Eduardo G Altmann |
| author_facet | Karina Arias-Calluari Theotime Colin Tanya Latty Mary Myerscough Eduardo G Altmann |
| author_sort | Karina Arias-Calluari |
| collection | DOAJ |
| description | A quantitative understanding of the dynamics of bee colonies is important to support global efforts to improve bee health and enhance pollination services. Traditional approaches focus either on theoretical models or data-centred statistical analyses. Here we argue that the combination of these two approaches is essential to obtain interpretable information on the state of bee colonies and show how this can be achieved in the case of time series of intra-day weight variation. We model how the foraging and food processing activities of bees affect global hive weight through a set of ordinary differential equations and show how to estimate the parameters of this model from measurements on a single day. Our analysis of 10 hives at different times shows that the estimation of crucial indicators of the health of honey bee colonies are statistically reliable and fall in ranges compatible with previously reported results. The crucial indicators, which include the amount of food collected (foraging success) and the number of active foragers, may be used to develop early warning indicators of colony failure. |
| first_indexed | 2024-04-10T05:23:18Z |
| format | Article |
| id | doaj.art-283069e7a9604e2898607a7c46f7b545 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-04-10T05:23:18Z |
| publishDate | 2023-03-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-283069e7a9604e2898607a7c46f7b5452023-03-08T05:30:41ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582023-03-01193e101088010.1371/journal.pcbi.1010880Modelling daily weight variation in honey bee hives.Karina Arias-CalluariTheotime ColinTanya LattyMary MyerscoughEduardo G AltmannA quantitative understanding of the dynamics of bee colonies is important to support global efforts to improve bee health and enhance pollination services. Traditional approaches focus either on theoretical models or data-centred statistical analyses. Here we argue that the combination of these two approaches is essential to obtain interpretable information on the state of bee colonies and show how this can be achieved in the case of time series of intra-day weight variation. We model how the foraging and food processing activities of bees affect global hive weight through a set of ordinary differential equations and show how to estimate the parameters of this model from measurements on a single day. Our analysis of 10 hives at different times shows that the estimation of crucial indicators of the health of honey bee colonies are statistically reliable and fall in ranges compatible with previously reported results. The crucial indicators, which include the amount of food collected (foraging success) and the number of active foragers, may be used to develop early warning indicators of colony failure.https://doi.org/10.1371/journal.pcbi.1010880 |
| spellingShingle | Karina Arias-Calluari Theotime Colin Tanya Latty Mary Myerscough Eduardo G Altmann Modelling daily weight variation in honey bee hives. PLoS Computational Biology |
| title | Modelling daily weight variation in honey bee hives. |
| title_full | Modelling daily weight variation in honey bee hives. |
| title_fullStr | Modelling daily weight variation in honey bee hives. |
| title_full_unstemmed | Modelling daily weight variation in honey bee hives. |
| title_short | Modelling daily weight variation in honey bee hives. |
| title_sort | modelling daily weight variation in honey bee hives |
| url | https://doi.org/10.1371/journal.pcbi.1010880 |
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