A team of researchers from the Life Sciences Department of the Faculty of Sciences and Technology of the UC (FCTUC), coordinated by José Paulo Sousa, collaborates with the MUST-B group, with “the objective of studying the integrated risk of multiple factors of 'stress' on honey bees and assess ways to mitigate it by improving crop management and agricultural landscapes”, reveals a note from UC released.
The FCTUC team is responsible for collecting field data on the development of colonies and the surrounding landscape. All the data "will be used for the calibration of the ApisRAM model - risk assessment model for honey bee colonies at European level -, which is being developed by the MUST-B group", explains José Paulo Sousa.
This model will allow, for example, “to predict the health status of bee colonies, adopting a holistic approach to the problem, integrating not only health information about colonies and effects derived from pesticide exposure, but also the influence of composition and management landscape, especially in terms of agricultural practices and availability of floral resources”.
The data collected by the Portuguese team are also being integrated into the EU Bee Partnership (EUBP) platform, with the active participation of FCTUC PhD student in Biosciences, Nuno Capela.
This platform, also supported by the European Food Safety Authority (EFSA in its original acronym in English), aims to collect and analyze data related to pollinators, and to present them in a visually clear and simple way, says the UC.
It also intends to “help the exploration of data and improve the understanding, by 'stakeholders' of different areas, about the health status of pollinators and their role in the environment”, he adds.
With the data collected as part of his PhD, the researcher Nuno Capela, from the Center for Functional Ecology, intends to “standardize the collection of future data and help in the creation of algorithms that can automatically detect events, trends and possible problems in bee colonies”.
Thus, "in the future, beekeepers, researchers or even citizens, will be able to add raw data to the platform, which will process it automatically, showing as a result graphs and tables that are easy to interpret".