Percorrer por autor "Rodrigues, Pedro J."
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- High accuracy monitoring of honey bee colony development by a quantitative methodPublication . Capela, Nuno; Dupont, Yoko L.; Rortais, Agnès; Sarmento, Artur; Papanikolaou, Alexandra; Topping, Christopher J.; Arnold, Gérard; Pinto, M. Alice; Rodrigues, Pedro J.; More, Simon J.; Tosi, Simone; Alves, Thiago da Silva; Sousa, José PauloHoney bees are key insect pollinators, providing important economic and ecological value for human beings and ecosystems. This has triggered the development of several monitoring methods for assessing the temporal development of colony size, food storage, brood and pathogens. Nonetheless, most of these methods are based on visual assessments that are observer-dependent and prone to bias. Furthermore, the impact on colony development (invasiveness), as well as accuracy, were rarely considered when implementing new methods. In this study, we present and test a novel accurate and observer-independent method for honey bee colony assessment, capable of being fully standardized. Honey bee colony size is quantified by assessing the weight of adult bees, while brood and provision are assessed by taking photos and conducting image analysis of the combs with the image analysis software DeepbeeVR . The invasiveness and accuracy of the method were investigated using field data from two experimental apiaries in Portugal, comparing results from test and control colonies. At the end of each field experiment, most of the tested colonies had the same colony size, brood levels and honey production as the control colonies. Nonetheless, continuous weight data indicated some disturbance in tested colonies in the first year of monitoring. The overall accuracy of the image analysis software was improved by training, indicating that it is possible to adapt the software to local conditions. We conclude that the use of this fully quantitative method offers a more accurate alternative to classic visual colony assessments, with negligible impact on colony development.
- Honey bee (Apis mellifera) wing images: a tool for identification and conservationPublication . Oleksa, Andrzej; Cauia, Eliza; Siceanu, Adrian; Puskadija, Zlatko; Kovačić, Marin; Pinto, M. Alice; Rodrigues, Pedro J.; Hatjina, Fani; Charistos, Leonidas; Bouga, Maria; Presern, Janez; Kandemir, Irfan; Rasic, Sladan; Kusza, Szilvia; Tofilski, AdamThe honey bee (Apis mellifera) is an ecologically and economically important species that provides pollination services to natural and agricultural systems. The biodiversity of the honey bee in parts of its native range is endangered by migratory beekeeping and commercial breeding. In consequence, some honey bee populations that are well adapted to the local environment are threatened with extinction. A crucial step for the protection of honey bee biodiversity is reliable differentiation between native and nonnative bees. One of the methods that can be used for this is the geometric morphometrics of wings. This method is fast, is low cost, and does not require expensive equipment. Therefore, it can be easily used by both scientists and beekeepers. However, wing geometric morphometrics is challenging due to the lack of reference data that can be reliably used for comparisons between different geographic regions. Here, we provide an unprecedented collection of 26,481 honey bee wing images representing 1,725 samples from 13 European countries. The wing images are accompanied by the coordinates of 19 landmarks and the geographic coordinates of the sampling locations. We present an R script that describes the workflow for analyzing the data and identifying an unknown sample. We compared the data with available reference samples for lineage and found general agreement with them. The extensive collection of wing images available on the Zenodo website can be used to identify the geographic origin of unknown samples and therefore assist in the monitoring and conservation of honey bee biodiversity in Europe.