Results of 2‐Year Ring Testing of a Semifield Study Design to Investigate Potential Impacts of Plant Protection Products on the Solitary Bees Osmia Bicornis and Osmia Cornuta and a Proposal for a Suitable Test Design
Abstract:There are various differences in size, behavior, and life history traits of non-Apis bee species compared with honey bees (Apis mellifera; Linnaeus, 1758). Currently, the risk assessment for bees in the international and national process of authorizing plant protection products has been based on honey bee data as a surrogate organism for non-Apis bees. To evaluate the feasibility of a semifield tunnel test for Osmia bicornis (Linnaeus, 1758) and Osmia cornuta (Latreille, 1805), a protocol was developed by the … Show more
“…in south-west Germany (Limburgerhof). All locations were provided with artificial nest sites and the similar to the methods reported for Osmia field testing (Franke, Elston et al 2021). After one initial week of acclimatization we checked the nest sites twice a week for newly built cells and removed the pollen provisions before the larvae had hatched and stored them in individual Eppendorf® tubes at -20°C till analysis.…”
Bees foraging in agricultural habitats can be exposed to plant protection products. In order to limit the risk of adverse events to occur a robust risk assessment is needed, which requires reliable estimates for the expected exposure. Especially the exposure pathways to developing solitary bees are not well described and in the currently proposed form rely on limited information. To address this topic, we used a published data set on the volume of pollen solitary bees provide for their larvae to build two scaling models predicting the amount of protein and pollen developing solitary bees need based on adult body weight. We test our models using both literature and experimental data, which both support the validity of the presented models. Using scaling models in the bee risk assessment could complement existing risk assessment approaches, facilitate the further development of accurate risk characterization for solitary bees and ultimately will help to protect them during their foraging activity in agricultural settings.
“…in south-west Germany (Limburgerhof). All locations were provided with artificial nest sites and the similar to the methods reported for Osmia field testing (Franke, Elston et al 2021). After one initial week of acclimatization we checked the nest sites twice a week for newly built cells and removed the pollen provisions before the larvae had hatched and stored them in individual Eppendorf® tubes at -20°C till analysis.…”
Bees foraging in agricultural habitats can be exposed to plant protection products. In order to limit the risk of adverse events to occur a robust risk assessment is needed, which requires reliable estimates for the expected exposure. Especially the exposure pathways to developing solitary bees are not well described and in the currently proposed form rely on limited information. To address this topic, we used a published data set on the volume of pollen solitary bees provide for their larvae to build two scaling models predicting the amount of protein and pollen developing solitary bees need based on adult body weight. We test our models using both literature and experimental data, which both support the validity of the presented models. Using scaling models in the bee risk assessment could complement existing risk assessment approaches, facilitate the further development of accurate risk characterization for solitary bees and ultimately will help to protect them during their foraging activity in agricultural settings.
“…Behavioral data can contribute to the understanding of behavior‐mediated impacts of environmental stressors on reproduction of solitary bee species (Artz & Pitts‐Singer, 2015). Pesticide exposure, for example, can impair orientation and memory (Siviter et al, 2018) and cause a reduction in nest recognition or foraging activity (Artz & Pitts‐Singer, 2015; Franke et al, 2021). Flight duration may also be increased by habitat degradation or food competition, which can cause increased flight distances to food sources (Gathmann & Tscharntke, 2002).…”
The foraging and nesting performance of bees can provide important information on bee health and is of interest for risk and impact assessment of environmental stressors. While radiofrequency identification (RFID) technology is an efficient tool increasingly used for the collection of behavioral data in social bee species such as honeybees, behavioral studies on solitary bees still largely depend on direct observations, which is very time‐consuming. Here, we present a novel automated methodological approach of individually and simultaneously tracking and analyzing foraging and nesting behavior of numerous cavity‐nesting solitary bees. The approach consists of monitoring nesting units by video recording and automated analysis of videos by machine learning‐based software. This Bee Tracker software consists of four trained deep learning networks to detect bees that enter or leave their nest and to recognize individual IDs on the bees’ thorax and the IDs of their nests according to their positions in the nesting unit. The software is able to identify each nest of each individual nesting bee, which permits to measure individual‐based measures of reproductive success. Moreover, the software quantifies the number of cavities a female enters until it finds its nest as a proxy of nest recognition, and it provides information on the number and duration of foraging trips. By training the software on 8 videos recording 24 nesting females per video, the software achieved a precision of 96% correct measurements of these parameters. The software could be adapted to various experimental setups by training it according to a set of videos. The presented method allows to efficiently collect large amounts of data on cavity‐nesting solitary bee species and represents a promising new tool for the monitoring and assessment of behavior and reproductive success under laboratory, semi‐field, and field conditions.
“…Log pollen provision dw mg 0.92 log bee dw mg 0.44. (EPPO, 2010;Franke et al, 2021;OECD, 2014). All locations were provided with artificial nest sites and were similar to the methods reported for Osmia field testing (Franke et al, 2021).…”
We would like to thank Dr. Magdalena Mair for providing insightful comments on an earlier version of the manuscript and a non-regulatory perspective on the topic.
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