Utilizing natural history collections and data mining to assess flower associations and phenology of North American bees in the genus Andrena (Hymenoptera: Andrenidae) subgenus Plastandrena

Five different Andrena species

 

by Zabinski

Even though bees are the most frequently discussed pollinators we still do not know when many species are active in the environment or what flowers they have preferences for. Learning about the activity and flower visitations of native bee species can help scientists better understand what potential ecological roles species may be playing in their environment. This is especially true in the mega diverse group of bees known as mining bees, in the genus Andrena. Due to such diversity within Andrena (1,738 recognized species) taxonomists has further separated Andrena into different subgenera. The subgenus Plastandrena is an interesting group found throughout Europe, Asian, and North America. The North American Plastandrena include 5 recognized species: Andrena mellea, Andrena argemonis, Andrena crataegi, Andrena fracta, and Andrena prunorum with A. crataegi and A. prunorum being very commonly encountered species. An in-depth look at the monthly activity and flower visitations for these species has never been conducted.

To study this, I gathered all the monthly occurrence records and flower visitations records from online data repositories, other bee experts, publications, and identified more specimens with records in natural history museums. This allowed me to amass many records to observe what time of year each species is active. As well as the breadth of flower species and flower families each species visits. This information demonstrated that A. mellea and A. argemonis can be classified as polylectic (or generalist) bees that visit a variety of flower genera and families. While A. crataegi, A. fracta, and A. prunorum can be classified as highly polylectic species, that visit a large variety of different flower genera and families. Andrena argemonis was the most specialized species, showing preferences for flowers in the genus Argemone but still has been found on a variety of other flower genera. The overall approach of this research may be a way to utilize the vast amount of information on label data that is stored in natural history collections to help assess the potential flower preferences for native bees. 

Read the scientific article in JPE 

Detecting bees in cherry flowers using timelapse images and foundational models

Example image where a bumble bee is automatically detected

by Devlin et al.

Bees are important for the pollination of flowers, and the subsequent fruit production, of many fruit crops such as sweet cherry.  This means that fruit growers will often introduce commercially-produced bumblebees to their farms.  Monitoring of these introduced bees is important to understand how bee activity affects fruit yield, particularly in relation to June drop which is a major cause of yield loss in cherry.  Cameras can be used to continuously monitor flowers, but analysis of the generated footage is time consuming.  The development of automatic image processing methods that can detect bees within camera images without manual image checking is a useful tool for studying bee pollination.

This work presents a novel method called BeeSAM2 for detecting bumblebees in time lapse images.  This combines two previously developed methods Grounding DINO which detects objects in images when given a text prompt and Segment Anything 2 which tracks objects through videos when provided with an example object to follow.  BEESAM2 detected over 95% of bumblebees captured in time-lapse images.  This method is sufficiently accurate for counting bumblebees active in cherry flowers, advancing the ability of researchers to monitor bee behaviour and interaction with flowers, while saving significant time on video processing.

Read the scientific paper in JPE