Bee dietary preferences, or the floral resources that they consistently collect, likely impact where a species can persist. For this reason it is likely that bee dietary preferences are dependent upon the composition of the plant community. In this study, we evaluated floral visits and pollen loads of the mining bee, Andrena angustitarsata Viereck, across a 630 km north-south range to understand dietary preferences along a floral resource gradient. Previous research, in a more geographically limited area, suggested this species was an eclectic oligolege on predominantly Apiaceae and in part Rosaceae. In the present study we found the species predominately visited and collected pollen from Apiaceae and Rosaceae, but visited 12 flower families and collected pollen from 32, distinguishing them as generalist foragers. The frequency of Apiaceae pollen on the bees and the species-level specialization index (a measure of visit specialization) were higher in regions with higher Apiaceae abundance. In addition Apiaceae and Rosaceae were the only plant families significantly preferred for pollen collection, regardless of floral abundance. We conclude that across our study region A. angustitarsata has a generalist dietary breadth, but also has dietary preference for Apiaceae and Rosaceae. Our study indicates that while bees may overall make generalist foraging decisions they may still prefer and likely benefit from selecting fewer flower taxa.
A challenge in conservation is the gap between knowledge generated by researchers and the information being used to inform conservation practice. This gap, widely known as the research-implementation gap, can limit the effectiveness of conservation practice. One way to address this is to design conservation tools that are easy for practitioners to use. Here, we implement data science methods to develop a tool to aid in conservation of pollinators in British Columbia. Specifically, in collaboration with Pollinator Partnership Canada, we jointly develop an interactive web app, the goal of which is two-fold: (i) to allow end users to easily find and interact with the data collected by researchers on pollinators in British Columbia (prior to development of this app, data were buried in supplements from individual research publications) and (ii) employ up to date statistical tools in order to analyse phenological coverage of a set of plants. Previously, these tools required high programming competency in order to access. Our app provides an example of one way that we can make the products of academic research more accessible to conservation practitioners. We also provide the source code to allow other developers to develop similar apps suitable for their data.
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