In both basic and applied studies, quantification of herbivory on foliage is a key metric in characterizing plant–herbivore interactions, which underpin many ecological, evolutionary and agricultural processes. Current methods of quantifying herbivory are slow or inaccurate. We present LeafByte, a free iOS application for measuring leaf area and herbivory. LeafByte can save data automatically, read and record barcodes, handle both light and dark coloured plant tissue, and be used non‐destructively. We evaluate its accuracy and efficiency relative to existing herbivory assessment tools. LeafByte has the same accuracy as ImageJ, the field standard, but is 50% faster. Other tools, such as BioLeaf and grid quantification, are quick and accurate, but limited in the information they can provide. Visual estimation is quickest, but it only provides a coarse measure of leaf damage and tends to overestimate herbivory. LeafByte is a quick and accurate means of measuring leaf area and herbivory, making it a useful tool for research in fields such as ecology, entomology, agronomy and plant science.

In both basic and applied studies, quantification of herbivory on foliage is a key metric in characterizing plant–herbivore interactions, which underpin many ecological, evolutionary and agricultural processes. Current methods of quantifying herbivory are slow or inaccurate. We present LeafByte, a free iOS application for measuring leaf area and herbivory. LeafByte can save data automatically, read and record barcodes, handle both light and dark coloured plant tissue, and be used non‐destructively. We evaluate its accuracy and efficiency relative to existing herbivory assessment tools. LeafByte has the same accuracy as ImageJ, the field standard, but is 50% faster. Other tools, such as BioLeaf and grid quantification, are quick and accurate, but limited in the information they can provide. Visual estimation is quickest, but it only provides a coarse measure of leaf damage and tends to overestimate herbivory. LeafByte is a quick and accurate means of measuring leaf area and herbivory, making it a useful tool for research in fields such as ecology, entomology, agronomy and plant science.

Bee populations have experienced declines in recent years, due in part to increased disease incidence. Multiple factors influence bee-pathogen interactions, including nectar and pollen quality and secondary metabolites. However, we lack an understanding of how plant interactions with their environment shape bee diet quality. We examined how plant interactions with the belowground environment alter floral rewards and, in turn, bee-pathogen interactions. Soil-dwelling mycorrhizal fungi are considered plant mutualists, although the outcome of the relationship depends on environmental conditions such as nutrients. In a 2 9 2 factorial design, we asked whether mycorrhizal fungi and nutrients affect concentrations of nectar and pollen alkaloids (anabasine and nicotine) previously shown to reduce infection by the gut pathogen Crithidia in the native bumble bee Bombus impatiens. To ask how plant interactions affect this common bee pathogen, we fed pollen and nectar from our treatment plants, and from a wildflower pollen control with artificial nectar, to bees infected with Crithidia. Mycorrhizal fungi and fertilizer both influenced flowering phenology and floral chemistry. While we found no anabasine or nicotine in nectar, high fertilizer increased anabasine and nicotine in pollen. Arbuscular mycorrhizal fungi (AMF) decreased nicotine concentrations, but the reduction due to AMF was stronger in high than low-nutrient conditions. AMF and nutrients also had interactive effects on bee pathogens via changes in nectar and pollen. High fertilizer reduced Crithidia cell counts relative to low fertilizer in AMF plants, but increased Crithidia in non-AMF plants. These results did not correspond with effects of fertilizer and AMF on pollen alkaloid concentrations, suggesting that other components of pollen or nectar were affected by treatments and shaped pathogen counts. Our results indicate that soil biotic and abiotic environment can alter bee-pathogen interactions via changes in floral rewards, and underscore the importance of integrative studies to predict disease dynamics and ecological outcomes.

Young for help with data collection and feedback, the UMass Amherst Quantitative Statistics Group for feedback on statistical analyses, Biobest (Ontario, Canada) for donating bumblebee colonies, and J. van Wyk and R. Malfi for providing constructive comments on the manuscript.