Data from: Foraging energetics reveals late-summer challenges for pollinators across two British cities
Abstract
Foraging pollinators often work within fine energetic margins, but recent work has shown that foraging conditions can vary markedly across the year. Despite the importance of seasonality for pollinator foraging, most work in this area has relied on indirect approaches. However, quantifying energetic efficiency, the ratio of energetic gain to cost during foraging, can provide a direct measure of foraging conditions experienced by nectar foragers. Here, we provide the first direct measure of seasonal changes in foraging conditions by tracking the energetic efficiency of honeybee nectar foragers across a whole season (April – October) on flower patches that colonies were actively exploiting. We combined foraging observations, flower nectar sampling, and physiological data from the literature to estimate foraging efficiency (ratio of energetic net profits to energy expenditure) on 19 study plant species in two locations ~600km apart in Britain. We found that foraging efficiency was lowest in late summer (mid-July – August), with predicted foraging efficiency reaching its lowest in mid-August. As honeybees are generalist foragers and continually monitor foraging conditions, our data suggests that foraging conditions may be challenging during late summer for many other flower-visitors. Similar patterns of energetic efficiency and energy per flower were observed for both study sites. However, the more urban site was less variable, highlighting the potential importance of land-use context for influencing seasonal continuity of floral resources. We provide the first direct assessment of seasonal variation in foraging efficiency of individual nectar foragers. Our results are relevant to conservation efforts and suggest that efforts to improve nectar general availability of nectar in Britain may be most valuable if provided in late summer.
Publication details
- Journal / source
- DRYAD
- Publication date
- 31 July 2026
- Language
- EN
- Document type
- Dataset