Given that global climate warming has been observed in many different ecosystems as a possible cause of phenological mismatch between mutualistic species, the acute threat such mismatch presents to pollinators and their host species has provoked a number of studies in the last few years. Forest and Thomson (2011) performed a study of synchrony between bee species and flowers in the Rocky Mountains over the course of three years which provides important insights into the understanding of what causes phenological mismatches. Unlike previous plant-pollinator research projects, Forest and Thomson were able to decouple bee flight data from flower phenology by observing bees at custom-built nests rather than at their host-plants. These trap-nests were placed across an altitude gradient on a mountain slope and monitored for seasonal emergence over the course of three years. Using this observational data, the researches created phenology models to compare plant and bee emergence and concluded local environmental conditions are the key regulators for both flora and fauna, and while both bees and plants showed capacity for variation, plants are more likely to advance phenological response to rising temperatures earlier in the spring.
Forrest, J., Thomson, James., 2011. An examination of synchrony between insect emergence and flowering in Rocky Mountain meadows. Ecological Monographts, 81. 3., pp. 469-491.
There exists abundant evidence that global climate warming has caused phenological advancement in many individual species worldwide. However, little research has been done to verify temporal mismatches between pollinators and host plants; major mismatches could be fatal for ecosystems which rely on bee pollinators. While both bees and plant depend on temperature to determine the beginning of foraging and blooming respectively, researchers have also observed a host of other possible factors. For example, researchers have observed photoperiod changes as an important factor in provoking blooming. Furthermore, some plants require passing through a period of cold temperatures before flowering; this so-called “chilling requirement” complicates simple degree-day models for predicting phenological advances in these plants. Finally, many mountain plants’ blooms are closely correlated to snowmelt. Insect development rate is also closely related to temperature and thus degree-day models have been used to predict bee phenology. However the challenge in collecting unbiased bee data lies in the fact that researchers have historically observed bees at flowers, which makes such data dependent on plant phenology. Thus, Forrest and Thomson seek to study insect phenology independent of plant behavior.
In order to achieve this, the researchers studied bee and wasp phenology in the subalpine Rocky Mountains across an altitudinal gradient in an area where plant phenology is believed to be closely tied to the annual snowmelt. To decouple bee data from plant data, the researchers created artificial “trap nests” with monitoring equipment to follow both the temperature of the nests throughout the year as well as when the bees were emerging in the spring. Thus, they were able to directly observe potential changes in bee phenology without relying on plant behavior. While the elevational gradient of the fourteen sites was only 350 m, it encompassed a wide variety of environmental and phenological diversity. After the initial season in 2007, researchers switched the colonies from the highest latitude and lowest latitude as switching the boxes which were higher and lower to the ground. Therefore they were able to isolate the environmental influences from the genotypic behaviors of the various bee species being researched.
Upon completion of the study, researchers found temperature to be the best predictor of phenological advance in bee species. In fact, using a degree-day model they were able to predict the peak dates of flowering and bee flight with significant accuracy for the 2008 season. With regards to the transplant experiment from higher and lower altitudes, results suggested there was no effect of site origin on mean emergence dates for the species studied. The nest height study also showed similar results, with average temperatures being similar after snowmelt and the lower level nests were no longer snowcapped. Snowmelt was ruled out as a major phenological factor because all traps were snow covered the first winter in 2007, however the next two years saw such light snowfall that none of the nests were covered through winter. Researchers conclude that temperature is the biggest factor in determining bee phenology and while both the bees and plants in the study area demonstrate capacity to vary with climate change, further research is required to assess the risk of major mismatch.