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Harvard Forest Symposium Abstract 2011
- Title: Global change and human health: Predicting ragweed allergy hotspots in New England
- Primary Author: Kristina Stinson (University of Massachusetts - Amherst )
- Additional Authors: Sydne Record (Harvard Forest); Christine Rogers (University of Massachusetts at Amherst)
- Abstract:
Common ragweed (Ambrosia artemisiifolia L.) is a leading cause of fall hay fever nationwide. This widespread species dramatically increases its pollen production when exposed to increased atmospheric carbon dioxide, but little is known about geographic variation in this response. This new, four-year study at the Harvard Forest (funded by EPA STAR grant # SU834359010) combines field sampling, geographic information system (GIS) analysis, and controlled experiments to predict when and where pollen allergies are most likely to increase in response to changes in atmospheric carbon dioxide and precipitation patterns in New England. Field surveys are employed to obtain population-level field data on pollen output, peak flowering times, and allergen protein. A set of complimentary climate-controlled experiments are being employed to determine the range of variation among climatically distinct populations in pollen production and pollen potency in response to current and future atmospheric CO2 and precipitation scenarios. Collectively, these datasets will be linked to national climate data and land cover attributes using regression modeling techniques to create spatially explicit maps of pollen abundance, potential dispersion, and pollen potency under IPCC predictions for regional climate scenarios. The expected outcomes include: greatly enhanced predictive tools and maps for forecasting allergy “hotspots” and demographically-relevant models of human exposure to pollen risk factors under a wide range of future climate scenarios.
- Research Category: Ecological Informatics and Modelling
Large Experiments and Permanent Plot Studies
Physiological Ecology, Population Dynamics, and Species Interactions
