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Harvard Forest REU Symposium Abstract 2010

  • Title: Factors that help predict the distribution of Ragweed in the New England Landscape
  • Author: Jesus I Marquez (San Diego State University)
  • Abstract:

    Ambrosia artemisiifolia, better known as common ragweed, is a plant that causes allergies such as hay fever. Mapping its distribution and understanding the environmental and human factors that can predict its presence is of vital importance in order to understand how allergy patterns might be affected with changes in land use and climate. The questions we are asking are how land use and temperature affect the distribution of ragweed and how this data can be used by public health authorities to analyze spatial distribution of ragweed on a changing landscape and climate. Because ragweed is an early successional plant that prefers disturbed soils, we hypothesized that there would be more presence in developed areas and farm fields. We also hypothesized that ragweed presence would be higher at warmer and drier climate temperatures. Using GIS, we created nine land cover per average minimum temperature (from 1970-2000) categories and collected presence/absence data from a number of random points across Massachusetts and New York. We are still in the process of collecting data from Vermont. We included census data to calculate population density per square kilometer in order to estimate development levels, household median income, and percentage of people living on farms. We used a classification and regression tree (CART) analysis to see what factors were more likely to predict presence of ragweed. So far, we have found that when using only GIS categories such as temperature, land cover and census data, the main factors predicting presence of ragweed are latitude, temperature and then longitude. In places where averaged minimum temperature is greater than 2.75 ˚F, longitude would be the next predicting factor. In places where averaged minimum temperature is lower than 2.75 ˚F, latitude would be the next predicting factor. We also found that when we combined GIS categories with field observations, agricultural fields, bare soils and longitude are the dominant predictors. We concluded GIS categories alone are sufficient for predicting temperature based variation in ragweed distribution, but easily collected field data are sensible predictors at smaller spatial scales, where farm fields and bare soils are highly identified as habitats for ragweed. Data can be use to create land use generalizations if spatial analysis is needed for public health or other issues of human and environmental concern.

  • Research Category: Invasive Plants, Pests & Pathogens