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An Investigation of the Impacts of Elevated Carbon Dioxide, Irrigation, and Fertilization on the Physiology and Growth of Loblolly Pine

  • Phillip M. Dougherty
  • H. Lee Allen
  • Lance W. Kress
  • Ramesh Murthy
  • Chris A. Maier
  • Timothy J. Albaugh
  • D. Arthur Sampson
Part of the Ecological Studies book series (ECOLSTUD, volume 128)

Abstract

Southern pine forests that are dominated by loblolly pine (Pinus taeda L.) are the most intensively managed forests in the United States. They provide more than 50% of the total softwood being harvested annually in the United States and represent the first or second most economically important agricultural crops in nine of the twelve southeastern states (U.S. Department Agriculture Forest Service, 1988). Thus, any changes in environmental conditions that will alter productivity of these forests will have important ecological, economical, and sociological consequences. Over the past several decades, the environment of southeastern forests has been changing. Increases in acidic deposition (SO4 and NOx), nitrogen inputs (Husar, 1986), atmospheric CO2 concentration (Conway et al., 1988; Keeling et al., 1989), and tropospheric ozone have all been documented to parallel the increase in population since the beginning of the industrial revolution. Climate change has also been predicted for the southeastern United States for the future. Each of these atmospheric and climatic elements that are being altered by human activities has the potential to affect productivity of southern pine forests. Nutrient availability, water availability, atmospheric CO2 concentration, and temperature are presently the principal factors that are limiting the productivity of southern pine forests. Thus, it is extremely important that we understand how changes in these factors will interact to affect physiological processes of forest stands.

Keywords

Leaf Area Gross Primary Productivity Fine Root Production Pinus Taeda Julian Date 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag New York, Inc. 1998

Authors and Affiliations

  • Phillip M. Dougherty
  • H. Lee Allen
  • Lance W. Kress
  • Ramesh Murthy
  • Chris A. Maier
  • Timothy J. Albaugh
  • D. Arthur Sampson

There are no affiliations available

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