Skip to main content

Forest Productivity, Leaf Area, and Terrain in Southern Appalachian Deciduous Forests

Buy Article:

$29.50 plus tax (Refund Policy)

Abstract:

Leaf area index (LAI) is an important structural characteristic of forest ecosystems which has been shown to be strongly related to forest mass and energy cycles and forest productivity. LAI is more easily measured than forest productivity, and so a strong relationship between LAI and productivity would be a valuable tool in forest management. While a linear relationship has been observed between LAI and forest productivity, most of these data have been collected in needle-leaved evergreen stands. The generality and consistency of the relationship between LAI and productivity has not been as well established for deciduous forests.

Leaf area index (LAI) and aboveground net primary production (ANPP) were measured on 16 forest stands in the southern Appalachian Mountains. These stands span a range of elevation, slope position, temperature, and moisture regimes. LAI averaged 5.8 m2 m-2 and ranged from 2.7 to 8.2. ANPP averaged 9.2 Mg ha-1 yr-1 and ranged from 5.2 to ll.8 Mg ha-1 yr-1.

LAI and ANPP decreased significantly from cove to ridge sites, and ANPP decreases significantly from low to high elevation (P < 0.05, linear regression slope). Elevation-related differences in ANPP do not appear to be due to changes in precipitation, leaf nitrogen content, or site N mineralization rates.

Linear ANPP-LAI equations fit to the data measured in this study were significant (P < 0.05). These relationships were not significantly different (P > 0.1) from linear relationships based on data reported in most other studies of ANPP and LAI in eastern deciduous forests of North America. However, the slope of a linear regression model based on North American eastern deciduous forests was significantly different (P < 0.05) from one based on data collected in temperate deciduous forests for the rest of the globe. The differences were slight over the range of observed data, however, and the difference may be due to a narrower range of data for North American deciduous forests. For. Sci. 47(3):419–427.

Keywords: ANPP; LAI; elevation; environmental management; forest; forest management; forest resources; forestry; forestry research; forestry science; natural resource management; natural resources; precipitation; temperature

Document Type: Miscellaneous

Affiliations: 1: Department of Forest Resources, University of Minnesota, 1530 Cleveland Ave. N., St. Paul, MN, 55108, pbolstad@forestry.umn.edu 2: Coweeta Hydrologic Lab, USDA Forest Service, 3160 Coweeta Lab Rd., Otto, North Carolina, 28763 3: Southern Forest Experiment Station, USDA Forest Service, 1509 Varsity Dr., Raleigh, NC, 27606

Publication date: 2001-08-01

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2015 Impact Factor: 1.702
    Ranking: 16 of 66 in forestry

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
  • Submit a Paper
  • Membership Information
  • Author Guidelines
  • Podcasts
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free ContentFree content
  • Partial Free ContentPartial Free content
  • New ContentNew content
  • Open Access ContentOpen access content
  • Partial Open Access ContentPartial Open access content
  • Subscribed ContentSubscribed content
  • Partial Subscribed ContentPartial Subscribed content
  • Free Trial ContentFree trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more