Welcome to the InfoSci Platform
Reference Hub1
Assessing Performance of Leaf Area Index in a Monitored Mountain Ecosystem on Mount Elgon-Uganda

Assessing Performance of Leaf Area Index in a Monitored Mountain Ecosystem on Mount Elgon-Uganda

Tonny Oyana, Ellen Kayendeke, Samuel Adu-Prah
Copyright: © 2017 |Volume: 8 |Issue: 1 |Pages: 17
ISSN: 1947-9654|EISSN: 1947-9662|EISBN13: 9781522513179|DOI: 10.4018/IJAGR.2017010104
Cite Article Cite Article

MLA

Oyana, Tonny, et al. "Assessing Performance of Leaf Area Index in a Monitored Mountain Ecosystem on Mount Elgon-Uganda." IJAGR vol.8, no.1 2017: pp.64-80. http://doi.org/10.4018/IJAGR.2017010104

APA

Oyana, T., Kayendeke, E., & Adu-Prah, S. (2017). Assessing Performance of Leaf Area Index in a Monitored Mountain Ecosystem on Mount Elgon-Uganda. International Journal of Applied Geospatial Research (IJAGR), 8(1), 64-80. http://doi.org/10.4018/IJAGR.2017010104

Chicago

Oyana, Tonny, Ellen Kayendeke, and Samuel Adu-Prah. "Assessing Performance of Leaf Area Index in a Monitored Mountain Ecosystem on Mount Elgon-Uganda," International Journal of Applied Geospatial Research (IJAGR) 8, no.1: 64-80. http://doi.org/10.4018/IJAGR.2017010104

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

This study investigated the performance of leaf area index (LAI) and photosynthetically active radiation (PAR) in a mountain ecosystem. The authors hypothesized that significant spatial and temporal differences exist in LAI and PAR values in the Manafwa catchment on Mt. Elgon. This was accomplished through field measurements of actual LAI and PAR values of diverse vegetation types along a ~900m altitudinal gradient (1141–2029 masl) in the catchment. In-situ measurements were obtained from 841 micro-scale study plots in 28 sampling plots using high resolution LAI sensors. The findings showed a significant positive relationship exists between elevation and observed LAI (r = 0.45, p = 0.01). A regression model further shows that elevation and curvature of the landscape slope were highly significant (p < 0.00002) predictors of LAI. Finally, the authors detected significant spatial and temporal differences in LAI and PAR values in the study area. The study provides a critical basis for setting up long-term monitoring plans to understand mountain ecosystems and global climate change.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.