Net primary productivity (NPP) is a key ecological parameter that is important in estimating carbon stocks in large forested areas. NPP is estimated using models of which leaf area index (LAI) is a key input. This research computes a variety of ground-based and remote sensing LAI estimation approaches and examines the impact of these estimates on modeled NPP. A relative comparison of ground-based LAI estimates from optical and allometric techniques showed that the integrated LAI-2000 and TRAC method was preferred. Spectral mixture analysis (SMA), accounting for subpixel influences on reflectance, outperformed vegetation indices in LAI prediction from remote sensing. LAI was shown to be the most important variable in modeled NPP in the Kananaskis, Alberta region compared to soil water content (SWC) and climate inputs. The variability in LAI and NPP estimates were not proportional, from which a threshold was suggested where first LAI is limiting than water availability. / xii, 181 leaves : ill. ; 28 cm.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:ALU.w.uleth.ca/dspace#10133/155 |
| Date | January 2002 |
| Creators | Davidson, Diedre P., University of Lethbridge. Faculty of Arts and Science |
| Contributors | Peddle, Derek |
| Publisher | Lethbridge, Alta. : University of Lethbridge, Faculty of Arts and Science, 2002, Arts and Science, Department of Geography |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
| Relation | Thesis (University of Lethbridge. Faculty of Arts and Science) |
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