Predicting duff moisture in a boreal forest ecosystem at various retention levels

• Main Author: Alam, Hosen M A
• Other Authors: Comeau, Philip (Renewable Resources), Thompson, Daniel (Canada Forest Service, Northern Forestry Centre), Flannigan, Mike (Renewable Resources)
• Format: Thesis
• Language: English
• Published: University of Alberta. Department of Renewable Resources. 2016
• Subjects: envir; socio; Canada; Duff; Peace River
• Online Access: http://hdl.handle.net/10402/era.42895

Specialization: Forest Biology and Management Degree: Master of Science Abstract: The Canadian Fire Weather Index (FWI) system is used across Canada and worldwide to provide numerical ratings of fuel moisture based on the fine fuel moisture code (FFMC), duff moisture code (DMC) and drought code (DC). DMC is related to dryness of the duff layer. While DMC has been widely calibrated and validated in different stand types, it has not yet been calibrated for retention harvesting sites in the boreal mixedwood landscape of north-central Alberta. The objective of this research was to explore whether duff characteristics (duff load) and stand parameters (leaf area index, basal area) could be used in predicting duff moisture and whether the standard-DMC estimated by the FWI system matches with field-DMC. This study was conducted in conifer-dominated mixedwood stands that had received a range of variable retention harvesting in 1998/1999 (clear-cut, 20%, 50% , 75% - retentions and control) as part of the EMEND research project near Peace River, Alberta. Duff moisture, duff characteristics and vegetation parameters were measured in the field and DMCs were estimated for June, July and August in 2014 across retention levels. A trenching experiment was conducted to see if transpiration losses were related to duff moisture across retention levels. The results indicated that duff characteristics were influenced by litter deposition during harvesting and addition of fresh leaf litter from regenerated aspen. Duff moisture was influenced by slope and elevation more than species composition. Among the duff variables, duff load was a better predictor of duff moisture (R2=0.60). A three-way ANOVA revealed that standard DMC-MC relationships underestimate both field and sensor DMC in June and July.