Fungal Community Composition as Affected by Litter Chemistry and Weather during Four Years of Litter Decomposition in Rainshadow Coastal Douglas-Fir Forests.

Climate and litter chemistry are major factors influencing litter decay, a process mediated by microbes, such as fungi, nitrogen-fixing bacteria and ammonia-oxidizing bacteria. Increasing atmospheric CO2 concentrations can decrease nitrogen (N) and increase condensed tannin (CT) content in foliar litter, reducing litter quality and slowing decomposition. We hypothesized that reduced litter quality inhibits microbes and is the mechanism causing decomposition to slow. Litterbags of Douglas-fir needles and poplar leaves with a range of N (0.61-1.57%) and CT (2.1-29.1%) treatment and natural acid unhydrolyzable residue (35.3-41.5%) concentrations were placed along climatic gradients in mature Douglas-fir stands of coastal British Columbia rainshadow forests. The structure (diversity, richness and evenness) and composition of microbial communities were analyzed using DGGE profiles of 18S, NifH-universal and AmoA PCR amplicons in foliar litter after 7, 12, 24 and 43 months of decay. High CT and low N concentrations in leaf litter were associated with changes in microbial community composition, especially fungi. Contrary to our hypothesis, high CT and low N treatments did not inhibit microbial colonization or diversity. The joint effects of air temperature and soil moisture on microbial community composition at our sites were more important than the effects of initial litter chemistry.

Implications of differing input data sources and approaches upon forest carbon stock estimation.

Site index is an important forest inventory attribute that relates productivity and growth expectation of forests over time. In forest inventory programs, site index is used in conjunction with other forest inventory attributes (i.e., height, age) for the estimation of stand volume. In turn, stand volumes are used to estimate biomass (and biomass components) and enable conversion to carbon. In this research, we explore the implications and consequences of different estimates of site index on carbon stock characterization for a 2,500-ha Douglas-fir-dominated landscape located on Eastern Vancouver Island, British Columbia, Canada. We compared site index estimates from an existing forest inventory to estimates generated from a combination of forest inventory and light detection and ranging (LIDAR)-derived attributes and then examined the resultant differences in biomass estimates generated from a carbon budget model (Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3)). Significant differences were found between the original and LIDAR-derived site indices for all species types and for the resulting 5-m site classes (p < 0.001). The LIDAR-derived site class was greater than the original site class for 42% of stands; however, 77% of stands were within +/-1 site class of the original class. Differences in biomass estimates between the model scenarios were significant for both total stand biomass and biomass per hectare (p < 0.001); differences for Douglas-fir-dominated stands (representing 85% of all stands) were not significant (p = 0.288). Overall, the relationship between the two biomass estimates was strong (R(2) = 0.92, p < 0.001), suggesting that in certain circumstances, LIDAR may have a role to play in site index estimation and biomass mapping.