Kobra Maleki
Research Scientist
(+47) 465 06 548
kobra.maleki@nibio.no
Place
Steinkjer
Visiting address
Innocamp Steinkjer, Skolegata 22, 7713 Steinkjer
Abstract
No abstract has been registered
Abstract
Aim Seedling recruitment is a vital process for forest regeneration and is influenced by various factors such as stand composition, climate, and soil disturbance. We conducted a long-term field experiment (18 years) to study the effects of these factors and their interactions on seedling recruitment. Location Our study focused on five main species in boreal mixed woods of eastern Canada: trembling aspen (Populus tremuloides), paper birch (Betula papyrifera), white spruce (Picea glauca), balsam fir (Abies balsamea), and white cedar (Thuja occidentalis). Methods Sixteen 1-m2 seedling monitoring subplots were set up in each of seven stands originating from different wildfires (fire years ranging from 1760 to 1944), with a soil scarification treatment applied to every other subplot. Annual new seedling counts were related to growing-season climate (mean temperature, growing degree days and drought code), scarification, and stand effects via a Bayesian generalized linear mixed model. Results Soil scarification had a large positive effect on seedling recruitment for three species (aspen, birch and spruce). As expected, high mean temperatures during the seed production period (two years prior to seedling emergence) increased seedling recruitment for all species but aspen. Contrary to other studies, we did not find a positive effect of dry conditions during the seed production period. Furthermore, high values of growing degree days suppressed conifer seedling recruitment. Except for white cedar, basal area was weakly correlated with seedling abundance, suggesting a small number of reproductive individuals is sufficient to saturate seedling recruitment. Conclusion Our findings underscore the importance of considering multiple factors, such as soil disturbance, climate, and stand composition, as well as their effects on different life stages when developing effective forest management strategies to promote regeneration in boreal mixed-wood ecosystems.
Abstract
Forest management planning often relies on Airborne Laser Scanning (ALS)-based Forest Management Inventories (FMIs) for sustainable and efficient decision-making. Employing the area-based (ABA) approach, these inventories estimate forest characteristics for grid cell areas (pixels), which are then usually summarized at the stand level. Using the ALS-based high-resolution Norwegian Forest Resource Maps (16 m × 16 m pixel resolution) alongside with stand-level growth and yield models, this study explores the impact of three levels of pixel aggregation (stand-level, stand-level with species strata, and pixel-level) on projected stand development. The results indicate significant differences in the projected outputs based on the aggregation level. Notably, the most substantial difference in estimated volume occurred between stand-level and pixel-level aggregation, ranging from −301 to +253 m3⋅ha−1 for single stands. The differences were, on average, higher for broadleaves than for spruce and pine dominated stands, and for mixed stands and stands with higher variability than for pure and homogenous stands. In conclusion, this research underscores the critical role of input data resolution in forest planning and management, emphasizing the need for improved data collection practices to ensure sustainable forest management.