Browsing by Subject "Canopy cover"

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  • Kulha, Niko Aleksi; Pasanen, Leena; Holmström, Lasse; Grandpre, Louis de; Kuuluvainen, Timo Tapio; Aakala, Tuomas (2019)
    Identifying the scales of variation in forest structures and the underlying processes are fundamental for understanding forest dynamics. Here, we studied these scale-dependencies in forest structure in naturally dynamic boreal forests on two continents. We identified the spatial scales at which forest structures varied, and analyzed how the scales of variation and the underlying drivers differed among the regions and at particular scales. We studied three 2kmx2km landscapes in northeastern Finland and two in eastern Canada. We estimated canopy cover in contiguous 0.1-ha cells from aerial photographs and used scale-derivative analysis to identify characteristic scales of variation in the canopy cover data. We analyzed the patterns of variation at these scales using Bayesian scale space analysis. We identified structural variation at three spatial scales in each landscape. Among landscapes, the largest scale of variation showed the greatest variability (20.1-321.4ha), related to topography, soil variability, and long-term disturbance history. Superimposed on this large-scale variation, forest structure varied at similar scales (1.3-2.8ha) in all landscapes. This variation correlated with recent disturbances, soil variability, and topographic position. We also detected intense variation at the smallest scale analyzed (0.1ha, grain of our data), partly driven by recent disturbances. The distinct scales of variation indicated hierarchical structure in the landscapes studied. Except for the large-scale variation, these scales were remarkably similar among the landscapes. This suggests that boreal forests may display characteristic scales of variation that occur somewhat independent of the tree species characteristics or the disturbance regime.
  • Greiser, Caroline; Meineri, Eric; Luoto, Miska; Ehrlen, Johan; Hylander, Kristoffer (2018)
    The majority of microclimate studies have been done in topographically complex landscapes to quantify and predict how near-ground temperatures vary as a function of terrain properties. However, in forests understory temperatures can be strongly influenced also by vegetation. We quantified the relative influence of vegetation features and physiography (topography and moisture-related variables) on understory temperatures in managed boreal forests in central Sweden. We used a multivariate regression approach to relate near-ground temperature of 203 loggers over the snow-free seasons in an area of ∼16,000 km2 to remotely sensed and on-site measured variables of forest structure and physiography. We produced climate grids of monthly minimum and maximum temperatures at 25m resolution by using only remotely sensed and mapped predictors. The quality and predictions of the models containing only remotely sensed predictors (MAP models) were compared with the models containing also on-site measured predictors (OS models). Our data suggest that during the warm season, where landscape microclimate variability is largest, canopy cover and basal area were the most important microclimatic drivers for both minimum and maximum temperatures, while physiographic drivers (mainly elevation) dominated maximum temperatures during autumn and early winter. The MAP models were able to reproduce findings from the OS models but tended to underestimate high and overestimate low temperatures. Including important microclimatic drivers, particularly soil moisture, that are yet lacking in a mapped form should improve the microclimate maps. Because of the dynamic nature of managed forests, continuous updates of mapped forest structure parameters are needed to accurately predict temperatures. Our results suggest that forest management (e.g. stand size, structure and composition) and conservation may play a key role in amplifying or impeding the effects of climate-forcing factors on near-ground temperature and may locally modify the impact of global warming.
  • Kulha, Niko; Pasanen, Leena; Holmström, Lasse; Grandpre, Louis de; Gauthier, Sylvie; Kuuluvainen, Timo; Aakala, Tuomas (2020)
    Context: Changes in the structure of boreal old-growth forests are typically studied at a specific spatial scale. Consequently, little is known about forest development across different spatial scales. Objectives: We investigated how and at what spatial scales forest structure changed over several decades in three 4 km² boreal old-growth forests landscapes in northeastern Finland and two in Quebec, Canada. Methods: We used canopy cover values visually interpreted to 0.1-ha grid cells from aerial photographs taken at three time points between the years 1959 and 2011, and error distributions quantified for the interpretation. We identified the spatial scales at which canopy cover changed between the time points, and examined the credibility of changes at these scales using the error distributions in Bayesian inference. Results: Canopy cover changed at three to four spatial scales, the number of scales depending on the studied landscape and time interval. At large scales (15.4–321.7 ha), canopy cover increased in Finland during all time intervals. In Quebec, the direction of the large-scale change varied between the studied time intervals, owing to the occurrence of an insect outbreak and a consequent recovery. However, parts of these landscapes also showed canopy cover increase. Superimposed on the large-scale developments, canopy cover changed variably at smaller scales (1.3–2.8-ha and 0.1-ha). Conclusions: Our findings support the idea that the structure of boreal old-growth forests changes at discernible spatial scales. Instead of being driven by gap dynamics, the old-growth forests in the studied regions are currently reacting to large-scale drivers by an increase in canopy cover.