Browsing by Subject "northern Fennoscandia"

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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.
  • Kulha, Niko; Pasanen, Leena; Aakala, Tuomas (2018)
    Time series of repeat aerial photographs currently span decades in many regions. However, the lack of calibration data limits their use in forest change analysis. We propose an approach where we combine repeat aerial photography, tree-ring reconstructions, and Bayesian inference to study changes in forests. Using stereopairs of aerial photographs from five boreal forest landscapes, we visually interpreted canopy cover in contiguous 0.1-ha cells at three time points during 1959-2011. We used tree-ring measurements to produce calibration data for the interpretation, and to quantify the bias and error associated with the interpretation. Then, we discerned credible canopy cover changes from the interpretation error noise using Bayesian inference. We underestimated canopy cover using the historical low-quality photographs, and overestimated it using the recent high-quality photographs. Further, due to differences in tree species composition and canopy cover in the cells, the interpretation bias varied between the landscapes. In addition, the random interpretation error varied between and within the landscapes. Due to the varying bias and error, the magnitude of credibly detectable canopy cover change in the 0.1-ha cells depended on the studied time interval and landscape, ranging from -10 to -18 percentage points (decrease), and from +10 to +19 percentage points (increase). Hence, changes occurring at stand scales were detectable, but smaller scale changes could not be separated from the error noise. Besides the abrupt changes, also slow continuous canopy cover changes could be detected with the proposed approach. Given the wide availability of historical aerial photographs, the proposed approach can be applied for forest change analysis in biomes where tree-rings form, while accounting for the bias and error in aerial photo interpretation.
  • Teittinen, Anette; Wang, Jianjun; Stromgard, Simon; Soininen, Janne (2017)
    Aim: Elevational biodiversity patterns are understudied in high-latitude aquatic systems, even though these systems are important for detecting very early impacts of climatic changes on Earth. The aim of this study was to examine the elevational trends in species richness and local contribution to beta diversity (LCBD) of three biofilm microbial groups in freshwater ponds and to identify the key mechanisms underlying these patterns. Location: One hundred and forty-six ponds in subarctic Finland and Norway distributed across the tree line along an elevational gradient of 10-1,038 m a.s.l., spanning from forested landscape to barren boulder fields. Time period: July-August 2015. Major taxa studied: Diatoms, cyanobacteria and non-cyanobacteria. Methods: Generalized linear models were used to identify the most important pond variables explaining richness and LCBD. Structural equation models were used to explore the direct and indirect effects of multiscale drivers on richness and LCBD. Results: Diatom and cyanobacteria richness showed unimodal elevational patterns, whereas non-cyanobacteria richness decreased with increasing elevation. The LCBD-elevation relationship was U-shaped for all three microbial groups. Diatom and cyanobacteria richness and LCBD were best explained by local pond variables, especially by pH. Non-cyanobacteria richness and LCBD were related to pond variables, elevation as a proxy for climatic conditions, and normalized difference vegetation index as a proxy for terrestrial productivity. Main conclusions: Aquatic autotrophs were primarily controlled by environmental filtering, whereas heterotrophic bacteria were also affected by terrestrial productivity and elevation. All studied aspects of microbial diversity were directly or indirectly linked to elevation; therefore, climatic changes may greatly alter aquatic microbial assemblages.