Global environmental change alters the structure and dynamics of boreal old-growth forests. Changes in these forests greatly influence key ecosystem properties such as biodiversity and carbon cycle. Hence, understanding the development of the remaining natural boreal forests is particularly important.
We examined how forest structure varies in space and changes over time in three natural boreal forest landscapes in northern Fennoscandia and two landscapes in eastern North America. Canopy cover that was visually interpreted from stereopairs of aerial photographs taken between the years 1959 and 2011 was used as a surrogate measure of forest structure, and Bayesian inference was used to separate credible ecological phenomena from the noise caused by interpretation error.
We identified credible changes in forest structure in each studied landscape, but also noted that the visual interpretation of canopy cover was prone to systematic and random error that depended on, e.g., aerial photo quality. The multi-scale change analysis revealed a synchronous and prevalent canopy cover increase at large spatial scales in the majority of the studied landscapes, and canopy cover decrease and increase in areas that were subjects to disturbances. Changes of variable direction and magnitude were detected at smaller spatial scales. Furthermore, forest structure varied at multiple spatial scales which showed similarities despite the differences in dominant tree species and disturbance regimes between the studied landscapes. The variability was connected with scale-dependent driving processes that also showed similarities among the landscapes.
Our observations indicate that the structure of natural boreal forests may vary at characteristic scales that are independent of, e.g., tree species composition and disturbance regime. However, contrary to the conventional view of boreal old-growth forest dynamics, the results suggest that the studied forests are currently undergoing large scale changes that increase their canopy cover and consequently biomass.