Using ecological land types to examine landscape-scale oak regeneration dynamics.

Abstract: The long-standing interest in regenerating oaks stimulated the development of a number of research studies during the past several decades. Most studies have focused on addressing oak regeneration problems and many of these suggested that oak regeneration failures occur where site conditions favor the establishment and growth of competing species that capture the growing space following crown release. Because ecosystem classification regimes incorporate information about site conditions including many of the biophysical factors that largely govern site quality, some forest scientists have proposed that they be used for predicting oak regeneration dynamics. We used a large data set from a replicated landscape-scale experiment comprising nine, 400-ha forest management compartments to systematically examine oak regeneration dynamics following the application of a range of regeneration methods (clearcutting, group and single-tree selection) across differing ecological land types. We found that species of the red oak group appeared to be regenerating successfully only in stands harvested with clearcutting and that regeneration success was greatest in clearcut stands located on ecological land types of lower site quality where the density of competitors was relatively low. In contrast, species of the white oak group were regenerated with clearcutting and with the combination of group and single-tree selection but their regeneration response did not appear to be related to ecological land type. We conclude that an ecological classification framework is valuable for partitioning the landscape into finer-scale land units each having a similar propensity to (1) accumulate red oak reproduction in advance of harvesting and (2) respond to various regeneration methods each in a uniform manner. This framework was less important for examining species in the white oak group, which had similar regeneration dynamics across land types. [Copyright &y& Elsevier]