Meta-analysis confirms suitability of group planting of oaks - Publication in "Forest Ecology & Management"
Growth and quality of young oaks (Quercus robur and Quercus petraea) grown in cluster plantings in central Europe: A weighted meta-analysis.
     Somidh Saha, Christian Kuehne, Ulrich Kohnle, Peter Brang, Andreas  Ehring, Julian Geisel, Bertram Leder, Michael Muth, Regina Petersen,  Jakob Peter, Werner Ruhm, Jürgen Bauhus.
    
Cluster planting of oaks (Quercus robur and Quercus petraea)   was introduced to central Europe in the 1980s and 1990s as an economic   and ecological alternative to the traditional and costly row planting   for re-afforestation of wind-thrown and clear-cut areas. Clusters   comprising 20–30 seedlings are either ‘nests’ (nest planting) with very   dense spacing of ca. 0.2 m between trees, or ‘groups’ (group planting)   with 1 m between trees. Commonly, 100 groups or 200 nests ha−1   were planted in uniform distribution. We used a comprehensive weighted   meta-analysis to compare the growth and quality (stem form, crown  shape,  branch free bole length, number of potential future crop trees)  of oaks  grown in clusters with those planted in rows (e.g. 2 × 1 m  spacing).  Data were obtained from 25 trials located in Germany,  Switzerland and  Austria. Tree survival, growth and quality were  significantly lower in  nests than in neighbouring row planting  counterparts. Very low initial  growing space was presumably one of the  main reasons for low survival,  unfavourable growth and quality  development of oaks in nest plantings.  In group plantings, survival,  growth and tree quality were similar or  superior to row plantings. Tree  quality benefitted from the presence of  trainer trees in group  plantings. Based on this study, we recommend  planting oak groups as an  alternative to traditional row planting. Our  study showed the  usefulness of weighted meta-analysis to develop a  synthesis from raw  data collected from independent silvicultural trials  established with  comparable designs and similar research goals.
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