PS 53-16
Spatiotemporal variation of tree growth in a northern hardwood forest
Tree growth is likely non-uniform within a forest because of variation in light availability, soil moisture, slope, aspect, pest outbreaks, tree species neighborhoods, and many other factors. We compared radial growth between 2008 and 2012 among 448 randomly selected deciduous and coniferous trees representing 16 species at the 25 ha Wabikon Forest Dynamics Plot in northern Wisconsin, USA, where all trees (n = 48,458) 1 cm DBH or larger were mapped, tagged, and measured in 2008-09. Intra-annual growth during 2012-13 was measured with aluminum dendrometer bands on the same 448 trees. Our objective was to demonstrate the degree of spatial and temporal variation in tree growth and to identify local ecological factors that are associated with this variation. Independent variables associated with each tree included tree species, tree height, elevation, slope, aspect, soil type, canopy cover, and the density and species composition of neighboring trees.
Results/Conclusions
Mean radial growth over 4 years and within a single year differed significantly among forest tree species and diameter size classes. Trees in large size classes experienced significantly larger growth increments than smaller diameter trees. Mean radial growth differed significantly between species within certain genera (Acer and Populus), but not between species within other genera (Picea, Fraxinus, and Betula). Overall, mean diameter growth of gymnosperms over 4 years ( = 6.3 mm) was significantly lower than that of angiosperms ( = 10.1 mm). Variation in growth associated with time of year and local microhabitat features reveals fine scale patterns of growth within the forest. These patterns have potentially important implications for forest management and provide insights into ecological interactions among other forest species, including primary consumers and decomposers. Fine scale variation in tree growth within topographically diverse forests like that at the Wabikon Plot also can be used to better predict responses of northern hardwood forests to change in climate and other landscape level environmental conditions.