Sentence examples for silviculture site from inspiring English sources
In southern Australia, for example, declines in yield of 25 30 percent in second rotation radiata pine (Pinus radiata) plantations have been corrected by a number of means, including intensive silviculture (site preparation, weed control, fertilization) during the early stages, retention and management of forest debris (leaves, branches, etc).
Interaction effects of site by silviculture, site by seedlot, silviculture by seedlot, and the three-way interaction were also included.
Known or postulated silviculture × site interaction in radiata pine, in terms of how impacts of site factors on means and expression of differences for specific tree variables are affected by silviculture (lower stockings/heavier thinning regimes, or fertiliser use).
Average values by site, silviculture, and seedlot were calculated for all measured traits.
Management of Douglas-fir stands to achieve particular end product outcomes requires information on how wood density and branch characteristics are affected by site, silviculture and genetics.
It is influenced by site, silviculture, and genetics, and models that predict the variation in wood density within and among trees are required by forest managers so that they can develop strategies to achieve certain wood density targets.
Both stress-wave velocity and wood density were found to be highly sensitive to site, silviculture and seedlot influences, and these traits could potentially be used together to identify material which has both high density and high stress-wave velocity.
This study examines the influences of site, silviculture and seedlot on diameter growth, wood density and estimated wood stiffness in mid-rotation radiata pine (Pinus radiata D Don) stands across New Zealand.
The wood density models developed in this paper were designed to be coupled to growth and yield models, so that the effects of site, silviculture, and genetics on wood density can be predicted.
More comprehensive analyses of these data are required along with the development of models that enable forest managers to predict how different combinations of site, silviculture, and genetics affect wood density.
