资源环境科技发展态势分析平台

Intensively managed forests are expected to play an increasingly important role in meeting future global demand for wood products. To meet this challenge, a key focus will be on lifting yields from these forests along with economic returns. In this study, we used data from a long-term series of trials that were established in radiata pine (Pinus radiata D. Don) to examine the effect that stand density, deployment of genetically-improved seedlots, and site have on economic returns. This dataset comprised end-of-rotation assessments of eight installations of a trial series in New Zealand that spanned a wide range of site productivity. Each installation typically contained four seedlots with differing levels of genetic improvement growing at three levels of stand density. Mixed effects models were used to examine the effects of stand density, site, seedlot genetic rating, and their interactions on Total Value (NZ$ ha(-1)) and Relative Value (NZ$ m(-3)). There was a strong positive relationship between stand density and Total Value, but there was generally no significant relationship between stand density and Relative Value. Of the variation in Total Value not explained by the fixed effect of stand density, approximately 60% was due to differences among trial installations (i.e. site) and 5-7% was due to seedlot genetic worth. There were significant first order interactions between seedlot and site, and between site and stand density. Seedlot genetic worth was able to explain a higher proportion of the variation in Relative Value (between 10 and 18% depending on the genetic trait under consideration). The genetic worth of a seedlot in terms of stem straightness rating was able to explain the greatest proportion of variation in Relative Value. These results highlight the importance of the choice of location and stand density management have on the economic returns from intensively-managed forests. While seedlot genetic rating has a smaller effect on economic returns, improvements in traits such as stem straightness and branch characteristics also make an important contribution. As silvicultural practices move towards higher stand densities, and the next generation of genetically improved trees are deployed, a more precise understanding of the interactions of site, silviculture and genetics will be needed. New ways of testing and modelling these interactions will be required but will ensure the delivery of a more informed approach to forest management.