Meta-Modelling to Quantify Yields of White Spruce and Hybrid Spruce Provenances in the Canadian Boreal Forest?

编号 010024201

推送时间 20200608

研究领域 森林生态 

年份 2020 

类型 期刊 

语种 英语

标题 Meta-Modelling to Quantify Yields of White Spruce and Hybrid Spruce Provenances in the Canadian Boreal Forest?

来源期刊 forest

期 第242期

发表时间 20200528

关键词 tree improvement;  growth and yield;  climatic transfer distances;  meta-model;  random-coefficients modelling; 

摘要 Tree improvement programs can improve forest management by increasing timber yields in some areas, thereby facilitating conservation of other forest lands. In this study, we used a meta-analytic approach to quantify yields of alternative white (Picea glauca (Moench) Voss) and hybrid spruce (Picea engelmannii Parry ex Engelmann x Picea glauca (Moench) Voss) stocks across planting sites in the boreal and hemiboreal forests of Canada. We extracted meta-data from published tree improvement program results for five Canadian provinces covering 38 planting sites and 330 white and hybrid spruce provenances. Using these meta-data and a random-coefficients nonlinear mixed-effects modelling approach, we modelled average height over time trajectories for varying planting site characteristics, as well as climate transfer distances between planting sites and provenances. Climatic transfer distances had strong effects on the height trajectory parameters. In particular, the asymptote parameter had a nonlinear increasing trend with planting site versus provenance mean annual temperature differences. We incorporated the height trajectory meta-analysis model into an existing growth and yield model to predict volume yields. Overall, this research provides a mechanism to quantify yields of alternative provenances at a particular planting site, as a component of decision support models for evaluating evaluate forest management investment into improved planting stocks alternatives under current and possible future climates.

服务人员 王璐

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