Stand-level growth models for long-term projections of the main species groups in Norway

IF 1.8 3区 农林科学 Q2 FORESTRY Scandinavian Journal of Forest Research Pub Date : 2022-02-17 DOI:10.1080/02827581.2022.2056632
Kobra Maleki, R. Astrup, C. Kuehne, J. Mclean, C. Antón-Fernández
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引用次数: 2

Abstract

ABSTRACT Stand-level growth and yield models are important tools that support forest managers and policymakers. We used recent data from the Norwegian National Forest Inventory to develop stand-level models, with components for dominant height, survival (number of survived trees), ingrowth (number of recruited trees), basal area, and total volume, that can predict long-term stand dynamics (i.e. 150 years) for the main species in Norway, namely Norway spruce (Picea abies (L.) Karst.), Scots pine (Pinus sylvestris L.), and birch (Betula pubescens Ehrh. and Betula pendula Roth). The data used represent the structurally heterogeneous forests found throughout Norway with a wide range of ages, tree size mixtures, and management intensities. This represents an important alternative to the use of dedicated and closely monitored long-term experiments established in single species even-aged forests for the purpose of building these stand-level models. Model examination by means of various fit statistics indicated that the models were unbiased, performed well within the data range and extrapolated to biologically plausible patterns. The proposed models have great potential to form the foundation for more sophisticated models, in which the influence of other factors such as natural disturbances, stand structure including species mixtures, and management practices can be included.
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挪威主要物种群长期预测的林分水平增长模型
摘要林分水平的增长和产量模型是支持森林管理者和决策者的重要工具。我们使用挪威国家森林目录的最新数据来开发林分水平模型,该模型包含优势高度、存活率(存活树木的数量)、向内生长率(招募的树木数量)、基底面积和总体积的组成部分,可以预测挪威主要物种的长期林分动态(即150年),即挪威云杉(Picea abies(L.)Karst.),苏格兰松(Pinus sylvestris L.)和桦树(Betula pubescens Ehrh.和Betula pendula Roth)。所使用的数据代表了挪威各地发现的结构异质的森林,其年龄、树木大小的混合物和管理强度各不相同。这是一个重要的替代方案,可以替代在单一物种甚至老化的森林中建立的专门和密切监测的长期实验,以建立这些林分水平的模型。通过各种拟合统计进行的模型检验表明,模型是无偏的,在数据范围内表现良好,并推断出生物学上合理的模式。所提出的模型有很大的潜力为更复杂的模型奠定基础,其中可以包括其他因素的影响,如自然干扰、包括物种混合物在内的林分结构和管理实践。
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来源期刊
CiteScore
3.00
自引率
5.60%
发文量
26
审稿时长
3.3 months
期刊介绍: The Scandinavian Journal of Forest Research is a leading international research journal with a focus on forests and forestry in boreal and temperate regions worldwide.
期刊最新文献
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