Purpose of Review

Producing wood of the right quality is an important part of forest management. In the same way that forest growth models are valuable decision support tools for producing desired yields, models that predict wood quality in standing trees should assist forest managers to make quality-influenced decisions. A challenge for wood quality (WQ) models is to predict the properties of potential products from standing trees, given multiple possible growing environments and silvicultural adjustments. While much research has been undertaken to model forest growth, much less work has focussed on producing wood quality models. As a result, many opportunities exist to expand our knowledge.

Recent Findings

There has been an increase in the availability and use of non-destructive methods for wood quality assessment in standing trees. In parallel, a range of new models have been proposed in the last two decades, predicting wood property variation, and as a result wood quality, using both fully empirical (statistical) and process-based (mechanistic) approaches.

Summary

We review here models that predict wood quality in standing trees. Although other research is mentioned where applicable, the focus is on research done within the last 20 years. We propose a simple classification of WQ models, first into two broad groupings: fully empirical and process-based. Comprehensive, although not exhaustive, summaries of a wide range of published models in both categories are given. The question of scale is addressed with relevance to the range of possibilities which these different types of models present. We distinguish between empirical models which predict stand or tree-level wood quality and those which predict within-tree wood quality variability. In this latter group are branching models (variation up the stem) and models predicting pith-to-bark clear-wood wood property variability. In the case of process-based models, simulation of within-tree variability, and specifically, how that variability arose over time, is always necessary. We discuss how wood quality models are, or should increasingly be, part of decision support systems that aid forest managers and give some perspectives on ways to increase model impact for forest management for wood quality.

中文翻译：

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木材质量建模进展及应用综述

审查目的

生产质量合适的木材是森林管理的重要组成部分。就像森林生长模型是产生预期产量的有价值的决策支持工具一样，预测立木木材质量的模型应该帮助森林管理者做出受质量影响的决策。考虑到多种可能的生长环境和造林调整，木材质量 (WQ) 模型面临的挑战是预测来自站立树木的潜在产品的特性。虽然已经进行了大量研究来模拟森林生长，但很少有工作专注于制作木材质量模型。因此，存在许多扩展我们知识的机会。

最近的发现

用于对立木进行木材质量评估的非破坏性方法的可用性和使用有所增加。与此同时，在过去的二十年中，人们提出了一系列新模型，预测木材特性变化，从而预测木材质量，同时使用完全经验（统计）和基于过程（机械）的方法。

概括

我们在这里回顾了预测立木木材质量的模型。尽管在适用的情况下提到了其他研究，但重点是在过去 20 年内完成的研究。我们提出了 WQ 模型的简单分类，首先分为两大类：完全经验和基于过程。对这两个类别中广泛的已发布模型进行了全面的（尽管不是详尽的）总结。规模问题与这些不同类型的模型所呈现的可能性范围有关。我们区分预测林分或树级木材质量的经验模型和预测树内木材质量变异性的经验模型。在后一组中是分枝模型（茎的变化）和预测从髓到树皮的清晰木材特性变化的模型。在基于过程的模型的情况下，总是需要模拟树内的可变性，特别是这种可变性如何随着时间的推移而产生。我们讨论了木材质量模型如何成为或应该越来越多地成为帮助森林管理者的决策支持系统的一部分，并就如何增加模型对森林管理对木材质量的影响提出一些看法。