Purpose of Review

Forest models are becoming essential tools in forest research, management, and policymaking but currently are under deep transformation. In this review of the most recent literature (2018–2022), we aim to provide an updated general view of the main topics currently attracting the efforts of forest modelers, the trends already in place, and some of the current and future challenges that the field will face.

Recent Findings

Four major topics attracting most of on current modelling efforts: data acquisition, productivity estimation, ecological pattern predictions, and forest management related to ecosystem services. Although the topics may seem different, they all are converging towards integrated modelling approaches by the pressure of climate change as the major coalescent force, pushing current research efforts into integrated mechanistic, cross-scale simulations of forest functioning and structure.

Summary

We conclude that forest modelling is experiencing an exciting but challenging time, due to the combination of new methods to easily acquire massive amounts of data, new techniques to statistically process such data, and refinements in mechanistic modelling that are incorporating higher levels of ecological complexity and breaking traditional barriers in spatial and temporal scales. However, new available data and techniques are also creating new challenges. In any case, forest modelling is increasingly acknowledged as a community and interdisciplinary effort. As such, ways to deliver simplified versions or easy entry points to models should be encouraged to integrate non-modelers stakeholders into the modelling process since its inception. This should be considered particularly as academic forest modelers may be increasing the ecological and mathematical complexity of forest models.

中文翻译：

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森林生态系统建模的最新趋势：新方法还是新方法？

审查目的

森林模型正在成为森林研究、管理和决策的重要工具，但目前正处于深刻变革之中。在这篇对最新文献（2018-2022 年）的回顾中，我们旨在对当前吸引森林建模者努力的主要主题、已经存在的趋势以及当前和未来的一些挑战提供更新的总体看法领域将面对。

最近的发现

吸引当前建模工作最多的四个主要主题：数据采集、生产力估计、生态格局预测和与生态系统服务相关的森林管理。尽管主题可能看起来不同，但它们都在气候变化的压力下趋向于综合建模方法作为主要的联合力量，将当前的研究工作推向森林功能和结构的综合机械、跨尺度模拟。

概括

我们得出的结论是，森林建模正在经历一个激动人心但充满挑战的时期，这是由于结合了可轻松获取大量数据的新方法、统计处理此类数据的新技术以及结合了更高水平的生态复杂性和打破空间和时间尺度上的传统障碍。然而，新的可用数据和技术也带来了新的挑战。无论如何，森林建模越来越被认为是一项社区和跨学科的工作。因此，应该鼓励提供简化版本或简单的模型入口点的方法，以将非建模者的利益相关者从建模过程开始就整合到建模过程中。