A process-based framework for validating forest landscape modeling outcomes

IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Environmental Modelling & Software Pub Date : 2025-02-01 DOI:10.1016/j.envsoft.2025.106327
Mia M. Wu , Yu Liang , Hong S. He , Jian Yang , Bo Liu , Tianxiao Ma
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Abstract

Forest landscape models (FLMs) simulate forest dynamics by integrating stand- and landscape-scale processes. Thus, evaluating FLMs simulations necessitates including both processes. Thus far, stand-scale processes were evaluated in some FLMs, whereas landscape-scale processes were rarely evaluated. This study presents a framework that evaluates both stand- and landscape-scale processes. For the stand-scale processes, we proposed using stand density management diagrams to evaluate the simulated stand development trajectories that encapsulate the interplay of tree growth, competition, and mortality. For the landscape-scale processes, we evaluated seed dispersal, the basic spatial process driving forest landscape dynamics and not evaluated previously, through comparing simulated tree species colonization pattern against tree age distribution data from inventory data. We demonstrated the applicability of the framework to a 300-year historical forest landscape reconstructed using LANDIS. Given the common features, the framework is applicable to other FLMs or terrestrial ecosystem models operating at large scales.
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用于验证森林景观建模结果的基于过程的框架
森林景观模型(FLMs)通过整合林分尺度和景观尺度过程来模拟森林动态。因此,评估flm模拟需要包括这两个过程。迄今为止,林分尺度的过程在一些生态系统中得到了评价,而景观尺度的过程很少得到评价。本研究提出了一个评估林分尺度和景观尺度过程的框架。对于林分尺度的过程,我们建议使用林分密度管理图来评估包含树木生长、竞争和死亡相互作用的模拟林分发展轨迹。对于景观尺度的过程,我们通过比较模拟树种定植模式和清查数据中的树龄分布数据,评估了种子传播这一驱动森林景观动态的基本空间过程。我们展示了该框架对使用LANDIS重建的300年历史森林景观的适用性。鉴于这些共同特征,该框架适用于其他大尺度的陆地生态系统模型或陆地生态系统模型。
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来源期刊
Environmental Modelling & Software
Environmental Modelling & Software 工程技术-工程:环境
CiteScore
9.30
自引率
8.20%
发文量
241
审稿时长
60 days
期刊介绍: Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.
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