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水力生态生理学与形成层生长的耦合模型——考虑生物物理限制和物候学可提高高时间分辨率下的茎直径预测能力。

A Coupled Model of Hydraulic Eco-Physiology and Cambial Growth - Accounting for Biophysical Limitations and Phenology Improves Stem Diameter Prediction at High Temporal Resolution.

作者信息

Liu Che, Peltoniemi Mikko, Alekseychik Pavel, Mäkelä Annikki, Hölttä Teemu

机构信息

Department of Forest Sciences, Faculty of Agriculture and Forestry, University of Helsinki, Helsinki, Finland.

Institute for Atmospheric and Earth System Research (INAR), University of Helsinki, Helsinki, Finland.

出版信息

Plant Cell Environ. 2025 Feb;48(2):1344-1365. doi: 10.1111/pce.15239. Epub 2024 Oct 24.

Abstract

Traditional photosynthesis-driven growth models have considerable uncertainties in predicting tree growth under changing climates, partially because sink activities are directly affected by the environment but not adequately addressed in growth modelling. Therefore, we developed a semi-mechanistic model coupling stomatal optimality, temperature control of enzymatic activities and phenology of cambial growth. Parameterized using Bayesian inference and measured data on Picea abies and Pinus sylvestris in peatland and mineral soils in Finland, the coupled model simulates transpiration and assimilation rates and stem radial dimension (SRD) simultaneously at 30 min resolution. The results suggest that both the sink and phenological formulations with environmental effects are indispensable for capturing SRD dynamics across hourly to seasonal scales. Simulated using the model, growth was more sensitive than assimilation to temperature and soil water, suggesting carbon gain is not driving growth at the current temporal scale. Also, leaf-specific production was occasionally positively correlated with growth duration but not with growth onset timing or annual cambial area increment. Thus, as it is hardly explained by carbon gain, phenology itself should be included in sink-driven growth models of the trees in the boreal zone and possibly other environments where sink activities and photosynthesis are both restrained by harsh conditions.

摘要

传统的光合作用驱动生长模型在预测气候变化下树木的生长方面存在相当大的不确定性,部分原因是库活动直接受环境影响,但在生长模型中未得到充分考虑。因此,我们开发了一个半机制模型,该模型耦合了气孔最优性、酶活性的温度控制和形成层生长的物候。利用贝叶斯推理以及芬兰泥炭地和矿质土壤中欧洲云杉和欧洲赤松的实测数据进行参数化,该耦合模型以30分钟的分辨率同时模拟蒸腾速率、同化速率和茎径向尺寸(SRD)。结果表明,考虑环境影响的库和物候公式对于捕捉从小时到季节尺度的SRD动态都是必不可少的。使用该模型进行模拟,生长对温度和土壤水分的敏感性高于同化,这表明在当前时间尺度上碳获取并非驱动生长的因素。此外,叶特定产量偶尔与生长持续时间呈正相关,但与生长开始时间或年形成层面积增量无关。因此,由于很难用碳获取来解释,物候本身应纳入北方地区以及可能其他库活动和光合作用均受恶劣条件限制的环境中树木的库驱动生长模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/15db/11695789/d069db509df3/PCE-48-1344-g003.jpg

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