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韧皮部筛管直径可预测木本植物茎的生长速度。

Diameters of phloem sieve elements can predict stem growth rates of woody plants.

机构信息

Northwest A&F University, College of Life Sciences, Yangling 712100, China.

Biomass Energy Center for Arid Lands, Northwest A & F University, Yangling 712100, China.

出版信息

Tree Physiol. 2022 Aug 6;42(8):1560-1569. doi: 10.1093/treephys/tpac022.

DOI:10.1093/treephys/tpac022
PMID:35218199
Abstract

Understanding forest dynamics is crucial to addressing climate change and reforestation challenges. Plant anatomy can help predict growth rates of woody plants, contributing key information on forest dynamics. Although features of the water-transport system (xylem) have long been used to predict plant growth, the potential contribution of carbon-transporting tissue (phloem) remains virtually unexplored. Here, we use data from 347 woody plant species to investigate whether species-specific stem diameter growth rates can be predicted by the diameter of both the xylem and phloem conducting cells when corrected for phylogenetic relatedness. We found positive correlations between growth rate, phloem sieve element diameter and xylem vessel diameter in liana species sampled in the field. Moreover, we obtained similar results for data extracted from the Xylem Database, an online repository of functional, anatomical and image data for woody plant species. Information from this database confirmed the correlation of sieve element diameter and growth rate across woody plants of various growth forms. Furthermore, we used data subsets to explore potential influences of biomes, growth forms and botanical family association. Subsequently, we combined anatomical and geoclimatic data to train an artificial neural network to predict growth rates. Our results demonstrate that sugar transport architecture is associated with growth rate to a similar degree as water-transport architecture. Furthermore, our results illustrate the potential value of artificial neural networks for modeling plant growth under future climatic scenarios.

摘要

理解森林动态对于应对气候变化和重新造林挑战至关重要。植物解剖学可以帮助预测木本植物的生长速度,为森林动态提供关键信息。尽管输水系统(木质部)的特征长期以来一直被用于预测植物生长,但碳输导组织(韧皮部)的潜在贡献实际上尚未得到探索。在这里,我们使用来自 347 种木本植物的数据来研究当校正系统发育相关性时,木质部和韧皮部导细胞的直径是否可以预测物种特异性的茎直径生长率。我们发现,在实地采样的藤本植物中,生长率与韧皮部筛管直径和木质部导管直径之间存在正相关关系。此外,我们从木质部数据库(一个木本植物功能、解剖和图像数据的在线存储库)中提取的数据也得到了类似的结果。该数据库中的信息证实了不同生长形式的木本植物中筛管直径与生长率之间的相关性。此外,我们使用数据子集来探索生物群落、生长形式和植物科属关联的潜在影响。随后,我们将解剖学和地理气候数据结合起来,训练人工神经网络来预测生长率。我们的结果表明,糖运输结构与生长率的关联程度与水运输结构相似。此外,我们的结果说明了人工神经网络在模拟未来气候情景下植物生长方面的潜在价值。

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