Suppr超能文献

利用树木年轮、δ¹³C、δ¹⁸O 和基于过程的模型研究古老生长的黄松生理学。

Investigating old-growth ponderosa pine physiology using tree-rings, δ C, δ O, and a process-based model.

机构信息

Bioscience Division, Los Alamos National Laboratory, P.O. Box 1663 MS M888, Los Alamos, New Mexico, 87545, USA.

Department of Forest Ecosystems and Society, Oregon State University, Corvallis, Oregon, 97331, USA.

出版信息

Ecology. 2019 Jun;100(6):e02656. doi: 10.1002/ecy.2656. Epub 2019 Apr 15.

Abstract

In dealing with predicted changes in environmental conditions outside those experienced today, forest managers and researchers rely on process-based models to inform physiological processes and predict future forest growth responses. The carbon and oxygen isotope ratios of tree-ring cellulose (δ C , δ O ) reveal long-term, integrated physiological responses to environmental conditions. We incorporated a submodel of δ O into the widely used Physiological Principles in Predicting Growth (3-PG) model for the first time, to complement a recently added δ C submodel. We parameterized the model using previously reported stand characteristics and long-term trajectories of tree-ring growth, δ C , and δ O collected from the Metolius AmeriFlux site in central Oregon (upland trees). We then applied the parameterized model to a nearby set of riparian trees to investigate the physiological drivers of differences in observed basal area increment (BAI) and δ C trajectories between upland and riparian trees. The model showed that greater available soil water and maximum canopy conductance likely explain the greater observed BAI and lower δ C of riparian trees. Unexpectedly, both observed and simulated δ O trajectories did not differ between the upland and riparian trees, likely due to similar δ O of source water isotope composition. The δ O submodel with a Peclet effect improved model estimates of δ O because its calculation utilizes 3-PG growth and allocation processes. Because simulated stand-level transpiration (E) is used in the δ O submodel, aspects of leaf-level anatomy such as the effective path length for transport of water from the xylem to the sites of evaporation could be estimated.

摘要

在应对目前环境条件以外的预测变化时,森林管理者和研究人员依赖基于过程的模型来了解生理过程并预测未来森林的生长反应。树木年轮纤维素的碳和氧同位素比值(δC、δO)揭示了长期综合的环境条件生理反应。我们首次将氧同位素的子模型纳入广泛使用的预测生长生理原理(3-PG)模型中,以补充最近添加的碳同位素子模型。我们使用以前报告的林分特征和从俄勒冈州中部梅托利乌斯 AmeriFlux 站点收集的树木年轮生长、δC 和 δO 的长期轨迹来对模型进行参数化。然后,我们将参数化模型应用于附近一组河岸树木,以研究观测到的底面积增量(BAI)和河岸树木 δC 轨迹之间差异的生理驱动因素。该模型表明,更大的可用土壤水和最大冠层导度可能解释了河岸树木更高的观测 BAI 和更低的 δC。出乎意料的是,河岸树木和模拟树木的 δO 轨迹没有差异,这可能是由于源水同位素组成的 δO 相似。具有 Peclet 效应的 δO 子模型改善了 δO 的模型估计,因为其计算利用了 3-PG 的生长和分配过程。由于 δO 子模型使用了模拟的林分蒸腾量(E),因此可以估计叶片解剖结构的某些方面,例如从木质部到蒸发部位的水运输的有效路径长度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e65b/6850584/a55031e26f41/ECY-100-na-g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验