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氮素和水分共同限制下森林光合作用与蒸腾作用的生态生理模型

An eco-physiological model of forest photosynthesis and transpiration under combined nitrogen and water limitation.

作者信息

Fransson Peter, Lim Hyungwoo, Zhao Peng, Tor-Ngern Pantana, Peichl Matthias, Laudon Hjalmar, Henriksson Nils, Näsholm Torgny, Franklin Oskar

机构信息

Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, Skogsmarksgränd 17, SE-901 83 Umeå, Sweden.

Interdisciplinary Center for Scientific Computing, Heidelberg University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany.

出版信息

Tree Physiol. 2025 Feb 3;45(2). doi: 10.1093/treephys/tpae168.

Abstract

Although the separate effects of water and nitrogen (N) limitations on forest growth are well known, the question of how to predict their combined effects remains a challenge for modeling of climate change impacts on forests. Here, we address this challenge by developing a new eco-physiological model that accounts for plasticity in stomatal conductance and leaf N concentration. Based on optimality principle, our model determines stomatal conductance and leaf N concentration by balancing carbon uptake maximization, hydraulic risk and cost of maintaining photosynthetic capacity. We demonstrate the accuracy of the model predictions by comparing them against gross primary production estimates from eddy covariance flux measurements and sap-flow measurement scaled canopy transpiration in a long-term fertilized and an unfertilized Scots pine (Pinus sylvestris L.) forest in northern Sweden. The model also explains the response to N fertilization as a consequence of (i) reduced carbon cost of N uptake and (ii) increased leaf area per hydraulic conductance. The results suggest that leaves optimally coordinate N concentration and stomatal conductance both on short (weekly) time scales in response to weather conditions and on longer time scales in response to soil water and N availabilities.

摘要

尽管水分和氮素(N)限制对森林生长的单独影响已为人熟知,但如何预测它们的综合影响仍是气候变化对森林影响建模面临的一项挑战。在此,我们通过开发一种新的生态生理模型来应对这一挑战,该模型考虑了气孔导度和叶片氮浓度的可塑性。基于最优性原理,我们的模型通过平衡碳吸收最大化、水力风险和维持光合能力的成本来确定气孔导度和叶片氮浓度。我们将模型预测结果与瑞典北部一片长期施肥和未施肥的苏格兰松(Pinus sylvestris L.)森林中涡度相关通量测量以及液流测量缩放冠层蒸腾的总初级生产力估计值进行比较,以此证明模型预测的准确性。该模型还解释了对氮肥施用的响应是由于(i)氮吸收的碳成本降低以及(ii)单位水力导度的叶面积增加。结果表明,叶片在短时间尺度(每周)上根据天气条件以及在长时间尺度上根据土壤水分和氮素有效性,对氮浓度和气孔导度进行了最优协调。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf21/11979779/a470986d8231/tpae168f1.jpg

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