Evidence map›Paper›PMID 42570310›Full record

ArticleTree physiology2026

Nutrient-mediated tree growth responses are governed by internal resource allocation: intra-organ water-carbon trade-offs and inter-organ carbon concentration gradient.

Hui Shao, Huimin Wang, Frederick C Meinzer, Xiaoqin Dai, Shengwang Meng, Liang Kou, Decai Gao, Fusheng Chen, Xiaoli Fu

Abstract read
In one paragraph

Article in Tree physiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Hui ShaoQianyanzhou Ecological Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China.
Huimin WangQianyanzhou Ecological Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China.
Frederick C MeinzerDepartment of Forest Ecosystems and Society, Oregon State University, 1500 SW Jefferson Way, Corvallis, OR 97331, USA.ORCID 0000-0003-2387-2031
Xiaoqin DaiQianyanzhou Ecological Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China.ORCID 0000-0001-7506-9406
Shengwang MengQianyanzhou Ecological Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China.
Liang KouQianyanzhou Ecological Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China.
Decai GaoQianyanzhou Ecological Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China.
Fusheng ChenJiangxi Provincial Key Laboratory of Silviculture, College of Forestry, Jiangxi Agricultural University, No. 1101 Zhimin Road, Economic & Technological Development Zone, Nanchang, Jiangxi 330045, China.
Xiaoli FuQianyanzhou Ecological Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China.ORCID 0000-0001-9116-4745

Funding

National Key Research and Development Program of China 2022YFD2201500National Natural Science Foundation of China 32122060National Natural Science Foundation of China 32271860National Natural Science Foundation of China 32330071
6 · The paper itself

Abstract

Nutrient deposition is reshaping forest productivity, yet the physiological mechanisms linking nitrogen (N) and phosphorus (P) enhancement to tree growth remain incompletely resolved. We propose that internal resource allocation strategies-specifically intra-organ trade-offs between water and carbohydrate resources and inter-organ carbohydrate concentration gradient-mediate nutrient-driven tree growth responses. Using a long-term fertilization experiment in subtropical Cunninghamia lanceolata (Lamb.) Hook. plantations, we measured relative water content (RWC) and traditional resource concentrations [soluble sugar (SS) concentration; starch (ST) concentration] during drought season. We rank-transformed RWC, SS and ST within each organ type across all samples. Intra-organ water-carbon trade-offs were quantified as two normalized ratios: ln(RWCrank/SSrank) for RWC:SS and ln(RWCrank/STrank) for RWC:ST, where higher values indicate greater solute dependence for turgor maintenance or greater ST storage volume fraction, respectively. The inter-organ carbon concentration gradient was quantified as differences in SS or ST between leaves and twigs (SSleaf-twig, STleaf-twig); and between absorptive roots and transport roots. We demonstrated three key nutrient-specific responses: (i) N addition promoted transport root ln(RWCrank/SSrank) while enhancing leaf ln(RWCrank/STrank), amplifying STleaf-twig; (ii) P addition reduced leaf and twig ln(RWCrank/SSrank) and (iii) combined N+P addition reduced twig ln(RWCrank/SSrank), while increasing leaf and twig ln(RWCrank/STrank). These reorganization patterns had direct growth consequences: while traditional resource concentrations explained 26.0% of growth variation, incorporating derived attributes increased explanatory power by 43.5% (to 37.3% total variance explained). Notably, the twig ln(RWCrank/STrank) emerged as the single strongest growth predictor, where N+P induced ST dominance correlated with enhanced growth rate. Nitrogen enrichment enhanced SS dominance in transport roots, a pattern that may occur at the expense of stem growth. Our results establish an internal resource allocation framework that mechanistically links nutrient-mediated carbon management patterns to forest productivity under global change, revealing how N+P co-enrichment synergistically optimizes carbon resource storage and utilization beyond single-nutrient effects.

Indexed as

CarbonCunninghamiaTreesWaterCarbohydrate MetabolismDroughtsNitrogenNutrientsPhosphorusPlant LeavesPlant RootsCarbonNitrogenPhosphorusWatergrowth ratenonstructural carbohydratenutrient gradientwater–carbon interdependencywater storage

Identifiers

PMID42570310
PMCPMC13565153

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.