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Summary Leaf dark respiration (Rdark), an important yet rarely quantified component of carbon cycling in forest ecosystems, is often simulated from leaf traits such as the maximum carboxylation capacity (Vcmax), leaf mass per area (LMA), nitrogen (N) and phosphorus (P) concentrations, in terrestrial biosphere models. However, the validity of these relationships across forest types remains to be thoroughly assessed.Here, we analyzedRdarkvariability and its associations withVcmaxand other leaf traits across three temperate, subtropical and tropical forests in China, evaluating the effectiveness of leaf spectroscopy as a superior monitoring alternative.We found that leaf magnesium and calcium concentrations were more significant in explaining cross‐siteRdarkthan commonly used traits like LMA, N and P concentrations, but univariate trait–Rdarkrelationships were always weak (r2 ≤ 0.15) and forest‐specific. Although multivariate relationships of leaf traits improved the model performance, leaf spectroscopy outperformed trait–Rdarkrelationships, accurately predicted cross‐siteRdark(r2 = 0.65) and pinpointed the factors contributing toRdarkvariability.Our findings reveal a few novel traits with greater cross‐site scalability regardingRdark, challenging the use of empirical trait–Rdarkrelationships in process models and emphasize the potential of leaf spectroscopy as a promising alternative for estimatingRdark, which could ultimately improve process modeling of terrestrial plant respiration.
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This content will become publicly available on May 19, 2026
Deciphering the variability of leaf phosphorus‐allocation strategies using leaf economic traits and reflectance spectroscopy across diverse forest types
Summary Allocation of leaf phosphorus (P) among different functional fractions represents a crucial adaptive strategy for optimizing P use. However, it remains challenging to monitor the variability in leaf P fractions and, ultimately, to understand P‐use strategies across diverse plant communities.We explored relationships between five leaf P fractions (orthophosphate P, Pi; lipid P, PL; nucleic acid P, PN; metabolite P, PM; and residual P, PR) and 11 leaf economic traits of 58 woody species from three biomes in China, including temperate, subtropical and tropical forests. Then, we developed trait‐based models and spectral models for leaf P fractions and compared their predictive abilities.We found that plants exhibiting conservative strategies increased the proportions of PNand PM, but decreased the proportions of Piand PL, thus enhancing photosynthetic P‐use efficiency, especially under P limitation. Spectral models outperformed trait‐based models in predicting cross‐site leaf P fractions, regardless of concentrations (R2 = 0.50–0.88 vs 0.34–0.74) or proportions (R2 = 0.43–0.70 vs 0.06–0.45).These findings enhance our understanding of leaf P‐allocation strategies and highlight reflectance spectroscopy as a promising alternative for characterizing large‐scale leaf P fractions and plant P‐use strategies, which could ultimately improve the physiological representation of the plant P cycle in land surface models.
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- Award ID(s):
- 2045968
- PAR ID:
- 10591253
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- New Phytologist
- Volume:
- 247
- Issue:
- 3
- ISSN:
- 0028-646X
- Format(s):
- Medium: X Size: p. 1129-1144
- Size(s):
- p. 1129-1144
- Sponsoring Org:
- National Science Foundation
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