Global resorption efficiencies and concentrations of carbon and nutrients in leaves of terrestrial plants

营养物 生态学 常绿 每年落叶的 营养循环 吸收 植物 生物地球化学循环 生物 农学 化学 内分泌学 有机化学
作者
Leonardus Vergütz,Stefano Manzoni,Amilcare Porporato,Roberto Ferreira Novais,Robert B. Jackson
出处
期刊:Ecological Monographs [Wiley]
卷期号:82 (2): 205-220 被引量:521
标识
DOI:10.1890/11-0416.1
摘要

Nutrient resorption in plants influences nutrient availability and cycling and is a key process in biogeochemical models. Improved estimates of resorption parameters are needed for predicting long‐term primary productivity and for improving such models. Currently, most models assume a value of 50% resorption for nitrogen (N) and phosphorus (P) and lack resorption data for other nutrients and for specific vegetation types. We provide global estimates of resorption efficiencies and nutrient concentrations for carbon (C), N, and P and the first global‐scale estimates for essential nutrients such as potassium (K), calcium (Ca), and magnesium (Mg). We also examine leaf mass loss during senescence (LML) globally and for different plant types, thus defining a mass loss correction factor (MLCF) needed to quantify unbiased resorption values. We used a global meta‐analysis of 86 studies and ∼1000 data points across climates for green and senesced leaves in six plant types: ferns, forbs, graminoids, conifers, and evergreen and deciduous woody angiosperms. In general, N and P resorption differed significantly from the commonly used global value of 50% (62.1%, 64.9%, respectively; P < 0.05). Ca, C, and Mg showed lower average resorptions of 10.9%, 23.2%, and 28.6%, respectively, while K had the highest resorption, at 70.1%. We also found that resorption of all nutrients except Ca depended on leaf nutrient‐status; globally, C, N, P, K, and Mg showed a decrease in resorption with increased nutrient status. On average, global leaf mass loss was 24.2%. Overall, our resorption data differ substantially from commonly assumed values and should help improve ecological theory and biogeochemical and land‐surface models.
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