Carbon use efficiency along resource stoichiometry gradients

Stefano Manzoni

Carbon use efficiency (CUE, the ratio of carbon used for growth over carbon taken up) is an important regulator of the carbon cycle. This dataset presents a collections of approximately 2200 CUE estimates at the single organism level (for animal consumers) and at the microbial community level, obtained from published literature sources. The dataset is designed to assess CUE changes along gradients of resource nutrient availability (nitrogen and phosphorus), in both terrestrial and aquatic ecosystems spanning all major climatic zones.

Terrestrial Soil Carbon Nitrogen Phosphorus Ecological stoichiometry Carbon-use efficiency Nutrient limitation

References

Manzoni S., Čapek P., Mooshammer M., Lindahl B., Richter A., H. Šantrůčková. 2017: Optimal metabolic regulation along resource stoichiometry gradients, Ecology Letters. DOI: 10.1111/ele.12815

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Data description

The dataset is provided in an xlsx file, which contains one 'data description' tab and one 'data' tab. The dataset is described in detail in the cited publication (Manzoni et al., 2017, Ecology Letters, doi: 10.1111/ele.12815). Specific explanations on data usage are provided in the data file.

Comments

CONDITIONS FOR USE: As a condition for the use of this database, we request that all users agree that: 1) Full citation to the main article Manzoni et al. (2017, Ecology Letters, doi: 10.1111/ele.12815) is provided when using the dataset. 2) This dataset is a collection of published data. Thus, full citation of the original articles (reported in the Supplementary Information to Manzoni et al. 2017) has to be provided when using data from individual species or sources. 3) The lead author S. Manzoni should be notified when the dataset is used in any publication or derivative work.
DISCLAIMER: The data points have been obtained from tables and digitalized figures, and in some cases subsequently analyzed, in the most accurate and reproduceable way. However, complete accuracy cannot be guaranteed and data are made available "as is". The authors of this dataset are thus not responsible for damages resulting from its use or interpretation in any derivative work.