Long-term ecosystem nitrogen limitation from foliar δ15N data and a land surface model

Silvia Caldararu, Tea Thum, Lin Yu, Melanie Kern, Richard Nair, Sönke Zaehle

Research output: Contribution to journalArticlepeer-review

Abstract

The effect of nutrient availability on plant growth and the terrestrial carbon sink under climate change and elevated CO2 remains one of the main uncertainties of the terrestrial carbon cycle. This is partially due to the difficulty of assessing nutrient limitation at large scales over long periods of time. Consistent declines in leaf nitrogen (N) content and leaf δ15N have been used to suggest that nitrogen limitation has increased in recent decades, most likely due to the concurrent increase in atmospheric CO2. However, such data sets are often not straightforward to interpret due to the complex factors that contribute to the spatial and temporal variation in leaf N and isotope concentration. We use the land surface model (LSM) QUINCY, which has the unique capacity to represent N isotopic processes, in conjunction with two large data sets of foliar N and N isotope content. We run the model with different scenarios to test whether foliar δ15N isotopic data can be used to infer large-scale N limitation and if the observed trends are caused by increasing atmospheric CO2, changes in climate or changes in sources and magnitude of anthropogenic N deposition. We show that while the model can capture the observed change in leaf N content and predict widespread increases in N limitation, it does not capture the pronounced, but very spatially heterogeneous, decrease in foliar δ15N observed in the data across the globe. The addition of an observation-based temporal trend in isotopic composition of N deposition leads to a more pronounced decrease in simulated leaf δ15N. Our results show that leaf δ15N observations cannot, on their own, be used to assess global-scale N limitation and that using such a data set in conjunction with an LSM can reveal the drivers behind the observed patterns.

Original languageEnglish
Pages (from-to)493-508
JournalGlobal Change Biology
Volume28
Issue number2
Early online date2021
DOIs
Publication statusPublished - 2022

Subject classification (UKÄ)

  • Physical Geography

Keywords

  • CO fertilization
  • land surface model
  • nitrogen
  • nitrogen deposition
  • nutrients
  • vegetation model

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