GFDL - Geophysical Fluid Dynamics Laboratory

Nitrogen cycling and feedbacks in a global dynamic land model

Key Findings

  • A new GFDL land model, LM3V-N, has been developed and includes nitrogen cycling and its feedbacks on terrestrial carbon.
  • LM3V-N captures features known to be essential from empirical studies of forest and grassland ecosystems.
  • LM3V-N offers a more realistic representation of real-world terrestrial ecosystem dynamics.

Stefan Gerber, Hedin L.O., Oppenheimer M., Pacala S.W., Shevliakova, E.. Global Biogeochemical Cycles – 24, doi:10.1029/2008GB00333.

Stefan Gerber and his colleagues at Princeton Cooperative Institute for Climate studies published a paper describing Nitrogen (N) cycling and its feedbacks on terrestrial Carbon (C) in a new GFDL land model LM3V-N. The new model simulates how nitrogen nutrient availability affects carbon exchange between land and atmosphere, and improves constraints on feedbacks among CO2, climate, and land dynamics in the GFDL Earth System Models.

The new model captures features that are known to be essential from empirical studies of forest and grassland ecosystems. It captures observed changes in forest net primary productivity under elevated CO2 as in free-air CO2 enrichment experiments (FACE). Modeled physical disturbance (i.e. removal of plant biomass) induces carbon-nitrogen (C-N) feedbacks expressed as increased soil nitrogen loss followed by vegetation recovery and nitrogen limitation. This is in line with theories and observations of successional vegetation dynamics. Finally, in contrast to other leading models, the model predicts a weakening of C-N feedbacks when ecosystem steady-state is approached.

The magnitude of the carbon feedback on climate change is one of the largest uncertainties in making future climate projections. This addition to the land model allows us to address this large uncertainty. It offers a more realistic representation of real-world terrestrial ecosystem dynamics.

Click here to access the manuscript that is in press.