Abstract
Abstract. Nitrogen is an essential element controlling ecosystem carbon (C) productivity and its response to climate change and atmospheric [CO2] increase. This study presents the evaluation – focussing on gross primary production (GPP) – of a new version of the ORCHIDEE model that gathers the representation of the nitrogen cycle and of its interactions with the carbon cycle from the OCN model and the most recent developments from the ORCHIDEE trunk version. We quantify the model skills at 78 FLUXNET sites by simulating the observed mean seasonal cycle, daily mean flux variations, and annual mean average GPP flux for grasslands and forests. Accounting for carbon–nitrogen interactions does not substantially change the main skills of ORCHIDEE, except for the site-to-site annual mean GPP variations, for which the version with carbon–nitrogen interactions is in better agreement with observations. However, the simulated GPP response to idealised [CO2] enrichment simulations is highly sensitive to whether or not carbon–nitrogen interactions are accounted for. Doubling of the atmospheric [CO2] induces an increase in the GPP, but the site-averaged GPP response to a CO2 increase projected by the model version with carbon–nitrogen interactions is half of the increase projected by the version without carbon–nitrogen interactions. This model's differentiated response has important consequences for the transpiration rate, which is on average 50 mm yr−1 lower with the version with carbon–nitrogen interactions. Simulated annual GPP for northern, tropical and southern latitudes shows good agreement with the observation-based MTE-GPP (model tree ensemble gross primary production) product for present-day conditions. An attribution experiment making use of this new version of ORCHIDEE for the time period 1860–2016 suggests that global GPP has increased by 50 %, the main driver being the enrichment of land in reactive nitrogen (through deposition and fertilisation), followed by the [CO2] increase. Based on our factorial experiment and sensitivity analysis, we conclude that if carbon–nitrogen interactions are accounted for, the functional responses of ORCHIDEE r4999 better agree with the current understanding of photosynthesis than when the carbon–nitrogen interactions are not accounted for and that carbon–nitrogen interactions are essential in understanding global terrestrial ecosystem productivity.
Highlights
Global terrestrial ecosystem models (GTEMs) are mathematical models which are dedicated to provide a better understanding of terrestrial ecosystem functioning and its interplay with environmental drivers such as temperature or precipitation
Based on our factorial experiment and sensitivity analysis, we conclude that if carbon–nitrogen interactions are accounted for, the functional responses of ORCHIDEE r4999 better agree with the current understanding of photosynthesis than when the carbon–nitrogen interactions are not accounted for and that carbon–nitrogen interactions are essential in understanding global terrestrial ecosystem productivity
In order to analyse how ORCHIDEE r4999 performs compared to r3977, we evaluated the gross primary production (GPP) simulated by ORCHIDEE r3977
Summary
Global terrestrial ecosystem models (GTEMs) are mathematical models which are dedicated to provide a better understanding of terrestrial ecosystem functioning and its interplay with environmental drivers such as temperature or precipitation. GTEMs aim at simulating the spatial patterns of the fluxes of carbon, water and energy between the land surface and the atmosphere, as well as their time evolution, in particular in a context of climate change. GTEMs accounted for climate forcing as well as the effect of atmospheric CO2 concentration (atmospheric [CO2]) on ecosystem productivity (Melillo et al, 1995). Atmospheric [CO2] is a key driver of the assimilation of carbon by photosynthesis. In the context of global change, wherein atmospheric [CO2] is increasing, quantifying the so-called [CO2] fertilisation effect, i.e. the increase in ecosystem productivity associated with increasing atmospheric [CO2], has been at the forefront (Lobell and Field, 2008; Wullschleger et al, 1995)
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