Preprints
https://doi.org/10.5194/gmd-2024-42
https://doi.org/10.5194/gmd-2024-42
Submitted as: methods for assessment of models
 | 
13 Mar 2024
Submitted as: methods for assessment of models |  | 13 Mar 2024
Status: a revised version of this preprint is currently under review for the journal GMD.

Impacts of land-use change on biospheric carbon: an oriented benchmark using ORCHIDEE land surface model

Thi Lan Anh Dinh, Daniel Goll, Philippe Ciais, and Ronny Lauerwald

Abstract. Land-use change (LUC) impacts biospheric carbon, encompassing biomass carbon and soil organic carbon (SOC). Despite the use of dynamic global vegetation models (DGVMs) in estimating the anthropogenic perturbation of biospheric carbon stocks, critical evaluations of model performance concerning LUC impacts are scarce. Here, we present a systematic evaluation of the performance of the DGVM ORCHIDEE to reproduce observed LUC impacts on biospheric carbon stocks over Europe. First, we compare model predictions with observation-based gridded estimates of net and gross primary productivity (NPP and GPP), biomass growth patterns, and SOC stocks. Second, we evaluate the predicted response of carbon stocks to LUC based on data from forest inventories, paired plots, chronosequences and repeated sampling designs. Third, we use interpretable machine learning to identify factors contributing to discrepancies between simulations and observations, including drivers and processes not resolved in ORCHIDEE (e.g. erosion, soil fertility). Results indicate agreement between the model and observed spatial patterns and temporal trends, such as the increase in biomass with age, when simulating biosphere carbon stocks. The direction of the SOC responses to LUC generally aligns between simulated and observed data. However, the model underestimates carbon gains for cropland-to-grassland and carbon losses for grassland-to-cropland and forest-to-cropland conversions. These discrepancies are attributed to bias arising from soil erosion rate, which is not fully captured in ORCHIDEE. Our study provides an oriented benchmark for assessing the DGVMs against observations and explores its potential in studying the impact of LUCs on SOC stocks.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Thi Lan Anh Dinh, Daniel Goll, Philippe Ciais, and Ronny Lauerwald

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2024-42', Anonymous Referee #1, 23 Apr 2024
  • RC2: 'Comment on gmd-2024-42', Anonymous Referee #2, 04 May 2024
  • AC1: 'Comment on gmd-2024-42', Thi Lan Anh Dinh, 24 Jun 2024
Thi Lan Anh Dinh, Daniel Goll, Philippe Ciais, and Ronny Lauerwald
Thi Lan Anh Dinh, Daniel Goll, Philippe Ciais, and Ronny Lauerwald

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Short summary
The study assesses the performance of the dynamic global vegetation model (DGVM), ORCHIDEE, in capturing the impact of land-use change on carbon stocks across Europe. Comparisons with observations reveal that the model accurately represents carbon fluxes and stocks. Despite the underestimations in certain land-use conversions, the model describes general trends in soil carbon response to land-use change, aligning with the site observations.