Estimating soil organic carbon changes in managed temperate moist grasslands with RothC

PLoS One. 2021 Aug 20;16(8):e0256219. doi: 10.1371/journal.pone.0256219. eCollection 2021.

Abstract

Temperate grassland soils store significant amounts of carbon (C). Estimating how much livestock grazing and manuring can influence grassland soil organic carbon (SOC) is key to improve greenhouse gas grassland budgets. The Rothamsted Carbon (RothC) model, although originally developed and parameterized to model the turnover of organic C in arable topsoil, has been widely used, with varied success, to estimate SOC changes in grassland under different climates, soils, and management conditions. In this paper, we hypothesise that RothC-based SOC predictions in managed grasslands under temperate moist climatic conditions can be improved by incorporating small modifications to the model based on existing field data from diverse experimental locations in Europe. For this, we described and evaluated changes at the level of: (1) the soil water function of RothC, (2) entry pools accounting for the degradability of the exogenous organic matter (EOM) applied (e.g., ruminant excreta), (3) the month-on-month change in the quality of C inputs coming from plant residues (i.e above-, below-ground plant residue and rhizodeposits), and (4) the livestock trampling effect (i.e., poaching damage) as a common problem in areas with higher annual precipitation. In order to evaluate the potential utility of these changes, we performed a simple sensitivity analysis and tested the model predictions against averaged data from four grassland experiments in Europe. Our evaluation showed that the default model's performance was 78% and whereas some of the modifications seemed to improve RothC SOC predictions (model performance of 95% and 86% for soil water function and plant residues, respectively), others did not lead to any/or almost any improvement (model performance of 80 and 46% for the change in the C input quality and livestock trampling, respectively). We concluded that, whereas adding more complexity to the RothC model by adding the livestock trampling would actually not improve the model, adding the modified soil water function and plant residue components, and at a lesser extent residues quality, could improve predictability of the RothC in managed grasslands under temperate moist climatic conditions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Carbon / metabolism*
  • Climate Change*
  • Ecosystem*
  • Europe
  • Grassland
  • Greenhouse Gases / metabolism
  • Livestock
  • Manure
  • Soil / chemistry*
  • Water / metabolism*

Substances

  • Greenhouse Gases
  • Manure
  • Soil
  • Water
  • Carbon

Grants and funding

We gratefully acknowledge the financial support of the Fundación Cándido de Iturriaga y Maria del Dañobeitia, Juan de la Cierva and the European Union's Horizon 2020 Research and Innovation Action (RIA) through the project “Innovation for sustainable sheep and Goat production in Europe (iSAGE)” undergrant agreement No 679302. BC3 is supported by the Basque Government through the BERC 2018-2021 program and by Spanish Ministry of Economy and Competitiveness MINECO through BC3 María de Maeztu excellence accreditation MDM-2017-0714. Agustin del Prado is financed by the programme Ramon y Cajal from the Spanish Ministry of Economy, Industry and Competitiveness (RYC-2017-22143). María Almagro was supported by the Juan de la Cierva Program (grant IJCI-2015-23500). Finally, we thank Dr. Katja Klumpp, Dr. Stephanie Jones and Dr. Magdalena Necpálová for providing useful information on field sites. The French field data was financed through French National Agency for Research (ANAEE-F, ANR-11-INBS-0001). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.