Drivers of long-term grassland CO2 fluxes and regrowth: effects of management and meteorological conditions over time

Grasslands serve a unique role in the global carbon (C) cycle and cover about 30 % of the European and about 70 % of the Swiss agricultural area. Carbon dioxide (CO2) fluxes of managed grasslands are substantially influenced by land management practices and meteorological conditions, but the temporal development of these drivers is still uncertain. With the eddy covariance (EC) technique, net ecosystem CO2 exchange (NEE) can be directly measured, and then partitioned into gross primary production (GPP; amount of CO2 fixed through photosynthesis) and ecosystem respiration (Reco; amount of CO2 released via plant and soil respiration). We used 20 years (2005–2024) of EC fluxes, meteorological data, and detailed management information collected from an intensively managed grassland site (Chamau) in Switzerland, and employed machine learning approaches, i.e., eXtreme Gradient Boosting (XGBoost) models in combination with SHapley Additive exPlanations (SHAP) analyses, to identify drivers and their temporal contributions over two decades. Our study aimed to (1) investigate intra- and inter-annual variations in grassland CO2 fluxes, (2) assess magnitude and drivers of GPP and Reco during the regrowth periods (i.e., after mowing, grazing, or reseeding), and (3) quantify driver contributions to GPP and Reco over time, with focus on management and extreme events. CO2 fluxes showed pronounced intra- and inter-annual variations, driven by both management activities as well as meteorological conditions. Despite significant increases in temperature and decreases in soil water content (SWC) during the two decades, GPP and Reco rates during regrowth periods remained stable, and no significant trend over time was detected, suggesting adapted, climate-smart decision making of the farmer. The most important drivers of GPP in the long-term were light, management, and temperature, while Reco was mainly driven by temperature, GPP, and management. However, during extreme drought periods in the peak growing season (June, July, August), SWC increased in importance and limited GPP. In contrast, the impact of nitrogen (N) fertilization was more differentiated, either acting in parallel with SWC, suggesting low N availability during drought periods, or increasing GPP in years after sward renewal despite low SWC. Overall, our study provided novel insights into relevant drivers of grassland CO2 fluxes and their complex temporal contributions in the short- and long-term. Our results suggest that even small climate-smart management adaptations could be promising solutions for stabilizing important grassland processes, such as grassland regrowth, under current and future climate.

Publication Details

Journal
Repository for Publications and Research Data (ETH Zurich)
Published
2025-07-30
DOI
https://doi.org/10.3929/ethz-c-000782614
Primary Topic
Plant Water Relations and Carbon Dynamics
Type
article
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article

Drivers of long-term grassland CO2 fluxes and regrowth: effects of management and meteorological conditions over time

Repository for Publications and Research Data (ETH Zurich)
Plant Water Relations and Carbon Dynamics
article

Drivers of long-term grassland CO2 fluxes and regrowth: effects of management and meteorological conditions over time

article en

Abstract

Grasslands serve a unique role in the global carbon (C) cycle and cover about 30 % of the European and about 70 % of the Swiss agricultural area. Carbon dioxide (CO2) fluxes of managed grasslands are substantially influenced by land management practices and meteorological conditions, but the temporal development of these drivers is still uncertain. With the eddy covariance (EC) technique, net ecosystem CO2 exchange (NEE) can be directly measured, and then partitioned into gross primary production (GPP; amount of CO2 fixed through photosynthesis) and ecosystem respiration (Reco; amount of CO2 released via plant and soil respiration). We used 20 years (2005–2024) of EC fluxes, meteorological data, and detailed management information collected from an intensively managed grassland site (Chamau) in Switzerland, and employed machine learning approaches, i.e., eXtreme Gradient Boosting (XGBoost) models in combination with SHapley Additive exPlanations (SHAP) analyses, to identify drivers and their temporal contributions over two decades. Our study aimed to (1) investigate intra- and inter-annual variations in grassland CO2 fluxes, (2) assess magnitude and drivers of GPP and Reco during the regrowth periods (i.e., after mowing, grazing, or reseeding), and (3) quantify driver contributions to GPP and Reco over time, with focus on management and extreme events. CO2 fluxes showed pronounced intra- and inter-annual variations, driven by both management activities as well as meteorological conditions. Despite significant increases in temperature and decreases in soil water content (SWC) during the two decades, GPP and Reco rates during regrowth periods remained stable, and no significant trend over time was detected, suggesting adapted, climate-smart decision making of the farmer. The most important drivers of GPP in the long-term were light, management, and temperature, while Reco was mainly driven by temperature, GPP, and management. However, during extreme drought periods in the peak growing season (June, July, August), SWC increased in importance and limited GPP. In contrast, the impact of nitrogen (N) fertilization was more differentiated, either acting in parallel with SWC, suggesting low N availability during drought periods, or increasing GPP in years after sward renewal despite low SWC. Overall, our study provided novel insights into relevant drivers of grassland CO2 fluxes and their complex temporal contributions in the short- and long-term. Our results suggest that even small climate-smart management adaptations could be promising solutions for stabilizing important grassland processes, such as grassland regrowth, under current and future climate.

Repository for Publications and Research Data (ETH Zurich)
Openalex Percentile: Top 59%
Plant Water Relations and Carbon Dynamics
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