Options to model the effects of tillage on N2O emissions at the global scale

Lutz, Femke; Stoorvogel, J.J.; Müller, Christoph

doi:10.1016/j.ecolmodel.2018.11.015

Cited by 12 publications

(11 citation statements)

References 94 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Despite the existence of various DSTs for agriculture, we find that very few tools evaluate agronomic measures quantitatively using impact assessment on targeted environmental as well as agronomic outcomes. This limitation is likely to originate from the fact that most of them use process-based models to evaluate the impacts of measures, being intrinsically difficult to parameterize on the field and farm scale (see e.g., Lutz, Stoorvogel, and Müller (2019b) for an overview of models assessing losses of nitrous oxide). In addition, model validation is challenging, because independent data on management impacts are limited, and model results often deviate from measurements due to the complexity of interactions between measures and soil process (see e.g., Lutz et al (2019a)).…”

Section: Introductionmentioning

confidence: 99%

A decision support framework assessing management impacts on crop yield, soil carbon changes and nitrogen losses to the environment

Young

Ros

Vries

2020

European J Soil Science

View full text Add to dashboard Cite

Agricultural management practices have multiple impacts on farming systems, including crop yield, soil fertility parameters such as soil organic carbon (SOC), and environmental quality. Agricultural decision support tools (DSTs) are key in sustainable farm strategies to optimize yield and minimize environmental losses because both the current agroecosystem properties as well as the effectiveness of management practices are highly variable in time and space.Here, we introduce a highly data-driven framework focusing on the evaluation of agronomic measures to reach agronomic and environmental targets. We demonstrate the potential of this approach by a proof of principle for 81 selected farm types across Europe, focusing on measures with respect to crop rotation, fertilization and soil tillage. Synthesizing data from long-term experiments and meta-analytical models, we estimated the impact of these measures on crop yield, SOC and N surpluses, while accounting for site- Highlights• We find a lack of empirical-based DSTs holistically assessing agronomic practices and indicators.• Meta-analytical models were used to assess impacts of best fertilizer, tillage and crop measures.

show abstract

Section: Introductionmentioning

confidence: 99%

A decision support framework assessing management impacts on crop yield, soil carbon changes and nitrogen losses to the environment

Young

Ros

Vries

2020

European J Soil Science

View full text Add to dashboard Cite

show abstract

“…The implementation of such effects is desirable but needs to be assessed with respect to the process understanding, the availability of input data at the global scale, and the availability of modeling approaches (Lutz et al, 2019a). Global-scale modeling approaches, in comparison to local or regional studies, allow for the possibility to identify regional patterns related to SOC sequestration responses with the potential to foster experimental studies in areas so far not investigated, but relevant for global assessments (Luo et al, 2016;Nishina et al, 2014).…”

Section: Potential For Soc Sequestration On Cropland and Recommendations For Future Analysismentioning

confidence: 99%

SOC sequestration potentials for agricultural management practices under climate change

Herzfeld¹,

Heinke²,

Rolinski³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Abstract. Sequestration of soil organic carbon (SOC) on cropland has been proposed as a climate change mitigation strategy to reduce global greenhouse gas (GHG) concentrations in the atmosphere, which is in particular needed to achieve the targets proposed in the Paris Agreement to limit the increase in atmospheric temperature to well below 2 °C. We here analyze the historical evolution and future development of cropland SOC using the global process-based biophysical model LPJmL, which was recently extended by a detailed representation of tillage practices and residues management (version 5.0–tillage2). We find that model results for historical global estimates for SOC stocks are at the upper end of available literature, with ~2650 Pg C of SOC stored globally in the year 2018, of which ~170 Pg C are stored in cropland soils. In future projections, assuming no further changes in current cropland patterns and under four different management assumptions with two different climate forcings, RCP2.6, and RCP8.5, results suggest that agricultural SOC stocks decline in all scenarios, as the decomposition of SOC outweighs the increase of carbon inputs into the soil from altered management practices. Different climate-change scenarios, as well as assumptions on tillage management, play a minor role in explaining differences in SOC stocks. The choice of tillage practice explains between 0.2 % and 1.3 % of total cropland SOC stock change in the year 2100. Future dynamics in cropland SOC are most strongly controlled by residue management, whether residues are left on the field or harvested. We find that on current cropland, global cropland SOC stocks decline until the end of the century by only 1.0 % to 1.4 % if residue-retention management systems are generally applied and by 26.7 % to 27.3 % in case of residues harvest. For different climatic regions, increases in cropland SOC can only be found for tropical dry, warm temperate moist, and warm temperate dry regions in management systems that retain residues.

show abstract

“…However, studies reported mixed results for the impacts of adapting no-tillage on N 2 O emissions from 3906 F. Lutz et al: Soil moisture representation for simulating tillage effects on N 2 O emissions in LPJmL5.0-tillage croplands (Deng et al, 2016;Venterea et al, 2011). For instance, no-tillage was found to increase N 2 O emissions (Mei et al, 2018;Van Kessel et al, 2013), decrease N 2 O emissions (Deng et al, 2016;Plaza-Bonilla et al, 2018;Yoo et al, 2016) or have no significant effects (Alvarez et al, 2012;Boeckx et al, 2011) in comparison to conventional tillage systems.…”

Section: Introductionmentioning

confidence: 99%

“…These processes are driven by microbial activity and strongly respond to soil properties such as moisture, temperature, oxygen, mineral N and organic carbon (Mosquera et al, 2005;Snyder et al, 2009;Van Kessel et al, 2013). These soil properties are affected by tillage (Lutz et al, 2019a;Lutz et al, 2019c) and other management practices (e.g., fertilizer application and residue treatment) (Van Kessel et al, 2013). Due to the complexity of the system, the simulation of tillage effects on N 2 O emissions is challenging and subject to great uncertainties.…”

Section: Introductionmentioning

confidence: 99%

The importance of management information and soil moisture representation for simulating tillage effects on N<sub>2</sub>O emissions in LPJmL5.0-tillage

et al. 2020

Self Cite

View full text Add to dashboard Cite

Abstract. No-tillage is often suggested as a strategy to reduce greenhouse gas emissions. Modeling tillage effects on nitrous oxide (N2O) emissions is challenging and subject to great uncertainties as the processes producing the emissions are complex and strongly nonlinear. Previous findings have shown deviations between the LPJmL5.0-tillage model (LPJmL: Lund–Potsdam–Jena managed Land) and results from meta-analysis on global estimates of tillage effects on N2O emissions. Here we tested LPJmL5.0-tillage at four different experimental sites across Europe and the USA to verify whether deviations in N2O emissions under different tillage regimes result from a lack of detailed information on agricultural management, the representation of soil water dynamics or both. Model results were compared to observational data and outputs from field-scale DayCent model simulations. DayCent has been successfully applied for the simulation of N2O emissions and provides a richer database for comparison than noncontinuous measurements at experimental sites. We found that adding information on agricultural management improved the simulation of tillage effects on N2O emissions in LPJmL. We also found that LPJmL overestimated N2O emissions and the effects of no-tillage on N2O emissions, whereas DayCent tended to underestimate the emissions of no-tillage treatments. LPJmL showed a general bias to overestimate soil moisture content. Modifications of hydraulic properties in LPJmL in order to match properties assumed in DayCent, as well as of the parameters related to residue cover, improved the overall simulation of soil water and N2O emissions simulated under tillage and no-tillage separately. However, the effects of no-tillage (shifting from tillage to no-tillage) did not improve. Advancing the current state of information on agricultural management and improvements in soil moisture highlights the potential to improve LPJmL5.0-tillage and global estimates of tillage effects on N2O emissions.

show abstract

Options to model the effects of tillage on N2O emissions at the global scale

Cited by 12 publications

References 94 publications

A decision support framework assessing management impacts on crop yield, soil carbon changes and nitrogen losses to the environment

A decision support framework assessing management impacts on crop yield, soil carbon changes and nitrogen losses to the environment

SOC sequestration potentials for agricultural management practices under climate change

The importance of management information and soil moisture representation for simulating tillage effects on N<sub>2</sub>O emissions in LPJmL5.0-tillage

Contact Info

Product

Resources

About

Options to model the effects of tillage on N2O emissions at the global scale

Cited by 12 publications

References 94 publications

A decision support framework assessing management impacts on crop yield, soil carbon changes and nitrogen losses to the environment

A decision support framework assessing management impacts on crop yield, soil carbon changes and nitrogen losses to the environment

SOC sequestration potentials for agricultural management practices under climate change

The importance of management information and soil moisture representation for simulating tillage effects on N&lt;sub&gt;2&lt;/sub&gt;O emissions in LPJmL5.0-tillage

Contact Info

Product

Resources

About

The importance of management information and soil moisture representation for simulating tillage effects on N<sub>2</sub>O emissions in LPJmL5.0-tillage