Including land management in a European carbon model with lateral transfer to the oceans DOI Creative Commons

Arthur Nicolaus Fendrich,

Philippe Ciais, Panos Panagos

и другие.

Environmental Research, Год журнала: 2023, Номер 245, С. 118014 - 118014

Опубликована: Дек. 25, 2023

The use of cover crops (CCs) is a promising cropland management practice with multiple benefits, notably in reducing soil erosion and increasing organic carbon (SOC) storage. However, the current ability to represent these factors land surface models remains limited small scales or simplified lumped approaches due lack sediment-carbon displacement scheme. This precludes thorough understanding consequences introducing CC into agricultural systems. In this work, problem was addressed two steps spatially distributed CE-DYNAM model. First, historical effect erosion, transport, deposition on budget at continental scale Europe characterized since early industrial era, using reconstructed climate forcings. Then, impact distinct policy-oriented scenarios for introduction CCs were evaluated, covering European cropping systems where rates nitrate susceptibility are critical. evaluation focused increase SOC storage export particulate (POC) oceans, compiling continental-scale budget. results indicated that exported 1.95 TgC/year POC oceans last decade, can contribute amount while Compared simulation without CCs, additional rate induced by peaked after 10 years their adoption, followed decrease, cumulative reduction stabilized around 13 years. findings indicate impacts reduced persistent regardless spatial allocation adopted scenarios. Together, highlight importance taking temporal aspect adoption account alone not sufficient meet targets 4‰ initiative. Despite some known model limitations, which include feedback net primary productivity representation fluxes an emulator, work constitutes first approach successfully couple routing scheme eroded emulator reasonably high resolution scale. SHORT ABSTRACT: A coupling cycle developed. it used simulate both carbon, show simultaneously reduce oceans. seemed distribution crops.

Язык: Английский

Soil organic carbon models need independent time-series validation for reliable prediction DOI Creative Commons
Julia Le Noë, Stefano Manzoni, Rose Abramoff

и другие.

Communications Earth & Environment, Год журнала: 2023, Номер 4(1)

Опубликована: Май 8, 2023

Abstract Numerical models are crucial to understand and/or predict past and future soil organic carbon dynamics. For those aiming at prediction, validation is a critical step gain confidence in projections. With comprehensive review of ~250 models, we assess how validated depending on their objectives features, discuss predictive can be improved. We find lack independent using observed time series. Conducting such validations should priority improve the model reliability. Approximately 60% analysed not designed for predictions, but rather conceptual understanding processes. These provide important insights by identifying key processes alternative formalisms that relevant models. argue combining based series improved information flow between will increase reliability predictions.

Язык: Английский

Процитировано

59
Long-term soil organic carbon and crop yield feedbacks differ between 16 soil-crop models in sub-Saharan Africa DOI Creative Commons
Antoine Couëdel, Gatien N. Falconnier, Myriam Adam

и другие.

European Journal of Agronomy, Год журнала: 2024, Номер 155, С. 127109 - 127109

Опубликована: Фев. 8, 2024

Язык: Английский

Процитировано

11
Learning vs. understanding: When does artificial intelligence outperform process-based modeling in soil organic carbon prediction? DOI Creative Commons
Luca Giuliano Bernardini, Christoph Rosinger, Gernot Bodner

и другие.

New Biotechnology, Год журнала: 2024, Номер 81, С. 20 - 31

Опубликована: Март 8, 2024

In recent years, machine learning (ML) algorithms have gained substantial recognition for ecological modeling across various temporal and spatial scales. However, little evaluation has been conducted the prediction of soil organic carbon (SOC) on small data sets commonly inherent to long-term research. this context, performance ML SOC never tested against traditional process-based approaches. Here, we compare algorithms, calibrated uncalibrated models as well multiple ensembles their in predicting using from five experimental sites (comprising 256 independent points) Austria. Using all available data, ML-based approaches Random forest support vector machines with a polynomial kernel were superior models. performed similar or worse when number training samples was reduced leave-one-site-out cross validation applied. This emphasizes that is strongly dependent data-size related quality information following well-known curse dimensionality phenomenon, while accuracy significantly relies proper calibration combination different Our study thus suggests superiority at scales where larger datasets are available, tools targeting exploration underlying biophysical biochemical mechanisms dynamics soils. Therefore, recommend applying combine advantages both

Язык: Английский

Процитировано

11
Factors affecting the net ecosystem productivity of agroecosystems on mineral soils: a meta-analysis DOI Creative Commons
Isobel L. Lloyd, Ross Morrison, Richard Grayson

и другие.

Agroecology and Sustainable Food Systems, Год журнала: 2025, Номер unknown, С. 1 - 32

Опубликована: Фев. 3, 2025

To optimize agricultural land management for soil carbon sequestration, it is necessary to identify whether agroecosystems are accumulating or gaining carbon. This can be done by determining an agroecosystem's net ecosystem productivity (NEP). study collated data from 40 papers, containing 242 annual measurements of NEP, assess the impact climate, type and on NEP croplands managed grasslands. Croplands lost significantly more (110 g Cm−2) than grasslands (29.9 there was little statistical influence soil, practice NEP. For sequester carbon, should a shift in focus toward implementing practices that increase retention within agroecosystems.

Язык: Английский

Процитировано

1
A calibration protocol for soil-crop models DOI Creative Commons
Daniel Wallach, Samuel Buis, Diana-Maria Seserman

и другие.

Environmental Modelling & Software, Год журнала: 2024, Номер 180, С. 106147 - 106147

Опубликована: Июль 17, 2024

Process-based soil-crop models are widely used in agronomic research. They major tools for evaluating climate change impact on crop production. Multi-model simulation studies show a wide diversity of results among models, implying that very uncertain. A path to improving is propose improved calibration practices applicable. This study proposes an innovative generic protocol. The two innovations concern the treatment multiple output variables and choice parameters estimate, both which based standard statistical procedure adapted particularities models. protocol performed well challenging artificial-data test. formulated so as be applicable range data sets. If adopted, it could substantially reduce model error inter-model variability, thus increase confidence simulations.

Язык: Английский

Процитировано

6
Ecosystem-scale modelling of soil carbon dynamics: Time for a radical shift of perspective? DOI Open Access
Philippe C. Baveye

Soil Biology and Biochemistry, Год журнала: 2023, Номер 184, С. 109112 - 109112

Опубликована: Июль 4, 2023

Язык: Английский

Процитировано

11
Soil carbon offset markets are not a just climate solution DOI Creative Commons

Mustafa Saifuddin,

Rose Abramoff, Erika J. Foster

и другие.

Frontiers in Ecology and the Environment, Год журнала: 2024, Номер 22(7)

Опубликована: Июль 1, 2024

There is growing interest in enhancing soil carbon sequestration (SCS) as a climate mitigation strategy, including neutralizing atmospheric emissions from fossil‐fuel combustion through the development of offset markets. Several studies have focused on refining estimates magnitude potential SCS or developing methods for quantification We call scientists and policy makers to resist assimilating soils into markets due not only fundamental flaws logic these reach neutrality but also environmental justice concerns. Here, we first highlight how rely an inappropriate substitution inert fossil with dynamic stocks carbon. then note failure account intersecting anthropogenic perturbations cycle, debt ongoing agricultural emissions. Next, invite consider functions beyond productivity profitability. Finally, describe support historical opposition by advocates. encourage their research communications can promote diverse just climate‐change mitigation.

Язык: Английский

Процитировано

4
European croplands under climate change: Carbon input changes required to increase projected soil organic carbon stocks DOI Creative Commons
Elisa Bruni, Emanuele Lugato,

Claire Chenu

и другие.

The Science of The Total Environment, Год журнала: 2024, Номер 954, С. 176525 - 176525

Опубликована: Сен. 27, 2024

Язык: Английский

Процитировано

3
Challenges and strategies in estimating soil organic carbon for multi-cropping systems: a review DOI Open Access

Zhiyuan Bai,

Datong Zhang, Zechen Wang

и другие.

Carbon Footprints, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 25, 2024

Multi-cropping systems play a crucial role in global agricultural production. Accurately estimating the soil carbon sequestration capacity of multi-cropping is significant importance for enhancing productivity, mitigating greenhouse gas emissions, and reducing footprint. However, cycling more complex compared with single-cropping systems, existing assessment methods cannot accurately estimate high operability. Here, we reviewed accuracy efficiency three primary methods, including statistical models, process-based Intergovernmental Panel on Climate Change (IPCC) steady-state method. Our study concludes that it difficult to simulate dynamic evolution organic (SOC) using while well simulation through models demands large amount data. Additionally, IPCC Tier 2 method be directly applied SOC due mismatches parameters time steps. We suggest modifying structures by revising inventory unit redetermining parameter values, which should efficiently address its bottleneck systems. Moreover, long-term experimental observations multi-model ensemble simulations are beneficial determining values data deficiencies 2. This aims explore pathways improving estimation and, thus, footprint calculation worldwide.

Язык: Английский

Процитировано

3
Cultivation of forage maize in boreal conditions – Assessment of trade-offs between increased productivity and environmental impact DOI Creative Commons
Anniina Lehtilä, Arezoo Taghizadeh‐Toosi, Marja Roitto

и другие.

Animal Feed Science and Technology, Год журнала: 2024, Номер 309, С. 115878 - 115878

Опубликована: Янв. 13, 2024

The cultivation of whole crop forage maize (Zea mays L.) for cattle feed has a potential increased yield while reducing nitrogen (N) fertilization compared to perennial grass-based systems. However, the possible environmental trade-offs remain unknown in boreal region due short growing season which limits practices. aim this study was compare impact with more widely cultivated crops Finland that include silage grass mixtures and spring cereal harvested as silage. use plastic mulch film included assessment well. A life cycle (LCA) conducted including categories global warming potential; marine freshwater eutrophication; terrestrial acidification; freshwater, ecotoxicity; land use; fossil resource depletion. Additionally, soil organic carbon (SOC) stock changes under long-term studied were simulated C-TOOL Yasso20 models methodological comparisons. only clear differences between lower (-26–48%) maize, eutrophication (+59–67%) acidification (+10–57%) higher grasses other forages. risk decreased SOC continuous observed. Forage could be used supplement without major associated risks. Future research shall on effect choices dairy milk production decreasing current high uncertainty nitrous oxide (N2O) emission factors modelling choices.

Язык: Английский

Процитировано

1