New approach to calculate agri-environmental indicators using greenhouse gas emissions in Switzerland as an example - Anina Gilgen; Jérôme Schneuwly; Cyrill Zosso; Lutz Merbold; Daniel Bretscher (Agricultural Systems, 2026)

Hyperspectral constraints reduce bias in ECOSTRESS evapotranspiration and drought indicators - Michael Marshall; Monica Pepe; Giulia Tagliabue; Vincent Odongo; Wim Timmermans; Francesco Vuolo; Agnieszka Soszynska; Kwasi Ofori-Karikari; Egor Prikaziuk; Volkan Yilmaz; Serkan Girgin; Cinzia Panigada; et al. (Remote Sensing of Environment, 2026)

Critical soil moisture thresholds for evapotranspiration in rainfed semi-arid maize in Kenya - Matti Räsänen; Julius Omondi; Vincent Odongo; Temesgen Abera; Juuso Tuure; Janne Heiskanen; Cheng-I Hsieh; Laura Alakukku; Lutz Merbold; Petri Pellikka; Timo Vesala (Agricultural and Forest Meteorology, 2026)

Tracking canopy conductance and transpiration of CAM-plants Agave sisalana with carbonyl sulfide fluxes - Kukka-Maaria Kohonen; Angelika Kübert; Lutz Merbold; Matti Räsänen; Nina Buchmann; Ivan Mammarella; Petri Pellikka; Timo Vesala (Agricultural and Forest Meteorology, 2026)

Opportunities and limitations of farm-level greenhouse gas accounting tools: An overview based on experience from practice - Daniel Bretscher; Nina Grassnick; Collier Isaacs; Claudia Heidecke; Bettina Koster; Lutz Merbold; Jens Leifeld (Science of The Total Environment, 2025)

Ecosystem-scale crassulacean acid metabolism (CAM) gas exchange of a sisal (Agave sisalana) plantation - Mikko Skogberg; Kukka-Maria Kohonen; Annalea Lohila; Lutz Merbold; Matti Räsänen; Ilja Vuorinne; Petri Pellikka; Timo Vesala; Angelika Kübert (Agriculture, Ecosystems & Environment, 2025)

Comparison of methodologies for estimating enteric methane emission factors from sheep in smallholder systems in Africa: A case study from Ethiopia - Endale B. Gurmu; Phyllis W. Ndung’u; Andreas Wilkes; Daniel Getahun; Michael W. Graham; Sonja M. Leitner; Svenja Marquardt; Daniel G. Mulat; Lutz Merbold; Tigist Worku; Jesse K. Gakige; Dereje Tadesse; et al. (Small Ruminant Research, 2024)

Toward compatibility with national dairy production and climate goals through locally appropriate mitigation interventions in Kenya - Michael W. Graham; Şeyda Özkan; Claudia Arndt; Ricardo González-Quintero; Daniel Korir; Lutz Merbold; Anne Mottet; Phyllis W. Ndung'u; An Notenbaert; Sonja M. Leitner (Agricultural Systems, 2024)

Mechanisms behind high N2O emissions from livestock enclosures in Kenya revealed by dual-isotope and functional gene analyses - Xiantao Fang; Stephen J. Harris; Sonja Maria Leitner; Klaus Butterbach-Bahl; Rafaela Feola Conz; Lutz Merbold; Michael Dannenmann; Antony Oyugi; Shuwei Liu; Jianwen Zou; Johan Six; Matti Barthel (Soil Biology and Biochemistry, 2024)

Greenhouse gas emissions from cattle enclosures in semi-arid sub-Saharan Africa: The case of a rangeland in South-Central Kenya - Sonja Maria Leitner; Victoria Carbonell; Rangarirayi Lucia Mhindu; Yuhao Zhu; Paul Mutuo; Klaus Butterbach-Bahl; Lutz Merbold (Agriculture, Ecosystems & Environment, 2024)

Methane emissions from animal agriculture: Micrometeorological solutions for challenging measurement situations - Johannes Laubach; Thomas K. Flesch; Christof Ammann; Mei Bai; Zhiling Gao; Lutz Merbold; David I. Campbell; Jordan P. Goodrich; Scott L. Graham; John E. Hunt; Aaron M. Wall; Louis A. Schipper (Agricultural and Forest Meteorology, 2024)

Greenhouse gas emissions from sheep excreta deposited onto tropical pastures in Kenya - Yuhao Zhu; Klaus Butterbach-Bahl; Lutz Merbold; Collins Ouma Oduor; Jesse Kagai Gakige; Paul Mwangi; Sonja Maria Leitner (Agriculture, Ecosystems & Environment, 2024)

Large inter-annual variation in carbon sink strength of a permanent grassland over 16 years: Impacts of management practices and climate - Iris Feigenwinter; Lukas Hörtnagl; Matthias J. Zeeman; Werner Eugster; Kathrin Fuchs; Lutz Merbold; Nina Buchmann (Agricultural and Forest Meteorology, 2023)

The Swiss agri-environmental data network (SAEDN): Description and critical review of the dataset - Anina Gilgen; Silvio Blaser; Jérôme Schneuwly; Frank Liebisch; Lutz Merbold (Agricultural Systems, 2023)

Enteric methane emission estimates for Kenyan cattle in a nighttime enclosure using a backward Lagrangian Stochastic dispersion technique - Kevin Wolz; Sonja Leitner; Lutz Merbold; Benjamin Wolf; Matthias Mauder (Theoretical and Applied Climatology, 2022)
This study provides methane (CH4) emission estimates for mature female African beef cattle in a semi-arid region in Southern Kenya using open-path laser spectroscopy together with a backward Lagrangian Stochastic (bLS) dispersion modeling technique. We deployed two open-path lasers to determine 10-min averages of line-integrated CH 4 measurements upwind and downwind of fenced enclosures (so-called bomas: a location where the cattle are gathered at night) during 14 nights in September/October 2019. The measurements were filtered for wind direction deviations and friction velocity before the model was applied. We compared the obtained emission factors (EFs) with the Intergovernmental Panel on Climate Change (IPCC) Tier 1 estimates for the Sub-Saharan African (SSA) countries, which were mostly derived from studies carried out in developed countries and adapted to the conditions in Africa. The resulting EF of 75.4 ± 15.99 kg year −1 and the EFs calculated from other studies carried out in Africa indicate the need for the further development of region-specific EFs depending on animal breed, livestock systems, feed quantity, and composition to improve the IPCC Tier 1 estimates.

Opportunities for an African greenhouse gas observation system - Lutz Merbold; Robert J. Scholes; Manuel Acosta; Johannes Beck; Antonio Bombelli; Bjoern Fiedler; Elisa Grieco; Joerg Helmschrot; Wim Hugo; Ville Kasurinen; Dong-Gill Kim; Arne Körtzinger; et al. (Regional Environmental Change, 2021)
Global population projections foresee the biggest increase to occur in Africa with most of the available uncultivated land to ensure food security remaining on the continent. Simultaneously, greenhouse gas emissions are expected to rise due to ongoing land use change, industrialisation, and transport amongst other reasons with Africa becoming a major emitter of greenhouse gases globally. However, distinct knowledge on greenhouse gas emissions sources and sinks as well as their variability remains largely unknown caused by its vast size and diversity and an according lack of observations across the continent. Thus, an environmental research infrastructure—as being setup in other regions—is more needed than ever. Here, we present the results of a design study that developed a blueprint for establishing such an environmental research infrastructure in Africa. The blueprint comprises an inventory of already existing observations, the spatial disaggregation of locations that will enable to reduce the uncertainty in climate forcing’s in Africa and globally as well as an overall estimated cost for such an endeavour of about 550 M€ over the next 30 years. We further highlight the importance of the development of an e-infrastructure, the necessity for capacity development and the inclusion of all stakeholders to ensure African ownership.

The effects of climate on decomposition of cattle, sheep and goat manure in Kenyan tropical pastures - Yuhao Zhu; Lutz Merbold; Sonja Leitner; David E. Pelster; Sheila Abwanda Okoma; Felix Ngetich; Alice Anyango Onyango; Petri Pellikka; Klaus Butterbach-Bahl (Plant and Soil, 2020)
Aims Decomposition of manure deposited onto pasture from grazing animals represents an important process for carbon (C) and nitrogen (N) cycles in grassland systems. However, studies investigating manure decomposition are scarce; especially in sub-Saharan Africa (SSA). Methods In this study, we measured decomposition of three types of animal manure (cattle, sheep, goat) over >1 year using litter bags at four climatically different sites across Kenya. Results Manure dry matter, total C, total N and ammonium concentrations decreased exponentially, with the most rapid decrease occurring during the first few weeks following application, followed by slower changes during the following 2–3 months. Rates of N mineralization were lower than those for C mineralization, resulting in decreasing C/N ratios over time. Generally, cattle manure decomposed faster than sheep or goat manure despite having a higher initial C/N ratio and lower N concentration, with decomposition rates for dry matter ranging from 0.200 to 0.989 k year −1 . Cellulose decomposed first, while lignin concentrations increased among all manure types and at all sites. Conclusions We found that total manure decomposition rates were positively correlated with cumulative precipitation and aridity index, but negatively correlated with mean temperature. Our results show much slower decomposition rates of manures in semi-arid tropical environments of East Africa as compared to the few previous studies in temperate climates.

Covariations between plant functional traits emerge from constraining parameterization of a terrestrial biosphere model - Marc Peaucelle; Cédric Bacour; Philippe Ciais; Nicolas Vuichard; Sylvain Kuppel; Josep Peñuelas; Luca Belelli Marchesini; Peter D. Blanken; Nina Buchmann; Jiquan Chen; Nicolas Delpierre; Ankur R. Desai; et al. (Global Ecology and Biogeography, 2019)
Aim The mechanisms of plant trait adaptation and acclimation are still poorly understood and, consequently, lack a consistent representation in terrestrial biosphere models (TBMs). Despite the increasing availability of geo‐referenced trait observations, current databases are still insufficient to cover all vegetation types and environmental conditions. In parallel, the growing number of continuous eddy‐covariance observations of energy and CO 2 fluxes has enabled modellers to optimize TBMs with these data. Past attempts to optimize TBM parameters mostly focused on model performance, overlooking the ecological properties of ecosystems. The aim of this study was to assess the ecological consistency of optimized trait‐related parameters while improving the model performances for gross primary productivity (GPP) at sites. Location Worldwide. Time period 1992–2012. Major taxa studied Trees and C 3 grasses. Methods We optimized parameters of the ORCHIDEE model against 371 site‐years of GPP estimates from the FLUXNET network, and we looked at global covariation among parameters and with climate. Results The optimized parameter values were shown to be consistent with leaf‐scale traits, in particular, with well‐known trade‐offs observed at the leaf level, echoing the leaf economic spectrum theory. Results showed a marked sensitivity of trait‐related parameters to local bioclimatic variables and reproduced the observed relationships between traits and climate. Main conclusions Our approach validates some biological processes implemented in the model and enables us to study ecological properties of vegetation at the canopy level, in addition to some traits that are difficult to observe experimentally. This study stresses the need for: (a) implementing explicit trade‐offs and acclimation processes in TBMs; (b) improving the representation of processes to avoid model‐specific parameterization; and (c) performing systematic measurements of traits at FLUXNET sites in order to gather information on plant ecophysiology and plant diversity, together with micro‐meteorological conditions.

Greenhouse gas fluxes over managed grasslands in Central Europe - Lukas Hörtnagl; Matti Barthel; Nina Buchmann; Werner Eugster; Klaus Butterbach‐Bahl; Eugenio Díaz‐Pinés; Matthias Zeeman; Katja Klumpp; Ralf Kiese; Michael Bahn; Albin Hammerle; Haiyan Lu; et al. (Global Change Biology, 2018)
Central European grasslands are characterized by a wide range of different management practices in close geographical proximity. Site‐specific management strategies strongly affect the biosphere–atmosphere exchange of the three greenhouse gases ( GHG ) carbon dioxide ( CO 2 ), nitrous oxide (N 2 O), and methane ( CH 4 ). The evaluation of environmental impacts at site level is challenging, because most in situ measurements focus on the quantification of CO 2 exchange, while long‐term N 2 O and CH 4 flux measurements at ecosystem scale remain scarce. Here, we synthesized ecosystem CO 2 , N 2 O, and CH 4 fluxes from 14 managed grassland sites, quantified by eddy covariance or chamber techniques. We found that grasslands were on average a CO 2 sink (−1,783 to −91 g CO 2 m −2 year −1 ), but a N 2 O source (18–638 g CO 2 ‐eq. m −2 year −1 ), and either a CH 4 sink or source (−9 to 488 g CO 2 ‐eq. m −2 year −1 ). The net GHG balance ( NGB ) of nine sites where measurements of all three GHG s were available was found between −2,761 and −58 g CO 2 ‐eq. m −2 year −1 , with N 2 O and CH 4 emissions offsetting concurrent CO 2 uptake by on average 21 ± 6% across sites. The only positive NGB was found for one site during a restoration year with ploughing. The predictive power of soil parameters for N 2 O and CH 4 fluxes was generally low and varied considerably within years. However, after site‐specific data normalization, we identified environmental conditions that indicated enhanced GHG source/sink activity (“sweet spots”) and gave a good prediction of normalized overall fluxes across sites. The application of animal slurry to grasslands increased N 2 O and CH 4 emissions. The N 2 O‐N emission factor across sites was 1.8 ± 0.5%, but varied considerably at site level among the years (0.1%–8.6%). Although grassland management led to increased N 2 O and CH 4 emissions, the CO 2 sink strength was generally the most dominant component of the annual GHG budget.

Assessing uncertainties in crop and pasture ensemble model simulations of productivity and N 2 O emissions - Fiona Ehrhardt; Jean‐François Soussana; Gianni Bellocchi; Peter Grace; Russel McAuliffe; Sylvie Recous; Renáta Sándor; Pete Smith; Val Snow; Massimiliano de Antoni Migliorati; Bruno Basso; Arti Bhatia; et al. (Global Change Biology, 2018)
Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi‐species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi‐model ensembles to predict productivity and nitrous oxide (N 2 O) emissions for wheat, maize, rice and temperate grasslands. Using a multi‐stage modelling protocol, from blind simulations (stage 1) to partial (stages 2–4) and full calibration (stage 5), 24 process‐based biogeochemical models were assessed individually or as an ensemble against long‐term experimental data from four temperate grassland and five arable crop rotation sites spanning four continents. Comparisons were performed by reference to the experimental uncertainties of observed yields and N 2 O emissions. Results showed that across sites and crop/grassland types, 23%–40% of the uncalibrated individual models were within two standard deviations ( SD ) of observed yields, while 42 (rice) to 96% (grasslands) of the models were within 1 SD of observed N 2 O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N 2 O emissions within experimental uncertainties for 44% and 33% of the crop and grassland growth cycles, respectively. Partial model calibration (stages 2–4) markedly reduced prediction errors of the full model ensemble E‐median for crop grain yields (from 36% at stage 1 down to 4% on average) and grassland productivity (from 44% to 27%) and to a lesser and more variable extent for N 2 O emissions. Yield‐scaled N 2 O emissions (N 2 O emissions divided by crop yields) were ranked accurately by three‐model ensembles across crop species and field sites. The potential of using process‐based model ensembles to predict jointly productivity and N 2 O emissions at field scale is discussed.

Plants, microorganisms, and soil temperatures contribute to a decrease in methane fluxes on a drained Arctic floodplain - Min Jung Kwon; Felix Beulig; Iulia Ilie; Marcus Wildner; Kirsten Küsel; Lutz Merbold; Miguel D. Mahecha; Nikita Zimov; Sergey A. Zimov; Martin Heimann; Edward A. G. Schuur; Joel E. Kostka; et al. (Global Change Biology, 2017)
As surface temperatures are expected to rise in the future, ice‐rich permafrost may thaw, altering soil topography and hydrology and creating a mosaic of wet and dry soil surfaces in the Arctic. Arctic wetlands are large sources of CH 4 , and investigating effects of soil hydrology on CH 4 fluxes is of great importance for predicting ecosystem feedback in response to climate change. In this study, we investigate how a decade‐long drying manipulation on an Arctic floodplain influences CH 4 ‐associated microorganisms, soil thermal regimes, and plant communities. Moreover, we examine how these drainage‐induced changes may then modify CH 4 fluxes in the growing and nongrowing seasons. This study shows that drainage substantially lowered the abundance of methanogens along with methanotrophic bacteria, which may have reduced CH 4 cycling. Soil temperatures of the drained areas were lower in deep, anoxic soil layers (below 30 cm), but higher in oxic topsoil layers (0–15 cm) compared to the control wet areas. This pattern of soil temperatures may have reduced the rates of methanogenesis while elevating those of CH 4 oxidation, thereby decreasing net CH 4 fluxes. The abundance of Eriophorum angustifolium , an aerenchymatous plant species, diminished significantly in the drained areas. Due to this decrease, a higher fraction of CH 4 was alternatively emitted to the atmosphere by diffusion, possibly increasing the potential for CH 4 oxidation and leading to a decrease in net CH 4 fluxes compared to a control site. Drainage lowered CH 4 fluxes by a factor of 20 during the growing season, with postdrainage changes in microbial communities, soil temperatures, and plant communities also contributing to this reduction. In contrast, we observed CH 4 emissions increased by 10% in the drained areas during the nongrowing season, although this difference was insignificant given the small magnitudes of fluxes. This study showed that long‐term drainage considerably reduced CH 4 fluxes through modified ecosystem properties.

N 2 O emissions and source processes in snow-covered soils in the Swiss Alps - Joachim Mohn; Christine Steinlin; Lutz Merbold; Lukas Emmenegger; Frank Hagedorn (Isotopes in Environmental and Health Studies, 2013)