Showing papers by "Wageningen University and Research Centre published in 2020"
University of Exeter1, École Normale Supérieure2, Norwich Research Park3, University of Groningen4, Wageningen University and Research Centre5, Ludwig Maximilian University of Munich6, Max Planck Society7, Commonwealth Scientific and Industrial Research Organisation8, Université Paris-Saclay9, Stanford University10, National Oceanic and Atmospheric Administration11, National Institute for Space Research12, University of Southampton13, Bermuda Institute of Ocean Sciences14, PSL Research University15, Japan Agency for Marine-Earth Science and Technology16, National Institute for Environmental Studies17, University of Maryland, College Park18, University of Leeds19, International Institute of Minnesota20, Flanders Marine Institute21, ETH Zurich22, University of East Anglia23, German Aerospace Center24, Woods Hole Research Center25, University of Illinois at Urbana–Champaign26, University of Toulouse27, Japan Meteorological Agency28, Plymouth Marine Laboratory29, University of Paris30, Hobart Corporation31, Oeschger Centre for Climate Change Research32, Tsinghua University33, National Center for Atmospheric Research34, Appalachian State University35, University of Colorado Boulder36, University of Washington37, Atlantic Oceanographic and Meteorological Laboratory38, Princeton University39, Met Office40, Leibniz Institute of Marine Sciences41, Auburn University42, University of Tasmania43, VU University Amsterdam44, Oak Ridge National Laboratory45, Sun Yat-sen University46, Nanjing University47
TL;DR: In this paper, the authors describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties, including emissions from land use and land-use change data and bookkeeping models.
Abstract: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2010–2019), EFOS was 9.6 ± 0.5 GtC yr−1 excluding the cement carbonation sink (9.4 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 1.6 ± 0.7 GtC yr−1. For the same decade, GATM was 5.1 ± 0.02 GtC yr−1 (2.4 ± 0.01 ppm yr−1), SOCEAN 2.5 ± 0.6 GtC yr−1, and SLAND 3.4 ± 0.9 GtC yr−1, with a budget imbalance BIM of −0.1 GtC yr−1 indicating a near balance between estimated sources and sinks over the last decade. For the year 2019 alone, the growth in EFOS was only about 0.1 % with fossil emissions increasing to 9.9 ± 0.5 GtC yr−1 excluding the cement carbonation sink (9.7 ± 0.5 GtC yr−1 when cement carbonation sink is included), and ELUC was 1.8 ± 0.7 GtC yr−1, for total anthropogenic CO2 emissions of 11.5 ± 0.9 GtC yr−1 (42.2 ± 3.3 GtCO2). Also for 2019, GATM was 5.4 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEAN was 2.6 ± 0.6 GtC yr−1, and SLAND was 3.1 ± 1.2 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 409.85 ± 0.1 ppm averaged over 2019. Preliminary data for 2020, accounting for the COVID-19-induced changes in emissions, suggest a decrease in EFOS relative to 2019 of about −7 % (median estimate) based on individual estimates from four studies of −6 %, −7 %, −7 % (−3 % to −11 %), and −13 %. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2019, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. Comparison of estimates from diverse approaches and observations shows (1) no consensus in the mean and trend in land-use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent discrepancy between the different methods for the ocean sink outside the tropics, particularly in the Southern Ocean. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Friedlingstein et al., 2019; Le Quere et al., 2018b, a, 2016, 2015b, a, 2014, 2013). The data presented in this work are available at https://doi.org/10.18160/gcp-2020 (Friedlingstein et al., 2020).
1,764 citations
National Institutes of Health1, Delft University of Technology2, Humboldt University of Berlin3, DuPont4, Laval University5, University of Alicante6, University of Copenhagen7, Vilnius University8, University of Georgia9, University of St Andrews10, University of Toronto11, Bangor University12, University of Freiburg13, Wageningen University and Research Centre14, North Carolina State University15
TL;DR: An updated evolutionary classification of CRISPR–Cas systems and cas genes is provided, with an emphasis on the major developments that have occurred since the publication of the latest classification, in 2015, which includes 2 classes, 6 types and 33 subtypes.
Abstract: The number and diversity of known CRISPR-Cas systems have substantially increased in recent years. Here, we provide an updated evolutionary classification of CRISPR-Cas systems and cas genes, with an emphasis on the major developments that have occurred since the publication of the latest classification, in 2015. The new classification includes 2 classes, 6 types and 33 subtypes, compared with 5 types and 16 subtypes in 2015. A key development is the ongoing discovery of multiple, novel class 2 CRISPR-Cas systems, which now include 3 types and 17 subtypes. A second major novelty is the discovery of numerous derived CRISPR-Cas variants, often associated with mobile genetic elements that lack the nucleases required for interference. Some of these variants are involved in RNA-guided transposition, whereas others are predicted to perform functions distinct from adaptive immunity that remain to be characterized experimentally. The third highlight is the discovery of numerous families of ancillary CRISPR-linked genes, often implicated in signal transduction. Together, these findings substantially clarify the functional diversity and evolutionary history of CRISPR-Cas.
1,153 citations
TL;DR: The extent of the trait data compiled in TRY is evaluated and emerging patterns of data coverage and representativeness are analyzed to conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements.
Abstract: Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
882 citations
Graz University of Technology1, Université Paris-Saclay2, University of Waterloo3, Guizhou University4, European Food Information Council5, Institut national de la recherche agronomique6, Agricultural University of Athens7, University of Minnesota8, University of Minho9, University of Vienna10, Agriculture and Agri-Food Canada11, Rothamsted Research12, Pacific Northwest National Laboratory13, Austrian Institute of Technology14, CABI15, Tallinn University of Technology16, Wageningen University and Research Centre17, Pondicherry University18, State University of Campinas19, University of Sydney20, Teagasc21
TL;DR: A definition of microbiome is proposed based on the compact, clear, and comprehensive description of the term provided by Whipps et al. in 1988, amended with a set of novel recommendations considering the latest technological developments and research findings.
Abstract: The field of microbiome research has evolved rapidly over the past few decades and has become a topic of great scientific and public interest. As a result of this rapid growth in interest covering different fields, we are lacking a clear commonly agreed definition of the term “microbiome.” Moreover, a consensus on best practices in microbiome research is missing. Recently, a panel of international experts discussed the current gaps in the frame of the European-funded MicrobiomeSupport project. The meeting brought together about 40 leaders from diverse microbiome areas, while more than a hundred experts from all over the world took part in an online survey accompanying the workshop. This article excerpts the outcomes of the workshop and the corresponding online survey embedded in a short historical introduction and future outlook. We propose a definition of microbiome based on the compact, clear, and comprehensive description of the term provided by Whipps et al. in 1988, amended with a set of novel recommendations considering the latest technological developments and research findings. We clearly separate the terms microbiome and microbiota and provide a comprehensive discussion considering the composition of microbiota, the heterogeneity and dynamics of microbiomes in time and space, the stability and resilience of microbial networks, the definition of core microbiomes, and functionally relevant keystone species as well as co-evolutionary principles of microbe-host and inter-species interactions within the microbiome. These broad definitions together with the suggested unifying concepts will help to improve standardization of microbiome studies in the future, and could be the starting point for an integrated assessment of data resulting in a more rapid transfer of knowledge from basic science into practice. Furthermore, microbiome standards are important for solving new challenges associated with anthropogenic-driven changes in the field of planetary health, for which the understanding of microbiomes might play a key role.
733 citations
Utrecht University1, University of Maryland, College Park2, Higher University of San Andrés3, Wageningen University and Research Centre4, University of St Andrews5, Royal Holloway, University of London6, Academy of Sciences of the Czech Republic7, Chinese Academy of Sciences8, University of Concepción9, University of Dayton10, Planetary Science Institute11, University of British Columbia12, Indian Institute of Science13, University of Maine14, International Centre for Integrated Mountain Development15, University of California, Los Angeles16, Johns Hopkins University17, University of Utah18, University of Zurich19, International Institute for Applied Systems Analysis20, Beijing Normal University21
TL;DR: The worldwide distribution and water supply of water towers (snowy or glacierized mountain ranges) is indexed, showing that the most important water towers are also the most vulnerable to socio-economic and climate-change stresses, with huge potential negative impacts on populations downstream.
Abstract: Mountains are the water towers of the world, supplying a substantial part of both natural and anthropogenic water demands1,2. They are highly sensitive and prone to climate change3,4, yet their importance and vulnerability have not been quantified at the global scale. Here we present a global water tower index (WTI), which ranks all water towers in terms of their water-supplying role and the downstream dependence of ecosystems and society. For each water tower, we assess its vulnerability related to water stress, governance, hydropolitical tension and future climatic and socio-economic changes. We conclude that the most important (highest WTI) water towers are also among the most vulnerable, and that climatic and socio-economic changes will affect them profoundly. This could negatively impact 1.9 billion people living in (0.3 billion) or directly downstream of (1.6 billion) mountainous areas. Immediate action is required to safeguard the future of the world’s most important and vulnerable water towers.
730 citations
TL;DR: The FLUXNET2015 dataset provides ecosystem-scale data on CO 2 , water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe, and is detailed in this paper.
Abstract: The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.
681 citations
University of Düsseldorf1, University of Duisburg-Essen2, Harvard University3, University of Warsaw4, University of Melbourne5, St. Vincent's Institute of Medical Research6, Johns Hopkins University7, Swiss Institute of Bioinformatics8, The Turing Institute9, Western General Hospital10, BC Cancer Agency11, University of British Columbia12, ETH Zurich13, Delft University of Technology14, Leiden University Medical Center15, Broad Institute16, Georgia State University17, Heidelberg Institute for Theoretical Studies18, Karlsruhe Institute of Technology19, Centrum Wiskunde & Informatica20, Utrecht University21, University of Amsterdam22, Imperial College London23, Radboud University Nijmegen24, University Medical Center Groningen25, Wageningen University and Research Centre26, University of Connecticut27, Wellcome Trust Sanger Institute28, European Bioinformatics Institute29, University of Cambridge30, Max Planck Society31, Saarland University32, Zuse Institute Berlin33, German Cancer Research Center34, Leiden University35, I.M. Sechenov First Moscow State Medical University36, Princeton University37, Memorial Sloan Kettering Cancer Center38
TL;DR: This compendium is for established researchers, newcomers, and students alike, highlighting interesting and rewarding problems for the coming years in single-cell data science.
Abstract: The recent boom in microfluidics and combinatorial indexing strategies, combined with low sequencing costs, has empowered single-cell sequencing technology. Thousands-or even millions-of cells analyzed in a single experiment amount to a data revolution in single-cell biology and pose unique data science problems. Here, we outline eleven challenges that will be central to bringing this emerging field of single-cell data science forward. For each challenge, we highlight motivating research questions, review prior work, and formulate open problems. This compendium is for established researchers, newcomers, and students alike, highlighting interesting and rewarding problems for the coming years.
677 citations
Bernhard Nocht Institute for Tropical Medicine1, Public Health England2, World Health Organization3, Icahn School of Medicine at Mount Sinai4, University of North Carolina at Chapel Hill5, European Medicines Agency6, Peking Union Medical College7, Katholieke Universiteit Leuven8, National Institutes of Health9, University of Alabama at Birmingham10, University of Pittsburgh11, University of Saskatchewan12, University of Maryland, Baltimore13, Erasmus University Medical Center14, Center for Biologics Evaluation and Research15, Université Paris-Saclay16, Wageningen University and Research Centre17, Columbia University18, University of California, San Diego19, University of Texas Medical Branch20, Autonomous University of Barcelona21, Friedrich Loeffler Institute22, Li Ka Shing Faculty of Medicine, University of Hong Kong23, University of Iowa24, Kansas State University25, Tulane University26, University of York27, Geelong Football Club28, Beth Israel Deaconess Medical Center29
TL;DR: The findings of a World Health Organization expert working group that is developing animal models to test vaccines and therapeutic agents for the treatment of COVID-19, and their relevance for preclinical testing, are reviewed.
Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the aetiological agent of coronavirus disease 2019 (COVID-19), an emerging respiratory infection caused by the introduction of a novel coronavirus into humans late in 2019 (first detected in Hubei province, China). As of 18 September 2020, SARS-CoV-2 has spread to 215 countries, has infected more than 30 million people and has caused more than 950,000 deaths. As humans do not have pre-existing immunity to SARS-CoV-2, there is an urgent need to develop therapeutic agents and vaccines to mitigate the current pandemic and to prevent the re-emergence of COVID-19. In February 2020, the World Health Organization (WHO) assembled an international panel to develop animal models for COVID-19 to accelerate the testing of vaccines and therapeutic agents. Here we summarize the findings to date and provides relevant information for preclinical testing of vaccine candidates and therapeutic agents for COVID-19.
630 citations
TL;DR: Variations in mink-derived viral genomes showed between-mink transmission and no infection link between the farms, and inhalable dust contained viral RNA, indicating possible exposure of workers.
Abstract: Respiratory disease and increased mortality occurred in minks on two farms in the Netherlands, with interstitial pneumonia and SARS-CoV-2 RNA in organ and swab samples. On both farms, at least one worker had coronavirus disease-associated symptoms before the outbreak. Variations in mink-derived viral genomes showed between-mink transmission and no infection link between the farms. Inhalable dust contained viral RNA, indicating possible exposure of workers. One worker is assumed to have attracted the virus from mink.
534 citations
University of California, San Diego1, University of Montana2, University of Münster3, University of Jena4, University of Lübeck5, Statens Serum Institut6, University of Tübingen7, University of Geneva8, Bruker9, Paris Descartes University10, University of São Paulo11, Technical University of Berlin12, Georgia Institute of Technology13, Saint Petersburg State University14, Waters Corporation15, Academy of Sciences of the Czech Republic16, Sookmyung Women's University17, University of Grenoble18, University of Oklahoma19, Carnegie Mellon University20, University of West Alabama21, Leibniz Association22, University of Corsica Pascal Paoli23, Massachusetts Institute of Technology24, Michigan State University25, University of Glasgow26, Wageningen University and Research Centre27, Kangwon National University28
TL;DR: Feature-based molecular networking (FBMN) as discussed by the authors is an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools.
Abstract: Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present feature-based molecular networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools. FBMN enables quantitative analysis and resolution of isomers, including from ion mobility spectrometry.
497 citations
TL;DR: This study performed a Systematic Literature Review to extract and synthesize the algorithms and features that have been used in crop yield prediction studies, and found Convolutional Neural Networks is the most widely used deep learning algorithm in these studies.
TL;DR: Two bioinformatic tools enable sequence similarity network and phylogenetic analysis of gene clusters and their families across hundreds of strains and in large datasets, leading to the discovery of new natural products.
Abstract: Genome mining has become a key technology to exploit natural product diversity. Although initially performed on a single-genome basis, the process is now being scaled up to mine entire genera, strain collections and microbiomes. However, no bioinformatic framework is currently available for effectively analyzing datasets of this size and complexity. In the present study, a streamlined computational workflow is provided, consisting of two new software tools: the ‘biosynthetic gene similarity clustering and prospecting engine’ (BiG-SCAPE), which facilitates fast and interactive sequence similarity network analysis of biosynthetic gene clusters and gene cluster families; and the ‘core analysis of syntenic orthologues to prioritize natural product gene clusters’ (CORASON), which elucidates phylogenetic relationships within and across these families. BiG-SCAPE is validated by correlating its output to metabolomic data across 363 actinobacterial strains and the discovery potential of CORASON is demonstrated by comprehensively mapping biosynthetic diversity across a range of detoxin/rimosamide-related gene cluster families, culminating in the characterization of seven detoxin analogues. Two bioinformatic tools, BiG-SCAPE and CORASON, enable sequence similarity network and phylogenetic analysis of gene clusters and their families across hundreds of strains and in large datasets, leading to the discovery of new natural products.
Utrecht University1, National Research Council2, Sea Education Association3, University of Hawaii at Manoa4, Polytechnic University of Catalonia5, Russian Academy of Sciences6, Shirshov Institute of Oceanology7, Alfred Wegener Institute for Polar and Marine Research8, University of Cádiz9, Brown University10, University of Oldenburg11, University of the Highlands and Islands12, Hobart Corporation13, Rochester Institute of Technology14, Kyushu University15, Imperial College London16, Wageningen University and Research Centre17, University of Delaware18, University of Bern19, University of Southampton20, National Physical Laboratory21, Institut de recherche pour le développement22, Plymouth Marine Laboratory23, Newcastle University24, University of Toulouse25, Paul Sabatier University26, California Institute of Technology27, Percy FitzPatrick Institute of African Ornithology28, University of Oregon29, Korean Ocean Research and Development Institute30, Catholic University of the North31, University of Oxford32
TL;DR: In this paper, the authors comprehensively discuss what is known about the different processes that govern the transport of floating marine plastic debris in both the open ocean and the coastal zones, based on the published literature and referring to insights from neighbouring fields such as oil spill dispersion, marine safety recovery, plankton connectivity, and others.
Abstract: Marine plastic debris floating on the ocean surface is a major environmental problem. However, its distribution in the ocean is poorly mapped, and most of the plastic waste estimated to have entered the ocean from land is unaccounted for. Better understanding of how plastic debris is transported from coastal and marine sources is crucial to quantify and close the global inventory of marine plastics, which in turn represents critical information for mitigation or policy strategies. At the same time, plastic is a unique tracer that provides an opportunity to learn more about the physics and dynamics of our ocean across multiple scales, from the Ekman convergence in basin-scale gyres to individual waves in the surfzone. In this review, we comprehensively discuss what is known about the different processes that govern the transport of floating marine plastic debris in both the open ocean and the coastal zones, based on the published literature and referring to insights from neighbouring fields such as oil spill dispersion, marine safety recovery, plankton connectivity, and others. We discuss how measurements of marine plastics (both in situ and in the laboratory), remote sensing, and numerical simulations can elucidate these processes and their interactions across spatio-temporal scales.
TL;DR: The findings support the feasibility of improving the habitual diet to modulate the gut microbiota which in turn has the potential to promote healthier ageing.
Abstract: Objective Ageing is accompanied by deterioration of multiple bodily functions and inflammation, which collectively contribute to frailty. We and others have shown that frailty co-varies with alterations in the gut microbiota in a manner accelerated by consumption of a restricted diversity diet. The Mediterranean diet (MedDiet) is associated with health. In the NU-AGE project, we investigated if a 1-year MedDiet intervention could alter the gut microbiota and reduce frailty. Design We profiled the gut microbiota in 612 non-frail or pre-frail subjects across five European countries (UK, France, Netherlands, Italy and Poland) before and after the administration of a 12-month long MedDiet intervention tailored to elderly subjects (NU-AGE diet). Results Adherence to the diet was associated with specific microbiome alterations. Taxa enriched by adherence to the diet were positively associated with several markers of lower frailty and improved cognitive function, and negatively associated with inflammatory markers including C-reactive protein and interleukin-17. Analysis of the inferred microbial metabolite profiles indicated that the diet-modulated microbiome change was associated with an increase in short/branch chained fatty acid production and lower production of secondary bile acids, p-cresols, ethanol and carbon dioxide. Microbiome ecosystem network analysis showed that the bacterial taxa that responded positively to the MedDiet intervention occupy keystone interaction positions, whereas frailty-associated taxa are peripheral in the networks. Conclusion Collectively, our findings support the feasibility of improving the habitual diet to modulate the gut microbiota which in turn has the potential to promote healthier ageing.
Paul M. Thompson1, Neda Jahanshad1, Christopher R.K. Ching1, Lauren E. Salminen1 +210 more•Institutions (99)
TL;DR: This review summarizes the last decade of work by the ENIGMA Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease, and highlights the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings.
Abstract: This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.
The Catholic University of America1, International Institute of Minnesota2, University of Queensland3, Federal University of Rio de Janeiro4, Wageningen University and Research Centre5, Autonomous University of Barcelona6, Federal Fluminense University7, University of Cambridge8, University of the Philippines Los Baños9, International Union for Conservation of Nature and Natural Resources10, University of Tasmania11, BirdLife International12, University of Natural Resources and Life Sciences, Vienna13, University of São Paulo14, Royal Society for the Protection of Birds15, National University of Cordoba16, World Conservation Monitoring Centre17, International Institute for Applied Systems Analysis18, Environmental Change Institute19, University of Vienna20
TL;DR: It is found that restoring 15% of converted lands in priority areas could avoid 60% of expected extinctions while sequestering 299 gigatonnes of CO 2 —30% of the total CO 2 increase in the atmosphere since the Industrial Revolution.
Abstract: Extensive ecosystem restoration is increasingly seen as being central to conserving biodiversity and stabilizing the climate of the Earth. Although ambitious national and global targets have been set, global priority areas that account for spatial variation in benefits and costs have yet to be identified. Here we develop and apply a multicriteria optimization approach that identifies priority areas for restoration across all terrestrial biomes, and estimates their benefits and costs. We find that restoring 15% of converted lands in priority areas could avoid 60% of expected extinctions while sequestering 299 gigatonnes of CO2—30% of the total CO2 increase in the atmosphere since the Industrial Revolution. The inclusion of several biomes is key to achieving multiple benefits. Cost effectiveness can increase up to 13-fold when spatial allocation is optimized using our multicriteria approach, which highlights the importance of spatial planning. Our results confirm the vast potential contributions of restoration to addressing global challenges, while underscoring the necessity of pursuing these goals synergistically.
International Institute for Applied Systems Analysis1, Environmental Change Institute2, University of Cambridge3, BirdLife International4, Indian Institutes of Technology5, ETH Zurich6, Natural History Museum7, Bioversity International8, Commonwealth Scientific and Industrial Research Organisation9, Sapienza University of Rome10, Netherlands Environmental Assessment Agency11, Zoological Society of London12, World Conservation Monitoring Centre13, Ritsumeikan University14, National Institute for Environmental Studies15, Radboud University Nijmegen16, Potsdam Institute for Climate Impact Research17, University College London18, Imperial College London19, Wageningen University and Research Centre20, Agricultural & Applied Economics Association21, Stockholm Resilience Centre22, Kyoto University23, Humboldt University of Berlin24, Leipzig University25, Pontifical Catholic University of Rio de Janeiro26, International Institute of Minnesota27, Utrecht University28, Wildlife Conservation Society29, University of Queensland30
TL;DR: In this paper, the authors used an ensemble of land-use and biodiversity models to assess whether and how humans can reverse the declines in terrestrial biodiversity caused by habitat conversion, which is a major threat to biodiversity.
Abstract: Increased efforts are required to prevent further losses to terrestrial biodiversity and the ecosystem services that it provides1,2. Ambitious targets have been proposed, such as reversing the declining trends in biodiversity3; however, just feeding the growing human population will make this a challenge4. Here we use an ensemble of land-use and biodiversity models to assess whether—and how—humanity can reverse the declines in terrestrial biodiversity caused by habitat conversion, which is a major threat to biodiversity5. We show that immediate efforts, consistent with the broader sustainability agenda but of unprecedented ambition and coordination, could enable the provision of food for the growing human population while reversing the global terrestrial biodiversity trends caused by habitat conversion. If we decide to increase the extent of land under conservation management, restore degraded land and generalize landscape-level conservation planning, biodiversity trends from habitat conversion could become positive by the mid-twenty-first century on average across models (confidence interval, 2042–2061), but this was not the case for all models. Food prices could increase and, on average across models, almost half (confidence interval, 34–50%) of the future biodiversity losses could not be avoided. However, additionally tackling the drivers of land-use change could avoid conflict with affordable food provision and reduces the environmental effects of the food-provision system. Through further sustainable intensification and trade, reduced food waste and more plant-based human diets, more than two thirds of future biodiversity losses are avoided and the biodiversity trends from habitat conversion are reversed by 2050 for almost all of the models. Although limiting further loss will remain challenging in several biodiversity-rich regions, and other threats—such as climate change—must be addressed to truly reverse the declines in biodiversity, our results show that ambitious conservation efforts and food system transformation are central to an effective post-2020 biodiversity strategy. To promote the recovery of the currently declining global trends in terrestrial biodiversity, increases in both the extent of land under conservation management and the sustainability of the global food system from farm to fork are required.
TL;DR: It is demonstrated that depending on scenarios of population growth and warming, over the coming 50 y, 1 to 3 billion people are projected to be left outside the climate conditions that have served humanity well over the past 6,000 y.
Abstract: All species have an environmental niche, and despite technological advances, humans are unlikely to be an exception. Here, we demonstrate that for millennia, human populations have resided in the same narrow part of the climatic envelope available on the globe, characterized by a major mode around ∼11 °C to 15 °C mean annual temperature (MAT). Supporting the fundamental nature of this temperature niche, current production of crops and livestock is largely limited to the same conditions, and the same optimum has been found for agricultural and nonagricultural economic output of countries through analyses of year-to-year variation. We show that in a business-as-usual climate change scenario, the geographical position of this temperature niche is projected to shift more over the coming 50 y than it has moved since 6000 BP. Populations will not simply track the shifting climate, as adaptation in situ may address some of the challenges, and many other factors affect decisions to migrate. Nevertheless, in the absence of migration, one third of the global population is projected to experience a MAT >29 °C currently found in only 0.8% of the Earth’s land surface, mostly concentrated in the Sahara. As the potentially most affected regions are among the poorest in the world, where adaptive capacity is low, enhancing human development in those areas should be a priority alongside climate mitigation.
TL;DR: The authors reviewed the literature on the political and power dimensions of co-production and showed how depoliticization dynamics in coproduction reinforce rather than mitigate existing unequal power relations and how they prevent wider societal transformation from taking place.
TL;DR: There is a need to return to vector control approaches based on a thorough knowledge of the determinants of pathogen transmission, which utilise a range of insecticide and non–insecticide-based approaches in a locally tailored manner for more effective and sustainable vector control.
Abstract: Vector-borne diseases (VBDs) such as malaria, dengue, and leishmaniasis exert a huge burden of morbidity and mortality worldwide, particularly affecting the poorest of the poor. The principal method by which these diseases are controlled is through vector control, which has a long and distinguished history. Vector control, to a greater extent than drugs or vaccines, has been responsible for shrinking the map of many VBDs. Here, we describe the history of vector control programmes worldwide from the late 1800s to date. Pre 1940, vector control relied on a thorough understanding of vector ecology and epidemiology, and implementation of environmental management tailored to the ecology and behaviour of local vector species. This complex understanding was replaced by a simplified dependency on a handful of insecticide-based tools, particularly for malaria control, without an adequate understanding of entomology and epidemiology and without proper monitoring and evaluation. With the rising threat from insecticide-resistant vectors, global environmental change, and the need to incorporate more vector control interventions to eliminate these diseases, we advocate for continued investment in evidence-based vector control. There is a need to return to vector control approaches based on a thorough knowledge of the determinants of pathogen transmission, which utilise a range of insecticide and non-insecticide-based approaches in a locally tailored manner for more effective and sustainable vector control.
TL;DR: Significant effects of biodegradable plastic residues on the rhizosphere bacterial communities and on the blend of volatiles emitted in therhizosphere are identified, suggesting the urgent need for more research examining their environmental impacts on agroecosystems.
TL;DR: Qualification of microplastic pollution in agricultural fields through the application of sewage sludge is largely unknown, and soils' plastic loads increased by 280 light density microplastics kg-1 and 430 heavy densitymicroplasticskg-1 with each successive application of Sewage sludge, indicating that wastewater sludge application results in accumulation of micro Plastics in agricultural soils.
University of Montana1, Oregon State University2, University of California, San Diego3, Wageningen University and Research Centre4, Sookmyung Women's University5, University of Nantes6, Acharya Nagarjuna University7, Ensenada Center for Scientific Research and Higher Education8, Universidad Autónoma de Chiriquí9, University of Costa Rica10, Auburn University11, Victoria University of Wellington12, University of Johannesburg13, University of Münster14, John Innes Centre15
TL;DR: This protocol describes how to use GNPS to explore uploaded metabolomics data, and provides step-by-step instructions for creating reproducible, high-quality molecular networks.
Abstract: Global Natural Product Social Molecular Networking (GNPS) is an interactive online small molecule-focused tandem mass spectrometry (MS2) data curation and analysis infrastructure. It is intended to provide as much chemical insight as possible into an untargeted MS2 dataset and to connect this chemical insight to the user's underlying biological questions. This can be performed within one liquid chromatography (LC)-MS2 experiment or at the repository scale. GNPS-MassIVE is a public data repository for untargeted MS2 data with sample information (metadata) and annotated MS2 spectra. These publicly accessible data can be annotated and updated with the GNPS infrastructure keeping a continuous record of all changes. This knowledge is disseminated across all public data; it is a living dataset. Molecular networking-one of the main analysis tools used within the GNPS platform-creates a structured data table that reflects the molecular diversity captured in tandem mass spectrometry experiments by computing the relationships of the MS2 spectra as spectral similarity. This protocol provides step-by-step instructions for creating reproducible, high-quality molecular networks. For training purposes, the reader is led through a 90- to 120-min procedure that starts by recalling an example public dataset and its sample information and proceeds to creating and interpreting a molecular network. Each data analysis job can be shared or cloned to disseminate the knowledge gained, thus propagating information that can lead to the discovery of molecules, metabolic pathways, and ecosystem/community interactions.
Free University of Berlin1, Leipzig University2, University of Wyoming3, Wageningen University and Research Centre4, University of Göttingen5, Florida International University6, Martin Luther University of Halle-Wittenberg7, University of Montpellier8, University of Toulouse9, Oak Ridge National Laboratory10, Max Planck Society11, Morton Arboretum12, University of Manchester13
TL;DR: A holistic view of the belowground economy is taken and it is shown that root-mycorrhizal collaboration can short circuit a one-dimensional economic spectrum, providing an entire space of economic possibilities.
Abstract: Plant economics run on carbon and nutrients instead of money. Leaf strategies aboveground span an economic spectrum from "live fast and die young" to "slow and steady," but the economy defined by root strategies belowground remains unclear. Here, we take a holistic view of the belowground economy and show that root-mycorrhizal collaboration can short circuit a one-dimensional economic spectrum, providing an entire space of economic possibilities. Root trait data from 1810 species across the globe confirm a classical fast-slow "conservation" gradient but show that most variation is explained by an orthogonal "collaboration" gradient, ranging from "do-it-yourself" resource uptake to "outsourcing" of resource uptake to mycorrhizal fungi. This broadened "root economics space" provides a solid foundation for predictive understanding of belowground responses to changing environmental conditions.
Technical University of Denmark1, VU University Amsterdam2, Heidelberg University3, École Polytechnique Fédérale de Lausanne4, RWTH Aachen University5, University of California, San Diego6, University of Toronto7, National Autonomous University of Mexico8, Institute for Systems Biology9, University of Tübingen10, University of Queensland11, Argonne National Laboratory12, Leiden University13, Spanish National Research Council14, Technical University of Madrid15, Hanze University of Applied Sciences16, Norwegian University of Life Sciences17, Wellcome Trust18, KAIST19, Max Planck Society20, Humboldt University of Berlin21, Wageningen University and Research Centre22, Agency for Science, Technology and Research23, Sungkyunkwan University24, King's College London25, Royal Institute of Technology26, Chinese Academy of Sciences27, University of Virginia28, Chalmers University of Technology29, University of Arkansas for Medical Sciences30, Oxford Brookes University31, University of Minho32, Nova Southeastern University33, University of Düsseldorf34
TL;DR: A community effort to develop a test suite named MEMOTE (for metabolic model tests) to assess GEM quality, and advocate adoption of the latest version of the Systems Biology Markup Language level 3 flux balance constraints (SBML3FBC) package as the primary description and exchange format.
Abstract: We acknowledge D. Dannaher and A. Lopez for their supporting work on the Angular parts of MEMOTE; resources and support from the DTU Computing Center; J. Cardoso, S. Gudmundsson, K. Jensen and D. Lappa for their feedback on conceptual details; and P. D. Karp and I. Thiele for critically reviewing the manuscript. We thank J. Daniel, T. Kristjansdottir, J. Saez-Saez, S. Sulheim, and P. Tubergen for being early adopters of MEMOTE and for providing written testimonials. J.O.V. received the Research Council of Norway grants 244164 (GenoSysFat), 248792 (DigiSal) and 248810 (Digital Life Norway); M.Z. received the Research Council of Norway grant 244164 (GenoSysFat); C.L. received funding from the Innovation Fund Denmark (project “Environmentally Friendly Protein Production (EFPro2)”); C.L., A.K., N. S., M.B., M.A., D.M., P.M, B.J.S., P.V., K.R.P. and M.H. received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 686070 (DD-DeCaF); B.G.O., F.T.B. and A.D. acknowledge funding from the US National Institutes of Health (NIH, grant number 2R01GM070923-13); A.D. was supported by infrastructural funding from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), Cluster of Excellence EXC 2124 Controlling Microbes to Fight Infections; N.E.L. received funding from NIGMS R35 GM119850, Novo Nordisk Foundation NNF10CC1016517 and the Keck Foundation; A.R. received a Lilly Innovation Fellowship Award; B.G.-J. and J. Nogales received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no 686585 for the project LIAR, and the Spanish Ministry of Economy and Competitivity through the RobDcode grant (BIO2014-59528-JIN); L.M.B. has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 633962 for project P4SB; R.F. received funding from the US Department of Energy, Offices of Advanced Scientific Computing Research and the Biological and Environmental Research as part of the Scientific Discovery Through Advanced Computing program, grant DE-SC0010429; A.M., C.Z., S.L. and J. Nielsen received funding from The Knut and Alice Wallenberg Foundation, Advanced Computing program, grant #DE-SC0010429; S.K.’s work was in part supported by the German Federal Ministry of Education and Research (de.NBI partner project “ModSim” (FKZ: 031L104B)); E.K. and J.A.H.W. were supported by the German Federal Ministry of Education and Research (project “SysToxChip”, FKZ 031A303A); M.K. is supported by the Federal Ministry of Education and Research (BMBF, Germany) within the research network Systems Medicine of the Liver (LiSyM, grant number 031L0054); J.A.P. and G.L.M. acknowledge funding from US National Institutes of Health (T32-LM012416, R01-AT010253, R01-GM108501) and the Wagner Foundation; G.L.M. acknowledges funding from a Grand Challenges Exploration Phase I grant (OPP1211869) from the Bill & Melinda Gates Foundation; H.H. and R.S.M.S. received funding from the Biotechnology and Biological Sciences Research Council MultiMod (BB/N019482/1); H.U.K. and S.Y.L. received funding from the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries (grants NRF-2012M1A2A2026556 and NRF-2012M1A2A2026557) from the Ministry of Science and ICT through the National Research Foundation (NRF) of Korea; H.U.K. received funding from the Bio & Medical Technology Development Program of the NRF, the Ministry of Science and ICT (NRF-2018M3A9H3020459); P.B., B.J.S., Z.K., B.O.P., C.L., M.B., N.S., M.H. and A.F. received funding through Novo Nordisk Foundation through the Center for Biosustainability at the Technical University of Denmark (NNF10CC1016517); D.-Y.L. received funding from the Next-Generation BioGreen 21 Program (SSAC, PJ01334605), Rural Development Administration, Republic of Korea; G.F. was supported by the RobustYeast within ERA net project via SystemsX.ch; V.H. received funding from the ETH Domain and Swiss National Science Foundation; M.P. acknowledges Oxford Brookes University; J.C.X. received support via European Research Council (666053) to W.F. Martin; B.E.E. acknowledges funding through the CSIRO-UQ Synthetic Biology Alliance; C.D. is supported by a Washington Research Foundation Distinguished Investigator Award. I.N. received funding from National Institutes of Health (NIH)/National Institute of General Medical Sciences (NIGMS) (grant P20GM125503).
Max Planck Society1, Woods Hole Research Center2, University of Valencia3, Karlsruhe Institute of Technology4, Wageningen University and Research Centre5, University of Jena6, Universidade Nova de Lisboa7, Université Paris-Saclay8, University of Augsburg9, Commonwealth Scientific and Industrial Research Organisation10, Chiba University11, University of Illinois at Urbana–Champaign12, Nanjing Normal University13, National Center for Atmospheric Research14, University of Exeter15, Central Maine Community College16, Tuscia University17, Ludwig Maximilian University of Munich18, Oak Ridge National Laboratory19
TL;DR: In this paper, the authors provide a systematic assessment of the latest upscaling efforts for gross primary production (GPP) and net ecosystem exchange (NEE) of the FLUXCOM initiative, where different machine learning methods and sets of predictor variables were employed.
Abstract: . FLUXNET comprises globally distributed eddy-covariance-based estimates of carbon fluxes between the biosphere and the
atmosphere. Since eddy covariance flux towers have a relatively small
footprint and are distributed unevenly across the world, upscaling the
observations is necessary to obtain global-scale estimates of
biosphere–atmosphere exchange. Based on cross-consistency checks with
atmospheric inversions, sun-induced fluorescence (SIF) and dynamic global
vegetation models (DGVMs), here we provide a systematic assessment of the
latest upscaling efforts for gross primary production (GPP) and net
ecosystem exchange (NEE) of the FLUXCOM initiative, where different machine
learning methods, forcing data sets and sets of predictor variables were
employed. Spatial patterns of mean GPP are consistent across FLUXCOM and DGVM
ensembles ( R2>0.94 at 1 ∘ spatial resolution)
while the majority of DGVMs show, for 70 % of the land surface, values
outside the FLUXCOM range. Global mean GPP magnitudes for 2008–2010 from
FLUXCOM members vary within 106 and 130 PgC yr −1 with the largest
uncertainty in the tropics. Seasonal variations in independent SIF estimates
agree better with FLUXCOM GPP (mean global pixel-wise R2∼0.75 ) than with GPP from DGVMs (mean global pixel-wise
R2∼0.6 ). Seasonal variations in FLUXCOM NEE show good
consistency with atmospheric inversion-based net land carbon fluxes,
particularly for temperate and boreal regions ( R2>0.92 ).
Interannual variability of global NEE in FLUXCOM is underestimated compared
to inversions and DGVMs. The FLUXCOM version which also uses meteorological
inputs shows a strong co-variation in interannual patterns with inversions
( R2=0.87 for 2001–2010). Mean regional NEE from FLUXCOM shows larger
uptake than inversion and DGVM-based estimates, particularly in the tropics
with discrepancies of up to several hundred grammes of carbon per square metre per year. These
discrepancies can only partly be reconciled by carbon loss pathways that are
implicit in inversions but not captured by the flux tower measurements such
as carbon emissions from fires and water bodies. We hypothesize that a
combination of systematic biases in the underlying eddy covariance data, in
particular in tall tropical forests, and a lack of site history effects on
NEE in FLUXCOM are likely responsible for the too strong tropical carbon
sink estimated by FLUXCOM. Furthermore, as FLUXCOM does not account for
CO2 fertilization effects, carbon flux trends are not realistic.
Overall, current FLUXCOM estimates of mean annual and seasonal cycles of GPP
as well as seasonal NEE variations provide useful constraints of global
carbon cycling, while interannual variability patterns from FLUXCOM are
valuable but require cautious interpretation. Exploring the diversity of
Earth observation data and of machine learning concepts along with improved
quality and quantity of flux tower measurements will facilitate further
improvements of the FLUXCOM approach overall.
TL;DR: More attention is needed for the inclusion and exclusion effects of Agriculture 4.0 technologies, and for reflection on how they relate to diverse transition pathways towards sustainable agricultural and food systems driven by mission-oriented innovation systems.
Wageningen University and Research Centre1, University of California, Davis2, University of Georgia3, Swedish University of Agricultural Sciences4, University of Maine5, University of Koblenz and Landau6, University of Bern7, University of Sussex8, Cornell University9, Michigan State University10, University of British Columbia11, University of Padua12, University of Worcester13, University of Reading14, University of California, Berkeley15, University of Göttingen16, Estonian University of Life Sciences17, Lancaster University18, Lincoln University (New Zealand)19
TL;DR: This synthesis identifies several important drivers of variability in effectiveness of plantings: pollination services declined exponentially with distance from plantings, and perennial and older flower strips with higher flowering plant diversity enhanced pollination more effectively.
Abstract: Floral plantings are promoted to foster ecological intensification of agriculture through provisioning of ecosystem services. However, a comprehensive assessment of the effectiveness of different floral plantings, their characteristics and consequences for crop yield is lacking. Here we quantified the impacts of flower strips and hedgerows on pest control (18 studies) and pollination services (17 studies) in adjacent crops in North America, Europe and New Zealand. Flower strips, but not hedgerows, enhanced pest control services in adjacent fields by 16% on average. However, effects on crop pollination and yield were more variable. Our synthesis identifies several important drivers of variability in effectiveness of plantings: pollination services declined exponentially with distance from plantings, and perennial and older flower strips with higher flowering plant diversity enhanced pollination more effectively. These findings provide promising pathways to optimise floral plantings to more effectively contribute to ecosystem service delivery and ecological intensification of agriculture in the future.
Commonwealth Scientific and Industrial Research Organisation1, International Livestock Research Institute2, Chatham House3, Potsdam Institute for Climate Impact Research4, University of Oslo5, Deakin University6, International Center for Tropical Agriculture7, University of Copenhagen8, University of Oxford9, Wageningen University and Research Centre10, International Institute for Applied Systems Analysis11, University of Minnesota12, Stanford University13, University of Queensland14, University of Potsdam15, University of Aberdeen16, Netherlands Environmental Assessment Agency17, CGIAR18, Utrecht University19
TL;DR: In this article, the authors identify technologies, assess their readiness and propose eight action points that could accelerate the transition towards a more sustainable food system and argue that the speed of innovation could be significantly increased with the appropriate incentives, regulations and social licence.
Abstract: Future technologies and systemic innovation are critical for the profound transformation the food system needs. These innovations range from food production, land use and emissions, all the way to improved diets and waste management. Here, we identify these technologies, assess their readiness and propose eight action points that could accelerate the transition towards a more sustainable food system. We argue that the speed of innovation could be significantly increased with the appropriate incentives, regulations and social licence. These, in turn, require constructive stakeholder dialogue and clear transition pathways.
Forschungszentrum Jülich1, University of Bonn2, The Nature Conservancy3, Wageningen University and Research Centre4, Technische Universität München5, Cornell University6, University of California, Berkeley7, University of Reading8, Ohio State University9, University of Sydney10, Nanjing Agricultural University11, Colorado State University12, Centre national de la recherche scientifique13, Indiana University14, Université catholique de Louvain15, University of Illinois at Urbana–Champaign16
TL;DR: This work proposes the establishment of a soil information system containing localised information on soil group, degradation status, crop yield gap, and the associated carbon-sequestration potentials, as well as the provision of incentives and policies to translate management options into region- and soil-specific practices.
Abstract: Sustainable soil carbon sequestration practices need to be rapidly scaled up and implemented to contribute to climate change mitigation. We highlight that the major potential for carbon sequestration is in cropland soils, especially those with large yield gaps and/or large historic soil organic carbon losses. The implementation of soil carbon sequestration measures requires a diverse set of options, each adapted to local soil conditions and management opportunities, and accounting for site-specific trade-offs. We propose the establishment of a soil information system containing localised information on soil group, degradation status, crop yield gap, and the associated carbon-sequestration potentials, as well as the provision of incentives and policies to translate management options into region- and soil-specific practices.