Agricultural soils are responsible for the majority of nitrous oxide (N2O) emissions in the USA. Irrigated cropping, particularly in the western USA, is an important source of N2O emissions. However, the impacts of tillage intensity and N fertilizer amount and type have not been extensively studied for irrigated systems. The DAYCENT biogeochemical model was tested using N2O, crop yield, soil N and C, and other data collected from irrigated cropping systems in northeastern Colorado during 2002 to 2006. DAYCENT uses daily weather, soil texture, and land management information to simulate C and N fluxes between the atmosphere, soil, and vegetation. The model properly represented the impacts of tillage intensity and N fertilizer amount on crop yields, soil organic C (SOC), and soil water content. DAYCENT N2O emissions matched the measured data in that simulated emissions increased as N fertilization rates increased and emissions from no\uffe2\uff80\uff90till (NT) tended to be lower on average than conventional\uffe2\uff80\uff90till (CT). However, the model overestimated N2O emissions. Lowering the amount of N2O emitted per unit of N nitrified from 2 to 1% helped improve model fit but the treatments receiving no N fertilizer were still overestimated by more than a factor of 2. Both the model and measurements showed that soil NO3\uffe2\uff88\uff92 levels increase with N fertilizer addition and with tillage intensity, but DAYCENT underestimated NO3\uffe2\uff88\uff92 levels, particularly for the treatments receiving no N fertilizer. We suggest that DAYCENT could be improved by reducing the background nitrification rate and by accounting for the impact of changes in microbial community structure on denitrification rates.
", "keywords": ["Crops", " Agricultural", "2. Zero hunger", "Colorado", "13. Climate action", "Nitrous Oxide", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "Models", " Theoretical", "15. Life on land", "6. Clean water"], "contacts": [{"organization": "A. D. Halvorson, S. J. Del Grosso, William J. Parton,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.2134/jeq2007.0292"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Environmental%20Quality", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.2134/jeq2007.0292", "name": "item", "description": "10.2134/jeq2007.0292", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2134/jeq2007.0292"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2008-07-01T00:00:00Z"}}, {"id": "10.3390/catal9030222", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:21:34Z", "type": "Journal Article", "created": "2019-03-04", "title": "Immobilised Cerium-Doped Zinc Oxide as a Photocatalyst for the Degradation of Antibiotics and the Inactivation of Antibiotic-Resistant Bacteria", "description": "The threat of antibiotic resistance to the wellbeing of societies is well established. Urban wastewater treatment plants (UWTPs) are recognised sources for antibiotic resistance dissemination in the environment. Herein a novel cerium-doped zinc oxide (Ce-ZnO) photocatalyst is compared to ZnO and the benchmark TiO2-P25 in the immobilised form on a metallic support, to evaluate a photocatalytic process as a possible tertiary treatment in UWTPs. The catalysts were compared for the removal of two antibiotics, trimethoprim (TMP) and sulfamethoxazole (SMX), and for the inactivation of Escherichia coli (E. coli) strain DH5-Alpha in isotonic sodium chloride solution and of autochthonous bacteria in real secondary wastewater. In real wastewater, E. coli and other coliforms were monitored, as well as the respective fractions resistant to ofloxacin and azithromycin. In parallel, Pseudomonas aeruginosa and the respective sub-population resistant to ofloxacin or ciprofloxacin were also monitored. Photocatalysis with both ZnO and Ce-ZnO was faster than using TiO2-P25 at degrading the antibiotics, with Ce-ZnO the fastest against SMX but slower than undoped ZnO in the removal of TMP. Ce-ZnO catalyst reuse in the immobilised form produced somewhat slower kinetics maintained >50% of the initial activity, even after five cycles of use. Approximately 3 log10 inactivation of E. coli in isotonic sodium chloride water was recorded with reproducible results. In the removal of autochthonous bacteria in real wastewater, Ce-ZnO performed better (more than 2 log values higher) than TiO2-P25. In all cases, E. coli and other coliforms, including their resistant subpopulations, were inactivated at a higher rate than P. aeruginosa. With short reaction times no evidence for enrichment of resistance was observed, yet with extended reaction times low levels of bacterial loads were not further inactivated. Overall, Ce-ZnO is an easy and cheap photocatalyst to produce and immobilise and the one that showed higher activity than the industry standard TiO2-P25 against the tested antibiotics and bacteria, including antibiotic-resistant bacteria.
", "keywords": ["tertiary treatment", "wastewater disinfection", "antibiotic resistance", "Antibiotic resistance", "Tertiary treatment", "immobilised photocatalyst", "Immobilised photocatalyst", "02 engineering and technology", "01 natural sciences", "6. Clean water", "3. Good health", "Wastewater disinfection", "13. Climate action", "11. Sustainability", "Antibiotic resistance; Immobilised photocatalyst; Photocatalysis; Tertiary treatment; Wastewater disinfection; Catalysis; Physical and Theoretical Chemistry", "Photocatalysis", "0210 nano-technology", "photocatalysis", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://www.mdpi.com/2073-4344/9/3/222/pdf"}, {"href": "https://www.iris.unisa.it/bitstream/11386/4723219/1/Zammit%20et%20al.%202019_Catalysts.pdf"}, {"href": "https://www.mdpi.com/2073-4344/9/3/222/pdf"}, {"href": "https://doi.org/10.3390/catal9030222"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Catalysts", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/catal9030222", "name": "item", "description": "10.3390/catal9030222", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/catal9030222"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-03-01T00:00:00Z"}}, {"id": "10.3390/rs12010072", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:21:44Z", "type": "Journal Article", "created": "2019-12-24", "title": "Evaluation of Backscattering Models and Support Vector Machine for the Retrieval of Bare Soil Moisture from Sentinel-1 Data", "description": "The main objective of this work was to retrieve surface soil moisture (SSM) by using scattering models and a support vector machine (SVM) technique driven by backscattering coefficients obtained from Sentinel-1 satellite images acquired over bare agricultural soil in the Tensfit basin of Morocco. Two backscattering models were selected in this study due to their wide use in inversion procedures: the theoretical integral equation model (IEM) and the semi-empirical model (Oh). To this end, the sensitivity of the SAR backscattering coefficients at V V ( \uffcf\uff83 v v \uffe2\uff88\uff98 ) and V H ( \uffcf\uff83 v h \uffe2\uff88\uff98 ) polarizations to in situ soil moisture data were analyzed first. As expected, the results showed that over bare soil the \uffcf\uff83 v v \uffe2\uff88\uff98 was well correlated with SSM compared to the \uffcf\uff83 v h \uffe2\uff88\uff98 , which showed more dispersion with correlation coefficients values (r) of about 0.84 and 0.61 for the V V and V H polarizations, respectively. Afterwards, these values of \uffcf\uff83 v v \uffe2\uff88\uff98 were compared to those simulated by the backscatter models. It was found that IEM driven by the measured length correlation L slightly underestimated SAR backscatter coefficients compared to the Oh model with a bias of about \uffe2\uff88\uff92 0.7 dB and \uffe2\uff88\uff92 1.2 dB and a root mean square (RMSE) of about 1.1 dB and 1.5 dB for Oh and IEM models, respectively. However, the use of an optimal value of L significantly improved the bias of IEM, which became near to zero, and the RMSE decreased to 0.9 dB. Then, a classical inversion approach of \uffcf\uff83 v v \uffe2\uff88\uff98 observations based on backscattering model is compared to a data driven retrieval technic (SVM). By comparing the retrieved soil moisture against ground truth measurements, it was found that results of SVM were very encouraging and were close to those obtained by IEM model. The bias and RMSE were about 0.28 vol.% and 2.77 vol.% and \uffe2\uff88\uff92 0.13 vol.% and 2.71 vol.% for SVM and IEM, respectively. However, by taking into account the difficultly of obtaining roughness parameter at large scale, it was concluded that SVM is still a useful tool to retrieve soil moisture, and therefore, can be fairly used to generate maps at such scales.
", "keywords": ["[SDE] Environmental Sciences", "soil moisture; synthetic aperture radar (SAR); Sentinel-1; semi-empirical and theoretical backscatter models; support vector machine; bare soil", "550", "Science", "sentinel-1", "Q", "0211 other engineering and technologies", "0207 environmental engineering", "support vector", "02 engineering and technology", "synthetic aperture radar (SAR)", "15. Life on land", "543", "bare soil", "[SDE]Environmental Sciences", "Sentinel-1", "support vector machine", "soil moisture", "synthetic aperture radar (sar)", "semi-empirical and theoretical backscatter models", "machine"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/12/1/72/pdf"}, {"href": "https://www.mdpi.com/2072-4292/12/1/72/pdf"}, {"href": "https://doi.org/10.3390/rs12010072"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Remote%20Sensing", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/rs12010072", "name": "item", "description": "10.3390/rs12010072", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/rs12010072"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-12-24T00:00:00Z"}}, {"id": "20.500.11850/667312", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:26:22Z", "type": "Journal Article", "created": "2024-03-25", "title": "Priorities, opportunities, and challenges for integrating microorganisms into Earth system models for climate change prediction", "description": "ABSTRACTClimate change jeopardizes human health, global biodiversity, and sustainability of the biosphere. To make reliable predictions about climate change, scientists use Earth system models (ESMs) that integrate physical, chemical, and biological processes occurring on land, the oceans, and the atmosphere. Although critical for catalyzing coupled biogeochemical processes, microorganisms have traditionally been left out of ESMs. Here, we generate a \uffe2\uff80\uff9ctop 10\uffe2\uff80\uff9d list of priorities, opportunities, and challenges for the explicit integration of microorganisms into ESMs. We discuss the need for coarse-graining microbial information into functionally relevant categories, as well as the capacity for microorganisms to rapidly evolve in response to climate-change drivers. Microbiologists are uniquely positioned to collect novel and valuable information necessary for next-generation ESMs, but this requires data harmonization and transdisciplinary collaboration to effectively guide adaptation strategies and mitigation policy.
", "keywords": ["Naturgeografi", "Earth", " Planet", "Climate Change", "Microbiology", "traits", "biogeochemistry", "Humans", "Ecosystem", "Biomedical and Clinical Sciences", "Bacteria", "biogeochemistry; modeling; traits; climate change", "modeling", "Opinion/Hypothesis", "Biodiversity", "Biological Sciences", "Medical microbiology", "Models", " Theoretical", "15. Life on land", "QR1-502", "6. Clean water", "Climate Science", "3. Good health", "Climate Action", "climate change", "Physical Geography", "Medical Microbiology", "13. Climate action", "Biochemistry and cell biology", "Biochemistry and Cell Biology", "Generic health relevance", "Klimatvetenskap"]}, "links": [{"href": "https://journals.asm.org/doi/pdf/10.1128/mbio.00455-24"}, {"href": "https://doi.org/20.500.11850/667312"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/mBio", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "20.500.11850/667312", "name": "item", "description": "20.500.11850/667312", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.11850/667312"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-05-08T00:00:00Z"}}, {"id": "10451/59767", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:25:40Z", "type": "Journal Article", "created": "2018-11-03", "title": "\u03b415N of lichens reflects the isotopic signature of ammonia source", "description": "Although it is generally accepted that \u03b415N in lichen reflects predominating N isotope sources in the environment, confirmation of the direct correlation between lichen \u03b415N and atmospheric \u03b415N is still missing, especially under field conditions with most confounding factors controlled. To fill this gap and investigate the response of lichens with different tolerance to atmospheric N deposition, thalli of the sensitive Evernia prunastri and the tolerant Xanthoria parietina were exposed for ten weeks to different forms and doses of N in a field manipulation experiment where confounding factors were minimized. During this period, several parameters, namely total N, \u03b415N and chlorophyll a fluorescence, were measured. Under the experimental conditions, \u03b415N in lichens quantitatively responded to the \u03b415N of released gaseous ammonia (NH3). Although a high correlation between the isotopic signatures in lichen tissue and supplied N was found both in tolerant and sensitive species, chlorophyll a fluorescence indicated that the sensitive species very soon lost its photosynthetic functionality with increasing N availability. The most damaging response to the different N chemical forms was observed with dry deposition of NH3, although wet deposition of ammonium ions had a significant observable physiological impact. Conversely, there was no significant effect of nitrate ions on chlorophyll a fluorescence, implying differential sensitivity to dry deposition versus wet deposition and to ammonium versus nitrate in wet deposition. Evernia prunastri was most sensitive to NH3, then NH4+, with lowest sensitivity to NO3-. Moreover, these results confirm that lichen \u03b415N can be used to indicate the \u03b415N of atmospheric ammonia, providing a suitable tool for the interpretation of the spatial distribution of NH3 sources in relation to their \u03b415N signal.", "keywords": ["Air Pollutants", "Nitrates", "Lichens", "Nitrogen Isotopes", "Chlorophyll A", "0211 other engineering and technologies", "02 engineering and technology", "Models", " Theoretical", "chlorophyll a fluorescence", "01 natural sciences", "nitrogen deposition", "Xanthoria parietina", "Species Specificity", "Ammonia", "13. Climate action", "source spatial distribution", "biomonitoring", "physiological response", "Photosynthesis", "Environmental Monitoring", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://repositorio.ulisboa.pt/bitstream/10451/59767/1/1-s2.0-S0048969718343560-main.pdf"}, {"href": "https://doi.org/10451/59767"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20of%20The%20Total%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10451/59767", "name": "item", "description": "10451/59767", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10451/59767"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-02-01T00:00:00Z"}}, {"id": "11019/2295", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:25:47Z", "type": "Journal Article", "created": "2017-11-24", "title": "Functional Land Management: Bridging the Think-Do-Gap using a multi-stakeholder science policy interface", "description": "Functional Land Management (FLM) is proposed as an integrator for sustainability policies and assesses the functional capacity of the soil and land to deliver primary productivity, water purification and regulation, carbon cycling and storage, habitat for biodiversity and recycling of nutrients. This paper presents the catchment challenge as a method to bridge the gap between science, stakeholders and policy for the effective management of soils to deliver these functions. Two challenges were completed by a wide range of stakeholders focused around a physical catchment model-(1) to design an optimised catchment based on soil function targets, (2) identify gaps to implementation of the proposed design. In challenge 1, a high level of consensus between different stakeholders emerged on soil and management measures to be implemented to achieve soil function targets. Key gaps including knowledge, a mix of market and voluntary incentives and mandatory measures were identified in challenge 2.", "keywords": ["Conservation of Natural Resources", "functional land management", "Soil functions", "01 natural sciences", "12. Responsible consumption", "Soil", "11. Sustainability", "Functional Land Management", "Policy framework", "Ecosystem", "0105 earth and related environmental sciences", "2. Zero hunger", "Think-Do-Gap", "Biodiversity", "04 agricultural and veterinary sciences", "soil functions", "Models", " Theoretical", "15. Life on land", "sustainability", "6. Clean water", "Sustainability", "13. Climate action", "think-do-gap", "Perspective", "0401 agriculture", " forestry", " and fisheries", "policy framework", "stakeholder workshops", "Stakeholder workshops"]}, "links": [{"href": "http://link.springer.com/content/pdf/10.1007/s13280-017-0983-x.pdf"}, {"href": "https://doi.org/11019/2295"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Ambio", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11019/2295", "name": "item", "description": "11019/2295", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11019/2295"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-11-24T00:00:00Z"}}, {"id": "2808068377", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:26:50Z", "type": "Journal Article", "created": "2018-06-15", "title": "Out of Shape During Stress: A Key Role for Auxin", "description": "In most abiotic stress conditions, including salinity and water deficit, the developmental plasticity of the plant root is regulated by the phytohormone auxin. Changes in auxin concentration are often attributed to changes in shoot-derived long-distance auxin flow. However, recent evidence suggests important contributions by short-distance auxin transport from local storage and local auxin biosynthesis, conjugation, and oxidation during abiotic stress. We discuss here current knowledge on long-distance auxin transport in stress responses, and subsequently debate how short-distance auxin transport and indole-3-acetic acid (IAA) metabolism play a role in influencing eventual auxin accumulation and signaling patterns. Our analysis stresses the importance of considering all these components together and highlights the use of mathematical modeling for predictions of plant physiological responses.", "keywords": ["0301 basic medicine", "0303 health sciences", "abiotic stress", "Indoleacetic Acids", "auxin transport", "mathematical modeling", "Biological Transport", "IAA homeostasis", "Models", " Theoretical", "Plants", "Plant Roots", "Article", "03 medical and health sciences", "Plant Growth Regulators", "root phenotypic plasticity", "Stress", " Physiological", "auxin", "Plant Physiological Phenomena", "Signal Transduction"]}, "links": [{"href": "https://doi.org/2808068377"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Trends%20in%20Plant%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2808068377", "name": "item", "description": "2808068377", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2808068377"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-09-01T00:00:00Z"}}, {"id": "2804595293", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:26:50Z", "type": "Journal Article", "created": "2018-05-26", "title": "Biotic responses buffer warming\u2010induced soil organic carbon loss in Arctic tundra", "description": "AbstractClimate warming can result in both abiotic (e.g., permafrost thaw) and biotic (e.g., microbial functional genes) changes in Arctic tundra. Recent research has incorporated dynamic permafrost thaw in Earth system models (ESMs) and indicates that Arctic tundra could be a significant future carbon (C) source due to the enhanced decomposition of thawed deep soil C. However, warming\uffe2\uff80\uff90induced biotic changes may influence biologically related parameters and the consequent projections inESMs. How model parameters associated with biotic responses will change under warming and to what extent these changes affect projected C budgets have not been carefully examined. In this study, we synthesized six data sets over 5\uffc2\uffa0years from a soil warming experiment at the Eight Mile Lake, Alaska, into the TerrestrialECOsystem (TECO) model with a probabilistic inversion approach. TheTECOmodel used multiple soil layers to track dynamics of thawed soil under different treatments. Our results show that warming increased light use efficiency of vegetation photosynthesis but decreased baseline (i.e., environment\uffe2\uff80\uff90corrected) turnover rates ofSOCin both the fast and slow pools in comparison with those under control. Moreover, the parameter changes generally amplified over time, suggesting processes of gradual physiological acclimation and functional gene shifts of both plants and microbes. TheTECOmodel predicted that field warming from 2009 to 2013 resulted in cumulative C losses of 224 or 87\uffc2\uffa0g/m2, respectively, without or with changes in those parameters. Thus, warming\uffe2\uff80\uff90induced parameter changes reduced predicted soil C loss by 61%. Our study suggests that it is critical to incorporate biotic changes inESMs to improve the model performance in predicting C dynamics in permafrost regions.
We lack strong empirical evidence for links between plant attributes (plant community attributes and functional traits) and the distribution of soil microbial communities at large spatial scales.
Using datasets from two contrasting regions and ecosystem types in Australia and England, we report that aboveground plant community attributes, such as diversity (species richness) and cover, and functional traits can predict a unique portion of the variation in the diversity (number of phylotypes) and community composition of soil bacteria and fungi that cannot be explained by soil abiotic properties and climate. We further identify the relative importance and evaluate the potential direct and indirect effects of climate, soil properties and plant attributes in regulating the diversity and community composition of soil microbial communities.
Finally, we deliver a list of examples of common taxa from Australia and England that are strongly related to specific plant traits, such as specific leaf area index, leaf nitrogen and nitrogen fixation.
Together, our work provides new evidence that plant attributes, especially plant functional traits, can predict the distribution of soil microbial communities at the regional scale and across two hemispheres.
One of the largest uncertainties in the terrestrial carbon cycle is the timing and magnitude of soil organic carbon (SOC) response to climate and vegetation change. This uncertainty prevents models from adequately capturing SOC dynamics and challenges the assessment of management and climate change effects on soils. Reducing these uncertainties requires simultaneous investigation of factors controlling the amount (SOC abundance) and duration (SOC persistence) of stored C. We present a global synthesis of SOC and radiocarbon profiles (nProfile\uffe2\uff80\uff89=\uffe2\uff80\uff89597) to assess the timescales of SOC storage. We use a combination of statistical and depth\uffe2\uff80\uff90resolved compartment models to explore key factors controlling the relationships between SOC abundance and persistence across pedo\uffe2\uff80\uff90climatic regions and with soil depth. This allows us to better understand (i) how SOC abundance and persistence covary across pedo\uffe2\uff80\uff90climatic regions and (ii) how the depth dependence of SOC dynamics relates to climatic and mineralogical controls on SOC abundance and persistence. We show that SOC abundance and persistence are differently related; the controls on these relationships differ substantially between major pedo\uffe2\uff80\uff90climatic regions and soil depth. For example, large amounts of persistent SOC can reflect climatic constraints on soils (e.g., in tundra/polar regions) or mineral absorption, reflected in slower decomposition and vertical transport rates. In contrast, lower SOC abundance can be found with lower SOC persistence (e.g., in highly weathered tropical soils) or higher SOC persistence (e.g., in drier and less productive regions). We relate variable patterns of SOC abundance and persistence to differences in the processes constraining plant C input, microbial decomposition, vertical C transport and mineral SOC stabilization potential. This process\uffe2\uff80\uff90oriented grouping of SOC abundance and persistence provides a valuable benchmark for global C models, highlighting that pedo\uffe2\uff80\uff90climatic boundary conditions are crucial for predicting the effects of climate change and soil management on future C abundance and persistence.Nitrous oxide (N2O) emissions from inland waters remain a major source of uncertainty in global greenhouse gas budgets. N2O emissions are typically estimated using emission factors (EFs), defined as the proportion of the terrestrial nitrogen (N) load to a water body that is emitted as N2O to the atmosphere. The Intergovernmental Panel on Climate Change (IPCC) has proposed EFs of 0.25% and 0.75%, though studies have suggested that both these values are either too high or too low. In this work, we develop a mechanistic modeling approach to explicitly predict N2O production and emissions via nitrification and denitrification in rivers, reservoirs and estuaries. In particular, we introduce a water residence time dependence, which kinetically limits the extent of denitrification and nitrification in water bodies. We revise existing spatially explicit estimates of N loads to inland waters to predict both lumped watershed and half\uffe2\uff80\uff90degree grid cell emissions and EFs worldwide, as well as the proportions of these emissions that originate from denitrification and nitrification. We estimate global inland water N2O emissions of 10.6\uffe2\uff80\uff9319.8\uffc2\uffa0Gmol\uffc2\uffa0N\uffc2\uffa0year\uffe2\uff88\uff921 (148\uffe2\uff80\uff93277\uffc2\uffa0Gg\uffc2\uffa0N\uffc2\uffa0year\uffe2\uff88\uff921), with reservoirs producing most N2O per unit area. Our results indicate that IPCC EFs are likely overestimated by up to an order of magnitude, and that achieving the magnitude of the IPCC's EFs is kinetically improbable in most river systems. Denitrification represents the major pathway of N2O production in river systems, whereas nitrification dominates production in reservoirs and estuaries.Lakes (including reservoirs) are an important component of the global carbon (C) cycle, as acknowledged by the fifth assessment report of the IPCC. In the context of lakes, the boreal region is disproportionately important contributing to 27% of the worldwide lake area, despite representing just 14% of global land surface area. In this study, we used a statistical approach to derive a prediction equation\uffc2\uffa0for the partial pressure of CO2 (pCO2) in lakes as a function of lake area, terrestrial net primary productivity (NPP), and precipitation (r2\uffc2\uffa0=\uffc2\uffa0.56), and to create the first high\uffe2\uff80\uff90resolution, circumboreal map (0.5\uffc2\uffb0) of lake pCO2. The map of\uffc2\uffa0pCO2 was combined with lake area from the recently published GLOWABO database and three different estimates of the gas transfer velocity k to produce a resulting map of CO2 evasion (FCO2). For the boreal region, we estimate an average, lake area weighted, pCO2 of 966 (678\uffe2\uff80\uff931,325) \uffce\uffbcatm and a total\uffc2\uffa0FCO2 of 189 (74\uffe2\uff80\uff93347) Tg\uffc2\uffa0C\uffc2\uffa0year\uffe2\uff88\uff921, and evaluate the corresponding uncertainties based on Monte Carlo simulation. Our estimate of FCO2 is approximately twofold greater than previous estimates, as a result of methodological and data source differences. We use our results along with published estimates of the other C fluxes through inland waters to derive a C budget for the boreal region, and find that FCO2 from lakes is the most significant flux of the land\uffe2\uff80\uff90ocean aquatic continuum, and of a similar magnitude as emissions from forest fires. Using the model and applying it to spatially resolved projections of terrestrial NPP and precipitation while keeping everything else constant, we predict a 107% increase in boreal lake FCO2 under emission scenario RCP8.5 by 2100. Our projections are largely driven by increases in terrestrial NPP over the same period, showing the very close connection between the terrestrial and aquatic C cycle.The river\uffe2\uff80\uff93floodplain network plays an important role in the carbon (C) cycle of the Amazon basin, as it transports and processes a significant fraction of the C fixed by terrestrial vegetation, most of which evades as CO2 from rivers and floodplains back to the atmosphere. There is empirical evidence that exceptionally dry or wet years have an impact on the net C balance in the Amazon. While seasonal and interannual variations in hydrology have a direct impact on the amounts of C transferred through the river\uffe2\uff80\uff93floodplain system, it is not known how far the variation of these fluxes affects the overall Amazon C balance. Here, we introduce a new wetland forcing file for the ORCHILEAK model, which improves the representation of floodplain dynamics and allows us to closely reproduce data\uffe2\uff80\uff90driven estimates of net C exports through the river\uffe2\uff80\uff93floodplain network. Based on this new wetland forcing and two climate forcing datasets, we show that across the Amazon, the percentage of net primary productivity lost to the river\uffe2\uff80\uff93floodplain system is highly variable at the interannual timescale, and wet years fuel aquatic CO2 evasion. However, at the same time overall net ecosystem productivity (NEP) and C sequestration are highest during wet years, partly due to reduced decomposition rates in water\uffe2\uff80\uff90logged floodplain soils. It is years with the lowest discharge and floodplain inundation, often associated with El Nino events, that have the lowest NEP and the highest total (terrestrial plus aquatic) CO2 emissions back to atmosphere. Furthermore, we find that aquatic C fluxes display greater variation than terrestrial C fluxes, and that this variation significantly dampens the interannual variability in NEP of the Amazon basin. These results call for a more integrative view of the C fluxes through the vegetation\uffe2\uff80\uff90soil\uffe2\uff80\uff90river\uffe2\uff80\uff90floodplain continuum, which directly places aquatic C fluxes into the overall C budget of the Amazon basin.Current biogeochemical models produce carbon\uffe2\uff80\uff93climate feedback projections with large uncertainties, often attributed to their structural differences when simulating soil organic carbon (SOC) dynamics worldwide. However, choices of model parameter values that quantify the strength and represent properties of different soil carbon cycle processes could also contribute to model simulation uncertainties. Here, we demonstrate the critical role of using common observational data in reducing model uncertainty in estimates of global SOC storage. Two structurally different models featuring distinctive carbon pools, decomposition kinetics, and carbon transfer pathways simulate opposite global SOC distributions with their customary parameter values yet converge to similar results after being informed by the same global SOC database using a data assimilation approach. The converged spatial SOC simulations result from similar simulations in key model components such as carbon transfer efficiency, baseline decomposition rate, and environmental effects on carbon fluxes by these two models after data assimilation. Moreover, data assimilation results suggest equally effective simulations of SOC using models following either first\uffe2\uff80\uff90order or Michaelis\uffe2\uff80\uff93Menten kinetics at the global scale. Nevertheless, a wider range of data with high\uffe2\uff80\uff90quality control and assurance are needed to further constrain SOC dynamics simulations and reduce unconstrained parameters. New sets of data, such as microbial genomics\uffe2\uff80\uff90function relationships, may also suggest novel structures to account for in future model development. Overall, our results highlight the importance of observational data in informing model development and constraining model predictions.Climate warming can result in both abiotic (e.g., permafrost thaw) and biotic (e.g., microbial functional genes) changes in Arctic tundra. Recent research has incorporated dynamic permafrost thaw in Earth system models (ESMs) and indicates that Arctic tundra could be a significant future carbon (C) source due to the enhanced decomposition of thawed deep soil C. However, warming\uffe2\uff80\uff90induced biotic changes may influence biologically related parameters and the consequent projections inESMs. How model parameters associated with biotic responses will change under warming and to what extent these changes affect projected C budgets have not been carefully examined. In this study, we synthesized six data sets over 5\uffc2\uffa0years from a soil warming experiment at the Eight Mile Lake, Alaska, into the TerrestrialECOsystem (TECO) model with a probabilistic inversion approach. TheTECOmodel used multiple soil layers to track dynamics of thawed soil under different treatments. Our results show that warming increased light use efficiency of vegetation photosynthesis but decreased baseline (i.e., environment\uffe2\uff80\uff90corrected) turnover rates ofSOCin both the fast and slow pools in comparison with those under control. Moreover, the parameter changes generally amplified over time, suggesting processes of gradual physiological acclimation and functional gene shifts of both plants and microbes. TheTECOmodel predicted that field warming from 2009 to 2013 resulted in cumulative C losses of 224 or 87\uffc2\uffa0g/m2, respectively, without or with changes in those parameters. Thus, warming\uffe2\uff80\uff90induced parameter changes reduced predicted soil C loss by 61%. Our study suggests that it is critical to incorporate biotic changes inESMs to improve the model performance in predicting C dynamics in permafrost regions.Global soil nitrogen (N) cycling remains poorly understood due to its complex driving mechanisms. Here, we present a comprehensive analysis of global soil \uffce\uffb415N, a stable isotopic signature indicative of the N input\uffe2\uff80\uff93output balance, using a machine\uffe2\uff80\uff90learning approach on 10,676 observations from 2670 sites. Our findings reveal prevalent joint effects of climatic conditions, plant N\uffe2\uff80\uff90use strategies, soil properties, and other natural and anthropogenic forcings on global soil \uffce\uffb415N. The joint effects of multiple drivers govern the latitudinal distribution of soil \uffce\uffb415N, with more rapid N cycling at lower latitudes than at higher latitudes. In contrast to previous climate\uffe2\uff80\uff90focused models, our data\uffe2\uff80\uff90driven model more accurately simulates spatial changes in global soil \uffce\uffb415N, highlighting the need to consider the joint effects of multiple drivers to estimate the Earth's N budget. These insights contribute to the reconciliation of discordances among empirical, theoretical, and modeling studies on soil N cycling, as well as sustainable N management.Microbial carbon use efficiency (CUE) is an important variable mediating microbial effects on soil organic carbon (SOC) since it summarizes how much carbon is used for microbial growth or is respired. Yet, the role of CUE in regulating SOC storage remains debated, with evidence for both positive and negative SOC\uffe2\uff80\uff90CUE relations. Here, we use a combination of measured data around the world and numerical simulations to explore SOC\uffe2\uff80\uff90CUE relations accounting for temperature (T) effects on CUE. Results reveal that the sign of the CUE\uffe2\uff80\uff90T relation controls the direction of the SOC\uffe2\uff80\uff90CUE relations. A negative CUE\uffe2\uff80\uff90T relation leads to a positive SOC\uffe2\uff80\uff90CUE relation and vice versa, highlighting that CUE\uffe2\uff80\uff90T patterns significantly affect how organic carbon is used by microbes and hence SOC\uffe2\uff80\uff90CUE relations. Numerical results also confirm the observed negative SOC\uffe2\uff80\uff90T relation, regardless of the CUE\uffe2\uff80\uff90T patterns, implying that temperature plays a more dominant role than CUE in controlling SOC storage. The SOC\uffe2\uff80\uff90CUE relation is usually negative when temperature effects are isolated, even though it can become positive when nonlinear microbial turnover is considered. These results indicate a dominant role of CUE\uffe2\uff80\uff90T patterns in controlling the SOC\uffe2\uff80\uff90CUE relation. Our findings help to better understand SOC and microbial responses to a warming climate.AbstractenviPath is a widely used database and prediction system for microbial biotransformation pathways of primarily xenobiotic compounds. Data and prediction system are freely available both via a web interface and a public REST API. Since its initial release in 2016, we extended the data available in enviPath and improved the performance of the prediction system and usability of the overall system. We now provide three diverse data sets, covering microbial biotransformation in different environments and under different experimental conditions. This also enabled developing a pathway prediction model that is applicable to a more diverse set of chemicals. In the prediction engine, we implemented a new evaluation tailored towards pathway prediction, which returns a more honest and holistic view on the performance. We also implemented a novel applicability domain algorithm, which allows the user to estimate how well the model will perform on their data. Finally, we improved the implementation to speed up the overall system and provide new functionality via a plugin system. Overall, enviPath has developed into a reliable database and prediction system with a unique use case in research in microbial biotransformations.
", "keywords": ["10120 Department of Chemistry", "0301 basic medicine", "0303 health sciences", "Biodegradation database", "Information technology", "T58.5-58.64", "1704 Computer Graphics and Computer-Aided Design", "3. Good health", "Database", "Chemistry", "03 medical and health sciences", "Metabolic pathways", "540 Chemistry", "Machine learning", "1706 Computer Science Applications", "Biodegradation pathway prediction", "3309 Library and Information Sciences", "1606 Physical and Theoretical Chemistry", "QD1-999"]}, "links": [{"href": "https://doi.org/PMC11304562"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Cheminformatics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "PMC11304562", "name": "item", "description": "PMC11304562", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/PMC11304562"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-11-15T00:00:00Z"}}, {"id": "PMC6121082", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:29:45Z", "type": "Journal Article", "created": "2018-06-15", "title": "Out of Shape During Stress: A Key Role for Auxin", "description": "In most abiotic stress conditions, including salinity and water deficit, the developmental plasticity of the plant root is regulated by the phytohormone auxin. Changes in auxin concentration are often attributed to changes in shoot-derived long-distance auxin flow. However, recent evidence suggests important contributions by short-distance auxin transport from local storage and local auxin biosynthesis, conjugation, and oxidation during abiotic stress. We discuss here current knowledge on long-distance auxin transport in stress responses, and subsequently debate how short-distance auxin transport and indole-3-acetic acid (IAA) metabolism play a role in influencing eventual auxin accumulation and signaling patterns. Our analysis stresses the importance of considering all these components together and highlights the use of mathematical modeling for predictions of plant physiological responses.", "keywords": ["0301 basic medicine", "0303 health sciences", "abiotic stress", "Indoleacetic Acids", "auxin transport", "mathematical modeling", "Biological Transport", "IAA homeostasis", "Models", " Theoretical", "Plants", "Plant Roots", "Article", "03 medical and health sciences", "Plant Growth Regulators", "root phenotypic plasticity", "Stress", " Physiological", "auxin", "Plant Physiological Phenomena", "Signal Transduction"]}, "links": [{"href": "https://doi.org/PMC6121082"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Trends%20in%20Plant%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "PMC6121082", "name": "item", "description": "PMC6121082", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/PMC6121082"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-09-01T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=+Theoretical&offset=50&f=json", "hreflang": "en-US"}, {"rel": "alternate", "type": "text/html", "title": "This document as HTML", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=+Theoretical&offset=50&f=html", "hreflang": "en-US"}, {"rel": "collection", "type": "application/json", "title": "Collection URL", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main", "hreflang": "en-US"}, {"type": "application/geo+json", "rel": "prev", "title": "items (prev)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=+Theoretical&offset=0", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=+Theoretical&offset=77", "hreflang": "en-US"}], "numberMatched": 77, "numberReturned": 27, "distributedFeatures": [], "timeStamp": "2026-06-25T11:15:45.441427Z"}