{"type": "FeatureCollection", "features": [{"id": "10.1002/2015gb005239", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:14:19Z", "type": "Journal Article", "created": "2015-12-19", "title": "Toward More Realistic Projections Of Soil Carbon Dynamics By Earth System Models", "description": "Abstract

Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real\uffe2\uff80\uff90world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first\uffe2\uff80\uff90order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth\uffe2\uff80\uff90dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool\uffe2\uff80\uff90 and flux\uffe2\uff80\uff90based data sets through data assimilation is among the highest priorities for near\uffe2\uff80\uff90term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. We recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.

", "keywords": ["550", "LAND MODELS", "Oceanography", "HETEROTROPHIC RESPIRATION", "01 natural sciences", "Atmospheric Sciences", "LITTER DECOMPOSITION", "ORGANIC-CARBON", "Geoinformatics", "GLOBAL CLIMATE-CHANGE", "DATA-ASSIMILATION", "Meteorology & Atmospheric Sciences", "TEMPERATURE SENSITIVITY", "CMIP5", "MICROBIAL MODELS", "0105 earth and related environmental sciences", "2. Zero hunger", "[SDU.OCEAN]Sciences of the Universe [physics]/Ocean", "Atmosphere", "[SDU.OCEAN] Sciences of the Universe [physics]/Ocean", " Atmosphere", "500", "Earth system models", "04 agricultural and veterinary sciences", "15. Life on land", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "6. Clean water", "TERRESTRIAL ECOSYSTEMS", "Climate Action", "Geochemistry", "Climate change impacts and adaptation", "realistic projections", "13. Climate action", "recommendations", "Earth Sciences", "0401 agriculture", " forestry", " and fisheries", "soil carbon dynamics", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "environment", "Climate Change Impacts and Adaptation", "Environmental Sciences", "PARAMETER-ESTIMATION"]}, "links": [{"href": "https://escholarship.org/content/qt1pw7g2r2/qt1pw7g2r2.pdf"}, {"href": "https://doi.org/10.1002/2015gb005239"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Biogeochemical%20Cycles", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/2015gb005239", "name": "item", "description": "10.1002/2015gb005239", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/2015gb005239"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-01-01T00:00:00Z"}}, {"id": "10.1029/2018gb005950", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:17:41Z", "type": "Journal Article", "created": "2018-10-12", "title": "Soil Organic Matter Persistence as a Stochastic Process: Age and Transit Time Distributions of Carbon in Soils", "description": "

The question of why some types of organic matter are more persistent while others decompose quickly in soils has motivated a large amount of research in recent years. Persistence is commonly characterized as turnover or mean residence time of soil organic matter (SOM). However, turnover and residence times are ambiguous measures of persistence, because they could represent the concept of either age or transit time. To disambiguate these concepts and propose a metric to assess SOM persistence, we calculated age and transit time distributions for a wide range of soil organic carbon models. Furthermore, we show how age and transit time distributions can be obtained from a stochastic approach that takes a deterministic model of mass transfers among different pools and creates an equivalent stochastic model at the level of atoms. Using this approach we show the following: (1) Age distributions have relatively old mean values and long tails in relation to transit time distributions, suggesting that carbon stored in soils is on average much older than carbon in the release flux. (2) The difference between mean ages and mean transit times is large, with estimates of soil organic carbon persistence on the order of centuries or millennia when assessed using ages and on the order of decades when using transit or turnover times. (3) The age distribution is an appropriate metric to characterize persistence of SOM. An important implication of our analysis is that random chance is a factor that helps to explain why some organic matter persists for millennia in soil.

", "keywords": ["2. Zero hunger", "Aging", "time scales", "04 agricultural and veterinary sciences", "carbon storage", "15. Life on land", "Oceanography", "01 natural sciences", "soil models", "Atmospheric Sciences", "Geochemistry", "Climate change impacts and adaptation", "13. Climate action", "Geoinformatics", "Earth Sciences", "Meteorology & Atmospheric Sciences", "0401 agriculture", " forestry", " and fisheries", "soil carbon", "Climate Change Impacts and Adaptation", "Environmental Sciences", "model diagnostics", "Research Articles", "biogeochemical cycling", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2018GB005950"}, {"href": "https://escholarship.org/content/qt2sh647x7/qt2sh647x7.pdf"}, {"href": "https://doi.org/10.1029/2018gb005950"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Biogeochemical%20Cycles", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1029/2018gb005950", "name": "item", "description": "10.1029/2018gb005950", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1029/2018gb005950"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-10-01T00:00:00Z"}}, {"id": "10.1111/gcb.14504", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:18:45Z", "type": "Journal Article", "created": "2018-10-29", "title": "Nitrous oxide emissions from inland waters: Are IPCC estimates too high?", "description": "Abstract

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.The question of why some types of organic matter are more persistent while others decompose quickly in soils has motivated a large amount of research in recent years. Persistence is commonly characterized as turnover or mean residence time of soil organic matter (SOM). However, turnover and residence times are ambiguous measures of persistence, because they could represent the concept of either age or transit time. To disambiguate these concepts and propose a metric to assess SOM persistence, we calculated age and transit time distributions for a wide range of soil organic carbon models. Furthermore, we show how age and transit time distributions can be obtained from a stochastic approach that takes a deterministic model of mass transfers among different pools and creates an equivalent stochastic model at the level of atoms. Using this approach we show the following: (1) Age distributions have relatively old mean values and long tails in relation to transit time distributions, suggesting that carbon stored in soils is on average much older than carbon in the release flux. (2) The difference between mean ages and mean transit times is large, with estimates of soil organic carbon persistence on the order of centuries or millennia when assessed using ages and on the order of decades when using transit or turnover times. (3) The age distribution is an appropriate metric to characterize persistence of SOM. An important implication of our analysis is that random chance is a factor that helps to explain why some organic matter persists for millennia in soil.

", "keywords": ["2. Zero hunger", "Aging", "time scales", "04 agricultural and veterinary sciences", "carbon storage", "15. Life on land", "Oceanography", "01 natural sciences", "soil models", "Atmospheric Sciences", "Geochemistry", "Climate change impacts and adaptation", "13. Climate action", "Geoinformatics", "Earth Sciences", "Meteorology & Atmospheric Sciences", "0401 agriculture", " forestry", " and fisheries", "soil carbon", "Climate Change Impacts and Adaptation", "Environmental Sciences", "model diagnostics", "Research Articles", "biogeochemical cycling", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2018GB005950"}, {"href": "https://escholarship.org/content/qt2sh647x7/qt2sh647x7.pdf"}, {"href": "https://doi.org/10.1029/2018GB005950"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Biogeochemical%20Cycles", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1029/2018GB005950", "name": "item", "description": "10.1029/2018GB005950", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1029/2018GB005950"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-10-01T00:00:00Z"}}, {"id": "10.1038/s41467-019-10373-z", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:17:48Z", "type": "Journal Article", "created": "2019-05-30", "title": "A few Ascomycota taxa dominate soil fungal communities worldwide", "description": "Abstract

Despite having key functions in terrestrial ecosystems, information on the dominant soil fungi and their ecological preferences at the global scale is lacking. To fill this knowledge gap, we surveyed 235 soils from across the globe. Our findings indicate that 83 phylotypes (<0.1% of the retrieved fungi), mostly belonging to wind dispersed, generalist Ascomycota, dominate soils globally. We identify patterns and ecological drivers of dominant soil fungal taxa occurrence, and present a map of their distribution in soils worldwide. Whole-genome comparisons with less dominant, generalist fungi point at a significantly higher number of genes related to stress-tolerance and resource uptake in the dominant fungi, suggesting that they might be better in colonising a wide range of environments. Our findings constitute a major advance in our understanding of the ecology of fungi, and have implications for the development of strategies to preserve them and the ecosystem functions they provide.Identifying the global drivers of soil priming is essential to understanding C cycling in terrestrial ecosystems. We conducted a survey of soils across 86 globally-distributed locations, spanning a wide range of climates, biotic communities, and soil conditions, and evaluated the apparent soil priming effect using13C-glucose labeling. Here we show that the magnitude of the positive apparent priming effect (increase in CO2release through accelerated microbial biomass turnover) was negatively associated with SOC content and microbial respiration rates. Our statistical modeling suggests that apparent priming effects tend to be negative in more mesic sites associated with higher SOC contents. In contrast, a single-input of labile C causes positive apparent priming effects in more arid locations with low SOC contents. Our results provide solid evidence that SOC content plays a critical role in regulating apparent priming effects, with important implications for the improvement of C cycling models under global change scenarios.Soil is the largest terrestrial reservoir of organic carbon and is central for climate change mitigation and carbon-climate feedbacks. Chemical and physical associations of soil carbon with minerals play a critical role in carbon storage, but the amount and global capacity for storage in this form remain unquantified. Here, we produce spatially-resolved global estimates of mineral-associated organic carbon stocks and carbon-storage capacity by analyzing 1144 globally-distributed soil profiles. We show that current stocks total 899 Pg C to a depth of 1\uffe2\uff80\uff89m in non-permafrost mineral soils. Although this constitutes 66% and 70% of soil carbon in surface and deeper layers, respectively, it is only 42% and 21% of the mineralogical capacity. Regions under agricultural management and deeper soil layers show the largest undersaturation of mineral-associated carbon. Critically, the degree of undersaturation indicates sequestration efficiency over years to decades. We show that, across 103 carbon-accrual measurements spanning management interventions globally, soils furthest from their mineralogical capacity are more effective at accruing carbon; sequestration rates average 3-times higher in soils at one tenth of their capacity compared to soils at one half of their capacity. Our findings provide insights into the world\uffe2\uff80\uff99s soils, their capacity to store carbon, and priority regions and actions for soil carbon management.Warming alters soil microbial traits through ecological and evolutionary processes, directly influencing the decomposition of organic matter, which significantly affects global soil carbon emissions. Yet, soil carbon models largely ignore these processes and their implications for global responses to warming. Here, we incorporate eco\uffe2\uff80\uff90evolutionary theory into a mechanistic model describing microbial soil carbon decomposition to address the question of whether such processes could have consequential effects on climate carbon feedbacks globally. We assume that a key trait of microbes, their resource allocation to production of exoenzymes (which facilitate decomposition of organic matter)\uffe2\uff80\uff94is optimized to environmental temperatures by natural selection. We find that eco\uffe2\uff80\uff90evolutionary optimization results in microbes allocating more resources to enzyme production under warming. When applied at the global scale, eco\uffe2\uff80\uff90evolutionary optimization enhances the biological realism of soil carbon models and significantly amplifies global soil carbon loss by 2100. Our results highlight the significant potential of microbial eco\uffe2\uff80\uff90evolutionary responses to influence carbon cycle feedbacks to climate change, and motivate an urgent need for more comprehensive data to accurately quantify the adaptive potential of microbiomes in response to climate change.

Terrestrial primary productivity and carbon cycle impacts of droughts are commonly quantified using vapour pressure deficit (VPD) data and remotely sensed greenness, without accounting for soil moisture. However, soil moisture limitation is known to strongly affect plant physiology.

Here, we investigate light use efficiency, the ratio of gross primary productivity (GPP) to absorbed light. We derive its fractional reduction due to soil moisture (fLUE), separated from VPD and greenness changes, using artificial neural networks trained on eddy covariance data, multiple soil moisture datasets and remotely sensed greenness.

This reveals substantial impacts of soil moisture alone that reduce GPP by up to 40% at sites located in sub\uffe2\uff80\uff90humid, semi\uffe2\uff80\uff90arid or arid regions. For sites in relatively moist climates, we find, paradoxically, a muted fLUE response to drying soil, but reduced fLUE under wet conditions.

fLUE identifies substantial drought impacts that are not captured when relying solely on VPD and greenness changes and, when seasonally recurring, are missed by traditional, anomaly\uffe2\uff80\uff90based drought indices. Counter to common assumptions, fLUE reductions are largest in drought\uffe2\uff80\uff90deciduous vegetation, including grasslands. Our results highlight the necessity to account for soil moisture limitation in terrestrial primary productivity data products, especially for drought\uffe2\uff80\uff90related assessments.

Our findings indicate the importance of paleoclimatic information to improve quantitative predictions of global soil C stocks.

", "keywords": ["0301 basic medicine", "arid regions", "550", "Climate Change", "Veterinary and Food Sciences", "41 Environmental Sciences", "anzsrc-for: 3007 Forestry Sciences", "Soil fertility", "30 Agricultural", "carbon content", "anzsrc-for: 41 Environmental Sciences", "climatic changes", "anzsrc-for: 30 Agricultural", "03 medical and health sciences", "Mid-Holocene", "XXXXXX - Unknown", "4101 Climate Change Impacts and Adaptation", "Global scale", "anzsrc-for: 31 Biological Sciences", "soils", "Research Articles", "agriculture", "13 Climate Action", "0303 health sciences", "Last Glacial Maximum", "3007 Forestry Sciences", "Soil Carbon", "15. Life on land", "anzsrc-for: 4101 Climate Change Impacts and Adaptation", "13. Climate action", "Croplands", "ecosystems", "31 Biological Sciences"]}, "links": [{"href": "https://doi.org/10.1126/sciadv.1602008"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20Advances", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1126/sciadv.1602008", "name": "item", "description": "10.1126/sciadv.1602008", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1126/sciadv.1602008"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-04-07T00:00:00Z"}}, {"id": "10.1126/sciadv.aat1296", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:19:10Z", "type": "Journal Article", "created": "2018-03-14", "title": "Response to comment on \u201cClimate legacies drive global soil carbon stocks in terrestrial ecosystem\u201d", "description": "

We discuss possible mechanisms to explain paleoclimate as a predictor of the current distribution of global soil C content.

", "keywords": ["550", "Climate", "paleoclimatology", "Technical Comments", "04 agricultural and veterinary sciences", "41 Environmental Sciences", "15. Life on land", "01 natural sciences", "carbon content", "Carbon", "anzsrc-for: 41 Environmental Sciences", "anzsrc-for: 4101 Climate Change Impacts and Adaptation", "Soil", "13. Climate action", "XXXXXX - Unknown", "4101 Climate Change Impacts and Adaptation", "0401 agriculture", " forestry", " and fisheries", "soils", "Ecosystem", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1126/sciadv.aat1296"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20Advances", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1126/sciadv.aat1296", "name": "item", "description": "10.1126/sciadv.aat1296", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1126/sciadv.aat1296"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-03-02T00:00:00Z"}}, {"id": "2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/282542", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:25:35Z", "type": "Journal Article", "created": "2018-10-29", "title": "Nitrous oxide emissions from inland waters: Are IPCC estimates too high?", "description": "Abstract

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.Abstract. Measuring in situ soil fluxes of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) continuously at high frequency requires appropriate technology. We tested the combination of a commercial automated soil CO2 flux chamber system (LI-8100A) with a CH4 and N2O analyzer (Picarro G2308) in a tropical rainforest for 4\uffc2\uffa0months. A chamber closure time of 2\uffe2\uff80\uff89min was sufficient for a reliable estimation of CO2 and CH4 fluxes (100\uffe2\uff80\uff89% and 98.5\uffe2\uff80\uff89% of fluxes were above minimum detectable flux \uffe2\uff80\uff93 MDF, respectively). This closure time was generally not suitable for a reliable estimation of the low N2O fluxes in this ecosystem but was sufficient for detecting rare major peak events. A closure time of 25\uffe2\uff80\uff89min was more appropriate for reliable estimation of most N2O fluxes (85.6\uffe2\uff80\uff89% of measured fluxes are above MDF\uffe2\uff80\uff89\uffc2\uffb1\uffe2\uff80\uff890.002\uffe2\uff80\uff89nmol\uffe2\uff80\uff89m\uffe2\uff88\uff922\uffe2\uff80\uff89s\uffe2\uff88\uff921). Our study highlights the importance of adjusted closure time for each gas.

", "keywords": ["rain-forest", "nitrous-oxide", "Environmental management", "550", "[SDV]Life Sciences [q-bio]", "spatial variation", "01 natural sciences", "630", "land-use change", "Life", "QH501-531", "Meteorology & Atmospheric Sciences", "biogeochemical controls", "Physical geography and environmental geoscience", "Biology", "QH540-549.5", "0105 earth and related environmental sciences", "QE1-996.5", "Ecology", "Physics", "n2o", "emissions", "land-use change ; nitrous-oxide ; rain-forest ;biogeochemical controls ; chamber measurements ; spatial variation ; co2 ;emissions; n2o ; respiration", "Geology", "04 agricultural and veterinary sciences", "Biological Sciences", "15. Life on land", "Climate Action", "[SDV] Life Sciences [q-bio]", "Chemistry", "13. Climate action", "Earth Sciences", "co2", "0401 agriculture", " forestry", " and fisheries", "chamber measurements", "Climate Change Impacts and Adaptation", "Environmental Sciences", "respiration"]}, "links": [{"href": "https://bg.copernicus.org/articles/16/785/2019/bg-16-785-2019.pdf"}, {"href": "https://escholarship.org/content/qt73p9116t/qt73p9116t.pdf"}, {"href": "https://doi.org/10.5194/bg-16-785-2019"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Biogeosciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/bg-16-785-2019", "name": "item", "description": "10.5194/bg-16-785-2019", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/bg-16-785-2019"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-08-15T00:00:00Z"}}, {"id": "10044/1/59029", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:24:34Z", "type": "Journal Article", "created": "2018-03-31", "title": "Quantifying soil moisture impacts on light use efficiency across biomes", "description": "Summary

Terrestrial primary productivity and carbon cycle impacts of droughts are commonly quantified using vapour pressure deficit (VPD) data and remotely sensed greenness, without accounting for soil moisture. However, soil moisture limitation is known to strongly affect plant physiology.

Here, we investigate light use efficiency, the ratio of gross primary productivity (GPP) to absorbed light. We derive its fractional reduction due to soil moisture (fLUE), separated from VPD and greenness changes, using artificial neural networks trained on eddy covariance data, multiple soil moisture datasets and remotely sensed greenness.

This reveals substantial impacts of soil moisture alone that reduce GPP by up to 40% at sites located in sub\uffe2\uff80\uff90humid, semi\uffe2\uff80\uff90arid or arid regions. For sites in relatively moist climates, we find, paradoxically, a muted fLUE response to drying soil, but reduced fLUE under wet conditions.

fLUE identifies substantial drought impacts that are not captured when relying solely on VPD and greenness changes and, when seasonally recurring, are missed by traditional, anomaly\uffe2\uff80\uff90based drought indices. Counter to common assumptions, fLUE reductions are largest in drought\uffe2\uff80\uff90deciduous vegetation, including grasslands. Our results highlight the necessity to account for soil moisture limitation in terrestrial primary productivity data products, especially for drought\uffe2\uff80\uff90related assessments.

Abstract. Measuring in situ soil fluxes of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) continuously at high frequency requires appropriate technology. We tested the combination of a commercial automated soil CO2 flux chamber system (LI-8100A) with a CH4 and N2O analyzer (Picarro G2308) in a tropical rainforest for 4\u00a0months. A chamber closure time of 2\u2009min was sufficient for a reliable estimation of CO2 and CH4 fluxes (100\u2009% and 98.5\u2009% of fluxes were above minimum detectable flux \u2013 MDF, respectively). This closure time was generally not suitable for a reliable estimation of the low N2O fluxes in this ecosystem but was sufficient for detecting rare major peak events. A closure time of 25\u2009min was more appropriate for reliable estimation of most N2O fluxes (85.6\u2009% of measured fluxes are above MDF\u2009\u00b1\u20090.002\u2009nmol\u2009m\u22122\u2009s\u22121). Our study highlights the importance of adjusted closure time for each gas.

", "keywords": ["rain-forest", "nitrous-oxide", "Environmental management", "550", "[SDV]Life Sciences [q-bio]", "spatial variation", "01 natural sciences", "630", "Meteorology & Atmospheric Sciences (science-metrix)", "3103 Ecology (for-2020)", "land-use change", "Life", "QH501-531", "4101 Climate Change Impacts and Adaptation (for-2020)", "Meteorology & Atmospheric Sciences", "04 Earth Sciences (for)", "biogeochemical controls", "Physical geography and environmental geoscience", "Biology", "QH540-549.5", "0105 earth and related environmental sciences", "QE1-996.5", "31 Biological Sciences (for-2020)", "41 Environmental Sciences (for-2020)", "Ecology", "Physics", "n2o", "emissions", "land-use change ; nitrous-oxide ; rain-forest ;biogeochemical controls ; chamber measurements ; spatial variation ; co2 ;emissions; n2o ; respiration", "Geology", "04 agricultural and veterinary sciences", "Biological Sciences", "15. Life on land", "4104 Environmental management (for-2020)", "06 Biological Sciences (for)", "Climate Action", "[SDV] Life Sciences [q-bio]", "Chemistry", "13. Climate action", "Earth Sciences", "co2", "0401 agriculture", " forestry", " and fisheries", "13 Climate Action (sdg)", "chamber measurements", "Climate Change Impacts and Adaptation", "3709 Physical geography and environmental geoscience (for-2020)", "Environmental Sciences", "05 Environmental Sciences (for)", "respiration"]}, "links": [{"href": "https://bg.copernicus.org/articles/16/785/2019/bg-16-785-2019.pdf"}, {"href": "https://escholarship.org/content/qt73p9116t/qt73p9116t.pdf"}, {"href": "https://doi.org/10067/1574910151162165141"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Biogeosciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10067/1574910151162165141", "name": "item", "description": "10067/1574910151162165141", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10067/1574910151162165141"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-08-15T00:00:00Z"}}, {"id": "10067/1897670151162165141", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:24:35Z", "type": "Journal Article", "created": "2022-07-01", "title": "Global stocks and capacity of mineral-associated soil organic carbon", "description": "Abstract

Soil is the largest terrestrial reservoir of organic carbon and is central for climate change mitigation and carbon-climate feedbacks. Chemical and physical associations of soil carbon with minerals play a critical role in carbon storage, but the amount and global capacity for storage in this form remain unquantified. Here, we produce spatially-resolved global estimates of mineral-associated organic carbon stocks and carbon-storage capacity by analyzing 1144 globally-distributed soil profiles. We show that current stocks total 899 Pg C to a depth of 1\uffe2\uff80\uff89m in non-permafrost mineral soils. Although this constitutes 66% and 70% of soil carbon in surface and deeper layers, respectively, it is only 42% and 21% of the mineralogical capacity. Regions under agricultural management and deeper soil layers show the largest undersaturation of mineral-associated carbon. Critically, the degree of undersaturation indicates sequestration efficiency over years to decades. We show that, across 103 carbon-accrual measurements spanning management interventions globally, soils furthest from their mineralogical capacity are more effective at accruing carbon; sequestration rates average 3-times higher in soils at one tenth of their capacity compared to soils at one half of their capacity. Our findings provide insights into the world\uffe2\uff80\uff99s soils, their capacity to store carbon, and priority regions and actions for soil carbon management.

We discuss possible mechanisms to explain paleoclimate as a predictor of the current distribution of global soil C content.

", "keywords": ["550", "Climate", "paleoclimatology", "Technical Comments", "04 agricultural and veterinary sciences", "41 Environmental Sciences", "15. Life on land", "01 natural sciences", "carbon content", "Carbon", "anzsrc-for: 41 Environmental Sciences", "anzsrc-for: 4101 Climate Change Impacts and Adaptation", "Soil", "13. Climate action", "XXXXXX - Unknown", "4101 Climate Change Impacts and Adaptation", "0401 agriculture", " forestry", " and fisheries", "soils", "Ecosystem", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/1959.4/unsworks_58880"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20Advances", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1959.4/unsworks_58880", "name": "item", "description": "1959.4/unsworks_58880", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1959.4/unsworks_58880"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-03-02T00:00:00Z"}}, {"id": "1959.4/unsworks_64930", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:25:20Z", "type": "Journal Article", "created": "2017-04-14", "title": "Climate legacies drive global soil carbon stocks in terrestrial ecosystems", "description": "

Our findings indicate the importance of paleoclimatic information to improve quantitative predictions of global soil C stocks.

", "keywords": ["0301 basic medicine", "arid regions", "550", "Climate Change", "Veterinary and Food Sciences", "41 Environmental Sciences", "anzsrc-for: 3007 Forestry Sciences", "Soil fertility", "30 Agricultural", "carbon content", "anzsrc-for: 41 Environmental Sciences", "climatic changes", "anzsrc-for: 30 Agricultural", "03 medical and health sciences", "Mid-Holocene", "XXXXXX - Unknown", "4101 Climate Change Impacts and Adaptation", "Global scale", "anzsrc-for: 31 Biological Sciences", "soils", "Research Articles", "agriculture", "13 Climate Action", "0303 health sciences", "Last Glacial Maximum", "3007 Forestry Sciences", "Soil Carbon", "15. Life on land", "anzsrc-for: 4101 Climate Change Impacts and Adaptation", "13. Climate action", "Croplands", "ecosystems", "31 Biological Sciences"]}, "links": [{"href": "https://doi.org/1959.4/unsworks_64930"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20Advances", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1959.4/unsworks_64930", "name": "item", "description": "1959.4/unsworks_64930", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1959.4/unsworks_64930"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-04-07T00:00:00Z"}}, {"id": "1959.4/unsworks_64939", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:25:20Z", "type": "Journal Article", "created": "2019-05-30", "title": "A few Ascomycota taxa dominate soil fungal communities worldwide", "description": "Abstract

Despite having key functions in terrestrial ecosystems, information on the dominant soil fungi and their ecological preferences at the global scale is lacking. To fill this knowledge gap, we surveyed 235 soils from across the globe. Our findings indicate that 83 phylotypes (<0.1% of the retrieved fungi), mostly belonging to wind dispersed, generalist Ascomycota, dominate soils globally. We identify patterns and ecological drivers of dominant soil fungal taxa occurrence, and present a map of their distribution in soils worldwide. Whole-genome comparisons with less dominant, generalist fungi point at a significantly higher number of genes related to stress-tolerance and resource uptake in the dominant fungi, suggesting that they might be better in colonising a wide range of environments. Our findings constitute a major advance in our understanding of the ecology of fungi, and have implications for the development of strategies to preserve them and the ecosystem functions they provide.Identifying the global drivers of soil priming is essential to understanding C cycling in terrestrial ecosystems. We conducted a survey of soils across 86 globally-distributed locations, spanning a wide range of climates, biotic communities, and soil conditions, and evaluated the apparent soil priming effect using13C-glucose labeling. Here we show that the magnitude of the positive apparent priming effect (increase in CO2release through accelerated microbial biomass turnover) was negatively associated with SOC content and microbial respiration rates. Our statistical modeling suggests that apparent priming effects tend to be negative in more mesic sites associated with higher SOC contents. In contrast, a single-input of labile C causes positive apparent priming effects in more arid locations with low SOC contents. Our results provide solid evidence that SOC content plays a critical role in regulating apparent priming effects, with important implications for the improvement of C cycling models under global change scenarios.

The question of why some types of organic matter are more persistent while others decompose quickly in soils has motivated a large amount of research in recent years. Persistence is commonly characterized as turnover or mean residence time of soil organic matter (SOM). However, turnover and residence times are ambiguous measures of persistence, because they could represent the concept of either age or transit time. To disambiguate these concepts and propose a metric to assess SOM persistence, we calculated age and transit time distributions for a wide range of soil organic carbon models. Furthermore, we show how age and transit time distributions can be obtained from a stochastic approach that takes a deterministic model of mass transfers among different pools and creates an equivalent stochastic model at the level of atoms. Using this approach we show the following: (1) Age distributions have relatively old mean values and long tails in relation to transit time distributions, suggesting that carbon stored in soils is on average much older than carbon in the release flux. (2) The difference between mean ages and mean transit times is large, with estimates of soil organic carbon persistence on the order of centuries or millennia when assessed using ages and on the order of decades when using transit or turnover times. (3) The age distribution is an appropriate metric to characterize persistence of SOM. An important implication of our analysis is that random chance is a factor that helps to explain why some organic matter persists for millennia in soil.

", "keywords": ["2. Zero hunger", "Aging", "time scales", "04 agricultural and veterinary sciences", "carbon storage", "15. Life on land", "Oceanography", "01 natural sciences", "soil models", "Atmospheric Sciences", "Geochemistry", "Climate change impacts and adaptation", "13. Climate action", "Geoinformatics", "Earth Sciences", "Meteorology & Atmospheric Sciences", "0401 agriculture", " forestry", " and fisheries", "soil carbon", "Climate Change Impacts and Adaptation", "Environmental Sciences", "model diagnostics", "Research Articles", "biogeochemical cycling", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2018GB005950"}, {"href": "https://escholarship.org/content/qt2sh647x7/qt2sh647x7.pdf"}, {"href": "https://doi.org/21.11116/0000-0002-8A0B-7"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Biogeochemical%20Cycles", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "21.11116/0000-0002-8A0B-7", "name": "item", "description": "21.11116/0000-0002-8A0B-7", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/21.11116/0000-0002-8A0B-7"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-10-01T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Climate+Change+Impacts+and+Adaptation&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=Climate+Change+Impacts+and+Adaptation&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": "first", "title": "items (first)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Climate+Change+Impacts+and+Adaptation&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Climate+Change+Impacts+and+Adaptation&offset=21", "hreflang": "en-US"}], "numberMatched": 21, "numberReturned": 21, "distributedFeatures": [], "timeStamp": "2026-07-26T13:13:41.618727Z"}