{"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<p>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.</p>", "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": "<?xml version='1.0' encoding='UTF-8'?><article><p>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.</p></article>", "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": "10.1029/2018GB005950", "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": "<p>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.</p>", "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": "10.1029/2019ms001776", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:17:42Z", "type": "Journal Article", "created": "2019-12-20", "title": "Mathematical Reconstruction of Land Carbon Models From Their Numerical Output: Computing Soil Radiocarbon From C Dynamics", "description": "Abstract<p>Radiocarbon (14C) is a powerful tracer of the global carbon cycle that is commonly used to assess carbon cycling rates in various Earth system reservoirs and as a benchmark to assess model performance. Therefore, it has been recommended that Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 report predicted radiocarbon values for relevant carbon pools. However, a detailed representation of radiocarbon dynamics may be an impractical burden on model developers. Here, we present an alternative approach to compute radiocarbon values from the numerical output of an ESM that does not explicitly represent these dynamics. The approach requires computed 12C stocks and fluxes among all carbon pools for a particular simulation of the model. From this output, a time\uffe2\uff80\uff90dependent linear compartmental system is computed with its respective state\uffe2\uff80\uff90transition matrix. Using transient atmospheric 14C values as inputs, the state\uffe2\uff80\uff90transition matrix is then applied to compute radiocarbon values for each pool, the average value for the entire system, and component fluxes. We demonstrate the approach with ELMv1\uffe2\uff80\uff90ECA, the land component of an ESM model that explicitly represents 12C, and 14C in 7 soil pools and 10 vertical layers. Results from our proposed method are highly accurate (relative error &lt;0.01%) compared with the ELMv1\uffe2\uff80\uff90ECA 12C and 14C predictions, demonstrating the potential to use this approach in CMIP6 and other model simulations that do not explicitly represent 14C.</p>", "keywords": ["Atmospheric sciences", "Life on Land", "Bioengineering", "Earth system models", "dynamical systems", "compartmental systems", "01 natural sciences", "Atmospheric Sciences", "13. Climate action", "Geoinformatics", "Earth Sciences", "radiocarbon", "model diagnostics", "carbon cycle models", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2019MS001776"}, {"href": "https://doi.org/10.1029/2019ms001776"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Advances%20in%20Modeling%20Earth%20Systems", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1029/2019ms001776", "name": "item", "description": "10.1029/2019ms001776", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1029/2019ms001776"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-01T00:00:00Z"}}, {"id": "10.3390/ijgi7040132", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:21:00Z", "type": "Journal Article", "created": "2018-02-01", "title": "Enhancing Location-Related Hydrogeological Knowledge", "description": "<p>1) Background: We analyzed the corpus of three geoscientific journals to investigate if there are enough locational references in research articles to apply a geographical search method, on the example of New Zealand. 2) Methods: Based on all available abstracts and all freely available papers of the New Zealand Journal of Geology and Geophysics, the New Zealand Journal of Marine and Freshwater Research, and the Journal of Hydrology, New Zealand, we searched title, abstracts and full texts for place name occurrences that match records from the official Land Information New Zealand (LINZ) gazetteer. We generated ISO standard compliant metadata records for each article including the spatial references and make them available in a public catalogue service. This catalogue can be queried for articles based on authors, titles, keywords, topics as well as by spatial reference. We visualize the results in a map to show which area the research articles are about. 3) Results: We outline the methodology and technical framework for the geo-referencing of the journal articles and the platform design for this knowledge inventory. The results indicate that the use of well-crafted abstracts for journal articles with carefully chosen place names of relevance for the article provides a guideline for geographically referencing unstructured information like journal articles and reports in order to make such resources discoverable through geographical queries. 4) Conclusion: This approach can actively support integrated holistic assessment of water resources and support decision making.</p>", "keywords": ["Geography (General)", "metadata", "0211 other engineering and technologies", "geo-referencing", "geoinformatics", "hydrology", "02 engineering and technology", "15. Life on land", "01 natural sciences", "ISO standards", "6. Clean water", "13. Climate action", "G1-922", "metadata; geo-referencing; CSW; ISO standards; hydrology", "CSW", "0101 mathematics"]}, "links": [{"href": "http://www.mdpi.com/2220-9964/7/4/132/pdf"}, {"href": "https://doi.org/10.3390/ijgi7040132"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/ISPRS%20International%20Journal%20of%20Geo-Information", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/ijgi7040132", "name": "item", "description": "10.3390/ijgi7040132", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/ijgi7040132"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-01-29T00:00:00Z"}}, {"id": "10.5194/essd-9-697-2017", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:21:50Z", "type": "Journal Article", "created": "2017-09-12", "description": "<p>Abstract. Climate, land use, and other anthropogenic and natural drivers have the potential to influence fire dynamics in many regions. To develop a mechanistic understanding of the changing role of these drivers and their impact on atmospheric composition, long-term fire records are needed that fuse information from different satellite and in situ data streams. Here we describe the fourth version of the Global Fire Emissions Database (GFED) and quantify global fire emissions patterns during 1997\uffe2\uff80\uff932016. The modeling system, based on the Carnegie\uffe2\uff80\uff93Ames\uffe2\uff80\uff93Stanford Approach (CASA) biogeochemical model, has several modifications from the previous version and uses higher quality input datasets. Significant upgrades include (1)\uffc2\uffa0new burned area estimates with contributions from small fires, (2)\uffc2\uffa0a revised fuel consumption parameterization optimized using field observations, (3)\uffc2\uffa0modifications that improve the representation of fuel consumption in frequently burning landscapes, and (4)\uffc2\uffa0fire severity estimates that better represent continental differences in burning processes across boreal regions of North America and Eurasia. The new version has a higher spatial resolution (0.25\uffc2\uffb0) and uses a different set of emission factors that separately resolves trace gas and aerosol emissions from temperate and boreal forest ecosystems. Global mean carbon emissions using the burned area dataset with small fires (GFED4s) were 2.2\uffe2\uff80\uffaf\uffe2\uff80\uff89\uffc3\uff97\uffe2\uff80\uff89\uffe2\uff80\uffaf1015\uffc2\uffa0grams of carbon per year (Pg\uffe2\uff80\uffafC\uffe2\uff80\uffafyr\uffe2\uff88\uff921) during 1997\uffe2\uff80\uff932016, with a maximum in 1997 (3.0\uffe2\uff80\uffafPg\uffe2\uff80\uffafC\uffe2\uff80\uffafyr\uffe2\uff88\uff921) and minimum in 2013 (1.8\uffe2\uff80\uffafPg\uffe2\uff80\uffafC\uffe2\uff80\uffafyr\uffe2\uff88\uff921). These estimates were 11\uffe2\uff80\uffaf% higher than our previous estimates (GFED3) during 1997\uffe2\uff80\uff932011, when the two datasets overlapped. This net increase was the result of a substantial increase in burned area (37\uffe2\uff80\uffaf%), mostly due to the inclusion of small fires, and a modest decrease in mean fuel consumption (\uffe2\uff88\uff9219\uffe2\uff80\uffaf%) to better match estimates from field studies, primarily in savannas and grasslands. For trace gas and aerosol emissions, differences between GFED4s and GFED3 were often larger due to the use of revised emission factors. If small fire burned area was excluded (GFED4 without the s for small fires), average emissions were 1.5\uffe2\uff80\uffafPg\uffe2\uff80\uffafC\uffe2\uff80\uffafyr\uffe2\uff88\uff921. The addition of small fires had the largest impact on emissions in temperate North America, Central America, Europe, and temperate Asia. This small fire layer carries substantial uncertainties; improving these estimates will require use of new burned area products derived from high-resolution satellite imagery. Our revised dataset provides an internally consistent set of burned area and emissions that may contribute to a better understanding of multi-decadal changes in fire dynamics and their impact on the Earth system. GFED data are available from http://www.globalfiredata.org.                     </p>", "keywords": ["Atmospheric sciences", "QE1-996.5", "Life on Land", "Geology", "15. Life on land", "01 natural sciences", "7. Clean energy", "Physical Geography and Environmental Geoscience", "Atmospheric Sciences", "Climate Action", "Environmental sciences", "Geochemistry", "13. Climate action", "Geoinformatics", "8. Economic growth", "11. Sustainability", "Earth Sciences", "GE1-350", "Physical geography and environmental geoscience", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://escholarship.org/content/qt2pm0d581/qt2pm0d581.pdf"}, {"href": "https://doi.org/10.5194/essd-9-697-2017"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth%20System%20Science%20Data", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/essd-9-697-2017", "name": "item", "description": "10.5194/essd-9-697-2017", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/essd-9-697-2017"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-09-12T00:00:00Z"}}, {"id": "2994789089", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:26:07Z", "type": "Journal Article", "created": "2019-12-20", "title": "Mathematical Reconstruction of Land Carbon Models From Their Numerical Output: Computing Soil Radiocarbon From C Dynamics", "description": "Abstract<p>Radiocarbon (14C) is a powerful tracer of the global carbon cycle that is commonly used to assess carbon cycling rates in various Earth system reservoirs and as a benchmark to assess model performance. Therefore, it has been recommended that Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 report predicted radiocarbon values for relevant carbon pools. However, a detailed representation of radiocarbon dynamics may be an impractical burden on model developers. Here, we present an alternative approach to compute radiocarbon values from the numerical output of an ESM that does not explicitly represent these dynamics. The approach requires computed 12C stocks and fluxes among all carbon pools for a particular simulation of the model. From this output, a time\uffe2\uff80\uff90dependent linear compartmental system is computed with its respective state\uffe2\uff80\uff90transition matrix. Using transient atmospheric 14C values as inputs, the state\uffe2\uff80\uff90transition matrix is then applied to compute radiocarbon values for each pool, the average value for the entire system, and component fluxes. We demonstrate the approach with ELMv1\uffe2\uff80\uff90ECA, the land component of an ESM model that explicitly represents 12C, and 14C in 7 soil pools and 10 vertical layers. Results from our proposed method are highly accurate (relative error &lt;0.01%) compared with the ELMv1\uffe2\uff80\uff90ECA 12C and 14C predictions, demonstrating the potential to use this approach in CMIP6 and other model simulations that do not explicitly represent 14C.</p", "keywords": ["Atmospheric sciences", "Life on Land", "Bioengineering", "Earth system models", "dynamical systems", "compartmental systems", "01 natural sciences", "Atmospheric Sciences", "13. Climate action", "Geoinformatics", "Earth Sciences", "radiocarbon", "model diagnostics", "carbon cycle models", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2019MS001776"}, {"href": "https://doi.org/2994789089"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Advances%20in%20Modeling%20Earth%20Systems", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2994789089", "name": "item", "description": "2994789089", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2994789089"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-01T00:00:00Z"}}, {"id": "21.11116/0000-0002-8A0B-7", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:25:37Z", "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": "<?xml version='1.0' encoding='UTF-8'?><article><p>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.</p></article>", "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=Geoinformatics&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=Geoinformatics&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=Geoinformatics&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Geoinformatics&offset=8", "hreflang": "en-US"}], "numberMatched": 8, "numberReturned": 8, "distributedFeatures": [], "timeStamp": "2026-07-26T13:09:35.695993Z"}