{"type": "FeatureCollection", "features": [{"id": "10.1007/s13595-016-0547-4", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:15:03Z", "type": "Journal Article", "created": "2016-03-24", "title": "Effects Of Experimental Warming On Soil Respiration And Biomass In Quercus Variabilis Blume And Pinus Densiflora Sieb. Et Zucc. Seedlings", "description": "AbstractKey messageIn the open-field warming experiment using infrared heaters, 3\u00a0\u00b0C warming affected soil respiration more in the deciduousQuercus variabilisBlume plot than in the evergreenPinus densifloraSieb. et Zucc. plot, but did not affect the plant biomass in either species.ContextUnderstanding the species-specific responses of belowground carbon processes to warming is essential for the accurate prediction of forest carbon cycles in ecosystems affected by future climate change.AimsThis study aimed to investigate the effect of experimental warming on soil CO2 efflux, soil-air CO2 concentration, and plant biomass for two taxonomically different temperate tree species.MethodsExperimental warming was conducted in an open-field planted with Q. variabilis and P. densiflora seedlings. Infrared heaters increased the air temperature by 3\u00a0\u00b0C in the warmed plots compared with the air temperature in the control plots over a 2-year period.ResultsThe increase in air and soil temperature stimulated soil CO2 efflux by 29 and 22\u00a0% for the Q. variabilis and P. densiflora plots, respectively. Seasonal variation in the warming effect on soil CO2 efflux was species-specific. Soil CO2 efflux was also positively related to both soil temperature and soil water content. The soil moisture deficit decreased the difference in soil CO2 efflux between the control and warmed plots. Warming did not affect soil CO2 concentration and plant biomass in either species; however, the mean soil CO2 concentration was positively correlated with root and total biomass.ConclusionWarming increased soil CO2 efflux in both Q. variabilis and P. densiflora plots, while the increase showed remarkable seasonal variations and different magnitudes for the two species.", "keywords": ["0106 biological sciences", "soil temperature", "evergreen tree", "soil water", "Red pine", "seedling", "soil respiration", "01 natural sciences", "experimental study", "Pinus resinosa", "Climate change", "Pinus densiflora", "seasonal variation", "concentration (composition)", "Quercus variabilis", "Oriental oak", "carbon dioxide", "Soil respiration", "04 agricultural and veterinary sciences", "15. Life on land", "air temperature", "carbon flux", "[SDV] Life Sciences [q-bio]", "climate change", "13. Climate action", "coniferous tree", "phytomass", "0401 agriculture", " forestry", " and fisheries", "Experimental warming", "soil moisture", "deciduous tree"]}, "links": [{"href": "https://doi.org/10.1007/s13595-016-0547-4"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Annals%20of%20Forest%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s13595-016-0547-4", "name": "item", "description": "10.1007/s13595-016-0547-4", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s13595-016-0547-4"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-03-24T00:00:00Z"}}, {"id": "10.1016/j.fcr.2015.07.007", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:15:39Z", "type": "Journal Article", "created": "2015-07-18", "title": "Rice Straw Incorporation Affects Global Warming Potential Differently In Early Vs. Late Cropping Seasons In Southeastern China", "description": "Paddy fields are a major global anthropogenic source of methane (CH\u2084) and nitrous oxide (N\u2082O), which are very potent greenhouse gases. China has the second largest area under rice cultivation, so developing valid and reliable methods for reducing emissions of greenhouse gases while sustaining crop productivity in paddy fields is of paramount importance. We examined the effects of applying straw, a residual product of rice cultivation containing high amounts of carbon and nutrients, to rice crops during both an early crop season (5 April - 25 July 2012) and a late crop season (1 August - 6 November 2012) on CH\u2084 and N\u2082O emissions in a subtropical paddy field in southeastern China. CH\u2084 fluxes had two seasonal peaks, on 5 May and 28 June, in the early crop but only one peak, on 13 August, in the late crop, which could be attributed to the lower temperatures after the final tillering stage in the late crop. Straw application significantly increased mean CH\u2084 cumulative production (g m\u05be\u00b2) relative to the control in the late crop (37.3 vs. 8.34 mg m\u207b\u00b2 P < 0.05) but not in the early crop (0.83 vs. 01.13 mg m\u207b\u00b2 P > 0.05). The application of straw significantly increased N\u2082O cumulative production relative to the control in the late crop (75.9 vs. 43.4 \u03bcg m\u207b\u00b2 h\u207b\u00b9) but decreased N\u2082O cumulative production by over 43% in the early crop (15.60 vs. 27.27 \u03bcg m\u207b\u00b2 h\u207b\u00b9) (P < 0.05). Straw application increased rice yield by 9.63% and 12.58% in early and late crop respectively. Straw incorporation decreased global warming potential in the early season, but increased it in the late season. Thus, despite straw application enhances emissions of greenhouse gases in some situations, its application in the adequate season (here early crop) may be an effective soil amendment that can increase soil fertility without enhancing or even mitigating emissions of greenhouse gases and thus climate change.", "keywords": ["2. Zero hunger", "CH\u2084 flux", "Straw application", "13. Climate action", "Seasonal variation", "8. Economic growth", "N\u2082O flux", "0401 agriculture", " forestry", " and fisheries", "Rice paddy", "04 agricultural and veterinary sciences", "15. Life on land", "12. Responsible consumption"]}, "links": [{"href": "https://doi.org/10.1016/j.fcr.2015.07.007"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Field%20Crops%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.fcr.2015.07.007", "name": "item", "description": "10.1016/j.fcr.2015.07.007", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.fcr.2015.07.007"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-09-01T00:00:00Z"}}, {"id": "10.17221/446/2013-pse", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:18:34Z", "type": "Journal Article", "created": "2018-02-10", "title": "Soil Microbial Metabolism And Invertase Activity Under Crop Rotation And No-Tillage In North China", "description": "Soil samples were collected at both jointing and maturing stages of maize and wheat to compare the effects of 4-year no-tillage (NT) and conventional tillage (CT) on seasonal variations of microbial biomass carbon (C), metabolic quotient, and invertase activity in a sandy loam soil in North China. Soil invertase activity significantly increased (P &lt; 0.05) from summer to spring of the next year and then significantly decreased (P &lt; 0.05) from spring to summer. With a delay of about 3 months, soil microbial biomass C and basal respiration altered in a similar pattern, while microbial metabolic quotient changed on the contrary. Compared with CT, the NT practice significantly increased (P &lt; 0.05) soil organic C content, and tended to result in higher soil microbial biomass C and invertase activity, as well as lower soil microbial metabolic quotient, especially at the jointing stage of maize. Our results indicated that NT might play an important role in the improvement of soil microbial efficiency, especially at the maize seedling season.", "keywords": ["soil organic carbon", "2. Zero hunger", "seasonal variation", "microbial biomass", "basal respiration", "Plant culture", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "metabolic quotient", "SB1-1110"]}, "links": [{"href": "https://doi.org/10.17221/446/2013-pse"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Plant%2C%20Soil%20and%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.17221/446/2013-pse", "name": "item", "description": "10.17221/446/2013-pse", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.17221/446/2013-pse"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-11-30T00:00:00Z"}}, {"id": "10.25338/B8P92J", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:19:09Z", "type": "Dataset", "created": "2023-07-13", "title": "Spatio-temporal dynamics of insect communities in constructed and natural tidal marshes with distinct landscape positions", "description": "unspecified| | | | | | | | |  ------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------- | ------------------------------------------------- | ------------------------------------------------------------------------------------------------------------- | ------- | ------------------------------------------------------ | | This readme file was generated on 2023-07-05 by Emily Fromenthal | | | | | | | | | | | | | | | | GENERAL INFORMATION | | | | | | | | | | | | | | | | Title of Dataset: Beyond the Marsh: Tidal Marsh Landscape Position Influences Insect Community Structure | | | | | | | | | | | | | | | | Author/Principal Investigator Information | | | | | | | | Name: Emily Fromenthal | | | | | | | | Institution: University of Alabama | | | | | | | | Email:[efromenthal@crimson.ua.edu](mailto:efromenthal@crimson.ua.edu) | | | | | | | | Author/Associate or Co-investigator Information | | | | | | | | Name: Shelby Rinehart | | | | | | | | ORCID:0000-0001-9820-1350 | | | | | | | | Institution: University of Alabama &amp; Drexel University | | | | | | | | Email: [srinehart@ucdavis.edu](mailto:srinehart@ucdavis.edu) OR [sarinehart@ua.edu](mailto:sarinehart@ua.edu) | | | | | | | | Author/Associate or Co-investigator Information | | | | | | | | Name: Jacob M Dybiec | | | | | | | | Institution: University of Alabama | | | | | | | | Email: [jmdybiec@crimson.ua.edu](mailto:jmdybiec@crimson.ua.edu) | | | | | | | | Author/Associate or Co-investigator Information | | | | | | | | Name: Julia A Cherry | | | | | | | | Institution: University of Alabama | | | | | | | | Email: [cherr002@ua.edu](mailto:cherr002@ua.edu) | | | | | | | | | | | | | | | | Date of data collection: 2021-04 through 2021-10 | | | | | | | | | | | | | | | | Geographic location of data collection: West Fowl River | Coden | Alabama | USA | | | | | CON-1: 30.368 N | -88.152 W | | | | | | | CON-2: 30.367 N | -88.151 W | | | | | | | NAT: 30.368 N | -88.160 W | | | | | | | | | | | | | | | Information about funding sources that supported the collection of the data: | | | | | | | | The Society of Wetland Scientists | | | | | | | | University of Alabama | Department of Biological Sciences | | | | | | | | | | | | | | | | | | | | | | | SHARING/ACCESS INFORMATION | | | | | | | | | | | | | | | | Licenses/restrictions placed on the data: None | | | | | | | | | | | | | | | | Links to publications that cite or use the data: Please see the publication associated with these data in XXXXXXXX (doi: XXXXXX) | | | | | | | | | | | | | | | | Recommended citation for this dataset: | | | | | | | | | | | | | | | | Fromenthal | E | S. Rinehart | J.M. Dybiec | and J.A Cherry. Beyond the Marsh: Tidal Marsh Landscape Position Influences Insect Community Structure. Dryad | Dataset | [https://doi.org/XXXXXXXXX](https://doi.org/XXXXXXXXX) | | | | | | | | | | | | | | | | | | DATA &amp; FILE OVERVIEW | | | | | | | | | | | | | | | | File List: | | | | | | | | Taxa- count data for each insect taxon observed at study sites | | | | | | | | Biodiversity- total individuals | taxa richness | and Shannon-Weiner diversity (H') indeces for each quadrat | | | | | | FloralCounts- total count | average count | standard deviation | and variance of Juncus roemerianus inflorescences | | | | | Herbivory- percent area of herbivory damage on J. roemerianus shoots collected from each quadrat in each marsh. | | | | | | | | | | | | | | | | METHODOLOGICAL INFORMATION | | | | | | | | | | | | | | | | Description of methods used for collection/generation of data: See the publication associated with these data in XXXXXXXX (doi: XXXXXX) for details on methods. | | | | | | | | | | | | | | | | Methods for processing the data: See the publication associated with these data in XXXXXXXX (doi: XXXXXX) for details on methods. | | | | | | | | | | | | | | | | Instrument- or software-specific information needed to interpret the data: Microsoft Excel | | | | | | | | | | | | | | | | Environmental/experimental conditions: CON-1 and CON-2 are two constructed tidal marshes hydrologically connected via canal to the West Fowl River in Mobile County | Alabama. NAT is a reference marsh directly connected to the West Fowl River. All marshes are located in a sub-tropical estuary along the northern Gulf fo Mexico. | | | | | | | | | | | | | | | Describe any quality-assurance procedures performed on the data: | | | | | | | | General QA/QC done by all co-authors. | | | | | | | | | | | | | | | | People involved with sample collection | processing | analysis | and/or submission: | | | | | Emily Fromenthal was involved in sample collection | processing | analysis | and submission. | | | | | Shelby Rinehart was involved in sample collection | analysis | and submission. | | | | | | Jacob M Dybiec was involved in sample collection and analysis. | | | | | | | | Julia A Cherry was involved in analysis and submission. | | | | | | | | | | | | | | | | DATA-SPECIFIC INFORMATION FOR: Taxa | | | | | | | | Number of variables: 86 | | | | | | | | Number of cases/rows: 146 | | | | | | | | Missing data codes: No data missing. | | | | | | | | Specialized formats or other abbreviations used: N/A. | | | | | | | | | | | | | | | | Variable List: | | | | | | | | Marsh-indicates the marsh (CON1 | CON2 | or NAT) that data was collected from | | | | | | Month- month that data was collected | | | | | | | | Method- method used to collect data (Pan | Net | Light | FC) | | | | | Quadrat- indicates the replicate quadrat (i.e. | CON1-1 | CON1-2 | etc.) that data was collected from | | | | | Variables E-CH (5-86) represent counts of indiviual taxa identified to the lowest possible taxa (family | in most cases). | | | | | | | | | | | | | | | DATA-SPECIFIC INFORMATION FOR: Biodiversity | | | | | | | | Number of variables: 5 | | | | | | | | Number of cases/rows: 12 | | | | | | | | | | | | | | | | Missing data codes: No missing data. | | | | | | | | Specialized formats or other abbreviations used: | | | | | | | | H'- Shannon-Wiener diversity index; calculated using the formula H^'= - _(i=1)^Rp _i ln p _i | | | | | | | | | | | | | | | | Variable List: | | | | | | | | Marsh- indicates the marsh (CON1 | CON2 | or NAT) that data was collected from | | | | | | Quadrat- indicates the replicate quadrat (i.e. | CON1-1 | CON1-2 | etc.) that data was collected from | | | | | Total Individuals- total count of individual insects per quadrat across all sampling strategies. | | | | | | | | Taxa Richness- number of unique taxa identified per quadrat across all sampling stratagies. | | | | | | | | H'- Shannon-Wiener diversity calculated for each quadrat across all sampling stratagies. | | | | | | | | | | | | | | | | DATA-SPECIFIC INFORMATION FOR: FloralCounts | | | | | | | | Number of variables: 4 | | | | | | | | Number of cases/rows: 37 | | | | | | | | | | | | | | | | Missing data codes: No missing data. | | | | | | | | Specialized formats or other abbreviations used: None | | | | | | | | | | | | | | | | Variable List: | | | | | | | | Marsh- indicates the marsh (CON1 | CON2 | or NAT) that data was collected from | | | | | | Quadrat- indicates the replicate quadrat (i.e. | CON1-1 | CON1-2 | etc.) that data was collected from | | | | | Replicate- inducates which sub-sample from each quadrat is associated with each observation | | | | | | | | Floral count- the number of flowering J. roemerianus shoots in each observation. | | | | | | | | | | | | | | | | DATA-SPECIFIC INFORMATION FOR: Herbivory | | | | | | | | Number of variables: 7 | | | | | | | | Number of cases/rows: 12 | | | | | | | | | | | | | | | | Missing data codes: No missing data. | | | | | | | | Specialized formats or other abbreviations used: N/A | | | | | | | | | | | | | | | | Variable List: | | | | | | | | Quadrat- indicates the replicate quadrat (i.e. | CON1-1 | CON1-2 | etc.) that data was collected from. | | | | | Marsh- notes which tidal wetland site the sample was collected from. | | | | | | | | Herbivory (sq inch)- area of insect herbivory damage/scars in square inches | | | | | | | | Herbivory (cm2)- area of insect herbivory damage/scars per cm2 | | | | | | | | Total area (sq inch)- total size (area) of J. roemerianus shoots in square inches | | | | | | | | Total area (cm2)- total size (area) of of J. roemerianus shoots in cm2. | | | | | | | | % Herbivory- the percent area of J. roemerianus shoots with insect herbivory damage | | | | | | |", "keywords": ["coastal wetlands", "Gulf of Mexico", "Restoration ecology", "insect ecology", "Seasonal variations", "Spatial and landscape ecology", "FOS: Natural sciences", "Species diversity"], "contacts": [{"organization": "Rinehart, Shelby, Fromenthal, Emily, Dybiec, Jacob, Cherry, Julia,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.25338/B8P92J"}, {"rel": "self", "type": "application/geo+json", "title": "10.25338/B8P92J", "name": "item", "description": "10.25338/B8P92J", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.25338/B8P92J"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-04-26T00:00:00Z"}}, {"id": "10.3390/rs13142755", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:19:30Z", "type": "Journal Article", "created": "2021-07-14", "title": "Aboveground Biomass Mapping of Crops Supported by Improved CASA Model and Sentinel-2 Multispectral Imagery", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The net primary productivity (NPP) and aboveground biomass mapping of crops based on remote sensing technology are not only conducive to understanding the growth and development of crops but can also be used to monitor timely agricultural information, thereby providing effective decision making for agricultural production management. To solve the saturation problem of the NDVI in the aboveground biomass mapping of crops, the original CASA model was improved using narrow-band red-edge information, which is sensitive to vegetation chlorophyll variation, and the fraction of photosynthetically active radiation (FPAR), NPP, and aboveground biomass of winter wheat and maize were mapped in the main growing seasons. Moreover, in this study, we deeply analyzed the seasonal change trends of crops\u2019 biophysical parameters in terms of the NDVI, FPAR, actual light use efficiency (LUE), and their influence on aboveground biomass. Finally, to analyze the uncertainty of the aboveground biomass mapping of crops, we further discussed the inversion differences of FPAR with different vegetation indices. The results demonstrated that the inversion accuracies of the FPAR of the red-edge normalized vegetation index (NDVIred-edge) and red-edge simple ratio vegetation index (SRred-edge) were higher than those of the original CASA model. Compared with the reference data, the accuracy of aboveground biomass estimated by the improved CASA model was 0.73 and 0.70, respectively, which was 0.21 and 0.13 higher than that of the original CASA model. In addition, the analysis of the FPAR inversions of different vegetation indices showed that the inversion accuracies of the red-edge vegetation indices NDVIred-edge and SRred-edge were higher than those of the other vegetation indices, which confirmed that the vegetation indices involving red-edge information can more effectively retrieve FPAR and aboveground biomass of crops.</p></article>", "keywords": ["2. Zero hunger", "NPP", "seasonal variation", "improved CASA", "biomass", "Science", "Q", "0401 agriculture", " forestry", " and fisheries", "improved CASA; red-edge band; NPP; biomass; seasonal variation", "04 agricultural and veterinary sciences", "15. Life on land", "red-edge band", "12. Responsible consumption"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/13/14/2755/pdf"}, {"href": "https://doi.org/10.3390/rs13142755"}, {"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/rs13142755", "name": "item", "description": "10.3390/rs13142755", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/rs13142755"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-13T00:00:00Z"}}, {"id": "10.5194/bg-22-601-2025", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:19:58Z", "type": "Journal Article", "created": "2025-01-31", "title": "Contrasting seasonal patterns in particle aggregation and dissolved organic matter transformation in a sub-Arctic fjord", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Particulate (POM) and dissolved (DOM) organic matter in the ocean are important components of the Earth's biogeochemical cycle. The two are in a constant state of dynamic change as a result of physical and biochemical processes; however, they are mostly treated as two distinct entities, separated operationally by a filter. We studied the seasonal transition of DOM and POM pools and their drivers in a sub-Arctic fjord by means of monthly environmental sampling and by performing experiments at selected time points. For the experiments, surface water (5\u2009m) was either pre-filtered through a GF/F filter (0.7\u2009\u00b5m) or left unfiltered, followed by 36\u2009h incubations. Before and after incubation, samples were collected for dissolved and particulate organic carbon concentrations (DOC, POC), extracellular polymeric substances (EPSs), microbial community (flow cytometry), and molecular composition of DOM (high-performance liquid chromatography coupled to high-resolution mass spectrometry \u2013 HPLC-HRMS). During the biologically productive period, when environmental POC concentrations were high (April, June, September), the filtered water showed an increase in POC concentrations. While POC concentrations increased in September, DOM lability decreased based on changes in the average hydrogen saturation and aromaticity of DOM molecules. In contrast, during the winter period (December and February), when environmental POC concentrations were low, lower concentrations of POC were measured at the end of the experiments compared to at the start. The change in POC concentrations was significantly different between the biologically productive period and the winter period (t test; p&lt;0.05). Simultaneously, the DOM pool became more labile during the incubation period, as indicated by changes in the average hydrogen saturation, aromaticity, and oxygen saturation, with implications for carbon cycling. The change in POC was not directly associated with an antagonistic change in DOC concentrations, highlighting the complexity of organic matter transformations, making the dynamics between POC and DOC difficult to quantify. However, in both periods, bacterial activity and EPS concentrations increased throughout the incubations, showing that bacterial degradation and physical DOM aggregation drive the transformations of POM and DOM in concert but at varying degrees under different environmental conditions.                     </p></article>", "keywords": ["particulate organic carbon", "seasonal variation", "QE1-996.5", "Ecology", "saturation", "aggregation", "surface water", "fjord", "Geology", "biogeochemical cycle", "Milj\u00f6vetenskap", "dissolved organic carbon", "microbial activity", "environmental conditions", "Life", "QH501-531", "microbial community", "Environmental Sciences", "QH540-549.5"], "contacts": [{"organization": "Maria G. Digernes, Yasemin V. Bodur, Mart\u00ed Amargant-Arum\u00ed, Oliver M\u00fcller, Jeffrey A. Hawkes, Stephen G. Kohler, Ulrike Dietrich, Marit Reigstad, Maria L. Paulsen,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5194/bg-22-601-2025"}, {"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-22-601-2025", "name": "item", "description": "10.5194/bg-22-601-2025", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/bg-22-601-2025"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-01-31T00:00:00Z"}}, {"id": "11250/3212345", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:22:16Z", "type": "Journal Article", "created": "2025-01-31", "title": "Contrasting seasonal patterns in particle aggregation and dissolved organic matter transformation in a sub-Arctic fjord", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Particulate (POM) and dissolved (DOM) organic matter in the ocean are important components of the Earth's biogeochemical cycle. The two are in a constant state of dynamic change as a result of physical and biochemical processes; however, they are mostly treated as two distinct entities, separated operationally by a filter. We studied the seasonal transition of DOM and POM pools and their drivers in a sub-Arctic fjord by means of monthly environmental sampling and by performing experiments at selected time points. For the experiments, surface water (5\u2009m) was either pre-filtered through a GF/F filter (0.7\u2009\u00b5m) or left unfiltered, followed by 36\u2009h incubations. Before and after incubation, samples were collected for dissolved and particulate organic carbon concentrations (DOC, POC), extracellular polymeric substances (EPSs), microbial community (flow cytometry), and molecular composition of DOM (high-performance liquid chromatography coupled to high-resolution mass spectrometry \u2013 HPLC-HRMS). During the biologically productive period, when environmental POC concentrations were high (April, June, September), the filtered water showed an increase in POC concentrations. While POC concentrations increased in September, DOM lability decreased based on changes in the average hydrogen saturation and aromaticity of DOM molecules. In contrast, during the winter period (December and February), when environmental POC concentrations were low, lower concentrations of POC were measured at the end of the experiments compared to at the start. The change in POC concentrations was significantly different between the biologically productive period and the winter period (t test; p&lt;0.05). Simultaneously, the DOM pool became more labile during the incubation period, as indicated by changes in the average hydrogen saturation, aromaticity, and oxygen saturation, with implications for carbon cycling. The change in POC was not directly associated with an antagonistic change in DOC concentrations, highlighting the complexity of organic matter transformations, making the dynamics between POC and DOC difficult to quantify. However, in both periods, bacterial activity and EPS concentrations increased throughout the incubations, showing that bacterial degradation and physical DOM aggregation drive the transformations of POM and DOM in concert but at varying degrees under different environmental conditions.</p></article>", "keywords": ["particulate organic carbon", "seasonal variation", "QE1-996.5", "Ecology", "saturation", "aggregation", "surface water", "fjord", "Geology", "biogeochemical cycle", "Milj\u00f6vetenskap", "dissolved organic carbon", "microbial activity", "environmental conditions", "Life", "QH501-531", "microbial community", "Environmental Sciences", "QH540-549.5"]}, "links": [{"href": "https://doi.org/11250/3212345"}, {"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": "11250/3212345", "name": "item", "description": "11250/3212345", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11250/3212345"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-01-31T00:00:00Z"}}, {"id": "10.5281/zenodo.8091249", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:21:25Z", "type": "Journal Article", "created": "2021-07-13", "title": "Aboveground Biomass Mapping of Crops Supported by Improved CASA Model and Sentinel-2 Multispectral Imagery", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The net primary productivity (NPP) and aboveground biomass mapping of crops based on remote sensing technology are not only conducive to understanding the growth and development of crops but can also be used to monitor timely agricultural information, thereby providing effective decision making for agricultural production management. To solve the saturation problem of the NDVI in the aboveground biomass mapping of crops, the original CASA model was improved using narrow-band red-edge information, which is sensitive to vegetation chlorophyll variation, and the fraction of photosynthetically active radiation (FPAR), NPP, and aboveground biomass of winter wheat and maize were mapped in the main growing seasons. Moreover, in this study, we deeply analyzed the seasonal change trends of crops\u2019 biophysical parameters in terms of the NDVI, FPAR, actual light use efficiency (LUE), and their influence on aboveground biomass. Finally, to analyze the uncertainty of the aboveground biomass mapping of crops, we further discussed the inversion differences of FPAR with different vegetation indices. The results demonstrated that the inversion accuracies of the FPAR of the red-edge normalized vegetation index (NDVIred-edge) and red-edge simple ratio vegetation index (SRred-edge) were higher than those of the original CASA model. Compared with the reference data, the accuracy of aboveground biomass estimated by the improved CASA model was 0.73 and 0.70, respectively, which was 0.21 and 0.13 higher than that of the original CASA model. In addition, the analysis of the FPAR inversions of different vegetation indices showed that the inversion accuracies of the red-edge vegetation indices NDVIred-edge and SRred-edge were higher than those of the other vegetation indices, which confirmed that the vegetation indices involving red-edge information can more effectively retrieve FPAR and aboveground biomass of crops.</p></article>", "keywords": ["2. Zero hunger", "NPP", "seasonal variation", "improved CASA", "biomass", "Science", "Q", "0401 agriculture", " forestry", " and fisheries", "improved CASA; red-edge band; NPP; biomass; seasonal variation", "04 agricultural and veterinary sciences", "15. Life on land", "red-edge band", "12. Responsible consumption"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/13/14/2755/pdf"}, {"href": "https://doi.org/10.5281/zenodo.8091249"}, {"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": "10.5281/zenodo.8091249", "name": "item", "description": "10.5281/zenodo.8091249", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.8091249"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-13T00:00:00Z"}}, {"id": "3180978627", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:23:12Z", "type": "Journal Article", "created": "2021-07-14", "title": "Aboveground Biomass Mapping of Crops Supported by Improved CASA Model and Sentinel-2 Multispectral Imagery", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The net primary productivity (NPP) and aboveground biomass mapping of crops based on remote sensing technology are not only conducive to understanding the growth and development of crops but can also be used to monitor timely agricultural information, thereby providing effective decision making for agricultural production management. To solve the saturation problem of the NDVI in the aboveground biomass mapping of crops, the original CASA model was improved using narrow-band red-edge information, which is sensitive to vegetation chlorophyll variation, and the fraction of photosynthetically active radiation (FPAR), NPP, and aboveground biomass of winter wheat and maize were mapped in the main growing seasons. Moreover, in this study, we deeply analyzed the seasonal change trends of crops\u2019 biophysical parameters in terms of the NDVI, FPAR, actual light use efficiency (LUE), and their influence on aboveground biomass. Finally, to analyze the uncertainty of the aboveground biomass mapping of crops, we further discussed the inversion differences of FPAR with different vegetation indices. The results demonstrated that the inversion accuracies of the FPAR of the red-edge normalized vegetation index (NDVIred-edge) and red-edge simple ratio vegetation index (SRred-edge) were higher than those of the original CASA model. Compared with the reference data, the accuracy of aboveground biomass estimated by the improved CASA model was 0.73 and 0.70, respectively, which was 0.21 and 0.13 higher than that of the original CASA model. In addition, the analysis of the FPAR inversions of different vegetation indices showed that the inversion accuracies of the red-edge vegetation indices NDVIred-edge and SRred-edge were higher than those of the other vegetation indices, which confirmed that the vegetation indices involving red-edge information can more effectively retrieve FPAR and aboveground biomass of crops.</p></article>", "keywords": ["2. Zero hunger", "NPP", "seasonal variation", "improved CASA", "biomass", "Science", "Q", "0401 agriculture", " forestry", " and fisheries", "improved CASA; red-edge band; NPP; biomass; seasonal variation", "04 agricultural and veterinary sciences", "15. Life on land", "red-edge band", "12. Responsible consumption"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/13/14/2755/pdf"}, {"href": "https://doi.org/3180978627"}, {"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": "3180978627", "name": "item", "description": "3180978627", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3180978627"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-13T00:00:00Z"}}, {"id": "33aa2643-5018-4e31-8b88-c2eb0a7a56f8", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[5.87, 47.27], [5.87, 55.06], [15.03, 55.06], [15.03, 47.27], [5.87, 47.27]]]}, "properties": {"themes": [{"concepts": [{"id": "farming"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Soil"}, {"id": "agricultural practices"}, {"id": "crop rotation"}, {"id": "environmental monitoring"}, {"id": "multiple regression analysis"}, {"id": "plant developmental stages"}, {"id": "phenology"}], "scheme": "AGROVOC Multilingual agricultural thesaurus"}, {"concepts": [{"id": "opendata"}], "scheme": "Individual"}, {"concepts": [{"id": "Boden"}, {"id": "agricultural management"}, {"id": "crop rotation"}, {"id": "environmental monitoring"}, {"id": "interpolation"}, {"id": "seasonal variation"}, {"id": "biological development"}], "scheme": "GEMET - Concepts, version 2.4"}, {"concepts": [{"id": "elevation"}, {"id": "land use"}, {"id": "meteorological geographical features"}, {"id": "geographical grid systems"}], "scheme": "INSPIRE"}, {"concepts": [{"id": "Germany"}], "scheme": "individual"}], "rights": "Restrictions applied to assure the protection of privacy or intellectual property, and any special restrictions or limitations or warnings on using the resource or metadata. Reports, articles, papers, scientific and non - scientific works of any form, including tables, maps, or any other kind of output, in printed or electronic form, based in whole or in part on the data supplied, must contain an acknowledgement of the form: \"Data reused from the BonaRes Repository www.bonares.de. This data were created as part of the JKI's research activities.\" Although every care has been taken in preparing and testing the data, the JKI and the BonaRes Data Centre cannot guarantee that the data are correct; neither does the JKI and the BonaRes Repository accept any liability whatsoever for any error, missing data or omission in the data, or for any loss or damage arising from its use. The Other and BonaRes Repository will not be responsible for any direct or indirect use which might be made of the data.", "updated": "2023-12-13", "type": "Dataset", "created": "2022-09-30", "language": "eng", "title": "Germany-wide time series of interpolated phenological observations for main crop types between 1993 and 2021", "description": "<p>The data set documents a Germany-wide and spatio-temporally consistent 1 \u00d7 1 km\u00b2 analysis-ready time series (ARD-TS) of interpolated DOYs (days of the year) covering 56 beginning phenological development stages (phases) of 9 main crop types for the period between 1993 and 2021. The derivation is based on Germany-wide observations of the German Weather Service (DWD), which were statistically filtered and interpolated. </p> \n<p>The German Weather Service operates a phenological observation network. About 1200 observers monitor 160 phenological phases of wild and cultivated plants. The PHASE model was developed to interpolate the phenological observations for the entire territory of Germany (Gerstmann et al. (2016) Rel.Identifer TAB 8). The model combines the concept of growing degree days (GDD) with a geostatistical interpolation procedure. The PHASE model was applied to create a Germany-wide and spatio-temporally consistent 1 \u00d7 1 km\u00b2 analysis-ready time series (ARD-TS) of interpolated DOYs (days of the year) covering 56 beginning phenological development stages (phases) of 9 main crop types for the period between 1993 and 2021. The dataset includes the following information: </p>\n<p>\n\u2022\tGermany-wide interpolated temperature data from the German Weather Service (DWD), <br/> \n\u2022\traster datasets of interpolated crop-specific and Germany-wide incipient phenological development stages for the period between 1993 and 2020. The value in each pixel of these rasters represents the Day Of the Year (DOY) of the respective beginning phenological plant development stage, \n<br/>\n\u2022\taccuracy metrics (RMSE, MSE, MAE, and R\u00b2) for each Germany-wide interpolation result. </p>\n<p>The code of the phase model is documented in a software repository (Rel.Identifer TAB 9 and 10). The temporally static model input data are also stored there. </p>\n<p><b>Research question </b> <br/> \nThe dataset allows the spatio-temporal definition of phenological windows for any available year and user-defined region (M\u00f6ller et al. (2020) Rel.Identifer TAB 1). Such information is important for various agricultural issues such as the derivation of weather or biodiversity indices, crop classification, soil erosion or crop yield modeling (Bucheli et al. (2022) Rel.Identifer TAB 5; Gerstmann et al. (2018) ; Rel.Identifer TAB 3; M\u00f6ller et al. (2017, 2018) ; Rel.Identifer TAB 2 and 4; Riedsel et al. (2022) ; Rel.Identifer TAB 6).  </p> \nAll relvant papers are listed under RelatedIdentifier. <br/>\nA form for creating an individual WCS can be found here:<br/>\n<a href=\"https://sf.julius-kuehn.de/openapi/phase/\">https://sf.julius-kuehn.de/openapi/phase/</a>", "formats": [{"name": "CSV"}], "keywords": ["Soil", "agricultural practices", "crop rotation", "environmental monitoring", "multiple regression analysis", "plant developmental stages", "phenology", "opendata", "Boden", "agricultural management", "crop rotation", "environmental monitoring", "interpolation", "seasonal variation", "biological development", "elevation", "land use", "meteorological geographical features", "geographical grid systems", "Germany"], "contacts": [{"name": "Markus M\u00f6ller", "organization": "Julius K\u00fchn Institute (JKI) \u2013 Federal Research Centre for Cultivated Plants, Institute for Crop and Soil Science, Bundesallee 69, D-38116 Braunschweig, Germany", "position": null, "roles": ["author"], "phones": [{"value": null}], "emails": [{"value": "markus.moeller@julius-kuehn.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": "https://orcid.org", "protocol": null, "protocol_url": "", "name": "0000-0002-1918-7747", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Markus M\u00f6ller", "organization": "Julius K\u00fchn Institute (JKI) \u2013 Federal Research Centre for Cultivated Plants, Institute for Crop and Soil Science, Bundesallee 58, 38116 Braunschweig, Germany", "position": null, "roles": ["projectLeader"], "phones": [{"value": null}], "emails": [{"value": "markus.moeller@julius-kuehn.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": "https://orcid.org", "protocol": null, "protocol_url": "", "name": "0000-0002-1918-7747", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Leibniz Centre for Agricultural Landscape Research", "organization": "ZALF", "position": "Research Platform 'Data Analysis & Simulation' - Workgroup Research Data Management", "roles": ["publisher"], "phones": [{"value": "+49 33432 82 300"}], "emails": [{"value": "dataservice@zalf.de"}], "addresses": [{"deliveryPoint": ["Eberswalder Strasse 84"], "city": "M\u00fcncheberg", "administrativeArea": "Brandenburg", "postalCode": "15374", "country": "Germany"}], "links": [{"href": null}]}, {"name": "Henning, Gerstmann", "organization": "Federal Agency for Nature Conservation (BfN), Alte Messe 6, 04103 Leipzig", "position": null, "roles": ["researcher"], "phones": [{"value": null}], "emails": [{"value": "henning.gerstmann@bfn.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"name": "Peter, Horney", "organization": "Julius K\u00fchn Institute (JKI) \u2013 Federal Research Centre for Cultivated Plants, Institute for for Strategies and Technology Assessment, Stahnsdorfer Damm 81, 14532 Kleinmachnow, Germany", "position": null, "roles": ["dataCurator"], "phones": [{"value": null}], "emails": [{"value": "peter.horney@julius-kuehn.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"organization": "Julius K\u00fchn Institute (JKI) \u2013 Federal Research Centre for Cultivated Plants, Institute for Crop and Soil Science, Bundesallee 69, D-38116 Braunschweig, Germany", "roles": ["contributor"]}]}, "links": [{"href": "https://maps.bonares.de/mapapps/resources/apps/bonares/index.html?lang=en&mid=33aa2643-5018-4e31-8b88-c2eb0a7a56f8", "rel": "information"}, {"href": "https://metadata.bonares.de:443/smartEditor/preview/DOYs_interpolated.png", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"rel": "self", "type": "application/geo+json", "title": "33aa2643-5018-4e31-8b88-c2eb0a7a56f8", "name": "item", "description": "33aa2643-5018-4e31-8b88-c2eb0a7a56f8", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/33aa2643-5018-4e31-8b88-c2eb0a7a56f8"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-12-13T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=seasonal+variation&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=seasonal+variation&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=seasonal+variation&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=seasonal+variation&offset=10", "hreflang": "en-US"}], "numberMatched": 10, "numberReturned": 10, "distributedFeatures": [], "timeStamp": "2026-09-22T06:58:50.085330Z"}