{"type": "FeatureCollection", "features": [{"id": "10.2134/jeq2015.04.0186", "type": "Feature", "geometry": null, "properties": {"license": "Closed Access", "updated": "2026-07-27T16:20:59Z", "type": "Journal Article", "created": "2016-02-12", "description": "Aerial extent of wetland ecosystems has decreased dramatically since precolonial times due to the conversion of these areas for human use. Wetlands provide various ecosystem services, and conservation efforts are being made to restore wetlands and their functions, including soil carbon storage. This Mid-Atlantic Regional USDA Wetland Conservation Effects Assessment Project study was conducted to evaluate the effects and effectiveness of wetland conservation practices along the Mid-Atlantic Coastal Plain. This study examined 48 wetland sites in Delaware, Maryland, Virginia, and North Carolina under natural, prior converted cropland, and 5- to 10-yr post wetland restoration states. The North Carolina sites mainly contained soils dominated by organic soil materials and therefore were analyzed separately from the rest of the sites, which primarily contained mineral soils. Soil samples were collected using the bulk density core method by horizon to a depth of 1 m and were analyzed for percent carbon. The natural wetlands were found to have significantly greater carbon stocks (21.5 \u00b1 5.2 kg C m) than prior converted croplands (7.95 \u00b1 1.93 kg C m; < 0.01) and restored wetlands (4.82 \u00b1 1.13 kg C m; < 0.001). The restored and prior converted sites did not differ significantly, possibly the result of the methods used to restore the wetlands, and the relatively young age of the restored sites. Wetlands were either restored by plugging drainage structures, with minimal surface disturbance, or by scraping the surface (i.e., excavation) to increase hydroperiod. Sites restored with the scraping technique had significantly lower carbon stocks (2.70 \u00b1 0.38 kg C m) than those restored by passive techniques (6.06 \u00b1 1.50 kg C m; = 0.09). Therefore, techniques that involve excavation and scraping to restore hydrology appear to negatively affect C storage.", "keywords": ["Soil", "Wetlands", "North Carolina", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "Delaware", "Carbon", "6. Clean water"]}, "links": [{"href": "https://doi.org/10.2134/jeq2015.04.0186"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Environmental%20Quality", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.2134/jeq2015.04.0186", "name": "item", "description": "10.2134/jeq2015.04.0186", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2134/jeq2015.04.0186"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-03-01T00:00:00Z"}}, {"id": "10.2166/wst.2022.179", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:21:15Z", "type": "Journal Article", "created": "2022-06-01", "title": "Comparison of simple models for total nitrogen removal from agricultural runoff in FWS wetlands", "description": "Abstract                <p>Free water surface (FWS) wetlands can be used to treat agricultural runoff, thereby reducing diffuse pollution. However, as these are highly dynamic systems, their design is still challenging. Complex models tend to require detailed information for calibration, which can only be obtained when the wetland is constructed. Hence simplified models are widely used for FWS wetlands design. The limitations of these models in full-scale FWS wetlands is that these systems often cope with stochastic events with different input concentrations. In our study, we compared different simple transport and degradation models for total nitrogen under steady- and unsteady-state conditions using information collected from a tracer experiment and data from two precipitation events from a full-scale FWS wetland. The tanks-in-series model proved to be robust for simulating solute transport, and the first-order degradation model with non-zero background concentration performed best for total nitrogen concentrations. However, the optimal background concentration changed from event to event. Thus, to use the model as a design tool, it is advisable to include an upper and lower background concentration to determine a range of wetland performance under different events. Models under steady- and unsteady-state conditions with simulated data showed good performance, demonstrating their potential for wetland design.</p>", "keywords": ["agricultural runoff", " design models", " free water surface wetlands", " modelling", " treatment wetlands", "Nitrogen", "treatment wetlands", "0207 environmental engineering", "Water", "02 engineering and technology", "15. Life on land", "Environmental technology. Sanitary engineering", "01 natural sciences", "agricultural runoff", "6. Clean water", "Water Purification", "modelling", "13. Climate action", "Wetlands", "Denitrification", "design models", "free water surface wetlands", "TD1-1066", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://cris.unibo.it/bitstream/11585/889925/1/wst085113301.pdf"}, {"href": "https://iwaponline.com/wst/article-pdf/85/11/3301/1062302/wst085113301.pdf"}, {"href": "https://doi.org/10.2166/wst.2022.179"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water%20Science%20and%20Technology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.2166/wst.2022.179", "name": "item", "description": "10.2166/wst.2022.179", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2166/wst.2022.179"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-06-01T00:00:00Z"}}, {"id": "10.25338/B8P92J", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-07-27T16:21:26Z", "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": "10.3389/fmicb.2021.652173", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:21:37Z", "type": "Journal Article", "created": "2021-06-11", "title": "Assessing METland\u00ae Design and Performance Through LCA: Techno-Environmental Study With Multifunctional Unit Perspective", "description": "<p>Conventional wastewater treatment technologies are costly and energy demanding; such issues are especially remarkable when small communities have to clean up their pollutants. In response to these requirements, a new variety of nature-based solution, so-called METland\uffc2\uffae, has been recently develop by using concepts from Microbial Electrochemical Technologies (MET) to outperform classical constructed wetland regarding wastewater treatment. Thus, the current study evaluates two operation modes (aerobic and aerobic\uffe2\uff80\uff93anoxic) of a full-scale METland\uffc2\uffae, including a Life Cycle Assessment (LCA) conducted under a Net Environmental Balance perspective. Moreover, a combined technical and environmental analysis using a Net Eutrophication Balance (NEuB) focus concluded that the downflow (aerobic) mode achieved the highest removal rates for both organic pollutant and nitrogen, and it was revealed as the most environmentally friendly design. Actually, aerobic configuration outperformed anaero/aero-mixed mode in a fold-range from 9 to 30%. LCA was indeed recalculated under diverse Functional Units (FU) to determine the influence of each FU in the impacts. Furthermore, in comparison with constructed wetland, METland\uffc2\uffae showed a remarkable increase in wastewater treatment capacity per surface area (0.6 m2/pe) without using external energy. Specifically, these results suggest that aerobic\uffe2\uff80\uff93anoxic configuration could be more environmentally friendly under specific situations where high N removal is required. The removal rates achieved demonstrated a robust adaptation to influent variations, revealing a removal average of 92% of Biology Oxygen Demand (BOD), 90% of Total Suspended Solids (TSS), 40% of total nitrogen (TN), and 30% of total phosphorus (TP). Moreover, regarding the global warming category, the overall impact was 75% lower compared to other conventional treatments like activated sludge. In conclusion, the LCA revealed that METland\uffc2\uffae appears as ideal solution for rural areas, considering the low energy requirements and high efficiency to remove organic pollutants, nitrogen, and phosphates from urban wastewater.</p>", "keywords": ["Funtional Unit", "treatment wetlands", "Net Environmental Balance", "QS Ecology", "15. Life on land", "Microbiology", "01 natural sciences", "QR1-502", "6. Clean water", "12. Responsible consumption", "wastewater treatment", "03 medical and health sciences", "0302 clinical medicine", "life cycle assessment", "13. Climate action", "11. Sustainability", "TD Environmental technology. Sanitary engineering", "METland", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.3389/fmicb.2021.652173"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Microbiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3389/fmicb.2021.652173", "name": "item", "description": "10.3389/fmicb.2021.652173", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3389/fmicb.2021.652173"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-06-11T00:00:00Z"}}, {"id": "10.3390/su13031570", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:22:03Z", "type": "Journal Article", "created": "2021-02-02", "title": "Agronomic and Environmental Performance of Lemnaminor Cultivated on Agricultural Wastewater Streams\u2014A Practical Approach", "description": "<p>This study investigated the potential of Lemna minor to valorise agricultural wastewater in protein-rich feed material in order to meet the growing demand for animal feed protein and reduce the excess of nutrients in certain European regions. For this purpose, three pilot-scale systems were monitored for 175 days under outdoor conditions in Flanders. The systems were fed with the effluent of aquaculture (pikeperch production\uffe2\uff80\uff94PP), a mixture of diluted pig manure wastewater (PM), and a synthetic medium (SM). PM showed the highest productivity (6.1 \uffc2\uffb1 2.5 g DW m\uffe2\uff88\uff922 d\uffe2\uff88\uff921) and N uptake (327 \uffc2\uffb1 107 mg N m\uffe2\uff88\uff922 d\uffe2\uff88\uff921). PP yielded a similar productivity and both wastewaters resulted in higher productivities than SM. Furthermore, all media showed similar P uptake rates (65\uffe2\uff80\uff9370 P m\uffe2\uff88\uff922 d\uffe2\uff88\uff921). Finally, duckweed had a beneficial amino acid composition for humans (essential amino acid index = 1.1), broilers and pigs. This study also showed that the growing medium had more influence on the productivity of duckweed than on its amino acid composition or protein content, with the latter being only slightly affected by the different media studied. Overall, these results demonstrate that duckweed can effectively remove nutrients from agriculture wastewaters while producing quality protein.</p>", "keywords": ["Planning and Development", "biological effluent treatment", "nutrient recycling", "2. Zero hunger", "0301 basic medicine", "Sustainability and the Environment", "Geography", "Monitoring", "Policy and Law", "constructed wetlands", "01 natural sciences", "6. Clean water", "Management", "12. Responsible consumption", "03 medical and health sciences", "13. Climate action", "Earth and Environmental Sciences", "protein alternatives", "Lemnaceae", "Renewable Energy", "amino acid composition", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://www.mdpi.com/2071-1050/13/3/1570/pdf"}, {"href": "https://www.mdpi.com/2071-1050/13/3/1570/pdf"}, {"href": "https://doi.org/10.3390/su13031570"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Sustainability", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/su13031570", "name": "item", "description": "10.3390/su13031570", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/su13031570"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-02-02T00:00:00Z"}}, {"id": "10.3390/w13141893", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:22:05Z", "type": "Journal Article", "created": "2021-07-08", "title": "Diffuse Water Pollution from Agriculture: A Review of Nature-Based Solutions for Nitrogen Removal and Recovery", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The implementation of nature-based solutions (NBSs) can be a suitable and sustainable approach to coping with environmental issues related to diffuse water pollution from agriculture. NBSs exploit natural mitigation processes that can promote the removal of different contaminants from agricultural wastewater, and they can also enable the recovery of otherwise lost resources (i.e., nutrients). Among these, nitrogen impacts different ecosystems, resulting in serious environmental and human health issues. Recent research activities have investigated the capability of NBS to remove nitrogen from polluted water. However, the regulating mechanisms for nitrogen removal can be complex, since a wide range of decontamination pathways, such as plant uptake, microbial degradation, substrate adsorption and filtration, precipitation, sedimentation, and volatilization, can be involved. Investigating these processes is beneficial for the enhancement of the performance of NBSs. The present study provides a comprehensive review of factors that can influence nitrogen removal in different types of NBSs, and the possible strategies for nitrogen recovery that have been reported in the literature.</p></article>", "keywords": ["2. Zero hunger", "13. Climate action", "15. Life on land", "nitrogen; constructed wetlands; buffer strips; vegetated channels; water sediment control basins; water pollution", "01 natural sciences", "6. Clean water", "3. Good health", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://cris.unibo.it/bitstream/11585/828003/1/2021_Diffuse%20Water%20Pollution%20from%20Agriculture.pdf"}, {"href": "https://www.mdpi.com/2073-4441/13/14/1893/pdf"}, {"href": "https://doi.org/10.3390/w13141893"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/w13141893", "name": "item", "description": "10.3390/w13141893", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/w13141893"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-08T00:00:00Z"}}, {"id": "10.3929/ethz-b-000582238", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:22:13Z", "type": "Journal Article", "created": "2022-10-23", "title": "Iron speciation changes and mobilization of colloids during redox cycling in Fe-rich, Icelandic peat soils", "description": "Open AccessISSN:0016-7061", "keywords": ["13. Climate action", "Wetlands", "Iceland", "0401 agriculture", " forestry", " and fisheries", "Colloids", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "Iron biogeochemistry", "Organic carbon", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.3929/ethz-b-000582238"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3929/ethz-b-000582238", "name": "item", "description": "10.3929/ethz-b-000582238", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3929/ethz-b-000582238"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-12-01T00:00:00Z"}}, {"id": "10.5061/dryad.3bk3j9kt3", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-07-27T16:22:23Z", "type": "Dataset", "created": "2024-03-31", "title": "Data from: Burrowing crab effects on the properties and functions of coastal soft sediments", "description": "unspecified# Data from: Burrowing crab effects on the properties and functions of  coastal soft sediments  [https://doi.org/10.5061/dryad.3bk3j9kt3](https://doi.org/10.5061/dryad.3bk3j9kt3) Effect size calculations (including means, sample sizes, and standard deviation) of crab burrowing effects (i.e., high density vs low density) on the properties, nutrient stocks, and functions of coastal sediments. Data comes from studies conducted across Africa, Asia, Australia, North America, and South America. ## Description of the data and file structure **File list:** 1. Rinehart_et_al.202X_Effectsizes CSV file containing the Hedges d effect size calculations (including the raw means, sample sizes, and standard deviations) for each extracted comparison/study from all 59 manuscripts. Additional extracted data (e.g., crab taxa, experimental conditions, habitat, burrow density) are also included for each comparison/study. 2. Rinehart_et_al.202X_Publicationbias CSV file containing the pooled standard deviation and the Hedges d effect size calculation for each comparison/study. This datafile was used to conduct analyses of publication bias for a resulting systematic meta-analysis. **Data-specific information for:** (1) Rinehart_et_al.202X_Effectsizes **Number of variables:** 47 **Number of cases/rows:** 1423 Variable List:\u00a0 1. id: the unique code assigned to each data row. 2. reference: author, year, and journal for each data source. 3. pub_year: year of reference publication. One in preparation study was included in the dataset (Rinehart et al. 20XX), it's publication year is denoted as 20XX. 4. paper id: the unique code assigned to each manuscript included in the dataset. 5. continent: the continent where the data was collected. 6. country: the country where the data was collected. 7. state: the state (united states only) where the data was collected. 8. estuary: the name of the estuary where the data was collected. 9. latitude_dd: the latitude associated with the data collected in decimal degrees (dd). 10. longitude_dd: the longitude associated with the data collected in decimal degrees (dd). 11. ecosystem: the type of ecosystem (e.g., salt marsh, mangrove forest, tidal flat) associated with the collected data. 12. vegetation: categorical variable noting the presence (vegetated) or absence (not unvegetated) of any vegetation. 13. ecosystem_type: categorical variable noting if the ecosystem was restored, created, or natural. 14. relative_salinity: categorical variable noting the relative salinity in the ecosystem where the data was collected. 15. tidal_amplitude_m: the tidal amplitude (in meters) in the ecosystem where the data was collected. 16. tidal_cycle: categorical variable noting the type of tidal cycle (e.g., diurnal) in the ecosystem where the data was collected. 17. soil_type: categorical variable noting the soil type (e.g., sand) in the ecosystem where the data was collected. 18. elevation_m: the elevation (in meters) of the ecosystem where the data was collected. 19. study_duration_d: the length of time (in days) that the study ran (applies mainly to manipulative studies). 20. study_timing: the seasons or months during which the study was run. 21. dominant_plant_genus: the genus of the dominant plant present in the ecosystem where the data was collected. 22. dominant_plant_species: the species of the dominant plant present in the ecosystem where the data was collected. 23. dominant_plant_functional_group: categorical variable noting the functional group (e.g., grass) of the dominant plant species in the ecosystem where the data was collected. 24. crab_genus: the genus of the dominant burrowing crab used in the study. Studies with mixed crab communities are denoted with by 'mixed'. 25. crab_species: the species of the dominant burrowing crab used in the study. Studies with mixed crab communities are denoted with by 'mixed'. 26. crab_diet: categorical variable noting the main feeding strategy (e.g., herbivore, detritivore) used by the dominant crab species. 27. crab_superfamily: the superfamily of the dominant burrowing crab used in the study. Studies with mixed crab communities are denoted with by 'mixed'. 28. mean_burrow_diameter_high_crab_treatment_mm: the mean burrow diameter in the study's high crab treatment in mm. 29. mean_burrow_diameter_low_crab_treatment_mm: the mean burrow diameter in the study's low crab treatment in mm. 30. mean_burrow_depth_cm: the mean burrow depth in cm reported by the study. 31. burrow_density_high_crab_m^2: the mean crab burrow density per meter-squared reported in the study's high crab treatment. 32. burrow_density_low_crab_m^2: the mean crab burrow density per meter-squared reported in the study's low crab treatment. 33. experiment_type: categorical variable noting if the study used observational or manipulative methodologies. 34. experiment_setting: categorical variable noting if the study was conducted in a laboratory or field setting. Laboratory studies also include outdoor mesocosm studies. 35. field_location: categorical variable noting where studies conducted in the field placed their study relative to the shoreline. Specifically, we noted if studied sampled in the ecosystem interior (far from shoreline) or at the ecosystem edge (adjacent to the shoreline). 36. soil_depth_cm: the depth, in cm, within the soil profile from which the sediment samples were collected. 37. soil_characteristic_measured: categorical variable identifying the specific sediment property, nutrient stock, or function that was quantified by the study. 38. soil_characteristic_units: the original units used to quantify the soil characteristic within the study. 39. mean_low_crab: the mean value of the soil characteristic measured in the low crab treatment within the study. 40. sd_low_crab: the standard deviation of the soil characteristic measured in the low crab treatment within the study. 41. n_low_crab: the sample size of the soil characteristic measured in the low crab treatment within the study. 42. mean_high_crab: the mean value of the soil characteristic measured in the high crab treatment within the study. 43. sd_high_crab: the standard deviation of the soil characteristic measured in the high crab treatment within the study. 44. n_high_crab: the sample size of the soil characteristic measured in the high crab treatment within the study. 45. crab_density: categorical variable noting if the study documented relative burrowing crab density within their study using burrow density (burrow) or counts of individuals (individuals). 46. hedges_d: the hedges d effect size calculated for the effects of burrowing crabs on the measured sediment characteristic. Hedges d values were calculated in OpenMee software (see code/software below). Positive effect sizes indicate that burrowing crabs increased the value of the sediment measurement, while negative effect sized indicate that burrowing crabs decreased the value of the sediment measurement. 47. hedges_d_var: the variation of the hedges d effect size calculated for the effects of burrowing crabs on the measured sediment characteristic. Hedges d variation values were calculated in OpenMee software (see code/software below). **Missing data codes:** na Data-specific information for: (2) Rinehart_et_al.202X_Publicationbias ***Number of variables:*** 22 ***Number of cases/rows:*** 1423 Variable List:\u00a0 1. id: the unique code assigned to each data row. 2. reference: author, year, and journal for each data source. 3. pub_year: year of reference publication. One in preparation study was included in the dataset (Rinehart et al. 20XX), it's publication year is denoted as 20XX. 4. paper id: the unique code assigned to each manuscript included in the dataset. 5. ecosystem: the type of ecosystem (e.g., salt marsh, mangrove forest, tidal flat) associated with the collected data. 6. vegetation: categorical variable noting the presence (vegetated) or absence (not unvegetated) of any vegetation. 7. crab_superfamily: the superfamily of the dominant burrowing crab used in the study. Studies with mixed crab communities are denoted with by 'mixed'. 8. burrow_density_high_crab_m^2: the mean crab burrow density per meter-squared reported in the study's high crab treatment. 9. experiment_type: categorical variable noting if the study used observational or manipulative methodologies. 10. experiment_setting: categorical variable noting if the study was conducted in a laboratory or field setting. Laboratory studies also include outdoor mesocosm studies. 11. soil_characteristic_measured: categorical variable identifying the specific sediment property, nutrient stock, or function that was quantified by the study. 12. soil_characteristic_units: the original units used to quantify the soil characteristic within the study. 13. mean_low_crab: the mean value of the soil characteristic measured in the low crab treatment within the study. 14. sd_low_crab: the standard deviation of the soil characteristic measured in the low crab treatment within the study. 15. n_low_crab: the sample size of the soil characteristic measured in the low crab treatment within the study. 16. mean_high_crab: the mean value of the soil characteristic measured in the high crab treatment within the study. 17. sd_high_crab: the standard deviation of the soil characteristic measured in the high crab treatment within the study. 18. n_high_crab: the sample size of the soil characteristic measured in the high crab treatment within the study. 19. pooled_sd: the pooled standard deviation of the high and low crab treatments for each study. 20. crab_density: categorical variable noting if the study documented relative burrowing crab density within their study using burrow density (burrow) or counts of individuals (individuals). 21. hedges_d: the hedges d effect size calculated for the effects of burrowing crabs on the measured sediment characteristic. Hedges d values were calculated in OpenMee software (see code/software below). Positive effect sizes indicate that burrowing crabs increased the value of the sediment measurement, while negative effect sized indicate that burrowing crabs decreased the value of the sediment measurement. 22. hedges_d_var: the variation of the hedges d effect size calculated for the effects of burrowing crabs on the measured sediment characteristic. Hedges d variation values were calculated in OpenMee software (see code/software below). **Missing data codes:** na ## Sharing/Access information All data are included in the provided datafiles. ## Code/Software Hedges\u2019 *d* (hereafter, *d*) effect sizes were calculated using meta-analysis using OpenMEE software (Build date: 26 July 2016; Wallace et al. 2017). Wallace, B. C., M. J. Lajeunesse, G. Dietz, I. J. Dahabreh, T. A. Trikalinos, C. H. Schmid, and J. Gurevitch. 2017. OpenMEE: Intuitive, open-source software for meta-analysis in ecology and evolutionary biology. Methods in Ecology and Evolution 8:941\u2013947.", "keywords": ["coastal wetlands", "density-dependance", "bioturbation", "animal effects", "Burrowing", "functional traits", "FOS: Earth and related environmental sciences", "habitat effects", "zoogeochemistry"], "contacts": [{"organization": "Rinehart, Shelby", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.3bk3j9kt3"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.3bk3j9kt3", "name": "item", "description": "10.5061/dryad.3bk3j9kt3", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.3bk3j9kt3"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-04-29T00:00:00Z"}}, {"id": "10.5061/dryad.hr67c5p", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-07-27T16:22:30Z", "type": "Dataset", "title": "Data from: Aggregation but not organo-metal complexes contributed to C storage in tidal freshwater wetland soils", "description": "unspecifiedOne of the many goals of wetland restoration is to promote the long-term  storage of carbon (C) in the terrestrial biosphere. Unfortunately, soil C  reservoirs in restored wetlands are slow to accumulate even after  hydrology and plant communities are reestablished. Oftentimes wetland  restoration changes the soil matrix and thus can dramatically alter how  soil C is stored and processed. Our research investigated whether soil  organic matter (SOM) preservation theories derived from studies in  non-wetland soil systems can be extended to wetland soils. We examined C  associated with water-stable soil aggregates, minerals, and metal oxides  within habitats of one natural and one restored tidal freshwater wetland.  This study revealed that a majority of the soil C in the natural site was  associated with large macroaggregates (&gt; 2000 \u03bcm), and soils from  the restored site stored more C in small macroaggregates (&gt; 250 to  &lt; 2000 \u03bcm). Despite these different associations, the chemical  composition of SOM followed similar patterns across each aggregate-size  class. Results from the sequential extraction procedure suggest  organo-metal oxide complexes do not contribute to C stabilization in these  habitats. This research is one of the few studies that have examined C  stabilization related to soil structure in wetland soils. Our results  suggest soil aggregate formation may be an important mechanism driving C  stabilization, and that disruption to macroaggregates may limit C  accumulation in restored wetlands. Additional empirical research and  long-term field monitoring are needed to confirm linkages between  aggregate-C stabilization and accumulation in wetland soils.", "keywords": ["tidal freshwater wetlands", "aggregates", "15. Life on land", "Soil carbon", "6. Clean water"], "contacts": [{"organization": "Maietta, Christine E., Bernstein, Zachary A., Gaimaro, Joshua R., Monsaint-Queeney, Victoria L., Buyer, Jeffrey, Rabenhorst, Martin, Baldwin, Andrew H., Yarwood, Stephanie A.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.hr67c5p"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.hr67c5p", "name": "item", "description": "10.5061/dryad.hr67c5p", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.hr67c5p"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-03-28T00:00:00Z"}}, {"id": "10.5061/dryad.qjq2bvqkn", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-07-27T16:22:33Z", "type": "Dataset", "title": "The contribution of Fe(III) reduction to soil carbon mineralization in montane meadows depends on soil chemistry, not parent material or microbial community", "description": "The long-term stability of soil carbon (C) is strongly influenced by  organo-mineral interactions.\u00a0Iron (Fe)-oxides can both inhibit  microbial decomposition by providing physicochemical protection for  organic molecules and enhance rates of C mineralization by serving as a  terminal electron acceptor, depending on redox conditions. Restoration of  floodplain hydrology in montane meadows has been proposed as a method of  sequestering C for climate change mitigation. However, dissimilatory  microbial reduction of Fe(III) could lead to C losses under increased  reducing conditions. In this study, we explored variations in Fe-C  interactions over a range of redox conditions and in soils derived from  two distinct parent materials to elucidate biochemical and microbial  controls on soil C cycling in Sierra Nevada montane meadows. Differences  in parent material were associated with different rates of Fe(III)  reduction at increasing soil moisture levels, but not with differences in  soil C mineralization. Known Fe(III)-reducing taxa were present in all  samples but neither the relative abundance nor richness of Fe(III)  reducers corresponded with measured rates of Fe(III) reduction. Under  reducing conditions, our results suggest that Fe(III) reduction  contributes to C mineralization only when Fe-bound C is present. However,  Fe-bound C was not present in all of our soils and was below theoretical  limits for C sorption onto Fe-oxides where it was found. Overall, our  results suggest that meadow-specific soil chemistry drives Fe-C  interactions and that the impact of Fe on C cycling in montane meadows may  be smaller than in other ecosystems.", "keywords": ["montane meadows", "13. Climate action", "Wetlands", "meadow restoration", "Iron reduction", "FOS: Earth and related environmental sciences", "biogeochemical cycles", "Carbon cycle", "15. Life on land"], "contacts": [{"organization": "Reed, Cody C., Dunham\u2010Cheatham, Sarrah M., Castle, Sarah C., Vuono, David C., Sullivan, Benjamin W.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.qjq2bvqkn"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.qjq2bvqkn", "name": "item", "description": "10.5061/dryad.qjq2bvqkn", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.qjq2bvqkn"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-05-11T00:00:00Z"}}, {"id": "10.5061/dryad.x95x69psf", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-07-27T16:22:35Z", "type": "Dataset", "created": "2024-03-11", "title": "Effects of biochar soil amendments on soil properties and plant recruitment in coastal climate change adaptation projects", "description": "unspecified# Effects of biochar soil amendments on soil properties and restoration  success in coastal climate change adaptation projects  [https://doi.org/10.5061/dryad.x95x69psf](https://doi.org/10.5061/dryad.x95x69psf) ### There are five files uploaded as part of this data release: 1. landscape_vegetation.csv - this file details the plant cover derived from drone imagery analysis in 2018-2023 in the landscape scale plots constructed at the Elkhorn Slough National Estuarine Research Reserve. 2. landscape_soil.csv - this file details soil analysis for soils collected in summer 2022 from landscape scale plots. 3. plot_vegetation.csv - this file details the plant cover derived from point-intercept field surveys conducted at Elkhorn Slough National Estuarine Research Reserve, Waquoit Bay National Estuarine Research Reserve, and Prudence Island National Estuarine Research Reserve in November of 2017, September of 2018, March of 2019, August of 2019, and August of 2020. 4. plot_soil.csv - this file details soil analysis for soils collected in March 2019 from small (0.7m x 0.7m) sediment addition plots. 5. particle_size.csv - this file details outputs of grain size analysis for the biochar amended plots for the landscape scale experiment. ## Description of the data and file structure **landscape_vegetation.csv** - This file contains seven fields: site, code, soil, treatment, amendment, date, plant_cover_fraction. The field site refers to which plot was sampled, 1, 2, or 3, where 1 refers to the northernmost series of plots, 2 refers to the middle series of plots, and 3 is the southernmost series of plots. The field code refers to A, B, or C, where A is the series of plots on the left facing south, B refers to the center series of plot facing south, and C is the right series plot facing south. The field soil refers to one of four soil types: hester_soil, which refers to the type of the sediment used in the whole 50-ha restoration, 50_50_mix, a 50:50 mix of granite fines with the restoration sediment, capped_fines a mixture of granite fines capped with restoration soil, or granite_fines alone, which is just granite fines. The field treatment refers to one of four treatments: reference, biochar, fines, or mix, where reference is the same sediment as the rest of the restoration, biochar refers to restoration soil mixed with biochar, fines refers to one of types of granite fine amended soils (see field soil), and mix refers to a mix of granite fine amended soils and biochar. The field amendment refers one of two values, biochar or none, representing biochar amendments or no amendments. The date refers to the date of the drone flight in YYYY-MM-DD format. The plant_cover_fraction refers to the area of the drone image that had plant cover. **landscape_soil.csv** - This file contains 24 fields, including analysis, site, code, replicate, old-Bag-code, new-Bag-code, plant, amendment, plant_cover, LOI, bulk_density, water_fraction, salinity, pH, redox, KCl_NH4, KCl_NO3, D50, sand_frct, mud_frct, silt_frct, clay_frct, sand_fines, CH4_flux_s, CH4_flux_h, CO2_flux. The field analysis refers to one of two codes: GHG or soil, where GHG refers to greenhouse gas flux measures, and soil refers to soil analysis measures. These measures were not taken at the same exact locations and had different numbers of replicates per plot. The field site refers to which plot was sampled, 1, 2, or 3, where 1 refers to the northernmost series of plots, 2 refers to the middle series of plots, and 3 is the southernmost series of plots. The field code refers to A, B, or C, where A is the series of plots on the left facing south, B refers to the center series of plot facing south, and C is the right series plot facing south. The field replicate refers to, where multiple measures are taken in one plot, the replicate number (1 or 2). The field old-Bag-code refers to the code written on the bag. The field new-Bag-code refers to the code which should have been written on the bag. The field plant, may be of two values, 0 or 1, where the value is 1 if the soil was collected beneath a plant or bare soil. The field amendment refers one of two values, biochar or none, representing biochar amendments or no amendments. The field plant_cover refers to field estimated plant cover in the plot, with values from 0-100. The field LOI refers to the organic content of the sediment, as a fraction (0-1). The field bulk_density refers to the bulk density of the soil sample, in g/cc. The field water_fraction is the fraction of the field moist sample that is water. The field salinity is the salinity of the sample, in ppt. The field ORP is redox of the soil sample in mV. The field pH is the pH of the sample on a 1:1 soil to water mix. The field KCl_NH4 is ammonium concentration of KCL extraction (uM / g dry sed). The field KCl_NO3 refers to nitrate concentrations of KCL extraction (uM / g dry sed). The field D50 refers to the median particle size diameter of the sample in micrometers. The field sand_frct refers to the fraction of the sample that is sand (0-1). The field mud_frct refers to the fraction of the sample that is mud (silt and clay) (0-1). The field silt_frct refers to the fraction of the sample that is silt (0-1). The field clay_frct refers to the fraction of the sample that is clay (0-1). The field sand_fines refers to the ratio of sand to mud (silt and clay). The field CH4_flux_s refers to methane emissions (CH4 flux) (in dark flux chambers) in uM/m^2/second. The field CH4_flux_h refers to methane emissions (CH4 flux) (in dark flux chambers) in uM/m2/hour. The field CO2 is soil respiration (CO2 flux) (in dark flux chambers) in uM/m^2/s. Missing data is coded -999. **plot_vegetation.csv** - This file contains eight fields: NERR_code, elevation, plot, treatment, name, cover, date, and time stamp. The NERR_code refers to which site the data was collected at: one of three codes, ELK for Elkhorn Slough, NAR, for Prudence Island, and WQB for Sage Lot Pond, Waquoit Bay. The field elevation is either high or low, as there were five high elevation plots per treatment and five low elevation plots per treatment. The field plot refers to the code of the plot (A, B, C, D, E), or which replicate it is. The field treatment lists one of four treatments: control (a paired plot that received no sediment), reference (a paired plot with high plant cover; the restoration target), 14 (14cm of sediment added) and biochar (14cm of sediment added with 10% biochar admixture). The field name is the plot name that includes the plot, elevation and treatment, H or L for high or low, A, B, C, D, or E for plot, and a code for treatment: 14 cm (14), 14 cm of sediment with biochar (b) reference (R), control (C). The field cover is the percent of the plot that had vegetation cover, with values 0-100. The field date is the date the measure was taken in MM/DD/YEAR. The field timestamp refers to when the measure was taken, before the sediment was added (pre_sediment), during the first year (year1_fall), in the second year during spring (year2_spring), during the second year during fall (year2_fall), and during the third year during fall (year3_fall). Missing data for reference plots is coded -999. **plot_soil.csv** - This file contains 14 fields: NERR_code, date,\u00a0 elevation, \u00a0plot, treatment, name, bulk_density, water_fraction, salinity, ORP, pH, NH4, CO2, vegetation_cover. The NERR_code refers to which site the data was collected at: one of three codes, ELK for Elkhorn Slough, NAR, for Prudence Island, and WQB for Sage Lot Pond, Waquoit Bay. The field date is the date the measure was taken in MM/DD/YEAR. The field elevation is either high or low, as there were five high elevation plots per treatment and five low elevation plots per treatment. The field plot refers to the code of the plot (A, B, C, D, E), or which replicate it is. The field treatment lists one of four treatments: control (a paired plot that received no sediment), reference (a paired plot with high plant cover; the restoration target), 14 (14cm of sediment added) and biochar (14cm of sediment added with 10% biochar admixture). The field name is the plot name that includes the plot, elevation and treatment, H or L for high or low, A, B, C, D, or E for plot, and a code for treatment: 14 cm (14), 14 cm of sediment with biochar (b) reference (R), control (C). The field bulk_density is the bulk density of the soil sample, in g/cc. The field water_fraction is the fraction of the field moist sample that is water. The field salinity is the salinity of the sample, in ppt. The field ORP is redox of the soil sample in mV. The field pH is the pH of the sample on a 1:1 soil to water mix. The field NH4 is ammonium concentration of KCL extraction (uM / g dry sed). The field CO2 is soil respiration (CO2 flux) (in dark flux chambers) in uM/m^2/s. The field vegetation_cover is the year 3 vegetation cover on plots, on a scale of 0-100. The missing or uncollected data is coded -999. **particle_size.csv** - This file has 125 fields, including project, site, code, replicate, old-Bag-code, new-Bag-code, amendment, and 117 codes that reflect particle size bins. The field project has two potential values, landscape or plot. The field site refers to which plot was sampled, 1, 2, or 3, where 1 refers to the northernmost series of plots, 2 refers to the middle series of plots, and 3 is the southernmost series of plots. The field code refers to A, B, or C, where A is the series of plots on the left facing south, B refers to the center series of plot facing south, and C is the right series plot facing south. The field replicate refers to, where multiple measures are taken in one plot, the replicate number (1 or 2). The field old-Bag-code refers to the code written on the bag. The field new-Bag-code refers to the code which should have been written on the bag. The field soil amendment refers one of two values, biochar or none, representing biochar amendments or no amendments. These bins include the following: 0.040\u00a0 0.044\u00a0\u00a0 0.048\u00a0\u00a0 0.053\u00a0\u00a0 0.058\u00a0\u00a0 0.064\u00a0\u00a0 0.070\u00a0\u00a0 0.077\u00a0\u00a0 0.084\u00a0\u00a0 0.093\u00a0\u00a0 0.102\u00a0\u00a0 0.112\u00a0\u00a0 0.122\u00a0\u00a0 0.134\u00a0\u00a0 0.148\u00a0\u00a0 0.162\u00a0\u00a0 0.178\u00a0\u00a0 0.195\u00a0\u00a0 0.214 0.235\u00a0\u00a0 0.258\u00a0\u00a0 0.284\u00a0\u00a0 0.311\u00a0\u00a0 0.342\u00a0\u00a0 0.375\u00a0\u00a0 0.412\u00a0\u00a0 0.452\u00a0\u00a0 0.496\u00a0\u00a0 0.545\u00a0\u00a0 0.598\u00a0\u00a0 0.657\u00a0\u00a0 0.721\u00a0\u00a0 0.791\u00a0\u00a0 0.869\u00a0\u00a0 0.953\u00a0\u00a0 1.047\u00a0\u00a0 1.149\u00a0\u00a01.261\u00a0\u00a0 1.385\u00a0\u00a0 1.520\u00a0\u00a0 1.669\u00a0\u00a0 1.832\u00a0\u00a0 2.010\u00a0\u00a0 2.207\u00a0\u00a0 2.423\u00a0\u00a0 2.660\u00a0\u00a0 2.920\u00a0\u00a0 3.206\u00a0\u00a0 3.519\u00a0\u00a0 3.862\u00a0\u00a0 4.241\u00a0\u00a0 4.656\u00a0\u00a0 5.111\u00a0\u00a0 5.611\u00a0\u00a0 6.158\u00a0\u00a0\u00a0\u00a0 6.761\u00a0\u00a0 7.421\u00a0\u00a0 8.147\u00a0\u00a0 8.944\u00a0\u00a0 9.819\u00a0\u00a0 10.78\u00a0\u00a0 11.83\u00a0\u00a0 12.99\u00a0\u00a0 14.26\u00a0\u00a0 15.65\u00a0\u00a0 17.17\u00a0\u00a0 18.86\u00a0\u00a0 20.70\u00a0\u00a0 22.73\u00a0\u00a0 24.95\u00a0\u00a0 27.38\u00a0\u00a0 30.07\u00a0\u00a0 33.00\u00a0\u00a036.24\u00a0\u00a0 39.77\u00a0\u00a0 43.66\u00a0\u00a0 47.93\u00a0\u00a0 52.63\u00a0\u00a0 57.77\u00a0\u00a0 63.41\u00a0\u00a0 69.62\u00a0\u00a0 76.43\u00a0\u00a0 83.90\u00a0\u00a0 92.09\u00a0\u00a0 101.1\u00a0\u00a0 111.0\u00a0\u00a0 121.8\u00a0\u00a0 133.7\u00a0\u00a0 146.8\u00a0\u00a0 161.2\u00a0\u00a0 176.8\u00a0\u00a0194.2\u00a0\u00a0 213.2\u00a0\u00a0 234.1\u00a0\u00a0 256.8\u00a0\u00a0 282.1\u00a0\u00a0 309.6\u00a0\u00a0 339.8\u00a0\u00a0 373.1\u00a0\u00a0 409.6\u00a0\u00a0 449.7\u00a0\u00a0 493.6\u00a0\u00a0 541.9\u00a0\u00a0 594.9\u00a0\u00a0 653.0\u00a0\u00a0 716.9\u00a0\u00a0 786.9\u00a0\u00a0 863.9\u00a0\u00a0 948.2\u00a0\u00a0 1041\u00a01143\u00a0\u00a0\u00a0 1255\u00a0\u00a0\u00a0 1377\u00a0\u00a0\u00a0 1512\u00a0\u00a0\u00a0 1660\u00a0\u00a0\u00a0 1822\u00a0\u00a0\u00a0 2000. Each of these particle size bins is the percent weight of sediment that falls between the bin labeled (e.g., 2000uM diameter), and the next lowest bin (e.g., 1822 uM). The sum of all the rows of data in the bins equals 100. ## Sharing/Access information There are no other publicly accessible data locations. ## Code/Software No code or software are provided.", "keywords": ["restoration", "Wetlands", "biochar", "FOS: Earth and related environmental sciences"], "contacts": [{"organization": "Barufaldi, Joshua, Fountain, Monique, Raposa, Kenneth, Tyrell, Megan, Ikeh, Rupert, Gray, Andrew, Watson, Elizabeth,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.x95x69psf"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.x95x69psf", "name": "item", "description": "10.5061/dryad.x95x69psf", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.x95x69psf"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-03-19T00:00:00Z"}}, {"id": "10.5061/dryad.z08kprrnc", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:22:35Z", "type": "Dataset", "created": "2024-04-19", "title": "Data from: Water level drawdown induces a legacy effect on the seed bank and retains sediment chemistry in a eutrophic clay wetland", "description": "Open Access<strong>2.1 Study site</strong>  The study was conducted in Oostvaardersplassen in the Netherlands  (coordinates: 52.456857, 5.355935). This eutrophic clay wetland of about  5600 ha consists of a 3600 ha marsh and a 2000 ha dryer border zone. This  study took place in the marsh part. The marsh is characterized by large  water bodies, reed vegetation and willow forests. Oostvaardersplassen is  part of the polder Zuidelijk Flevoland, which is located in the former  Zuiderzee estuary, a marine habitat (see van Leeuwen et al., 2021 for a  detailed description). For water safety reasons the decision was made to  separate the inland Zuiderzee from the North Sea through the construction  of a dike, named the Afsluitdijk. After completion of the construction and  within five years, the Zuiderzee transformed into a freshwater lake,  IJsselmeer. In this freshwater lake, several polders were established to  create land for agriculture; Zuidelijk Flevoland was reclaimed in 1968.  Since Oostvaardersplassen is located in, what was then, the lowest part of  the polder, it remained wet during the first years after reclamation and  no actions were taken to develop this area into the industrial site as it  was planned to be (Cornelissen et al., 2014). The  marine clay soil and its associated high nutrient concentrations  (eutrophic) in combination with the unmanaged and wet conditions, led  nature to develop quickly. This made the area into an important breeding  and resting area for many wetland birds and therefore became a protected  wetland nature reserve in 1974. In 1989 it became a protected area within  the European Bird directive and under the Ramsar agreement. Additionally,  it was qualified as a Natura 2000 area in 2009. Later on, the relatively  high water levels at the end of winter, due to the height of the weir, in  combination with high grazing pressure by moulting greylag geese  (<em>Anser anser</em>) from May to July, resulted in the loss  of reed cover (<em>Phragmites australis</em>) (Vulink and Van  Eerden, 1998). This in turn resulted in decreasing bird numbers due to  lower food and habitat availability (Beemster et al., 2010). To restore  reed-dominated wetlands and to increase food and habitat availability for  birds, a complete multi-year water level drawdown was induced in the  western part of the marsh from 1987 till 1991\u00a0(Vulink and Van Eerden,  1998). The eastern part was hydrologically separated from the western part  by a low dike\u00a0and water levels and dynamics remained unchanged in this  area. The implemented water level drawdown resulted in the development of  c. 600 ha of reed-dominated vegetation in the western part, after which  typical wetland birds, e.g., bearded reedling (<em>Paranrus  biarmicus</em>), marsh harrier (<em>Circus  aeruginosus</em>) and Eurasian bittern (<em>Botaurus  stellaris</em>), increased in numbers (Beemster et al., 2012; Vulink  and Van Eerden, 1998). The study area experiences  seasonal variation in water level, but lacks long-term dynamics in water  level that would be caused by extreme climatological periods. As the marsh  is rainwater fed, natural water level dynamics occur with a high water  level at the end of winter (March) and low levels at the end of summer  (September;). The surplus of water in winter leaves the marsh via a weir.  The average difference in water level between summer and winter is  approximately 30 cm. During \u2018dry\u2019 summers the water level can drop 50 cm  at the end of the growing season. Due to both the climate conditions in  combination with the height of the weir, set as to pertain high water  levels in the reed beds during late winter and spring, these naturally  occurring \u2018dry\u2019 summers did not result in enough mudflat exposure  throughout the area to allow extensive marsh recovery. At the time of  sampling, both the water level drawdown and the non-water level drawdown  area were characterized by a sharp border between vegetation and open  water. The vegetation on the shores was similar in both areas and  dominated by <em>Phragmites australis</em>, <em>Salix  spp. </em>and, to a lesser extent, <em>Convolvulus  spp.</em>. At drier sites, with greater proximity to the lake,  <em>Urtica dioica</em> and <em>Carduus spp.  </em>were present in higher abundances.\u00a0The shores of the lake, that  sometimes fall dry during dry summers, are colonized quickly by species  among which <em>Tephroseris palustris </em>(also known as  <em>Senecio congestus</em>), <em>Epilobium  hirsutum</em> and<strong> </strong><em>Ranunculus  sceleratus</em>.  <strong>2.2 Experimental  design</strong> We examined the legacy effects of  a water level drawdown, a water level gradient and water level  fluctuations on seed bank germination and nutrient availability using  field sampling and mesocosm experiment. The unique field situation  consisting of areas with and without a water level drawdown history allows  to explore legacy effects on seed bank properties (Part 1.1) and nutrient  availability (Part 2.1). This approach focusses on the long-term effects  of inducing a four-year water level drawdown, in this case 30 years after  the event, by sampling 20 locations in each subarea that have been  inundated since the last water level drawdown. In addition, soil samples  have been taken in these two hydrologically distinct areas, along a water  level gradient that is dictated by elevational differences of about 20 cm.  With this approach, we used the elevational gradient to distinguish  between higher locations, that would fall dry more often due to for  example dry summers, and lower locations. The latter had not fallen dry  for 30 years in case of the water level drawdown area and 50 years in case  of the non\u2013water level drawdown area. By taking soil samples on 7  (germination) or 5 (nutrient) locations along this water level gradient,  we were able to research how changes in water level alter seed bank  properties (Part 2.1) and nutrient availability (Part 2.2) on a smaller  seasonal time scale. In addition to the above two sampling campaigns, a  mesocosm experiment was conducted to study the effects of water level on  germination (Part 3.1) and nutrient availability (Part 3.2) . With this  approach it was possible to determine effects of a specified water level  (inundated, saturated, dry) on an even smaller time scale of weeks/months  and how such a response might be influenced by events in the past, in this  case drawdown history.\u00a0 <strong>2.2.1 Part 1:  Water level drawdown history </strong> To  investigate the legacy effects of a previously induced water level  drawdown on the seed bank (part 1.1) and on nutrient availability (part  1.2), we compared seed bank properties (density, diversity, species  composition) and sediment nutrient concentrations between an area with  water level drawdown history and an area without. For the method on  sediment nutrient concentrations we would like to refer to the section on  water level gradient (2.2.2) for field sampling and lab  protocols. <em>2.2.1.1 Seed bank properties (part  1.1)</em> We collected sediment samples from both  areas in Oostvaardersplassen in June 2021, when both areas were still  inundated. To cover the spatial heterogeneity of the area, 40 locations  were sampled. 20 Sample points were located in the area that was  continuously inundated for 50 years (non-water level drawdown history,  <em>n = 20</em>) and 20 in the area that had undergone a water  level drawdown from 1987 till 1991 and was subsequently inundated for 30  years (water level drawdown history, <em>n =  20</em>). In June 2021, we took ten sediment  cores of 23.8 cm<sup>2</sup> (diameter = 5.5 cm) to a depth of  10 cm and pooled the 0-5 cm and 5-10 cm depth in separate plastic bags at  each location (Verhofstad et al., 2017). The bags were stored in the dark  at 4\u00b0C for approximately one month to allow seed stratification, after  which the sediment was sieved (mesh width: 150 \u00b5m) and the residue,  containing the seeds, was spread across a tray (37\u00d727 cm) containing  sediment for propagation and germination (Lensli substrates; pH = ~5.3;  electrical conductivity = ~0.5mS/cm). The trays were placed in a  greenhouse with supplementary light from 6:00-22:00h so that light  conditions on plant level corresponded with 250  \u03bcmol.m<sup>2</sup>/s. The temperature in the greenhouse was on  average 21\u00b0C between 6:00-22:00 and 16\u00b0C between 22:00-6:00. The relative  humidity (Rh) in the greenhouse was on average 60% (-5/+5%). To ensure  optimal sediment moisture, the trays were watered at least once a week  with rainwater. The germinating plants were then identified to species  level and removed afterwards. This was done to minimize possible  competition effects between seedlings. Unidentified plants were  transferred from the trays to individual pots, providing the space for  them to grow and/or flower until their identification could be determined.  When germination stopped, the sediment was mixed to allow seeds deeper in  the sediment to germinate. The trays were kept in the greenhouse until  germination stopped again, which lasted up to 5 months.  <strong>2.2.2 Part 2: Water level  gradient</strong> To determine how a water level  gradient, induced through a gradient in soil elevation of around 20 cm,  affects seed bank properties (density, diversity, species composition;  Part 2.1) and nutrient availability (part 2.2), we collected sediment  samples in the field. Sample collection occurred at seven locations (seed  bank) and five locations (nutrient availability) along four transects  perpendicular to the border of the reed vegetation. The indicated  direction was chosen to cover differences in soil elevation, with  locations on a relatively higher elevation falling dry more often due to  small fluctuations in the water level and locations on a lower elevation  falling dry less often. <em>2.2.2.1 Seed bank  properties (part 2.1)</em> To assess how a water  level gradient alters seed bank properties, we collected sediment samples  in June 2021 along four transects, each consisting of seven sampling  points (<em>n</em> = 28). The sampling points cover a gradient  of soil elevation, where the locations indicated by a 1 are located at the  highest elevation, and thus fall dry the most, while locations indicated  by a higher number (2-7) are decreasing in soil elevation and thus fall  dry less often or never. Each transect covered around 777.5 \u00b1 418.7 meter.  Two transects were located in the area without water level drawdown  history and two in the area with water level drawdown history. The  sampling and germination protocol was identical to the one described in  section 2.2.1. <em>2.2.2.2 Nutrient availability  (part 2.2)</em> To examine how a water level  gradient affect nutrient availability, sediment samples were collected  along four transects (different from the transects in 2.2.2.1) in November  2021. Each transect consists of five sampling points that were sampled in  duplicate (<em>n</em> = 40). The sampling points cover a  gradient of soil elevation, where the locations indicated by a 1 are  located at the highest elevation, and thus fall dry the most, while  locations indicated by a higher number (2-5) are decreasing in soil  elevation and thus fall dry less often or never. Each transect covered  around 237.5 \u00b1 17.9 meter. Two transects were situated in the area without  water level drawdown history and two in the area with water level drawdown  history. At each sampling location, four sediment cores of 23.8  cm<sup>2</sup> (diameter = 5.5 cm) to a depth of 0-10 cm and  20-30 cm were collected for pore-water extraction and one sediment core of  23.8 cm<sup>2</sup> (diameter = 5.5 cm) to a depth of 0-10 and  20-30 cm was collected for sediment nutrient analyses. Soil elevation  measurements were conducted with a dGPS (Topcon, HiPer SR). At each  location, we took three measurements which were averaged.  Pore-water extraction was initiated in the lab on the same day as  sediment collection and collected the next morning. Pore-water samples  were extracted using vacuum syringes attached to rhizons (Rhizon SMS;  Rhizosphere Research Products; Eijkelkamp Agrisearch Equipment, Giesbeek,  The Netherlands). The pore-water was analyzed for pH, alkalinity (Metrohm,  877 Titrino plus), total inorganic carbon (TIC; infrared carbon Analyser,  IRGA; ABB Analytical, Frankfurt, Germany) and nutrient  concentrations. Sediment samples were analyzed on water  content, bulk density loss of ignition (LOI; proxy for organic matter  content) and bioavailable phosphorus and  NH<sub>4</sub><sup>+</sup> and  NO<sub>3</sub><sup>-</sup>. The elaborated method  can be found in the supplementary material S1. Nitrite  (NO<sub>2</sub><sup>-</sup>) concentrations were  barely detectable and therefore left out of the analysis.  <strong>2.2.3 Part 3: Water level  fluctuations</strong> <strong>Experimental  setup</strong> To unravel how water level  influences germination (part 3.1) and nutrient availability (part 3.2), we  performed a mesocosm experiment with different water levels on intact  sediment cores from sites with and without water level drawdown history  from Oostvaardersplassen. The different water levels reflect the different  stages the system goes through during the first phase (drying) of a water  level drawdown cycle: (1) Dry, the water level was 20 cm below sediment  surface level (\u2018dry\u2019 for brevity), (2) saturated, the water level was  equal to the sediment surface level (\u2018saturated\u2019 for brevity), and (3)  wet, the water level was eight cm above sediment surface level (\u2018wet\u2019 for  brevity). The experiment ran for eight consecutive weeks in which each  core experienced one of the water level treatments (inundated, saturated  or dry) following Vonk et al. (2017). In November 2020, intact sediment  cores were collected from Oostvaardersplassen at ten locations that were  inundated. Half of these locations were situated in an area with a water  level drawdown history (<em>n</em> = 5, water level = 13.8 +/-  3.9 cm), while the other half were situated in a continuously inundated  area (<em>n</em> = 5, water level = 17 +/- 5.4 cm). At each  location, four sediment cores with a diameter of 16 cm and a depth of 40  cm were collected by pressing a PVC-tube in the sediment and sealing it  with a cap on the bottom. Three of the intact cores for each location were  placed in a climate room for an acclimation period of six days, after  which the experiment started. The cores were placed in the climate room  with a temperature regime of 20\u00b0C from 6:00-22:00 and 15\u00b0C from  22:00-6:00. The average humidity in the climate chamber was 45% and the  average light conditions at sediment level were 554  \u03bcmol.m<sup>2</sup>/s (LI-COR LI-250 photometer) with 16 hours  light and 8 hours dark. The cores were placed using a randomized block  design (<em>n</em> = 5), each block consisted of six sediment  cores. The treatments were applied by drilling holes in the PVC-tube at  the corresponding water level treatment height (-20 cm, 0 cm, +8 cm  relative to the sediment height). To regulate the water level in the core,  we placed the PVC-tube in a larger water-proof PVC-core (diameter = 20 cm,  length = 50 cm). Water collected from the Oostvaardersplassen was used to  initiate the treatments. During the experiment, water was replenished till  treatment level with rainwater (pH = 5.18, alkalinity = 0.33 mEQ/L). The  fourth core was used to determine sediment nutrient starting conditions by  taking two sediment samples of 40 cm deep (23.8  cm<sup>2</sup>) after which it was split in two sections of 10  cm (0-10, 20-30). The two sediment samples from the sediment core were  pooled per location and per depth and stored in the freezer at -20\u00b0C until  further analyses. The same analysis protocol was used as in approach 2  (section 2.2.2.2). <em>2.2.3.1 Seed bank  properties(part 3.1)</em> Through the use of  intact soil cores in an experimental setup, we could identify possible  environmental filters that would exert selection on the type of plants  that were able to germinate during different phases of a water level  drawdown cycle. During the 8-week experiment, the mesocosms were checked  weekly for plant germination. Germinated plants were counted and  identified to species level if possible. Plants were not removed during  the experiment. <em>2.2.3.2 Nutrient availability  (part 3.2)</em> The experimental setup allowed us  to assess how a certain water level regime impacts nutrient availability  in the system, in this case, we selected three water levels to mimic  different phases of the water level drawdown cycle. By monitoring these  changes it would be possible to identify possible nutrient depletion in  the system upon repeated water level drawdown implementation. Nutrient  concentrations were determined in both the pore-water and the sediment. To  collect pore-water samples during the experiment, rhizons (Rhizon SMS;  Rhizosphere Research Products; Eijkelkamp Agrisearch Equipment, Giesbeek,  The Netherlands) were installed in the sediment core at a depth of 10 cm  and a vacuum syringe could be attached to extract pore-water. This was  done at the start of the experiment (day 0), and repeated five times on  day 7, 14, 21, 35 and 56. Pore-water samples were analyzed in the same way  as in approach 2. At the end of the experiment, sediment samples were  taken from the sediment cores at two different depths (0-10 cm and 20-30  cm) following the same sampling strategy as at the start of the  experiment. These samples were stored in the freezer at -20\u00b0C until  further analyses, following the analysis protocol as described in approach  2 (section 2.2.2.2). <strong>2.3 Statistical  analyses </strong> Data were analyzed in RStudio  version 4.0.3 (R Core Team, 2023). For all hypotheses testing procedures  the significance level was set at \u03b1 = 0.05. All data are shown with their  average \u00b1 standard deviation (sd). <strong>Part  1: Water level drawdown history</strong>  <em>Part 1.1 Seed bank properties</em>  To determine the effect of water level drawdown history (Yes or  No) on mean Shannon-Wiener diversity, mean species richness, and mean  germination densities (log transformed), we used mixed linear models from  the GlmmTMB package (Mollie et al., 2017), using location ID as a random  effect. Differences in the total sum of germinated individuals between the  water level drawdown and non-water level drawdown area were tested using a  Chi-Square test. Shannon-Wiener diversity was calculated using the \u2018vegan  package\u2019 (Oksanen et al., 2022). To assess the effect of water level  drawdown history on species composition a permanova analysis with a  Bray-Curtis dissimilarity index was used, in combination with non-metric  multidimensional scaling (NMDS) (vegan package: Oksanen et al.,  2022). <em>Part 1.2 Nutrient  availability</em> To determine the effect of  water level drawdown history and sampling depth (independent variables) on  the nutrient availability (dependent variables) along the transect survey  (method section 2.2.2.2), we used mixed linear models from the GlmmTMB  package (Mollie et al., 2017). The model was performed for both the  sediment- and the pore-water nutrient concentrations. Location ID was used  as a random effect to correct for the duplicate measurements.  Tukey-adjusted comparisons were done using \u201cemmeans\u201d (Russell, 2022).  Normality and heterogeneity of the residuals of the models were assessed  using histograms, and transformed if necessary.  Additionally, we used the nutrient starting concentrations from  the experimental water level experiment (part 3) to determine differences  in nutrient concentrations due to the water level drawdown history. To  determine the effect of water level drawdown history (independent  variable) on nutrient availability (dependent variables), we used mixed  linear models from the GlmmTMB package (Mollie et al., 2017). Starting  nutrient concentrations (day 0; field conditions) were used as the  dependent variable. Field location ID was used as a random effect to  correct for samples taken at the same location.  <strong>Part 2: Water level  gradient</strong> <em>Part 2.1 Seed bank  properties</em> To determine the best fit of the  relation between germination and distance to the reed border, we compared  the AIC of linear, parabolic, hyperbolic and exponential decay functions.  An \u0394AIC \u2265 2 was used to differentiate models ( \u2018stats\u2019 package (R Core  Team, 2023). To assess the effect of water level drawdown history and  location along soil elevation gradient on species composition, a permanova  analysis with a Bray-Curtis dissimilarity index was used in combination  with non-metric multidimensional scaling (NMDS) (Oksanen et al.,  2022). To determine differences in Shannon-Wiener  diversity, species richness and germination densities (dependent  variables) along the transect survey (location within transect as  independent variable), we used mixed linear models from the GlmmTMB  package with location ID as a random effect (Mollie et al., 2017). Species  richness was fitted with a Poisson distribution. This approach was done  separately for the water level drawdown and the non-water level drawdown  area. Tukey-adjusted comparisons were done using \u201cemmeans\u201d (Russell,  2022). Shannon-Wiener diversity was calculated using the \u2018vegan package\u2019  (Oksanen et al., 2022). Differences in the sum of germinated individuals  per location along the water level gradient were tested using a Chi-Square  test. <em>Part 2.2 Nutrient  availability</em> To test for differences in  nutrient availability along the elevational gradient of current water  level fluctuations in the transect survey, we performed Spearman  correlations. The Spearman correlations were done between nutrient  concentration as the dependent variable and elevation in meters NAP as the  independent variable. <strong>Part 3: Water level  fluctuations</strong> <em>Part 3.1: Seed  bank properties</em> Due to the low germination  rate, no statistical analysis were performed on seed bank properties in  relation to any of the water level treatments.  <em>Part 3.2: Nutrient availability</em>  To determine the effect of water level treatment (independent  variable) on nutrient availability (dependent variables), we used mixed  linear models from the GlmmTMB package (Mollie et al., 2017). Nutrient  concentrations from the end of the experiment (day 56) were used as  dependent variable. Nutrient starting concentrations were used as a  covariate into the model and the blocking factor was used as a random  effect. Additionally, nutrient concentrations were tested for changes over  time during the eight-week experiment using mixed linear models from the  GlmmTMB package (Mollie et al., 2017). Nutrient concentrations were used  as the dependent variable, the blocking factor was used as a covariate in  the model and date was used as the independent variable. To test for  differences among the independent variables, Tukey-adjusted comparisons  were done using \u201cemmeans\u201d for all models (Russell, 2022). All models were  fitted with a Gaussian-error distribution. Normality and heterogeneity of  the residuals of the models were assessed using histograms, and were  transformed if necessary. For more details we would  like to refer to\u00a0<strong>Figure 1</strong> in the related  manuscript.", "keywords": ["fluctuating water level", "nutrients", "Seedlings", "Wetlands", "seedlings", "Fluctuating water level", "Nutrients", "mesocosms", "natural sciences", "Mesocosms", "FOS: Natural sciences", "wetlands"]}, "links": [{"href": "https://doi.org/10.5061/dryad.z08kprrnc"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.z08kprrnc", "name": "item", "description": "10.5061/dryad.z08kprrnc", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.z08kprrnc"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.10888463", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-07-27T16:23:08Z", "type": "Dataset", "title": "Urban Riparian Wetland Water Quality Dataset_Stormwater Capture in Beaver-mediated Wetlands along Walnut Creek, Raleigh, North Carolina, USA", "description": "This is the initial release of a\u00a0water quality\u00a0dataset pertaining to the\u00a0riparian floodplain wetlands\u00a0alongside Walnut Creek in Raleigh, North Carolina USA.\u00a0 Walnut Creek is the main drainage channel in an\u00a0urbanized watershed\u00a0(HUC-12: 030202011101) in central North Carolina.\u00a0 There are several riparian floodplain wetlands along the creek which are largely supplied by\u00a0urban stormwater\u00a0runoff including directed\u00a0storm sewer flows\u00a0and regular\u00a0overbank flooding\u00a0events. In many of these wetlands local water retention and residence time in the surface ponds is mediated by the damming activity of\u00a0North American beavers (Castor canadensis).\u00a0 This dataset contains data specific to the water quality values of Walnut Creek, its tributary Little Rock Creek, and the surface ponds and groundwater at the\u00a0Walnut Creek Wetland Park\u00a0which is actively influenced by resident beavers.\u00a0 The period of this dataset is from\u00a0January 5, 2023 through October 28, 2023.\u00a0  This dataset includes a variety of common water quality parameters measured in situ by use of a YSI Pro water quality meter, as well as dissolved nutrient values determined by laboratory analysis of collected water samples.\u00a0 YSI data was collected on a weekly basis and water samples were collected for laboratory analysis on a monthly basis. Additional measurements and collection took place during six large rainfall events to allow comparison between baseflow and stormflow conditions across the site.\u00a0 This dataset aims to provide a comprehensive look at the water quality of Walnut Creek in comparison with the surface ponds and groundwater in the Walnut Creek Wetland Park, which are all ultimately sourced from urban stormwater runoff.   This water quality dataset is intended to accompany the separate hydrology dataset published on Zenodo at URL: https://doi.org/10.5281/zenodo.10709630. Together, these datasets are meant to support an improved understanding of the water availability and water quality found in connection with beaver-mediated stormwater capture in an urbanized watershed in the North Carolina Piedmont.  \u00a0This dataset resulted from research supported with a Graduate Student Research Grant awarded by the\u00a0North Carolina Water Resources Research Institute (WRRI), under Project Number 23-10-W: 'Stormwater Diversion, Storage, and Treatment by Beaver-enhanced Floodplain Wetlands in Piedmont Urban Watersheds'. \u00a0  This material is based upon work supported by the\u00a0National Science Foundation (NSF)\u00a0Graduate Research Fellowship Program (GRFP) under Grant No. (DGE 2137100). Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors(s) and do not necessarily reflect the views of the National Science Foundation.  Special thanks to\u00a0Raleigh Parks\u00a0and\u00a0Walnut Creek Wetland Park\u00a0for making this work possible.  Laboratory analysis support for evaluation of dissolved nutrients (nitrate+nitrite, TKN, total phosphorus, and total organic carbon) was provided by the NC State Environmental and Agricultural Testing Services (EATS) laboratory, Department of Crop and Soil Sciences.  \u00a0Additional laboratory analysis support for evaluation of dissolved nutrients (TKN and total phosphorus) was provided by the NC State Environmental Analysis Laboratory (EAL), Department of Biological and Agricultural Engineering (BAE).  \u00a0Usage of and technical support for the YSI Pro water quality meter used in this study was made possible by the Osburn Lab, Department of Marine, Earth and Atmospheric Sciences (MEAS), NC State University.", "keywords": ["beaver", "Piedmont", "Castor canadensis", "stormwater", "urbanization", "water quality", "wetlands"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.10888463"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.10888463", "name": "item", "description": "10.5281/zenodo.10888463", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.10888463"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-03-27T00:00:00Z"}}, {"id": "10.5281/zenodo.13696300", "type": "Feature", "geometry": null, "properties": {"license": "Restricted", "updated": "2026-07-27T16:23:20Z", "type": "Dataset", "title": "Wetland sediment soil organic carbon sequestration data to support radiometric technique comparisons", "description": "This workbook shows the ID, the geographical location, the year of sampling, and sediment core information in samples collected from undisturbed wetlands situated across four provinces of Canada (Alberta, Saskatchewan, Manitoba, and Ontario) from 2016 to 2019.", "keywords": ["carbon", "sediments", "sequestration", "wetlands", "soil"], "contacts": [{"organization": "Irena, Creed", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13696300"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13696300", "name": "item", "description": "10.5281/zenodo.13696300", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13696300"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-09-05T00:00:00Z"}}, {"id": "3146941420", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:27:39Z", "type": "Journal Article", "created": "2021-03-31", "title": "Impact of future climate scenarios on peatland and constructed wetland water quality: A mesocosm experiment within climate chambers", "description": "Water purification is one of the most essential services provided by wetlands. A lot of concerns regarding wetlands subjected to climate change relate to their susceptibility to hydrological change and the increase in temperature as a result of global warming. A warmer condition may accelerate the rate of decomposition and release of nutrients, which can be exported downstream and cause serious ecological challenges; e.g., eutrophication and acidification. The aim of this study is to investigate the effect of climate change on water quality in peatland and constructed wetland ecosystems subject to water level management. For this purpose, the authors simulated the current climate scenario base on the database from Malm\u00f6 station (Scania, Sweden) for 2016 and 2017 as well as the future climate scenarios for the last 30 years of the century based on the Representative Concentration Pathway (RCP) and different regional climate models (RCM) for a region wider than Scania County. For future climate change, the authors simulated low (RCP 2.6), moderate (RCP 4.5) and extreme (RCP 8.5) climate scenarios. All simulations were conducted within climate chambers for experimental peatland and constructed wetland mesocosms. Our results demonstrate that the effect of climate scenario is significantly different for peatlands and constructed wetlands (interactive effect) for the combined chemical variables. The warmest climate scenario RCP 8.5 is linked to a higher water purification function for constructed wetlands, but to a lower water purification function and a subsequent deterioration of peatland water qualities, even if subjected to water level management. The explanation for the different response of constructed wetlands and peatlands to climate change could be due to the fact that the substrate in the constructed wetland mesocosms and peatlands was different in terms of the organic matter quality and quantity. The utilization of nutrients by the plants and microbial community readily exceed the mineralization under a limited nutrient content (as we had in constructed wetland) when the temperature rises. However, concerning the extreme scenario RCP 8.5, the peatlands have shown a tendency to have reverse processes.", "keywords": ["Sweden", "13. Climate action", "Climate Change", "Water Quality", "Wetlands", "14. Life underwater", "15. Life on land", "01 natural sciences", "Ecosystem", "6. Clean water", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/3146941420"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Environmental%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3146941420", "name": "item", "description": "3146941420", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3146941420"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-01T00:00:00Z"}}, {"id": "10.5281/zenodo.15264191", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:23:53Z", "type": "Other", "title": "Supporting data for the development of simplified models related to WATERAGRI innovations.", "description": "The ZIP file contains three Excel documents, each corresponding to a different simplified model: tracer methods, biochar for soil water retention, and free water surface wetlands.      Tracer Methods: This dataset includes results from numerical simulations performed using HYDRUS-1D. It contains data on Oxygen-18 concentrations in soil water profiles across different seasons and soil types.     Biochar Model: This model was developed based on bibliographic data related to the effects of biochar on soil water retention.     Free Water Surface Wetlands Model: This dataset is based on average values commonly used in the design of such systems, complemented by long-term observational data from real-world systems.    These data support the development of simplified models for innovations within the WATERAGRI project", "keywords": ["constructed wetlands", "treatment wetlands", "Water Stable Isotopes", "biochar"], "contacts": [{"organization": "Canet-Mart\u00ed, Alba, Langergraber, Guenter, Stumpp, Christine,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15264191"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15264191", "name": "item", "description": "10.5281/zenodo.15264191", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15264191"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-04-22T00:00:00Z"}}, {"id": "10.5281/zenodo.15264192", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:23:53Z", "type": "Other", "title": "Supporting data for the development of simplified models related to WATERAGRI innovations.", "description": "The ZIP file contains three Excel documents, each corresponding to a different simplified model: tracer methods, biochar for soil water retention, and free water surface wetlands.      Tracer Methods: This dataset includes results from numerical simulations performed using HYDRUS-1D. It contains data on Oxygen-18 concentrations in soil water profiles across different seasons and soil types.     Biochar Model: This model was developed based on bibliographic data related to the effects of biochar on soil water retention.     Free Water Surface Wetlands Model: This dataset is based on average values commonly used in the design of such systems, complemented by long-term observational data from real-world systems.    These data support the development of simplified models for innovations within the WATERAGRI project", "keywords": ["constructed wetlands", "treatment wetlands", "Water Stable Isotopes", "biochar"], "contacts": [{"organization": "Canet-Mart\u00ed, Alba, Langergraber, Guenter, Stumpp, Christine,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15264192"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15264192", "name": "item", "description": "10.5281/zenodo.15264192", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15264192"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-04-22T00:00:00Z"}}, {"id": "10.5281/zenodo.15398850", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-07-27T16:23:56Z", "type": "Dataset", "title": "Wetland sediment soil organic carbon stock and sequestration rates in undisturbed and rewetted Canadian wetlands", "description": "This workbook shows the ID, the geographical location, the year of sampling, and sediment core information in samples collected from undisturbed and rewetted wetlands situated across four provinces of Canada (Alberta, Saskatchewan, Manitoba, and Ontario) from 2016 to 2019.", "keywords": ["restoration", "carbon", "sediments", "sequestration", "wetlands", "soil"], "contacts": [{"organization": "Creed, Irena", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15398850"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15398850", "name": "item", "description": "10.5281/zenodo.15398850", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15398850"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-05-13T00:00:00Z"}}, {"id": "10.5281/zenodo.15484766", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-07-27T16:24:00Z", "type": "Dataset", "title": "Wetland sediment soil organic carbon sequestration rates in undisturbed Canadian wetlands and data to support predictive modeling", "description": "Table in RF Model Data worksheet in workbook shows (1) ID, \u00a0geographical location, \u00a0year of sampling, and measured organic carbon sequestration rates (OCSR) \u00a0in samples collected from undisturbed wetlands situated across Canada, and (2) direct controls on OCSR extracted from geospatial data. These data were used to support random forest (RF) modeling to develop modeled estimates of OCSR.\u00a0 Table data is also provided as a .csv file and supporting readme document.", "keywords": ["carbon", "sediments", "sequestration", "wetlands", "soil"], "contacts": [{"organization": "Creed, Irena", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15484766"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15484766", "name": "item", "description": "10.5281/zenodo.15484766", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15484766"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-05-21T00:00:00Z"}}, {"id": "10.5281/zenodo.16817357", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-07-27T16:24:10Z", "type": "Dataset", "title": "Soil carbon predictions for manuscript submission: Improving soil organic carbon spatial distribution and interpretation of cross-scale drivers with probabilistic wetland representation", "description": "This zipped folder contains the predicted soil carbon stocks from model described in the manuscript and using the code at https://github.com/ajs0428/SOC-patterns-drivers", "keywords": ["digital soil mapping", "soil carbon", "geospatial", "wetlands"], "contacts": [{"organization": "Stewart, Anthony", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.16817357"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.16817357", "name": "item", "description": "10.5281/zenodo.16817357", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.16817357"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-08-12T00:00:00Z"}}, {"id": "10.5281/zenodo.17834473", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-07-27T16:24:16Z", "type": "Dataset", "title": "Vast, overlooked peat and organic soils in Brazil's Cerrado: carbon storage, dynamics, and stability", "description": "Data accompanying the paper 'Vast, overlooked peat and organic soils in Brazil's Cerrado: carbon storage, dynamics, and stability.'Authors: Larissa S Verona1,2, Amy E Zanne2, Susan Trumbore3, Paulo N. Bernardino\u00b2,4, Guilherme M Alencar4, Thalia Andreuccetti\u00b9, David Herrera3,5,6, Jo\u00e3o C F Cardoso7, Demetrius Lira-Martins4, Guilherme G Mazzochini8, Natashi Pilon4, Rafael S Oliveira4  1. Programa de p\u00f3s-gradua\u00e7\u00e3o em Biologia Vegetal, Departamento de Biologia Vegetal,Instituto de Biologia, Universidade Estadual de Campinas, Campinas, S\u00e3o Paulo, Brazil;  2. Cary Institute of Ecosystems Studies, Millbrook, NY, US;  3. Max Planck Institute for Biogeochemistry, Jena, Germany  4. Universidade Estadual de Campinas, Departamento de Biologia Vegetal, Campinas, S\u00e3o Paulo, Brazil;  5. Yale School of the Environment, Yale University, New Haven, US;  6. Yale Institute for Biospheric Studies, Yale University, New Haven, US;  7. Programa de P\u00f3s-Gradua\u00e7\u00e3o em Ecologia, Conserva\u00e7\u00e3o e Manejo da Fauna Silvestre, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.  8. Programa de P\u00f3s-Gradua\u00e7\u00e3o em Ecologia, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Rio de Janeiro, Brazil  \u00a0  # SupportingTable1_CarbonStorageData:Data regarding herbaceous biomass, palm biomass, and soil carbon storage.## Tab: Biomass - HerbaceousDry height for herbaceous biomass in each plot, point, and site, for above and below-ground sampling.  ## Tab: \u00a0Tab: Biomass - PalmsPalm height and derived above and below-ground biomass according Goodman et al., 2013, in each point and site.\u00a0## Tab: Soil CarbonCarbon and Nitrogen %, dry bulk density, volume, length, and carbon density for each sample, point, transect and site.\u00a0  # SupportingTable2_ValidationPointsRandomForestLatitude, Longitude (WGS84), and Class for validation points used to train Random Forest models.  # SupportingTable3_CarbonStabilityData## Tab: RadiocarbonF14, error for F14 measures, derived calendar age max, min, mean and errors, max probability for calendar age, and curve used to estimate calendar age for each sample, point, and site.\u00a0## Tab: FTIRHolecellulose and lignin percentages, carbon %, and flooding patterns for each sample, point, and site.\u00a0# SupportingTable4_FluxesAndEnviromentalVariablesData## LocationSampling information description including temporal replication, spatial replication, point, site, month, position, latitude and longitude (WGS84) and flooding pattern. ## GasesGas measurements including flux, rate, coefficient of determination r,\u00b2 and coefficient of variation for CH4 and CO2## Environmental VariableTotal and mean precipitation in lags of 0-6 months.\u00a0  # SupportingTable5_ConfusionMatricesPredicted and truth classes for validation points in 10\u00a0 random forest models.", "keywords": ["Veredas", "climate change", "tropical peatlands", "methane", "carbon cycle", "carbon dioxide", "Cerrado", "wetlands"], "contacts": [{"organization": "da Silveira Verona, Larissa", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.17834473"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.17834473", "name": "item", "description": "10.5281/zenodo.17834473", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.17834473"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-12-05T00:00:00Z"}}, {"id": "10.5281/zenodo.17817651", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-07-27T16:24:16Z", "type": "Dataset", "title": "Wetland sediment soil organic carbon sequestration rates in undisturbed Canadian wetlands and data to support predictive modeling", "description": "Table in RF Model Data worksheet in workbook shows (1) ID, \u00a0geographical location, \u00a0year of sampling, and measured organic carbon sequestration rates (OCSR) \u00a0in samples collected from undisturbed wetlands situated across Canada, and (2) direct controls on OCSR extracted from geospatial data. These data were used to support random forest (RF) modeling to develop modeled estimates of OCSR.\u00a0 Table data is also provided as a .csv file and supporting readme document.", "keywords": ["carbon", "sediments", "sequestration", "wetlands", "soil"], "contacts": [{"organization": "Creed, Irena", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.17817651"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.17817651", "name": "item", "description": "10.5281/zenodo.17817651", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.17817651"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-05-21T00:00:00Z"}}, {"id": "20.500.11769/649311", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:26:42Z", "type": "Journal Article", "created": "2022-09-26", "title": "Cost-benefit of green infrastructures for water management: A sustainability assessment of full-scale constructed wetlands in Northern and Southern Italy", "description": "Sustainable water management has become an urgent challenge due to irregular water availability patterns and water quality issues. The effect of climate change exacerbates this phenomenon in water-scarce areas, such as the Mediterranean region, stimulating the implementation of solutions aiming to mitigate or improve environmental, social, and economic conditions. A novel solution inspired by nature, technology-oriented, explored in the past years, is constructed wetlands. Commonly applied for different types of wastewater due to its low cost and simple maintenance, they are considered a promising solution to remove pollutants while creating an improved ecosystem by increasing biodiversity around them. This research aims to assess the sustainability of two typologies of constructed wetlands in two Italian areas: Sicily, with a vertical subsurface flow constructed wetland, and Emilia Romagna, with a surface flow constructed wetland. The assessment is performed by applying a cost-benefit analysis combining primary and secondary data sources. The analysis considered the market and non-market values in both proposed scenarios to establish the feasibility of the two options and identify the most convenient one. Results show that both constructed wetlands bring more benefits (benefits-cost ratio, BCR) than costs (BCR &gt; 0). In the case of Sicily, the BCR is lower (1) in the constructed wetland scenario, while in its absence it is almost double. If other ecosystem services are included the constructed wetland scenario reach a BCR of 4 and a ROI of 5, showing a better performance from a costing perspective than the absence one. In Emilia Romagna, the constructed wetland scenario shows a high BCR (10) and ROI (9), while the scenario in absence has obtained a negative present value indicating that the cost do not cover the benefits expected.", "keywords": ["FOS: Economics and business", "Constructed wetlands; Cost-benefit analysis; Nature-based solution", "General Economics (econ.GN)", "13. Climate action", "11. Sustainability", "15. Life on land", "01 natural sciences", "Cost-benefit analysis", " Constructed wetlands", " Nature-based solution", "6. Clean water", "Economics - General Economics", "0105 earth and related environmental sciences", "12. Responsible consumption"]}, "links": [{"href": "https://cris.unibo.it/bitstream/11585/895282/5/Garc%c3%ada-Herrero%20et%20al%20%282022%29_preprint.pdf"}, {"href": "https://cris.unibo.it/bitstream/11585/895282/10/Garcia-Herrero%20et%20al%20%282022%29_postprint.pdf"}, {"href": "https://www.iris.unict.it/bitstream/20.500.11769/649311/1/Herrero%20et%20al_2022_Ecological_eng.pdf"}, {"href": "https://doi.org/20.500.11769/649311"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Ecological%20Engineering", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "20.500.11769/649311", "name": "item", "description": "20.500.11769/649311", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.11769/649311"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-12-01T00:00:00Z"}}, {"id": "10.5281/zenodo.17953406", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-07-27T16:24:17Z", "type": "Dataset", "title": "Wetland sediment soil organic carbon stock and sequestration rates in undisturbed and rewetted Canadian wetlands", "description": "'Mistry et al - Comm Earth Environ - Supp Data.XLSX' file contains supporting data and description for the manuscript 'Mistry et al. Rewetting wetlands results in amplification of Natural Climate Solutions', including data on the Wetland ID, the geographical location, the year of sampling, and organic carbon (OC) data in samples collected from undisturbed and rewetted wetlands situated across Canada (Alberta, Saskatchewan, Manitoba, and Ontario), which were used to compute normality tests, descriptive statistics, frequency distribution, Spearman correlation coefficients, simple linear regression, and generalized additive model (GAM) analyses.  'Mistry et al - Comm Earth Environ - R Script.R' contains an annotated script to run the simple linear regression and GAM to evaluate the influence of time since rewetting and hydro-biogeochemical factors on (1) total post-rewetting OC stock and (2) net change in OC sequestration rate post-rewetting.  'Mistry et al - Comm Earth Environ - R Data.CSV' contains data designed to be used alongside the script 'Mistry et al - Comm Earth Environ - R Script.R'.  'Mistry et al - Comm Earth Environ - R Script and Data - Readme.TXT' contains a description of 'Mistry et al - Comm Earth Environ - R Script.R' and 'Mistry et al - Comm Earth Environ - R Data.CSV'.  For details, see Mistry et al. Rewetting wetlands results in amplification of Natural Climate Solutions.  Please contact Irena Creed for more information: \u00a0irena.creed@utoronto.ca", "keywords": ["restoration", "carbon", "sediments", "sequestration", "wetlands", "soil"], "contacts": [{"organization": "Creed, Irena", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.17953406"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.17953406", "name": "item", "description": "10.5281/zenodo.17953406", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.17953406"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-05-13T00:00:00Z"}}, {"id": "2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/287489", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:26:50Z", "type": "Journal Article", "created": "2019-03-18", "title": "Aquatic carbon fluxes dampen the overall variation of net ecosystem productivity in the Amazon basin: An analysis of the interannual variability in the boundless carbon cycle", "description": "Abstract<p>The river\uffe2\uff80\uff93floodplain network plays an important role in the carbon (C) cycle of the Amazon basin, as it transports and processes a significant fraction of the C fixed by terrestrial vegetation, most of which evades as CO2 from rivers and floodplains back to the atmosphere. There is empirical evidence that exceptionally dry or wet years have an impact on the net C balance in the Amazon. While seasonal and interannual variations in hydrology have a direct impact on the amounts of C transferred through the river\uffe2\uff80\uff93floodplain system, it is not known how far the variation of these fluxes affects the overall Amazon C balance. Here, we introduce a new wetland forcing file for the ORCHILEAK model, which improves the representation of floodplain dynamics and allows us to closely reproduce data\uffe2\uff80\uff90driven estimates of net C exports through the river\uffe2\uff80\uff93floodplain network. Based on this new wetland forcing and two climate forcing datasets, we show that across the Amazon, the percentage of net primary productivity lost to the river\uffe2\uff80\uff93floodplain system is highly variable at the interannual timescale, and wet years fuel aquatic CO2 evasion. However, at the same time overall net ecosystem productivity (NEP) and C sequestration are highest during wet years, partly due to reduced decomposition rates in water\uffe2\uff80\uff90logged floodplain soils. It is years with the lowest discharge and floodplain inundation, often associated with El Nino events, that have the lowest NEP and the highest total (terrestrial plus aquatic) CO2 emissions back to atmosphere. Furthermore, we find that aquatic C fluxes display greater variation than terrestrial C fluxes, and that this variation significantly dampens the interannual variability in NEP of the Amazon basin. These results call for a more integrative view of the C fluxes through the vegetation\uffe2\uff80\uff90soil\uffe2\uff80\uff90river\uffe2\uff80\uff90floodplain continuum, which directly places aquatic C fluxes into the overall C budget of the Amazon basin.</p", "keywords": ["boundless carbon cycle", "550", "Climate", "01 natural sciences", "Carbon Cycle", "Environnement et pollution", "Soil", "Rivers", "Amazon", "Ecosystem", "0105 earth and related environmental sciences", "[SDU.OCEAN]Sciences of the Universe [physics]/Ocean", "Ecologie", "interannual variation", "[SDU.OCEAN] Sciences of the Universe [physics]/Ocean", " Atmosphere", "Atmosphere", "carbon", "Models", " Theoretical", "15. Life on land", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "Carbon", "6. Clean water", "floodplains", "NEP", "13. Climate action", "Wetlands", "contr\u00f4le de la pollution", "Technologie de l'environnement", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "ENSO", "environment", "CO 2 evasion"]}, "links": [{"href": "https://doi.org/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/287489"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Change%20Biology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/287489", "name": "item", "description": "2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/287489", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/287489"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-04-15T00:00:00Z"}}, {"id": "10138/570237", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:25:48Z", "type": "Journal Article", "created": "2023-02-08", "title": "Plant phenology and species\u2010specific traits control plant CH4 emissions in a northern boreal fen", "description": "Summary<p> <p>Aerenchymatic transport is an important mechanism through which plants affect methane (CH4) emissions from peatlands. Controlling environmental factors and the effects of plant phenology remain, however, uncertain.</p> <p>We identified factors controlling seasonal CH4 flux rate and investigated transport efficiency (flux rate per unit of rhizospheric porewater CH4 concentration). We measured CH4 fluxes through individual shoots of Carex rostrata, Menyanthes trifoliata, Betula nana and Salix lapponum throughout growing seasons in 2020 and 2021 and Equisetum fluviatile and Comarum palustre in high summer 2021 along with water\uffe2\uff80\uff90table level, peat temperature and porewater CH4 concentration.</p> <p>CH4 flux rate of C. rostrata was related to plant phenology and peat temperature. Flux rates of M. trifoliata and shrubs B. nana and S. lapponum were insensitive to the investigated environmental variables. In high summer, flux rate and efficiency were highest for C. rostrata (6.86\uffe2\uff80\uff89mg\uffe2\uff80\uff89m\uffe2\uff88\uff922\uffc2\uffa0h\uffe2\uff88\uff921 and 0.36\uffe2\uff80\uff89mg\uffe2\uff80\uff89m\uffe2\uff88\uff922\uffc2\uffa0h\uffe2\uff88\uff921 (\uffce\uffbcmol\uffe2\uff80\uff89l\uffe2\uff88\uff921)\uffe2\uff88\uff921, respectively). Menyanthes trifoliata showed a high flux rate, but limited efficiency. Low flux rates and efficiency were detected for the remaining species.</p> <p>Knowledge of the species\uffe2\uff80\uff90specific CH4 flux rate and their different responses to plant phenology and environmental factors can significantly improve the estimation of ecosystem\uffe2\uff80\uff90scale CH4 dynamics in boreal peatlands.</p> </p", "keywords": ["550", "Herbs", "Peatlands", "plant-enclosure", "metaani", "kosteikot", "Soil", "11. Sustainability", "peatlands", "Ecosystem", "580", "2. Zero hunger", "plant methane (CH4) transport", "porewater CH4 concentration", "Temperature", "temperature", "herbs", "Carbon Dioxide", "15. Life on land", "11831 Plant biology", "shrubs", "13. Climate action", "kosteikkokasvit", "Wetlands", "ta1181", "Plant-enclosure", "Shrubs", "Seasons", "Methane"]}, "links": [{"href": "https://nph.onlinelibrary.wiley.com/doi/pdf/10.1111/nph.18798"}, {"href": "https://doi.org/10138/570237"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/New%20Phytologist", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10138/570237", "name": "item", "description": "10138/570237", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10138/570237"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-03-07T00:00:00Z"}}, {"id": "10259/9749", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:25:49Z", "type": "Journal Article", "created": "2024-12-01", "title": "Metal(loid) tolerance, accumulation, and phytoremediation potential of wetland macrophytes for multi-metal(loid)s polluted water.", "description": "<title>Abstract</title>         <p>Natural based solutions, notably constructed/artificial wetland treatment systems, rely heavily on identification and use of macrophytes with the ability to tolerate multiple contaminants and grow for an extended period to reduce contamination. The potential to tolerate and remediate metal(loid) contaminated groundwater from an industrial site located in Flanders (Belgium) was assessed for 10 wetland macrophytes (including <italic>Carex riparia, Cyperus longus, Cyperus rotundus, Iris pseudacorus, Juncus effusus, Lythrum salicaria, Menta aquatica, Phragmites australis, Scirpus holoschoenus,</italic> and <italic>Typha angustifolia</italic>). The experiment was conducted under static conditions, where plants were exposed to polluted acidic (pH~4)water, having high level of metal(loid)s for 15 days. Plant biomass, morphology, and metal uptake by roots and shoots were analysed every 5 days for all species. <italic>T. angustifolia</italic> and <italic>S. holoschoenus </italic>produced ~3 and ~1.1 times more dried biomass than the controls, respectively. For <italic>S. holoschoenus, P. australis,</italic> and <italic>T. angustifolia</italic>, no apparent morphological stress symptoms were observed, and plant heights were similar between control and plants exposed to polluted groundwater. Higher concentrations of all metal(loid)s were detected in the roots indicating a potential for phytostabilization of metal(loid)s below the water column. For <italic>J. effusus</italic> and <italic>T. angustifolia</italic>, Cd, Ni, and Zn accumulation was observed higher in the shoots. <italic>S. holoschoenus</italic>, <italic>P. australis,</italic> and <italic>T. angustifolia</italic> are proposed for restoration and phytostabilization strategies in natural and/or constructed wetland and aquatic ecosystems affected by metal(loid) inputs.</p>", "keywords": ["580", "570", "Constructed wetlands ; Metals/metabolism [MeSH] ; Groundwater ; Phytostabilization ; Wetlands [MeSH] ; Metals", " Heavy/metabolism [MeSH] ; Heavy metals ; Macrophytes ; Water Pollutants", " Chemical/metabolism [MeSH] ; Research Article ; Biodegradation", " Environmental [MeSH] ; Belgium [MeSH]", "Constructed wetlands", "15. Life on land", "Biorremediaci\u00f3n", "6. Clean water", "Macrophytes", "Agua-Contaminaci\u00f3n", "Biodegradation", " Environmental", "Heavy metals", "Water-Pollution", "Belgium", "Metals", "13. Climate action", "Wetlands", "Metals", " Heavy", "Phytostabilization", "Groundwater", "Bioremediation", "Water Pollutants", " Chemical", "Research Article"]}, "links": [{"href": "https://doi.org/10259/9749"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Science%20and%20Pollution%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10259/9749", "name": "item", "description": "10259/9749", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10259/9749"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-12-12T00:00:00Z"}}, {"id": "10261/376900", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:25:56Z", "type": "Journal Article", "created": "2025-01-09", "title": "Assessment of intensified constructed wetlands for the attenuation of PMT compounds from groundwater and wastewater: Characterization of biofilm communities", "description": "Open AccessObjectius de Desenvolupament Sostenible::6 - Aigua Neta i Sanejament::6.3 - Per a 2030, millorar la qualitat de l\u2019aigua mitjan\u00e7ant la reducci\u00f3 de la contaminaci\u00f3, l\u2019eliminaci\u00f3 dels abocaments i la reducci\u00f3 al m\u00ednim de la desc\u00e0rrega de materials i productes qu\u00edmics perillosos, la reducci\u00f3 a la meitat del percentatge d\u2019aig\u00fces residuals sense tractar, i un augment substancial a escala mundial del reciclat i de la reutilitzaci\u00f3 en condicions de seguretat", "keywords": ["Persistent", " mobile and toxic compounds", "Ensure availability and sustainable management of water and sanitation for all", "http://metadata.un.org/sdg/6", "http://metadata.un.org/sdg/3", "Intensified constructed wetlands", "http://metadata.un.org/sdg/9", "\u00c0rees tem\u00e0tiques de la UPC::Desenvolupament hum\u00e0 i sostenible::Medi ambient", "mobile and toxic compounds", "Build resilient infrastructure", " promote inclusive and sustainable industrialization and foster innovation", "Microbial electrochemical technologies", "Electroconductive materials", "Persistent", "Water treatment", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria agroaliment\u00e0ria::Enginyeria del medi rural", "Ensure healthy lives and promote well-being for all at all ages"]}, "links": [{"href": "https://doi.org/10261/376900"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Water%20Process%20Engineering", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10261/376900", "name": "item", "description": "10261/376900", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/376900"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-02-01T00:00:00Z"}}, {"id": "11392/2582471", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:26:14Z", "type": "Journal Article", "created": "2025-02-14", "title": "Different Denitrification Capacity in Phragmites australis and Typha latifolia Sediments: Does the Availability of Surface Area for Biofilm Colonization Matter?", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Denitrification is a permanent nitrogen removal pathway; thus, it is a desirable ecosystem function in water bodies receiving agricultural runoff. Knowledge of denitrification capacity in response to vegetation type and varying NO3\u2212 loads is essential for designing effectively constructed wetlands to control eutrophication. The aim of this study was to compare the nitrogen removal efficiency of two common wetland macrophytes, i.e., Phragmites australis and Typha latifolia in a NO3\u2212 enrichment experiment (50\u2212800 \u00b5M). Measurements of NO3\u2212 consumption, and N2 production were performed in vegetated and unvegetated mesocosms incubated in summer (26 \u00b0C) at biomass peak. Vegetated sediments demonstrated higher efficiency in converting NO3\u2212 to N2 via denitrification (&lt;600\u201318,000 \u00b5mol N m\u22122 h\u22121) than bare sediments (300\u20133300 \u00b5mol N m\u22122 h\u22121). However, the denitrification stimulation effect from NO3\u2212 pulsing differed significantly between plant types. It can be hypothesized that P. australis played a more beneficial role than T. latifolia due to its greater submerged surface area, which facilitated enhanced opportunities for contact between NO3\u2212 and denitrifying bacteria. This ultimately resulted in an increased treatment performance. Understanding the interactions between plants and environmental drivers regulating denitrification is critical information for optimal wetland species selection. With an increasing global focus on sustainable water quality management, this research provides valuable insights into optimizing nature-based solutions.</p></article>", "keywords": ["biofilms; constructed wetlands; denitrification; nature-based solutions; nitrate pollution; P. australis; T. latifolia"]}, "links": [{"href": "https://sfera.unife.it/bitstream/11392/2582471/1/water-17-00560-v2.pdf"}, {"href": "https://www.mdpi.com/2073-4441/17/4/560/pdf"}, {"href": "https://doi.org/11392/2582471"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11392/2582471", "name": "item", "description": "11392/2582471", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11392/2582471"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-02-14T00:00:00Z"}}, {"id": "11585/828003", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:26:18Z", "type": "Journal Article", "created": "2021-07-08", "title": "Diffuse Water Pollution from Agriculture: A Review of Nature-Based Solutions for Nitrogen Removal and Recovery", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The implementation of nature-based solutions (NBSs) can be a suitable and sustainable approach to coping with environmental issues related to diffuse water pollution from agriculture. NBSs exploit natural mitigation processes that can promote the removal of different contaminants from agricultural wastewater, and they can also enable the recovery of otherwise lost resources (i.e., nutrients). Among these, nitrogen impacts different ecosystems, resulting in serious environmental and human health issues. Recent research activities have investigated the capability of NBS to remove nitrogen from polluted water. However, the regulating mechanisms for nitrogen removal can be complex, since a wide range of decontamination pathways, such as plant uptake, microbial degradation, substrate adsorption and filtration, precipitation, sedimentation, and volatilization, can be involved. Investigating these processes is beneficial for the enhancement of the performance of NBSs. The present study provides a comprehensive review of factors that can influence nitrogen removal in different types of NBSs, and the possible strategies for nitrogen recovery that have been reported in the literature.</p></article>", "keywords": ["2. Zero hunger", "13. Climate action", "15. Life on land", "nitrogen; constructed wetlands; buffer strips; vegetated channels; water sediment control basins; water pollution", "01 natural sciences", "6. Clean water", "0105 earth and related environmental sciences", "3. Good health"]}, "links": [{"href": "https://cris.unibo.it/bitstream/11585/828003/1/2021_Diffuse%20Water%20Pollution%20from%20Agriculture.pdf"}, {"href": "https://www.mdpi.com/2073-4441/13/14/1893/pdf"}, {"href": "https://doi.org/11585/828003"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11585/828003", "name": "item", "description": "11585/828003", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11585/828003"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-08T00:00:00Z"}}, {"id": "11585/889925", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:26:18Z", "type": "Journal Article", "created": "2022-06-01", "title": "Comparison of simple models for total nitrogen removal from agricultural runoff in FWS wetlands", "description": "Abstract                <p>Free water surface (FWS) wetlands can be used to treat agricultural runoff, thereby reducing diffuse pollution. However, as these are highly dynamic systems, their design is still challenging. Complex models tend to require detailed information for calibration, which can only be obtained when the wetland is constructed. Hence simplified models are widely used for FWS wetlands design. The limitations of these models in full-scale FWS wetlands is that these systems often cope with stochastic events with different input concentrations. In our study, we compared different simple transport and degradation models for total nitrogen under steady- and unsteady-state conditions using information collected from a tracer experiment and data from two precipitation events from a full-scale FWS wetland. The tanks-in-series model proved to be robust for simulating solute transport, and the first-order degradation model with non-zero background concentration performed best for total nitrogen concentrations. However, the optimal background concentration changed from event to event. Thus, to use the model as a design tool, it is advisable to include an upper and lower background concentration to determine a range of wetland performance under different events. Models under steady- and unsteady-state conditions with simulated data showed good performance, demonstrating their potential for wetland design.</p", "keywords": ["agricultural runoff", " design models", " free water surface wetlands", " modelling", " treatment wetlands", "Nitrogen", "treatment wetlands", "0207 environmental engineering", "Water", "02 engineering and technology", "15. Life on land", "Environmental technology. Sanitary engineering", "01 natural sciences", "agricultural runoff", "6. Clean water", "Water Purification", "modelling", "13. Climate action", "Wetlands", "Denitrification", "design models", "free water surface wetlands", "TD1-1066", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://cris.unibo.it/bitstream/11585/889925/1/wst085113301.pdf"}, {"href": "https://iwaponline.com/wst/article-pdf/85/11/3301/1062302/wst085113301.pdf"}, {"href": "https://doi.org/11585/889925"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water%20Science%20and%20Technology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11585/889925", "name": "item", "description": "11585/889925", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11585/889925"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-06-01T00:00:00Z"}}, {"id": "20.500.11850/529133", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:26:44Z", "type": "Journal Article", "created": "2021-11-08", "title": "Mineral characterization and composition of Fe-rich flocs from wetlands of Iceland: Implications for Fe, C and trace element export", "description": "Open AccessIn freshwater wetlands, redox interfaces characterized by circumneutral pH, steep gradients in O2, and a continual supply of Fe(II) form ecological niches favorable to microaerophilic iron(II) oxidizing bacteria (FeOB) and the formation of flocs; associations of (a)biotic mineral phases, microorganisms, and (microbially-derived) organic matter. On the volcanic island of Iceland, wetlands are replenished with Fe-rich surface-, ground- and springwater. Combined with extensive drainage of lowland wetlands, which forms artificial redox gradients, accumulations of bright orange (a)biotically-derived Fe-rich flocs are common features of Icelandic wetlands. These loosely consolidated flocs are easily mobilized, and, considering the proximity of Iceland's lowland wetlands to the coast, are likely to contribute to the suspended sediment load transported to coastal waters. To date, however, little is known regarding (Fe) mineral and elemental composition of the flocs. In this study, flocs from wetlands (n = 16) across Iceland were analyzed using X-ray diffraction and spectroscopic techniques (X-ray absorption and 57Fe M\u00f6ssbauer) combined with chemical extractions and (electron) microscopy to comprehensively characterize floc mineral, elemental, and structural composition. All flocs were rich in Fe (229\u2013414 mg/g), and floc Fe minerals comprised primarily ferrihydrite and nano-crystalline lepidocrocite, with a single floc sample containing nano-crystalline goethite. Floc mineralogy also included Fe in clay minerals and appreciable poorly-crystalline aluminosilicates, most likely allophane and/or imogolite. Microscopy images revealed that floc (bio)organics largely comprised mineral encrusted microbially-derived components (i.e. sheaths, stalks, and EPS) indicative of common FeOB Leptothrix spp. and Gallionella spp. Trace element contents in the flocs were in the low \u03bcg/g range, however nearly all trace elements were extracted with hydroxylamine hydrochloride. This finding suggests that the (a)biotic reductive dissolution of floc Fe minerals, plausibly driven by exposure to the varied geochemical conditions of coastal waters following floc mobilization, could lead to the release of associated trace elements. Thus, the flocs should be considered vectors for transport of Fe, organic carbon, and trace elements from Icelandic wetlands to coastal waters.", "keywords": ["Minerals", "Iron", "Iceland", "Freshwater flocs", "04 agricultural and veterinary sciences", "15. Life on land", "Ferric Compounds", "01 natural sciences", "6. Clean water", "Trace Elements", "EXAFS", "13. Climate action", "Freshwater flocs; Fe(II)-oxidizing bacteria; Biominerals; Wetlands; EXAFS; 57Fe M\u00f6ssbauer", "Wetlands", "57Fe M\u00f6ssbauer", "Biominerals", "Fe(II)-oxidizing bacteria", "0401 agriculture", " forestry", " and fisheries", "14. Life underwater", "Oxidation-Reduction", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/20.500.11850/529133"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20of%20The%20Total%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "20.500.11850/529133", "name": "item", "description": "20.500.11850/529133", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.11850/529133"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-04-01T00:00:00Z"}}, {"id": "20.500.11850/582238", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:26:44Z", "type": "Report", "title": "Iron speciation changes and mobilization of colloids during redox cycling in Fe-rich, Icelandic peat soils", "description": "Open AccessISSN:0016-7061", "keywords": ["Iceland; Iron biogeochemistry; Organic carbon; Colloids; Wetlands"], "contacts": [{"organization": "Thomas Arrigo, Laurel K., Kretzschmar, Ruben; id_orcid0000-0003-2587-2430,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/20.500.11850/582238"}, {"rel": "self", "type": "application/geo+json", "title": "20.500.11850/582238", "name": "item", "description": "20.500.11850/582238", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.11850/582238"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-12-15T00:00:00Z"}}, {"id": "2117/433687", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:26:57Z", "type": "Journal Article", "created": "2025-01-09", "title": "Assessment of intensified constructed wetlands for the attenuation of PMT compounds from groundwater and wastewater: Characterization of biofilm communities", "description": "Open AccessPeer reviewed", "keywords": ["Persistent", " mobile and toxic compounds", "Ensure availability and sustainable management of water and sanitation for all", "mobile and toxic compounds", "Build resilient infrastructure", " promote inclusive and sustainable industrialization and foster innovation", "Electroconductive materials", "Microbial electrochemical technologies", "Persistent", "Water treatment", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria agroaliment\u00e0ria::Enginyeria del medi rural", "Intensified constructed wetlands", "Ensure healthy lives and promote well-being for all at all ages", "\u00c0rees tem\u00e0tiques de la UPC::Desenvolupament hum\u00e0 i sostenible::Medi ambient"], "contacts": [{"organization": "Cano-L\u00f3pez, Alicia, Escol\u00e0-Casas, M\u00f2nica, Subirats, J\u00e8ssica, Matamoros, V\u00edctor,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/2117/433687"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Water%20Process%20Engineering", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2117/433687", "name": "item", "description": "2117/433687", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2117/433687"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-02-01T00:00:00Z"}}, {"id": "2164/19435", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:26:59Z", "type": "Journal Article", "created": "2022-03-17", "title": "Structure and function of the soil microbiome underlying N2O emissions from global wetlands", "description": "Abstract<p>Wetland soils are the greatest source of nitrous oxide (N2O), a critical greenhouse gas and ozone depleter released by microbes. Yet, microbial players and processes underlying the N2O emissions from wetland soils are poorly understood. Using in situ N2O measurements and by determining the structure and potential functional of microbial communities in 645 wetland soil samples globally, we examined the potential role of archaea, bacteria, and fungi in nitrogen (N) cycling and N2O emissions. We show that N2O emissions are higher in drained and warm wetland soils, and are correlated with functional diversity of microbes. We further provide evidence that despite their much lower abundance compared to bacteria, nitrifying archaeal abundance is a key factor explaining N2O emissions from wetland soils globally. Our data suggest that ongoing global warming and intensifying environmental change may boost archaeal nitrifiers, collectively transforming wetland soils to a greater source of N2O.</p", "keywords": ["0301 basic medicine", "570", "571", "Supplementary Data", "QH301 Biology", "Science", "General Biochemistry", "Genetics and Molecular Biology", "Nitrous Oxide", "General Physics and Astronomy", "Soil Science", "551", "852993", "Article", "DH150187", "QH301", "Greenhouse Gases", "Soil", "03 medical and health sciences", "948219", "General", "Soil Microbiology", "0303 health sciences", "Microbiota", "Q", "General Chemistry", "15. Life on land", "6. Clean water", "BBS/e/F/000Pr10355", "13. Climate action", "BB/r012490/1", "Wetlands", "Biotechnology and Biological Sciences Research Council (BBSRC)", "Other", "European Research Council"]}, "links": [{"href": "https://pub.epsilon.slu.se/27540/1/bahram-m-et-al-220412.pdf"}, {"href": "https://ueaeprints.uea.ac.uk/id/eprint/84269/1/Published_Version.pdf"}, {"href": "https://www.nature.com/articles/s41467-022-29161-3.pdf"}, {"href": "https://doi.org/2164/19435"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Nature%20Communications", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2164/19435", "name": "item", "description": "2164/19435", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2164/19435"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-03-17T00:00:00Z"}}, {"id": "3131855811", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:27:37Z", "type": "Journal Article", "created": "2021-02-21", "title": "Impact of climate change on wetland ecosystems: A critical review of experimental wetlands", "description": "Climate change is identified as a major threat to wetlands. Altered hydrology and rising temperature can change the biogeochemistry and function of a wetland to the degree that some important services might be turned into disservices. This means that they will, for example, no longer provide a water purification service and adversely they may start to decompose and release nutrients to the surface water. Moreover, a higher rate of decomposition than primary production (photosynthesis) may lead to a shift of their function from being a sink of carbon to a source. This review paper assesses the potential response of natural wetlands (peatlands) and constructed wetlands to climate change in terms of gas emission and nutrients release. In addition, the impact of key climatic factors such as temperature and water availability on wetlands has been reviewed. The authors identified the methodological gaps and weaknesses in the literature and then introduced a new framework for conducting a comprehensive mesocosm experiment to address the existing gaps in literature to support future climate change research on wetland ecosystems. In the future, higher temperatures resulting in drought might shift the role of both constructed wetland and peatland from a sink to a source of carbon. However, higher temperatures accompanied by more precipitation can promote photosynthesis to a degree that might exceed the respiration and maintain the carbon sink role of the wetland. There might be a critical water level at which the wetland can preserve most of its services. In order to find that level, a study of the key factors of climate change and their interactions using an appropriate experimental method is necessary. Some contradictory results of past experiments can be associated with different methodologies, designs, time periods, climates, and natural variability. Hence a long-term simulation of climate change for wetlands according to the proposed framework is recommended. This framework provides relatively more accurate and realistic simulations, valid comparative results, comprehensive understanding and supports coordination between researchers. This can help to find a sustainable management strategy for wetlands to be resilient to climate change.", "keywords": ["2. Zero hunger", "Carbon Sequestration", "13. Climate action", "Climate Change", "Wetlands", "Hydrology", "15. Life on land", "01 natural sciences", "Ecosystem", "6. Clean water", "0105 earth and related environmental sciences"], "contacts": [{"organization": "Miklas Scholz, Miklas Scholz, Miklas Scholz, Suhad A.A.A.N. Almuktar, Suhad A.A.A.N. Almuktar, Shokoufeh Salimi,", "roles": ["creator"]}]}, "links": [{"href": "https://orca.cardiff.ac.uk/id/eprint/150461/1/1-s2.0-S030147972100222X-main.pdf"}, {"href": "https://doi.org/3131855811"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Environmental%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3131855811", "name": "item", "description": "3131855811", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3131855811"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-05-01T00:00:00Z"}}, {"id": "33611067", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:27:51Z", "type": "Journal Article", "created": "2021-02-21", "title": "Impact of climate change on wetland ecosystems: A critical review of experimental wetlands", "description": "Climate change is identified as a major threat to wetlands. Altered hydrology and rising temperature can change the biogeochemistry and function of a wetland to the degree that some important services might be turned into disservices. This means that they will, for example, no longer provide a water purification service and adversely they may start to decompose and release nutrients to the surface water. Moreover, a higher rate of decomposition than primary production (photosynthesis) may lead to a shift of their function from being a sink of carbon to a source. This review paper assesses the potential response of natural wetlands (peatlands) and constructed wetlands to climate change in terms of gas emission and nutrients release. In addition, the impact of key climatic factors such as temperature and water availability on wetlands has been reviewed. The authors identified the methodological gaps and weaknesses in the literature and then introduced a new framework for conducting a comprehensive mesocosm experiment to address the existing gaps in literature to support future climate change research on wetland ecosystems. In the future, higher temperatures resulting in drought might shift the role of both constructed wetland and peatland from a sink to a source of carbon. However, higher temperatures accompanied by more precipitation can promote photosynthesis to a degree that might exceed the respiration and maintain the carbon sink role of the wetland. There might be a critical water level at which the wetland can preserve most of its services. In order to find that level, a study of the key factors of climate change and their interactions using an appropriate experimental method is necessary. Some contradictory results of past experiments can be associated with different methodologies, designs, time periods, climates, and natural variability. Hence a long-term simulation of climate change for wetlands according to the proposed framework is recommended. This framework provides relatively more accurate and realistic simulations, valid comparative results, comprehensive understanding and supports coordination between researchers. This can help to find a sustainable management strategy for wetlands to be resilient to climate change.", "keywords": ["2. Zero hunger", "Carbon Sequestration", "13. Climate action", "Climate Change", "Wetlands", "Hydrology", "15. Life on land", "01 natural sciences", "Ecosystem", "6. Clean water", "0105 earth and related environmental sciences"], "contacts": [{"organization": "Salimi, Shokoufeh, Almuktar, Suhad, Scholz, Miklas,", "roles": ["creator"]}]}, "links": [{"href": "https://orca.cardiff.ac.uk/id/eprint/150461/1/1-s2.0-S030147972100222X-main.pdf"}, {"href": "https://doi.org/33611067"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Environmental%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "33611067", "name": "item", "description": "33611067", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/33611067"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-05-01T00:00:00Z"}}, {"id": "33799066", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:27:51Z", "type": "Journal Article", "created": "2021-03-30", "title": "Impact of future climate scenarios on peatland and constructed wetland water quality: A mesocosm experiment within climate chambers", "description": "Water purification is one of the most essential services provided by wetlands. A lot of concerns regarding wetlands subjected to climate change relate to their susceptibility to hydrological change and the increase in temperature as a result of global warming. A warmer condition may accelerate the rate of decomposition and release of nutrients, which can be exported downstream and cause serious ecological challenges; e.g., eutrophication and acidification. The aim of this study is to investigate the effect of climate change on water quality in peatland and constructed wetland ecosystems subject to water level management. For this purpose, the authors simulated the current climate scenario base on the database from Malm\u00f6 station (Scania, Sweden) for 2016 and 2017 as well as the future climate scenarios for the last 30 years of the century based on the Representative Concentration Pathway (RCP) and different regional climate models (RCM) for a region wider than Scania County. For future climate change, the authors simulated low (RCP 2.6), moderate (RCP 4.5) and extreme (RCP 8.5) climate scenarios. All simulations were conducted within climate chambers for experimental peatland and constructed wetland mesocosms. Our results demonstrate that the effect of climate scenario is significantly different for peatlands and constructed wetlands (interactive effect) for the combined chemical variables. The warmest climate scenario RCP 8.5 is linked to a higher water purification function for constructed wetlands, but to a lower water purification function and a subsequent deterioration of peatland water qualities, even if subjected to water level management. The explanation for the different response of constructed wetlands and peatlands to climate change could be due to the fact that the substrate in the constructed wetland mesocosms and peatlands was different in terms of the organic matter quality and quantity. The utilization of nutrients by the plants and microbial community readily exceed the mineralization under a limited nutrient content (as we had in constructed wetland) when the temperature rises. However, concerning the extreme scenario RCP 8.5, the peatlands have shown a tendency to have reverse processes.", "keywords": ["Sweden", "13. Climate action", "Climate Change", "Water Quality", "Wetlands", "14. Life underwater", "15. Life on land", "01 natural sciences", "Ecosystem", "6. Clean water", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/33799066"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Environmental%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "33799066", "name": "item", "description": "33799066", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/33799066"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-01T00:00:00Z"}}, {"id": "38159777", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:27:58Z", "type": "Journal Article", "created": "2023-12-28", "title": "Plant-mediated CH4 exchange in wetlands: A review of mechanisms and measurement methods with implications for modelling", "description": "Plant-mediated CH4 transport (PMT) is the dominant pathway through which soil-produced CH4 can escape into the atmosphere and thus plays an important role in controlling ecosystem CH4 emission. PMT is affected by abiotic and biotic factors simultaneously, and the effects of biotic factors, such as the dominant plant species and their traits, can override the effects of abiotic factors. Increasing evidence shows that plant-mediated CH4 fluxes include not only PMT, but also within-plant CH4 production and oxidation due to the detection of methanogens and methanotrophs attached to the shoots. Despite the inter-species and seasonal differences, and the probable contribution of within-plant microbes to total plant-mediated CH4 exchange (PME), current process-based ecosystem models only estimate PMT based on the bulk biomass or leaf area index of aerenchymatous plants. We highlight five knowledge gaps to which more research efforts should be devoted. First, large between-species variation, even within the same family, complicates general estimation of PMT, and calls for further work on the key dominant species in different types of wetlands. Second, the interface (rhizosphere-root, root-shoot, or leaf-atmosphere) and plant traits controlling PMT remain poorly documented, but would be required for generalizations from species to relevant functional groups. Third, the main environmental controls of PMT across species remain uncertain. Fourth, the role of within-plant CH4 production and oxidation is poorly quantified. Fifth, the simplistic description of PMT in current process models results in uncertainty and potentially high errors in predictions of the ecosystem CH4 flux. Our review suggest that flux measurements should be conducted over multiple growing seasons and be paired with trait assessment and microbial analysis, and that trait-based models should be developed. Only then we are capable to accurately estimate plant-mediated CH4 emissions, and eventually ecosystem total CH4 emissions at both regional and global scales.", "keywords": ["Drivers", "330", "Plants", "Carbon Dioxide", "metaani", "Modelling", "Processes", "Soil", "Wetland plants", "Wetlands", "Mechanisms", "suot", "suokasvillisuus", "Plant CH4 transport", "Biomass", "Methane", "Ecosystem"]}, "links": [{"href": "https://doi.org/38159777"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20of%20The%20Total%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "38159777", "name": "item", "description": "38159777", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/38159777"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-03-01T00:00:00Z"}}, {"id": "5fc1b45a-715a-466e-b576-1be0ced40e2a", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[-30.92, 25.96], [-30.92, 70.64], [46.96, 70.64], [46.96, 25.96], [-30.92, 25.96]]]}, "properties": {"themes": [{"concepts": [{"id": "environment"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Land cover"}], "scheme": "http://inspire.ec.europa.eu/theme"}, {"concepts": [{"id": "biodiversity"}, {"id": "Water Framework Directive"}, {"id": "wetlands ecosystem"}, {"id": "ecosystem"}, {"id": "ecosystem assessment"}, {"id": "wetland"}], "scheme": "GEMET"}, {"concepts": [{"id": "EEA39"}], "scheme": "Continents, countries, sea regions of the world."}, {"concepts": [{"id": "European"}], "scheme": "Spatial scope"}, {"concepts": [{"id": "Biodiversity"}], "scheme": "EEA topics"}], "license": "License CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Copyright holder: European Environment Agency (EEA).", "updated": "2025-10-09T10:53:28.435109Z", "type": "Dataset", "created": "2019-09-15", "language": "eng", "title": "Extended wetland ecosystem layer 2012 (raster 100m) version 1, Nov. 2019", "description": "This raster dataset presents the ecosystem wetlands extent in 2012 in Europe. It includes 20 wetland classes which, besides inland and coastal wetlands, includes transitional ecosystems corresponding to wetlands such as riparian forests, wet grasslands, estuaries, or rice fields.\nA great diversity of wetlands exists making the definition of a wetland ecosystem both challenging and controversial. The development of an extended wetland ecosystem layer is an explicit policy request in Europe which builds on an ecosystem-based justification of an inclusive definition, delimitation and delineation of wetlands, looking at the \u201chydro-ecological\u201d boundaries of this ecosystem (including their wetness and flow characteristics).", "formats": [{"name": "GeoTIFF"}, {"name": "EEA:FOLDERPATH"}, {"name": "WWW:URL"}, {"name": "OGC:WMS"}, {"name": "ESRI:REST"}], "keywords": ["Land cover", "biodiversity", "Water Framework Directive", "wetlands ecosystem", "ecosystem", "ecosystem assessment", "wetland", "EEA39", "European", "Biodiversity"], "contacts": [{"name": null, "organization": "European Environment Agency", "position": null, "roles": ["pointOfContact"], "phones": [{"value": null}], "emails": [{"value": "sdi@eea.europa.eu"}], "addresses": [{"deliveryPoint": ["Kongens Nytorv 6"], "city": "Copenhagen", "administrativeArea": "K", "postalCode": "1050", "country": "Denmark"}], "links": [{"href": {"url": "http://www.eea.europa.eu", "protocol": "WWW:LINK-1.0-http--link", "protocol_url": "", "name": "European Environment Agency public website", "name_url": "", "description": null, "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": "information"}}]}, {"name": null, "organization": "European Environment Agency", "position": null, "roles": ["custodian"], "phones": [{"value": null}], "emails": [{"value": "sdi@eea.europa.eu"}], "addresses": [{"deliveryPoint": ["Kongens Nytorv 6"], "city": "Copenhagen", "administrativeArea": "K", "postalCode": "1050", "country": "Denmark"}], "links": [{"href": null}]}], "distancevalue": "100", "distanceuom": "m", "edition": "01.00"}, "links": [{"href": "https://sdi.eea.europa.eu/webdav/datastore/public/eea_r_3035_100_m_extended-wetland-ecosystem_p_2012_v01_r00/", "protocol": "EEA:FOLDERPATH", "rel": "download"}, {"href": "https://sdi.eea.europa.eu/data/5fc1b45a-715a-466e-b576-1be0ced40e2a", "name": "Direct download", "protocol": "WWW:URL", "rel": "download"}, {"href": "https://land.discomap.eea.europa.eu/arcgis/services/Land/Extended_wetland_ecosystem_2012/ImageServer/WMSServer?request=GetCapabilities&service=WMS", "protocol": "OGC:WMS", "rel": "information"}, {"href": "https://land.discomap.eea.europa.eu/arcgis/rest/services/Land/Extended_wetland_ecosystem_2012/ImageServer", "protocol": "ESRI:REST", "rel": "information"}, {"href": "https://sdi.eea.europa.eu/public/catalogue-graphic-overview/5fc1b45a-715a-466e-b576-1be0ced40e2a.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": "5fc1b45a-715a-466e-b576-1be0ced40e2a", "name": "item", "description": "5fc1b45a-715a-466e-b576-1be0ced40e2a", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/5fc1b45a-715a-466e-b576-1be0ced40e2a"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["2012-01-01T00:00:00Z", "2012-12-31T00:00:00Z"]}}, {"id": "c6c68c1f-7c2f-4816-bbed-16cb44e429ef", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[13.47, 53.29], [13.47, 53.43], [13.86, 53.43], [13.86, 53.29], [13.47, 53.29]]]}, "properties": {"themes": [{"concepts": [{"id": "environment"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "biodiversity"}, {"id": "habitat connectivity"}, {"id": "Apidae"}, {"id": "pollination"}, {"id": "kettle holes"}, {"id": "wetlands"}], "scheme": "AGROVOC Multilingual agricultural thesaurus"}, {"concepts": [{"id": "opendata"}, {"id": "pollination service"}, {"id": "metacommunity"}], "scheme": "Individual"}, {"concepts": [{"id": "biodiversity"}, {"id": "ecological community"}, {"id": "Lebensr\u00e4ume und Biotope"}], "scheme": "GEMET - INSPIRE themes, version 1.0"}, {"concepts": [{"id": "Germany"}, {"id": "Brandenburg"}, {"id": "Uckermark"}, {"id": "Quillow"}], "scheme": "Individual"}], "license": "CC BY", "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 Data Centre www.bonares.de. This data were created as part of the ZALF's research activities.\" Although every care has been taken in preparing and testing the data, the ZALF and the BonaRes Data Centre cannot guarantee that the data are correct; neither does the ZALF and the BonaRes Data Centre 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 ZALF and BonaRes Data Centre will not be responsible for any direct or indirect use which might be made of the data.", "updated": "2023-08-16", "type": "Dataset", "created": "2021-05-20", "language": "eng", "title": "Bee diversity in island-like habitats (kettle holes) to assess connectivity in agricultural landscapes - Part 1 of data collection", "description": "During June and July of 2017, wild bees were collected using color traps (blue, yellow and white pans) in small water bodies called kettle holes embedded in agricultural landscapes in the north of Germany. After all wild bees were identified to species level, from a subset of samples we measured the Intertegular distance ITD (distance between the wings) as body size and searched for functional traits regarding sociality (solitary, eusocial, parasitic) nesting type (below- or aboveground), and lecty (poly- or oligolectic). In addition, biotic and abiotic characteristics of these kettle holes were recorded to evaluate how they affect wild bee diversity. These factors included size of the kettle hole, the degree of isolation (number of neighboring kettle holes at different distances), percentage of flowering species and total of plant species (herbs and woody plants). We tested the effect of all these factors on wild bee abundance and bee species richness, as well on body size and functional traits.\n-\nApplied Methods for sampling and identification:\nCollection of individuals using colour traps. One trap had 6 coloured plastic containers (white, blue and yellow) placed in three levels randomly. Water with some drops of soap was added to each container and traps were place in each kettle hole during 48 hours. A total of 4 traps were set up in each kettle hole and a total of 36 kettle holes were studied. After 2 days insects trapped in the water were collected without differentiating the colour of the plastic container. Bee individuals were separated and taken to the lab for further preparation and identification.\n-\nBee specimens were pinned and dried at room temperature. Individuals were identified until species level by specialists K. Rupik from Bielefeld University and C. Saure at the Natural History Museum in Berlin. Information about functional traits regarding sociality, lecty and nesting were compiled from the literature with the final list of species. Body size was characterized as intertegular distance (distance between wings) measured in a subset of randomly selected individuals per species.\n\nResearch domain: Bee diversity", "formats": [{"name": "CSV"}], "keywords": ["biodiversity", "habitat connectivity", "Apidae", "pollination", "kettle holes", "wetlands", "opendata", "pollination service", "metacommunity", "biodiversity", "ecological community", "Lebensr\u00e4ume und Biotope", "Germany", "Brandenburg", "Uckermark", "Quillow"], "contacts": [{"name": "BonaRes Data Centre", "organization": "Leibniz Centre for Agricultural Landscape Research (ZALF)", "position": "Research Platform 'Data Analysis & Simulation' - WG Geodata", "roles": ["publisher"], "phones": [{"value": "+49 33432 82 171"}], "emails": [{"value": "bonares-datenzentrum@zalf.de"}], "addresses": [{"deliveryPoint": ["Eberswalder Strasse 84"], "city": "M\u00fcncheberg", "administrativeArea": "Brandenburg", "postalCode": "15374", "country": "Germany"}], "links": [{"href": 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