{"type": "FeatureCollection", "features": [{"id": "86fa9373-ceb9-4be8-8bef-ba387298d562", "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": "pollinators"}, {"id": "biodiversity"}], "scheme": "AGROVOC Multilingual agricultural thesaurus"}, {"concepts": [{"id": "opendata"}, {"id": "plant functional traits"}, {"id": "landscape ecology"}, {"id": "hoverfly"}], "scheme": "Individual"}, {"concepts": [{"id": "biodiversity conservation"}, {"id": "bee conservation"}, {"id": "Lebensr\u00e4ume und Biotope"}], "scheme": "GEMET - INSPIRE themes, version 1.0"}, {"concepts": [{"id": "Germany"}, {"id": "Brandenburg"}, {"id": "Uckermark"}, {"id": "Quillow"}], "scheme": "Individual"}], "rights": "Restrictions applied to assure the protection of privacy or intellectual property, and any special restrictions or limitations or warnings on using the resource or metadata. Reports, articles, papers, scientific and non - scientific works of any form, including tables, maps, or any other kind of output, in printed or electronic form, based in whole or in part on the data supplied, must contain an acknowledgement of the form: \"Data reused from the BonaRes Data Centre www.bonares.de. This data were created as part of the Other's research activities.\" Although every care has been taken in preparing and testing the data, the Other and the BonaRes Data Centre cannot guarantee that the data are correct; neither does the Other 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 Other and BonaRes Data Centre will not be responsible for any direct or indirect use which might be made of the data. The access to this data is restricted during embargo time. If prior access is requested, contact the data owner / author.", "updated": "2023-08-16", "type": "Dataset", "created": "2022-02-25", "language": "eng", "title": "Pollinator guilds respond contrastingly at different scales to landscape parameters of land-use intensity (Part 1 of data collection, table data_coordinates)", "description": "Wild bee and hoverly species and abundance caught with pan traps (yellow, blue, white) on dry grasslands (n=22) in the AgroScapeLab in three sampling campaigns (May, June, August). Additionally, flowering forb species in the vicinity of traps (r=5m) were recoreded.\n\nResearch domain: Ecology of Agricultural Landscapes\n\nData Collection: Related tables see under Related Identifier", "formats": [{"name": "CSV"}], "keywords": ["pollinators", "biodiversity", "opendata", "plant functional traits", "landscape ecology", "hoverfly", "biodiversity conservation", "bee conservation", "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": null}]}, {"name": "Kolja Bergholz", "organization": "University of Potsdam, Plant Ecology & Nature Conservation", "position": null, "roles": ["author"], "phones": [{"value": null}], "emails": [{"value": "bergholz@uni-potsdam.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": null, "protocol": null, "protocol_url": "", "name": "0000-0003-4443-3214", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Kolja Bergholz", "organization": "University of Potsdam, Plant Ecology & Nature Conservation", "position": null, "roles": ["projectLeader"], "phones": [{"value": null}], "emails": [{"value": "bergholz@uni-potsdam.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": null, "protocol": null, "protocol_url": "", "name": "0000-0003-4443-3214", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Kolja Bergholz", "organization": "University of Potsdam, Plant Ecology & Nature Conservation", "position": null, "roles": ["dataCollector"], "phones": [{"value": null}], "emails": [{"value": "bergholz@uni-potsdam.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": null, "protocol": null, "protocol_url": "", "name": "0000-0003-4443-3214", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Lara Pauline Sittel", "organization": "German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig", "position": null, "roles": ["dataCollector"], "phones": [{"value": null}], "emails": [{"value": "lara-pauline.sittel@idiv.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"name": "Michael Ristow", "organization": "University of Potsdam, Plant Ecology & Nature Conservation", "position": null, "roles": ["dataCollector"], "phones": [{"value": null}], "emails": [{"value": "ristow@uni-potsdam.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"organization": "University of Potsdam, Plant Ecology & Nature Conservation", "roles": ["contributor"]}]}, "links": [{"href": "https://maps.bonares.de/mapapps/resources/apps/bonares/index.html?lang=en&mid=86fa9373-ceb9-4be8-8bef-ba387298d562", "rel": "information"}, {"rel": "self", "type": "application/geo+json", "title": "86fa9373-ceb9-4be8-8bef-ba387298d562", "name": "item", "description": "86fa9373-ceb9-4be8-8bef-ba387298d562", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/86fa9373-ceb9-4be8-8bef-ba387298d562"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["2017-05-15T00:00:00Z", "2017-08-18T00:00:00Z"]}}, {"id": "10.5061/dryad.51c59zwfs", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:00Z", "type": "Dataset", "created": "2023-11-17", "title": "A meta-analysis reveals increases in soil organic carbon following the restoration and recovery of croplands in Southwest China", "description": "unspecifiedIn China, the Grain for Green Program (GGP) is an ambitious project to  convert croplands into natural vegetation, but exactly how changes in  vegetation translate into changes in soil organic carbon remains less  clear. Here we conducted a meta-analysis using 734 observations to explore  the effects of land recovery on the soil organic carbon and nutrients in 4  provinces in Southwest China. Following GGP, the soil organic carbon  content (SOCc) and soil organic carbon storage (SOCs) increased by 33.73%  and 22.39%, respectively. Likewise, soil nitrogen increased, while  phosphorus decreased. Outcomes were heterogeneous, however, depending on  variation in soil and environmental characteristics. Both the regional  land use and cover change indicated by landscape type transfer matrix and  net primary production from 2000 to 2020 further confirmed that GGP  promoted the forest area (2.95%) and regional mean net primary production  (52.94%). Our findings suggest that GGP could enhance soil and vegetation  carbon sequestration in Southwest China and help to develop carbon neutral  strategy.", "keywords": ["2. Zero hunger", "soil organic carbon", "Net primary production", "Grain for Green Program", "FOS: Other natural sciences", "landscape type transfer matrix", "forest restoration", "15. Life on land", "Southwest China"], "contacts": [{"organization": "Guo, Zihao, Zhang, Shuting, Zhang, Lichen, Xiang, Yangzhou, Wu, Jianping,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.51c59zwfs"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.51c59zwfs", "name": "item", "description": "10.5061/dryad.51c59zwfs", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.51c59zwfs"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-12-04T00:00:00Z"}}, {"id": "10.5061/dryad.9ghx3ffpz", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:02Z", "type": "Dataset", "created": "2023-10-24", "title": "The functional significance of tree species diversity in European forests - the FunDivEUROPE dataset", "description": "unspecifiedGeneral design  The FunDivEUROPE project,  short for 'Functional Significance of Forest Biodiversity in  Europe,' aimed at exploring the intricate relationships between  forest biodiversity and ecosystem functioning, focusing specifically on  European forests (Baeten et al., 2019; Baeten et al., 2013; Ratcliffe et  al., 2017; van der Plas et al., 2016a; van der Plas et al., 2016b; van der  Plas et al., 2018). In total, 209 mature forest plots measuring 30 x 30  meters were located in six European countries, ranging from boreal to  Mediterranean zones, and with each representing a major European forest  type: Finland (28 plots, boreal forest), Poland (43 plots, hemiboreal  forest), Germany (38 plots, temperate deciduous forest), Romania (28  plots, mountainous deciduous forest), Italy (36 plots, thermophilous  deciduous forest), and Spain (36 plots, Mediterranean mixed forest). These  plots were primarily established to investigate the role of the richness  of regionally common and economically important \u2018target\u2019 species on  ecosystem functioning and were hence selected to differ as much as  possible in the richness of these. Plot selection was aimed at mimicking  the design of a biodiversity experiment, in which variation in environment  is minimized and diversity is not confounded with composition, as in most  observational studies of diversity. Hence, plots were carefully selected  so that correlations between tree species richness and community  composition, topography (slope, altitude), and potentially confounding  soil factors (texture, depth, pH) were minimized, thus ensuring robust  tests of diversity-ecosystem function relationships (comparative study  design). Most forest plots were historically used for timber production  but are now managed by low-frequency thinning or with minimal  intervention. Hence, species compositions and diversity patterns in  forests are predominantly management-driven and/or are the result of  random species assembly, from the regional species pool. All sites are  considered as mature forests. In total, there were 15 target  species across all 209 plots, and plots were selected so that almost all  possible combinations of these target species were realized. Target  species contributed to more than 90% of the tree biomass in the plots and  therefore we expected them to be most important for ecosystem functioning.  Richness levels of one, two, three, four, and five target species were  replicated 56, 67, 54, 29, and 3 times, respectively, across countries,  and most possible target species compositions were realized. For the  majority of species combinations, we included two or more \u201crealizations\u201d  (not strict replicates, because species abundances differ), which allows  for comparing the importance of species diversity with that of species  composition for this subset of plots. At each richness level, each target  tree species was present in at least one plot, allowing us to  statistically test for the effects of presence/absence of species on  ecosystem functioning. Since species evenness might also affect ecosystem  functioning, all plots were selected to have target species with similar  abundances (with Pielou\u2019s evenness values above 0.6 in &gt; 91% of the  plots). To reach this goal, we <em>a priori</em> decided to  exclude locally rare target species (&lt;2 individuals per plot) in  richness measures. To describe community composition and to estimate  biomass values of each tree in each plot, we identified all stems \u22657.5 cm  in diameter to species and permanently marked them (12,939 stems in  total). More details about the design of the FunDivEUROPE plot network can  be found in Baeten et al. (2013). We determined a high number of basic  data for each of the 209 plots, describing geographic and  geomorphological, as well as soil and bedrock characteristics, see also  Ratcliffe et al (2017). Soil pH was determined in the same samples used  for C and N determination (see below) with a 0.01M  CaCl<sub>2</sub> solution at a ratio of 1:2.5 using a 827 pH  labs Metrohm AG, Herisau, Switzerland; see details in Dawud et al. (2017).  For each plot, we extracted mean annual temperature, temperature  seasonality (standard deviation of mean monthly temperatures), annual  precipitation, and precipitation seasonality (standard deviation of mean  monthly precipitation) from the WorldClim dataset (interpolated from  measurements taken between 1960 and to 1990 and at a spatial resolution of  one square kilometer) and the slope from the GTOPO30\u2014digital elevation  model with a spatial resolution of one square kilometer (data available  from the U.S. Geological Survey); see details in Kambach et al. (2019). We  further quantified several measures of tree diversity, based on the  initial inventory made in each plot, see Baeten et al. (2013). Short  description of all these variables are available in the \u201cMetadata\u201d sheet  of the data file. Ecosystem functions  methodology A major strength of the FunDivEUROPE  project was the general philosophy to measure all ecosystem functions in  all plots, following the same protocol by the same observers across the  six forest types. Measurements are thus directly comparable across plots  and show high coverage. In each of the 209 plots, 27  ecosystem functions were measured. The functions were <em>a  priori</em> classified into six groups reflecting basic ecological  processes (groups 1 to 5 below), and which have established links to  supporting, provisioning, regulating, or cultural ecosystem services.  These functions were also used in Chao et al. (in press): Hill-Chao  numbers allow decomposing gamma-multifunctionality into alpha and beta  components. Ecology Letters. In addition, we quantified timber quality as  an additional ecosystem service. \u00a0 In the  following, we describe the methodology for each measured ecosystem  function/service. (For more details, see also Baeten et al., 2019;  Ratcliffe et al., 2017; van der Plas et al., 2016a; van der Plas et al.,  2016b; van der Plas et al., 2018), and other FunDivEUROPE publications  that focus on specific ecosystem properties and functions. Additional  datasets are stored in the FunDivEUROPE data portal  (https://data.botanik.uni-halle.de/fundiveurope/, logon required to view  most data; all metadata is publicly available). 1.  Nutrient and carbon cycling-related drivers (header in the data table in  parentheses): a.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Earthworm biomass: \u00a0Biomass of all earthworms [g m<sup>-2</sup>] (earthworm_biomass) Earthworm sampling was carried out in spring 2012 in Italy, Germany, and Finland, and in autumn 2012 in Poland, Romania, and Spain. Plots were divided in nine (10 x 10) m subplots. One sample per plot was taken in the center subplot. Sampling close to tree stems was avoided and whenever possible performed, in between multiple, different tree species. At each sampling point, earthworms were sampled by means of a combined method. First litter was handsorted over an area of (25 x 25) cm<sup>2</sup>. After litter removal over an enlarged area of 0.5 m\u00b2, ethological extraction using a mustard suspension was applied. Finally, hand sorting of a soil sample of (25 \u00d7 25) cm<sup>2</sup> and 20 cm depth was performed in the middle of the 0.5 m\u00b2 area. Earthworms were preserved in ethanol (70%) for two weeks, and transferred to a 5% formaldehyde solution for fixation (until constant weight), after which they were transferred to ethanol (70%) again for further preservation and identification. All worms were individually weighed, including gut content, and identified to species level. \u00a0Results per unit area of the three sampling techniques were summed to determine the total earthworm biomass per m\u00b2. For details on earthworm biomass measurements, we refer to De Wandeler et al. (2018; 2016). b.\u00a0\u00a0\u00a0\u00a0\u00a0 Fine woody debris: Number of snags and standing dead trees shorter than 1.3 m and thinner than 5 cm DBH, and all stumps and other dead wood pieces lying on the forest floor (fine_woody_debris) Fine woody debris (FWD) was measured in two circular subplots (radius of 7 m) located in the opposite corners of each plot. All standing dead trees thinner than 5 cm diameter at breast height and snags shorter than 1.3 m, and all stumps and other dead wood pieces lying on the forest floor, were surveyed. In this study, we used the number of FWD pieces in each plot. c.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Microbial biomass: Mineral soil (0\u20135cm layer) microbial biomass carbon [mg C kg<sup>-1</sup>] (microbial_biomass_mineral) For soil sampling, each of the 209 plots was divided into nine 10x10m subplots. A soil sample was taken from five of the nine subplots and mixed to obtain one representative composite sample from each plot. Forest floor and mineral soil horizons (0-5 cm) were sampled separately. Soils were sieved fresh (4mm), stored at 4\u00b0C and analyzed within two weeks. Sampling was performed in spring 2012 in Italy, Germany, and Finland, and in autumn 2012 in Poland, Romania, and Spain. No forest floor was collected from the plots in Germany. Soil microbial biomass C was determined by the chloroform fumigation extraction method, of 10g and 15g (organic and mineral soil, respectively) soil, followed by 0.5 M K<sub>2</sub>SO<sub>4</sub> extraction of both fumigated and unfumigated soils (soil:solution ratio, 1:5). Fumigations were carried out for three days in vacuum desiccators with alcohol-free chloroform. Extracts were filtered (Whatman n\u00b0 42), and dissolved organic carbon in fumigated and unfumigated extracts was measured with a Total Organic Carbon analyser (Labtoc, Pollution and Process Monitoring Limited, UK). Soil microbial biomass C was calculated by dividing the difference of total extract between fumigated and unfumigated samples with a kEC (extractable part of microbial biomass C after fumigation) of 0.45 for biomass C (Joergensen and Mueller, 1996). d.\u00a0\u00a0\u00a0\u00a0\u00a0 Soil carbon stocks: \u00a0Total soil carbon stock in forest floor and 0\u201310 cm mineral soil layer combined [Mg ha<sup>-1</sup>] (soil_c_ff_10) Soil sampling was carried out from May 2012 to October 2012 (i.e. Poland in May 2012, Spain in June 2012, Finland and Germany in August 2012, Romania in September 2012 and Italy in October 2012). Nine forest floor samples and nine cores of mineral soil were collected from each plot and these were subsequently pooled into one sample per plot by each soil layer, i.e. forest floor, 0\u201310cm and 10\u201320cm depths for samples from Germany, Finland, Italy, and Romania. For Poland, the fixed depth was extended to 20\u201330cm and 30\u201340 cm whereas for Spain it was only possible to sample up to the 0\u201310cm layer due to the stoniness of the site. We oven-dried the samples at 55\u00b0C to constant weight, sorted out stones and other materials, ground the forest floor first with a heavy-duty SM 2000-Retsch cutting mill, and we then took subsamples and ground it further into finer particles with a planetary ball mill (PM 400-Retsch) for six minutes at 280rpm. The mineral soil samples were sieved through 2mm diameter mesh. We carried out carbonate removal treatments for those soil samples whose pH value exceeded the threshold point and proved presence of carbonates when tested with a 4N HCl fizz test. We used 6% (w/v) H<sub>2</sub>SO<sub>3</sub> solution and followed the carbonate removal procedure described by\u00a0(Skjemstad and Baldock, 2007). We took subsamples and further ground it into finer particles with a planetary ball mill (PM 400-Retsch) for six minutes at 280 rpm before analyzing soil organic carbon (SOC) with a Thermo Scientific FLASH 2000 soil CN analyzer. Soil organic C stocks were estimated by multiplying the SOC concentrations with soil bulk density, relative root volume and relative stone volume using the formula described in Vesterdal et al., (2008). We also determined the moisture content of the soil samples by oven-dried subsamples at 105\u00b0C and the reported SOC stock is thus on 105\u00b0C dry weight basis.\u00a0 2. Nutrient cycling related processes a.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Litter decomposition: Decomposition of leaf litter using the litterbag methodology [% daily rate] (litter_decomp_day) Litter collection and litterbag construction Leaf litter from all target tree species of the cross-region exploratory platform was collected at tree species-specific peak leaf litter fall between October 2011 and November 2012. Except for the Finnish forests, where freshly fallen leaf litter was collected from the forest floor, litter was collected using suspended litter traps, which were regularly harvested at one to two-week intervals. In all cases, litter was collected nearby, but not within the experimental plots. Litter was then air-dried and stored until the preparation of the litterbags. Litterbags (15 x 15 cm) were constructed using polyethylene fabrics of two different mesh sizes. For the bottom side of the litterbags, we used a small mesh width of 0.5 x 0.5 mm in order to minimize losses of litter fragments, while for the upper side, we used a large mesh width of 5 x 8 mm to allow soil macrofauna access to the litter within bags. Litterbags were filled with 10 g of litter. For litter mixtures, litterbags were filled with equivalent proportion of each litter species. Subsamples of all litter species were weighed, dried at 65\u00b0C for 48 h and reweighed to get a 65\u00b0C dry mass correction factor. Litterbag incubation Within each experimental plot, three litterbags with the plot-specific litter type (either single litter species or specific mixtures) were placed on bare soil after the natural litter layer had been removed, and fixed to the soil by placing chicken wire on top of it. The litterbags were removed from the field when 50\u201360% of the initial litter mass of the region\u2019s fastest decomposing species was remaining (evaluated with an extra set of litterbags that were harvested regularly). As a consequence, the duration of litter decomposition varied among regions. This procedure ensured that litter was sampled at similar decomposition stages across all sites, facilitating meaningful comparisons of litter diversity effects. Litter processing Harvested litterbags were sent to Montpellier where they were dried at 65\u00b0C. Litter was cleaned of pieces of wood, stones or other foreign material that occasionally got into the litterbags. Litter was then weighed, ground to a particle size of 1 mm with a Cyclotec Sample Mill (Tecator, H\u00f6gan\u00e4s, Sweden). To correct for potential soil contamination during decomposition in the field, we determined the ash content of initial and final litter material on all samples and expressed litter mass loss on ash-free litter mass.\u00a0 Litter mass loss was expressed as the percentage of mass lost from each litterbag, calculated as followed: Mass Loss = 100 x (Initial (ash free) mass \u2013 Final (ash free) mass)/Initial (ash free) mass. For details on litter decomposition measurements, we refer to Joly et al. (2017; 2023). b.\u00a0\u00a0\u00a0\u00a0\u00a0 Nitrogen resorption efficiency: Difference in N content between green and senescent leaves divided by N content of green leaves [%] (nutrient_resorption_efficiency) In each plot, fresh leaf and needle samples were collected from the south-exposed sun crown of all dominant tree species during the growing season (June to August) of 2012 and 2013. Twigs with leaves and needles were cut down from six trees per species in the monocultures and from three trees per species in the mixtures. Depending on the local conditions, tree loppers, tree climbers, or ruffles were used for this purpose. The selected material was placed in paper bags and was either oven-dried or air-dried, depending on the facilities available. Furthermore, collection of leaves from the litter traps, as representative of senescent leaves, has been conducted at periods of maximum litterfall during 2012 and 2013. For this purpose, five litter traps per plot were established and the collected litter was separated into the different species it originated from (see \u201cLitter production\u201d below). All samples were ground and analysed for nitrogen and calcium content by means of Near Infra Red Spectroscopy (NIRS) as described in detail by Pollastrini et al. (2016a). For the calibration of the NIRS spectra for the Ca analysis, a subset of samples was analysed with an atom absorption spectrometer (AAS, iCE 3000 series, ThermoScientific, China). Nitrogen resorption efficiency was calculated as follows, taking into account the N content of green and senescent leaves: NRE(%) = 100 x ((N green leaves - N senescent leaves)/(N green leaves)) Furthermore, the estimated NRE was corrected in order to take into account the leaf mass loss occurring during senescence. Thus, NRE was corrected based on the Ca foliar concentration, since Ca is rather immobile and is not resorbed during senescence (Van Heerwaarden et al., 2003). To validate the correction of NRE based on Ca concentrations, the Mass Loss Correction Factors (MLCF) suggested by Vergutz et al. (2012) have also been used. c.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Soil C/N ratio: Soil C/N ratio in forest floor and 0\u201310 cm mineral soil layer combined (soil_cn_ff_10) Soil sampling was carried out between May 2012 and October 2012 in all the regions.\u00a0Nine forest floor samples were collected using a 25 x 25 cm wooden frame, and the mineral soil (0-10 cm layer) was sampled, after forest floor removal, using a cylindrical metal corer. Total soil carbon and nitrogen concentrations were measured with a Thermo Scientific FLASH 2000 soil CN analyser on the forest floor and 0-10 cm layer samples. For full details on soil carbon and nitrogen methodology see Dawud et al. (2017). d.\u00a0\u00a0\u00a0\u00a0\u00a0 Wood decomposition: Decomposition of flat wooden sticks placed on forest floor [% daily rate] (wood_decomp_day) Flat wooden sticks (wooden tongue depressors made of <em>Betula pendula</em> wood) were placed to decompose at each plot of the exploratory platform. Each wooden stick was initially weighed (average of 2.5 g). As the weighing was done on air-dry sticks, subsamples were weighed, dried at 65\u00b0C for 48 h and reweighed to get a 65\u00b0C dry mass correction factor. Within each plot, three wooden sticks were placed on the bare soil after the natural litter layer had been locally removed, and fixed to the soil by placing chicken wire on top of it. The wooden sticks stayed in the field for different durations among regions depending on the mass loss of the region\u2019s fastest decomposing litter species (target of 50 to 60 % mass remaining), that was placed in the field at the same time as the wooden sticks.\u00a0 After field exposure wooden sticks were harvested, dried at 65\u00b0C, and weighed. Mass loss of wooden sticks was expressed as the percentage of initial mass lost, calculated as followed: Mass Loss = 100 x (Initial mass \u2013 Final mass)/Initial mass. For details on wood decomposition measurements, we refer to Joly et al. (2017; 2023). 3. Primary production a.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Fine root biomass: Total biomass of living fine roots in forest floor and 0-10 mineral soil layer combined [g m<sup>-2</sup>] (root_biomass) On each plot for determining fine root biomass, nine soil samples were taken from a predefined grid. The sampling was done in the six countries during May-October 2012. The forest floor was sampled using a wooden frame of size 25 cm x 25 cm, and thereafter the mineral soil was sampled using a cylindrical metal corer with 36 mm of inside diameter. The mineral soil was sampled down to 20 cm, except for the plots in Poland (down to 40 cm) and in Spain (down to 10 cm). Samples were pooled by layer and plot into one sample. Living fine roots (diameter \u2264 2 mm) were separated from the soil samples by hand to two categories, tree roots and ground vegetation roots. After separation, the roots were washed with water to remove adhering soil. Subsequently, the roots were dried at 40\u00b0C until constant mass and weighed for biomass. The root biomass was corrected with a correction factor for soil stoniness (CFstones= 100-(% stones)/100), where the respective volumetric stoniness was estimated with the metal rod method (Tamminen and Starr, 1994) on each plot. For this study, total tree fine root biomass for each plot was calculated (g m<sup>-2</sup>) for the sampled soil layer (forest floor + sampled mineral soil). For further details, see also Fin\u00e9r et al. (2017). b.\u00a0\u00a0\u00a0\u00a0\u00a0 Leaf mass: Leaf Area Index (lai) As a proxy for the leaf mass of each plot, we used the Leaf Area Index (LAI), which is the projected leaf area per unit of ground area. Five measurements of LAI in each plot were carried out at two time points, either early in the morning (shortly before sunrise) or late in the evening (shortly after sunset) in order to work in the presence of diffuse solar radiation and thus reduce the effect of scattered blue light in the canopy. LAI measurements were carried out in early September 2012, before the beginning of leaf shedding, using a Plant Canopy Analyzer LAI-2000 (LI-Cor Inc., Nebraska). With the LAI-2000, the incident light above the canopy and the light transmission below the canopy were measured using one sensor with five fisheye light sensors (lenses), with central zenith angle of 7\u00b0,23\u00b0, 38\u00b0, 53\u00b0 and 68\u00b0 (LAI-2000 manual, Li-Cor). The protocol used in each plot consisted of five measurements within the plots (light transmission below the canopy), and five measurements outside the forest (as proxy of the light incidence above the canopy), in an open space that was in close proximity of the sampled plots. LAI data were processed using Li-Cor\u2019s FV2200 software (LI-COR Biogeosciences, Inc. 2010). The light transmittance measurements of the fifth ring were removed to minimise the boundary effects on LAI. The LAI value per plot was the mean value of the five measurements for each plot. \u00a0For full details of the LAI measurement, see Pollastrini et al., (2016a) c.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Litter production: Annual production of foliar litter dry mass [g] (leaf_litter_production) In each of the 209 plots, five geodetic litter traps of 0.5m\u00b2 collection surface were installed in a regular grid. The sampling period covered a whole year and litters were collected several times. Sampling frequency was irregular and depended on working capacity within a region and seasonality of litter production. The litter was pooled per plot, and stored in plastic bags for transportation from the field site to the local laboratories. After air-drying, litter samples were sorted by species and by different fractions for dry weighing and chemical analysis. The following fractions were used: foliar litter (leaves or needles), woody litter (twigs, branches, bark parts), reproductive litter (flowers, cones, fruits, seeds, fruit capsules, etc.), other (e.g. bud scales, indefinable or small parts). Here, only the foliar litter is reported. A subsample of all litter types per species and region was dried at 65\u00b0C to constant weight to determine the conversion factor from air-dried to oven-dried values of litter dry mass (g). d.\u00a0\u00a0\u00a0\u00a0\u00a0 Photosynthetic efficiency: Chlorophyll fluorescence methodology [ChlF] (photo_eff_tot) Photosynthetic efficiency was measured using chlorophyll fluorescence (ChlF). ChlF measurements were replicated on eight randomly chosen leaves per tree from both the top and the bottom of the crown. The measurements were done on the twigs after the dark adaptation (i.e. after a minimum of 4 hours in a black plastic bag, at ambient temperature). In evergreen conifers, chlorophyll fluorescence measurements were taken in the current year\u2019s needles (i.e. needles sprouted in 2012). For full details of the ChlF measurement see Pollastrini et al. (2016b). e.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Tree productivity: Annual aboveground wood production [Mg C ha<sup>-1</sup> yr<sup>-1</sup>] (tree_growth) Wood cores Tree ring data were used to reconstruct the past annually resolved wood production. Between March and October of 2012, bark-to-pith increment cores (5 mm in diameter) were collected for a subset of trees in each plot following a size-stratified random sampling approach (Jucker et al., 2014a). We cored 12 trees per plot in monocultures and six trees per species in mixtures (except in Poland, where only five cores per species were taken in all plots due to restrictions imposed by park authorities), for a total of 3138 cored trees. Short of coring all trees within a stand, this approach has been shown to provide the most reliable estimates of plot-level productivity when using tree ring data, as it ensured that the size distribution of each plot is adequately represented by the subsample. Wood cores were stored in polycarbonate sheeting and allowed to air dry before being mounted on wooden boards and sanded with progressively finer grit sizes. A high-resolution flatbed scanner (2400 dpi optical resolution) was then used to image the cores. \u00a0From tree rings to aboveground wood production We followed a four-step approach (i\u2013iv) to estimate temporal trends in aboveground wood production (AWP, in MgC ha<sup>-1</sup> yr<sup>-1</sup>) from tree ring data (Jucker et al., 2014a). i.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Measuring growth increments from wood cores We measured yearly radial growth increments (mm yr<sup>-1</sup>) for each cored tree from the scanned images. To minimize measurement errors associated with incorrectly placed ring boundaries, we crossdated each sample against a species-level reference curve obtained by averaging all ring-width chronologies belonging to a given species from a given site. In this process, 188 cores which showed poor agreement with reference curves were excluded from further analysis, giving a final total of 2950 tree ring chronologies. Both radial growth measurements and crossdating were performed using CDendro (Cybis Elektronik &amp; Data, Saltsj\u00f6baden, Sweden). Here we report data from the five-year period between 2007 and 2011. ii. Converting diameter increments into biomass growth We combined radial increments and allometric functions to express the growth rate of individual trees in units of biomass. We calculated the average yearly biomass growth between 2007\u20132011 (G, kgC yr<sup>-1</sup>) of cored trees as G = (AGBt<sub>2</sub> \u2013 AGBt<sub>1</sub>)/ \u0394t, where AGBt<sub>2</sub> is the tree\u2019s biomass, estimated with equations presented in Jucker et al. (2014b) in the most recent time period (i.e., end of 2011) and AGBt<sub>1</sub> is its biomass at the previous time step (i.e., end of 2006), \u0394t and is the elapsed time (i.e., five years). AGBt<sub>1</sub> was estimated by replacing current diameter and height measurements used to fit biomass equations with past values. Past diameters were reconstructed directly from wood core samples by progressively subtracting each year\u2019s diameter increment. Height growth was estimated by using height-diameter functions to predict the past height of a tree based on its past diameter. iii. Modelling individual tree biomass growth We modelled the biomass growth of each species as a function of tree size, competition for light, species richness, and a random plot effect: log(G<sub>i</sub>) = \u03b1<sub>j[i]</sub> + \u03b2<sub>1</sub> x log(D<sub>i</sub>) + \u03b2<sub>2</sub> x CI<sub>i</sub> + \u03b2<sub>3</sub> x SR<sub>j</sub> + \u03b5<sub>i</sub>\u00a0 where G<sub>i</sub>, D<sub>i</sub> and CI<sub>i</sub> are, respectively, the biomass growth, stem diameter and crown illumination index of tree i growing in plot j; SR<sub>j</sub> is the species richness of plot j; \u03b1<sub>j</sub> is a species\u2019 intrinsic growth rate for a tree growing in plot j; \u03b2<sub>1-3</sub> are, respectively, a species\u2019 growth response to size, light availability and species richness; and \u03b5<sub>i</sub> is the residual error. The structure of the growth model is adapted from Jucker et al. (2014b) and was fitted using the lmer function in R. Model robustness was assessed both visually, by comparing plots of predicted vs observed growth, and through a combination of model selection and goodness-of-fit tests (AIC model comparison and R<sup>2</sup>). Across all species, individual growth models explained much of the variation in growth among trees (Jucker et al., 2014a). iv. Scaling up to plot-level AWP To quantify AWP at the plot level, we used the fitted growth models to estimate the biomass growth of all trees that had not been cored. For each plot, we then summed the biomass growth of all standing trees to obtain an estimate of AWP. Growth estimates were generated using the predict.lmer function in R. f.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Tree biomass: Aboveground biomass of all trees [Mg C ha<sup>-1</sup>] (tree_biomass) In each plot, the aboveground biomass (AGB, Mg C ha<sup>-1</sup>) of all the individual trees was estimated using tree diameter and height measurements in combination with species-specific biomass functions (see above). Biomass estimates of the individual trees were then summed to quantify the plot-level tree biomass. g.\u00a0\u00a0\u00a0\u00a0\u00a0 Understorey biomass: Dry weight of all understorey vegetation in a quadrant [g] (total_understorey_weight) In three subplots in each plot (upper right, central, lower left), a quadrant of 5 m x 5 m was marked for identification and estimation of cover of understorey vascular plant species (both woody and non-woody). Within each quadrant, all understorey vegetation was identified to species and afterwards clipped in a zone of 0.5 m x 0.5 m, where vegetation was relatively abundant and the composition was representative of the whole quadrant. The biomass samples (g) were dried for 48 h at 70\u00b0C before weighing. 4 4.\u00a0Regeneration a.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Sapling growth: Growth of saplings up to 1.60 m tall [cm] (sapling_growth) Sapling growth measurements (cm) were taken in 2012 on a total of 30 saplings per species wherever possible. Saplings (up to 1.60 m tall) of all tree species in the regional species pool were selected in a subplot of 4x4 m located in the central part of the main plot. Sapling growth was quantified as the distance between the bud scars (internodes) along the main stem of the last five years (i.e. from 2007 to 2011), without considering the shoot of the current growing season. For details on the methodology, see Bastias et al. (2019). b.\u00a0\u00a0\u00a0\u00a0\u00a0 Tree seedling regeneration: Number of saplings up to 1.60 m tall (regeneration_seedlings) Field sampling for tree seedling regeneration was carried out at the same time and in the same subplot as the tree juvenile regeneration (see below). Tree seedling regeneration was quantified as the number of tree seedlings (i.e. less than a year old) of all tree species in the regional species pool. For details on the methodology, see Bastias et al. (2019). c.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Tree juvenile regeneration: Number of tree seedlings less than a year old (regeneration_juveniles) Field sampling to quantify regeneration was carried out in 2012, from April to late August, in a subplot of 4x4m (16m2) delimited in the central part of the main plot. Tree juvenile regeneration was quantified as the number of sapling trees of tree species in the regional species pool over one year old and up to 1.60 m tall. For details on the methodology, see Bastias et al. (2019). 5 5.\u00a0Resistance to disturbance a.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Resistance to drought: Difference in carbon isotope composition in wood cores between dry and wet years [\u2030] (wue) For each plot, we randomly selected six trees among the 12 largest ones (i.e. largest diameter at breast height, DBH). For the mixed plots, three trees per species were randomly selected among the six largest trees of each species. This selection was conducted as to only select dominant and/or co-dominant trees in order to avoid confounding factors related to light interception. From each selected tree, a wood core was extracted at breast height during the summers of 2012 and 2013. For each site, we selected two years with contrasting climatic conditions during the growing season (dry vs. wet year) during the 1997-2010 period, see Grossiord et al. (2014) for full details. Latewood samples from these two years were carefully extracted from each wood core. The late wood sections from a given year and a given species in a given plot were bulked and analyzed for their carbon isotope composition (\u03b4<sup>13</sup>C, \u2030) with a mass spectrometer. By only selecting latewood sections, we characterized the functioning of the trees during the second part of the growing season and avoided potential effects related to the remobilization of stored carbohydrates from the previous growing season or to a favorable spring climate. Plot-level \u03b4<sup>13</sup>C was calculated as the basal-area weighted average value of species-level \u03b4<sup>13</sup>C measurements. Soil drought exposure in each forest stand was calculated as the stand-level increase in carbon isotope composition of late wood from the wet to the dry year (\u0394\u03b4<sup>13</sup>CS). For more details on resistance to drought measurements, we refer to Grossiord et al. 2014 (2014). b.\u00a0\u00a0\u00a0\u00a0\u00a0 Resistance to insect damage: Foliage not damaged by insects [%] (resistance_insects) As for fungal pathogens sampling (see below), we estimated insect herbivory on six trees per species in monocultures and three trees per focal species in mixed forests. The herbivory assessment was done once, from late spring to early summer (see periods on fungal pathogens protocol below). The insect herbivory protocol was derived from the ICP Forests manual. It was adapted to better account for total insect damage by observing the whole tree crown, instead of the \u201cassessable crown\u201d only. Damage on the crown exposed to sunlight and in the shade was recorded separately, as foliar loss may be also due to competition for light or natural pruning in the shaded part, particularly in heliophilous tree species. We considered damage as leaf area loss or shoot mortality i.e. defoliation. To estimate herbivore impact, we compared the sampled trees to a \u201creference tree\u201d, i.e. a healthy tree with intact foliage in its vicinity. Using binoculars, we estimated the proportion of defoliation in the living crown (i.e. the crown excluding the dead branches) in both parts of the crown (sunlight-exposed PDL and in the shade PDS) and put the estimates in one out of seven percentage classes: 0%, 0.5-1%, 1-12.5%, 12.5-25%, 25-50%, 50-75% and &gt; 75% damage. The assessment was done from at least two sides of the crown to account for all damage. When a different score was attributed from different sides to a focal tree, the mean of damage class median was used. The total percent of defoliation was calculated as the natural logarithm of the sum of PDL and PDS. For further details on the methodology, see Guyot et al. (2016). c.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Resistance to mammal browsing: Twigs not damaged by browsers [%] (lack_browsing) All plots were sampled using four 5m x 5m subplots located in the same areas of each plot.\u00a0 Within each of the four 5x5m subplots each woody species individual was visually inspected for browsing damage (bitten twigs).\u00a0 When browsing was found, the species was recorded, an estimation of the percentage of twigs browsed (between a height of 0.5\u20132 m) was made (biomass removed), and the stem diameter (at the base) and upper and lower limits of browsing were recorded. With these data, a plot-level average of the percentage of twigs browsed was calculated, and resistance to mammal browsing was defined as 100 - % of twigs browsed. d.\u00a0\u00a0\u00a0\u00a0\u00a0 Resistance to pathogen damage: Foliage not damaged by pathogens [%] (no_pathogen_damage) Fungal pathogen damage was assessed over a two-week period at each plot during the growing period, over two years. Foliage was collected from Italy (June-July 2012), Germany (July 2012), Finland (August 2012), Spain (June 2013), Romania (July 2013), and Poland (July-August 2013). In each plot, the six trees with the largest DBH per species were selected for trees within monoculture plots, and three trees with the largest DBH per species for trees within mixture plots. Foliage (leaves and shoots) samples were collected from branches from two levels of the tree canopy (25-60 leaves and 10 current-year shoots per branch) for each focal tree species. The number of leaves sampled from each focal tree and the number of plots within each tree species richness levels are enumerated in Table S8 in van der Plas et al. (2016a).\u00a0 Visual assessments for fungal pathogen damages were conducted on fresh leaves within one day of sampling. Leaves and shoots were assessed for four classes of fungal damages: oak powdery mildew and leaf spots for the broadleaved tree species, and rust and needle cast for the conifer species. The number of leaves or shoots with the respective damages per tree was recorded, as well as the number of leaves and shoots free from fungal pathogen damage, i.e. healthy foliage. To obtain a value of healthy foliage at the plot level, the sum of all healthy foliage for all trees within the plot was calculated and this was divided by the total number of foliage replicates to acquire a plot-level proportion of healthy foliage. All assessments were conducted by one person to avoid observer bias. For details on the sampling effort, we refer to Nguyen et al.(2016). e.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Tree growth recovery: Ratio between post-drought growth and growth during the respective drought period (tree_growth_recovery) Following Lloret et al. (Lloret et al., 2011), growth recovery was defined as the ability to recover growth rates (see tree productivity section) after a decline in growth experienced during the low-growth period (see growth resistance section). It corresponds to the ratio between the average post-drought growth in the five years after a drought year and the growth during the respective low-growth year. Values less than 1 indicate a decline in growth after the drought year, while values greater than one indicate (partial) recovery. f.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Tree growth resilience: Ratio between growth after and before the drought period (tree_growth_resilience) Following Lloret et al. (Lloret et al., 2011), growth resilience was defined as the capacity of the forest stand to return to pre-drought growth (see tree productivity section) levels after a drought and is estimated as the ratio between average growth in the five years after and before the low-growth period (see growth resistance section). g.\u00a0\u00a0\u00a0\u00a0\u00a0 Tree growth resistance: Ratio of tree growth during a drought period and growth during the previous five-year high-growth period (tree_growth_resistance) Following Lloret et al. (Lloret et al., 2011), growth resistance was quantified by comparing tree growth in a low-growth year to the mean growth in the preceding five years. The year with the lowest growth across the regions was 2003, with the exception of Germany and Spain, where the lowest growth was in 1998 and 2005, respectively. 1998 and 2003 were known as drought years across Europe, with the exception of Spain where 2005 was even drier. Growth resistance was defined as the reversal of the reduction in growth (methodology described in the tree productivity section) during the drought: as the ratio of growth during the low-growth year and the growth during the previous five-year high-growth period. The larger the value, the greater the resistance of tree growth to drought. h.\u00a0\u00a0\u00a0\u00a0\u00a0 Tree growth stability: Mean annual tree growth divided by standard deviation in annual tree growth between 1992 and 2011 (tree_growth_stability) Using the annual aboveground wood production (AWP, see tree productivity section above), for each plot the growth stability was calculated as: mean(AWP) / <em>sd(AWP)</em> where mean(AWP) is the temporal mean AWP and <em>sd(AWP)</em> is the standard deviation in AWP between 1992 and 2011. See Jucker <em>et al.</em> (2014) for more details. 6 6.\u00a0Timber quality a.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Stem quality: Mean plot silvicultural quality assessment based on stem characteristics (timber_quality) For timber quality measurements, in each plot, dendrometric data and externally visible stem characteristics were recorded. The silvicultural quality assessment was based on stem characteristics that can be measured and evaluated non-destructively and rapidly along with a measurement of potentially influencing factors at the tree- and stand-level. For each tree within a plot, total height, height of the crown base, height of the lowest dead branch (&gt; 1 cm diameter), and type of fork (or steeply angled branch) were measured. In addition, the presence of the following stem quality parameters was recorded: curving, stem lean, epicormic branching, coppicing, pathogenic, and other defects. Due to the multiple factors constituting stem quality and wood quality, a four-class stem quality grading scheme was used to aggregate all stem quality parameters collected for each tree into an appropriate stem quality score, allowing for the analysis of a single response variable across all regions, species diversity levels and compositions; see Table 1 in Benneter et al (2018), with quality class D=1 being the lowest, and class A=4 being the highest quality class. The assessment of stem quality parameters was limited to the butt log of the tree, which represented the lowest 5 meters of the stem for broadleaved tree species and a maximum of 10 meters from the stem base for conifers. Multiples of the 5-meter section were only considered if the second log showed at least quality class C=2, but only if the green crown base was above the section considered. It has been estimated that for most commercial species in Europe, these butt logs comprise up to 50-70 % (softwood) and 80-95 % (hardwood) of the total commercial tree value. Plot-level timber quality was then calculated as the average timber quality of all the individual trees. For further details, see Benneter et al. (2018). We further quantified the diversity of several forest-associated taxonomic groups (bats, birds, spiders, insects, earthworms, fungal pathogens, soil microbes, understorey plants, and their multi-diversity and multi-abundance/-activity indices) and many aspects of habitat quality (tree functional and structural diversity), in each plot; the respective data can be found here: Allan, E. et al. (2019). Tree diversity is key for promoting the diversity and abundance of forest\u2010associated taxa in Europe [Dataset]. Dryad. https://doi.org/10.5061/dryad.sf7m0cg22. See also: Ampoorter, E. et al. 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Continental mapping of forest ecosystem functions reveals a high but unrealised potential for forest multifunctionality. Ecol Lett, 21(1): 31-42. Van Heerwaarden, L.M., Toet, S. and Aerts, R., 2003. Current measures of nutrient resorption efficiency lead to a substantial underestimation of real resorption efficiency: facts and solutions. Oikos 101: 664-669. Vergutz, L., Manzoni, S., Porporato, A., Novais, R.F. and Jackson, R.B., 2012. Global resorption efficiencies and concentrations of carbon and nutrients in leaves of terrestrial plants. Ecological Monographs 82: 205-220. Vesterdal, L., Schmidt, I.K., Callesen, I., Nilsson, L.O. and Gundersen, P., 2008. Carbon and nitrogen in forest floor and mineral soil under six common European tree species. Forest Ecol Manag, 255(1): 35-48.", "keywords": ["Ecology", "FunDivEUROPE", "Biodiversity", "FOS: Earth and related environmental sciences", "15. Life on land", "6. Clean water", "multifunctionality", "13. Climate action", "FOS: Biological sciences", "11. Sustainability", "Ecosystem functioning", "14. Life underwater", "Ecology", " Evolution", " Behavior and Systematics", "Nature and Landscape Conservation"], "contacts": [{"organization": "Scherer-Lorenzen, Michael, Allan, Eric, Ampoorter, Evy, Avacaritiei, Daniel, Baeten, Lander, Barnoaiea, Ionut, Bastias, Cristina C., Bauhus, J\u00fcrgen, Benavides, Raquel, Benneter, Adam, Berger, Sigrid, Bonal, Damien, Bouriaud, Olivier, Bruelheide, Helge, Bussotti, Filippo, Carnol, Monique, Castagneyrol, Bastien, Che\u0107ko, Ewa, Coomes, David, Coppi, Andrea, Cosofret, Cosmin, Danila, Iulian, Dawud, Seid Muhie, De Wandeler, Hans, Domisch, Timo, Duduman, Gabriel, Fin\u00e9r, Leena, Fischer, Markus, Fotelli, Mariangela, Gessler, Arthur, Gimeno, Teresa E., Grossiord, Charlotte, Guyot, Virginie, H\u00e4ttenschwiler, Stephan, Jactel, Herv\u00e9, Jaroszewicz, Bogdan, Joly, Fran\u00e7ois\u2010Xavier, Jucker, Tommaso, Koricheva, Julia, L\u00f3pez-Quiroga, David, Milligan, Harriet, M\u00fcller, Sandra, Muys, Bart, Nguyen, Diem, Pollastrini, Martina, Rabasa, Sonia G., Radoglou, Kalliopi, Ratcliffe, Sophia, Raulund\u2010Rasmussen, Karsten, Ruiz\u2010Benito, Paloma, Seidl, Rupert, Seiferling, Ian, Selvi, Federico, Smerczy\u0144ski, Ireneusz, Stenlid, Jan, Valladares, Fernando, van der Plas, Fons, Verheyen, Kris, Vesterdal, Lars, von Wilpert, Klaus, Wirth, Christian, Zavala, Miguel A.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.9ghx3ffpz"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.9ghx3ffpz", "name": "item", "description": "10.5061/dryad.9ghx3ffpz", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.9ghx3ffpz"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-11-06T00:00:00Z"}}, {"id": "10.5061/dryad.ns92q", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:05Z", "type": "Dataset", "title": "Data from: Soil carbon response to woody plant encroachment: Importance of spatial heterogeneity and deep soil storage", "description": "unspecified1. Recent global trends of increasing woody plant abundance in  grass-dominated ecosystems may substantially enhance soil organic carbon  (SOC) storage and could represent a strong carbon (C) sink in the  terrestrial environment. However, few studies have quantitatively  addressed the influence of spatial heterogeneity of vegetation and soil  properties on SOC storage at the landscape scale. In addition, most  studies assessing SOC response to woody encroachment consider only surface  soils, and have not explicitly assessed the extent to which deeper  portions of the soil profile may be sequestering C. 2. We quantified the  direction, magnitude, and pattern of spatial heterogeneity of SOC in the  upper 1.2 m of the profile following woody encroachment via  spatially-specific intensive soil sampling across a landscape in a  subtropical savanna in the Rio Grande Plains, USA, that has undergone  woody proliferation during the past century. 3. Increased SOC accumulation  following woody encroachment was observed to considerable depth, albeit at  reduced magnitudes in deeper portions of the profile. Overall, woody  clusters and groves accumulated 12.87 and 18.67 Mg C ha-1 more SOC  compared to grasslands to a depth of 1.2 m. 4. Woody encroachment  significantly altered the pattern of spatial heterogeneity of SOC to a  depth of 5 cm, with marginal effect at 5-15 cm, and no significant impact  on soils below 15 cm. Fine root density explained greater variability of  SOC in the upper 15 cm, while a combination of fine root density and soil  clay content accounted for more of the variation in SOC in soils below 15  cm across this landscape. 5. Synthesis: Substantial SOC sequestration can  occur in deeper portions of the soil profile following woody encroachment.  Furthermore, vegetation patterns and soil properties influenced the  spatial heterogeneity and uncertainty of SOC in this landscape,  highlighting the need for spatially specific sampling that can  characterize this variability and enable scaling and modeling. Given the  geographic extent of woody encroachment on a global scale, this  undocumented deep soil C sequestration suggests this vegetation change may  play a more significant role in regional and global C sequestration than  previously thought.", "keywords": ["2. Zero hunger", "deep soil carbon", "13. Climate action", "\u03b413C value", "landscape scale", "woody plant encroachment", "15. Life on land", "pattern of spatial heterogeneity", "SOC storage", "subtropical savanna"], "contacts": [{"organization": "Zhou, Yong, Boutton, Thomas W., Wu, X. Ben,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.ns92q"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.ns92q", "name": "item", "description": "10.5061/dryad.ns92q", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.ns92q"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-03-10T00:00:00Z"}}, {"id": "10.5194/bg-10-3691-2013", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:10Z", "type": "Journal Article", "created": "2013-01-14", "title": "A meta-analysis on the impacts of partial cutting on forest structure and carbon storage", "description": "<p>Abstract. Partial cutting, which removes some individual trees from a forest, is one of the major and widespread forest management practices that can significantly alter both forest structure and carbon (C) storage. Using 746 observations from 82 publications, we synthesized the impacts of partial cutting on three variables associated with forest structure (i.e. mean annual growth of diameter at breast height (DBH), basal area (BA), and volume) and four variables related to various C stock components (i.e. aboveground biomass C (AGBC), understory C, forest floor C, and mineral soil C). Results shows that the growth of DBH elevated by 112% after partial cutting, compared to the uncut control, while stand BA and volume reduced immediately by 34% and 29%, respectively. On average, partial cutting reduced AGBC by 43%, increased understory C storage by 392%, but did not show significant effects on C storages on forest floor and in mineral soil. All the effects on DBH growth, stand BA, volume, and AGBC intensified linearly with cutting intensity (CI) and decreased linearly with the number of recovery years (RY). In addition to the strong impacts of CI and RY, other factors such as climate zone and forest type also affected forest responses to partial cutting. The data assembled in this synthesis were not sufficient to determine how long it would take for a complete recovery after cutting because long-term experiments were rare. Future efforts should be tailored to increase the duration of the experiments and balance geographic locations of field studies.                         </p>", "keywords": ["Biomass (ecology)", "0106 biological sciences", "Sustainable forest management", "Volume (thermodynamics)", "Diameter at breast height", "Forest Carbon Sequestration", "Estimation of Forest Biomass and Carbon Stocks", "Quantum mechanics", "01 natural sciences", "Environmental science", "Basal area", "Agricultural and Biological Sciences", "Life", "Forest structure", "QH501-531", "Development and Impacts of Bioenergy Crops", "FOS: Mathematics", "Climate change", "Carbon stock", "Agroforestry", "Biology", "QH540-549.5", "Nature and Landscape Conservation", "QE1-996.5", "Global and Planetary Change", "Understory", "Forest management", "Ecology", "Geography", "Physics", "Confidence interval", "Statistics", "Canopy", "Life Sciences", "Geology", "Forestry", "15. Life on land", "Clearcutting", "Climate Change Impacts on Forest Carbon Sequestration", "Forest Site Productivity", "FOS: Biological sciences", "Environmental Science", "Physical Sciences", "Tree Height-Diameter Models", "Agronomy and Crop Science", "Biomass Estimation", "Animal science", "Mathematics"]}, "links": [{"href": "https://doi.org/10.5194/bg-10-3691-2013"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Biogeosciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/bg-10-3691-2013", "name": "item", "description": "10.5194/bg-10-3691-2013", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/bg-10-3691-2013"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-01-14T00:00:00Z"}}, {"id": "10.5281/zenodo.13975260", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:43Z", "type": "Dataset", "title": "Soil parameters measured in European Mole (Talpa europaea) mounds and nearby control areas on a meadow near Lad, Hungary", "description": "Soil parameters measured by the near-infrared device of Agrocares Ltd (the Netherlands): pH(H2O), soil organic matter (%), P (M3) (mg/kg), total nitrogen (g/kg), exchangeable K, Mg and Ca (mmol/kg), organic carbon (g/kg), potentially mineralizable nitrogen (g/kg), cation exchange capacity (mmol/kg), total Al (g/kg), total Fe (g/kg), clay (%) and soil moisture (%).", "keywords": ["comparison", "Landscape ecology", "nature conservation", "land use", "European mole", "", "effects", "landscape"], "contacts": [{"organization": "Centeri, Csaba", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13975260"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13975260", "name": "item", "description": "10.5281/zenodo.13975260", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13975260"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-23T00:00:00Z"}}, {"id": "10261/366352", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:20Z", "type": "Journal Article", "created": "2024-06-14", "title": "Modelling of gully widening, a review. Implications for research on gully evolution and restoration", "description": "Open AccessGully erosion is recognised as a major soil degradation process, with gully growth being a complex phenomenon that is controlled by different processes: incision, gully headcut retreat and gully widening, coupling at different spatial and temporal scales. While gully modelling research has paid considerable attention to headcut retreat processes and incision, our review of the available literature in Web of Science database shows that less attention has been paid to the modelling of gully widening processes. This might hamper progress on gully evolution studies or on gully control and restoration programmes. Our review has found seven models described in the indexed literature: three of them empirical, three based on processes, and a seventh one that can be classified as hybrid. The latter, despite being based on process-based equations, is simplified and requires empirical calibration for implementation. Our review has also noted a limited number of publications using these models, rather for validation or for case studies, with very few examples of models used outside the team that developed it. Of the four process-based models, two of them are the most comprehensive - BSTEM and GULTEM - both incorporating a combination of processes to predict bank failure based on soil, climate and vegetation parameters, coupled with others describing the effect of concentrated channel flow. A third one, the Bank Failure Model (hereafter BFM), is also embedded in the well know landscape evolution model CHILD. Of the seven models identified, only two of them, BSTEM and BFM through CHILD, are directly available to potential users with access to executable versions and instructions, while the others need to be requested from the authors or built from the published equations. The models cover a wide range of spatial and temporal scales, from event to centuries, and from gully stretch to regional scale. Our review suggests that process-based models are the ones providing the most comprehensive approach, especially those including geotechnical approaches, although they would benefit from further development to include wider spatial and temporal scales. This research suggests that more studies and field data are required for calibration, understanding lateral flows, wetting and drying cycles, tension crack prediction, and integrating widening with other gully erosion processes. They should also include further testing and validation of available models beyond the teams that developed them, ideally in model intercomparison exercises.", "keywords": ["Flow erosion", "Bank collapse", "Geotechnical", "Landscape"]}, "links": [{"href": "https://doi.org/10261/366352"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth-Science%20Reviews", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10261/366352", "name": "item", "description": "10261/366352", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/366352"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-08-01T00:00:00Z"}}, {"id": "10.5281/zenodo.14506215", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:52Z", "type": "Report", "title": "More than a Dialogue between actors, seeking the integration of soil-based principles in agroecological systems: Synthesis of Into-DIALOGUE outcomes", "description": "The adoption of agroecological approaches is currently relatively limited to pioneering farmers and farmer associations in the EJP-Soil countries (included Turkey); and although the PRACTICES are being stimulated through the European Union Common Agricultural Policy (CAP) and some programmes in Turkey, the implementation of sustainable agroecological SYSTEMS is until now not promoted by specific policies in these agricultural landscapes.The Into-DIALOGUE project has sought to identify why the conjunction of various practices, which farmers are already selectively implementing, is complicated and slow to combine as a whole, and on a landscape or a territorial scale (which would constitute a SYSTEM). Does it depend on the ecological identity of the farmers? Of the slowness in the development of policies and measures? Of the characteristics of the farms?.... This report presents the synthesis of the work carried out by Into-DIALOGUE partners and links to the documents in which the most relevant information and results are presented.", "keywords": ["Agroecological Systems", "Agrarian Landscape Characterization", "Agroecological practices", "Farmers Ecological Identity", "Common Agricultural Policy"], "contacts": [{"organization": "Asins-Velis, Sabina, \u00dcn, Akin,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14506215"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14506215", "name": "item", "description": "10.5281/zenodo.14506215", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14506215"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-12-17T00:00:00Z"}}, {"id": "10261/279272", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:17Z", "type": "Journal Article", "created": "2022-02-21", "title": "How Socio-Economic Drivers Explain Landscape Soil Erosion Regulation Services in Polish Catchments", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Most studies that address the relationship between socio-economic characteristics and soil erosion focus on the effects of soil erosion on socio-economic conditions at different levels, from global to smallholder. Few, if any, efforts are made to address the influence of socio-economic variables on the soil erosion rate as an indicator of landscape degradation. The present study was carried out using spatial data from 402 catchments that cover Poland, to find out how socio-economic variables, which include area-weighted average income per capita (PLN km\u22122), area-weighted average gross domestic product (PLN km\u22122), population density (person km\u22122), and human development index can drive the soil erosion rate (kg ha\u22121 yr\u22121), along with annual precipitation, soil and geomorphological variables that include soil organic carbon content, soil water content, clay ratio, stream gradient, and terrain slope. The results showed that the soil erosion rate is indirectly driven by the socio-economic variables in the study catchments, as it is alleviated by increasing population density, the area-weighted average gross domestic product, and the human development index. Furthermore, analyzing the incremental relationship between soil erosion rate and the area-weighted average of socio-economic variables revealed that no uniform change can be observed in the relationship between the area-weighted average socio-economic variables and soil erosion in the study catchments.</p></article>", "keywords": ["HDI", "2. Zero hunger", "Conservation of Natural Resources", "landscape; ecosystem services; soil erosion regulation; area-weighted average income per capita; area-weighted average GDP; HDI", "04 agricultural and veterinary sciences", "15. Life on land", "Area-weighted average income per capita", "01 natural sciences", "Article", "Carbon", "Area-weighted average GDP", "Soil erosion regulation", "Soil", "Socioeconomic Factors", "13. Climate action", "11. Sustainability", "Ecosystem services", "Humans", "0401 agriculture", " forestry", " and fisheries", "Landscape", "Poland", "Environmental Monitoring", "Soil Erosion", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://www.mdpi.com/1660-4601/19/4/2372/pdf"}, {"href": "https://www.mdpi.com/1660-4601/19/4/2372/pdf"}, {"href": "https://doi.org/10261/279272"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/International%20Journal%20of%20Environmental%20Research%20and%20Public%20Health", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10261/279272", "name": "item", "description": "10261/279272", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/279272"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-02-18T00:00:00Z"}}, {"id": "10.5281/zenodo.17000055", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:21:15Z", "type": "Dataset", "title": "Soil parameters measured in European Mole (Talpa europaea) mounds and nearby control areas on a meadow near Csom\u00e1d, Hungary", "description": "Soil parameters measured by the near-infrared device of Agrocares Ltd (the Netherlands): pH(H2O), soil organic matter (%), P (M3) (mg/kg), total nitrogen (g/kg), exchangeable K, Mg and Ca (mmol/kg), organic carbon (g/kg), potentially mineralizable nitrogen (g/kg), cation exchange capacity (mmol/kg), total Al (g/kg), total Fe (g/kg), clay (%) and soil moisture (%).", "keywords": ["comparison", "Landscape ecology", "nature conservation", "land use", "European mole", "", "effects", "landscape"], "contacts": [{"organization": "Centeri, Csaba", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.17000055"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.17000055", "name": "item", "description": "10.5281/zenodo.17000055", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.17000055"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-23T00:00:00Z"}}, {"id": "111731d9-b65d-4211-a754-d1a16ccb49ba", "type": "Feature", "geometry": null, "properties": {"updated": "2025-09-20T08:25:15Z", "type": "Dataset", "language": "en", "title": "National Ecosystem and Ecosystem Services Map - Ecosystem Service Stock Map: Soil Carbon", "description": "This dataset contains a raster file showing the contribution of land to the regulation of greenhouse gases (carbon) through carbon sequestration associated with the soil.  This dataset is part of a dataset series that establishes an ecosystem service maps (national scale) for a set of services prioritised through stakeholder consultation and any intermediate layers created by Environment Systems Ltd in the cause of the project. The individual dataset resources in the datasets series are to be considered in conjunction with the project report: https://www.npws.ie/research-projects/ecosystems-services-mapping-and-assessment  The project provides a National Ecosystem and Ecosystem Services (ES) map for a suite of prioritised services to assist implementation of MAES (Mapping and Assessment of Ecosystems and their services) in Ireland.  This involves stakeholder consultation for identification of services to be mapped, the development of a list of indicators and proxies for mapping, as well as an assessment of limitations to ES mapping on differing scales (Local, Catchment, Region, National, EU) based on data availability. Reporting on data gaps forms part of the project outputs.  The project relied on the usage of pre-existing data, which was also utilised to create intermediate data layers to aid in ES mapping. For a full list of the data used throughout the project workings, please refer to the project report.", "formats": [{"name": "HTML"}], "keywords": ["biota", "ecosystem", "ecosystem-services", "environment", "geoscientificinformation", "habitat-protection", "habitats-and-biotopes", "heritage", "ie", "ireland", "landscape", "national-biodiversity-plan", "national-parks-and-wildlife-service", "npws", "soil"], "contacts": [{"organization": "Department of Housing, Local Government and Heritage", "roles": ["creator"]}, {"organization": "https://data.gov.ie/organization/department-of-housing-planning-community-and-local-government", "roles": ["publisher"]}]}, "links": [{"href": "https://dahg.maps.arcgis.com/apps/MapSeries/index.html?appid=cb5040a4a19645b6b424bed940c54fff"}, {"href": "https://www.npws.ie/sites/default/files/general/MAES15_ESmap_SoilCarbon_Final.zip"}, {"href": "http://data.europa.eu/88u/dataset/111731d9-b65d-4211-a754-d1a16ccb49ba~~1"}, {"rel": "self", "type": "application/geo+json", "title": "111731d9-b65d-4211-a754-d1a16ccb49ba", "name": "item", "description": "111731d9-b65d-4211-a754-d1a16ccb49ba", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/111731d9-b65d-4211-a754-d1a16ccb49ba"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "10.5281/zenodo.4384105", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:21:23Z", "type": "Software", "title": "A Colab-Python script code to identify palaeo-landscape features", "description": "Open Access{'references': ['1. Python Software Foundation. Python Language Reference. 2020. Available: http://www.python.org', '2. Wu Q. geemap: A Python package for interactive mapping with Google Earth Engine. Journal of Open Source Software. 2020;5: 2305', '3. Bisong E. Google Colaboratory. In: Bisong E, editor. Building Machine Learning and Deep Learning Models on Google Cloud Platform: u00a0 u00a0  u00a0A Comprehensive Guide for Beginners. Berkeley, CA: Apress; 2019. pp. 59 u201364', '4. Project Jupyter. Jupyter Notebook. 2020. Available: https://jupyter.org/', '5. QGIS Development Team. QGIS Geographic Information System. Open Source Geospatial Foundation Project. 2019. u00a0  u00a0  u00a0Available: https://www.qgis.org/en/site/index.html', '6. Gillies S et al. Rasterio: geospatial raster I/O for Python programmers. Mapbox; 2013. Available: https://github.com/mapbox/rasterio', '7. Hunter JD. Matplotlib: A 2D Graphics Environment. Comput Sci Eng. 2007;9: 90 u201395.']}", "keywords": ["Remote Sensing", "Multispectral analysis", "Landscape Archaeology", "Spectral decomposition", "15. Life on land", "Sentinel-2", "Riverscape", "Fluvial and Alluvial Archaeology", "12. Responsible consumption", "Python"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4384105"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4384105", "name": "item", "description": "10.5281/zenodo.4384105", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4384105"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-12-22T00:00:00Z"}}, {"id": "10.5281/zenodo.5235030", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:21:25Z", "type": "Software", "title": "A Colab-Python script code to identify palaeo-landscape features", "description": "Open Access{'references': ['1. Python Software Foundation. Python Language Reference. 2020. Available: http://www.python.org', '2. Wu Q. geemap: A Python package for interactive mapping with Google Earth Engine. Journal of Open Source Software. 2020;5: 2305', '3. Bisong E. Google Colaboratory. In: Bisong E, editor. Building Machine Learning and Deep Learning Models on Google Cloud Platform: u00a0 u00a0  u00a0A Comprehensive Guide for Beginners. Berkeley, CA: Apress; 2019. pp. 59 u201364', '4. Project Jupyter. Jupyter Notebook. 2020. Available: https://jupyter.org/', '5. QGIS Development Team. QGIS Geographic Information System. Open Source Geospatial Foundation Project. 2019. u00a0  u00a0  u00a0Available: https://www.qgis.org/en/site/index.html', '6. Gillies S et al. Rasterio: geospatial raster I/O for Python programmers. Mapbox; 2013. Available: https://github.com/mapbox/rasterio', '7. Hunter JD. Matplotlib: A 2D Graphics Environment. Comput Sci Eng. 2007;9: 90 u201395.']}", "keywords": ["Remote Sensing", "Multispectral analysis", "Landscape Archaeology", "Spectral decomposition", "15. Life on land", "Sentinel-2", "Riverscape", "Fluvial and Alluvial Archaeology", "12. Responsible consumption", "Python"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.5235030"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.5235030", "name": "item", "description": "10.5281/zenodo.5235030", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.5235030"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-12-22T00:00:00Z"}}, {"id": "10.5281/zenodo.580814", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:21:26Z", "type": "Journal Article", "title": "Mapping the abstractions of forest landscape patterns", "description": "The evaluation of landscape patterns is necessary to explain the relationships between ecological processes and spatial patterns. For decades, landscape metrics have been used for measuring and abstracting landscape patterns. Since the emergence of FRAGTATS in 1993 the measures and methods incorporated in this software are very widely used and they have become a de facto standard tool for calculating landscape metrics. There are no special metrics for forest landscapes. The selection of metrics rather depends on the purpose of the study than on the land use type. However, there are some metrics that are more used for forest habitats. Forest landscape patterns are changing fast due to natural and human disturbances. Remote sensing offers rapid method of acquiring up-to-date information over a large geographical area and is therefore widely used as a source of data needed for pattern assessment.  However, in order to obtain meaningful results from landscape metrics calculation, the correct preparation of the data is essential. In this chapter we will give an overview of the various metrics used to measure forest landscapes for different purposes. The chapter will deal with five main issues from the perspective of forest landscape patterns: (1) data preparation for metrics calculation (vector vs raster, scale, classification etc); (2) landscape configuration and composition measured by metrics; (3) interpretation of the results; (4) possible usages of the outcomes; (5) future perspectives (3D landscape metrics).", "keywords": ["0106 biological sciences", "pattern analysis", " configuration", " composition", " landscape metrics", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"], "contacts": [{"organization": "Uuemaa, Evelyn; Oja, T\u00f5nu", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.580814"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Mapping%20Forest%20Landscape%20Patterns", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.580814", "name": "item", "description": "10.5281/zenodo.580814", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.580814"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-05-18T00:00:00Z"}}, {"id": "10.5281/zenodo.5907228", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:21:26Z", "type": "Software", "title": "Spatial statistics to reveal patterns and connections in the historic landscape", "description": "The R script code was developed by dr. F. Brandolini (Newcastle University, UK) to accompany the paper: F. Brandolini &amp; S. Turner (2022<em>) Revealing patterns and connections in the historic landscape of the northern Apennines (Vetto, Italy),</em> Journal of Maps, DOI: 10.1080/17445647.2022.2088305 <strong>Abstract</strong> In the Northern Apennines, significant modifications to the characteristic historic features of landscapes occurred since the 1950s as agriculture declined in importance and villages were progressively depopulated. Today European and national policies are promoting the repopulation of these regions in order to help preserve the cultural identity of territories and to reduce demographic pressure in urban areas. Such initiatives increase the need for cultural and natural landscape management to be better integrated using interdisciplinary approaches. Sustainable landscape management is a dynamic process involving the formulation of a set of strategies to underpin the preservation of landscape heritage and to foster local development on the basis of the values and opportunities provided by landscapes themselves. This study uses landscape archaeology and spatial statistics to provide insights into which parts of the historic landscape retain the greatest time-depth and which parts reflect more recent radical change, enabling an understanding which goes beyond the basic spatial relationships between landscape components. <strong>Methods</strong> This dataset was explored with two spatial statistical tools using the programming language R (R Core Team 2021): Local Indicators for Categorical Data (LICD) and Point Pattern analysis (PPA). The LICD method is based on join-count statistics (JCS), a solid method to measure the correlation between binomial variables and the distance between observations. LICD has been recently employed in landscape archaeological studies for verifying visible patterns and disclosing hidden spatial relationships (article: Carrer et al. 2021, Data: Zenodo Repository) The application of PPA in landscape studies has been widely applied in Ecology and it is growing popular also in Archaeology (Knitter and Nakoinz 2018; Brandolini and Carrer 2020; Costanzo et al. 2021). In this study, PPA was employed to provide a quantitative assessment of the correlations between different components of the Vetto landscape. <strong>List of files included in Brandolini_Turner_tjom_2022.zip:</strong> R_script_code named 'tjom_supplementary' in .rmd format Output folder: png and .txt products of the R script code GeoTiff folder (.TIFF file format): Geomorphons Euclidean distances from Irregular Fields (IF) Euclidean distances from Combined Fields (CF) EsriSHP folder (.shp file format): H_sites folder: historic settlements (h_sites.shp) rural_ruins folder: abandoned rural ruins (rural_ruins.shp) hlc folder: HLC_periods.shp HLC_types.shp roi folder: Region Of Interest (roi.shp) <strong>Contacts</strong> <em>dr. F. Brandolin</em>i: filippo.brandolini@newcastle.ac.uk <strong>Acknowledgements</strong> The authors would like to acknowledge the help of the mayor Mr Fabio Ruffini and all the staff of Vetto d\u2019 Enza, Dr. Alessandra Curotti and Dr. Chiara Cantini and (Unione Montana dei Comuni dell\u2019Appennino Reggiano) and Dott.ssa Annalisa Capurso (Soprintendenza Archeologia Belle Arti e Paesaggio per la citt\u00e0 metropolitana di Bologna e le province di Modena, Reggio Emilia e Ferrara) for their administrative assistance in preparation of the project fieldwork activities. Also, we wish to thank Dr Anna Campeol and Mr Davide Cavecchi (Provincia di Reggio Emilia - Ufficio Topografico) for their help in retrieving and digitising the Nuovo Catasto Terreni cadastral map. The authors also thank the AsRe (Archivio Stato di Reggio Emilia) and AsPr (Archivio Stato di Parma) administration and staff for giving the right to digitise the historical maps and for helping during the consultation at the archives. Finally, we thank Francesco Carrer (Newcastle University, Newcastle upon Tyne, UK) for his comments on the R script code, and Christopher Sevara (Newcastle University, Newcastle upon Tyne, UK) for his suggestions in retrieving historical satellite images.", "keywords": ["Landscape Heritage", "Landscape Management", "Landscape Archaeology", "Spatial Statistics", "11. Sustainability", "Spatial Humanities", "Digital Geoarchaeology", "15. Life on land", "Historic Landscape Characterisation", "Point Pattern Analysis", "Local Indicator for Categorical Data"], "contacts": [{"organization": "Brandolini, Filippo", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.5907228"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.5907228", "name": "item", "description": "10.5281/zenodo.5907228", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.5907228"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-26T00:00:00Z"}}, {"id": "10.5281/zenodo.7735993", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:21:35Z", "type": "Software", "title": "HiLSS Project", "description": "The R script code was developed by dr. F. Brandolini (Newcastle University, UK) to accompany the paper: '<em>Brandolini, F., Kinnaird, T.C., Srivastava, A., Turner S. - Modelling the impact of historic landscape change on soil erosion and degradation. Sci Rep 13, 4949 (2023)</em>'. <strong>List of files included in <em>HLC_RUSLE.zip</em>:</strong> <em>R_script_code named 'HLC_RUSLE' in .rmd format</em> <em>Output folder: </em> <em>Figures folder: .png products of the R script code</em> <em>Rasters folder: .png products of the R script code</em> <em>Tables folder: .pdf products of the R script code</em> <em>GeoTiff folder (.TIFF file format): Regional RUSLE Data</em> <em>GPKG:</em> <em>HLC </em>dataset and <em>Region Of Interest file in .gpkg format.</em>", "keywords": ["13. Climate action", "Landscape Archaeology", "11. Sustainability", "RUSLE", "15. Life on land", "Historic Landscape Characterisation", "Soil Sustainability", "Soil Erosion Modelling", "12. Responsible consumption"], "contacts": [{"organization": "Brandolini Filippo", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.7735993"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.7735993", "name": "item", "description": "10.5281/zenodo.7735993", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.7735993"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-10-10T00:00:00Z"}}, {"id": "10.5281/zenodo.7777673", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:21:35Z", "type": "Software", "title": "HiLSS Project", "description": "The R script code was developed by dr. F. Brandolini (Newcastle University, UK) to accompany the paper: '<em>Brandolini, F., Kinnaird, T.C., Srivastava, A., Turner S. - Modelling the impact of historic landscape change on soil erosion and degradation. Sci Rep 13, 4949 (2023)</em>'. <strong>List of files included in <em>HLC_RUSLE.zip</em>:</strong> <em>R_script_code named 'HLC_RUSLE' in .rmd format</em> <em>Output folder: </em> <em>Figures folder: .png products of the R script code</em> <em>Rasters folder: .png products of the R script code</em> <em>Tables folder: .pdf products of the R script code</em> <em>GeoTiff folder (.TIFF file format): Regional RUSLE Data</em> <em>GPKG:</em> <em>HLC </em>dataset and <em>Region Of Interest file in .gpkg format.</em>", "keywords": ["13. Climate action", "Landscape Archaeology", "11. Sustainability", "RUSLE", "15. Life on land", "Historic Landscape Characterisation", "Soil Sustainability", "Soil Erosion Modelling", "12. Responsible consumption"], "contacts": [{"organization": "Filippo, Brandolini", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.7777673"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.7777673", "name": "item", "description": "10.5281/zenodo.7777673", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.7777673"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-10-10T00:00:00Z"}}, {"id": "10.5281/zenodo.7934059", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:21:36Z", "type": "Dataset", "title": "HiLSS Project", "description": "This\u00a0repository is periodically updated.   Historic Landscape and Soil Sustainability (MSCA-IF-2019 - Individual Fellowships)   The HiLSS Project aims to investigate the relationships between sustainability and landscape heritage with particular reference to soil loss and degradation over the long term. The project will take a multidisciplinary approach that combines archaeology, Historical Landscape Characterisation (HLC), geosciences, and computer-based geospatial analysis (GIS - Geographical Information Systems) and modelling (RUSLE - Revisited Universal Soil Loss Equation). The research objectives of the HiLSS project are to quantify the impact of human activities during the Late Holocene in order to create spatial models which can inform the development of sustainable conservation strategies for rural landscape heritage. This project will focus on two mountainous regions that present historical and cultural similarities but located in different climatic zones of Europe (1- Tuscan-Emilian Apennines, Italy; 2- Northern-mid Galicia, Spain). In previous HLC studies, land-use has been evaluated from the perspective of cultural heritage, whereas RUSLE have used it as a proxy for the land-cover of an area and its effect on soil erosion. The HiLSS project will propose an innovative methodology that combines both the historic/cultural values and the environmental values of land-use to inform development of a model for the sustainable conservation. By considering the different agricultural land-use HLC types in GIS-RUSLE modelling, it will be possible to quantify the effect on soil loss for each HLC type and consequently to devise more environmentally sustainable management for each type. Environmental sustainability and historic landscape conservation are typically treated as two separate fields, but the HiLSS project will develop a transformative model for interdisciplinary research, proposing a new way to embrace both cultural and natural values as components of the same landscape management plans.     HLC_RUSLE.zip    The R script code was developed by dr. F. Brandolini (Newcastle University, UK) to accompany the paper: 'Brandolini, F., Kinnaird, T.C., Srivastava, A., Turner S. -\u00a0Modelling the impact of historic landscape change on soil erosion and degradation. Sci Rep 13, 4949 (2023)'.   List of files included in HLC_RUSLE.zip:      R_script_code named 'HLC_RUSLE'\u00a0in .rmd format   Output folder:        Figures folder: .png products of the R script code    Rasters\u00a0folder: .png products of the R script code    Tables\u00a0folder: .pdf\u00a0products of the R script code       GeoTiff folder (.TIFF file format): Regional RUSLE\u00a0Data   GPKG:\u00a0HLC dataset\u00a0and\u00a0Region Of Interest file in .gpkg format      Spatial statistics to reveal patterns and connections in the historic landscape    The R script code was developed by dr. F. Brandolini (Newcastle University, UK) to accompany the paper: '\u00a0F.\u00a0Brandolini & S.\u00a0Turner\u00a0(2022)\u00a0Revealing patterns and connections in the historic landscape of the northern Apennines (Vetto, Italy),\u00a0Journal of Maps,\u00a0DOI:\u00a010.1080/17445647.2022.2088305.\u00a0'.   It is available at:\u00a0https://doi.org/10.5281/zenodo.5907229     Supplementary material_Land _SI_Historic Landscape Evolution.zip    Supplementary Materials to accompaing\u00a0the paper:\u00a0The evolution of historic agroforestry landscape in the Northern Apennines (Italy) and its consequences for slope geomorphic processes, submitted to\u00a0Land,\u00a0Special Issue\u00a0Historic Landscape Transformation.     Project_Publications.zip    List of .pdf file included in the folder:\u00a0   1) Brandolini F, Domingo-Ribas G, Zerboni A and Turner S. A Google Earth Engine-enabled Python approach for the identification of anthropogenic palaeo-landscape features [version 2; peer review: 2 approved, 1 approved with reservations]. Open Res Europe 2021,\u00a01:22\u00a0(https://doi.org/10.12688/openreseurope.13135.2)   2) Brandolini F., Turner S.\u00a0 2022 - Revealing patterns and connections in the historic landscape of the northern Apennines (Vetto, Italy), \u00a0Journal of Maps,\u00a0 (https://doi.org/10.1080/17445647.2022.2088305)   3) Brandolini, F., Kinnaird, T.C., Srivastava, A., Turner S. 2023 -\u00a0Modelling the impact of historic landscape change on soil erosion and degradation. Sci Rep 13, 4949 (2023), (https://doi.org/10.1038/s41598-023-31334-z)   4)\u00a0Brandolini, F., Compostella, C., Pelfini, M., and Turner, S. 2023 - 'The Evolution of Historic Agroforestry Landscape in the Northern Apennines (Italy) and Its Consequences for Slope Geomorphic Processes' Land 12, no. 5: 1054. (https://doi.org/10.3390/land12051054)", "keywords": ["2. Zero hunger", "13. Climate action", "Landscape Archaeology", "11. Sustainability", "RUSLE", "USPED", "15. Life on land", "Historic Landscape Characterisation", "Soil Sustainability", "Soil Erosion Modelling", "12. Responsible consumption"], "contacts": [{"organization": "Brandolini Filippo", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.7934059"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.7934059", "name": "item", "description": "10.5281/zenodo.7934059", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.7934059"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-10-10T00:00:00Z"}}, {"id": "10.7910/DVN/GVNJAB", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:10Z", "type": "Dataset", "created": "2019-06-24", "title": "Physical topsoil  properties in Murugusi, Western Kenya", "description": "Open Access&lt;b&gt;General:&lt;/b&gt; Lab determined topsoil bulk density, contents of sand, clay and organic carbon in Murugusi, W. Kenya, together with spatial coordinates of where the soil samples were taken (rounded to the closest center point of a 250 m \u00d7 250 m raster). All lab analyses were carried out at the ILRI/CIAT lab in Nairob, Kenya.  &lt;br&gt;  &lt;b&gt;Soil sampling:&lt;/b&gt; At each sample location, one composite topsoil sample was taken; three cores of 7 cm in diameter taken within an area of one square meter. The soil was taken from 0-0.2 m depth below any organic (O) horizon.   &lt;br&gt;  &lt;b&gt;Determination of soil properties:&lt;/b&gt; The bulk density of the soil was determined by taking two undisturbed soil samples (0-10 cm and 10-20 cm depth) of known volume (100 cm2) and weighting them after air drying. Soil fractions of clay (&lt;0.002 mm) and sand (0.05-2 mm) were determined by the hydrometer method (Estefan et al., 2014), using 10% sodium hexametaphosphate as the dispersing agent. Soil pH was determined potentiometrically on a soil suspension of 1:2 (soil: water). Total carbon was measured after dry combustion using an elemental analyser (Elementar Vario max cube; ISO 10694, first edition 1995-03-01)  &lt;br&gt;  &lt;b&gt;Reference: &lt;/b&gt;Estefan G., Sommer R., Ryan J. (2014) Analytical Methods for Soil-Plant and Water in Dry Areas. A Manual of Relevance to the West Asia and North Africa Region. 3rd Edition, International Center for Agricultural Research in the Dry Areas, Aleppo, 255 pp. Available online at: http://repo.mel.cgiar.org:8080/handle/20.500.11766/7512?show=full. Verified: October 9, 2018.  &lt;br&gt;  &lt;b&gt;Acknowledgements: &lt;/b&gt; We are deeply thankful for the good services provided by John Mukulama (soil sampling), John Yumbya Mutua (soil sampling) and Francis Mungthu Njenga (lab analyses) The project was carried out within the CGIAR Research Program on Water, Land and Ecosystems (WLE).", "keywords": ["Soil organic matter", "Agricultural Sciences", "Soil organic carbon", "sand", "Kenya", "Carbon", "Latin America and the Caribbean", "soil", "Soil", "Soil bulk density", "Sand", "soil organic matter", "Earth and Environmental Sciences", "Soil texture", "Murugusi", "Africa", "Clay", "Texture", "Western Kenya", "Agroecosystems and Sustainable Landscapes - ASL"], "contacts": [{"organization": "Piikki, Kristin, S\u00f6derstr\u00f6m, Mats, Sommer, Rolf, Da Silva, Mayesse,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/GVNJAB"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/GVNJAB", "name": "item", "description": "10.7910/DVN/GVNJAB", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/GVNJAB"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-01-01T00:00:00Z"}}, {"id": "10.7910/DVN/XZIRK0", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:10Z", "type": "Dataset", "title": "Baselines for land degradation neutrality indicators in the Omusati region, Namibia", "description": "This data was collected to develop baselines for three Land Degradation Neutrality (LDN) indicators: land use and land cover change (LUC) for the period 2001-2017, soil organic carbon (SOC) stocks for 2017 and bush density for 2017 as a baseline for bush encroachment in Omusati region, Namibia.", "keywords": ["SDG 15.3", "Land cover", "sustainable development", "UNCCD", "Land degradation neutrality", "Agricultural Sciences", "land degradation", "carbon", "Namibia", "Soil carbon", "Carbon", "soil", "Soil", "land cover", "Omusati", "Earth and Environmental Sciences", "Sustainable development", "Africa", "Bush density", "Land degradation", "Agroecosystems and Sustainable Landscapes - ASL"], "contacts": [{"organization": "Hengari, Simeon, Angombe, Simon, Katjioungua, Georgina, Fabiano, Ezequiel, Zauisomue, Erlich, Nakashona, Natalia, Ipinge, Selma, Andreas, Amon, Muhoko, Edward, Emvula, Emerit, Mutua, John, Kempen, Bas, Nijbroek, Ravic,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/XZIRK0"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/XZIRK0", "name": "item", "description": "10.7910/DVN/XZIRK0", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/XZIRK0"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-01-01T00:00:00Z"}}, {"id": "2434/878015", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:23:03Z", "type": "Journal Article", "created": "2021-09-06", "title": "A Google Earth Engine-enabled Python approach for the identification of anthropogenic palaeo-landscape features", "description": "<ns4:p>The necessity of sustainable development for landscapes has emerged as an important theme in recent decades. Current methods take a holistic approach to landscape heritage and promote an interdisciplinary dialogue to facilitate complementary landscape management strategies. With the socio-economic values of the \u201cnatural\u201d and \u201ccultural\u201d landscape heritage increasingly recognised worldwide, remote sensing tools are being used more and more to facilitate the recording and management of landscape heritage. The advent of freeware cloud computing services has enabled significant improvements in landscape research allowing the rapid exploration and processing of satellite imagery such as the Landsat and Copernicus Sentinel datasets. This research represents one of the first applications of the Google Earth Engine (GEE) \u00a0Python application programming interface (API) in studies of historic landscapes. The complete free and open-source software (FOSS) cloud protocol proposed here consists of a Python code script developed in Google Colab, which could be adapted and replicated in different areas of the world. A multi-temporal approach has been adopted to investigate the potential of Sentinel-2 satellite imagery to detect buried hydrological and anthropogenic features along with spectral index and spectral decomposition analysis. The protocol's effectiveness in identifying palaeo-riverscape features has been tested in the Po Plain (N Italy).</ns4:p>", "keywords": ["FOS: Computer and information sciences", "Landscape Archaeology", "Computer Vision and Pattern Recognition (cs.CV)", "Computer Science - Computer Vision and Pattern Recognition", "0211 other engineering and technologies", "Articles", "02 engineering and technology", "15. Life on land", "01 natural sciences", "Fluvial and Alluvial Archaeology", "12. Responsible consumption", "Multispectral analysis", "Computer Science - Computers and Society", "Buried features", "Multispectral analysis;Sentinel-2;Spectral decomposition;Python;Riverscape;Fluvial and Alluvial Archaeology;Landscape Archaeology;Buried features", "13. Climate action", "Computers and Society (cs.CY)", "11. Sustainability", "Spectral decomposition", "Sentinel-2", "Riverscape", "Python", "Research Article", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://air.unimi.it/bitstream/2434/878015/4/Brandolini%2bet%2bal_ORE_2021_compressed%20%282%29.pdf"}, {"href": "https://doi.org/2434/878015"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Open%20Research%20Europe", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2434/878015", "name": "item", "description": "2434/878015", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2434/878015"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-03-24T00:00:00Z"}}, {"id": "10.5751/es-08841-220125", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:21:57Z", "type": "Journal Article", "created": "2017-02-24", "title": "Using An Agent-Based Model To Examine Forest Management Outcomes In A Fire-Prone Landscape In Oregon, Usa", "description": "Fire-prone landscapes present many challenges for both managers and policy makers in developing adaptive behaviors and institutions. We used a coupled human and natural systems framework and an agent-based landscape model to examine how alternative management scenarios affect fire and ecosystem services metrics in a fire-prone multiownership landscape in the eastern Cascades of Oregon. Our model incorporated existing models of vegetation succession and fire spread and information from original empirical studies of landowner decision making. Our findings indicate that alternative management strategies can have variable effects on landscape outcomes over 50 years for fire, socioeconomic, and ecosystem services metrics. For example, scenarios with federal restoration treatments had slightly less high-severity fire than a scenario without treatment; exposure of homes in the wildland-urban interface to fire was also slightly less with restoration treatments compared to no management. Treatments appeared to be more effective at reducing high-severity fire in years with more fire than in years with less fire. Under the current management scenario, timber production could be maintained for at least 50 years on federal lands. Under an accelerated restoration scenario, timber production fell because of a shortage of areas meeting current stand structure treatment targets. Trade-offs between restoration outcomes (e.g., open forests with large fire-resistant trees) and habitat for species that require dense older forests were evident. For example, the proportional area of nesting habitat for northern spotted owl (Strix occidentalis) was somewhat less after 50 years under the restoration scenarios than under no management. However, the amount of resilient older forest structure and habitat for white-headed woodpecker (Leuconotopicus albolarvatus) was higher after 50 years under active management. More carbon was stored on this landscape without management than with management, despite the occurrence of high-severity wildfire. Our results and further applications of the model could be used in collaborative settings to facilitate discussion and development of policies and practices for fire-prone landscapes.", "keywords": ["2. Zero hunger", "Ecology", "QH301-705.5", "adaptation", "landscape", "15. Life on land", "01 natural sciences", "wildfire", "13. Climate action", "11. Sustainability", "Biology (General)", "ecosystem services", "management", "QH540-549.5", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.5751/es-08841-220125"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Ecology%20and%20Society", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5751/es-08841-220125", "name": "item", "description": "10.5751/es-08841-220125", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5751/es-08841-220125"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-01-01T00:00:00Z"}}, {"id": "10.60692/00fqh-scr74", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:00Z", "type": "Journal Article", "created": "2022-02-28", "title": "Expansion of olive orchards and their impact on the cultivation and landscape through a case study in the countryside of Cordoba (Spain)", "description": "Open Access\u062a\u0645 \u062a\u0639\u0632\u064a\u0632 \u0627\u0633\u062a\u062f\u0627\u0645\u0629 \u0627\u0644\u0646\u0638\u0645 \u0627\u0644\u0632\u0631\u0627\u0639\u064a\u0629 \u0645\u0646 \u062e\u0644\u0627\u0644 \u0627\u0644\u062a\u0634\u0631\u064a\u0639\u0627\u062a \u0639\u0644\u0649 \u0645\u0633\u062a\u0648\u064a\u0627\u062a \u0645\u062e\u062a\u0644\u0641\u0629\u060c \u0648\u0644\u0643\u0646 \u0641\u064a \u0627\u0644\u0648\u0642\u062a \u0646\u0641\u0633\u0647 \u062a\u0639\u0632\u0632 \u0647\u0630\u0647 \u0627\u0644\u0633\u064a\u0627\u0633\u0627\u062a \u0623\u064a\u0636\u064b\u0627 \u0623\u0646\u0638\u0645\u0629 \u0623\u0643\u062b\u0631 \u0625\u0646\u062a\u0627\u062c\u064a\u0629 \u0645\u0646 \u062e\u0644\u0627\u0644 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\u0643\u0645\u0646\u0627\u0637\u0642 \u0627\u0633\u062a\u0639\u0627\u062f\u0629 \u0645\u062d\u062a\u0645\u0644\u0629 \u0644\u062a\u0639\u0632\u064a\u0632 \u062a\u0648\u0641\u064a\u0631 \u062e\u062f\u0645\u0627\u062a \u0627\u0644\u0646\u0638\u0627\u0645 \u0627\u0644\u0625\u064a\u0643\u0648\u0644\u0648\u062c\u064a.", "keywords": ["Period (music)", "Soil Degradation", "Vascular Flora of Mediterranean Europe and North Africa", "Soil Science", "Orchard", "Plant Science", "Mediterranean", "Horticulture", "Genetic and Environmental Factors in Grapevine Cultivation", "01 natural sciences", "Environmental science", "Agricultural and Biological Sciences", "Pathology", "Ecosystem services", "Landscape elements", "Agroforestry", "Irrigation", "Biology", "0105 earth and related environmental sciences", "2. Zero hunger", "Geography", "Ecology", "Physics", "Common agricultural policy", "Olive groves", "Life Sciences", "Agriculture", "Forestry", "Acoustics", "04 agricultural and veterinary sciences", "15. Life on land", "Soil Erosion and Agricultural Sustainability", "Olive trees", "Agronomy", "Sustainability", "Archaeology", "FOS: Biological sciences", "Shifting cultivation", "Medicine", "0401 agriculture", " forestry", " and fisheries", "Vegetation (pathology)"]}, "links": [{"href": "https://doi.org/10.60692/00fqh-scr74"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Land%20Use%20Policy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.60692/00fqh-scr74", "name": "item", "description": "10.60692/00fqh-scr74", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.60692/00fqh-scr74"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-05-01T00:00:00Z"}}, {"id": "10.60692/qa6mq-50k15", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:00Z", "type": "Journal Article", "created": "2022-07-04", "title": "Tree species identity is the predominant modulator of the effects of soil fauna on leaf litter decomposition", "description": "Open AccessLa faune du sol est l'un des principaux moteurs de la d\u00e9composition de la liti\u00e8re \u00e0 l'\u00e9chelle locale et mondiale, mais le r\u00f4le des esp\u00e8ces d'arbres dans la m\u00e9diation des effets de la faune du sol sur la d\u00e9composition de la liti\u00e8re reste insaisissable. Nous avons men\u00e9 une exp\u00e9rience sur le terrain en utilisant des sacs de liti\u00e8re avec trois tailles de maille diff\u00e9rentes qui ont permis l'acc\u00e8s \u00e0 la microfaune (0,1 mm), \u00e0 la micro et m\u00e9sofaune (2 mm) et \u00e0 la faune totale du sol (5 mm) pour \u00e9valuer la d\u00e9composition de la liti\u00e8re foliaire de deux esp\u00e8ces d'arbres associ\u00e9es \u00e0 des champignons mycorhiziens arbusculaires (MA) et de trois esp\u00e8ces d'arbres associ\u00e9es \u00e0 des champignons ectomycorhiziens (ECM) dans six sites de jardins communs danois. Nous avons \u00e9galement \u00e9valu\u00e9 comment les diff\u00e9rences dans la qualit\u00e9 initiale de la liti\u00e8re, les propri\u00e9t\u00e9s du sol et la composition de la communaut\u00e9 microbienne parmi les esp\u00e8ces d'arbres peuvent affecter la d\u00e9composition de la liti\u00e8re ainsi que les effets de la faune du sol sur la d\u00e9composition de la liti\u00e8re. Les r\u00e9sultats ont montr\u00e9 que (1) la perte de masse de la liti\u00e8re variait consid\u00e9rablement selon la taille des mailles et les esp\u00e8ces d'arbres, avec des taux de d\u00e9composition de la liti\u00e8re (k) allant de 0,273 \u00e0 3,482\u00a0; (2) l'acc\u00e8s \u00e0 la m\u00e9sofaune augmentait significativement la liti\u00e8re k de 0,658 pour la MA et de 0,396 pour les esp\u00e8ces d'arbres ECM sans acc\u00e8s \u00e0 la faune du sol, respectivement de 255 et 92%, tandis que l'acc\u00e8s \u00e0 la fois \u00e0 la m\u00e9so- et \u00e0 la macrofaune augmentait k de 265 et 108% pour les arbres AM et ECM, respectivement\u00a0; (3) l'identit\u00e9 des esp\u00e8ces d'arbres, l'association mycorhizienne, la qualit\u00e9 initiale de la liti\u00e8re, les propri\u00e9t\u00e9s du sol, la composition des communaut\u00e9s microbiennes et la biomasse de la faune du sol ambiant \u00e9taient tous des facteurs influen\u00e7ant significativement la d\u00e9composition de la liti\u00e8re, mais l'identit\u00e9 des esp\u00e8ces d'arbres \u00e9tait le facteur dominant ind\u00e9pendamment de la taille des mailles des sacs de liti\u00e8re\u00a0; et (4) les effets de la m\u00e9sofaune sur la d\u00e9composition de la liti\u00e8re \u00e9taient principalement contr\u00f4l\u00e9s par l'identit\u00e9 des esp\u00e8ces d'arbres, la concentration initiale en Mg de la liti\u00e8re et le rapport lignine\u00a0:N, tandis que le petit impact suppl\u00e9mentaire de l'acc\u00e8s \u00e0 la macrofaune n'\u00e9tait pas bien expliqu\u00e9 par aucun des facteurs \u00e9valu\u00e9s. Dans l'ensemble, nos r\u00e9sultats sugg\u00e8rent que les esp\u00e8ces d'arbres affectent la d\u00e9composition de la liti\u00e8re via une stimulation diff\u00e9rente du fonctionnement de la faune du sol, et que les esp\u00e8ces d'arbres associ\u00e9es \u00e0 la MA et \u00e0 la mec diff\u00e8rent dans le degr\u00e9 auquel la faune du sol stimule la d\u00e9composition de la liti\u00e8re. Cependant, le mod\u00e8le n'\u00e9tait pas enti\u00e8rement coh\u00e9rent car les taux de d\u00e9composition de la liti\u00e8re pour la chaux associ\u00e9e \u00e0 la mec \u00e9taient stimul\u00e9s dans la m\u00eame mesure que les taux pour les esp\u00e8ces d'arbres associ\u00e9es \u00e0 la MA, le fr\u00eane et l'\u00e9rable. Dans l'ensemble, nos r\u00e9sultats sugg\u00e8rent que les communaut\u00e9s de m\u00e9so- et de macrofaune du sol peuvent am\u00e9liorer les effets des esp\u00e8ces d'arbres sur la d\u00e9composition de la liti\u00e8re ainsi que l'incorporation de la liti\u00e8re C dans le sol min\u00e9ral.", "keywords": ["Biomass (ecology)", "0106 biological sciences", "Litter quality", "Microfauna", "Plant Science", "Soil mesofauna", "01 natural sciences", "Plant litter", "Soil fauna", "Agricultural and Biological Sciences", "Biodiversity Conservation and Ecosystem Management", "Soil biology", "Microbial community", "Mycorrhizal Fungi and Plant Interactions", "Litter", "Soil water", "Wood Decomposition", "Saproxylic Insect Ecology and Forest Management", "Plant Interactions", "Biology", "Ecosystem", "Nature and Landscape Conservation", "Ecology", "Soil property", "Life Sciences", "04 agricultural and veterinary sciences", "15. Life on land", "Fauna", "Insect Science", "FOS: Biological sciences", "Environmental Science", "Physical Sciences", "Common garden", "0401 agriculture", " forestry", " and fisheries", "Litterbag mesh size"]}, "links": [{"href": "https://doi.org/10.60692/qa6mq-50k15"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Forest%20Ecology%20and%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.60692/qa6mq-50k15", "name": "item", "description": "10.60692/qa6mq-50k15", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.60692/qa6mq-50k15"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-09-01T00:00:00Z"}}, {"id": "10.6084/m9.figshare.20477290", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:03Z", "type": "Journal Article", "created": "2022-08-11", "title": "Revealing patterns and connections in the historic landscape of the northern Apennines (Vetto, Italy)", "description": "In the Northern Apennines, significant modifications to the characteristic historical features of landscapes have occurred since the 1950s as agriculture declined in importance and villages were progressively depopulated. Today, European policies are promoting the repopulation of these regions to help preserve the cultural identity of territories and reduce demographic pressure inurban areas. Such initiatives increase the need for cultural and natural landscape management to be better integrated using interdisciplinary approaches. Sustainable landscape management is a dynamic process involving the formulation of strategies to underpin the preservation of landscape heritage and foster local development based on the values and opportunities provided by landscapes themselves. This study uses landscape archaeology and spatial statistics to provide insights into which parts of the historic landscape retain the greatest time-depth and which parts reflect the more recent radical change, enabling an understanding which goes beyond the basic spatial relationships between landscape components.", "keywords": ["local indicators for categorical data", "point pattern analysis", "G3180-9980", "Landscape archaeology", "Maps", "11. Sustainability", "landscape management", "15. Life on land", "01 natural sciences", "historic landscape characterisation", "spatial statistics", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://www.tandfonline.com/doi/pdf/10.1080/17445647.2022.2088305"}, {"href": "https://eprints.ncl.ac.uk/fulltext.aspx?url=284595/39618FDF-222E-4078-8426-E55819A569AD.pdf&pub_id=284595"}, {"href": "https://doi.org/10.6084/m9.figshare.20477290"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Maps", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.6084/m9.figshare.20477290", "name": "item", "description": "10.6084/m9.figshare.20477290", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.6084/m9.figshare.20477290"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-01T00:00:00Z"}}, {"id": "10.7910/DVN/3BLW7E", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:09Z", "type": "Dataset", "created": "2020-02-20", "title": "Soil organic carbon in agricultural systems of six countries in East Africa  \u2013 a literature review of status and carbon sequestration potential", "description": "Open AccessA systematic literature review of existing evidence on soil organic carbon (SOC) responses to agronomic best management practices (BMPs) in cultivated soils of East Africa, focusing on Ethiopia, Kenya, Rwanda, Tanzania, Uganda, and Burundi. Examining current evidence on the extent to which BMPs can increase SOC stocks and whether net SOC sequestration is attainable in this region. The study also sought to identify knowledge gaps and make recommendations for future research. Independent variables:  \u2022 Annual rainfall (mm year-1), as semi-arid (&lt;600), sub-humid (601-1200), moist sub-humid (1201-1500), or humid (&gt;1500) \u2022 Temperature \u2022 Location,  \u2022 Altitude - lowland (&lt;1500 m above sea level (a.s.l.)) or highland (\u2265 1500 m a.s.l.).  \u2022 Soil characteristics \u2013 type, bulk density, texture \u2022 The time period after which changes in SOC were measured - short-term (&lt;10 years), medium-term (10-25 years), and long-term (&gt;25 years).  \u2022 Soil depth: 0-30 cm, 0-50 cm, and 0-100 cm. Dependent variables \u2022 Soil organic carbon stock (t C ha 1) \u2022 Soil organic carbon sequestration (t C ha 1 year-1) \u2022 Soil organic carbon loss (t C ha 1 year-1)", "keywords": ["soil organic carbon", "carbono organico del suelo", "Agricultural Sciences", "Soil organic carbon", "Earth and Environmental Sciences", "cropland", "Africa", "Cropland", "Multifunctional Landscapes", "tierras agricolas", "Best management practices", "East Africa"], "contacts": [{"organization": "Namirembe, Sara, Piikki, Kristin, Sommer, Rolf, S\u00f6derstr\u00f6m, Mats, Tessema, Bezaye, Nyawira, Sylvia,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/3BLW7E"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/3BLW7E", "name": "item", "description": "10.7910/DVN/3BLW7E", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/3BLW7E"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-01T00:00:00Z"}}, {"id": "10.7910/DVN/86009C", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:09Z", "type": "Dataset", "created": "2019-07-31", "title": "CROSST - Version 1.0.1", "description": "Open AccessCROSST is an Excel-based tool that assesses both agro-environmental and socio-economic impacts of Green Manure Cover Crop (GMCC) technologies. The tool quantifies gross economic margin, productivity (yield), soil health (N and P balances, soil structure, and soil organic carbon), required labor hours, and the trade-offs between these indicators. The tool was pilot-tested in Benin and Kenya under the BMZ-GIZ program on \u2018Soil Protection and Rehabilitation for Food Security.\u2019", "keywords": ["Agricultural Sciences", "Agrobiodiversity - AGBIO", "Earth and Environmental Sciences", "Africa", "Ex-ante impact assessment", "Economic analysis", "Environmental modelling", "Agroecosystems and Sustainable Landscapes - ASL", "Agronomy", "Productivity"]}, "links": [{"href": "https://doi.org/10.7910/DVN/86009C"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/86009C", "name": "item", "description": "10.7910/DVN/86009C", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/86009C"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-01-01T00:00:00Z"}}, {"id": "10.7910/DVN/9BGO2X", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:09Z", "type": "Dataset", "created": "2016-01-01", "title": "Replication Data for: Reducing losses but failing to sequester carbon in soils \u2013 the case of Conservation Agriculture and Integrated Soil Fertility Management in the humid tropical agro-ecosystem of Western Kenya", "description": "Soil organic carbon content of topsoil (0-15 cm depths) of two agronomic long-term trial (CT1 and INM3), collected repeatedly throughout the years", "keywords": ["Agricultural Sciences", "Conservation agriculture", "Soil organic carbon", "soil fertility", "conservation", "Soil fertility", "climate change mitigation", "soil organic carbon", "4p1000", "Climate change mitigation", "climate change", "Earth and Environmental Sciences", "greenhouse gases", "Greenhouse gas emissions", "Africa", "Climate change", "Agroecosystems and Sustainable Landscapes - ASL", "C-sink"], "contacts": [{"organization": "Sommer, Rolf, Paul, Birthe, Kihara, Job, Mukalama, John,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/9BGO2X"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/9BGO2X", "name": "item", "description": "10.7910/DVN/9BGO2X", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/9BGO2X"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-01-01T00:00:00Z"}}, {"id": "10.7910/DVN/GXUNAZ", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:10Z", "type": "Dataset", "title": "Non-responsiveness of crops to fertilizers under some soils in sub-Saharan Africa", "description": "Open AccessLow productivity of agriculture observed in different parts of sub-Saharan Africa is threatening food security in the region. Decades of production with mostly application of small amounts of inorganic fertilizers (mostly macronutrients) and scarce organic resources in the context of integrated soil fertility management (ISFM) result in nutrient mining of secondary and micronutrients in majority of smallholder farms. With the last decade, crop non-responsiveness to nutrient application has become an important issue requiring scientific understanding. We provide data focused on identifying the extent of non-responsiveness of crops to nutrient application and the associated factors. Data contains crop yield response to secondary and micronutrient (SMN), manure and lime application relative to yields of only NP/K application.", "keywords": ["Nutrient response", "carbono organico del suelo", "Agricultural Sciences", "Soil organic carbon", "CGIAR Research Program on Water", " Land and Ecosystems", "Inorganic fertilisers", "abonos inorganicos", "Multifunctional Landscapes", "micronutrients fertilizers", "Soil fertility", "Micronutrient fertilizers", "soil organic carbon", "Manure", "Earth and Environmental Sciences", "Africa", "inorganic fertilizers", "fertilizantes de oligoelementos"], "contacts": [{"organization": "Kihara, Job Maguta, Okeyo, Jeremiah, Bolo, Peter Omondi, Kinyua, Michael,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/GXUNAZ"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/GXUNAZ", "name": "item", "description": "10.7910/DVN/GXUNAZ", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/GXUNAZ"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-01T00:00:00Z"}}, {"id": "10.7910/DVN/ZJMJ7K", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:11Z", "type": "Dataset", "created": "2018-01-01", "title": "Predicted soil organic carbon (SOC) content (g/kg) and SOC stock (t/ha) in the Eastern Plains of Colombia", "description": "Open AccessMaps allocated in this repository were predicted using a digital soil mapping (DSM) approach (McBratney et al, 2003) based on random forest (Breiman, 2001). A dataset consisting of 653 geo-referenced soil points and a series of environmental covariates that represent the soil-forming factors were used in order to adjust the DSM models. Models\u2019 assessment for SOC content was performed using the 100-fold cross-validation, through the coefficient of determination (R2), root mean squared error (RMSE) and the mean error. Results showed 50.3% of the variance explained, and a RMSE and ME of 0.461 g/kg and 0.038 g/kg, respectively.", "keywords": ["digital surface models", "Eastern Plains", "carbon stock", "carbono org\u00e1nico del suelo", "Colombia", "land use mapping", "Latin America and the Caribbean", "soil", "soil organic carbon", "cartograf\u00eda del uso de la tierra", "Orinoco region", "Earth and Environmental Sciences", "digital soil mapping", "Soil and Water Management", "reconocimiento de suelos", "Multifunctional landscapes", "soil surveys"]}, "links": [{"href": "https://doi.org/10.7910/DVN/ZJMJ7K"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/ZJMJ7K", "name": "item", "description": "10.7910/DVN/ZJMJ7K", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/ZJMJ7K"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-01T00:00:00Z"}}, {"id": "10.7910/DVN/1AN9GO", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:09Z", "type": "Dataset", "title": "Edaphic and Topographic Constraints on Exploitation of the Central Kenya Rift by Large Mammals and Early Hominins", "description": "Soil samples were analysed using standard protocols provided by KALRO (Kenya Agricultural and Livestock Research Organisation). For thin soils, we generally sampled the uppermost horizon (&lt;25cm). Soil and plant tissue analysis was carried out at the KALRO laboratories.   During field seasons in 2013 and 2014 a total of 163 soil samples and 160 plant tissue samples in the Kenya Rift from Lake Magadi in the south to Lake Baringo in the north. All samples were tested for concentration of the following trace elements and nutrients: calcium (Ca), copper (Cu), iron (Fe), manganese (Mn), magnesium (Mg), nitrogen (N), potassium (K), sodium (Na), phosphorus (P), and zinc (Zn). Further, soil samples were tested for pH-value, electrical conductivity, and total organic carbon (Table S1). Water samples from springs and boreholes around Lake Elmenteita to test for fluoride are also shown. The location of sample sites are tabulated (Table S2). The consequences of excess or deficiency of certain elements are shown in Table S3.", "keywords": ["Central Kenya Rift", "Edaphic and Topographic Constraints", "Agricultural Sciences", "Soil edaphics", "Lake Magadi", "Kariandusi", "soil analyses", "Lake Baringo", "Nakuru", "Medicine", " Health and Life Sciences", "Complex topography", "Earth and Environmental Sciences", "Hominins", "African Mammals", "Tectonic landscapes", "Site formation", "Acheulean"], "contacts": [{"organization": "K\u00fcbler, Simon, Rucina, Stephen, Reynolds, Sally, Owenga. Peter, Bailey, Geoffrey, King, Geoffrey,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/1AN9GO"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/1AN9GO", "name": "item", "description": "10.7910/DVN/1AN9GO", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/1AN9GO"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-01-01T00:00:00Z"}}, {"id": "10.7910/DVN/1YZAQZ", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:09Z", "type": "Dataset", "title": "Landscape-scale variability of soil health indicators: Effects of cultivation on soil organic carbon in the Usambara Mountains of Tanzania", "description": "During the Phase I of the CCAFS project we conducted a systematic land and soil health assessment in Lushoto District in November 2012. These data were used to inform climate-smart agricultural interventions for the IFAD project as well as to parameterize DSSAT crop models for maize and beans. The land and soil health assessment that was carried out using the Land Degradation Surveillance Framework (LDSF). These data were also used to assess the effect of cultivation on soil organic carbon dynamics across the landscape. Finally, these data provide a biophysical assessment for the Lushoto CCAFS Climate Smart Village.", "keywords": ["Land and soil health assessment", "Soil organic matter", "land and soil health", "carbon", "landscape", "Soil degradation", "Carbon", "soil", "soil degradation", "soil organic matter", "Earth and Environmental Sciences", "Africa", "Land and soil health", "Soils", "Landscape"], "contacts": [{"organization": "Winowiecki, Leigh, V\u00e5gen, Tor Gunnar, Lyamchai, Charles, Sayula, George, Msoka, Elizabeth,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/1YZAQZ"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/1YZAQZ", "name": "item", "description": "10.7910/DVN/1YZAQZ", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/1YZAQZ"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-01-01T00:00:00Z"}}, {"id": "10.7910/DVN/ESK6BB", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:10Z", "type": "Dataset", "title": "Current and future forage suitability maps for Rwanda and Tanzania", "description": "This data was produced using Targeting Tools \u2013 a web-based GIS tool, which matches a suitability criteria that include climate and environmental requirements for each of the forage varieties with a spatial database that\u2019s comprises organic carbon, soil PH, annual precipitation, mean temperature, growing days and elevation data to characterize the suitability.", "keywords": ["rwanda", "kenya", "Forage", "Agricultural Sciences", "Forage suitability", "Agrobiodiversity - AGBIO", "Earth and Environmental Sciences", "Maps", "Africa", "Rwanda", "forage", "Agroecosystems and Sustainable Landscapes - ASL", "Kenya"], "contacts": [{"organization": "Mutua, John, Notenbaert, An,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/ESK6BB"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/ESK6BB", "name": "item", "description": "10.7910/DVN/ESK6BB", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/ESK6BB"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-01-01T00:00:00Z"}}, {"id": "10.7910/DVN/FNEGDP", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:10Z", "type": "Dataset", "title": "Current and future forage suitability maps for Ethiopia and Kenya", "description": "This data was produced using Targeting Tools \u2013 a web-based GIS tool, which matches a suitability criteria that include climate and environmental requirements for each of the forage varieties with a spatial database that\u2019s comprises organic carbon, soil PH, annual precipitation, mean temperature, growing days and elevation data to characterize the suitability.", "keywords": ["Forage", "Agricultural Sciences", "Forage suitability", "Agrobiodiversity - AGBIO", "Earth and Environmental Sciences", "Maps", "Africa", "forage", "Ethiopia", "Agroecosystems and Sustainable Landscapes - ASL", "Kenya"], "contacts": [{"organization": "Mutua, John, Notenbaert, An,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/FNEGDP"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/FNEGDP", "name": "item", "description": "10.7910/DVN/FNEGDP", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/FNEGDP"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-01-01T00:00:00Z"}}, {"id": "10316/112143", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:22Z", "type": "Journal Article", "created": "2023-12-09", "title": "Exotic, traditional and hybrid landscapes: The subtle history of the Iberian Peninsula maize between \u2018tradition\u2019 and \u2018modernity\u2019", "description": "Societal Impact Statement<p>Maize is the world's second most important agricultural crop. The cereal was unknown to Europeans before the end of the 15th century, but since its arrival in Europe, it has changed agriculture, food and landscapes. Terraces where maize was cultivated in the Northwest of the Iberian Peninsula contributed to the formation of local cultures and identities. The history of maize and maize landscape are mementos that help to recover traditional practices, fostering identities, and are crucial for the successful implementation of sustainable policies to provide prosperous futures.</p>Summary<p>  <p>Maize (Zea mays L.) in the Iberian Peninsula embodies a history of landscape changes where the concepts of \uffe2\uff80\uff98exotic\uffe2\uff80\uff99, \uffe2\uff80\uff98traditional\uffe2\uff80\uff99 and \uffe2\uff80\uff98hybrid\uffe2\uff80\uff99 help to understand the engagements between landscape, farmers, agronomists (since the 19th and 20th centuries) and seeds. Today, landscapes reveal biophysical and ecological changes that reflect a panoply of intentions. A multitude of agents, and their interactions, acted upon those territories over time.</p> <p>Using historical sources from the leading institutions dedicated to agricultural research in the Iberian Peninsula, this paper aims to (1) contribute to a better understanding of the maize landscape and culture in the Iberian Peninsula and (2) interrogate how landscape changes (and the landscape history of maize) can frame local or regional heritage and identities reflecting customs or ways of life.</p> <p>The analysis unveils networks of knowledge, agricultural technologies and seed exchange. Politicians, economists, engineers, agronomists, farmers, governmental officials and agricultural industries planned and transformed traditional rural practices into modern and industrialised ones. Experts and politicians, willing to improve agricultural practices and seeds, using hybrid seeds or building new irrigation systems, led to deep social and landscape changes, allowing maize to cover territories far away from its traditional domains. Moreover, despite farmers' resistance, hybrid maize substituted landraces, eroding agrobiodiversity. Nowadays, the south and east regions of the Iberian Peninsula are the main producers of maize (hybrid), whereas in the Northwest maize is an occasional crop, being replaced by vineyards for economic reasons.</p> </p", "keywords": ["2. Zero hunger", "0301 basic medicine", "0303 health sciences", "crop science", "hybrid", "exotic", "Botany", "landscape", "15. Life on land", "maize", "Environmental sciences", "03 medical and health sciences", "QK1-989", "11. Sustainability", "GE1-350", "landrace", "identity", "Iberian Peninsula"]}, "links": [{"href": "https://doi.org/10316/112143"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/PLANTS%2C%20PEOPLE%2C%20PLANET", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10316/112143", "name": "item", "description": "10316/112143", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10316/112143"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-12-09T00:00:00Z"}}, {"id": "10023/27354", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:11Z", "type": "Journal Article", "created": "2023-03-27", "title": "Modelling the impact of historic landscape change on soil erosion and degradation", "description": "Abstract<p>International policies and guidelines often highlight the divide between \uffe2\uff80\uff98nature\uffe2\uff80\uff99 and \uffe2\uff80\uff98heritage\uffe2\uff80\uff99 in landscape management, and the weakness of monodisciplinary approaches. This study argues that historic agricultural practices have played a key role in shaping today\uffe2\uff80\uff99s landscapes, creating a heritage which affords opportunities for more sustainable landscape management. The paper develops a new interdisciplinary approach with particular reference to soil loss and degradation over the long term. It presents innovative methods for assessing and modelling how pre-industrial agricultural features can mitigate soil erosion risk in response to current environmental conditions. Landscape archaeology data presented through Historic Landscape Characterisation are integrated in a GIS-RUSLE model to illustrate the impact of varying historic land-uses on soil erosion. The resulting analyses could be used to inform strategies for sustainable land resource planning.</p", "keywords": ["2. Zero hunger", "MCC", "GE", "330", "Science", "Q", "R", "DAS", "CC Archaeology", "15. Life on land", "CC", "333", "Article", "12. Responsible consumption", "13. Climate action", "11. Sustainability", "Medicine", "SDG 2 - Zero Hunger", "soil erosion; geomorphology; landscape archaeology; gis modelling", "GE Environmental Sciences", "SDG 15 - Life on Land"]}, "links": [{"href": "https://air.unimi.it/bitstream/2434/1157142/2/s41598-023-31334-z.pdf"}, {"href": "https://www.nature.com/articles/s41598-023-31334-z.pdf"}, {"href": "https://eprints.ncl.ac.uk/fulltext.aspx?url=290514/25AE1152-3C53-4F19-82F7-C273FA162B1A.pdf&pub_id=290514"}, {"href": "https://doi.org/10023/27354"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Scientific%20Reports", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10023/27354", "name": "item", "description": "10023/27354", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10023/27354"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-03-27T00:00:00Z"}}, {"id": "10138/308070", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:14Z", "type": "Journal Article", "created": "2017-12-13", "title": "Effects of climate change on the distribution of hoverfly species (Diptera: Syrphidae) in Southeast Europe", "description": "\u00a9 2017, Springer Science+Business Media B.V., part of Springer Nature. Climate change presents a serious threat to global biodiversity. Loss of pollinators in particular has major implications, with extirpation of these species potentially leading to severe losses in agriculture and, thus, economic losses. In this study, we forecast the effects of climate change on the distribution of hoverflies in Southeast Europe using species distribution modelling and climate change scenarios for two time-periods. For 2041\u20132060, 19 analysed species were predicted to increase their areas of occupancy, with the other 25 losing some of their ranges. For 2061\u20132080, 55% of species were predicted to increase their area of occupancy, while 45% were predicted to experience range decline. In general, range size changes for most species were below 20%, indicating a relatively high resilience of hoverflies to climate change when only environmental variables are considered. Additionally, range-restricted species are not predicted to lose more area proportionally to widespread species. Based on our results, two distributional trends can be established: the predicted gain of species in alpine regions, and future loss of species from lowland areas. Considering that the loss of pollinators from present lowland agricultural areas is predicted and that habitat degradation presents a threat to possible range expansion of hoverflies in the future, developing conservation management strategy for the preservation of these species is crucial. This study represents an important step towards the assessment of the effects of climate changes on hoverflies and can be a valuable asset in creating future conservation plan, thus helping in mitigating potential consequences.", "keywords": ["0106 biological sciences", "LAND-USE", "SELECTING THRESHOLDS", "Global warming", "AQUATIC ECOSYSTEMS", "Conservation", "15. Life on land", "DISTRIBUTION MODELS", "EXTINCTION RISK", "01 natural sciences", "ENVIRONMENTAL-CHANGE", "Insects", "Environmental sciences", "Ecology", " evolutionary biology", "13. Climate action", "Species distribution modelling", "GEOGRAPHIC DISTRIBUTIONS", "LANDSCAPE STRUCTURE", "AGRICULTURAL INTENSIFICATION", "BALKAN PENINSULA", "Endemism"]}, "links": [{"href": "http://link.springer.com/content/pdf/10.1007/s10531-017-1486-6.pdf"}, {"href": "https://doi.org/10138/308070"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Biodiversity%20and%20Conservation", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10138/308070", "name": "item", "description": "10138/308070", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10138/308070"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-12-13T00:00:00Z"}}, {"id": "10261/279273", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:17Z", "type": "Journal Article", "created": "2021-11-19", "title": "Modeling the Soil Erosion Regulation Ecosystem Services of the Landscape in Polish Catchments", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>In this study, the soil erosion regulation ecosystem services of the CORINE land use/ land cover types along with soil intrinsic features and geomorphological factors were examined by using the soil erosion data of 327 catchments in Poland, with a mean area of 510 \u00b1 330 km2, applying a multivariate regression modeling approach. The results showed that soil erosion is accelerated by the discontinuous urban fabric (r = 0.224, p \u2264 0.01), by construction sites (r = 0.141, p \u2264 0.05), non-irrigated arable land (r = 0.237, p \u2264 0.01), and is mitigated by coniferous forest (r = \u22120.322, p \u2264 0.01), the clay ratio (r = \u22120.652, p \u2264 0.01), and the organic content of the soil (r = \u22120.622, p \u2264 0.01). The models also indicated that there is a strong relationship between soil erosion and the percentage of land use/land cover types (r2 = [0.62, 0.82, 0.83, 0.74]), i.e., mixed forest, non-irrigated arable land, fruit trees and berry plantations, broad-leaf forest, sport and leisure facilities, construction sites, and mineral extraction sites. The findings show that the soil erosion regulation ecosystem service is sensitive to broadleaf forests, rainfed agriculture, soil water content, terrain slope, drainage network density, annual precipitation, the clay ratio, the soil carbon content, and the degree of sensitivity increases from the broadleaf forest to the soil carbon content.</p></article>", "keywords": ["Akaike information criterion", "2. Zero hunger", "landscape composition", "goodness of fit tests", "regression models", "Goodness of fit tests", "Landscape composition", "04 agricultural and veterinary sciences", "Regression models", "15. Life on land", "01 natural sciences", "6. Clean water", "sensitivity analysis", "11. Sustainability", "0401 agriculture", " forestry", " and fisheries", "Sensitivity analysis", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://www.mdpi.com/2073-4441/13/22/3274/pdf"}, {"href": "https://www.mdpi.com/2073-4441/13/22/3274/pdf"}, {"href": "https://doi.org/10261/279273"}, {"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": "10261/279273", "name": "item", "description": "10261/279273", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/279273"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-18T00:00:00Z"}}, {"id": "10261/279275", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:17Z", "type": "Journal Article", "created": "2021-12-14", "title": "The Small Water Cycle in the Czech Landscape: How Has It Been Affected by Land Management Changes Over Time?", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>For the Czech Republic to recover from the effects of past mismanagement, it is necessary to determine how its landscape management can be improved holistically by reinforcing the small water cycle. We conducted a scenario analysis across four time periods using SWAT (Soil and Water Assessment Tool) to determine the effects of land use, land management, and crop rotation shifts since the 1800s in what is now the Czech Republic. The 1852 and 1954 land-use scenarios behaved the most similarly hydrologically across all four scenarios, likely due to minimal landscape transformation and the fact that these two scenarios occur prior to the widespread incorporation of subsurface tile drainages across the landscape. Additionally, the crop rotation of 1920\u20131938 reinforces the small water cycle the most, while that of 1950\u20131989 reinforces the small water cycle the least. Diversified crop rotations should be incentivized to farmers, and increasing the areas of forest, brush, and permanent grassland should be prioritized to further reinforce the small water cycle. It is necessary to foster relationships and open communication between watershed managers, landowners, and scientists to improve the small water cycle and to pave the way for successful future hydrological modeling in the Czech Republic.</p></article>", "keywords": ["landscape management; small water cycle; crop rotation; land-use change; scenario analysis; SWAT", "2. Zero hunger", "Land-use change", "04 agricultural and veterinary sciences", "15. Life on land", "Small water cycle", "01 natural sciences", "Scenario analysis", "6. Clean water", "Landscape management", "Crop rotation", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "SWAT", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://www.mdpi.com/2071-1050/13/24/13757/pdf"}, {"href": "https://www.mdpi.com/2071-1050/13/24/13757/pdf"}, {"href": "https://doi.org/10261/279275"}, {"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": "10261/279275", "name": "item", "description": "10261/279275", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/279275"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-12-13T00:00:00Z"}}, {"id": "10419/302564", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:23Z", "type": "Report", "title": "Sustainable Cultivated Landscapes in Germany: Goals and Requirements from an Ecological, Economic and Legal Perspective", "description": "The global increase in greenhouse gases is also changing the climate conditions more severely in Germany. This particularly affects local cultivated landscapes, which cover large parts of Germany and are already experiencing a wide range of ecological problems. Although agricultural land use characterises cultivated landscapes, their sustainability does not only depend on a change in farming methods. The creation of sustainable cultivated landscapes requires an approach that goes beyond individual actions, which is rather a task for society as a whole that extends well beyond the responsibility and possibilities of individual landowners and managers. Based on the common ecological problems and the specific challenges of climate change described in more detail in the article, we therefore analyse what sustainability means and which social goals and requirements can be identified for cultivated landscapes. The article aims to create a basis for developing practical concepts for measures, government regulations and state subsidies.", "keywords": ["2. Zero hunger", "ddc:330", "Landscape ecology", "forestry", "International law", "Sustainable agriculture", "nature conservation", "cultivated landscape", "climate change", " cultivated landscape", " agriculture", " forestry", " sustainability", " international law", " European law", " constitutional law", " nature conservation", " ecosystems", " biodiversity", "15. Life on land", "sustainability", "constitutional law", "European law", "Ecosystems", "12. Responsible consumption", "Constitutional law", "climate change", "13. Climate action", "11. Sustainability", "Sustainability sciences", "Law enforcement", "international law", "ecosystems", "agriculture", "biodiversity"]}, "links": [{"href": "https://doi.org/10419/302564"}, {"rel": "self", "type": "application/geo+json", "title": "10419/302564", "name": "item", "description": "10419/302564", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10419/302564"}, {"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": "10419/302565", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:23Z", "type": "Report", "title": "Sustainable Cultivated Landscapes in Germany: Comparison of 27 Practical Measures for more Sustainability and their Effectiveness", "description": "With months of drought, hot summers and flooding, global warming has also become increasingly apparent in Germany over recent years. The Climate Protection Act, which was amended in 2021, therefore aims to achieve climate neutrality by 2045. At the same time, a favourable conservation status for habitats, species and water bodies are still the exception in cultivated landscapes, in spite of obligations under European law to achieve this. In this article, we estimate the potential impacts of various landscape designs and integrated land-use measures in terms of climate change mitigation and adaptation, favourable conservation status as well as long-term food security and profitable land use. Based on these impact assessments, we then identify priority measures to be taken. The comparative assessment of effectiveness is intended to help prioritise the most suitable measures in view of limited financial and human resources.", "keywords": ["2. Zero hunger", "ddc:330", "forestry", "security of food", "climate adaptation", "15. Life on land", "7. Clean energy", "6. Clean water", "12. Responsible consumption", "climate change", "13. Climate action", "11. Sustainability", "design of cultivated landscapes", "integrated measures", "water and biomass supply", "agriculture", "prioritisation", "biodiversity"]}, "links": [{"href": "https://doi.org/10419/302565"}, {"rel": "self", "type": "application/geo+json", "title": "10419/302565", "name": "item", "description": "10419/302565", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10419/302565"}, {"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": "20.500.11850/524138", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:49Z", "type": "Journal Article", "created": "2022-01-09", "title": "Lessons learned from a long\u2010term irrigation experiment in a dry Scots pine forest: Impacts on traits and functioning", "description": "Abstract<p>Climate change exposes ecosystems to strong and rapid changes in their environmental boundary conditions mainly due to the altered temperature and precipitation patterns. It is still poorly understood how fast interlinked ecosystem processes respond to altered environmental conditions, if these responses occur gradually or suddenly when thresholds are exceeded, and if the patterns of the responses will reach a stable state. We conducted an irrigation experiment in the Pfynwald, Switzerland from 2003\uffe2\uff80\uff932018. A naturally dry Scots pine (Pinus sylvestris L.) forest was irrigated with amounts that doubled natural precipitation, thus releasing the forest stand from water limitation. The aim of this study was to provide a quantitative understanding on how different traits and functions of individual trees and the whole ecosystem responded to increased water availability, and how the patterns and magnitudes of these responses developed over time. We found that the response magnitude, the temporal trajectory of responses, and the length of initial lag period prior to significant response largely varied across traits. We detected rapid and stronger responses from aboveground tree traits (e.g., tree\uffe2\uff80\uff90ring width, needle length, and crown transparency) compared to belowground tree traits (e.g., fine\uffe2\uff80\uff90root biomass). The altered aboveground traits during the initial years of irrigation increased the water demand and trees adjusted by increasing root biomass during the later years of irrigation, resulting in an increased survival rate of Scots pine trees in irrigated plots. The irrigation also stimulated ecosystem\uffe2\uff80\uff90level foliar decomposition rate, fungal fruit body biomass, and regeneration abundances of broadleaved tree species. However, irrigation did not promote the regeneration of Scots pine trees, which are reported to be vulnerable to extreme droughts. Our results provide extensive evidence that tree\uffe2\uff80\uff90 and ecosystem\uffe2\uff80\uff90level responses were pervasive across a number of traits on long\uffe2\uff80\uff90term temporal scales. However, after reaching a peak, the magnitude of these responses either decreased or reached a new stable state, providing important insights into how resource alterations could change the system functioning and its boundary conditions.</p", "keywords": ["Biomass (ecology)", "0106 biological sciences", "Atmospheric Science", "Ecosystem Resilience", "01 natural sciences", "Environmental science", "Biodiversity Conservation and Ecosystem Management", "Ecosystem properties", "Climate change", "functional traits", "Irrigation", "Biology", "Ecosystem", "Nature and Landscape Conservation", "Climate change; Ecosystem properties; Ecosystem resilience; functional traits; long-term irrigation; Scots pine", "Global and Planetary Change", "Tree Line Shifts", "Ecology", "Global Forest Drought Response and Climate Change", "Causes and Impacts of Climate Change Over Millennia", "Botany", "15. Life on land", "Pinus", "Agronomy", "6. 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In this study, we assessed habitat quality by using the Syrph The Net database and data on decreasing species richness over a 25-year period for the two largest phytophagous hoverfly genera (Merodon and Cheilosia). Furthermore, within this time frame, we explored congruence between ecological responses (species richness and Biodiversity Maintenance Function for these two genera) and landscape structural changes through correlation analysis. Our results indicate that landscapes have experienced changes in aggregation, isolation/connectivity and landscape diversity, with these parameters being significantly correlated with Cheilosia species richness loss and habitat quality. 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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. The access to this data is restricted during embargo time. 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Landscape Research (ZALF), GRID: 433014.1", "position": null, "roles": ["dataCollector"], "phones": [{"value": null}], "emails": [{"value": "larissa.raatz@uni-potsdam.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": null, "protocol": null, "protocol_url": "", "name": "0000-0002-6051-4068", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Larissa Raatz", "organization": "University of Potsdam, GRID: 11348.3f and Leibniz Centre for Agricultural Landscape Research (ZALF), GRID: 433014.1", "position": null, "roles": ["pointOfContact"], "phones": [{"value": null}], "emails": [{"value": "larissa.raatz@uni-potsdam.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": null, "protocol": null, "protocol_url": "", "name": "0000-0002-6051-4068", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Gernot Verch", "organization": "Leibniz Centre for Agricultural Landscape Research (ZALF), GRID: 433014.1", "position": null, "roles": ["dataCollector"], "phones": [{"value": null}], "emails": [{"value": "verch@zalf.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"name": "Marina M\u00fcller", "organization": "Leibniz Centre for Agricultural Landscape Research (ZALF), GRID: 433014.1", "position": null, "roles": ["dataCollector"], "phones": [{"value": null}], "emails": [{"value": "mmueller@zalf.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"name": "Karin Pirhofer Walzl", "organization": "Plant Ecology, Institute of Biology, Freie Universit\u00e4t Berlin, Altensteinstra\u00dfe 6, 14195 Berlin, Germany and Leibniz-Centre for Agricultural Landscape Research (ZALF) e.V.", "position": null, "roles": ["dataCollector"], "phones": [{"value": null}], "emails": [{"value": "karin.pirhofer@gmail.com"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": null, "protocol": null, "protocol_url": "", "name": "0000-0003-2185-4016", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Christoph Scherber", "organization": "Centre for Biodiversity Monitoring Zoological Research Museum Alexander Koenig, Bonn", "position": null, "roles": ["supervisor"], "phones": [{"value": null}], "emails": [{"value": "c.scherber@leibniz-zfmk.de"}], "addresses": [{"deliveryPoint": [null], 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Joshi", "organization": "Landscape Architecture, Institute for Landscape and Open Space, Hochschule f\u00fcr Technik Rapperswil (HSR), GRID: 507560.1", "position": null, "roles": ["supervisor"], "phones": [{"value": null}], "emails": [{"value": "jasmin.joshi@ost.ch"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": null, "protocol": null, "protocol_url": "", "name": "0000-0002-4210-2465", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"organization": "University of Potsdam, GRID: 11348.3f and Leibniz Centre for Agricultural Landscape Research (ZALF), GRID: 433014.1", "roles": ["contributor"]}], "title_alternate": "Leaf Herbivory (child table)"}, "links": [{"href": "https://maps.bonares.de/mapapps/resources/apps/bonares/index.html?lang=en&mid=13715847-0b54-424d-a9a7-c8aa6f79df5c", "rel": "information"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/fb679ec3-1df0-4ce0-82d6-dcba484b9a71", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "13715847-0b54-424d-a9a7-c8aa6f79df5c", "name": "item", "description": "13715847-0b54-424d-a9a7-c8aa6f79df5c", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/13715847-0b54-424d-a9a7-c8aa6f79df5c"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-06-29T00:00:00Z"}}, {"id": "1854/LU-01HKW8NV919BHYC76RGK7TE6QG", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:40Z", "type": "Journal Article", "created": "2023-11-22", "title": "First Steps in Developing a Fast, Cheap, and Reliable Method to Distinguish Wild Mushroom and Truffle Species", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Wild mushrooms and truffles (MT) are important resources, which can contribute to the socioeconomic sustainability of forestry ecosystems. However, not all wild MT are edible. Fast, cheap, and reliable methods that distinguish wild MT species (including the deadly ones) can contribute to valuing these important forest resources. Here, we tested if wild MT species, and their edibility, could be distinguished based on their aroma profiles (i.e., smellprints). For that, we combined the use of the electronic nose with classification models (linear discriminant analysis (LDA) and partial least squares discriminant analysis (PLS-DA)) to distinguish between 14 wild MT species (including edible and non-edible species) collected in Portugal. The 14 wild MT species could be accurately distinguished using LDA (93% accuracy), while the edible and non-edible species could be accurately distinguished using both LDA and PLS-DA (97% and 99% accuracy, respectively). Keeping in mind that our methodological design\u2019s feasibility was verified using a small sample, the data show the potential of the combined use of the electronic nose with discriminant analysis to distinguish wild MT species and their edibility based on their aromatic profile. Although a larger dataset will be necessary to develop a quick and reliable identification method, it shows potential to be as accurate as the identification performed by mycologists and molecular biology, yet requiring less technical training, and the analyses are cheaper and faster.</p></article>", "keywords": ["Agriculture and Food Sciences", "electronic nose", "electronic nose; forest resources; identification method; volatile profile; wild mushrooms and truffles", "identification method", "IDENTIFICATION", "Science", "Q", "FUNGI", "volatile profile", "04 agricultural and veterinary sciences", "NUTRITIONAL-VALUE", "15. Life on land", "CHEMICAL-COMPOSITION", "FOREST", "0404 agricultural biotechnology", "FOOD", "MANAGEMENT", "wild mushrooms and truffles", "0405 other agricultural sciences", "POISONOUS MUSHROOMS", "forest resources", "Nature and Landscape Conservation"]}, "links": [{"href": "https://repositorio.ulisboa.pt/bitstream/10451/61723/1/Ferreira%20et%20al%202023c.pdf"}, {"href": "https://doi.org/1854/LU-01HKW8NV919BHYC76RGK7TE6QG"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Resources", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1854/LU-01HKW8NV919BHYC76RGK7TE6QG", "name": "item", "description": "1854/LU-01HKW8NV919BHYC76RGK7TE6QG", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1854/LU-01HKW8NV919BHYC76RGK7TE6QG"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-11-22T00:00:00Z"}}, {"id": "1959.7/uws:63733", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:43Z", "type": "Journal Article", "created": "2018-02-27", "title": "Temperature and aridity regulate spatial variability of soil multifunctionality in drylands across the globe", "description": "Abstract<p>The relationship between the spatial variability of soil multifunctionality (i.e., the capacity of soils to conduct multiple functions; SVM) and major climatic drivers, such as temperature and aridity, has never been assessed globally in terrestrial ecosystems. We surveyed 236 dryland ecosystems from six continents to evaluate the relative importance of aridity and mean annual temperature, and of other abiotic (e.g., texture) and biotic (e.g., plant cover) variables as drivers of SVM, calculated as the averaged coefficient of variation for multiple soil variables linked to nutrient stocks and cycling. We found that increases in temperature and aridity were globally correlated to increases in SVM. Some of these climatic effects on SVM were direct, but others were indirectly driven through reductions in the number of vegetation patches and increases in soil sand content. The predictive capacity of our structural equation\uffc2\uffa0modelling was clearly higher for the spatial variability of N\uffe2\uff80\uff90 than for C\uffe2\uff80\uff90 and P\uffe2\uff80\uff90related soil variables. In the case of N cycling, the effects of temperature and aridity were both direct and indirect via changes in soil properties. For C and P, the effect of climate was mainly indirect via changes in plant attributes. These results suggest that future changes in climate may decouple the spatial availability of these elements for plants and microbes in dryland soils. Our findings significantly advance our understanding of the patterns and mechanisms driving SVM in drylands across the globe, which is critical for predicting changes in ecosystem functioning in response to climate change.</p", "keywords": ["Abiotic component", "Atmospheric sciences", "Physical geography", "Arid", "Climate Change", "Soil Science", "Spatial variability", "Environmental science", "Agricultural and Biological Sciences", "Soil", "Biodiversity Conservation and Ecosystem Management", "Soil texture", "Aridity index", "XXXXXX - Unknown", "Soil water", "FOS: Mathematics", "Pathology", "Climate change", "Biology", "Ecosystem", "Nature and Landscape Conservation", "Soil science", "2. Zero hunger", "Global and Planetary Change", "Soil Fertility", "Ecology", "Geography", "Global Forest Drought Response and Climate Change", "Statistics", "Temperature", "Life Sciences", "Cycling", "Geology", "FOS: Earth and related environmental sciences", "04 agricultural and veterinary sciences", "Plants", "15. Life on land", "Archaeology", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Physical Sciences", "Medicine", "0401 agriculture", " forestry", " and fisheries", "Soil Carbon Dynamics and Nutrient Cycling in Ecosystems", "Ecosystem Functioning", "Vegetation (pathology)", "Mathematics"]}, "links": [{"href": "https://eprints.whiterose.ac.uk/128150/8/Dur-n_et_al-2018-Ecology.pdf"}, {"href": "https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecy.2199"}, {"href": "https://doi.org/1959.7/uws:63733"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Ecology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1959.7/uws:63733", "name": "item", "description": "1959.7/uws:63733", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1959.7/uws:63733"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-05-01T00:00:00Z"}}, {"id": "20.500.14243/532230", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:53Z", "type": "Journal Article", "created": "2024-07-06", "title": "Disentangling soil-based ecosystem services synergies, trade-offs, multifunctionality, and bundles: A case study at regional scale (NE Italy) to support environmental planning", "description": "The explicit use of ecosystem services (ESs) assessments has been called as a way to guide environmental decision making, yet the promise of the ES approach lies behind its potential. A way to consolidate the approach could be to introduce some aspects into the ESs assessments which might have been neglected so far. Such aspects are mainly: (1) a focus on the complex ESs relations (such as synergies and trade-offs) that can impact the supply of multiple SESs (soil ecosystem services), and (2) focus on potential drivers of SESs relations. We applied bivariate and multivariate approaches to SESs indicators derived from a solid pedological knowledge of the Emilia-Romagna study area in NE Italy. We focused on 7 SES: (1) habitat for soil organisms, (2) filtering and buffering capacity, (3) contribution to microclimate regulation, (4) carbon sequestration, (5) food provision potential, (6) water regulation, and (7) water storage capacity. These SESs were estimated through a combination of point observations, and pedotransfer functions (PTF) estimates spatialised over the area of interest with geostatistical simulation techniques. We found that SESs bivariate spatial relations could be categorised mainly in three types of patterns at regional scale, either: (1) synergistic SESs relations dominating at the region level, (2) trade-offs dominating, or (3) both kind of relations more or less equally frequent. Interestingly, in some cases the dominant regional SESs relation switched at a local level, and such switch was driven by soil properties. For the multivariate case (>2 SESs), two main results are highlighted. First, the combination of properties of some soils is so characteristic that they conform a single SESs bundle, as in the case of the rich SOM soils of alluvial origin in the NE of the region with low agricultural productivity, but high value in regulating SESs. Secondly, some SESs such as potential food provision and water regulation are more important than others to determine locations with high multi-services value at a regional level. This suggests that attention must be paid when ascribing high multi-services value locations as this is not independent of SESs relations. Overall, our results highlight the importance of soils in the potential supply of ESs and show that SESs relations are useful in the implementation of the concept in environmental assessments.", "keywords": ["2. Zero hunger", "Soil multifunctionality index", "Science", "Q", "15. Life on land", "Bivariate local indicators of spatial association", "01 natural sciences", "Soil-based ecosystem services relations", "6. Clean water", "Ecosystem services relations\u2019 drivers", "Pedo-landscapes; Soil multifunctionality index; Soil-based ecosystem services relations; Bivariate local indicators of spatial association; SES k-means clustering; Ecosystem services relations\u2019 drivers", "SES k-means clustering", "Pedo-landscapes", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://iris.cnr.it/bitstream/20.500.14243/532230/1/1-s2.0-S0016706124001915-main.pdf"}, {"href": "https://doi.org/20.500.14243/532230"}, {"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": "20.500.14243/532230", "name": "item", "description": "20.500.14243/532230", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.14243/532230"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-08-01T00:00:00Z"}}, {"id": "1d860c98-603d-466b-b487-6cc05b4ff414", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[11.87, 50.17], [11.87, 51.68], [15.04, 51.68], [15.04, 50.17], [11.87, 50.17]]]}, "properties": {"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 Datenerfassung's research activities.\" Although every care has been taken in preparing and testing the data, the ZALF Datenerfassung and the BonaRes Data Centre cannot guarantee that the data are correct; neither does the ZALF Datenerfassung 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 Datenerfassung and BonaRes Data Centre will not be responsible for any direct or indirect use which might be made of the data.", "updated": "2025-11-26", "type": "Service", "created": "2025-11-05", "language": "eng", "title": "Web Map Service of the dataset 'ECO\u00b2SCAPE Social Network Analysis'", "description": "This Web Map Service includes spatial information used by the dataset 'ECO\u00b2SCAPE Social Network Analysis'", "keywords": ["infoMapAccessService", "agricultural landscape", "farmers", "biodiversity", "resource conservation", "network analysis", "sociology"], "contacts": [{"name": "Leibniz Centre for the Social Sciences", "organization": "GESIS", "position": null, "roles": ["publisher"], "phones": [{"value": null}], "emails": [{"value": "pm@gesis.org"}], "addresses": [{"deliveryPoint": [null], "city": "Mannheim", "administrativeArea": "Baden-W\u00fcrttemberg", "postalCode": null, "country": "Germany"}], "links": [{"href": {"url": null, "protocol": null, "protocol_url": "", "name": "https://ror.org/018afyw53", "name_url": "", "description": "ROR", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Tobias Naaf", "organization": "Leibniz Centre for Agricultural Landscape Research", "position": null, "roles": ["author"], "phones": [{"value": null}], "emails": [{"value": "naaf@zalf.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": null, "protocol": null, "protocol_url": "", "name": "0000-0002-4809-3694", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Maria Kernecker", "organization": "Leibniz Centre for Agricultural Landscape Research", "position": null, "roles": ["projectLeader"], "phones": [{"value": null}], "emails": [{"value": "maria.kernecker@zalf.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": null, "protocol": null, "protocol_url": "", "name": "0000-0002-6118-9164", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Landschaftspflegeverband Nordwestsachsen", "organization": "LPV", "position": null, "roles": ["dataCollector"], "phones": [{"value": null}], "emails": [{"value": "info@lpv-nordwestsachsen.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"organization": "Leibniz Centre for Agricultural Landscape Research", "roles": ["contributor"]}], "themes": [{"concepts": [{"id": "infoMapAccessService"}], "scheme": "GEMET - 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