{"type": "FeatureCollection", "features": [{"id": "10.2134/agronj2010.0504", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:20:47Z", "type": "Journal Article", "created": "2011-07-12", "title": "Western Oregon Grass Seed Crop Rotation And Straw Residue Effects On Soil Quality", "description": "

Understanding the impact of crop rotation and residue management in grass seed production systems on soil quality and, in particular soil C dynamics, is critical in making long\uffe2\uff80\uff90term soil management decisions supporting farm sustainability. The effects of a 6\uffe2\uff80\uff90yr rotation and residue management (high vs. low residue) on soil quality were investigated at three locations in Oregon, each contrasting in soil drainage classification. The crop rotations were continuous perennial grass seed production, grass/legume seed production, and grass/legume/cereal seed production. The grass species grown at each location were different and represented those most commonly produced in each environment; perennial ryegrass (Lolium perenne L.), tall fescue [Schedonorus phoenix (Scop.) Holub], and creeping red fescue (Festuca rubra L.). All three grass seed crop rotations and residue methods maintained high soil quality in conventional or direct seeded soils, but under some situations, soil quality was higher with continuous grass rotation and high residue. Data suggest that straw removal for value\uffe2\uff80\uff90added use, like bioenergy production, can be accomplished in the Pacific Northwest Marine climate without appreciably affecting soil quality. Furthermore, grass seed cropping systems play an important role in soil C storage and enhancement, a valuable ecosystem service in this region where grass seed is produced on land that is not suitable for production of conventional crops that require better\uffe2\uff80\uff90drained soil. We conclude that by nature perennial grass seed crops promote high soil fertility and enriched soil C pools and consequently contribute to the tolerance of these systems to the use of less conservation\uffe2\uff80\uff90oriented crop management methods at times when crop loss could be potentially high. This attribute provides producers greater latitude in selecting soil and crop management options to address issues of soil fertility, pest, weed, or seed certification to minimize economic crop yield losses.

", "keywords": ["2. Zero hunger", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "6. Clean water"], "contacts": [{"organization": "Gerald Whittaker, Richard P. Dick, Gary M. Banowetz, Stephen M. Griffith, George W. Mueller-Warrant,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.2134/agronj2010.0504"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agronomy%20Journal", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.2134/agronj2010.0504", "name": "item", "description": "10.2134/agronj2010.0504", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2134/agronj2010.0504"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2011-07-01T00:00:00Z"}}, {"id": "10.2136/sssaj1995.03615995005900050022x", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:20:55Z", "type": "Journal Article", "created": "2010-07-27", "description": "Abstract

Long\uffe2\uff80\uff90term N fertilization affects soil organic N reserves, N mineralization potential, and crop response to applied N, but little information is available on the influence of short\uffe2\uff80\uff90term N fertilizer (STN) management on soil organic N availability and crop response. This study was conducted to determine if STN changes soil N supplying capability to corn (Zea mays L.) after 3 yr of differential N fertilization on a Fayette silt loam soil (fine\uffe2\uff80\uff90silty, mixed, mesic Typic Hapludalf) in Wisconsin. Various rates of N fertilizer (0\uffe2\uff80\uff93402 kg N ha\uffe2\uff88\uff921) were applied to corn in 1983, 1984, and 1985, and their residual effects on corn response were evaluated in 1986. Soil profile No3\uffe2\uff80\uff90N levels in spring 1986 were very low in all plots (48 \uffc2\uffb1 4 kg ha\uffe2\uff88\uff921 [90 cm]\uffe2\uff88\uff921), yet grain yields and N uptake were significantly increased by STN applications. Corn N uptake was linearly related to the total amount of N returned to soil in crop residues during the previous 3 yr. Increased organic N availability under high STN management was equivalent to a 78 kg N ha\uffe2\uff88\uff921 rate, or 47% of the N fertilizer required for optimum crop yields. In aerobic incubations (40 wk) of spring 1986 soil (0\uffe2\uff80\uff9330 cm), STN additions increased N release only in the first few weeks. Kinetics of N mineralization were best described by a two\uffe2\uff80\uff90component model in which the active fraction (NA) of soil organic N was highly correlated with corn N uptake (r = 0.88). Simulation of field conditions showed that 95% of NA is available before crop maturity. A phosphate\uffe2\uff80\uff90borate buffer organic N availability index was significantly and consistently related to STN treatments. Relative increases in total soil organic N corresponded with the 3\uffe2\uff80\uff90yr N balance between fertilizer additions and grain removals, and were about 10 times larger than mineralizable N. These results indicate that immobilization of excess mineral N into stable soil organic N during decomposition of crop residues should be considered in determining the environmental risk of N fertilization. Although labile organic N is a small fraction of the total fertilizer N contribution to soil N, its quantification should allow a more accurate assessment of crop N needs.

", "keywords": ["2. Zero hunger", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "6. Clean water"]}, "links": [{"href": "https://doi.org/10.2136/sssaj1995.03615995005900050022x"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Soil%20Science%20Society%20of%20America%20Journal", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.2136/sssaj1995.03615995005900050022x", "name": "item", "description": "10.2136/sssaj1995.03615995005900050022x", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2136/sssaj1995.03615995005900050022x"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "1995-09-01T00:00:00Z"}}, {"id": "10.2139/ssrn.5084742", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:21:06Z", "type": "Journal Article", "created": "2025-05-25", "title": "ZnO-nanostructured electrochemical sensor for efficient detection of glyphosate in water", "description": "Glyphosate is a widely used broad-spectrum herbicide for controlling grassy weeds, despite having potential health hazards. Herein, we report on a solid-state electrochemical sensor based on ZnO nanoparticles (ZnO NPs) for on-site detection of glyphosate. Accordingly, ZnO NPs was drop-cast on the surface of a disposable screen-printed carbon electrode. Eco-friendly ZnO NPs of only 7 nm crystallite sizes were obtained by green sol-gel synthesis using lemon (Citrus limon) waste aqueous extract as the green reducing and capping/stabilizing agent and Zn nitrate precursor as evidenced by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction and diffuse reflectance. SEM confirmed successful electrode functionalization with the synthesized nanoparticles. Under laboratory conditions in acetate buffer (pH 5), the sensor demonstrated excellent selectivity and sensitivity, with a detection limit of 0.648 \u00b5M, a wide linear detection range (0.5 \u00b5M to 7.5 mM), and a rapid detection time of 30 min. When tested in river water, the sensor achieved a detection limit of 0.96 \u00b5M using differential pulse voltammetry. It also exceptionally tolerated interference from similar organophosphorus compounds and ions commonly found in river water. The excellent detection performance of the sensor was attributed to the strong coordination interactions between Zn atoms and phosphonate/carboxylate groups that are enhanced by a hydrogen bond at acidic pH, as determined by chemical calculations. This disposable sensor offers a cost-effective, efficient, and environmentally friendly solution for monitoring glyphosate in water systems.", "keywords": ["QD71-142", "Environmental water", "Eco-friendly ZnO nanoparticles", "Computational modeling", "Pesticides", "Eco-friendly ZnO nanoparticles;", "[SDV.MP] Life Sciences [q-bio]/Microbiology and Parasitology", "Analytical chemistry", "Sensor"]}, "links": [{"href": "https://doi.org/10.2139/ssrn.5084742"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Talanta%20Open", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.2139/ssrn.5084742", "name": "item", "description": "10.2139/ssrn.5084742", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2139/ssrn.5084742"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-01-01T00:00:00Z"}}, {"id": "10.22541/essoar.171865325.50703739/v1", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:21:09Z", "type": "Journal Article", "created": "2024-06-17", "title": "Physics-Informed Neural Networks for Estimating a Continuous Form of the Soil Water Retention Curve from Basic Soil Properties", "description": "

The soil water retention curve (SWRC) is essential for describing water and energy exchange processes at the interface between the solid earth and the atmosphere. Despite its importance, measuring the SWRC using standard laboratory methods is challenging and time-consuming. This paper presents a novel physics-informed neural network (PINN) approach for developing pedotransfer functions (PTFs) to predict continuous SWRCs based on soil texture, organic carbon content, and dry bulk density. In contrast to conventional parametric PTFs developed for specific SWRC models, the PINN learns a non-specific form of the SWRC by effectively integrating both measurements and physical constraints into the training process. This approach allows the estimated SWRC to maintain its physical integrity from saturation to oven-dry conditions, even in scenarios with sparse data. The new approach is particularly effective for tackling the challenges encountered in developing PTFs on large SWRC datasets, which often have an imbalance towards the wet-end and include numerous samples with limited and unevenly distributed measurements. We compared the performance of the PINN with that of a conventional physics-agnostic neural network using a dataset of 4200 soil samples. While both networks performed similarly at the wet-end where data are abundant, the PINN excelled at the dry-end where data are sparse and unevenly distributed, achieving a normalized RMSE of 0.172 compared to 0.522 for the conventional neural network. The SWRC derived from the PINN is differentiable with respect to the matric potential and can be seamlessly integrated into the governing equations of water flow in the unsaturated zone.

", "keywords": ["Environmental sciences", "physics-constrained machine learning", "physics\u2010constrained machine learning", "soil hydraulic properties", "GE1-350", "15. Life on land", "continuous pedotransfer functions"]}, "links": [{"href": "https://doi.org/10.22541/essoar.171865325.50703739/v1"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water%20Resources%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.22541/essoar.171865325.50703739/v1", "name": "item", "description": "10.22541/essoar.171865325.50703739/v1", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.22541/essoar.171865325.50703739/v1"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-06-17T00:00:00Z"}}, {"id": "10.2307/2265779", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:21:11Z", "type": "Journal Article", "created": "2006-05-09", "title": "Responses Of A C-4 Grass And Three C-3 Forbs To Variation In Nitrogen And Light In Tallgrass Prairie", "description": "

In tallgrass prairie, high plant species diversity results not from a large number of grass species, but from a large number of forb (nongrass, herbaceous) species. Forbs exhibit morphological, life history, and ecophysiological characteristics that contrast sharply with those of the dominant C4 grasses. Success of the subdominant forbs varies strongly with topographic position and burning regime, and landscape scale patterns of abundance are well documented. But comparatively little is known about the mechanisms determining these patterns in persistent tallgrass prairie forbs. To elucidate these mechanisms, (1) leaf\uffe2\uff80\uff94level physiological characteristics of the dominant C4 grass, Andropogon gerardii, and four co\uffe2\uff80\uff94occurring C3 forbs were measured in response to natural and experimentally manipulated gradients of N availability, and (2) seasonal light environments of forbs in contrasting topographic positions and burning regimes and their morphological and physiological responses in these environments were compared to determine whether resource availability and utilization patterns contributed to patterns of forb distribution and abundance. The effects of burning regime and topographic position on maximum rate of photosynthesis (A) and stomatal conductance to water vapor (g) measured at the leaf level were not consistent with patterns of forb abundance. Nitrogen did not appear to limit forb physiological processes, even though increased N availability resulted in higher tissue N concentrations and greater biomass. There was no consistent increase in (A) or decrease in (g) in response to fertilization. However, (A) at low light levels was as much as 67% higher in fertilized Vernonia baldwinii and A. gerardii compared to unfertilized plants. Greater light availability to forbs in the canopy was associated with lower grass biomass production in uplands compared to lowlands and in unburned compared to burned sites. Forbs did not appear to adjust morphologically (leaf area and plant height) to different light environments at different sites. As a result, as much as 90% of forb leaf area in the burned lowland was displayed in low light, whereas as little as 30% of forb leaf area was in low light in the uplands at midseason. Estimates of potential whole\uffe2\uff80\uff94plant carbon uptake, based on leaf area distribution relative to available light and (A) as a function of light availability, agreed well with patterns of forb abundance and production. Differences in light availability may account for much of the variability in forb abundance related to burning regime and topographic position by limiting carbon gain in forbs more in burned lowlands than in other sites.

", "keywords": ["0106 biological sciences", "2. Zero hunger", "15. Life on land", "01 natural sciences"], "contacts": [{"organization": "C. L. Turner, Alan K. Knapp,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.2307/2265779"}, {"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": "10.2307/2265779", "name": "item", "description": "10.2307/2265779", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2307/2265779"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "1996-09-01T00:00:00Z"}}, {"id": "10.2307/2425415", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:21:11Z", "type": "Journal Article", "created": "2006-04-24", "title": "The Effect Of Nitrogen-Fertilization On The Production Of Halophytes In An Inland Salt-Marsh", "description": "The effect of nitrogen fertilization on plant production, soil and plant nitrogen content, and species distribution in an Ohio salt marsh was analyzed. Seasonal measurements indicate that the three dominant species attained maximal production at different times during the growing season. Production of Salicornia europaea increased with nitrogen fertilization and it appears that reduced soil nitrogen concentrations may be responsible for the different growth forms of S. europaea found in this marsh. Shoot nitrogen concentrations of S. europaea were inversely related to the growth response to fertilization. High tissue nitrogen concentrations in Hordeum jubatum and Atriplex triangularis suggest that some factor other than nitrogen is limiting to these species. INTRODUCTION A number of studies concerning production of plants in coastal salt marsh ecosystems suggest that productivity may be limited by availability of nitrogen (Tyler, 1967; Pigott, 1969; Stewart et al., 1972, 1973; Valiela and Teal, 1974; Gallagher, 1975; Patrick and Delaune, 1976; Mendelssohn, 1979b; Haines, 1979). Smart and Barko (1980) showed that although biomass was ultimately determined by the availability of nitrogen, growth rate was affected by the salinity of the sediments. Other effects of nitrogen fertilization on coastal salt marsh vegetation include: increased allocation of resources to sexual reproduction (Jefferies and Perkins, 1977), increased levels of nitrogen in the plant material (Buresh et al., 1980; Pigott, 1969) and a change in the distribution of plants in the salt marsh (Valiela et al., 1975). While these studies suggest that nitrogen may be an important limiting factor in the productivity of coastal marshes, no studies have been done to ascertain if this is true in inland salt marshes. Studies of plant production from inland saline areas (Hadley and Buccos, 1967, Hadley, 1970) have either not examined it in relation to nitrogen limitation, or else have concentrated on the response to nitrogen additions of a single species when grown under greenhouse conditions (Cords, 1960). Lack of tidal action and differences in species composition preclude the assumption that coastal and inland salt marshes respond similarly tonitrogen addition. The Atlantic coastal marshes of the United States are generally characterized by a bay-to-upland sequence of zones consisting of perennial grasses in the low marsh, giving way to annual succulents in the higher portions of the marsh (Niering and Warren, 1980). In an Ohio salt marsh this vegetational pattern was reversed. The annual species Salicornia europaea and Atriplex triangularis form two zones bordering the center of the saline pan with the perennial grass Hordeumjubatum occurring on the outer edge of the marsh, in the area of lower salinity (Ungar et al., 1979). The objectives of this study were to determine seasonal change in plant production, the effect of the nitrate and ammonium forms of nitrogen fertilization on plant production in an inland salt marsh and to determine if nitrogen deficiencies are responsible for the difference in the growth forms of Salicornia. MATERIALS AND METHODS The study area is a saline pan located at the site of the Morton Salt Company, in the city of Rittman, Wayne Co., Ohio (long. 810 47' 30', lat. 400 57' 30':SW?4 Sec 12, T 18N, R 13W). Three vegetation zones characterize the site: a Hordeum jubatum zone, an Atriplex triangularis zone and a zone of Salicornia europaea that was divided into", "keywords": ["0106 biological sciences", "2. Zero hunger", "15. Life on land", "01 natural sciences"], "contacts": [{"organization": "Irwin A. Ungar, David G. Loveland,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.2307/2425415"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/American%20Midland%20Naturalist", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.2307/2425415", "name": "item", "description": "10.2307/2425415", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2307/2425415"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "1983-04-01T00:00:00Z"}}, {"id": "10.2489/jswc.72.4.361", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:21:15Z", "type": "Journal Article", "created": "2017-06-24", "description": "Cover cropping is a widely promoted strategy to enhance soil health in agricultural systems. Despite a substantial body of literature demonstrating links between cover crops and soil biology, an important component of soil health, research evaluating how specific cover crop species influence soil microbial communities remains limited. This study examined the effects of eight fall-sown cover crop species grown singly and in multispecies mixtures on microbial community structure and soil biological activity using phospholipid fatty acid (PLFA) profiles and daily respiration rates, respectively. Fourteen cover crop treatments and a no cover crop control were established in August of 2011 and 2012 on adjacent fields in central Pennsylvania following spring oats (Avena sativa L.). Soil communities were sampled from bulk soil collected to a depth of 20 cm (7.9 in) in fall and spring, approximately two and nine months after cover crop planting and prior to cover crop termination. In both fall and spring, cover crops led to an increase in total PLFA concentration relative to the arable weed community present in control plots (increases of 5.37 nmol g\u22121 and 10.20 nmol g\u22121, respectively). While there was a positive correlation between aboveground plant biomass (whether from arable weeds or cover crops) and total PLFA concentration, we also found that individual cover crop species favored particular microbial functional groups. Arbuscular mycorrhizal (AM) fungi were more abundant beneath oat and cereal rye (Secale cereale L.) cover crops. Non-AM fungi were positively associated with hairy vetch (Vicia villosa L.). These cover crop-microbial group associations were present not only in monocultures, but also multispecies cover crop mixtures. Arable weed communities were associated with higher proportions of actinomycetes and Gram-positive bacteria. Soil biological activity varied by treatment and was positively correlated with both the size and composition (fungal:bacterial ratio) of the microbial community. This research establishes a clear link between cover crops, microbial communities, and soil health. We have shown that while cover crops generally promote microbial biomass and activity, there are species-specific cover crop effects on soil microbial community composition that ultimately influence soil biological activity. This discovery paves the way for intentional management of the soil microbiome to enhance soil health through cover crop selection.", "keywords": ["2. Zero hunger", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land"]}, "links": [{"href": "https://doi.org/10.2489/jswc.72.4.361"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Soil%20and%20Water%20Conservation", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.2489/jswc.72.4.361", "name": "item", "description": "10.2489/jswc.72.4.361", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2489/jswc.72.4.361"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-07-01T00:00:00Z"}}, {"id": "10.3389/fagro.2022.841086", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:21:22Z", "type": "Journal Article", "created": "2022-03-07", "title": "Laser Weeding with Small Autonomous Vehicles: Friends or Foes?", "description": "

Weed control is necessary to ensure a high crop yield with good quality. Herbicide application and mechanical weeding are the most common methods worldwide. The use of herbicides has led to the increasing occurrence of herbicide-resistant weeds and unwanted contamination of the environment. Mechanical weed control harms beneficial organisms, increases the degradation of organic matter, may dry out the soil, and stimulate new cohorts of weed seeds to germinate. Therefore, there is a need to develop more sustainable weed control means. We suggest using small autonomous vehicles equipped with lasers as a sustainable alternative method. Laser beams are based on electricity, which can be produced from non-fossil fuels. Deep learning methods can be used to locate and identify weed and crop plants for targeting and delivery of laser energy with robotic actuators. Given the targeted nature of laser beams, the area exposed for weed control can be reduced substantially compared to commonly used weed control methods. Therefore, the risk of affecting non-target organisms is minimized, and the soil will be kept untouched in the field, avoiding triggering weed seeds to germinate. Small autonomous vehicles may have limited weeding capacity, and precautions need to be taken as reflections from the laser beam can be harmful to humans and animals. In this paper, we discuss the pros and cons of replacing or supplementing common used weed control methods with laser weeding. The ability to use laser weeding technology is relatively new and not yet widely practiced or commercially available. Therefore, we do not discuss and compare the costs of the various methods at this early stage of the development of the technology.

", "keywords": ["2. Zero hunger", "S", "alternative weed control", " integrated weed management", " non-chemical weed control", " site-specific weed management", " thermal weed control", " weed killers", "non-chemical weed control", "Plant culture", "Agriculture", "04 agricultural and veterinary sciences", "15. Life on land", "SB1-1110", "thermal weed control", "integrated weed management", "13. Climate action", "site-specific weed management", "0401 agriculture", " forestry", " and fisheries", "weed killers", "alternative weed control"], "contacts": [{"organization": "Andreasen Christian, Scholle Karsten, Saberi Mahin,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.3389/fagro.2022.841086"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3389/fagro.2022.841086", "name": "item", "description": "10.3389/fagro.2022.841086", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3389/fagro.2022.841086"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-03-07T00:00:00Z"}}, {"id": "10.3389/fmicb.2019.02597", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:21:25Z", "type": "Journal Article", "created": "2019-11-08", "title": "New Insights Into Cinnamoyl Esterase Activity of Oenococcus oeni.", "description": "Some strains of Oenococcus oeni possess cinnamoyl esterase activity that can be relevant in the malolactic stage of wine production liberating hydroxycinnamic acids that are precursors of volatile phenols responsible for sensory faults. The objective of this study was to better understand the basis of the differential activity between strains. After initial screening, five commercial strains of O. oeni were selected, three were found to exhibit cinnamoyl esterase activity (CE+) and two not (CE-). Although the use of functional annotation of genes revealed genotypic variations between the strains, no specific genes common only to the three CE+ strains could explain the different activities. Pasteurized wine was used as a natural source of tartrate esters in growth and metabolism experiments conducted in MRS medium, whilst commercial trans-caftaric acid was used as substrate for enzyme assays. Detoxification did not seem to be the main biological mechanism involved in the activity since unlike its phenolic cleavage products and their immediate metabolites (trans-caffeic acid and 4-ethylcatechol), trans-caftaric acid was not toxic toward O. oeni. In the case of the two CE+ strains OenosTM and CiNeTM, wine-exposed samples showed a more rapid degradation of trans-caftaric acid than the unexposed ones. The CE activity was present in all cell-free extracts of both wine-exposed and unexposed strains, except in the cell-free extracts of the CE- strain CH11TM. This activity may be constitutive rather than induced by exposure to tartrate esters. Trans-caftaric acid was totally cleaved to trans-caffeic acid by cell-free extracts of the three CE+ strains, whilst cell-free extracts of the CE- strain CH16TM showed significantly lower activity, although higher for the strains in experiments with no prior wine exposure. The EstB28 esterase gene, found in the genomes of the 5 strains, did not reveal any difference on the upstream regulation and transport functionality between the strains. This study highlights the complexity of the basis of this activity in wine related O. oeni population. Variable cinnamoyl esterases or/and membrane transport activities in the O. oeni strains analyzed and a possible implication of wine molecules could explain this phenomenon.", "keywords": ["0301 basic medicine", "0303 health sciences", "tartrate esters", "cinnamoyl esterase", "Tartrate esters", "Hydroxycinnamic acids", "Wine", "hydroxycinnamic acids", "[SDV.IDA] Life Sciences [q-bio]/Food engineering", "Microbiology", "QR1-502", "03 medical and health sciences", "Cinnamoyl esterase", "wine", "Oenococcus oeni"]}, "links": [{"href": "https://doi.org/10.3389/fmicb.2019.02597"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Microbiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3389/fmicb.2019.02597", "name": "item", "description": "10.3389/fmicb.2019.02597", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3389/fmicb.2019.02597"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-11-08T00:00:00Z"}}, {"id": "10.3389/fmicb.2022.983823", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:21:26Z", "type": "Journal Article", "created": "2022-11-08", "title": "Long-term effects of early-life rumen microbiota modulation on dairy cow production performance and methane emissions", "description": "

Rumen microbiota modulation during the pre-weaning period has been suggested as means to affect animal performance later in life. In this follow-up study, we examined the post-weaning rumen microbiota development differences in monozygotic twin-heifers that were inoculated (T-group) or not inoculated (C-group) (n\uffe2\uff80\uff89=\uffe2\uff80\uff894 each) with fresh adult rumen liquid during their pre-weaning period. We also assessed the treatment effect on production parameters and methane emissions of cows during their 1st lactation period. The rumen microbiota was determined by the 16S rRNA gene, 18S rRNA gene, and ITS1 amplicon sequencing. Animal weight gain and rumen fermentation parameters were monitored from 2 to 12\uffe2\uff80\uff89months of age. The weight gain was not affected by treatment, but butyrate proportion was higher in T-group in month 3 (p\uffe2\uff80\uff89=\uffe2\uff80\uff890.04). Apart from archaea (p\uffe2\uff80\uff89=\uffe2\uff80\uff890.084), the richness of bacteria (p\uffe2\uff80\uff89<\uffe2\uff80\uff890.0001) and ciliate protozoa increased until month 7 (p\uffe2\uff80\uff89=\uffe2\uff80\uff890.004) and anaerobic fungi until month 11 (p\uffe2\uff80\uff89=\uffe2\uff80\uff890.005). The microbiota structure, measured as Bray\uffe2\uff80\uff93Curtis distances, continued to develop until months 3, 6, 7, and 10, in archaea, ciliate protozoa, bacteria, and anaerobic fungi, respectively (for all: p\uffe2\uff80\uff89=\uffe2\uff80\uff890.001). Treatment or age \uffc3\uff97 treatment interaction had a significant (p\uffe2\uff80\uff89<\uffe2\uff80\uff890.05) effect on 18 bacterial, 2 archaeal, and 6 ciliate protozoan taxonomic groups, with differences occurring mostly before month 4 in bacteria, and month 3 in archaea and ciliate protozoa. Treatment stimulated earlier maturation of prokaryote community in T-group before month 4 and earlier maturation of ciliate protozoa at month 2 (Random Forest: 0.75\uffe2\uff80\uff89month for bacteria and 1.5\uffe2\uff80\uff89month for protozoa). No treatment effect on the maturity of anaerobic fungi was observed. The milk production and quality, feed efficiency, and methane emissions were monitored during cow\uffe2\uff80\uff99s 1st lactation. The T-group had lower variation in energy-corrected milk yield (p\uffe2\uff80\uff89<\uffe2\uff80\uff890.001), tended to differ in pattern of residual energy intake over time (p\uffe2\uff80\uff89=\uffe2\uff80\uff890.069), and had numerically lower somatic cell count throughout their 1st lactation period (p\uffe2\uff80\uff89=\uffe2\uff80\uff890.081), but no differences between the groups in methane emissions (g/d, g/kg DMI, or g/kg milk) were observed. Our results demonstrated that the orally administered microbial inoculant induced transient changes in early rumen microbiome maturation. In addition, the treatment may influence the later production performance, although the mechanisms that mediate these effects need to be further explored.

", "keywords": ["microbiome modulation", "0301 basic medicine", "570", "ta412", "microbiome establishment", "Heifer", "dairy cow", "Rumen function", "Animal science", " dairy science", "Microbiology", "630", "Microbiome modulation", "QR1-502", "rumen function", "Microbiome establishment", "03 medical and health sciences", "Dairy cow", "heifer"]}, "links": [{"href": "https://doi.org/10.3389/fmicb.2022.983823"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Microbiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3389/fmicb.2022.983823", "name": "item", "description": "10.3389/fmicb.2022.983823", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3389/fmicb.2022.983823"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-11-08T00:00:00Z"}}, {"id": "10.3402/tellusb.v54i5.16689", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:21:50Z", "type": "Journal Article", "created": "2012-12-17", "description": "We present a first analysis of data (June 1998 to December 2000) from the long-term eddy covariance site established in a\u00a0Pinus sylvestris stand near Zotino in central Siberia as part of the EUROSIBERIAN CARBONFLUX project. As well as examining seasonal patterns in net ecosystem exchange\u00a0(NE), daily, seasonal and annual estimates of the canopy photosynthesis (or gross primary productivity,\u00a0GP) were obtained using\u00a0NE and ecosystem respiration measurements.Although the forest was a small (but significant) source of CO2 throughout the snow season (typically mid-October to early May) there was a rapid commencement of photosynthetic capacity shortly following the commencement of above-zero air temperatures in spring: in 1999 the forest went from a quiescent state to significant photosynthetic activity in only a few days. Nevertheless, canopy photosynthetic capacity was observed to continue to increase slowly throughout the summer months for both 1999 and 2000, reaching a maximum capacity in early August. During September there was a marked decline in canopy photosynthesis which was only partially attributable to less favourable environmental conditions. This suggests a reduction in canopy photosynthetic capacity in autumn, perhaps associated with the cold hardening process. For individual time periods the canopy photosynthetic rate was mostly dependent upon incoming photon irradiance. However, reductions in both canopy conductance and overall photosynthetic rate in response to high canopy-to-air vapour differences were clearly evident on hot dry days. The relationship between canopy conductance and photosynthesis was examined using Cowan's notion of optimality in which stomata serve to maximise the marginal evaporative cost of plant carbon gain. The associated Lagrangian multiplier (\u03bb) was surprisingly constant throughout the growing season. Somewhat remarkably, however, its value was markedly different between years, being\u00a0416 mol mol\u22121 in 1999 but\u00a0815 mol mol\u22121 in 2000. Overall the forest was a substantial sink for CO2 in both 1999 and 2000: around\u00a013 mol C m\u22122 a\u22121. Data from this experiment, when combined with estimates of net primary productivity from biomass sampling suggest that about 20% of this sink was associated with increasing plant biomass and about 80% with an increase in the litter and soil organic carbon pools. This high implied rate of carbon accumulation in the litter soil organic matter pool seems unsustainable in the long term and is hard to explain on the basis of current knowledge.DOI:\u00a010.1034/j.1600-0889.2002.01487.x", "keywords": ["13. Climate action", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.3402/tellusb.v54i5.16689"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Tellus%20B%3A%20Chemical%20and%20Physical%20Meteorology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3402/tellusb.v54i5.16689", "name": "item", "description": "10.3402/tellusb.v54i5.16689", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3402/tellusb.v54i5.16689"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2002-01-01T00:00:00Z"}}, {"id": "10.4081/ija.2012.e26", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:21:58Z", "type": "Journal Article", "created": "2012-05-31", "description": "Interest in biochar (BC) has grown dramatically in recent years, due mainly to the fact that its incorporation into soil reportedly enhances carbon sequestration and fertility. Currently, BC types most under investigation are those obtained from organic matter (OM) of plant origin. As great amounts of manure solids are expected to become available in the near future, thanks to the development of technologies for the separation of the solid fraction of animal effluents, processing of manure solids for BC production seems an interesting possibility for the recycling of OM of high nutrient value. The aim of this study was to investigate carbon (C) sequestration and nutrient dynamics in soil amended with BC from dried swine manure solids. The experiment was carried out in laboratory microcosms on a silty clay soil. The effect on nutrient dynamics of interaction between BC and fresh digestate obtained from a biogas plant was also investigated to test the hypothesis that BC can retain nutrients. A comparison was made of the following treatments: soil amended with swine manure solids (LC), soil amended with charred swine manure solids (LT), soil amended with wood chip (CC), soil amended with charred wood chip (CT), soil with no amendment as control (Cs), each one of them with and without incorporation of digestate (D) for a total of 10 treatments. Biochar was obtained by treating OM (wood chip or swine manure) with moisture content of less than 10% at 420\u00b0C in anoxic conditions. The CO2-C release and organic C, available phosphorus (P) (Olsen P, POls) and inorganic (ammonium+nitrate) nitrogen (N) (Nmin) contents at the start and three months after the start of the experiment were measured in the amended and control soils. After three months of incubation at 30\u00b0C, the CO2-C emissions from soil with BC (CT and LT, \u00b1D) were the same as those in the control soil (Cs) and were lower than those in the soils with untreated amendments (CC and LC, \u00b1D). The organic C content decreased in CT and LT to a lesser extent than in CC and LC. In soils with D (+D), the CO2-C emissions were equal to or higher than those in soils without (-D). The Nmin content increased in all treatments; the POls content decreased in the +D treatments. The incorporation of BC into soil, by reducing CO2 emissions, actually contributes to C sequestration without modifying N availability for crops. For a given N content, the BC from swine manure solids supplies much more P than the non-treated OM and, therefore, represents an interesting source of P for crops.", "keywords": ["2. Zero hunger", "S", "emissions", "Plant culture", "Agriculture", "04 agricultural and veterinary sciences", "nitrogen", "6. Clean water", "SB1-1110", "13. Climate action", "manure", "0401 agriculture", " forestry", " and fisheries", "biochar", "phosphorus"]}, "links": [{"href": "https://doi.org/10.4081/ija.2012.e26"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Italian%20Journal%20of%20Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.4081/ija.2012.e26", "name": "item", "description": "10.4081/ija.2012.e26", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.4081/ija.2012.e26"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2012-01-01T00:00:00Z"}}, {"id": "10.5061/dryad.wh70rxwww", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:22:15Z", "type": "Dataset", "created": "2024-06-19", "title": "Data from: Competition between mixo- and heterotrophic ciliates under dynamic resource supply", "description": "unspecifiedThe outcome of species competition strongly depends on the traits of the competitors and associated trade-offs, as well as on environmental variability. Here we investigate the relevance of consumer trait variation for species coexistence in a ciliate consumer \u2013 microalgal prey system under fluctuating regimes of resource supply. We focus on consumer competition and feeding traits, and specifically on the consumer\u2019s ability to overcome periods of resource limitation by mixotrophy, i. e. the ability of photosynthetic carbon fixation via algal symbionts in addition to phagotrophy. In a 48-day chemostat experiment, we investigated competitive interactions of different heterotrophic and mixotrophic ciliates of the genera Euplotes and Coleps under different resource regimes, providing prey either continuously or in pulses under constant or fluctuating light, entailing periods of resource depletion in fluctuating environments, but overall providing the same amount of prey and light. Although ultimate competition results remained unaffected, population dynamics of mixotrophic and heterotrophic ciliates were significantly altered by resource supply mode. However, the effects differed among species combinations and changed over time. Whether mixotrophs or heterotrophs dominated in competition strongly depended on the genera of the competing species and thus species-specific differences in the minimum resource requirements that are associated with feeding on shared prey, nutrient uptake, light harvesting and access to additional resources such as bacteria. Potential differences in the curvature of the species\u2019 resource-dependent growth functions may have further mediated the species-specific responses to the different resource supply modes. Overall, our study demonstrates that genus- or species-specific traits other than related to nutritional mode may override the relevance of acquired phototrophy by heterotrophs in competitive interactions, and that the potential advantage of photosynthetic carbon fixation of symbiont-bearing mixotrophs in competition with pure heterotrophs may differ greatly among different mixotrophs, playing out under different environmental conditions and depending on the specific requirements of the species. Complex trophic interactions determine the outcome of competition, which can only be understood by taking on a multidimensional trait perspective.", "keywords": ["Ciliates", "mixotrophy", "FOS: Biological sciences", "coexistence", "resource fluctuations", "microalgae-ciliate symbiosis"], "contacts": [{"organization": "Fl\u00f6der, Sabine, Klauschies, Toni, Klaassen, Moritz, Stoffers, Tjardo, Lambrecht, Max, Moorthi, Stefanie,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.wh70rxwww"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.wh70rxwww", "name": "item", "description": "10.5061/dryad.wh70rxwww", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.wh70rxwww"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-06-23T00:00:00Z"}}, {"id": "10.5194/amt-2021-82", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:22:19Z", "type": "Journal Article", "created": "2021-03-22", "title": "An automated system for trace gas \ufb02ux measurements from plantfoliage and other plant compartments", "description": "

Abstract. Plant shoots can act as sources or sinks of trace gases including methane and nitrous oxide. Accurate measurementsof these trace gas fluxes require enclosing of shoots in closed non-steady state chambers. Due to plant physiological activity, this type of enclosures, however, lead to CO2 depletion in the enclosed air volume, condensation of transpired water, and warmingof the enclosures exposed to sunlight, all of which may bias the flux measurements. Here, we present PlasTraGAS, ab novel measurement system designed for continuous and automated measurements of trace gas and volatile organic compound (VOC) fluxes from plant shoots. The system uses transparent shoot enclosures equipped with Peltier cooling elements and automatically replaces fixated CO2 and removes transpired water from the enclosure. The system is designed for measuring trace gasfluxes over extended periods, capturing diurnal and seasonal variations and linking trace gas exchange to plant physiologicalfunctioning and environmental drivers. Initial measurements show daytime CH4 emissions two pine shoots of 0.056 and 0.089 nmol g\u22121 foliage d.w.h\u22121or 7.80 and 13.1 nmol m\u22122 h\u22121. Simultaneously measured CO2 uptake rates were 9.2 and 7.6 mmol m\u22122 sec\u22121 and transpiration rates of 1.24 and 0.90 mol m\u22122 h\u22121. Concurrent measurement of VOC emissionsdemonstrated that potential effects of spectral interferences on CH4 flux measurements were at least ten-fold smaller than themeasured CH4 fluxes. Overall, this new system solves multiple technical problems that so far prevented automated plant shoottrace gas flux measurements, and holds the potential for providing important new insights into the role of plant foliage in the global CH4 and N2O cycles.

", "keywords": ["Earthwork. Foundations", "13. Climate action", "TA715-787", "Environmental engineering", "TA170-171", "15. Life on land", "7. Clean energy", "01 natural sciences", "Geosciences", "EMISSIONS", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://amt.copernicus.org/articles/14/4445/2021/amt-14-4445-2021.pdf"}, {"href": "https://doi.org/10.5194/amt-2021-82"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Atmospheric%20Measurement%20Techniques", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/amt-2021-82", "name": "item", "description": "10.5194/amt-2021-82", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/amt-2021-82"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-03-22T00:00:00Z"}}, {"id": "10.5194/bg-11-6969-2014", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:22:20Z", "type": "Journal Article", "created": "2014-12-11", "title": "Meta-analysis of high-latitude nitrogen-addition and warming studies implies ecological mechanisms overlooked by land models", "description": "

Abstract. Accurate representation of ecosystem processes in land models is crucial for reducing predictive uncertainty in energy and greenhouse gas feedbacks with the climate. Here we describe an observational and modeling meta-analysis approach to benchmark land models, and apply the method to the land model CLM4.5 with two versions of belowground biogeochemistry. We focused our analysis on the aboveground and belowground responses to warming and nitrogen addition in high-latitude ecosystems, and identified absent or poorly parameterized mechanisms in CLM4.5. While the two model versions predicted similar soil carbon stock trajectories following both warming and nitrogen addition, other predicted variables (e.g., belowground respiration) differed from observations in both magnitude and direction, indicating that CLM4.5 has inadequate underlying mechanisms for representing high-latitude ecosystems. On the basis of observational synthesis, we attribute the model\uffe2\uff80\uff93observation differences to missing representations of microbial dynamics, aboveground and belowground coupling, and nutrient cycling, and we use the observational meta-analysis to discuss potential approaches to improving the current models. However, we also urge caution concerning the selection of data sets and experiments for meta-analysis. For example, the concentrations of nitrogen applied in the synthesized field experiments (average = 72 kg ha\uffe2\uff88\uff921 yr\uffe2\uff88\uff921) are many times higher than projected soil nitrogen concentrations (from nitrogen deposition and release during mineralization), which precludes a rigorous evaluation of the model responses to likely nitrogen perturbations. Overall, we demonstrate that elucidating ecological mechanisms via meta-analysis can identify deficiencies in ecosystem models and empirical experiments.

", "keywords": ["0301 basic medicine", "QE1-996.5", "Ecology", "Geology", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "03 medical and health sciences", "Life", "13. Climate action", "QH501-531", "0401 agriculture", " forestry", " and fisheries", "QH540-549.5", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.5194/bg-11-6969-2014"}, {"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-11-6969-2014", "name": "item", "description": "10.5194/bg-11-6969-2014", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/bg-11-6969-2014"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2014-08-18T00:00:00Z"}}, {"id": "10.5194/soil-2020-96", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:22:34Z", "type": "Report", "created": "2021-02-06", "title": "Controls on heterotrophic soil respiration and carbon cycling in geochemically distinct African tropical forest soils", "description": "

Abstract. Heterotrophic soil respiration is an important component of the global terrestrial carbon (C) cycle, driven by environmental factors acting from local to continental scales. For tropical Africa, these factors and their interactions remain largely unknown. Here, using samples collected along strong topographic and geochemical gradients in the East African Rift Valley, we study how soil chemistry and soil fertility, derived from the geochemical composition of soil parent material, can drive soil respiration even after many millennia of weathering and soil development. To address the drivers of soil respiration, we incubated soils from three regions with contrasting geochemistry (mafic, felsic, and mixed sedimentary) sampled along slope gradients. For three soil depths, we measured the potential maximum heterotrophic respiration under stable environmental conditions as well as the radiocarbon content (\u039414C) of the bulk soil and respired CO2. We found that soil microbial communities were able to mineralize C from fossil as well as other poor quality C sources under laboratory conditions representative of tropical topsoils. Furthermore, despite similarities in terms of climate, vegetation, and the size of soil C stocks, soil respiration showed distinct patterns with soil depth and parent material geochemistry. The topographic origin of our samples was not a main determinant of the observed respiration rates and \u039414C. In situ, however, soil hydrological conditions likely influence soil C stability by inhibiting decomposition in valley subsoils. Our study shows that soil fertility conditions are the main determinant of C stability in tropical forest soils. Further, in the presence of organic carbon sources of poor quality or the presence of strong mineral related C stabilization, microorganisms tend to discriminate against these sources in favor of more accessible forms of soil organic matter as energy sources, resulting in a slower rate of C cycling. Our results demonstrate that even in deeply weathered tropical soils, parent material has a long-lasting effect on soil chemistry that can influence and control microbial activity, the size of subsoil C stocks, and the turnover of C in soil. Soil parent material and its lasting control on soil chemistry need to be taken into account to understand and predict C stabilization and rates of C cycling in tropical forest soils.

", "keywords": ["2. Zero hunger", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.5194/soil-2020-96"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/soil-2020-96", "name": "item", "description": "10.5194/soil-2020-96", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/soil-2020-96"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-02-04T00:00:00Z"}}, {"id": "10.5281/zenodo.14274476", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-24T16:23:26Z", "type": "Dataset", "title": "SEN4LDN National Demonstration Products on Trends in Carbon Stocks for Land Degradation Neutrality Monitoring", "description": "This dataset contains the National Demonstration products that were generated within the\u00a0ESA SEN4LDN project: 'High resolution Land Degradation Neutrality Monitoring'\u00a0for the sub-indicator on\u00a0Trends in Carbon Stocks over Colombia, Portugal and Uganda. The concept of carbon stocks in terms of LDN assessments according to the United Nations Convention to Combat Desertification (UNCCD) Good Practice Guidance is primarily related to the soil carbon pool and its changes. However, since soil organic carbon (SOC) stock change estimates from remote sensing data are not globally readily available (yet), SEN4LDN explored the use of above-ground biomass (AGB) changes as a proxy for carbon stock changes to provide an estimate independent of the other two sub-indicators (i.e. trends in land cover and trends in land productivity). Two approaches were combined (averaged) to quantify trends in carbon stocks (Araza et al., 2023): a stock change approach based on European Space Agency (ESA) Climate Change Initiative (CCI) biomass maps (version 5), and a gain-loss approach based on the World Resource Institute (WRI) carbon flux model. Results from our hybrid approach provide the estimate of AGB evolution between 2010 and 2018 as well as the standard deviation, indicating the absolute uncertainty of the modeling results. Maps at 100 m spatial resolution have been generated for three countries (Colombia, Portugal and Uganda) as a feasibility assessment. The dataset includes: Hybrid AGB Average 2010-2018, with file naming SEN4LDN_Hybrid-Avg_V100_2010-2018__MAP.tif Hybrid AGB Standard Deviation 2010-2018, with file naming SEN4LDN_Hybrid-Stdev_V100_2010-2018__MAP.tif Products are distributed as country-wide Geotiff files with 0.00088888\u00b0 resolution (~100m). More information on product format and content can be found in the Product User Guide, available on the\u00a0SEN4LDN Deliverables web page. The SEN4LDN project aimed to develop, demonstrate and validate a robust and scientifically-sound EO methodology that exploits the high frequency and spatial resolution of open and free-of-charge satellite imagery to increase the spatial details of national assessments of land degradation and restoration, and provide synoptic information for countries to plan LDN interventions at appropriate scales. More information on\u00a0http://esa-sen4ldn.org/\u00a0. Click here to view the maps in an interactive Google Earth Engine application.", "keywords": ["Life Science"], "contacts": [{"organization": "Araza, Arnan, Berger, Katja, Herold, Martin, Tot\u00e9, Carolien, Van De Kerchove, Ruben,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14274476"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14274476", "name": "item", "description": "10.5281/zenodo.14274476", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14274476"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.14875898", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:23:35Z", "type": "Other", "title": "Les mod\u00e8les de COS doivent \u00eatre valid\u00e9s par des s\u00e9ries temporelles ind\u00e9pendantes pour permettre une pr\u00e9diction fiable", "description": "Les efforts visant \u00e0 maintenir les jeux de donn\u00e9es sont imp\u00e9ratifs pour obtenir des projections et des pr\u00e9visions pr\u00e9cises en mati\u00e8re de COS.", "keywords": ["[SDV.SA.AGRO] Life Sciences [q-bio]/Agricultural sciences/Agronomy", "[SDV.SA.SDS] Life Sciences [q-bio]/Agricultural sciences/Soil study"], "contacts": [{"organization": "Le No\u00eb, Julia, Manzoni, Stefano, Abramoff, Rose, B\u00f6lscher, Tobias, Bruni, Elisa, Cardinael, R\u00e9mi, Ciais, Philippe, Chenu, Claire, Clivot, Hugues, Derrien, Delphine, Ferchaud, Fabien, Garnier, Patricia, Goll, Daniel, Lashermes, Gwena\u00eblle, Martin, Manuel, Rasse, Daniel, Rees, Fr\u00e9d\u00e9ric, Sainte-Marie, Julien, Salmon, \u00c9lodie, Schiedung, Marcus, Schimel, Josh, Wieder, William, Abiven, Samuel, Barr\u00e9, Pierre, C\u00e9cillon, Lauric, Guenet, Bertrand, Delahaie, Amicie,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14875898"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14875898", "name": "item", "description": "10.5281/zenodo.14875898", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14875898"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.14936177", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:23:38Z", "type": "Dataset", "title": "Precision Liming Soil Datasets (LimeSoDa) Zenodo Repository", "description": "Overview Precision Liming Soil Datasets (LimeSoDa) is a collection of 31 datasets from a field- and farm-scale soil mapping context. These datasets are 'ready-to-use' for modeling purposes, as they include target soil properties and features in a tidy tabular format. Three target soil properties are present in every dataset: (1) soil organic matter (SOM) or soil organic carbon (SOC), (2) pH, and (3) clay content, while the features for modeling are dataset-specific. The primary goal of `LimeSoDa` is to enable more reliable benchmarking of machine learning methods in digital soil mapping and pedometrics. All the associated materials and data from LimeSoDa can be downloaded in this data repository. However, for a more in-depth analysis, we refer to the published paper 'LimeSoDa: A Dataset Collection for Benchmarking of Machine Learning Regressors in Digital Soil Mapping' by Schmidinger et al. (2025). You may also use our R\u00a0and Python package likewise called LimeSoDa. \u00a0 Citation Upon usage of datasets from LimeSoDa, please cite our associated paper: Schmidinger, J., Vogel, S., Barkov, V., Pham, A.-D., Gebbers, R., Tavakoli, H., Correa, J., Tavares, T.R., Filippi, P., Jones, E. J., Lukas, V., Boenecke, E., Ruehlmann, J., Schroeter, I., Kramer, E., Paetzold, S., Kodaira, M., Wadoux, A.M.J.-C., Bragazza, L., Metzger, K., Huang, J., Valente, D.S.M., Safanelli, J.L., Bottega, E.L., Dalmolin, R.S.D., Farkas, C., Steiger, A., Horst, T. Z., Ramirez-Lopez, L., Scholten, T., Stumpf, F., Rosso, P., Costa, M.M., Zandonadi, R.S., Wetterlind, J. & Atzmueller, M. (2025). LimeSoDa: A Dataset Collection for Benchmarking of Machine Learning Regressors in Digital Soil Mapping.", "keywords": ["Environmental sciences", "Soil Organic Carbon", "Pedometrics", "pH", "Soil Organic Matter", "Clay", "Remote sensing", "Digital Soil Mapping"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14936177"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14936177", "name": "item", "description": "10.5281/zenodo.14936177", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14936177"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.15680931", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:23:54Z", "type": "Journal Article", "created": "2025-06-15", "title": "Investigating the extent of PFAS contamination in the Upper Danube Basin across environmental compartments", "description": "Abstract Background

Per- and polyfluoroalkyl substances (PFAS) are emerging organic pollutants widely detected in environmental systems, posing risks to human health and the ecosystem. Despite increasing efforts to monitor PFAS in river systems, knowledge gaps remain regarding sources and emissions via different pathways. This study investigates PFAS contamination across multiple environmental compartments in the Upper Danube Basin, including surface water, groundwater, wastewater, landfill leachate, surface runoff, and atmospheric deposition. The primary objectives are to assess the extent of PFAS contamination, identify key emission sources and transport pathways, and evaluate associated risks in terms of the potential exceedance of current and proposed environmental regulatory thresholds in the European Union.

Results

The findings reveal a widespread presence of PFAS, with PFOA, PFOS and short-chain compounds being predominant. The Alz River and Gendorf chemical park emerge as hotspots with far-reaching effects downstream, contributing significantly to diffuse legacy contamination of PFOA and being a significant source of two industrial PFOA substitutes, ADONA and GenX. Wastewater treatment plants, old municipal landfills, and sites with a history of fire-fighting foam application are identified as key pathways or sources of legacy pollution, exhibiting higher concentrations compared to the other matrices. Notably, no significant removal is observed when comparing influent and effluent samples from conventional WWTPs. The study further demonstrates that groundwater is vulnerable to contamination from point sources and to infiltration from rivers, with bank filtration proving largely ineffective in preventing PFAS contamination.

Conclusions

The study underscores the necessity for source and pathway control measures to mitigate PFAS pollution, the implementation of advanced treatment technologies to safeguard drinking water and surface water quality, and targeted remediation for legacy soil and groundwater contamination. Additionally, strong use regulations should be explored to minimize ongoing emissions. The multi-compartment monitoring proves to be a crucial approach to understand the complexity of PFAS distribution at the catchment scale. Comparative analysis and risk assessment highlight challenging situations for water management, offering an indispensable basis for emission modeling as a next step for quantitative assessment of the relevance of different sources and pathways for surface water pollution.

", "keywords": ["Emerging contaminants", "Emerging Pollutants", "PFAS", "Source identification", "Watershed management", "Environmental sciences", "Emission", "Water Framework Directive", "Environmental law", "Water pollution", "GE1-350", "K3581-3598", "Catchment monitoring", "Environmental Monitoring"]}, "links": [{"href": "https://link.springer.com/content/pdf/10.1186/s12302-025-01141-6.pdf"}, {"href": "https://doi.org/10.5281/zenodo.15680931"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Sciences%20Europe", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15680931", "name": "item", "description": "10.5281/zenodo.15680931", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15680931"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-06-15T00:00:00Z"}}, {"id": "10.5281/zenodo.16017208", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:23:58Z", "type": "Dataset", "title": "Cashew orchard soil properties, Dodamarg, Northern Western Ghats, India", "description": "Soil properties of cashew orchards of the Northern Western Ghats, India This project contains chemical properties of soil collected from cashew orchards of Dodamarg, Northern Western Ghats, for a study investigating the factors influencing the effects of forest cover, flower abundance, temperature and (potentially) soil composition on cashew pollinators. Taxonomic Coverage:\u00a0Not applicable Geographic Coverage: Dodamarg, Sindhudurg District, Maharashtra, India Temporal Coverage: March 2025 \u00a0 Description of field and lab methods Soil collection: Soil samples were collected from 30 cashew orchards, using soil core sampler. The diameter of the core sampler was measured before soil collection. All soil samples were collected from 10 cm depth after removing all the leaf litter from the ground. From each orchard, 10 soil columns were collected for analysis of chemical properties. Chemical Properties: We estimated thirteen soil chemical properties for all soil samples collected. The following parameters were analyzed by Zuari Farmhubs Laboratory: pH, electrical conductivity (E.C.) at 25\u00b0C, organic carbon (O.C.), available phosphorus (P\u2082O\u2085), available potassium (K\u2082O), available calcium (Ca), magnesium (Mg), sulfur (S), boron (B), zinc (Zn), iron (Fe), copper (Cu), and manganese (Mn). More details about the data can be obtained from Aditya Satish (adityasatish@ncf-india.org) and Rohit Naniwadekar (rohit@ncf-india.org) from the Nature Conservation Foundation (www.ncf-india.org). File Descriptions: Data file: Dodamarg_2025_Cashew_Soil_Properties.csv We have also included a ReadMe.txt file that explains the data file, akin to the description in the metadata. Description of the columns of the data file: Sl no: Serial number Site: Site ID Code: Site code (General location) Latitude: latitude co-ordinate of the plot (in decimal degrees, \u00b0N) Longitude: longitude co-ordinate of the plot (in decimal degrees, \u00b0E) pH: pH of the soil E.C.: Electrical Conductivity at 25\u00b0C (in dS/m) O.C.: Organic Carbon (in %) P\u2082O\u2085: Available P\u2082O\u2085 (in Kg /acre) K\u2082O: Available Potassium (in Kg /acre) Ca: Available Calcium (in mg/Kg) Mg: Available Magnesium (in mg/Kg) S: Available Sulphur (in mg/Kg) B: Available Boron (in mg/Kg) Zn: Available Zinc (in mg/Kg) Fe: Available Iron (in mg/Kg) Cu: Available Copper (in mg/Kg) Mn: Available Manganese (in mg/Kg) Funding:\u00a0 Godrej Consumer Products Limited Arvind Datar Rohini Nilekani Philanthropies", "keywords": ["Soil chemical properties", "Cashew orchards", "Ecology", "FOS: Biological sciences", "Northern Western Ghats"], "contacts": [{"organization": "Sadekar, Vishal, Satish, Aditya, Naniwadekar, Rohit,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.16017208"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.16017208", "name": "item", "description": "10.5281/zenodo.16017208", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.16017208"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-07-17T00:00:00Z"}}, {"id": "10.5281/zenodo.4655380", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:24:14Z", "type": "Journal Article", "created": "2021-03-29", "title": "pH-Responsive Release of Ruthenium Metallotherapeutics from Mesoporous Silica-Based Nanocarriers.", "description": "

Ruthenium complexes are attracting interest in cancer treatment due to their potent cytotoxic activity. However, as their high toxicity may also affect healthy tissues, efficient and selective drug delivery systems to tumour tissues are needed. Our study focuses on the construction of such drug delivery systems for the delivery of cytotoxic Ru(II) complexes upon exposure to a weakly acidic environment of tumours. As nanocarriers, mesoporous silica nanoparticles (MSN) are utilized, whose surface is functionalized with two types of ligands, (2-thienylmethyl)hydrazine hydrochloride (H1) and (5,6-dimethylthieno[2,3-d]pyrimidin-4-yl)hydrazine (H2), which were attached to MSN through a pH-responsive hydrazone linkage. Further coordination to ruthenium(II) center yielded two types of nanomaterials MSN-H1[Ru] and MSN-H2[Ru]. Spectrophotometric measurements of the drug release kinetics at different pH (5.0, 6.0 and 7.4) confirm the enhanced release of Ru(II) complexes at lower pH values, which is further supported by inductively coupled plasma optical emission spectrometry (ICP-OES) measurements. Furthermore, the cytotoxicity effect of the released metallotherapeutics is evaluated in vitro on metastatic B16F1 melanoma cells and enhanced cancer cell-killing efficacy is demonstrated upon exposure of the nanomaterials to weakly acidic conditions. The obtained results showcase the promising capabilities of the designed MSN nanocarriers for the pH-responsive delivery of metallotherapeutics and targeted treatment of cancer.

", "keywords": ["Ruthenium-based anti-cancer drugs", "ruthenium-based anticancer drugs", "PH-responsive drug delivery", "Mesoporous silica nanoparticles", "pH-responsive drug delivery", "02 engineering and technology", "controlled drug delivery", "01 natural sciences", "Article", "cancer treatment", "ddc:", "3. Good health", "0104 chemical sciences", "RS1-441", "Pharmacy and materia medica", "Cancer treatment", "mesoporous silica nanoparticles", "0210 nano-technology", "Controlled drug delivery"]}, "links": [{"href": "http://www.mdpi.com/1999-4923/13/4/460/pdf"}, {"href": "https://www.mdpi.com/1999-4923/13/4/460/pdf"}, {"href": "https://doi.org/10.5281/zenodo.4655380"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Pharmaceutics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4655380", "name": "item", "description": "10.5281/zenodo.4655380", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4655380"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-03-28T00:00:00Z"}}, {"id": "10.5281/zenodo.5574882", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:24:17Z", "type": "Report", "created": "2020-03-09", "title": "Hyperspectral imaging for high resolution mapping of soil profile organic carbon distribution in an Austrian Alpine landscape", "description": "

<p>Studies on soil organic carbon (SOC) stocks mostly focus on topsoils (< 30 cm). However, 30 to 63% of the SOC are stored in the subsoils (30 to 100 cm), and the factors controlling SOC storage in subsoils may be substantially different than in topsoils. The low mean SOC content in subsoils makes its quantification and characterization challenging. Thus, new approaches are required to depict the SOC stocks distribution in full soil profile. Hyperspectral imaging of soil core samples can provide high spatial resolution of the vertical distribution of SOC in a soil profile. The main objective of the ongoing study, within the Horizon 2020 European Project Circular Agronomics, is to apply laboratory hyperspectral imaging with a variety of machine learning approaches for the mapping of OC distribution in undisturbed soil cores. Soil cores were collected down to a depth of one meter in grasslands of 15 organic farms located in the Lungau Valley, in Austria. Some samples were divided into five depths in the field for classical bulk soil measurements (total carbon and nitrogen, texture, pH, EC and bulk density) on disturbed samples. Undisturbed soil cores were sliced vertically for laboratory hyperspectral imaging in the range of Vis-NIR (400-1000 nm). We were able to reveal the hotspots of OC and map the OC distribution in soil profile by applying a variety of machine learning approaches (i.e. partial least square and random forest regression) as a function of spectral responses. A digital elevation model was further exploited to investigate the effects of topographical factors such as elevation, aspect and slope on SOC profile distribution. Landsat 8 data were also used to depict the spatial variability of land insensitive cover/vegetation in study area.</p>

", "keywords": ["2. Zero hunger", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "Vis-NIR imaging spectroscopy", " Alpine grassland", " Digital elevation model", " Subsoils"], "contacts": [{"organization": "YASER OSTOVARI, K\u00f6ppend\u00f6rfer, Baptist, Guigue, Julien, Van Groenigen, Jan Willem, Creamer, Rachel, Guggenberger, Thomas, Grassauer, Florian, Hobley, Eleanor, Ferron, Laura, Martens, Henk, K\u00f6gel-Knabner, Ingrid, Vidal, Alix,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.5574882"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.5574882", "name": "item", "description": "10.5281/zenodo.5574882", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.5574882"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-03-23T00:00:00Z"}}, {"id": "10.5281/zenodo.8089699", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:24:33Z", "type": "Journal Article", "created": "2019-11-28", "title": "High-resolution and three-dimensional mapping of soil texture of China", "description": "The lack of detailed three-dimensional soil texture information largely restricts many applications in agriculture, hydrology, climate, ecology and environment. This study predicted 90 m resolution spatial variations of sand, silt and clay contents at a national extent across China and at multiple depths 0\u20135, 5\u201315, 15\u201330, 30\u201360, 60\u2013100 and 100\u2013200 cm. We used 4579 soil profiles collected from a national soil series inventory conducted recently and currently available environmental covariates. The covariates characterized environmental factors including climate, parent materials, terrain, vegetation and soil conditions. We constructed random forest models and employed a parallel computing strategy for the predictions of soil texture fractions based on its relationship with the environmental factors. Quantile regression forest was used to estimate the uncertainty of the predictions. Results showed that the predicted maps were much more accurate and detailed than the conventional linkage maps and the SoilGrids250m product, and could well represent spatial variation of soil texture across China. The relative accuracy improvement was around 245\u2013370% relative to the linkage maps and 83\u2013112% relative to the SoilGrids250m product with regard to the R2, and it was around 24\u201326% and 14\u201319% respectively with regard to the RMSE. The wide range between 5% lower and 95% upper prediction limits may suggest that there was a substantial room to improve current predictions. Besides, we found that climate and terrain factors are major controllers for spatial patterns of soil texture in China. The heat and water-driven physical and chemical weathering and wind-driven erosion processes primarily shape the pattern of clay content. The terrain, wind and water-driven deposition, erosion and transportation sorting processes of soil particles primarily shape the pattern of silt. The findings provide clues for modeling future soil evolution and for national soil security management under the background of global and regional environmental changes.", "keywords": ["2. Zero hunger", "Digital soil mapping", "13. Climate action", "Large extent", "Machine learning", "Environmental factors", "Uncertainty", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.8089699"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.8089699", "name": "item", "description": "10.5281/zenodo.8089699", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.8089699"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-03-01T00:00:00Z"}}, {"id": "10.5846/stxb201105220671", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:25:03Z", "type": "Journal Article", "created": "2012-08-20", "description": "Litter decomposition is an important component of nutrient cycling and carbon decomposition in grassland ecosystems,and livestock grazing has been a major human intervention to these process.The effects of grazing on litter decomposition vary with climate environment conditions and grassland vegetation types.Alpine mesophytic meadow and alpine semi-hydric marsh meadow are the two rangeland ecosystems commonly seen on the eastern Qinghai-Tibet Plateau,which differentiate themselves by not only the physic/bio environments but also the plant species composition and therefore the litter qualities.In order to understand grazing effects on the litter decomposition of these two meadows,grazed and fenced plots were set respectively on the both meadows.The rates of decomposition and nutrient release were measured for the three littler samples(mesophytic meadow mixed litter,Deschampsia caespitos litter,and Potentilla anserine litter) in the alpine mesophytic meadow plots,and three litter samples(semi-hydric marsh mixed litter,Carex muliensis litter\u3001Kobresia tibetica litter) in the semi-hyddric marsh meadow plots.The four species generally also represented the dominant species showing respectively in the reverse succession series driven by grazing and climate warming.It was found that there were significant differences in litter decompositions for the dominant species.In alpine mesophytic meadow,Potentilla anserine decomposed faster than Deschampsia caespitos,while in alpine semi-hydric meadowKobresia tibetica decomposed more quickly.Grazing accelerated the litter decomposition in general,but the responses varied with the species.On the other hand,Deschamp siacaespitos and Carex muliensis have lower decomposition rates in the grazed plots.Grazing has little effect on organic carbon decomposition and the release of C,but positively affected on the release of N and P from the litters.The patterns of litter decomposition and nutrient release of the dominant species suggested that there might exist a positive feedback effect in the alpine marsh meadow degradation due to the accelerating decomposition rate and C release along the reverse succession series.In addition,Potentilla anserine,a typical dominant species of in degraded meadow,was found to have higher litter quality and faster decomposition rate than the other species,reflecting that in the mesophytic community,the plant adopted 'evasion strategy' rather than 'resistance strategy' in response to heavy grazing.", "keywords": ["2. Zero hunger", "0211 other engineering and technologies", "02 engineering and technology", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"], "contacts": [{"organization": "\u738b\u5fd7\u8fdc Wang Zhiyuan, \u5b59\u5e9a Sun Geng, \u5434\u5b81 Wu Ning, \u7f57\u5149\u8363 Luo Guangrong, \u5f20\u8273\u535a Zhang Yanbo, \u7f57\u9e4f Luo Peng, \u725f\u6210\u9999 Mou Chengxiang,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5846/stxb201105220671"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Acta%20Ecologica%20Sinica", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5846/stxb201105220671", "name": "item", "description": "10.5846/stxb201105220671", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5846/stxb201105220671"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2012-01-01T00:00:00Z"}}, {"id": "10.7910/DVN/KPTWFS", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:25:20Z", "type": "Dataset", "title": "Replication Data for: PERFORMANCE EVALUATION OF INTEGRATED RICE FISH FARMING USING KEBBI AND EBONYI STATE AND THEIR ADJOINING INSTITUTIONAL BASED PLATFORMS AS CASE STUDIES", "description": "Options for farm diversification through integrated aquaculture-agriculture (IAA) are being gradually embraced as a competitive alternative to traditional agriculture because of resource use efficiency and overall productivity. Despite the numerous benefits, the practice of IAA especially integrated rice-fish (IRF) farming in African countries such as Nigeria is limited, therefore, there is a need for proper documentation and demonstration to further encourage IRF adoption. This study was carried out on the MSU/USAID/FAO IRF plot (22m by 15m) for 16 weeks in two states which are Ebonyi and Kebbi and their adjoining institutional-based platforms which are the University of Ibadan (UI) and Usmanu Dan Fodiyo university (UDU) to evaluate the production efficiency and to access the water productivity of combining rice-fish. After transplanting rice seedlings and stocking fish seeds, data were collected on the growth and yield performance of fish such as average body weight(g) and length(cm), survival rate (%) and on rice such as number and length of tiller(cm) number and length of panicles(cm), paddy, grain yield(ton/ha). Water and soil quality parameters such as pH, alkalinity, nitrite, nitrate, ammonia, organic carbon and nitrogen were collected biweekly and monthly. Water use efficiency(kg/ha/cm) was also calculated. Statistical analysis was carried out through analysis of variance (ANOVA) and Ducan multiple range test to find the difference at 5% (p < 0.05) levels. Water quality parameters result showed that alkalinity(mg/l) ranged from 17.8\u00b19.6(Kebbi) to 106.8\u00b14.5(UI), pH ranged from 6.0\u00b11.2(UI) to 8.5\u00b12.1(UDU), nitrate(mg/l) ranged from 0.0\u00b10.0(UI) to 0.3\u00b10.1(Kebbi), nitrite(mg/l) ranged from 0.0\u00b10.0(UI) to 0.5\u00b10.1(Kebbi), ammonia(mg/l) ranged from 0.0\u00b10.1(UI) to 0.5\u00b10.2(UI), hardness(mg/l) ranged from 34.4\u00b118.5(UDU) to 178.6\u00b110.0(UI) and dissolved oxygen(mg/l) ranged from 4.8\u00b10.5(UI) to 13.8\u00b12.8(UDU). For the soil quality parameters result, pH ranged from 5.8\u00b11.1(UI) to 8.0\u00b10.0(UI), nitrogen(g/kg) ranged from 0.6\u00b10.1(UI) to 2.3\u00b10.2(Ebonyi), phosphorus(mg/kg) ranged from 1.2\u00b10.0(Ebonyi) to 13.0\u00b10.0(UI), dissolved oxygen(mg/l) ranged from 4.2\u00b10.4(UI) to 5.6\u00b10.9(UI), organic carbon(g/kg) ranged from 5.0\u00b10.1(UI) to 24.3\u00b16.6(Ebonyi) and potassium(cmol/kg) ranged from 0.1\u00b10.0(Ebonyi) to 1.0\u00b10.3(Kebbi). The number (cell/litre) and abundance(cell/litre) of plankton ranged from 13.0\u00b11.1(Ebonyi) to 230\u00b15.9(UI) and 12.0\u00b11.2(UDUS) to 239\u00b175(UI) respectively. The most dominant species of plankton recorded were rotifera spp, euglena spp, Ulothrix spp and spiruna spp. The highest (73.3) and least (21.5) survival rates (%) were recorded in UI and Ebonyi respectively. The highest (8.3) and the least (1.6) fish yield (ton/ha) were recorded in UI and Kebbi respectively. The highest (5.1) and the least (1.9) rice yield(ton/ha) were recorded in UI and Ebonyi respectively. Consumptive water used(m3) ranged from 197.4\u00b120.5(UI) to 1000.7\u00b160.5(Kebbi), water use efficiency(kg/ha/cm) ranged from 0.5\u00b10.0(Ebonyi) to 1.5\u00b12.2(UI) and water productivity(kg/m3) ranged from 425\u00b140.2(UDU) to 1680\u00b178(Kebbi). There were no significant differences between the mean of water quality parameters in the adaptative plots except for the dissolved oxygen in UDU and Kebbi which were significantly different from UI and Ebonyi. The result revealed that integrated rice fish farming could increase the yield of rice and fish compare to monoculture system of either rice and fish. Therefore, more research should be done and documented on integrated rice fish farming system to ascertain importance of this system for a wider adoption.", "keywords": ["Agricultural Sciences", "Integrated Rice and Fish Farming"], "contacts": [{"organization": "Halwart Mathias, K., Ajani Emmanuel, N. Bart, Amrit, Ajayi, Oluwafemi, Bamidele Omitoyin, Oyebola, Taiwo, Stankus, Austin, Burtle, Gary, E. Fonsah, Greg, Kazeem O. Kareem, Oduntan O., B., Yahaya Abubakar, Ikwuemesi Johnpaul,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/KPTWFS"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/KPTWFS", "name": "item", "description": "10.7910/DVN/KPTWFS", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/KPTWFS"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-01T00:00:00Z"}}, {"id": "10.7910/DVN/M4ZGXP", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:25:21Z", "type": "Dataset", "title": "MSZSI: Multi-Scale Zonal Statistics [AgriClimate] Inventory", "description": "<b>MSZSI: Multi-Scale Zonal Statistics [AgriClimate] Inventory</b> <br><br> -------------------------------------------------------------------------------------- <br> MSZSI is a data extraction tool for Google Earth Engine that aggregates time-series remote sensing information to multiple administrative levels using the FAO GAUL data layers. The code at the bottom of this page (metadata) can be pasted into the Google Earth Engine JavaScript code editor and ran at https://code.earthengine.google.com/. <br><br> <i>Please refer to the associated publication</i>: <br> Peter, B.G., Messina, J.P., Breeze, V., Fung, C.Y., Kapoor, A. and Fan, P., 2024. Perspectives on modifiable spatiotemporal unit problems in remote sensing of agriculture: evaluating rice production in Vietnam and tools for analysis. <i>Frontiers in Remote Sensing</i>, 5, p.1042624. <br> <a href='https://www.frontiersin.org/journals/remote-sensing/articles/10.3389/frsen.2024.1042624'>https://www.frontiersin.org/journals/remote-sensing/articles/10.3389/frsen.2024.1042624</a> <br><br> <i>Input options:</i> <br> [1] Country of interest <br> [2] Start and end year <br> [3] Start and end month <br> [4] Option to mask data to a specific land-use/land-cover type <br> [5] Land-use/land-cover type code from CGLS LULC <br> [6] Image collection for data aggregation <br> [7] Desired band from the image collection <br> [8] Statistics type for the zonal aggregations <br> [9] Statistic to use for annual aggregation <br> [10] Scaling options <br> [11] Export folder and label suffix <br><br> <i>Output:</i> Two CSVs containing zonal statistics for each of the FAO GAUL administrative level boundaries <br> <i>Output fields:</i> system:index, 0-ADM0_CODE, 0-ADM0_NAME, 0-ADM1_CODE, 0-ADM1_NAME, 0-ADMN_CODE, 0-ADMN_NAME, 1-AREA_PERCENT_LULC, 1-AREA_SQM_LULC, 1-AREA_SQM_ZONE, 2-X_2001, 2-X_2002, 2-X_2003, ..., 2-X_2020, .geo <br><br> <img src ='https://github.com/cartoscience/seagul/blob/main/mszsi/mszsi_input_v5.PNG?raw=true' width='1000' height='auto'</img> <br><br> <b>PREPROCESSED DATA DOWNLOAD</b> <br><br> The datasets available for download contain zonal statistics at 2 administrative levels (FAO GAUL levels 1 and 2). Select countries from Southeast Asia and Sub-Saharan Africa <b>(Cambodia, Indonesia, Lao PDR, Myanmar, Philippines, Thailand, Vietnam, Burundi, Kenya, Malawi, Mozambique, Rwanda, Tanzania, Uganda, Zambia, Zimbabwe)</b> are included in the current version, with plans to extend the dataset to contain global metrics. Each zip file is described below and two example NDVI tables are available for preview. <br><br> <b>Key</b>: [source, data, units, temporal range, aggregation, masking, zonal statistic, notes] <br><br> Currently available: <br><b>MSZSI-V2_V-NDVI-MEAN.tar</b>: [NASA-MODIS, NDVI, index, 2001\u20132020, annual mean, agriculture, mean, n/a] <br><b>MSZSI-V2_T-LST-DAY-MEAN.tar</b>: [NASA-MODIS, LST Day, \u00b0C, 2001\u20132020, annual mean, agriculture, mean, n/a] <br><b>MSZSI-V2_T-LST-NIGHT-MEAN.tar</b>: [NASA-MODIS, LST Night, \u00b0C, 2001\u20132020, annual mean, agriculture, mean, n/a] <br><b>MSZSI-V2_R-PRECIP-SUM.tar</b>: [UCSB-CHG-CHIRPS, Precipitation, mm, 2001\u20132020, annual sum, agriculture, mean, n/a] <br><b>MSZSI-V2_S-BDENS-MEAN.tar</b>: [OpenLandMap, Bulk density, g/cm3, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] <br><b>MSZSI-V2_S-ORGC-MEAN.tar</b>: [OpenLandMap, Organic carbon, g/kg, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] <br><b>MSZSI-V2_S-PH-MEAN.tar</b>: [OpenLandMap, pH in H2O, pH, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] <br><b>MSZSI-V2_S-WATER-MEAN.tar</b>: [OpenLandMap, Soil water, % at 33kPa, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] <br><b>MSZSI-V2_S-SAND-MEAN.tar</b>: [OpenLandMap, Sand, %, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] <br><b>MSZSI-V2_S-SILT-MEAN.tar</b>: [OpenLandMap, Silt, %, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] <br><b>MSZSI-V2_S-CLAY-MEAN.tar</b>: [OpenLandMap, Clay, %, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] <br><b>MSZSI-V2_E-ELEV-MEAN.tar</b>: [MERIT, [elevation, slope, flowacc, HAND], [m, degrees, km<sup>2</sup>, m], static, n/a, agriculture, mean, n/a] <br><br><i>Coming soon</i> <br><b>MSZSI-V2_C-STAX-MEAN.tar</b>: [OpenLandMap, Soil taxonomy, category, static, n/a, agriculture, area sum, n/a] <br><b>MSZSI-V2_C-LULC-MEAN.tar</b>: [CGLS-LC100-V3, LULC, category, 2015\u20132019, mode, none, area sum, n/a] <br><br><br> <img src ='https://github.com/cartoscience/seagul/blob/main/mszsi/mszsi_diagram_v2.png?raw=true' width='1000' height='auto'</img> <br><br> <b>Data sources:</b> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MOD13Q1'>https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MOD13Q1</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MOD11A2'>https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MOD11A2</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/UCSB-CHG_CHIRPS_PENTAD'>https://developers.google.com/earth-engine/datasets/catalog/UCSB-CHG_CHIRPS_PENTAD</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_BULKDENS-FINEEARTH_USDA-4A1H_M_v02'>https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_BULKDENS-FINEEARTH_USDA-4A1H_M_v02</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_ORGANIC-CARBON_USDA-6A1C_M_v02'>https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_ORGANIC-CARBON_USDA-6A1C_M_v02</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_PH-H2O_USDA-4C1A2A_M_v02'>https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_PH-H2O_USDA-4C1A2A_M_v02</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_WATERCONTENT-33KPA_USDA-4B1C_M_v01'>https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_WATERCONTENT-33KPA_USDA-4B1C_M_v01</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_CLAY-WFRACTION_USDA-3A1A1A_M_v02'>https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_CLAY-WFRACTION_USDA-3A1A1A_M_v02</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_SAND-WFRACTION_USDA-3A1A1A_M_v02'>https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_SAND-WFRACTION_USDA-3A1A1A_M_v02</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_GRTGROUP_USDA-SOILTAX_C_v01'>https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_GRTGROUP_USDA-SOILTAX_C_v01</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_Landcover_100m_Proba-V-C3_Global'>https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_Landcover_100m_Proba-V-C3_Global</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/MERIT_Hydro_v1_0_1'>https://developers.google.com/earth-engine/datasets/catalog/MERIT_Hydro_v1_0_1</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level0'>https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level0</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level1'>https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level1</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level2'>https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level2</a></li> <br> <b>Project information:</b> <br> SEAGUL: Southeast Asia Globalization, Urbanization, Land and Environment Changes <br> <a href='http://seagul.info/'>http://seagul.info/</a>; <a href='https://lcluc.umd.edu/projects/divergent-local-responses-globalization-urbanization-land-transition-and-environmental'>https://lcluc.umd.edu/projects/divergent-local-responses-globalization-urbanization-land-transition-and-environmental</a> <br> This project was made possible by the the NASA Land-Cover/Land-Use Change Program (Grant #: 80NSSC20K0740) <br><br> For an additional interactive visualization, visit: <a href='https://cartoscience.users.earthengine.app/view/maup-mapper-multi-scale-modis-ndvi'>https://cartoscience.users.earthengine.app/view/maup-mapper-multi-scale-modis-ndvi</a> <br><br> <img src ='https://github.com/cartoscience/seagul/blob/main/mszsi/mszsi_app.png?raw=true' width='1000' height='auto'</img> <br><br><br> <i> Google Earth Engine code</i> <pre> /*/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// MSZSI: Multi-Scale Zonal Statistics Inventory Authors: Brad G. Peter, Department of Geography, University of Alabama Joseph Messina, Department of Geography, University of Alabama Austin Raney, Department of Geography, University of Alabama Rodrigo E. Principe, AgriCircle AG Peilei Fan, Department of Geography, Environment, and Spatial Sciences, Michigan State University Citation: Peter, Brad; Messina, Joseph; Raney, Austin; Principe, Rodrigo; Fan, Peilei, 2021, 'MSZSI: Multi-Scale Zonal Statistics Inventory', https://doi.org/10.7910/DVN/YCUBXS, Harvard Dataverse, V# SEAGUL: Southeast Asia Globalization, Urbanization, Land and Environment Changes http://seagul.info/ https://lcluc.umd.edu/projects/divergent-local-responses-globalization-urbanization-land-transition-and-environmental This project was made possible by the the NASA Land-Cover/Land-Use Change Program (Grant #: 80NSSC20K0740) ///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////*/ /*----------------------------------------------------------------------------------------------------------------------------------- Description: MSZSI is a data extraction tool for aggregating time-series remote sensing information to multiple administrative levels using the FAO GAUL data layers. Input parameterization: [1] Enter the country code for the desired country [2] Select a start and end year. Be sure to check for data availability in the collection selected in input 6. [3] Select a start month and end month to specify a temporal range within each year. [4] Select an image collection for data aggregation. [5] Select the desired band from the image collection. [6] Option to mask data to a specific land-use/land-cover type. Enter 'TRUE' or 'FALSE'. [7] Enter a land-use/land-cover type code from CGLS LULC. Ignore this option if no masking is desired and set input 4 to 'FALSE'. [8] Select a statistics type for the zonal aggregations (defaults to mean) [9] Select a statistic for temporal aggregation (see available options in the parameterization below) [10] Scaling options [11] Export folder output file label suffix Check tasks tab for CSV exports. Select a point on the map to view timeseries statistics. Hover over the layers panel to turn layers on/off and set visualization parameters. For an additional interactive visualization, visit: https://cartoscience.users.earthengine.app/view/maup-mapper-multi-scale-modis-ndvi Boundary data Layers: https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level0 https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level1 https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level2 -----------------------------------------------------------------------------------------------------------------------------------*/ // \u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022 USER PARAMETERIZATION \u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022 /*[1]*/ var countryCode = 264 // Refer to http://www.fao.org/in-action/countrystat/news-and-events/events/training-material/gaul-codes2014/en/ /*[2]*/ var startYear = 2001 // Check data availability for the collection selected in input 4 var endYear = 2020 /*[3]*/ var startMonth = 1 var endMonth = 12 /*[4]*/ var ic = ee.ImageCollection('MODIS/006/MOD13Q1') /*[5]*/ var band = 'NDVI' /*[6]*/ var maskToLULC = 'TRUE' // Set to 'TRUE' or 'FALSE' /*[7]*/ var lcType = 40 // Refer to https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_Landcover_100m_Proba-V-C3_Global /*[8]*/ var zonalStatType = ee.Reducer.mean() // examples: ee.Reducer.mean(), ee.Reducer.median(), ee.Reducer.stdDev(), // ee.Reducer.min(), ee.Reducer.max(), ee.Reducer.sum() /*[9]*/ var temporalAggregateType = 'mean' // available options: 'mean', 'median', 'stddev', 'min', 'max', 'sum' /*[10]*/ var nativeScale = 'TRUE' // Set to 'TRUE' or 'FALSE' var scale = 1000 // option to increase the scale to avoid memory crashes /*[11]*/ var exportFolder = 'GEE_Exports' var labelSuffix = 'NDVI-MEAN_VIETNAM' // sample export name: MSZSI-V2_2001-2020_1-12_LC40_GAUL-152-L1_NDVI-MEAN_VIETNAM, but can be changed during download prompt // note that some country names will need to be adjusted in the download prompt if they contain special characters ///////////////////////////////////////////////////// NO USER INPUT NEEDED BELOW //////////////////////////////////////////////////// // Administrative zones and preprocessing ------------------------------------------------------------------------------------------- ic = ic.select(band) var years = ee.List.sequence(startYear,endYear) var fc_L0 = ee.FeatureCollection('FAO/GAUL/2015/level0').filterMetadata('ADM0_CODE','equals',countryCode) var fc_L1 = ee.FeatureCollection('FAO/GAUL/2015/level1').filterMetadata('ADM0_CODE','equals',countryCode) .select(['ADM0_CODE','ADM0_NAME','ADM1_CODE','ADM1_NAME'], ['0-ADM0_CODE','0-ADM0_NAME','0-ADM1_CODE','0-ADM1_NAME']) fc_L1 = fc_L1.map(function(f) { return f.set('0-ADM2_CODE','NULL').set('0-ADM2_NAME','NULL') }) var fc_L2 = ee.FeatureCollection('FAO/GAUL/2015/level2').filterMetadata('ADM0_CODE','equals',countryCode) .select(['ADM0_CODE','ADM0_NAME','ADM1_CODE','ADM1_NAME','ADM2_CODE','ADM2_NAME'], ['0-ADM0_CODE','0-ADM0_NAME','0-ADM1_CODE','0-ADM1_NAME','0-ADM2_CODE','0-ADM2_NAME']) // LULC preprocessing --------------------------------------------------------------------------------------------------------------- var lulc = ee.ImageCollection('COPERNICUS/Landcover/100m/Proba-V-C3/Global').select('discrete_classification') var lulcMode = lulc.mode().eq(lcType) var lcLabel = '_LC'+lcType var lulcClip = lulcMode.clip(fc_L0) var lulcZone = lulcClip.remap([0,1],[1,1]).rename('zoneArea') var mask = lulcClip.updateMask(lulcClip.eq(1)).rename('mask') if(maskToLULC == 'FALSE') { lcLabel = '' mask = lulcZone } if(nativeScale == 'TRUE') { scale = lulc.first().projection().nominalScale() } // Add area fields ------------------------------------------------------------------------------------------------------------------ var temporal = ee.ImageCollection(years.map(function(y) { var filterYear = ic.filter(ee.Filter.calendarRange(y,y,'year')) .filter(ee.Filter.calendarRange(startMonth, endMonth, 'month')) var aggregate // the temporal aggregation type is set in input 9 if (temporalAggregateType == 'mean') { aggregate = filterYear.mean() } if (temporalAggregateType == 'median') { aggregate = filterYear.median() } if (temporalAggregateType == 'stddev') { aggregate = filterYear.stdDev() } if (temporalAggregateType == 'min') { aggregate = filterYear.min() } if (temporalAggregateType == 'max') { aggregate = filterYear.max() } if (temporalAggregateType == 'sum') { aggregate = filterYear.sum() } return aggregate.where(aggregate.eq(0),1e-10) // True zeroes are currently set to 1e-10 to avoid false no data flags .updateMask(mask) .set('extract',ee.String('2-'+labelSuffix+'_').cat(ee.Number(y).toInt())) .set('year',ee.Number(y).toInt()) .rename('band') })) // Run functions for each administrative level -------------------------------------------------------------------------------------- var zonal_L1 = zonalStat(fc_L1) var zonal_L2 = zonalStat(fc_L2) var merge = zonal_L1.combine(zonal_L2) var fcAreas_L1 = getAreas(fc_L1) var fcAreas_L2 = getAreas(fc_L2) var samples_L1 = createSamples(fc_L1) var samples_L2 = createSamples(fc_L2) var added_L1 = addFields(samples_L1,fcAreas_L1.select('zoneAreas'),fcAreas_L1.select('lulcAreas')) var added_L2 = addFields(samples_L2,fcAreas_L2.select('zoneAreas'),fcAreas_L2.select('lulcAreas')) exporter(added_L1,zonal_L1,1) exporter(added_L2,zonal_L2,2) // Calculate zonal statistics ------------------------------------------------------------------------------------------------------- function zonalStat(fc) { return temporal.map(function(i) { var year = i.get('year') return i.reduceRegions({ collection: fc, reducer: ee.Reducer.mean().setOutputs(['zStat']), scale: scale }).reduceToImage({ properties: ['zStat'], reducer: ee.Reducer.first() }).set('extract',i.get('extract')).set('year',year).rename('band') }) } // Calculate areas ------------------------------------------------------------------------------------------------------------------ function getAreas(fc) { var zoneAreas = ee.Image.pixelArea().updateMask(lulcZone).reduceRegions({ collection: fc, reducer: ee.Reducer.sum(), scale: scale }).reduceToImage({ properties: ['sum'], reducer: ee.Reducer.first() }).rename('zoneAreas') var lulcAreas = ee.Image.pixelArea().updateMask(mask).reduceRegions({ collection: fc, reducer: ee.Reducer.sum(), scale: scale }).reduceToImage({ properties: ['sum'], reducer: ee.Reducer.first() }).rename('lulcAreas') return zoneAreas.addBands(lulcAreas) } // Feature to points ---------------------------------------------------------------------------------------------------------------- function createSamples(fc) { return fc.map(function(g) { return ee.Feature(ee.FeatureCollection.randomPoints({ region: g.geometry(), points: 1, seed: 0 }).geometry()).copyProperties(g) }) } // Add area fields ------------------------------------------------------------------------------------------------------------------ function addFields(samples, areaGridZone, areaGridLULC) { return samples.map(function(p) { var point = p.geometry() var zoneArea = areaGridZone.rename('area').reduceRegion({ reducer: ee.Reducer.first(), geometry: point, scale: 1, maxPixels: 1e13 }).get('area') var lulcArea = areaGridLULC.rename('area').reduceRegion({ reducer: ee.Reducer.first(), geometry: point, scale: 1 }).get('area') var percLULC = ee.Number(lulcArea).divide(zoneArea).multiply(100) return ee.Feature(p).set('1-AREA_SQM_LULC',0) .set('1-AREA_SQM_ZONE',zoneArea).set('1-AREA_SQM_LULC',ee.Algorithms.If(lulcArea,lulcArea,0)) .set('1-AREA_PERCENT_LULC',ee.Algorithms.If(lulcArea,percLULC,0)) }) } // Export function ------------------------------------------------------------------------------------------------------------------ function exporter(e,zones,n) { var extracted = e.map(extractToPoints) function extractToPoints(feature) { var geom = feature.geometry() var addField = function(image, f) { var newFeature = ee.Feature(f) var getName = image.get('extract') var setValue = image.reduceRegion({ reducer: ee.Reducer.first(), geometry: geom, scale: 1, maxPixels: 1e13 }).get('band') return ee.Feature(ee.Algorithms.If(setValue, newFeature.set(getName, ee.String(setValue)), newFeature.set(getName, ee.String('No data')))) } var newFeature = ee.Feature(zones.iterate(addField, feature)) return newFeature } Export.table.toDrive({ collection: extracted, description: 'MSZSI-V2_'+startYear+'-'+endYear+'_'+startMonth+'-'+endMonth +lcLabel+'_GAUL-'+countryCode+'-L'+n+'_'+labelSuffix, folder: exportFolder }) } // Map display settings ------------------------------------------------------------------------------------------------------------- var leftMap = ui.Map() var rightMap = ui.Map() ui.Map.Linker([leftMap, rightMap]) ui.root.widgets().reset([leftMap,rightMap]) leftMap.centerObject(fc_L0) leftMap.setOptions('HYBRID').style().set('cursor', 'crosshair') rightMap.setOptions('HYBRID').style().set('cursor', 'crosshair') // Adds each image to the map displays var len = years.length().getInfo() for (var i = 0; i < len; i++) { var year = i+startYear var namer = 'ZSTATS_'+year var image_L1 = ee.Image(zonal_L1.toList(zonal_L1.size()).get(i)).rename(band) var image_L2 = ee.Image(zonal_L2.toList(zonal_L2.size()).get(i)).rename(band) leftMap.addLayer(image_L1,{},namer,false) rightMap.addLayer(image_L2,{},namer,false) } var hollow = {color: 'white', width: 0.3, fillColor: '00000000'} leftMap.addLayer(fc_L1.style(hollow),{},'FAO-GAUL-L1') rightMap.addLayer(fc_L2.style(hollow),{},'FAO-GAUL-L2') // Chart display settings ----------------------------------------------------------------------------------------------------------- var chartOptions = { fontSize: 11, width: '100px', curveType: 'function', format: 'short', margin: '0 0 0 0', hAxis: {format: '0000', textStyle: {fontSize: 10, color: '303030'}, gridlines: {color: 'transparent'}}, vAxis: {textStyle: {fontSize: 10, color: '303030'}, gridlines: {}}, trendlines: {0: {color: '303030', lineWidth: 0.5, visibleInLegend: false}}, series: {0: {color: '303030', lineWidth: 0.8}}, legend: {textStyle: {color: '303030'}}, } var panelStyle = { width: '235px', position: 'bottom-left', margin: '0 0 0 0', border: '1px solid #303030' } var leftChart = ui.Panel({ widgets: ui.Label('Select a point to chart regional time-series',{margin: '0 0 0 0', color:'303030'}), style: panelStyle }) leftMap.add(leftChart) // onClick function to query time-series -------------------------------------------------------------------------------------------- function pickLocation(location) { leftChart.widgets().set(0,ui.Label('Time-series',{fontSize: '14px', fontWeight: 'bold', color: '303030', margin: '7px 0 7px 10px'})) var chartOptions = { fontSize: 10, height: '200px', curveType: 'function', format: 'short', margin: '0 0 0 0', hAxis: {format: '0000', textStyle: {fontSize: 11, color: '303030'}, gridlines: {color: 'transparent'}}, vAxis: {textStyle: {fontSize: 10, color: '303030'}, gridlines: {}}, trendlines: {0: {color: 'blue', lineWidth: 0.5, visibleInLegend: false}, 1: {color: 'red', lineWidth: 0.5, visibleInLegend: false} }, series: {0: {color: 'blue', lineWidth: 0.8}, 1: {color: 'red', lineWidth: 0.8} }, legend: {position:'none'} } leftChart.widgets().set(1,ui.Label('Loading...',{fontSize: '13px',color:'9C9C9C', margin: '0 0 7px 10px'})) leftChart.widgets().set(2,ui.Label('',{fontSize: '13px',color:'9C9C9C', margin: '0 0 7px 10px'})) var pLat = location.lat var pLon = location.lon var point = ee.Geometry.Point([pLon,pLat]) var selection_L1 = fc_L1.filterBounds(point) var selection_L2 = fc_L2.filterBounds(point) var zone_L1_name = ee.Feature(selection_L1.first()).get('0-ADM1_NAME') var zone_L2_name = ee.Feature(selection_L2.first()).get('0-ADM2_NAME') leftChart.widgets().set(3,ui.Chart.image.series({ imageCollection: merge, region: point, scale: scale, xProperty: 'year' }).setOptions(chartOptions)) zone_L1_name.evaluate(function(result_L1) { zone_L2_name.evaluate(function(result_L2) { leftChart.widgets().set(1,ui.Label(result_L1+' (L1)',{fontSize: '13px', color: 'blue', margin: '0 0 7px 10px'})) leftChart.widgets().set(2,ui.Label(result_L2+' (L2)',{fontSize: '13px', color: 'red', margin: '0 0 0 10px'})) }) }) leftMap.layers().set(len+1, ui.Map.Layer(point,{color: 'blue', opacity: 0.6},'Selected point')) rightMap.layers().set(len+1, ui.Map.Layer(point,{color: 'red', opacity: 0.6},'Selected point')) } leftMap.onClick(pickLocation) rightMap.onClick(pickLocation) </pre>", "keywords": ["Computer and Information Science", "Agricultural Sciences", "Earth and Environmental Sciences", "Social Sciences"], "contacts": [{"organization": "Peter, Brad, Messina, Joseph, Raney, Austin, Principe, Rodrigo, Fan, Peilei,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/M4ZGXP"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/M4ZGXP", "name": "item", "description": "10.7910/DVN/M4ZGXP", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/M4ZGXP"}, {"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/MIYBQE", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:25:21Z", "type": "Dataset", "title": "Ecogeographic land characterization map of the SADC region", "description": "With the aim of planning for the in situ and ex situ conservation of priority crop wild relatives (CWR) of the Southern African Development Community (SADC), a gap analysis at intra-specific level (i.e. ecogeographic diversity level used as a proxy of genetic diversity), was carried out. For this purpose, a generalist Ecogeographic Land Characterization (ELC) map for the SADC region was created using the ELC mapas tool of CAPFITOGEN (http://www.capfitogen.net/, Parra-Quijano et al., 2008, 2016) based on 16 ecogeographic variables from three different components (four geophysic variables, seven edaphic, and five bioclimatic; see the list below) at a resolution of 2.5 arc minutes (approximately 4.5 km at the equator). The Calinski-Harabasz (1974) criterion was applied to obtain an objective number of clusters for each bioclimatic, edaphic and geophysic multivariate analysis. The ELC map was then clipped to the SADC countries using ArcGIS 10.4.1 (ESRI, 2016). A total of 16 ecogeographic categories were identified in the SADC region with distinct ecogeographic characteristiscs (see file 'ELC_SADC_region_statistics.xlsx'). The files made available here include: the raster file of the ELC map of the SADC region (which is composed of 16 different files) and an Excel file which describes the statistics (i.e. average, median, maximum, minimum and standard deviation) of each ecogeographic category present in the map ('ELC_SADC_region_statistics.xlsx').<br> <br><b>Variables:</b> Geophysic: altitude (m) (WorldClim 1.4, http://worldclim.org), slope (\u00b0), latitude (decimal degrees), longitude (decimal degrees). Edaphic: topsoil organic carbon (% weight), topsoil pH (H2O) [-log(H+)], topsoil silt fraction (% weight), topsoil sand fraction (% weight), topsoil gravel content (% vol.), topsoil clay fraction (% weight), topsoil TEB (total exchangeable bases) (cmol/kg) (HWS Database, http://www.iiasa.ac.at/Research/LUC/External-World-soil-database/). Bioclimatic: annual precipitation (bio_12) (mm), precipitation seasonality (coefficient of variation) (bio_15) (mm), isothermality (bio_2/bio_7) (*100) (bio_3), max temperature of warmest month (bio_5) (\u00b0C), min temperature of coldest month (bio_6) (\u00b0C) (WorldClim 1.4, http://worldclim.org).<br> <br><b>References:</b> Calinski T and Harabasz J (1974) A dendrite method for cluster analysis. Communications in Statistics, 3(1): 1\u201227. ESRI (2016) ArcGIS Desktop release Version 10.4.1. Environmental Systems Research Institute. Redlands. CA. Parra-Quijano M, Draper D and Torres E (2008) Ecogeographical representativeness in crop wild relative ex situ collections. In: Maxted N, Ford\u2010Lloyd BV, Kell SP, Iriondo JM, Dulloo E and Turok J (eds), Crop wild relative conservation and use, pp. 249\u201373. Wallingford: CAB International. Parra-Quijano M, Torres E, Iriondo JM, L\u00f3pez F and Molina A (2016) CAPFITOGEN tools user manual, version 2.0. Rome, Italy: International Treaty on Plant Genetic Resources for Food and Agriculture, FAO. Available at: http://www.capfitogen.net/en/access/manuals/ [Accessed July 2021].", "keywords": ["Agricultural Sciences", "PLANNING", "PLANT GENETIC RESOURCES", "AGROBIODIVERSITY", "GENETIC DIVERSITY AS RESOURCE"], "contacts": [{"organization": "Magos Brehm, Joana", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/MIYBQE"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/MIYBQE", "name": "item", "description": "10.7910/DVN/MIYBQE", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/MIYBQE"}, {"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/T8CMAT", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:25:21Z", "type": "Dataset", "created": "2016-02-28", "title": "GMCSD-2. Global Mangrove Carbon, 2000 to 2012, 1 Arc-second, 1 m soil.", "description": "Open AccessGlobal Mangrove Carbon, 2000 to 2012, 1 Arc-Second, 1 m Soil, mid, EQ5.

Annual stocks.

Each of these 13 years is 3TB when extracted. So that is 39 TB as a tif.

We needed to use file geodatabase format to compress enough to post on the Dataverse. Hence no TIffs.", "keywords": ["Earth and Environmental Sciences", "Raster", "ArcGIS file Geodatabase rasters", "Global Mangrove Carbon"], "contacts": [{"organization": "Hamilton, Stuart", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/T8CMAT"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/T8CMAT", "name": "item", "description": "10.7910/DVN/T8CMAT", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/T8CMAT"}, {"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/W9LSAD", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:25:21Z", "type": "Dataset", "created": "2015-01-01", "title": "Replication data: Zn efficient rice genotypes alter soil Zn availability, composition and Zn uptake in Zn-deficient and Zn-sufficient field soils under continuous flooding", "description": "Open Accessapplication/vnd.ms-excel, null", "keywords": ["biofortification", "Agricultural Sciences", "zinc deficiency", "Oryza sativa"], "contacts": [{"organization": "Goloran, Johnvie", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/W9LSAD"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/W9LSAD", "name": "item", "description": "10.7910/DVN/W9LSAD", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/W9LSAD"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-01-24T00:00:00Z"}}, {"id": "11572/255256", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:25:54Z", "type": "Journal Article", "created": "2019-09-23", "title": "Elastica catastrophe machine: theory, design and experiments", "description": "Open Access31 pages, 18 figures", "keywords": ["Nonlinear mechanics; Snap mechanisms; Structural instability", "0203 mechanical engineering", "FOS: Physical sciences", "02 engineering and technology", "Chaotic Dynamics (nlin.CD)", "Nonlinear Sciences - Chaotic Dynamics", "0210 nano-technology"]}, "links": [{"href": "https://iris.unitn.it/bitstream/11572/255256/1/1-s2.0-S002250961930523X-main.pdf"}, {"href": "https://doi.org/11572/255256"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20the%20Mechanics%20and%20Physics%20of%20Solids", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11572/255256", "name": "item", "description": "11572/255256", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11572/255256"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-03-01T00:00:00Z"}}, {"id": "11585/996230", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:25:57Z", "type": "Journal Article", "created": "2023-10-10", "title": "Beyond PLFA: Concurrent extraction of neutral and glycolipid fatty acids provides new insights into soil microbial communities", "description": "The analysis of phospholipid fatty acids (PLFAs) is one of the most common methods used to quantify the abundance, and analyse the community structure, of soil microbes. The PLFA extraction method can yield two additional lipid fractions\u2014neutral lipids and glycolipids\u2014which potentially hold additional, valuable information on soil microbial communities. Yet its quantitative sensitivity on complete neutral lipid (NLFA) and glycolipid fatty acid (GLFA) profiles has never been validated. In this study we tested (i) if the high-throughput PLFA method can be expanded to concurrently extract complete NLFA and GLFA profiles, as well as sterols, (ii) whether taxonomic specificities of signature fatty acids are retained across the three lipid fractions in pure culture strains, and (iii) whether NLFAs and GLFAs allow soil-specific fingerprinting to the same extent as PLFA analysis. By adjusting the polarity of chloroform with 2% ethanol for solid phase extraction, pure lipid standards were fully fractionated into neutral lipids, glycolipids, and phospholipids. Sterols eluted in the neutral lipid fraction, and a betaine lipid co-eluted with phospholipids. We found consistent taxonomic specificities of fatty acid markers across the three lipid fractions by analysing pure culture extracts representative of soil microbes. Fatty acid profiles from soil extracts, however, showed stronger differences between PLFAs, NLFAs, and GLFAs than between soil types. This indicates that PLFAs and NLFAs signify different community properties (biomass vs. carbon storage, putatively), and that GLFAs are sensitive markers for community traits which behave differently than PLFAs. Although we consistently found high abundances of characteristic sterols in fungal extracts, the PLFA extraction method only yielded miniscule amounts of ergosterol from soil extracts. We argue that concomitant measurement of fatty acid profiles from all three lipid fractions is a low-effort and potentially information-rich addition to the PLFA method, and discuss its applicability for soil microbial community analyses.", "keywords": ["0301 basic medicine", "2. Zero hunger", "106022 Mikrobiologie", "0303 health sciences", "15. Life on land", "Soil lipids", "03 medical and health sciences", "106026 \u00d6kosystemforschung", "NLFA", "Ergosterol", "Ergosterol; GLFA; NLFA; Phospholipid fatty acids; Soil lipids", "Phospholipid fatty acid", "soil lipids", "Phospholipid fatty acids", "106022 Microbiology", "GLFA", "106026 Ecosystem research"]}, "links": [{"href": "https://doi.org/11585/996230"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Soil%20Biology%20and%20Biochemistry", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11585/996230", "name": "item", "description": "11585/996230", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11585/996230"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-12-01T00:00:00Z"}}, {"id": "11586/524923", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:25:57Z", "type": "Journal Article", "created": "2024-12-03", "title": "Addressing the environmental sustainability of plastics used in agriculture: a multi-actor perspective", "description": "Abstract

Plastics used in agriculture, commonly known as agriplastics (AP), offer numerous advantages in terrestrial agriculture, forestry, fisheries and aquaculture, but the diffusion of AP-intensive practices has led to extensive pollution. This review aims to synthesise scientific and policy discussions surrounding AP, examining evidence of their benefits and detrimental environmental and agricultural impacts. Following the proposal of a preliminary general taxonomy of AP, this paper presents the findings from a survey conducted among international experts from the plastic industry, farmer organisations, NGOs and environmental research institutes. This analysis highlights knowledge gaps, demands and perspectives for the sustainable future use of AP. Stakeholder positions vary on the options of \uffe2\uff80\uff98rejection\uffe2\uff80\uff99 or \uffe2\uff80\uff98reduction\uffe2\uff80\uff99 of AP, as well as the role of alternative materials such as (bio)degradable and compostable plastics. However, there is consensus on critical issues such as redesign, labelling, traceability, environmental safety standards, deployment and retrieval standards, as well as innovative waste management approaches. All stakeholders express concern for the environment. A \uffe2\uff80\uff98best practice\uffe2\uff80\uff99-based circular model was elaborated capturing these perspectives. In the context of global food systems increasingly reliant on AP, scientists emphasise the need to simultaneously preserve nature-based and traditional knowledge-based sustainable agricultural practices to enhance food system resilience.

Abstract. In fire emission models, the spatial resolution of both the modelling framework and the satellite data used to quantify burned area can have considerable impact on emission estimates. Consideration of this sensitivity is especially important in areas with heterogeneous land cover and fire regimes and when constraining model output with field measurements. We developed a global fire emissions model with a spatial resolution of 500\u2009m using MODerate resolution Imaging Spectroradiometer (MODIS) data. To accommodate this spatial resolution, our model is based on a simplified version of the Global Fire Emissions Database (GFED) modelling framework. Tree mortality as a result of fire, i.e.\u00a0fire-related forest loss, was modelled based on the overlap between 30\u2009m forest loss data and MODIS burned area and active fire detections. Using this new 500\u2009m model, we calculated global average carbon emissions from fire of 2.1\u00b10.2 (\u00b11\u03c3 interannual variability, IAV)\u2009Pg\u2009C\u2009yr\u22121 during 2002\u20132020. Fire-related forest loss accounted for 2.6\u00b10.7\u2009% (uncertainty range =1.9\u2009%\u20133.3\u2009%) of global burned area and 24\u00b16\u2009% (uncertainty range =16\u2009%\u201331\u2009%) of emissions, indicating that fuel consumption in forest fires is an order of magnitude higher than the global average. Emissions from the combustion of soil organic carbon (SOC) in the boreal region and tropical peatlands accounted for 13\u00b14\u2009% of global emissions. Our global fire emissions estimate was higher than the 1.5\u2009Pg\u2009C\u2009yr\u22121 from GFED4 and similar to 2.1\u2009Pg\u2009C\u2009yr\u22121 from GFED4s. Even though GFED4s included more burned area by accounting for small fires undetected by the MODIS burned area mapping algorithm, our emissions were similar to GFED4s due to higher average fuel consumption. The global difference in fuel consumption could mainly be explained by higher SOC emissions from the boreal region as constrained by additional measurements. The higher resolution of the 500\u2009m model also contributed to the difference by improving the simulation of landscape heterogeneity and reducing the scale mismatch in comparing field measurements to model grid cell averages during model calibration. Furthermore, the fire-related forest loss algorithm introduced in our model led to more accurate and widespread estimation of high-fuel-consumption burned area. Recent advances in burned area detection at resolutions of 30\u2009m and finer show a substantial amount of burned area that remains undetected with 500\u2009m sensors, suggesting that global carbon emissions from fire are likely higher than our 500\u2009m estimates. The ability to model fire emissions at 500\u2009m resolution provides a framework for further improvements with the development of new satellite-based estimates of fuels, burned area, and fire behaviour, for use in the next generation of GFED.

", "keywords": ["QE1-996.5", "13. Climate action", "11. Sustainability", "Geology", "15. Life on land", "7. Clean energy", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/1871.1/bbc7e25d-d1b9-4c7d-baa4-1a09012f06b2"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoscientific%20Model%20Development", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1871.1/bbc7e25d-d1b9-4c7d-baa4-1a09012f06b2", "name": "item", "description": "1871.1/bbc7e25d-d1b9-4c7d-baa4-1a09012f06b2", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1871.1/bbc7e25d-d1b9-4c7d-baa4-1a09012f06b2"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-05-30T00:00:00Z"}}, {"id": "1959.7/uws:75008", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:26:13Z", "type": "Journal Article", "created": "2023-10-04", "title": "Plant footprint decreases the functional diversity of molecules in topsoil organic matter after millions of years of ecosystem development", "description": "AbstractAim

Theory suggests that the diversity of molecules in soil organic matter (SOM functional diversity) provides key insights on multiple ecosystem services. We aimed to investigate how and why SOM functional diversity and composition change as topsoils develop, and its implications for key soil functions (e.g., from nutrient pool to water regulation).

Location

We reported data on 16 soil chronosequences globally distributed in nine countries from six continents.

Time Period

2016\uffe2\uff80\uff932017.

Major Taxa Studied

Soil microbes (bacteria and fungi) and vascular plants.

Methods

SOM functional diversity and composition without mineral interference were measured using diffuse reflectance mid\uffe2\uff80\uff90infrared Fourier transform spectroscopy (DRIFT). We aimed to characterize the main environmental factors related to SOM functional diversity and composition. Also, we calculated the links among SOM functional diversity and key soil functions.

Results

We found that SOM functional diversity declines after millions of years of soil formation (pedogenesis). We further showed that increases in plant cover and productivity led to a higher ratio of reduced (e.g., alkanes) over oxidized carbon forms (i.e., C: O\uffe2\uff80\uff90functional groups ratio), which was positively correlated to SOM functional diversity as soils age. Our findings indicated that the plant footprint (i.e., the accumulation of plant\uffe2\uff80\uff90derived material promoting the C: O\uffe2\uff80\uff90functional group ratio) would explain the reduction of SOM functional diversity as ecosystems develop. Moreover, the dissimilarity in SOM composition consistently increased with soil age, with the soil development stage emerging as the main predictor of SOM dissimilarity across contrasting biomes.

Main Conclusions

Our global survey contextualized the natural history of SOM functional diversity and composition during long\uffe2\uff80\uff90term soil development. Together, we showed how plant footprint drives the losses of SOM functional diversity with increasing age, which might provide a novel mechanism to explain typically reported losses in ecosystem functions during ecosystem retrogression.A broader knowledge of the contribution of carbon (C) released by plant roots (exudates) to soil is a prerequisite for optimizing the management of organic matter in arable soils. This is the first study to show the contribution of constantly applied13C\uffe2\uff80\uff90labelled maize and wheat exudates to water extractable organic carbon (WEOC), microbial biomass\uffe2\uff80\uff90C (MB\uffe2\uff80\uff90C), and CO2\uffe2\uff80\uff90C evolution during a 25\uffe2\uff80\uff90day incubation of agricultural soil material. The CO2\uffe2\uff80\uff90C evolution and respective \uffce\uffb413C values were measured daily. The WEOC and MB\uffe2\uff80\uff90C contents were determined weekly and a newly developed method for determining \uffce\uffb413C values in soil extracts was applied. Around 36% of exudate\uffe2\uff80\uff90C of both plants was recovered after the incubation, in the order WEOC < MB\uffe2\uff80\uff90C < CO2\uffe2\uff80\uff90C for maize and MB\uffe2\uff80\uff90C < WEOC < CO2\uffe2\uff80\uff90C for wheat. Around 64% of added exudate\uffe2\uff80\uff90C was not retrieved with the methods used here. Our results suggest that great amounts of exudates became stabilized in non\uffe2\uff80\uff90water extractable organic fractions. The amounts of MB\uffe2\uff80\uff90C stayed relatively constant over time despite a continuous exudate\uffe2\uff80\uff90C supply, which is the prerequisite for a growing microbial population. A lack of mineral nutrients might have limited microbial growth. The CO2\uffe2\uff80\uff90C mineralization rate declined during the incubation and this was probably caused by a shift in the microbial community structure. Consequently, incoming WEOC was left in the soil solution leading to rising WEOC amounts over time. In the exudate\uffe2\uff80\uff90treated soil additional amounts of soil\uffe2\uff80\uff90derived WEOC (up to 110 \uffce\uffbcg g\uffe2\uff88\uff921) and MB\uffe2\uff80\uff90C (up to 60 \uffce\uffbcg g\uffe2\uff88\uff921) relative to the control were determined. We suggest therefore that positive priming effects (i.e. accelerated turnover of soil organic matter due to the addition of organic substrates) can be explained by exchange processes between charged, soluble C\uffe2\uff80\uff90components and the soil matrix. As a result of this exchange, soil\uffe2\uff80\uff90derived WEOC becomes available for mineralization.

", "keywords": ["2. Zero hunger", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land"], "contacts": [{"organization": "A. Gattinger, F. Buegger, M. Marx, J. C. Munch, A. Zsolnay,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1111/j.1365-2389.2007.00911.x"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/European%20Journal%20of%20Soil%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/j.1365-2389.2007.00911.x", "name": "item", "description": "10.1111/j.1365-2389.2007.00911.x", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/j.1365-2389.2007.00911.x"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2007-03-27T00:00:00Z"}}, {"id": "10.1002/ldr.2158", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:14:57Z", "type": "Journal Article", "created": "2012-04-03", "title": "Changes in soil organic carbon under eucalyptus plantations in brazil: a comparative analysis", "description": "ABSTRACT

Proper assessment of environmental quality or degradation requires knowledge of how terrestrial C pools respond to land use change. Forest plantations offer a considerable potential to sequester C in aboveground biomass. However, their impact on initial levels of soil organic carbon (SOC) varies from strong losses to gains, possibly affecting C balances in afforestation or reforestation initiatives. We compiled paired\uffe2\uff80\uff90plot studies on how SOC stocks under native vegetation change after planting fast\uffe2\uff80\uff90growth Eucalyptus species in Brazil, where these plantations are becoming increasingly important. SOC changes for the 0\uffe2\uff80\uff9320 and 0\uffe2\uff80\uff9340\uffe2\uff80\uff89cm depths varied between \uffe2\uff88\uff9225 and 42\uffe2\uff80\uff89Mg\uffe2\uff80\uff89ha\uffe2\uff88\uff921, following a normal distribution centered near zero. After replacing native vegetation by Eucalyptus plantations, mean SOC changes were \uffe2\uff88\uff921\uffc2\uffb75 and 0\uffc2\uffb73\uffe2\uff80\uff89Mg\uffe2\uff80\uff89ha\uffe2\uff88\uff921 for the 0\uffe2\uff80\uff9320 and 0\uffe2\uff80\uff9340\uffe2\uff80\uff89cm depths, respectively. These are very low figures in comparison to C stocks usually sequestered in aboveground biomass and were statistically nonsignificant as demonstrated by a t\uffe2\uff80\uff90test at p\uffe2\uff80\uff89<\uffe2\uff80\uff890\uffc2\uffb705. Similar low, nonsignificant SOC changes were estimated after data were stratified into first or second rotation cycles, soil texture and biome (savanna, rainforest or grassland). Although strong SOC losses or gains effectively occurred in some cases, their underpinning causes could not be generally identified in the present work and must be ascribed in a case basis, considering the full set of environmental and management conditions. We conclude that Eucalyptus spp. plantations in average have no net effect on SOC stocks in Brazil. Copyright \uffc2\uffa9 2012 John Wiley & Sons, Ltd.

", "keywords": ["Soil organic matter", "Carbon stocks", "Tropical soils", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "Fast-growth tree plantations", "Land use change"]}, "links": [{"href": "https://doi.org/10.1002/ldr.2158"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Land%20Degradation%20%26amp%3B%20Development", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/ldr.2158", "name": "item", "description": "10.1002/ldr.2158", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/ldr.2158"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2012-04-03T00:00:00Z"}}, {"id": "10.1016/j.agee.2017.04.015", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:16:13Z", "type": "Journal Article", "created": "2017-05-06", "title": "Ecosystem service delivery of agri-environment measures: A synthesis for hedgerows and grass strips on arable land", "description": "Abstract In north western Europe, agricultural systems are generally managed to maximize the potential delivery of provisioning ecosystem services. This has often been at the expense of other ecosystem services. Because the current supply of most ecosystem services is insufficient to meet the increasing demand, particular attention to ecosystem service delivery and hence multifunctionality in agriculture is vital. In this paper, we quantitatively assessed the impact of hedgerows and grass strips bordering parcels with annual arable crops on the simultaneous delivery of a set of ecosystem services and from there we identified synergies and trade-offs on virtual parcels. After a systematic literature search, mixed models were applied on observations from 60 studies and quantitative effect relationships between ecosystem service delivery and hedgerow and grass strip characteristics were developed. Next to the hedgerow, until a distance of twice the hedgerow height, arable crop yield was reduced by 29%. Beyond this distance, until 20 times the hedgerow height, crop yield was increased by 6%. Compared to a similar arable parcel without hedgerow or grass strip, soil carbon stock was 22% higher in the hedgerow, on average 6% higher in the adjacent parcel next to the hedgerow and 37% higher in the upper 30\u00a0cm soil layer in the grass strip. Both hedgerows and grass strips intercepted nitrogen from the surface (69% and 67%, respectively) and subsurface (34% and 32%, respectively) flow and phosphorus (67% and 73%, respectively) and soil sediment (91% and 90%, respectively) from the surface flow. More natural predator species were found on parcels with hedgerows, but the number of predators was unaffected. On parcels with grass strips, both predator density and diversity was higher and aphid density was reduced. Our calculations on parcel level indicate that the trade-off between arable crop yield and regulating ecosystem services depends on hedgerow width and height and parcel dimensions. A similar trade-off is found on parcels with grass strips, but increasing grass strip width results in a proportionally higher delivery of regulating ecosystem services.", "keywords": ["2. Zero hunger", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.agee.2017.04.015"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agriculture%2C%20Ecosystems%20%26amp%3B%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agee.2017.04.015", "name": "item", "description": "10.1016/j.agee.2017.04.015", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agee.2017.04.015"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-06-01T00:00:00Z"}}, {"id": "10.1016/j.soilbio.2010.09.005", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:17:36Z", "type": "Journal Article", "created": "2010-10-02", "title": "Microbial Community Composition And Carbon Cycling Within Soil Microenvironments Of Conventional, Low-Input, And Organic Cropping Systems", "description": "This study coupled stable isotope probing with phospholipid fatty acid analysis ((13)C-PLFA) to describe the role of microbial community composition in the short-term processing (i.e., C incorporation into microbial biomass and/or deposition or respiration of C) of root- versus residue-C and, ultimately, in long-term C sequestration in conventional (annual synthetic fertilizer applications), low-input (synthetic fertilizer and cover crop applied in alternating years), and organic (annual composted manure and cover crop additions) maize-tomato (Zea mays - Lycopersicum esculentum) cropping systems. During the maize growing season, we traced (13)C-labeled hairy vetch (Vicia dasycarpa) roots and residues into PLFAs extracted from soil microaggregates (53-250 \u03bcm) and silt-and-clay (<53 \u03bcm) particles. Total PLFA biomass was greatest in the organic (41.4 nmol g(-1) soil) and similar between the conventional and low-input systems (31.0 and 30.1 nmol g(-1) soil, respectively), with Gram-positive bacterial PLFA dominating the microbial communities in all systems. Although total PLFA-C derived from roots was over four times greater than from residues, relative distributions (mol%) of root- and residue-derived C into the microbial communities were not different among the three cropping systems. Additionally, neither the PLFA profiles nor the amount of root- and residue-C incorporation into the PLFAs of the microaggregates were consistently different when compared with the silt-and-clay particles. More fungal PLFA-C was measured, however, in microaggregates compared with silt-and-clay. The lack of differences between the mol% within the microbial communities of the cropping systems and between the PLFA-C in the microaggregates and the silt-and-clay may have been due to (i) insufficient differences in quality between roots and residues and/or (ii) the high N availability in these N-fertilized cropping systems that augmented the abilities of the microbial communities to process a wide range of substrate qualities. The main implications of this study are that (i) the greater short-term microbial processing of root- than residue-C can be a mechanistic explanation for the higher relative retention of root- over residue-C, but microbial community composition did not influence long-term C sequestration trends in the three cropping systems and (ii) in spite of the similarity between the microbial community profiles of the microaggregates and the silt-and-clay, more C was processed in the microaggregates by fungi, suggesting that the microaggregate is a relatively unique microenvironment for fungal activity.", "keywords": ["2. Zero hunger", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land"]}, "links": [{"href": "https://doi.org/10.1016/j.soilbio.2010.09.005"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Soil%20Biology%20and%20Biochemistry", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.soilbio.2010.09.005", "name": "item", "description": "10.1016/j.soilbio.2010.09.005", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.soilbio.2010.09.005"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2011-01-01T00:00:00Z"}}, {"id": "10.1016/j.agsy.2016.06.007", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:16:17Z", "type": "Journal Article", "created": "2016-07-20", "title": "Greening And Producing: An Economic Assessment Framework For Integrating Trees In Cropping Systems", "description": "Abstract Environmental measures in an agricultural context often lead to extra constraints in current farming. This suggests trade-offs between the environmental objectives and profitability. Whether trade-offs exist, or may be turned into win-win, depends on creative farm options to comply new constraints. This paper concentrates on Ecological Focus Areas as a new EU Common Agricultural Policy greening requirement, and investigates profitability changes of two greening options with permanent woody elements, hedgerows and alley cropping. We predicted discounted gross margins for a hedgerow and alley cropping greening option and four market scenarios on a representative arable farm in Flanders (Belgium). Starting from the tree row, over a distance of 1.64 times the tree height, relative crop yield is 70% as compared to a treeless situation. Between 1.64 and 9.52 times the tree height, relative yield is 107%. Beyond that point, the effect is considered negligible. Discounted gross margins are calculated to account for the time horizon. Relative discounted gross margins at farm level, compared to the business as usual option, vary between 91% and 108%, depending on market conditions and policy support. The calculations show that fulfilment of the 5% ecological focus area greening requirement on arable farms with hedgerows and alley cropping only becomes economically competitive to the traditional cropping systems with extra financial stimuli (e.g. greening payments). We also show and discuss how the calculations can be fine-tuned and used in policy making, e.g. by i) getting better insights in the tree-crop interactions, ii) including the effect of e.g. crop type, tree species, tree line space and tree line orientation in the meta-information, iii) evaluating this conditional competitiveness and suggesting a better linking between subsidy level and ecological value and ecosystem services and iv) exploring novel valorization channels for wood products.", "keywords": ["2. Zero hunger", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "12. Responsible consumption", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.agsy.2016.06.007"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agricultural%20Systems", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agsy.2016.06.007", "name": "item", "description": "10.1016/j.agsy.2016.06.007", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agsy.2016.06.007"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-10-01T00:00:00Z"}}, {"id": "2950304570", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:26:56Z", "type": "Journal Article", "created": "2019-06-21", "title": "Novel tetrahedral Ag3PO4@N-rGO for photocatalytic detoxification of sulfamethoxazole: Process optimization, transformation pathways and biotoxicity assessment", "description": "Abstract Global spreading of antibiotic resistant microorganisms and genes calls for the development of effective strategy to eliminate antibiotic pollution from the environment. Tetrahedral silver phosphate (Ag3PO4) is one of the master visible light photocatalysts but encountered the drawback of low stability due to photocorrosion. Integration of Ag3PO4 with N-doped reduced graphene oxide (N-rGO) that has large specific surface area, ample functional groups and hetero atoms doping is anticipated to overcome the problem. Thus, the present study prepared high stability Ag3PO4@N-rGO hybrid catalysts and applied for detoxification of sulfamethoxazole (SMX). Further, the operational parameters towards the photocatalytic degradation was systematically optimized to maximize the efficiency through response surface methodology (RSM) based on central composite design (CCD). The parameters that influenced the SMX degradation efficiency was as follows: pH\u202f>\u202fN-content\u202f>\u202fcatalyst dosage. Under the optimal conditions (catalyst dosage\u202f=\u202f0.2\u202fg/L, pH\u202f=\u202f5.8, and N-content\u2009of 5.14%), 93.8% of SMX degradation was obtained within 60\u202fmin. The plausible degradation products generation during the photocatalytic degradation of SMX was analyzed by LC-ESI/MS and the degradation pathway was proposed. In addition, the toxicity of the degradation products was investigated through Escherichia coli colony forming unit assay and a substantial biotoxicity reduction by this photodegradation was observed.", "keywords": ["13. Climate action", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/2950304570"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Chemical%20Engineering%20Journal", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2950304570", "name": "item", "description": "2950304570", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2950304570"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-11-01T00:00:00Z"}}, {"id": "10.1016/j.eja.2015.09.012", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:16:42Z", "type": "Journal Article", "created": "2015-11-04", "title": "Contribution Of Green Manure Legumes To Nitrogen Dynamics In Traditional Winter Wheat Cropping System In The Loess Plateau Of China", "description": "Abstract Excessive application of N fertilizer in pursuit of higher yields is common due to poor soil fertility and low crop productivity. However, this practice causes serious soil depletion and N loss in the traditional wheat cropping system in the Loess Plateau of China. Growing summer legumes as the green manure (GM) crop is a viable solution because of its unique ability to fix atmospheric N 2 . Actually, little is known about the contribution of GM N to grain and N utilization in the subsequent crop. Therefore, we conducted a four-year field experiment with four winter wheat-based rotations (summer fallow-wheat, Huai bean\u2013wheat, soybean\u2013wheat, and mung bean\u2013wheat) and four nitrogen fertilizer rates applied to wheat (0, 108, 135, and 162\u00a0kg\u00a0N/ha) to investigate the fate of GM nitrogen via decomposition, utilization by wheat, and contribution to grain production and nitrogen economy through GM legumes. Here we showed that GM legumes accumulated 53\u201376\u00a0kg\u00a0N/ha per year. After decomposing for approximately one year, more than 32\u00a0kg\u00a0N/ha was released from GM legumes. The amount of nitrogen released via GM decomposition that was subsequently utilized by wheat was 7\u201327\u00a0kg N/ha. Incorporation of GM legumes effectively replaced 13\u201348% (average 31%) of the applied mineral nitrogen fertilizer. Additionally, the GM approach during the fallow period reduced the risk of nitrate-N leaching to depths of 0\u2013100\u00a0cm and 100\u2013200\u00a0cm by 4.8 and 19.6\u00a0kg\u00a0N/ha, respectively. The soil nitrogen pool was effectively improved by incorporation of GM legumes at the times of wheat sowing. Cultivation of leguminous GM during summer is a better option than bare fallow to maintain the soil nitrogen pool, and decrease the rates required for N fertilization not only in the Loess Plateau of China but also in other similar dryland regions worldwide.", "keywords": ["2. Zero hunger", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "6. Clean water"], "contacts": [{"organization": "Zhang Dabin, Yao Pengwei, Cao Weidong, Zhao Na, Yu Changwei, Gao Yajun,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1016/j.eja.2015.09.012"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/European%20Journal%20of%20Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.eja.2015.09.012", "name": "item", "description": "10.1016/j.eja.2015.09.012", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.eja.2015.09.012"}, {"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": "10.1016/j.eja.2022.126515", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:16:42Z", "type": "Journal Article", "created": "2022-04-26", "title": "Simulating water lateral inflow and its contribution to spatial variations of rainfed wheat yields", "description": "Spatial variations of crop yields are commonly observed in typical rainfed systems worldwide. It is accepted that such variations are likely to be associated, among other factors, with water spatial variations due to lateral water flows occurring in fields with undulating topography. However, some of the main processes governing water spatial distribution such as lateral flow are not entirely considered by the most commonly adopted crop simulation models. This brings uncertainty to the process of yield simulation at field-scale, especially under water-limited conditions. Although it is expected that lateral water movement determines spatial variations of crop yields, it is still unclear what is the net contribution of lateral water inflows (LIF) to spatial variations of rainfed yields in fields of undulating topography. In this sense, by combining field experimentation, simulation models (HYDRUS-1D and AquaCrop), and the use of artificial neural networks, we assessed the occurrence and magnitude of LIF, and their impact on wheat yields in Cordoba, Spain, over a 30-year period. Seasonal precipitation varied over 30 years from 212.8 to 759.5 mm, and cumulative LIF ranged from 30 to 125 mm. The ratio of seasonal cumulative LIF divided by seasonal precipitation varied from 10.7% to 38.9% over the 30 years. The net contribution of LIF to spatial variations of rainfed potential yields showed to be relevant but highly irregular among years. Despite the inter-annual variability, typical of Mediterranean conditions, the occurrence of LIF caused simulated wheat yields to vary + 16% from up to downslope areas of the field. The net yield responses to LIF, in downslope areas were on average 383 kg grain yield (GY) ha\u22121, and the LIF marginal water productivity reached 24.6 ( \u00b1 13.2) kg GY ha\u22121 mm\u22121 in years of maximum responsiveness. Decision makers are encouraged to take water spatial variations into account when adjusting management to different potential yielding zones within the same field. However, this process is expected to benefit from further advances in in-season weather forecasting that should be coupled with a methodological approach such as the one presented here. This research received funding from the European Commission under project SHui - Grant agreement ID 773903 and also from the Spanish Government under Grant PID2019-105793RB-I00. Peer reviewed", "keywords": ["0106 biological sciences", "2. Zero hunger", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.eja.2022.126515"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/European%20Journal%20of%20Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.eja.2022.126515", "name": "item", "description": "10.1016/j.eja.2022.126515", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.eja.2022.126515"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-07-01T00:00:00Z"}}, {"id": "10.1016/j.agee.2004.04.001", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:16:04Z", "type": "Journal Article", "created": "2004-08-26", "title": "Carbon Sequestration In Tropical And Temperate Agroforestry Systems: A Review With Examples From Costa Rica And Southern Canada", "description": "Deforestation in the tropics, and fossil fuel burning in temperate regions contribute to the largest flux of CO 2 to the atmosphere. Therefore, land-use systems that increase the soil organic matter (SOM) pool and stabilize soil organic carbon (SOC) need to be implemented. Agroforestry systems have the potential to sequester atmospheric carbon (C) in trees and soil while maintaining sustainable productivity. The potential to sequester C in agroforestry systems in tropical and temperate regions is promising, but little information is available to date. The objective of this paper is to give an overview of the history of agroforestry and to outline differences in management practices between tropical and temperate systems. This review focuses on C inputs, SOC pools and SOC stabilization with highlights from Costa Rican and Canadian systems, and their role in C sequestration and trading. The potential to sequester C in aboveground components in agroforestry systems is estimated to be 2.1 \u00d7 10 9 Mg C year \u22121 in tropical and 1.9 \u00d7 10 9 Mg C year \u22121 in temperate biomes. However, the type of agroforestry systems and their capacity to sequester C vary globally. For example, alley cropping is an agroforestry practice where trees are integrated with crops, therefore storing C in the woody components of the trees and in the soil, with a continual addition of organic material from tree prunings and crop residues. Studies from Costa Rica have shown that a 10-year-old system with E. poeppigianasequestered C at a rate of 0.4 Mg C ha \u22121 year \u22121 in coarse roots and 0.3 Mg C ha \u22121 year \u22121 in tree trunks. Tree branches and leaves are added to the soil as mulch, contributing 1.4 Mg C ha \u22121 year \u22121 in addition to 3.0 Mg ha \u22121 year \u22121 from crop residues. This resulted in an annual increase of the SOC pool by 0.6 Mg ha \u22121 year \u22121 . Despite the two crop rotations in tropical agroforests, C input from crop residues is similar between the two biomes. The total organic matter input, however, is still greater in tropical systems due to the larger addition from tree prunings. This greater input does not necessarily increase the SOC pool significantly when compared to a temperate system of similar age as a result of faster turnover rates of the SOM pool. \u00a9 2004 Elsevier B.V. All rights reserved.", "keywords": ["2. Zero hunger", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.agee.2004.04.001"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agriculture%2C%20Ecosystems%20%26amp%3B%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agee.2004.04.001", "name": "item", "description": "10.1016/j.agee.2004.04.001", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agee.2004.04.001"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2004-12-01T00:00:00Z"}}, {"id": "10.1016/j.agee.2005.09.013", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:16:05Z", "type": "Journal Article", "created": "2005-11-18", "title": "Responses Of Soil Microbial Biomass And N Availability To Transition Strategies From Conventional To Organic Farming Systems", "description": "Abstract Organic farming can enhance soil biodiversity, alleviate environmental concerns and improve food safety through eliminating the applications of synthetic chemicals. However, yield reduction due to nutrient limitation and pest incidence in the early stages of transition from conventional to organic systems is a major concern for organic farmers, and is thus a barrier to implementing the practice of organic farming. Therefore, identifying transition strategies that minimize yield loss is critical for facilitating the implementation of organic practices. Soil microorganisms play a dominant role in nutrient cycling and pest control in organic farming systems, and their responses to changes in soil management practices may critically impact crop growth and yield. Here we examined soil microbial biomass and N supply in response to several strategies for transitioning from conventional to organic farming systems in a long-term field experiment in Goldsboro, NC, USA. The transitional strategies included one fully organic strategy (ORG) and four reduced-input strategies (withdrawal of each or gradual reduction of major conventional inputs\u2014synthetic fertilizers, pesticides (insecticides/fungicides), and herbicides), with a conventional practice (CNV) serving as a control. Microbial biomass and respiration rate were more sensitive to changes in soil management practices than total C and N. In the first 2 years, the ORG was most effective in enhancing soil microbial biomass C and N among the transition strategies, but was accompanied with high yield losses. By the third year, soil microbial biomass C and N in the reduced-input transition strategies were statistically significantly greater than those in the CNV (averaging 32 and 35% higher, respectively), although they were slightly lower than those in the ORG (averaging 13 and 17% lower, respectively). Soil microbial respiration rate and net N mineralization in all transitional systems were statistically significantly higher than those in the CNV (averagely 83 and 66% greater, respectively), with no differences among the various transition strategies. These findings suggest that the transitional strategies that partially or gradually reduce conventional inputs can serve as alternatives that could potentially minimize economic hardships as well as benefit microbial growth during the early stages of transition to organic farming systems.", "keywords": ["2. Zero hunger", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land"]}, "links": [{"href": "https://doi.org/10.1016/j.agee.2005.09.013"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agriculture%2C%20Ecosystems%20%26amp%3B%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agee.2005.09.013", "name": "item", "description": "10.1016/j.agee.2005.09.013", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agee.2005.09.013"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2006-04-01T00:00:00Z"}}, {"id": "10.1016/j.agee.2006.01.004", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:16:05Z", "type": "Journal Article", "created": "2006-03-01", "title": "Changes In Intrasystem N Cycling From N-2-Fixing Shrub Encroachment In Grassland: Multiple Positive Feedbacks", "description": "Nitrogen-fixing species can increase both the availability and cycling of nitrogen (N) in ecosystems. Autumn olive (Elaeagnus umbellata Thunb.) is an exotic woody shrub associated with N2-fixing actinomycetes that forms dense patches in disturbed landscapes (i.e., riparian zones adjacent to crop systems, old fields and agricultural grasslands) throughout the midwestern United States. We used paired plots dominated by either E. umbellata or C3 grassland to test whether the shrub encroachment altered pools and fluxes of nitrogen (N) and carbon (C) in the soil. Annual mean of NO3\u2010N concentrations in soil water collected from porous cup tension lysimeters every 2 weeks for 1 year was 20 times higher in soil beneath E. umbellata compared to grassland vegetation. Temporal variation in NO3\u2010N leaching occurred in the shrubencroached plots, with more nitrate leaching in the dormant season relative to the growing season. Potential net N mineralization, nitrification rates, and extractable N in the surface 10 cm of soil were also higher below E. umbellata. Following establishment of N2-fixing shrub patches for 7\u201013 years, the soil C:N ratio showed a declining trend due to lower total soil C rather than an increase in N. Labile carbon pools (i.e., microbial biomass C (MBC) and soil respiration rates) were lower in surface soil below E. umbellata, which demonstrated an additional positive feedback between encroachment of E. umbellata and N export. Less demand for mineralized N due to associated N2 fixation, coupled with higher rates of nitrification and lower microbial demand for N collectively contributed to higher export of N below the E. umbellata patched relative to the grassland system. Thus, areas invaded by this exotic N2-fixing species may function as N sources rather than the N conserving systems typically expected early successional communities following agricultural abandonment. # 2006 Elsevier B.V. All rights reserved.", "keywords": ["0106 biological sciences", "2. Zero hunger", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.agee.2006.01.004"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agriculture%2C%20Ecosystems%20%26amp%3B%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agee.2006.01.004", "name": "item", "description": "10.1016/j.agee.2006.01.004", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agee.2006.01.004"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2006-07-01T00:00:00Z"}}, {"id": "3168726210", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-24T16:27:18Z", "type": "Journal Article", "created": "2021-07-13", "title": "A talaj elektromos vezet\u0151k\u00e9pess\u00e9ge \u00e9s a term\u0151helyi z\u00f3n\u00e1k talajtulajdons\u00e1gai k\u00f6z\u00f6tti \u00f6sszef\u00fcgg\u00e9sek", "description": "

Vizsg\uffc3\uffa1latunk c\uffc3\uffa9lja az volt, hogy egy Somogyban elhelyezked\uffc5\uff91, dombvid\uffc3\uffa9ki mintater\uffc3\uffbclet sz\uffc3\uffa1nt\uffc3\uffb3in elemezz\uffc3\uffbck a m\uffc3\uffa9rt talaj-vezet\uffc5\uff91k\uffc3\uffa9pess\uffc3\uffa9g (EC) \uffc3\uffa9rt\uffc3\uffa9kek \uffc3\uffa9s lehat\uffc3\uffa1rolt term\uffc5\uff91helyi (m\uffc5\uffb1vel\uffc3\uffa9si) z\uffc3\uffb3n\uffc3\uffa1k talajtulajdons\uffc3\uffa1gai k\uffc3\uffb6z\uffc3\uffb6tti \uffc3\uffb6sszef\uffc3\uffbcgg\uffc3\uffa9seket. A vizsg\uffc3\uffa1lt sz\uffc3\uffa1nt\uffc3\uffb3ter\uffc3\uffbcletek l\uffc3\uffb6sz\uffc3\uffb6n kialakult, t\uffc3\uffadpusos Ramann-f\uffc3\uffa9le barna erd\uffc5\uff91talajon \uffc3\uffa9s karbon\uffc3\uffa1tos csernozjom barna erd\uffc5\uff91talajon helyezkednek el. Feltalajuk d\uffc3\uffb6nt\uffc5\uff91en v\uffc3\uffa1lyog \uffc3\uffa9s agyagos v\uffc3\uffa1lyog fizikai f\uffc3\uffa9les\uffc3\uffa9g\uffc5\uffb1. A talaj vezet\uffc5\uff91k\uffc3\uffa9pess\uffc3\uffa9g\uffc3\uffa9t 50 \uffc3\uffa9s 100 cm-es talajm\uffc3\uffa9lys\uffc3\uffa9gben m\uffc3\uffa9rt\uffc3\uffbck.

A mintater\uffc3\uffbclet talajadatait t\uffc3\uffa9rinformatikai \uffc3\uffa1llom\uffc3\uffa1nyba foglaltuk, az adatok rendez\uffc3\uffa9s\uffc3\uffa9t \uffc3\uffa9s azok \uffc3\uffb6sszekapcsol\uffc3\uffa1s\uffc3\uffa1t az ESRI ArcGIS 10.0 programmal v\uffc3\uffa9gezt\uffc3\uffbck el. A t\uffc3\uffa1bl\uffc3\uffa1k heterogenit\uffc3\uffa1s\uffc3\uffa1t mutat\uffc3\uffb3 laborat\uffc3\uffb3riumi talajvizsg\uffc3\uffa1latok eredm\uffc3\uffa9nyeit a m\uffc3\uffa9rt EC \uffc3\uffa9rt\uffc3\uffa9kekkel \uffc3\uffb6sszevetett\uffc3\uffbck, amelyhez az IBM SPSS Statistics 20 szoftver seg\uffc3\uffadts\uffc3\uffa9g\uffc3\uffa9vel stepwise-t\uffc3\uffadpus\uffc3\uffba line\uffc3\uffa1ris regresszi\uffc3\uffb3t alkalmaztunk. A regresszi\uffc3\uffb3kat a talajvizsg\uffc3\uffa1latok csoportos\uffc3\uffadt\uffc3\uffa1s\uffc3\uffa1val megegyez\uffc5\uff91en: alap (\uffe2\uff80\uff9ea\uffe2\uff80\uff9d eset), b\uffc5\uff91v\uffc3\uffadtett (\uffe2\uff80\uff9eb\uffe2\uff80\uff9d eset) \uffc3\uffa9s teljesk\uffc3\uffb6r\uffc5\uffb1 (\uffe2\uff80\uff9ec\uffe2\uff80\uff9deset) alapj\uffc3\uffa1n futtattuk le. A sz\uffc3\uffa1m\uffc3\uffadt\uffc3\uffa1sokn\uffc3\uffa1l az \uffe2\uff80\uff9ea\uffe2\uff80\uff9d eset a talajtulajdons\uffc3\uffa1gokat meghat\uffc3\uffa1roz\uffc3\uffb3 fontosabb talajparam\uffc3\uffa9terek (k\uffc3\uffb6t\uffc3\uffb6tts\uffc3\uffa9g, humusz- \uffc3\uffa9s m\uffc3\uffa9sztartalom, k\uffc3\uffa9mhat\uffc3\uffa1s), a \uffe2\uff80\uff9eb\uffe2\uff80\uff9d eset az alap talajparam\uffc3\uffa9tereket \uffc3\uffa9s a makro t\uffc3\uffa1panyagok (NPK ell\uffc3\uffa1totts\uffc3\uffa1got), valamint a \uffe2\uff80\uff9ec\uffe2\uff80\uff9d eset az el\uffc5\uff91z\uffc5\uff91 kett\uffc5\uff91t \uffc3\uffa9s mikro t\uffc3\uffa1panyagok (Mg2+, Na+, Zn2+, Cu2+, Mn2+, SO42\uffe2\uff80\uff93, Fe2+ + Fe3+) k\uffc3\uffb6r\uffc3\uffa9t jelenti.

A k\uffc3\uffbcl\uffc3\uffb6nb\uffc3\uffb6z\uffc5\uff91 csoportos\uffc3\uffadt\uffc3\uffa1sban elv\uffc3\uffa9gzett elemz\uffc3\uffa9sek sor\uffc3\uffa1n arra voltunk k\uffc3\uffadv\uffc3\uffa1ncsiak, hogy a vizsg\uffc3\uffa1lati talajparam\uffc3\uffa9terek k\uffc3\uffb6r\uffc3\uffa9nek v\uffc3\uffa1ltoztat\uffc3\uffa1s\uffc3\uffa1val szorosabb kapcsolatokat tal\uffc3\uffa1lunk-e a m\uffc3\uffa9rt \uffc3\uffa1tlagos EC \uffc3\uffa9rt\uffc3\uffa9kek \uffc3\uffa9s a talajtulajdons\uffc3\uffa1gok k\uffc3\uffb6z\uffc3\uffb6tt. Az eredm\uffc3\uffa9nyeink \uffc3\uffa1ltal kaphatunk-e olyan kell\uffc5\uff91 pontoss\uffc3\uffa1g\uffc3\uffba \uffc3\uffa9s megb\uffc3\uffadzhat\uffc3\uffb3s\uffc3\uffa1g\uffc3\uffba becsl\uffc5\uff91modellt, amely a talajok t\uffc3\uffa9rbeli heterogenit\uffc3\uffa1s\uffc3\uffa1t megmutatja az EC \uffc3\uffa9rt\uffc3\uffa9kek alapj\uffc3\uffa1n, \uffc3\uffadgy a m\uffc3\uffb3dszer nagyban meggyors\uffc3\uffadthatja \uffc3\uffa9s leegyszer\uffc5\uffb1s\uffc3\uffadtheti a \uffe2\uff80\uff9ehagyom\uffc3\uffa1nyos\uffe2\uff80\uff9d talajvizsg\uffc3\uffa1latokhoz k\uffc3\uffa9pest a term\uffc5\uff91helyi z\uffc3\uffb3n\uffc3\uffa1k elk\uffc3\uffbcl\uffc3\uffb6n\uffc3\uffadt\uffc3\uffa9s\uffc3\uffa9t.

A vizsg\uffc3\uffa1lati eredm\uffc3\uffa9nyeink alapj\uffc3\uffa1n elmondhat\uffc3\uffb3, hogy mindh\uffc3\uffa1rom regresszi\uffc3\uffb3s csoportos\uffc3\uffadt\uffc3\uffa1s eset\uffc3\uffa9n a tengerszint feletti magass\uffc3\uffa1g cs\uffc3\uffb6kken\uffc3\uffa9s\uffc3\uffa9vel ar\uffc3\uffa1nyosan n\uffc5\uff91 a talaj-vezet\uffc5\uff91k\uffc3\uffa9pess\uffc3\uffa9g, illetve az EC \uffc3\uffa9rt\uffc3\uffa9kek n\uffc3\uffb6veked\uffc3\uffa9s\uffc3\uffa9vel n\uffc5\uff91 a talajok k\uffc3\uffb6t\uffc3\uffb6tts\uffc3\uffa9ge, amellyel egy\uffc3\uffbctt n\uffc3\uffb6vekszik az agyagtartalom is. Ez a folyamat 100 cm-es talajm\uffc3\uffa9lys\uffc3\uffa9gben a nagyobb v\uffc3\uffadztartalom miatt er\uffc5\uff91teljesebben jelentkezik, mint az 50 cm-es talajm\uffc3\uffa9lys\uffc3\uffa9gben. A term\uffc5\uff91helyi z\uffc3\uffb3n\uffc3\uffa1k term\uffc3\uffa9kenys\uffc3\uffa9gi viszonyait az els\uffc5\uff91dleges talajtulajdons\uffc3\uffa1gokon, illetve a makro \uffc3\uffa9s a mikro t\uffc3\uffa1panyag-ell\uffc3\uffa1totts\uffc3\uffa1gokon k\uffc3\uffadv\uffc3\uffbcl a domborzati viszonyok is m\uffc3\uffb3dos\uffc3\uffadthatj\uffc3\uffa1k. A talajellen\uffc3\uffa1ll\uffc3\uffa1s m\uffc3\uffa9r\uffc3\uffa9se b\uffc3\uffa1rki sz\uffc3\uffa1m\uffc3\uffa1ra el\uffc3\uffa9rhet\uffc5\uff91, gyors \uffc3\uffa9s egyszer\uffc5\uffb1 m\uffc3\uffb3dszer. A laborat\uffc3\uffb3riumi talajvizsg\uffc3\uffa1latokat kieg\uffc3\uffa9sz\uffc3\uffadtve alkalmas arra, hogy a prec\uffc3\uffadzi\uffc3\uffb3s n\uffc3\uffb6v\uffc3\uffa9nytermeszt\uffc3\uffa9sben seg\uffc3\uffadts\uffc3\uffa9get ny\uffc3\uffbajtson a term\uffc5\uff91helyi z\uffc3\uffb3n\uffc3\uffa1k lehat\uffc3\uffa1rol\uffc3\uffa1s\uffc3\uffa1ban.

Our aim was to analyse the relationships between the measured soil electrical conductivity (EC) and the soil properties of different delimited production (tillage) zones in a hillside sample area situated in Somogy county. The examined arable lands are situated in typical Ramann-type brown forest soil and chernozem-brown forest soil mostly with loam and clay loam formed on loess. For the investigations, two soil resistance values (measured at 50 cm and 100 cm depth) were used.

Soil data of the sample area were incorporated into a GIS file, the ordering and connection of the data was performed by ESRI ArcGIS 10.0 program. The results of the soil laboratory tests (which show soil heterogeneity) were correlated to the measured EC-values with stepwise linear regression using IBM SPSS Statistics 20 software. The regression were run in line with the alignment of soil investigations: basic (case \uffe2\uff80\uff9ea\uffe2\uff80\uff9d), extended (case \uffe2\uff80\uff9eb\uffe2\uff80\uff9d) and completed (case \uffe2\uff80\uff9ec\uffe2\uff80\uff9d). By the calculations, case \uffe2\uff80\uff9ea\uffe2\uff80\uff9d means the group of the most important soil parameters which are determinative soil characteristics (upper limit of plasticity or KA, humus-, lime content, pH), case \uffe2\uff80\uff9eb\uffe2\uff80\uff9d means the previous one plus the group of macronutrients (NPK-content), while case \uffe2\uff80\uff9ec\uffe2\uff80\uff9d means case \uffe2\uff80\uff9eb\uffe2\uff80\uff9d plus the group of micronutrients (Mg2+, Na+, Zn2+, Cu2+, Mn2+, SO42\uffe2\uff80\uff93, Fe2+ + Fe3+).

With the analyses made in different alignments our aim was to determine whether with the changing of examined soil parameters there will be tighter relationships between the measured EC-values and soil properties. Further aim was to examine whether it is possible to make a properly accurate and reliable estimation model, which can show the real soil circumstances (spatial heterogeneity of soils) based on EC-values, since this method can accelerate and simplify the separation of productivity zones compared to the conventional soil examinations.

Based on the results it can be concluded that in case of all the three regression groups the electrical conductivity increases proportionally with the decreasing of elevation. Besides, with the increasing of EC-values the KA \uffe2\uff80\uff93 and with it, the clay content also \uffe2\uff80\uff93 increases. This process develops in a more significant way in the depth of 100 cm than in 50 cm because of the higher water content. Besides the primary soil characteristics and the amount of macro- and micronutrients, the fertility conditions of the production zones can be affected by the geographical circumstances as well. The measurement of soil resistance is a fast, easy and generally available method, which is suitable \uffe2\uff80\uff93 with the completion of laboratory examinations \uffe2\uff80\uff93 for giving assistance to delineate the production zones in the precision crop production.