Maps of heavy metals in the soils of the European Union and proposed priority areas for detailed assessment

AbstractSoil contamination is one of the greatest concerns among the threats to soil resources in Europe and globally. Despite of its importance there was only very course scale (1/5000km2) data available on soil heavy metal concentrations prior to the LUCAS topsoil survey, which had a sampling density of 200km2. Based on the results of the LUCAS sampling and auxiliary information detailed and up-to-date maps of heavy metals (As, Cd, Cr, Cu, Hg, Pb, Zn, Sb, Co and Ni) in the topsoil of the European Union were produced. Using the maps of heavy metal concentration in topsoil we made a spatial prediction of areas where local assessment is suggested to monitor and eventually control the potential threat from heavy metals. Most of the examined elements remain under the corresponding threshold values in the majority of the land of the EU. However, one or more of the elements exceed the applied threshold concentration on 1.2Mkm2, which is 28.3% of the total surface area of the EU. While natural backgrounds might be the reason for high concentrations on large proportion of the affected soils, historical and recent industrial and mining areas show elevated concentrations (predominantly of As, Cd, Pb and Hg) too, indicating the magnitude of anthropogenic effect on soil quality in Europe

Phosphorus levels in croplands of the European Union with implications for P fertilizer use

tIn the frame of the Land Use/Land Cover Area Frame Survey sampling of topsoil was carried out on around22,000 points in 25 EU Member States in 2009 and in additional 2 Member States in 2012. Besidesother basic soil properties soil phosphorus (P) content of the samples were also measured in a singlelaboratory in both years. Based on the results of the LUCAS topsoil survey we performed an assessmentof plant available P status of European croplands. Higher P levels can be observed in regions where highercrop yields can be expected and where high fertilizer P inputs are reported. Plant available phosphoruslevels were determined using two selected fertilizer recommendation systems: one from Hungary andone from the United Kingdom. The fertilizer recommendation system of the UK does not recommendadditional fertilizer use on croplands with highest P supply, which covers regions mostly in Belgiumand the Netherlands. According to a Hungarian advisory system there is a need for fertilizer P input inall regions of the EU. We established a P fertilizer need map based on integrating results from the twosystems. Based on data from 2009 and 2012, P input demand of croplands in the European Union wasestimated to 3, 849, 873 tons(P2O5)/year. Meanwhile we found disparities of calculated input need andreported fertilizer statistics both on local (country) scale and EU level. The first ever uniform topsoilP survey of the EU highlights the contradictions between soil P management of different countries ofthe Union and the inconsistencies between reported P fertilizer consumption and advised P doses. Ouranalysis shows a status of a baseline period of the years 2009 and 2012, while a repeated LUCAS topsoilsurvey can be a useful tool to monitor future changes of nutrient levels, including P in soils of the EU

MARTA: Magyarországi Részletes Talajfizikai Adatbázis létrehozása és alkalmazása a talaj vízgazdálkodásának jellemzésére szélsőséges időjárási körülmények között = MARTA: Development and use of a database of hydrophysical properties of Hungarian soils to characterize the soil water management under extreme weather conditions

A pályázat keretében létrehozott MARTHA (Magyarországi Részletes Talajfizikai és Hidrológiai Adatbázis) adatbázis a hazai talajfizikai laboratóriumokban mért talajfizikai és vízgazdálkodási mérési eredmények (és a hozzájuk kapcsolódó talajtani alapadatok) egységes rendszerbe szervezett gyűjteménye. Reprezentativitása kiterjed az ország egész területére. Alapot nyújt országos és területi pedotranszfer függvények előállítására éppúgy, mint a talajtérképi információk alapján történő csoportbecslési módszerek kidolgozására. A jelenlegi MARTHA ver 2.0 adatbázis mintegy 4000 talajszelvény 15 000 talajrétegének adatait tartalmazza. | The Hungarian Detailed Soil Hydrophysical Database, called MARTHA ver2.0 was developed to collect laboratory test results of physical properties, water management characteristics and basic soil properties. Datasets of the database cover the whole area of Hungary and are organized according to a uniform metadata model and presented in a harmonized manner. The MARTHA database provides a basis for the development of pedotransfer functions for regional or country scale applications. It can be also used for the development of group estimate methods based on soil map information. The current version (v2.0) of the MARTHA databases holds data of some 15000 soil layers from approximately 4000 soil profiles

Diszkrimináció a tanári értékelésben

A kutatók a kutatás során azt vizsgálták, milyen különbségek lelhetőek fel a tanárok osztályozási gyakorlatában és továbbtanulási ajánlásaiban és ezeknek milyen szándékolt és nem szándékolt következményei vannak a tanulók egyes csoportjaira. Kutatásuk során általános iskolai magyar és matematika szakos pedagógusokat kértek meg arra, hogy vegyenek részt egy online, önkitöltős kérdőíves kutatásban. A kérdőív első felében arra kérték őket, hogy 6 darab nyolcadikos szintű magyar vagy matematika dolgozatot javítsanak ki, pontozzanak és osztályozzanak le, majd a dolgozat alapján adjanak javaslatot a középiskolai továbbtanulásra vonatkozóan. A dolgozatok fiktív roma és nem roma fiú és lány neveket tartalmaztak, amelyeket a kitöltők között randomizáltak. A kérdőív második része a résztvevők demográfiai jellemzőjével, tanítási tapasztalatával és osztályozási gyakorlatával és elveivel kapcsolatban tartalmazott kérdéseket. Kutatásukban arra voltak kíváncsiak, hogy a tanárok osztályozási gyakorlatában meglévő egyéni, mikro-szintű különbségek vezetnek-e makro-szinten, az összes válaszadó válaszait tekintve átlagosan nemi vagy etnikai különbségekhez az osztályzatokban. A gyűjteményben található kérdőív és adatfile egy 24 hónapos, 2024. júniusig tartó embargós időszakot követően a kutatásvezető hozzájárulásával lesz elérhető

Fine-scale vertical position as an indicator of vegetation in alkaligrasslands – Case study based on remotely sensed data

tVertical position is an important driver of vegetation zonation at multiple scales, via determining abioticenvironmental parameters, such as climate, soil properties and water balance. In inland alkali landscapes,elevation is a key factor for understanding patterns of salt accumulation and water table which is thereforeconsidered a good indicator of alkali vegetation types. Remote sensing techniques offer viable solutionsfor linking elevation data to vegetation patterns by providing an elevation model of extended areas.Our goal was to test the relationships between fine-scale differences in vertical position and vegetationpatterns in inland alkali landscapes by vegetation data collected in the field and elevation data generatedusing airborne laser scanning (ALS). We studied whether vertical position influences vegetation patternsat the level of main vegetation groups (based on alliances) or even at the level of associations. Our studysites were situated in a lowland alkali landscape in Hortobágy National Park (East-Hungary). We groupedthe associations into four main vegetation groups: loess grasslands, alkali steppes, open alkali swards andalkali meadows. Even though we detected a very limited range (121 cm) in the vertical position of the mainvegetation groups, they were well separated by their vertical positions. At the level of associations, a moredetailed elevation-based distinction was also possible in many cases. The revealed elevation–vegetationcorrelations show that high-resolution mapping based on ALS remote sensing techniques is an idealsolution in complex lowland areas, such as alkali landscapes. Our findings suggest that in other typesof lowland landscapes, characterised by elevation differences, the applied method might hold a greatpotential as a supporting tool for vegetation mapping