laborczi@rissac.hu 
The results show that data-driven spatial models can be successfully applied to estimate soil erosion. However, the transferability of the models even between nearby sample areas requires further investigation.
The paper, published in the journal Land, is available at the link below:
Takáts T, Pásztor L, Árvai M, Albert G, Mészáros J. Testing the Applicability and Transferability of Data-Driven Geospatial Models for Predicting Soil Erosion in Vineyards. Land. 2025; 14(1):163.
Using paleontological data spanning 1.45 million years, historical records from place names, and monitoring data from 1964 to 2020, the authors analyse population trends and change of the ground squirrel’s distribution range in Hungary primarily but the findings can be extended to the Pannonian Ecoregion as well in terms of long term trends. Statistical modelling, including two times interrupted ARIMA and Bayesian structural time series models, is employed to forecast future population numbers and identify breakpoints in the population history. The study identifies significant, about 10 percent annual population declines prior to agricultural changes in the 1960s and after that a more dramatic decline until nowadays. The study also explores the impact of conservation interventions, such as legal protection and translocation programs. The results suggest a potential positive effect from recent conservation translocations but highlight ongoing uncertainty regarding the species’ long-term future.
The original article can be freely available at the link below:
Cserkész T, Váczi O, Takáts T, Pazonyi P, Mikesy G, Brevik E C, Nagy L, Csathó A I, Németh A, Szitta T, Kiss Cs, Laborczi A, Mészáros J, Gedeon Cs. 2025. Past and present existence of Spermophilus citellus in Hungary with a forecast of its population using time series models. Journal for Nature Conservation 84, 126836.
These high-resolution particle size distribution maps will support a more accurate understanding of soil hydrology and water management conditions in the mapped regions. This, in turn, will aid agricultural and water management planning, helping to adapt to increasingly frequent extreme climatic events.
The study has been published in Geoderma and is available at the following link:
The original article is available at the following link:
A number of presentations were given by internationally renowned researchers on recent scientific findings and challenges related to soil health. During the poster sessions, participants had the opportunity to talk to the researchers in person, and during the breaks, informal discussions provided an opportunity to build professional relationships and share experiences. For those who could not attend in person, the presentations were streamed online and posters were made available digitally.
The programme and the book of abstracts of the Budapest Soil Health Forum can be found at www.soilhealthforum.hu.
To create these maps, the researchers applied advanced machine learning technique that modeled the spatial and temporal changes of SOC based on topographical, climatic, and land use factors. The results not only show the distribution of SOC but also quantify the associated uncertainty, thus supporting scientifically sound decision-making.
The resulting maps are freely available and can serve as valuable tools for sustainable land use, rural development, ecosystem services assessment, etc. These findings may contribute to achieving the goals of the Soil Monitoring Law, the European Green Deal, and other international sustainability initiatives, promoting more effective soil protection and carbon sequestration.
The presented methodology stands out by using a hybrid approach that integrates machine learning with space-time geostatistics, addressing key limitations of previous approaches. It allows for reliable SOC predictions along with uncertainty estimates at any spatial and temporal scale, even in years where no direct SOC measurements are available. This comprehensive method offers a more robust and dynamic understanding of SOC changes not just in space but also in time. The compiled map series provide valuable information for researchers, society and even policymakers, helping to tackle environmental challenges such as land and soil degradation, climate change, and ecosystem assessment. These findings support ongoing initiatives like the EU Soil Monitoring Directive and the UN Sustainable Development Goals, offering practical tools for tracking SOC changes and assessing soil health over time.
This research fills a key gap in our understanding of SOC dynamics in Hungary and offers a methodology that can be adapted internationally to improve the accuracy and utility of SOC data to address the environmental challenges and crises of our time.
In Europe, different types of monitoring networks currently exist in parallel. Many EU Member states developed their own national soil information monitoring system, some being in place for decades (e.g. the Hungarian Soil Information and Monitoring System). In parallel in 2009, the European Commission extended the periodic Land Use/Land Cover Area Frame Survey (LUCAS) led by EUROSTAT to sample and analyse the main properties of topsoil in EU in order to develop a homogeneous dataset for EU.
The latest publication compares the soil sampling strategies (e.g. spatial density, distribution of soil types and land cover) within countries in the national and the European soil information system. The distribution of three basic soil properties (pH, organic carbon, and clay content) and two soil health indicators (organic carbon/clay ratio and pH classes) are also compared. The comparison highlights the differences and gaps between national and international soil information databases across countries, the potential and obstacles to their combined use, and the need to harmonise the methodology used by each country.
Different potassium supply levels were achieved by the initial build-up in autumn 1989. Adequate nitrogen and phosphorus supplies were provided by yearly NP fertilization. The year studied was favourable for maize growth and development. The plant density had a more pronounced effect on grain yield than the different K supplies. Stalk yields showed trends similar to those for grain yields, but plant density had the opposite effect on the leaf weight in the flowering stage. K fertilization increased the K content to the greatest extent in the vegetative parts (leaf and stalk), while increasing plant density had a reverse effect. The K-Ca-Mg antagonism was also the most pronounced in the vegetative parts, i.e. maize leaves in the flowering stage.
According to the results obtained in the field trial, it seems that a century ago, in our grandparents’ time, food contained more minerals than nowadays, due to the fact that plant density decreases grain mineral composition more than mineral fertilization can increase it.
The results of the research can be found in the following publication:
The Forum consists of four events, including two international conferences, a workshop and a panel discussion:
Our colleagues play a major role in the organisation of the Forum, moreover the HUN-REN ATK Soil Science Institute is the organiser of the conference “Improving Soil Health” as well as co-organiser of the conference “Artificial Intelligence for Soil Health”.
More information about the events and registration is available at soilhealthforum.hu