Attila Nemes
Seniorforsker
(+47) 920 10 865
attila.nemes@nibio.no
Sted
Ås - Bygg O43
Besøksadresse
Oluf Thesens vei 43, 1433 Ås (Varelevering: Elizabeth Stephansens vei 21)
Vedlegg
CV_2022Biografi
I graduated as an agronomist (MSc) and later specialized in soil physics and hydrology (PhD). My core research interest is in the improvement of the model-data-process background of environmental modeling towards better water (quality and quantity) and resource management in agriculture and the environment. I have worked in an international cultural and research environment for over 25 years.
Current research interests include:
- Quantitative characterization of soil pore systems and soil structural development
- Exploration of climate-soil feed-backs, with focus on soil structure
- Characterization of flow pathways in field soils (e.g. agricultural areas, buffer-zones, etc.)
- Standardization of measurement methods in soil physics
- Improving the effectiveness of retention pond – wetland systems in retaining sediment and nutrients
- Database management, data harmonization and quality assurance
- Exploration of complex data sets using machine learning techniques
Key competencies:
- Field and laboratory experimentation
- Data mining
- Environmental modeling
- Programming
Forfattere
P.L. Sullivan S.A. Billings D. Hirmas L. Li X. Zhang S. Ziegler K. Murenbeeld H. Ajami A. Guthrie K. Singha D. Giménez A. Duro V. Moreno A. Flores A. Cueva A.N. Koop E.L. Aronson H.R. Barnard S.A. Banwart R.M. Keen Attila Nemes N.P. Nikolaidis J.B. Nippert D. Richter D.A. Robinson K. Sadayappan Souza de Souza M. Unruh H. WenSammendrag
Soils form the skin of the Earth’s surface, regulating water and biogeochemical cycles and generating production of food, timber, and textiles around the world. Changes in soil and its ability to perform a range of processes have important implications for Earth system function, especially in the critical zone (CZ)—the area that extends from the top of the canopy to the bottom of groundwater and that harbors most of Earth’s biosphere. A key aspect of the way soil functions results from its structure, defined as the size, shape, and arrangement of soil particles and pores. The network of pores provides storage space for at least a quarter of Earth’s biodiversity, while the abundance, size and connectivity of the pore space regulates fluxes of heat, water, nutrients and gases that define the physical and chemical environment. Here we review the nature of soil structure, focusing on its co-evolution with the plants and microbes that live within the soil, and the degree to which these processes have been incorporated into flow and transport models. Though it is well known that soil structure can change with wetting and drying events, often oscillating seasonally, the dynamic nature of soil structure that we discuss is a systematic shift that results in changes in its hydro-bio-geochemical function over decades to centuries, timescales over which major changes in carbon and nutrient cycles have been observed in the Anthropocene. We argue that the variable nature of soil structure, and its dynamics, need to be better understood and captured by land surface and ecosystem models, which currently describe soil structure as static. We further argue that modelers and empiricists both are well-poised to quantify and incorporate these dynamics into their studies. From these efforts, four fundamental questions emerge: 1) How do rates of soil aggregate formation and collapse, and their overall arrangements, interact in the Anthropocene to regulate CZ functioning from soil particle to continental scales? 2) How do alterations in rooting-depth distributions in the Anthropocene influence pore structure to control hydrological partitioning, biogeochemical transformations and fluxes, exchanges of energy and carbon with the atmosphere and climate, regolith weathering, and thus regulation of CZ functioning? 3) How does changing microbial functioning in a high CO2, warmer world with shifting precipitation patterns influence soil organic carbon dynamics and void-aggregate profile dynamics? 4) How deeply does human influence in the Anthropocene propagate into the subsurface, how does this depth relate to profile structure, and how does this alter the rate at which the CZ develops? The United Nations has recently recognized that 33% of the Earth's soils are already degraded and over 90% could become degraded by 2050. This recognition highlights the importance of addressing these proposed questions, which will promote a predictive understanding of soil structure.
Forfattere
David A. Robinson Attila Nemes Sabine Reinsch Alan Radbourne Laura Bentley Aidan M. KeithSammendrag
Det er ikke registrert sammendrag
Forfattere
Pierre-Adrien Rivier Dorina Jamniczky Attila Nemes Andras Mako Gyöngyi Barna Nikolett Uzinger Márk Rékási Csilla FarkasSammendrag
Det er ikke registrert sammendrag
Forfattere
Daniel R. Hirmas Daniel Gimenez Attila Nemes Ruth Kerry Nathaniel A. Brunsell Cassandra J. WilsonSammendrag
Soil macroporosity affects field-scale water-cycle processes, such as infiltration, nutrient transport and runoff1,2, that are important for the development of successful global strategies that address challenges of food security, water scarcity, human health and loss of biodiversity3. Macropores—large pores that freely drain water under the influence of gravity—often represent less than 1 per cent of the soil volume, but can contribute more than 70 per cent of the total soil water infiltration4, which greatly magnifies their influence on the regional and global water cycle. Although climate influences the development of macropores through soil-forming processes, the extent and rate of such development and its effect on the water cycle are currently unknown. Here we show that drier climates induce the formation of greater soil macroporosity than do more humid ones, and that such climate-induced changes occur over shorter timescales than have previously been considered—probably years to decades. Furthermore, we find that changes in the effective porosity, a proxy for macroporosity, predicted from mean annual precipitation at the end of the century would result in changes in saturated soil hydraulic conductivity ranging from −55 to 34 per cent for five physiographic regions in the USA. Our results indicate that soil macroporosity may be altered rapidly in response to climate change and that associated continental-scale changes in soil hydraulic properties may set up unexplored feedbacks between climate and the land surface and thus intensify the water cycle.
Sammendrag
Pedotransfer functions (PTFs) are widely used as an efficient alternative for estimating soil hydraulic properties. However, insufficient understanding of how specific input data characteristics drive PTF prediction performance, coupled with challenges in assessing PTF transferability beyond their development datasets, limit their robustness and broad application. Here, we employed the hierarchical Rosetta3 as the development dataset and evaluated its PTF performance using two independent application datasets (National Cooperative Soil Survey (NCSS) and HYBRAS-V2), comprising over 51,900 samples. To further investigate the effect of the input similarity on PTF performance, the Chamfer Distance (CD) was used to quantify the similarity between the development and application datasets. The extensive NCSS database allowed us to stratify the application dataset by soil temperature regimes, texture classes, and depths for a detailed performance evaluation. Results showed that incorporating additional inputs (e.g., bulk density, field capacity, and wilting point) moderately reduces the correlations between these newly added inputs and the estimation residuals, and that higher residual-input correlations are associated with inferior PTF performance. Furthermore, a lower CD (better resemblance of development and application dataset) leads to better PTF performance. However, increasing input complexity using the hierarchical Rosetta3 models mitigates this effect of resemblance, enhancing robustness across diverse soil and environmental conditions. These findings highlight the importance of analyzing residual-input correlations and suggest that quantifying input-data similarity between PTF development and application datasets can serve as a practical approach to assess the transferability of PTFs.
Sammendrag
Det er ikke registrert sammendrag
Sammendrag
Understanding how soil porosity varies across environmental gradients is critical for interpreting land–surface processes, including water storage, flow pathways, gas exchange, and carbon cycling. While organic carbon (OC) and soil texture are important influences on soil structure, their combined influence on porosity at landscape to continental scales remains incompletely resolved. Here, we compile topsoil datasets from Great Britain, Wales, the European LUCAS survey, and the USDA-NRCS NCSS database (n = 6335) to quantify relationships between porosity, OC, and clay content across diverse environmental conditions. Focusing on minimally disturbed soils, we evaluate individual and combined controls using generalized additive models. We develop and test simple empirical descriptors of OC:clay ratio, including a signed metric (NonCOCC) representing deviation from a reference ratio of 1 g OC to 10 g clay, positioning soils along a continuum from clay excess to OC excess. Across all regions, OC has the strongest relationship to porosity, explaining substantially more variation than OC:clay ratio metrics. NonCOCC provided a modest improvement in model performance when combined with OC and clay. Across regional datasets, the steepest portions of the fitted NonCOCC partial responses generally occurred at low positive values, suggesting a region of elevated porosity sensitivity. In a subset with aggregate-size data, this range of NonCOCC values also corresponds to a shift towards larger aggregates. This may suggest a structural pathway linking organic enrichment, aggregation, and porosity, but requires testing using data with measured OC partitions. The findings confirm importance of OC for predicting porosity and identify added value of simple metrics (NonCOCC) from widely available soil observations.
