Martin Wiesmeier

Bio: Martin Wiesmeier is an academic researcher from Technische Universität München. The author has contributed to research in topics: Soil carbon & Soil water. The author has an hindex of 29, co-authored 72 publications receiving 3080 citations. Previous affiliations of Martin Wiesmeier include Fujian Agriculture and Forestry University.

Digital mapping of soil organic matter stocks using Random Forest modeling in a semi-arid steppe ecosystem

Abstract: Spatial prediction of soil organic matter is a global challenge and of particular importance for regions with intensive land use and where availability of soil data is limited. This study evaluated a Digital Soil Mapping (DSM) approach to model the spatial distribution of stocks of soil organic carbon (SOC), total carbon (Ctot), total nitrogen (Ntot) and total sulphur (Stot) for a data-sparse, semi-arid catchment in Inner Mongolia, Northern China. Random Forest (RF) was used as a new modeling tool for soil properties and Classification and Regression Trees (CART) as an additional method for the analysis of variable importance. At 120 locations soil profiles to 1 m depth were analyzed for soil texture, SOC, Ctot, Ntot, Stot, bulk density (BD) and pH. On the basis of a digital elevation model, the catchment was divided into pixels of 90 m × 90 m and for each cell, predictor variables were determined: land use unit, Reference Soil Group (RSG), geological unit and 12 topography-related variables. Prediction maps showed that the highest amounts of SOC, Ctot, Ntot and Stot stocks are stored under marshland, steppes and mountain meadows. River-like structures of very high elemental stocks in valleys within the steppes are partly responsible for the high amounts of SOC for grasslands (81–84% of total catchment stocks). Analysis of variable importance showed that land use, RSG and geology are the most important variables influencing SOC storage. Prediction accuracy of the RF modeling and the generated maps was acceptable and explained variances of 42 to 62% and 66 to 75%, respectively. A decline of up to 70% in elemental stocks was calculated after conversion of steppe to arable land confirming the risk of rapid soil degradation if steppes are cultivated. Thus their suitability for agricultural use is limited.

Soil organic carbon stocks in southeast Germany (Bavaria) as affected by land use, soil type and sampling depth

Abstract: Precise estimations of soil organic carbon (SOC) stocks are of decided importance for the detection of C sequestration or emission potential induced by land use changes. For Germany, a comprehensive, land use–specific SOC data set has not yet been compiled. We evaluated a unique data set of 1460 soil profiles in southeast Germany in order to calculate representative SOC stocks to a depth of 1 m for the main land use types. The results showed that grassland soils stored the highest amount of SOC, with a median value of 11.8 kg m−2, whereas considerably lower stocks of 9.8 and 9.0 kg m−2 were found for forest and cropland soils, respectively. However, the differences between extensively used land (grassland, forest) and cropland were much lower compared with results from other studies in central European countries. The depth distribution of SOC showed that despite low SOC concentrations in A horizons of cropland soils, their stocks were not considerably lower compared with other land uses. This was due to a deepening of the topsoil compared with grassland soils. Higher grassland SOC stocks were caused by an accumulation of SOC in the B horizon which was attributable to a high proportion of C-rich Gleysols within grassland soils. This demonstrates the relevance of pedogenetic SOC inventories instead of solely land use–based approaches. Our study indicated that cultivation-induced SOC depletion was probably often overestimated since most studies use fixed depth increments. Moreover, the application of modelled parameters in SOC inventories is questioned because a calculation of SOC stocks using different pedotransfer functions revealed considerably biased results. We recommend SOC stocks be determined by horizon for the entire soil profile in order to estimate the impact of land use changes precisely and to evaluate C sequestration potentials more accurately.

Isolating organic carbon fractions with varying turnover rates in temperate agricultural soils : a comprehensive method comparison

Abstract: Fractionation of soil organic carbon (SOC) is crucial for mechanistic understanding and modeling of soil organic matter decomposition and stabilization processes. It is often aimed at separating the bulk SOC into fractions with varying turnover rates, but a comprehensive comparison of methods to achieve this is lacking. In this study, a total of 20 different SOC fractionation methods were tested by participating laboratories for their suitability to isolate fractions with varying turnover rates, using agricultural soils from three experimental sites with vegetation change from C3 to C4 22–36 years ago. Enrichment of C4-derived carbon was traced and used as a proxy for turnover rates in the fractions. Methods that apply a combination of physical (density, size) and chemical (oxidation, extraction) fractionation were identified as most effective in separating SOC into fractions with distinct turnover rates. Coarse light SOC separated by density fractionation was the most C4-carbon enriched fraction, while oxidation-resistant SOC left after extraction with NaOCl was the least C4-carbon enriched fraction. Surprisingly, even after 36 years of C4 crop cultivation in a temperate climate, no method was able to isolate a fraction with more than 76% turnover, which challenges the link to the most active plant-derived carbon pools in models. Particles with density >2.8 g cm−3 showed similar C4-carbon enrichment as oxidation-resistant SOC, highlighting the importance of sesquioxides for SOC stabilization. The importance of clay and silt-sized particles (

Greenhouse gas emissions from soils—A review

Abstract: Soils act as sources and sinks for greenhouse gases (GHG) such as carbon dioxide (CO 2 ), methane (CH 4 ), and nitrous oxide (N 2 O). Since both storage and emission capacities may be large, precise quantifications are needed to obtain reliable global budgets that are necessary for land-use management (agriculture, forestry), global change and for climate research. This paper discusses exclusively the soil emission-related processes and their influencing parameters. It reviews soil emission studies involving the most important land-cover types and climate zones and introduces important measuring systems for soil emissions. It addresses current shortcomings and the obvious bias towards northern hemispheric data. When using a conservative average of 300 mg CO 2 e m −2 h −1 (based on our literature review), this leads to global annual net soil emissions of ≥350 Pg CO 2 e (CO 2 e = CO 2 equivalents = total effect of all GHG normalized to CO 2 ). This corresponds to roughly 21% of the global soil C and N pools. For comparison, 33.4 Pg CO 2 are being emitted annually by fossil fuel combustion and the cement industry.

Modeling Soil Processes: Review, Key Challenges, and New Perspectives

Abstract: The remarkable complexity of soil and its importance to a wide range of ecosystem services presents major challenges to the modeling of soil processes. Although major progress in soil models has occurred in the last decades, models of soil processes remain disjointed between disciplines or ecosystem services, with considerable uncertainty remaining in the quality of predictions and several challenges that remain yet to be addressed. First, there is a need to improve exchange of knowledge and experience among the different disciplines in soil science and to reach out to other Earth science communities. Second, the community needs to develop a new generation of soil models based on a systemic approach comprising relevant physical, chemical, and biological processes to address critical knowledge gaps in our understanding of soil processes and their interactions. Overcoming these challenges will facilitate exchanges between soil modeling and climate, plant, and social science modeling communities. It will allow us to contribute to preserve and improve our assessment of ecosystem services and advance our understanding of climate-change feedback mechanisms, among others, thereby facilitating and strengthening communication among scientific disciplines and society. We review the role of modeling soil processes in quantifying key soil processes that shape ecosystem services, with a focus on provisioning and regulating services. We then identify key challenges in modeling soil processes, including the systematic incorporation of heterogeneity and uncertainty, the integration of data and models, and strategies for effective integration of knowledge on physical, chemical, and biological soil processes. We discuss how the soil modeling community could best interface with modern modeling activities in other disciplines, such as climate, ecology, and plant research, and how to weave novel observation and measurement techniques into soil models. We propose the establishment of an international soil modeling consortium to coherently advance soil modeling activities and foster communication with other Earth science disciplines. Such a consortium should promote soil modeling platforms and data repository for model development, calibration and intercomparison essential for addressing contemporary challenges.