Organic carbon content determination in soils: challenges and opportunities of elemental analysis versus thermogravimetry

Sustainable soil management needs reliable and accurate monitoring of soil organic carbon (SOC) content. However, despite of the development of analytical techniques during last decades, the detection opportunities for short term and rather small changes in SOC induced by organic fertilization, organic amendments or land use changes are still limited with the available methods. This study aims to quantify the theoretical detection opportunities for changes in SOC content with elemental analysis (EA) as the standard method in comparing with thermogravimetry (TG) as an enhanced traditional approach derived from soil organic matter determination via mass losses on ignition. The carried out experiments consist of mixing soil samples from non-fertilized plots of three long-term agricultural experiments in Bad Lauchstaedt, Großbeeren and Muencheberg (silty loam, loamy sand and silty sand) with straw, farmyard manure, sheep faeces and charcoal in four quantities (3 t×ha-1, 20 t×ha-1, 60 t×ha-1 and 180 t×ha‑1fresh matter) under laboratory conditions.The quantities were based on fresh matter application in agricultural practice accepting different amounts of added organic carbon. The results confirm EA as a method of higher reliability and accuracy for carbon content determination. TG allows to distinguish the different types of added amendments with high sensitivity. This was achieved by using newly developed evaluation algorithms for the thermal decay dynamics. We conclude from these results that TG cannot substitute EA to determine organic carbon on a routine base. However, TG could be a supplementary fingerprinting technique for the detection of added organic carbon to soils from organic fertilizers and to distinguish sources of geological or anthropogenic origin enabling a future assessment of soil organic carbon quality

Multi-modelling predictions show high uncertainty of required carbon input changes to reach a 4‰ target

Soils store vast amounts of carbon (C) on land, and increasing soil organic carbon (SOC) stocks in already managed soils such as croplands may be one way to remove C from the atmosphere, thereby limiting subsequent warming. The main objective of this study was to estimate the amount of additional C input needed to annually increase SOC stocks by 4%(0) at 16 long-term agricultural experiments in Europe, including exogenous organic matter (EOM) additions. We used an ensemble of six SOC models and ran them under two configurations: (1) with default parametrization and (2) with parameters calibrated site-by-site to fit the evolution of SOC stocks in the control treatments (without EOM). We compared model simulations and analysed the factors generating variability across models. The calibrated ensemble was able to reproduce the SOC stock evolution in the unfertilised control treatments. We found that, on average, the experimental sites needed an additional 1.5 +/- 1.2 Mg C ha(-)(1) year(-1) to increase SOC stocks by 4%(0) per year over 30 years, compared to the C input in the control treatments (multi-model median +/- median standard deviation across sites). That is, a 119% increase compared to the control. While mean annual temperature, initial SOC stocks and initial C input had a significant effect on the variability of the predicted C input in the default configuration (i.e., the relative standard deviation of the predicted C input from the mean), only water-related variables (i.e., mean annual precipitation and potential evapotranspiration) explained the divergence between models when calibrated. Our work highlights the challenge of increasing SOC stocks in agriculture and accentuates the need to increasingly lean on multi-model ensembles when predicting SOC stock trends and related processes. To increase the reliability of SOC models under future climate change, we suggest model developers to better constrain the effect of water-related variables on SOC decomposition

Nitrogen fertiliser replacement values for organic amendments appear to increase with N application rates

Nitrogen (N) supply from organic amendments [such as farmyard manure (FYM), slurries or crop residues] to crops is commonly expressed in the amendment’s Nitrogen Fertiliser Replacement Value (NFRV). Values for NFRV can be determined by comparison of crop yield or N uptake in amended plots against mineral fertiliser-only plots. NFRV is then defined as the amount of mineral fertiliser N saved when using organic amendment-N (kg/kg), while attaining the same crop yield. Factors known to affect NFRV are crop type cultivated, soil type, manuring history and method or time of application. We investigated whether long-term NFRV depends on N application rates. Using data from eight long term experiments in Europe, values of NFRV at low total N supply were compared with values of NFRV at high total N supply. Our findings show that FYM has a significant higher NFRV value at high total N supply than at low total N supply (1.12 vs. 0.53, p = 0.04). For the other amendment types investigated, NFRV was also higher at high total N supply than at low total N supply, but sample sizes were too small or variations too large to detect significant differences. Farmers in Europe usually operate at high rates of total N applied. If fertiliser supplements are based on NFRV of the manure estimated at low total N supply, N fertiliser requirements might be overestimated. This might lead to overuse of N, lower N use efficiency and larger losses of N to the environment

Nitrogen fertiliser replacement values for organic amendments appear to increase with N application rates

Nitrogen (N) supply from organic amendments [such as farmyard manure (FYM), slurries or crop residues] to crops is commonly expressed in the amendment’s Nitrogen Fertiliser Replacement Value (NFRV). Values for NFRV can be determined by comparison of crop yield or N uptake in amended plots against mineral fertiliser-only plots. NFRV is then defined as the amount of mineral fertiliser N saved when using organic amendment-N (kg/kg), while attaining the same crop yield. Factors known to affect NFRV are crop type cultivated, soil type, manuring history and method or time of application. We investigated whether long-term NFRV depends on N application rates. Using data from eight long term experiments in Europe, values of NFRV at low total N supply were compared with values of NFRV at high total N supply. Our findings show that FYM has a significant higher NFRV value at high total N supply than at low total N supply (1.12 vs. 0.53, p = 0.04). For the other amendment types investigated, NFRV was also higher at high total N supply than at low total N supply, but sample sizes were too small or variations too large to detect significant differences. Farmers in Europe usually operate at high rates of total N applied. If fertiliser supplements are based on NFRV of the manure estimated at low total N supply, N fertiliser requirements might be overestimated. This might lead to overuse of N, lower N use efficiency and larger losses of N to the environment.</p

Si cycling in a forest biogeosystem – the importance of transient state biogenic Si pools

The relevance of biological Si cycling for dissolved silica (DSi) export from terrestrial biogeosystems is still in debate. Even in systems showing a high content of weatherable minerals, like Cambisols on volcanic tuff, biogenic Si (BSi) might contribute &gt; 50% to DSi (Gerard et al., 2008). However, the number of biogeosystem studies is rather limited for generalized conclusions. To cover one end of controlling factors on DSi, i.e., weatherable minerals content, we studied a forested site with absolute quartz dominance (&gt; 95%). Here we hypothesise minimal effects of chemical weathering of silicates on DSi. During a four year observation period (05/2007–04/2011), we quantified (i) internal and external Si fluxes of a temperate-humid biogeosystem (beech, 120 yr) by BIOME-BGC (version ZALF), (ii) related Si budgets, and (iii) Si pools in soil and beech, chemically as well as by SEM-EDX. For the first time two compartments of biogenic Si in soils were analysed, i.e., phytogenic and zoogenic Si pool (testate amoebae). We quantified an average Si plant uptake of 35 kg Si ha−1 yr−1 – most of which is recycled to the soil by litterfall – and calculated an annual biosilicification from idiosomic testate amoebae of 17 kg Si ha−1. The comparatively high DSi concentrations (6 mg L−1) and DSi exports (12 kg Si ha−1 yr−1) could not be explained by chemical weathering of feldspars or quartz dissolution. Instead, dissolution of a relictic, phytogenic Si pool seems to be the main process for the DSi observed. We identified canopy closure accompanied by a disappearance of grasses as well as the selective extraction of pine trees 30 yr ago as the most probable control for the phenomena observed. From our results we concluded the biogeosystem to be in a transient state in terms of Si cycling

Reproducing CO<inf>2</inf> exchange rates of a crop rotation at contrasting terrain positions using two different modelling approaches

In undulating landscapes erosion is largely responsible for the spatial distribution of C stocks in agricultural soils. Whether these stocks contribute to global atmospheric CO2 concentrations as source or sink of CO2 is under constant debate. Periodic CO2 measurements were carried out at a hummocky ground moraine site grown with maize, fodder rye and sorghum using dynamic non-steady-state transparent and opaque chambers. Flux calculation for CO2 was conducted using the empirical gap-filling model of Hoffmann et al. (2015b), which uses temperature and radiation to simulate ecosystem respiration (Reco) and gross primary production (GPP) and to calculate net ecosystem CO2 exchange (NEE). This model was compared with a process-based agro-ecosystem simulation model, MONICA, which was tested for its ability to simulate Reco, GPP and NEE, using the empirical model as benchmark. Both models simulated GPP and Reco in the same order of magnitude, with MONICA simulating a considerably higher amount of CO2 produced by photosynthesis for maize and less deviating CO2 produced by photosynthesis for the other crops and CO2 consumed by respiration for all crops as compared to the empirical model. Both models largely agree in CO2 flux patterns, but show considerable differences directly after harvest and during bare soil periods. Strengths and weaknesses of both approaches were discussed and synergies of applying both approaches in conjunction were identified in a way that (i) MONICA may act as an independent method to identify significant deviations from the optimum crop growth pattern and thus point at times during which assumptions of the empirical model for simulating NEE may be violated and that (ii) the empirical model may act as a calibration benchmark for MONICA flux simulations