The humus balance model (HU-MOD): a simple tool for the assessment of management change impact on soil organic matter levels in arable soils

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The demand for information on cropping system impact on soil organic matter (SOM) calls for efforts to improve the utilization of short‐term field experiments (e.g., to evaluate the parameterization of cropping systems in models). Those approaches have coped with the problem of determining small SOM changes within a large background mass. Thus, objectives of this survey are (1) the improvement of the minimum detectable difference (MDD) in SOM in the hudycrop short‐term field experiment by methods of sampling design and data treatment, (2) the verification to what extend the hudycrop short‐term field experiment allows for the determination of management induced effects on SOM, and (3) the investigation to what extent the obtained results may be suitable to evaluate the parameterization of a SOM balance model. The design of the hudycrop is suitable for excluding outliers plotwise. The estimation of plot means can be improved by the sampling design. Instead of determining a single plot mean in a mixed sampling procedure, the design provides multiple values for each plot, allowing for the identification of extreme values before calculating plot means. In consequence, minimum detectable differences decrease by a factor of 0.53 for soil organic C (SOC) and 0.63 for soil total N (STN) masses, allowing for detection of changes in the magnitude of 3.7 and 2.6% of background SOC and STN levels, respectively. Differences between treatments, however, are significant with corrected values (after outlier exclusion) for the crop production systems with the highest impact (potatoes and mulched red clover). Determining outliers based on Student's t‐test gives the lowest MDD and is therefore considered to be the most suitable method in this case. Correlations between apparent changes and SOM balances according to the HU‐MOD–2 model, used in this survey, indicate that the experimental design, in principal, is suitable for the evaluation of the parameterization of crop production systems in models. Still, an improved precision in SOM change detection is necessary. Reasonable options for that purpose are discussed in the paper.

Section: Methodsmentioning

confidence: 99%

Improving minimum detectable differences in the assessment of soil organic matter change in short‐term field experiments

Knebl

Leithold

Brock

2015

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“…The findings are in accordance with the humus balance results of our study. This supports the use of humus balance models as a tool to compare the impact of farming systems and cropland structures and to roughly estimate SOC changes ( Hülsbergen , 2003; Küstermann et al, 2008; Brock et al, 2012a; Brock et al, 2012b), also under Austrian conditions.…”

Section: Discussionmentioning

confidence: 56%

“…The difference between humus supply and humus demand is shown in the humus balance, according to the scheme: humus balance = humus supply – humus demand. The relevant parameters and mathematical algorithms applied are described in detail in Hülsbergen (2003) and Brock et al (2012a). The supply and demand parameters are gained using humus reproduction coefficients assigned to crops and fertilizers.…”

Section: Methodsmentioning

confidence: 99%

Humus balances of different farm production systems in main production areas in Austria

Kasper

Freyer

Hülsbergen

et al. 2014

The importance of the soil humus content is indisputable. Soil humus plays an important role in preserving soil fertility and exerts great influence on plant production and yield potential. However, proofing that management‐related changes in the stock of soil organic matter (SOM) have taken place against the background of spatial and temporal variation is a difficult task. In most cases, sampling over a long period of time is needed to verify these changes. Alternatively, potential changes in the SOM stock can be estimated using humus balancing models, which help to identify the need for humus reproduction on a farm. In general, a humus balance is the difference between the humus demand of cultivated crops and humus supply through crops and organic fertilizers. In this study, the ‘Dynamic Humus Unit Method' within the modelling program REPRO was applied to calculate the humus balance for 29 model‐farms that are representative of most of the agricultural production in Austria. Each model‐farm represents a specific production type (PT) and farming system in a defined region or main production area (MPA). This approach gives an overview of the humus balances at a large scale and allows a general trend in Austria to be estimated. Besides differing between conventional and organic farming systems, specific site conditions can also be selected in the model. The constructed model‐farms belong to different PTs such as “forage production”, “cash crops”, “refinement”, and “permanent crops”. The PT “permanent crops” refers to the cultivation of wine. The cropping system of each PT was analyzed in detail, while livestock keeping was considered only when applicable. Positive humus balances were found for all PTs except for permanent crops. The results ranged from –122 to 890 kg C ha−1 y−1. Regions and farm structure, e.g., forage production compared to cash crop, were found to have a greater influence than the kind of farming system (i.e., organic vs. conventional farming). Comparing the different PTs, forage production had the highest positive humus balances (219 to 890 kg C ha−1 y−1), followed by cash crop (24 to 239 kg C ha−1 y−1), refinement (–64 to 402 kg C ha−1 y−1) and permanent crops (–122 to –38 kg C ha−1 y−1). Regarding the farming system, organic farming led to more humus accumulation than conventional farming due to a higher share of fodder legumes and catch crops and more diverse crop rotations. The results were within the range of available empirical data on SOM change, and it was therefore concluded that the results are reasonable. In general, humus reproduction can be regarded as sufficient for agricultural production.

“…This situation must be considered in organic crop production and must be recognized in decision support and sustainability assessment tools such as SOM balances. A validated model that was originally based on the calculation for FOM demand described here has been presented by Brock et al (2012b).…”

Section: Estimation Of Crop‐specific Demand For Fom Supply In Organmentioning

confidence: 99%

Organic matter returns to soils must be higher under organic compared to conventional farming

Leithold

Hülsbergen

Brock

2014

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The aim of this paper is to discuss the demand of fresh organic matter (FOM) supply to maintain soil organic matter (SOM) levels and productivity of arable soils under organic management. The basic question is whether the different frame conditions in organic vs. conventional farming result in a different and system‐specific FOM demand. If this is the case, it would follow that the farming system has to be considered in the calculation of SOM balances. SOM balances are the most common decision support tools in organic matter management. A conversion to organic farming in practice usually leads to an increase of SOM levels as well as soil microbial activity over time. The system‐specific driver of this effect is the indispensable extension of the share of (perennial) legumes in crop rotations at the expense of non‐legumes such as cereals, row crops, and maize. Extended legume cropping is essential for N supply in crop rotations as the import of N fertilizer in total is limited by organic farming regulations and mineral N fertilizer may not be used at all. Based on this characteristic of organic management, we argue that the demand of FOM supply to soils must be higher than in conventional crop production. The most relevant factors are (1) the non‐existence of mineral N fertilizer as an external N source that supports the maintenance of SOM by decreasing the demand for SOM‐N, (2) benefits of increasing SOM stocks and turnover for soil productivity under organic management, and, (3) increased mass‐losses of FOM and easily degradable SOM compartments due to higher microbial activity in soils. These effects have to be quantified and must be considered in SOM balances in order to avoid misleading assessments and erroneous decisions.