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Exports and inputs of organic carbon on agricultural soils in Germany

Exports and inputs of organic carbon on agricultural soils in Germany Nutr Cycl Agroecosyst (2020) 118:249–271 https://doi.org/10.1007/s10705-020-10087-5(0123456789().,-volV)(0123456789().,-volV) ORIGINAL ARTICLE Exports and inputs of organic carbon on agricultural soils in Germany . . . . Anna Jacobs Christopher Poeplau Christian Weiser Andrea Fahrion-Nitschke Axel Don Received: 16 January 2020 / Accepted: 28 July 2020 / Published online: 8 October 2020 The Author(s) 2020 Abstract The quantity and quality of organic carbon agricultural soils in Central Europe. Mean total NPP (C ) input drive soil C stocks and thus fertility and calculated for arable and grassland soils was 6.9 ± 2.3 org org -1 -1 climate mitigation potential of soils. To estimate and 5.9 ± 2.9 Mg C ha yr , respectively, of org fluxes of C as net primary production (NPP), which approximately half was exported. On average, org exports, and inputs on German arable and grassland total C input calculated did not differ between org -1 -1 soils, we used field management data surveyed within arable (3.7 ± 1.8 Mg ha yr ) and grassland soils -1 -1 the Agricultural Soil Inventory (n = 27.404 cases of (3.7 ± 1.3 Mg ha yr ) but C sources were org sites multiplied by years). Further, we refined the different: Grasslands received 1.4 times more C org concept of yield-based C allocation coefficients and from root material than arable soils and we suggest org delivered a new regionalized method applicable for that this difference in quality rather than quantity drives differences in soil C stocks between land use org systems. On arable soils, side products were exported Electronic supplementary material The online version of in 43% of the site * years. Cover crops were cultivated this article (https://doi.org/10.1007/s10705-020-10087-5) con- in 11% of site * years and contributed on average 3% tains supplementary material, which is available to authorized users. of the mean annual total NPP. Across arable crops, total NPP drove C input (R = 0.47) stronger than org A. Jacobs (&)  C. Poeplau  C. Weiser  2 organic fertilization (R = 0.11). Thus, maximizing A. Fahrion-Nitschke  A. Don plant growth enhances C input to soil. Our results org Thu¨nen Institute of Climate-Smart Agriculture, Bundesallee 65, 38116 Brunswick, Germany are reliable estimates of management related C org e-mail: anna.jacobs@thuenen.de fluxes on agricultural soils in Germany. A. Jacobs Keywords Carbon sequestration  Manure  Net Coordination Unit Soil of Thu¨nen Institute, Bundesallee primary productivity  Carbon balance  Net biome 49, 38116 Brunswick, Germany productivity Present Address: C. Weiser Fachagentur Nachwachsende Rohstoffe e. V, Hofplatz 1, 18276 Gu¨lzow-Pru¨zen, Germany Introduction Present Address: A. Fahrion-Nitschke The content or stock of soil organic carbon (SOC) in Niedersa¨chsische Landesforsten, Forstplanungsamt, agricultural soils is regarded as the key parameter Forstweg 1A, 38302 Wolfenbu¨ttel, Germany 123 250 Nutr Cycl Agroecosyst (2020) 118:249–271 sustaining soil fertility and health. Moreover, the being closely linked to SOC dynamics. The absolute carbon (C) cycle of agricultural systems plays a role in magnitude of the major management-related annual climate change mitigation: since the more C is stored fluxes of C on agricultural soils, i.e. NPP ,C org tot org as organic C (C ) in the soil and the longer it is stored export from the site, and C input from external org org for, the less it contributes to climate change as the sources are generally not well quantified. Estimates of major greenhouse gas CO (Minasny et al. 2017). It is C input to soil, e.g. when modeling SOC dynamics 2 org widely acknowledged that farming practices can within the context of greenhouse gas reporting, are influence SOC levels to a certain extent (Freibauer thus often derived from national or regional agricul- et al. 2004). On field scale, SOC stocks are strongly tural yield statistics (Andren et al. 2008). These correlated with the amount of C input, which is the statistics are than combined with plant-specific harvest org almost exclusive source of SOC (Ka¨tterer et al. 2012). indices and C allocation coefficients which are org However, on a national scale, there are very few data published for the major crops, forages (wheat, barley, available on the amount of C input to agricultural oat, triticale, oil seed rape, grain maize, silage maize, org soils. potato, sugar beet, mustard, some legumes) and The quantity, and also the quality, of organic inputs grasslands (Bolinder et al. 2007, 2015; Gan et al. play an important role in SOC build-up and dynamics. 2009). Manure application rates can be roughly For example, recent studies suggested that root- and estimated from the number of animals reported in a manure-derived C has stronger effects on SOC specific region, while harvest residue management is org stocks than straw-derived C (Ka¨tterer et al. 2011; not given in agricultural yield statistics. However, org Rasse et al. 2005). Both the quantity and quality (e.g. residue management is somewhat important for C org C to nitrogen ratio of organic material) of C input input to soil since some harvest residues are removed org org to soil are controlled by the farmer through the choice from the field, e.g., for bioenergy provision and some of crop rotation, amount and type of mineral and are left in situ. organic fertilizers applied, and harvest residue man- Apart from obvious uncertainties in agricultural agement. The farmer also determines total net primary activity data, another major source of uncertainty is -1 -1 production (NPP ;Mg C ha yr ), the fraction of the use of C allocation coefficients and harvest tot org org NPP that is harvested as the main product, and the indices derived from global reviews. However, C org amount of C ultimately returned to the soil. There allocation coefficients are needed to convert yield data org are five main pathways of C input to agricultural into root- and shoot-derived C input. Keel et al. org org soils, governed by: (1) type and amount of above- (2017) and Riggers et al. (2019) demonstrated that the ground harvest residues if left in the field, stubbles choice of allocation coefficients used for C input org always remaining in the field or mulch if left in the estimation strongly influences the SOC trends mod- field, (2) type and amount of organic fertilizers eled. Region-specific up-to-date allocation coeffi- applied, (3) type and amount of excreta produced by cients and harvest indices are required to minimize grazing animals, (4) cover crops used for green this source of error. So far, region-specific allocation manure, and (5) belowground biomass as dead roots coefficients are not applied for estimates of C input org and rhizodeposition. This implies that agricultural although validated values for, e.g., crop-specific soils have C-sink potential and that implementation of harvest indices are available. certain management practices could help mitigate The specific aims of this study were to climate change (Minasny et al. 2017). (1) establish a sound method for estimation of mean To understand, predict, and report SOC stock annual NPP ,C inputs, and C exports tot org org changes in agricultural systems, information on man- from arable and grassland sites under Central agement and related C fluxes from and to the soil is org European environmental conditions. of critical importance. In addition, knowledge on the (2) quantify and compare mean annual NPP ,C tot org regional distribution of harvest exports and inputs of inputs and C exports across land use systems org C to soil is required for development of climate- org in Germany. smart and sustainable solutions in agriculture. How- (3) determine the spatial distribution of C input org ever, field-specific data are often not available at and its sources in Germany. national scales preventing ‘C management’ from org 123 Nutr Cycl Agroecosyst (2020) 118:249–271 251 Data from the first German Agricultural Soil grassland sites for the evaluation. These values were Inventory were used in the analysis. These comprised multiplied by the site-specific management years, and 10 years of management data, including crop type, thus a total of 19,987 arable site * years and 7417 yield, fertilization practices, harvest residue manage- grassland site * years in the period 2001–2016 were ment, field operations, and other key variables such as evaluated as cases in the present study. If not stated livestock density, for each of 3104 arable and grass- otherwise, results are shown as mean of site * years. land sites surveyed within the Agricultural Soil Inventory. Based on this ‘first-hand’ dataset and on Method’s development: Organic carbon allocation regional harvest indices, we estimated NPP on coefficients for arable crops grown under Central tot arable and grassland sites, total C export via harvest European conditions org of main products, and sources of C input across org Germany. Based on crop-specific harvest indices and on a set of coefficients of C allocation among crop compart- org ments taken from the literature, we derived C org Materials and methods allocation factors specific for cultivation conditions in Central Europe in order to estimate annual C input org -1 -1 Database of agronomic and grassland management (Mg C ha yr ) to soil based on yield information. org The concept of C allocation, as described in detail org The German Agricultural Soil Inventory collected by Bolinder et al. (2007), is based on the assumption samples of soils under agricultural land use in a that the sum of C within all plant compartments org -1 -1 8km 9 8 km grid across Germany (Jacobs et al. equals NPP (Mg C ha yr ) and that all C tot org org 2018) accompanied by collection of arable and allocation factors add up to 1. permanent grassland management data through a For arable crops, we applied the following five, questionnaire sent to the farmers on whose sites soil crop-specific C allocation factors (CA ): org x sampling was performed. Thereby, for the definition of CA þ CA þ CA þ CA þ CA ¼ 1 MP HR ST R RD ‘permanent grassland’ (referred to as ‘grassland’ in the ð1Þ following), we referred to the one used in agricultural practice where a grassland is permanent after five where MP is the main product, HR is the harvest years of continuous grassland use. Farmers were asked residues, ST is stubbles as the part of HR always to record type of crop rotation, fresh matter yield of the remaining in the field, R is dead roots, and RD is main product, harvest residues management regimes, rhizodeposition. cover crops management regimes, and the amount and We calculated the C allocation factors for arable org type of organic fertilizers used. For grassland sites, main products, harvest residues, and stubbles based on farmers were asked to record dry matter yield, number C content, dry matter content, harvest index, and a org of cuts per year, mulching, amount and type of organic stubble index for arable crops obtained in a literature fertilizers used, and number and species of grazing search prioritizing German references (Table 1). The animals. If possible, farmers were supposed to deliver selection criteria for the search were, in descending the respective data on the previous decade of man- order: (1) agricultural management representative of agement, if possible. However, in the present analysis, commercial farming in Germany, (2) factors quotable, we had to exclude some records (site * years) from the and (3) factors consistent with each other. We data set due to incomplete information especially on generally took the mean value when more than one (1) crops and cover crops indicated as ‘unknown’ or value was available. There are generally no data ‘unspecified’ (n = 79 and 247, respectively), (2) data available specifically for cultivars used in organic entries with no information on harvest residues agriculture although it is known that the physiology, management (n = 485), (3) data entries on use of and thus C allocation, of these cultivars differs from org organic fertilizer that did not state the amount or type that of cultivars used in conventional agriculture. In (n = 45), and (4) data entries on pastures with no this study, only 5% of the arable sites evaluated were information on grazing animals or farm’s livestock under organic management and we ignored this (n = 631). This left 2097 arable sites and 718 123 252 Nutr Cycl Agroecosyst (2020) 118:249–271 Table 1 Harvest index (HI = yield of main product/(yield of main pro- suggested to be the same than of HR), index for the amount of HR remaining in the -1 duct ? biomass of harvest residues)), dry matter (DM; (Mg DM Mg fresh field as stubble (stubble index = SI) when HR were exported, and allocation -1 -1 -1 matter )), and organic carbon content (C; (Mg C Mg DM ) of main product coefficients for organic carbon (CA) within crops (R = roots, RD = rhizodeposition) harvested (MP) and aboveground harvest residues (HR) (C of stubbles (ST) was calculated as described in the text Crop DM C C HI SI CA CA CA CA CA Comments, suggestions made MP MP HR MP HR ST R RD -1 -1 -1 (Mg Mg ) (Mg Mg ) (Mg Mg ) 1 3 2,3,4,5,6 1,2 9 9,10,11 Winter wheat 0.86 0.46 0.46 0.55 0.15 0.417 0.284 0.050 0.190 0.059 1 3,5 2,3,4,5,6 1,2 9 9,10 Winter barley 0.86 0.47 0.46 0.57 0.15 0.444 0.279 0.049 0.174 0.054 1 3 2,3,4,5 1,2 9 Spring barley 0.86 0.46 0.46 0.57 0.15 0.422 0.268 0.047 0.200 0.062 CA : mean of all cereals 1 3,5 2,3,4 1 9 Winter rye 0.86 0.47 0.47 0.53 0.15 0.404 0.308 0.054 0.178 0.055 CA : mean of all winter cereals 1 5 2,5 1 9 9 Winter triticale 0.86 0.45 0.46 0.53 0.15 0.421 0.326 0.058 0.149 0.046 1 2,5,6 1 9 9,10 Oat 0.86 0.46 0.45 0.48 0.15 0.312 0.288 0.051 0.267 0.083 C : as spring barley MP Other winter cereals 0.86 0.46 0.46 0.55 0.15 0.423 0.292 0.052 0.178 0.055 mean of all winter cereals 1 9 Other spring cereals 0.86 0.46 0.46 0.57 0.15 0.422 0.268 0.047 0.200 0.062 HI, DM ,C ,C : as spring barley; MP MP HR CA : mean of all cereals 1,2 5 2,6 1,2 9 9,10 Corn, sweet corn 0.86 0.48 0.43 0.50 0.10 0.396 0.315 0.035 0.194 0.060 1,7,8 2,6 9 9 Silage maize, 0.31 0.43 1 0.05 0.772 0 0.039 0.145 0.045 HI = 1 for total biomass harvest sorghum 1,8 5 9 9,10 10 Clover (whole plant) 0.20 0.41 1 0.25 0.455 0 0.114 0.329 0.102 HI = 1 for total biomass harvest; in ref ‘stem’ is equal the MP; CA ,CA : for R RD annual cultivation only, otherwise see text 1 6 1 9,10 Clover (seeds) 0.91 0.47 0.11 0.15 0.063 0.430 0.076 0.329 0.102 C : value for ‘herbaceous and agricultural MP biomass’; SI: as cereals; CA ,CA : for R RD annual cultivation only, otherwise see text 1 6 2,5 1,2 9 9,11 Fodder and 0.86 0.47 0.45 0.47 0.10 0.380 0.321 0.040 0.166 0.052 C = value for ‘herbaceous and MP vegetable legumes agricultural biomass’; CA ,CA : for R RD (grains) annual cultivation only, otherwise see text 1,2 2,4,5,6 9 9,10 Fodder legumes 0.20 0.46 1.00 0.25 0.455 0.000 0.114 0.329 0.102 HI = 1 for total biomass harvest; CA : MP (whole plant) in ‘stem’ is equal the MP; CA ,CA : R RD for annual cultivation only, otherwise see text 1 3 2,3,4,6 1,2 11 Oilseed rape 0.91 0.63 0.47 0.38 0.15 0.320 0.332 0.059 0.222 0.069 SI: as cereals 1 6 6 1 10,12 Potatoes 0.22 0.47 0.47 0.83 0.00 0.798 0.160 0.000 0.033 0.010 C ,C : value for ‘herbaceous and MP HR agricultural biomass’; SI = 0 for root crop harvest 1 5 2,9 17 10,12 Sugar beet 0.23 0.45 0.41 0.81 0.00 0.788 0.169 0.000 0.033 0.010 SI = 0 for root crop harvest 1 5 1,17 Fodder beet 0.12 0.45 0.41 0.76 0.00 0.744 0.221 0.000 0.033 0.010 C ,CA : as sugar beet; SI = 0 for root HR R crop harvest Nutr Cycl Agroecosyst (2020) 118:249–271 253 Table 1 continued Crop DM C C HI SI CA CA CA CA CA Comments, suggestions made MP MP HR MP HR ST R RD -1 -1 -1 (Mg Mg ) (Mg Mg ) (Mg Mg ) 1,8 7 9 9 Grass with legumes 0.20 0.40 1 0.15 0.303 0.000 0.045 0.498 0.154 HI = 1 for total biomass harvest; CA , (whole plant) CA : for annual cultivation only, RD otherwise see text 1 4,5,7 9 9,10 Grass without 0.20 0.45 1 0.15 0.533 0.000 0.080 0.295 0.092 HI = 1 for total biomass harvest; CA : MP legumes (whole in ‘stem’ is equal the MP; CA ,CA : R RD plant) for annual cultivation only, otherwise see text 8 6 6 Strawberries 0.10 0.47 0.47 0.50 0 0.302 0.302 0.000 0.302 0.094 HI = own suggestion; C ,C = value MP HR for ‘herbaceous and agricultural biomass’; SI = 0 for no stubble occurrence; CA : own suggestion as MP 66% of biomass is aboveground with HI = 0.5; CA : own estimation as 33% of biomass is belowground 8 6 Asparagus 0.10 0.47 1 0 0.957 0.000 0.000 0.033 0.010 HI = 1 for total biomass harvest; C : MP value for ‘herbaceous and agricultural biomass’; SI = 0 for root crop harvest; CA : mean of potatoes and sugar beet 7 7 2 13 15,16 White cabbage & 0.13 0.51 0.43 0.60 0 0.450 0.246 0.000 0.232 0.072 SI = 0 for no stubble occurrence; CA : ‘other vegetables’ mean value of turnip rape, fodder cabbage, swede, turnip, fodder radish as ‘vegetable-like’ cover crops 7 7 2 13 15,16 Red cabbage 0.13 0.51 0.43 0.54 0 0.409 0.287 0.000 0.232 0.072 SI = 0 for no stubble occurrence; CA : mean value of turnip rape, fodder cabbage, swede, turnip, fodder radish as ‘vegetable-like’ cover crops 7 7 2 13 15,16 Green cabbage 0.13 0.51 0.43 0.74 0 0.536 0.160 0.000 0.232 0.072 SI = 0 for no stubble occurrence; CA : mean value of turnip rape, fodder cabbage, swede, turnip, fodder radish as ‘vegetable-like’ cover crops 7 7 2 13 15,16 Broccoli 0.13 0.51 0.43 0.56 0 0.421 0.276 0.000 0.232 0.072 SI = 0 for no stubble occurrence; CA : mean value of turnip rape, fodder cabbage, swede, turnip, fodder radish as ‘vegetable-like’ cover crops 7 7 2 13 15,16 Cauliflower 0.13 0.51 0.43 0.63 0 0.468 0.228 0.000 0.232 0.072 SI = 0 for no stubble occurrence; CA : mean value of turnip rape, fodder cabbage, swede, turnip, fodder radish as ‘vegetable-like’ cover crops 254 Nutr Cycl Agroecosyst (2020) 118:249–271 Table 1 continued Crop DM C C HI SI CA CA CA CA CA Comments, suggestions made MP MP HR MP HR ST R RD -1 -1 -1 (Mg Mg ) (Mg Mg ) (Mg Mg ) 7 7 2 13 Carrot 0.13 0.51 0.43 0.86 0 0.842 0.115 0.000 0.033 0.010 SI = 0 for no stubble occurrence; CA : mean of potatoes and sugar beet 7 7 2 13 Beetroot 0.13 0.51 0.43 0.77 0 0.769 0.188 0.000 0.033 0.010 SI = 0 for no stubble occurrence; CA : mean of potatoes and sugar beet 7 7 2 13 Small radish 0.13 0.51 0.43 0.88 0 0.855 0.102 0.000 0.033 0.010 SI = 0 for no stubble occurrence; CA : mean of potatoes and sugar beet 7 7 2 13 13 Radish 0.13 0.51 0.43 0.79 0.779 0.178 0.000 0.033 0.010 SI = 0 for no stubble occurrence; CA : mean of potatoes and sugar beet 7 7 2 13 Onion 0.13 0.51 0.43 0.80 0 0.789 0.168 0.000 0.033 0.010 SI = 0 for no stubble occurrence; CA : mean of potatoes and sugar beet 7 7 2 13 15,16 Celeriac 0.13 0.51 0.43 0.83 0 0.817 0.140 0.000 0.232 0.072 SI = 0 for no stubble occurrence; CA : mean value of turnip rape, fodder cabbage, swede, turnip, fodder radish as ‘vegetable-like’ cover crops 7 7 2 13 15,16 Cucumber 0.13 0.51 0.43 0.72 0 0.522 0.174 0.000 0.232 0.072 SI = 0 for no stubble occurrence; CA : mean value of turnip rape, fodder cabbage, swede, turnip, fodder radish as ‘vegetable-like’ cover crops 7 7 2 13 15,16 Pumpkin 0.13 0.51 0.43 0.67 0 0.490 0.206 0.000 0.232 0.072 SI = 0 for no stubble occurrence; CA : mean value of turnip rape, fodder cabbage, swede, turnip, fodder radish as ‘vegetable-like’ cover crops 7 7 2 13 15,16 Salad 0.13 0.51 0.43 0.82 0 0.585 0.111 0.000 0.232 0.072 SI = 0 for no stubble occurrence; CA : mean value of turnip rape, fodder cabbage, swede, turnip, fodder radish as ‘vegetable-like’ cover crops 7 7 2 13 15,16 Spinach 0.13 0.51 0.43 0.75 0 0.543 0.153 0.000 0.232 0.072 SI = 0 for no stubble occurrence; CA : mean value of turnip rape, fodder cabbage, swede, turnip, fodder radish as ‘vegetable-like’ cover crops Herbs 0.20 0.47 1 0.25 0.483 0.000 0.121 0.302 0.094 HI = 1 for total biomass harvest; DM :as MP grass without legumes; C : value for MP ‘herbaceous and agricultural biomass’; SI: as fodder legumes (whole plant); CA : own suggestion as 66% of MP biomass is aboveground with an HI of 1; CA : own suggestion as 33% of biomass is belowground; CA ,CA : for annual R RD cultivation only, otherwise see text Nutr Cycl Agroecosyst (2020) 118:249–271 255 Table 1 continued Crop DM C C HI SI CA CA CA CA CA Comments, suggestions made MP MP HR MP HR ST R RD -1 -1 -1 (Mg Mg ) (Mg Mg ) (Mg Mg ) Cereal silage (whole 0.35 0.47 1 0.05 0.702 0.000 0.035 0.200 0.062 HI = 1 for total biomass harvest; C :as MP plant) winter rye; SI: as silage maize; CA : mean of all cereals 1 6 4,5,7 1 Grass without 0.86 0.47 0.45 0.11 0.15 0.072 0.460 0.081 0.295 0.092 C = value for ‘herbaceous and MP legumes (seeds) agricultural biomass’; SI: as cereals; CA : as grass without legumes (whole plant); CA ,CA : for annual cultivation R RD only, otherwise see text 1 5 5 1 Sunflower & ‘other’ 0.91 0.52 0.44 0.33 0.15 0.264 0.379 0.067 0.222 0.069 SI: as cereals; CA : as oilseed rape oil crops 1 5 5 1 Linseed 0.91 0.52 0.44 0.40 0.15 0.313 0.337 0.059 0.222 0.069 SI: as cereals; CA : as oilseed rape 6 6 Tobacco 0.20 0.47 0.47 0.67 0.00 0.466 0.230 0.000 0.232 0.072 HI: mean of vegetables; DM : as harvest MP residues of sugar beet; SI = 0 for no stubble occurrence; CA : as aboveground vegetables 1 6 Hemp 0.40 0.47 1 0.05 0.772 0.000 0.039 0.145 0.045 HI = 1 for total biomass harvest; SI, CA : as silage maize Fallow 0.20 0.45 1 0.15 0.533 0.000 0.080 0.295 0.092 As grass without legumes (whole plant); not to be interpreted as bare fallow but as years of non-cultivation during which soil is covered by (volunteer) grass which is not harvested 1 2 3 4 5 6 7 Anonymous (2017), Franko et al. (2011), Obernberger et al. (2006), Nordin (1994), BIOS Bioenergiesysteme GmbH (2018), Vassilev et al. (2010), Rynk et al. (1992), 8 9 10 11 12 13 14 15 Zorn et al. (2007), Bolinder et al. (2007), Li et al. (1997), Gan et al. (2009), Bolinder et al. (2015), Feller et al. (2011), Pausch and Kuzyakov (2018), Nordrhein- 16 17 Westfalen (2015), Kuratorium fu¨r Technik und Bauwesen in der Landwirtschaft (KTBL) (2009), Laufer et al. (2016) 256 Nutr Cycl Agroecosyst (2020) 118:249–271 circumstance and applied the mean values we found to below) although there are recent findings that at least all records. wheat has rather a fixed than a yield-dependent The C allocation factor of the main product NPP (Taghizadeh-Toosi et al. 2016). However, org below (CA ) was calculated as: these results were not proven for the broad spectra of MP arable crops we evaluated here and thus we used the AMP  DM  C MP MP CA ¼ ð2Þ conventional concept of C allocation based on MP org NPP tot findings of Bolinder et al. (2007). where A-MP is the fresh matter yield of the main To derive the C allocation factor for rhizodepo- org -1 -1 product of an arable crop (Mg ha yr ), DM is its sition, we used a recent values published in a review MP -1 dry matter content (Mg Mg ), C is the C content by Pausch and Kuzyakov (2018) who concluded that MP org -1 -1 (Mg Mg dry matter ) (Table 1), and NPP (Mg rhizodeposition is 0.31 * root-C for most arable tot org -1 -1 C ha yr ) was calculated as described below. org crops. The term rhizodeposition as used here is equal The C allocation factor of harvest residues to the net rhizodeposition defined by Pausch and org (CA ) was calculated as: HR Kuzyakov (2018) as the part of C remaining longer org in soil since it is not mineralized by soil organisms DM MP AMP  ðÞ 1  HI C ðÞ 1  SI HR HI CA ¼ immediately after being released into the soil. HR NPP tot ð3Þ Calculation of annual net primary production on arable sites where A-MP is the fresh matter yield of the MP of an -1 -1 arable crop (Mg ha yr ), DM is its dry matter MP -1 For arable crops, calculations of annual NPP (Mg tot content (Mg Mg ), HI is the harvest index, C is the HR -1 -1 -1 C ha yr ) for each site * year was based on the org C content of harvest residues (Mg Mg dry org -1 fresh matter yield of the respective main product, matter ), SI is the stubble index as the proportion which in most cases (79% of site * years evaluated) of HR always remaining in the field as stubbles and was recorded by the farmer. Missing values were therefore supposed to be calculated as a separate replaced as accurately as possible by statistical values compartment of the crop (for crops for which MP is in a three-step procedure: (1) If available, the year- total aboveground biomass harvested, it is a proportion -1 -1 specific yield of the main product at site-specific of MP) (Table 1), and NPP (Mg C ha yr ) was tot org NUTS3 level (Landkreis) was used; (2) otherwise, the calculated as described below. year-specific mean value of the respective Federal The C allocation factor for stubbles (CA ) was org ST State was used; (3) if still not available, a statistical calculated as: mean of Germany was used or a rough estimate was DM MP AMP  ðÞ 1  HI SI  C HR made (Graf et al. 2005; Kuratrorium fu¨r Technik und HI CA ¼ ð4Þ ST NPP tot Bauwesen in der Landwirtschaft (KTBL) 2009; Landwirtschaftskammer Niedersachsen 2007, 2014, where A-MP is the fresh matter yield of the main -1 -1 Statistisches Bundesamt (Destatis) 2003–2018, Tech- product of an arable crop (Mg ha yr ), DM is its MP -1 nologie- und Fo¨rderzentrum (TFZ) im Kompetenzzen- dry matter content (Mg Mg ), HI is the harvest trum Nachwachsende Rohstoffe 2007). The statistical index, C is the C content of the harvest residues HR org -1 -1 values of yield of the main product were adjusted to (Mg Mg dry matter ), SI is the stubble index the yield level of the specific farm: For each farm and assuming that stubbles have the same C content as org -1 -1 crop, a ‘recorded:statistical’ factor was calculated harvest residues (Table 1); NPP (Mg C ha yr ) tot org when the respective yield was recorded at least for 2 was calculated as described below. years; otherwise, the factor was calculated as the mean To develop the C allocation factor for roots, we org factor across all crops recorded. If no records were used crop-specific constant ratios of aboveground NPP available, no adjustment was made. (NPP ) to belowground NPP (NPP ) allocation above below If a record indicated that an arable crop was not empirically derived from different studies following harvested and all biomass was tilled into the soil, as the general concept of C allocation (Table 1). We org done for fallow (unharvested grass; 3% of the site * applied the NPP : NPP ratio to NPP (see above below above years evaluated) or after extreme weather events 123 Nutr Cycl Agroecosyst (2020) 118:249–271 257 (0.3% of the site * years evaluated), the yield of the ANPP ¼ðÞ AMP  DM  C above MP MP main product was set as zero. However, in further MP þ AMP  DM   CA MP HR calculations, e.g. NPP , we needed an equivalent to above CA MP the potential yield and estimated it as being about 50% MP þ AMP  DM   CA MP ST of a default fresh matter yield (own suggestions as a CA MP rough estimate based on Graf et al. 2005; Kuratrorium ð6Þ fur Technik und Bauwesen in der Landwirtschaft (KTBL) 2009; Landwirtschaftskammer Niedersach- MP ANPP ¼ AMP  DM   CA below MP R sen 2007, 2014; Statistisches Bundesamt (Destatis) CA MP 2003–2018; Technologie- und Fo¨rderzentrum (TFZ) MP þ AMP  DM   CA MP RD im Kompetenzzentrum Nachwachsende Rohstoffe CA MP -1 2007): fallow: 15 Mg fresh matter ha , grass: ð7Þ -1 15 Mg fresh matter ha , winter rye: 2.5 Mg fresh -1 matter ha , clover (whole plant): 17.5 Mg fresh where A-MP is the fresh matter yield of the main -1 -1 -1 matter ha , grass with legumes (whole plant): product of an arable crop (Mg ha yr ), DM is its MP -1 -1 17.5 Mg fresh matter ha , fodder legumes (whole dry matter content (Mg Mg ), C is its C content MP org -1 -1 -1 plant): 17.5 Mg fresh matter ha , winter wheat: 4 Mg (Mg Mg dry matter ), CA is the C allocation MP org -1 fresh matter ha , fodder legumes (grains): 1.5 Mg factor of the main product, CA is the C allocation HR org -1 fresh matter ha , grass without legumes (grains): 0.5 factor of the harvest residues, CA is the C ST org -1 fresh matter Mg ha , winter oilseed rape: 18 Mg allocation factor of the stubbles, C is the C AR org -1 fresh matter ha . allocation factor of the roots, and CA is the C RD org On arable sites, NPP comprised all aboveground allocation factor of the rhizodeposition (Table 1). tot and belowground biomass compartments of the main crop and the cover crop. For perennial cultivation of Calculation of annual net primary production grass, legumes, and herbs, NPP was calculated as of grassland sites below for permanent grasslands (see below) except in the last -1 -1 year of the cultivation period. For cover crops, yield For grassland sites, annual NPP (Mg C ha yr ) tot org and belowground biomass were not recorded, and was again based on the ‘yield’, which was also were thus estimated based on a literature search and a recorded in the questionnaire. Three different types of -1 -1 default C content of 0.47 Mg Mg dry matter grassland were distinguished and we developed org (‘herbaceous and agricultural biomass’ in Vassilev specific approaches to fill gaps in yield data and to et al. (2010)) to obtain NPP and NPP for estimate NPP for these grassland types: meadows above below above cover crops (Table S1). Rhizodeposition by cover (grassland mown), pastures (grassland grazed) and crops was set at 0.31 * root-C (Pausch and mown pastures (grassland grazed and mown). org Kuzyakov 2018). Missing yield data for meadows (42% of site * -1 -1 The annual NPP (Mg C ha yr ) on arable years recorded) were replaced with statistical values, tot org sites (A-NPP ) was calculated as the sum of NPP in the same way as for arable crops, to derive the tot above and NPP of the main product and the cover crop amount of biomass exported. However, for meadows, below (CC-) (Eq. 5). For A-NPP and A-NPP ,C the average values obtained from NUTS3 statistics did above below org allocation factors were applied to the fresh matter not distinguish between different management inten- yield (Eqs. 6, 7).: sities. The biomass exported from meadows is corre- lated to the number of cuts per year which is also an ANPP ¼ ANPP þ ANPP tot above below indicator for management intensity. Wendland et al. þ CCNPP þ CCNPP ð5Þ above below (2018), representing the agricultural extension service in Bavaria, published a linear relationship (y = 16.2 ? 25; R = 0.99) for intensively managed meadows for the use of official fertilization recom- mendations. Based on these long term experiences, we 123 258 Nutr Cycl Agroecosyst (2020) 118:249–271 adjusted the statistical values as follows: We assumed The calculation of annual NPP on grassland above -1 -1 that the statistical grassland yield values reflect a sites (G-NPP ;Mg C ha yr ) was the sum of above org common number of cuts, which we set equal to the all grassland biomass grown on the site (for exact country-wide average number of cuts (2.66) recorded calculation, see Table S4): in the Agricultural Soil Inventory database. We then GNPP ¼ GMP þ GMP þ MU  1:215 above up adjusted the statistical grassland main product by the 0:45 number of cuts recorded using specific factors ð8Þ (Table S2), based on a linear relationship between yield and number of cuts derived from field observa- where G-MP is the dry matter yield of the main -1 -1 tion (Wendland et al. 2018). Thus, for meadows with product of the grassland site (Mg ha yr ), G-MP up two or fewer cuts, we reduced the statistical yield, -1 -1 is the biomass taken up by animals (Mg ha yr ), -1 -1 while for meadows with of three or more cuts we MU is the biomass mulched (Mg ha yr ), the increased it. factor 1.215 represents the part of biomass that grows For pastures, yield data recorded were assumed to each year after the last cut or before/after grazing be an estimate of total uptake by grazing animals, period of animals which is about 30% of the biomass which we refer to as grassland main product taken-up. measured as G-MP or G-MP or MU (Christensen up When no yield for pastures was recorded, biomass et al. 2009) and of which 50% decays within the year uptake was calculated from recorded livestock units evaluated (Poeplau 2016), and 0.45 is the C content org -1 -1 grazing on the site and mean biomass uptake values for (Mg Mg dry matter ) of the aboveground biomass all cattle specimen used in the German National (Bolinder et al. 2007). Inventory Report (Ro¨semann et al. 2017). This was the Grassland specimen were lately proven to be case for 23% of all site * years recorded for pastures. extremely variable in the ratio of NPP to NPP above be- Missing data on livestock units grazing were replaced (also known as ‘root:shoot ratio’) with increasing low by dividing the number, species, and days of animals values due to management intensity, especially due to grazing recorded for the entire farm by the total fertilization (Ammann et al. 2009; Cong et al. 2019; pasture area recorded for the farm. This was the case Poeplau 2016; Sochorova et al. 2016). Meanwhile, the for 71% of all site * years recorded for pastures. The studies cited showed that belowground biomass of major assumption in this approach was that grazing grassland specimen was rather unaffected by manage- animals were equally distributed over the total pasture ment. In accordance to that, an earlier study (Poeplau area of the farm. Default values used to calculate et al. 2018), in which seven different long-term species-specific grassland main product taken up are fertilized grassland experiments in Germany were given in Table S3. sampled, we statistically proved that NPP was below For mown pastures, the yield recorded was divided unaffected by fertilization and site. The average root- into main product yield and biomass taken up in the C stock to a depth of 100 cm in that study was org -1 following way and as a rough approximation (for 3.38 ± 1.15 Mg C ha . Within the dataset used for org details, see Table S4): If one cut was performed, it the present study, the entire range of fertilization accounted for 25% of the total yield, two cuts intensity was represented and the application of C org accounted for 50%, and more than two cuts accounted allocation as a ratio of NPP to NPP would above below for 75% of the yield, while the rest was assigned to have caused large errors. Thus, we made use of our biomass taken up. When the yield was not recorded for data published in Poeplau et al. (2018) and established mown pastures, we calculated the biomass taken up as a fixed and yield-independent value to estimate described for pastures and multiplied the number of NPP as it appeared advisable according to latest below -1 cuts recorded by 1.7 Mg dry matter ha as the best publications. Based on the root-C stock of 3.38 Mg org -1 estimate of yield, based on the equation given above. C ha found by Poeplau et al. (2018), we assumed org This was the case for 38% of the records evaluated for an average annual root turnover of 50% (Gill and pastures. Jackson 2000) and an additional 31% of annual root- If not stated otherwise, we assumed that a record C produced being allocated belowground as rhi- org indicating mulching was one cut of 1.7 Mg dry matter zodeposition (Pausch and Kuzyakov 2018). The -1 ha remaining in the field. 123 Nutr Cycl Agroecosyst (2020) 118:249–271 259 grassland’s NPP was thus fixed to 2.2 Mg C NPP is the NPP of the cover crop (Mg C below org above above org -1 -1 -1 -1 ha yr , assuming that the assessment of root ha yr ), and 0.75 is the factor for the part of CC- biomass to a depth of 100 cm approximately captured biomass exported. the total root biomass. For grassland sites, the total annual C export (G- org -1 -1 EX ;Mg C ha yr ) occurs via the yield as the tot org Calculation of annual carbon export from arable main product on meadows and mown pastures, and via land and grassland biomass uptake as the main product on pastures and mown pastures. It was calculated as: -1 For arable sites, total annual C export (Mg C ha org org GEX ¼ GMP þ GMP  0:45 ð13Þ -1 tot up yr ) occurs via the main product harvested, harvest residues when exported as side products, and cover where G-MP is the dry matter yield of the main -1 -1 crops when harvested for fodder or energy use. If a product of the grassland site (Mg ha yr ), G-MP up -1 -1 record indicated that a main product was not harvested is the biomass taken up by animals (Mg ha yr ), -1 -1 and all biomass was tilled into the soil, as done for 0.45 is the C content (Mg Mg dry matter )of org fallow (grass unharvested) or after extreme weather aboveground biomass (Bolinder et al. 2007). events, C export was set to zero. Information on org whether harvest residues and/or cover crops were Calculation of plant-derived annual carbon inputs exported from the field was retrieved from the farmer on arable and grassland soils questionnaire. If the use of a cover crop was not recorded, it was assumed here that its biomass was not On arable sites, the plant-derived annual C input to org -1 -1 exported, since this is estimated to be applied soil (Mg C ha yr ) occurs via harvest residues if org in [ 80% of cases. left in the field (as recorded in the questionnaire), Total annual C export from arable sites (A-EX ; org tot stubbles which always remain in the field, roots, -1 -1 Mg C ha yr ) was calculated as the sum of C org org rhizodeposition, and cover crops. For this study, it was export via main product, harvest residues and cover not differentiated in which soil depth the C was org crops (CC-) harvested (Eq. 9). For export via main incorporated by tillage since the focus was rather on product and harvest residues, C allocation factors org the amount of C left on the site. If a cover crop was org were applied to NPP of the arable site (Eqs. 10, 11). tot recorded as being exported, it was assumed that 25% For cover crops which were exported from the site it of its NPP was left in the field as stubbles above was suggested that export accounts for 75% of the (Bolinder et al. 2007). biomass only (Bolinder et al. 2007) (Eq. 12). The total C input to arable soils (A-IN ;Mg C org tot org -1 -1 ha yr ) was calculated as (although sources of AEX ¼ AEX þ AEX þ CCEX ð9Þ tot MP HR plant-derived C input are shown separately): org AEX ¼ ANPP  CA ð10Þ MP tot MP AIN ¼ðÞ ANPP  AEX ð14Þ tot tot tot AEX ¼ ANPP  CA ð11Þ where A-NPP is the NPP of the arable site (Mg HR tot HR tot tot -1 -1 C ha yr ) and A-EX is the C export from the org tot org -1 -1 CCEX ¼ CCNPP  0:75 ð12Þ above site (Mg C ha yr ). org On grassland sites, the plant-derived annual C org where A-EX is the C export via the arable main MP org -1 -1 input to soil occurs via mulch, decaying aboveground, crop (Mg C ha yr ), A-EX is the C export org HR org -1 and belowground residues of the main product. of the harvest residues as side products (Mg C ha org -1 Decaying aboveground residues were suggested to yr ), CC-EX is the C export via the cover crop org -1 -1 comprise 50% of the biomass produced that was not harvested (Mg C ha yr ), A-NPP is the NPP org tot tot -1 -1 harvested or grazed (Poeplau 2016). The C input org of the arable site (Mg C ha yr ), CA is the org MP from decaying belowground residues (roots and C allocation factor of the main product, CA is the org HR rhizodeposition) was equal to NPP (2.2 Mg C below org C allocation factor of the harvest residue, CC- org -1 -1 ha yr ). This was based on the notion that in a 123 260 Nutr Cycl Agroecosyst (2020) 118:249–271 mature permanent grassland, annual root biomass where FER is the dry matter amount of grazing an growth and turnover are in a steady state. -1 -1 animals excreta (Mg ha yr ) and C is its C FER org The annual C input to grassland soils (G-IN ; -1 -1 org tot content (Mg Mg dry matter ; Table S5). -1 -1 Mg C ha yr ) was calculated as: org GIN ¼½ MU  0:45þ ½ðGNPP tot above ð15Þ Results GEX ðÞ MU  0:45Þ 0:5þ 2:22 tot where MU is the dry matter biomass mulched Net primary production on and export of organic -1 -1 -1 (Mg ha yr ), 0.45 is the C content (Mg Mg carbon from arable and grassland sites org -1 dry matter ) of aboveground biomass (Bolinder et al. 2007), G-NPP is the NPP of the grassland site The majority of crops cultivated on German arable above above -1 -1 (Mg C ha yr ), G-EX is the C export from soils between 2001 and 2015 were winter wheat, silage org tot org -1 -1 the grassland site (Mg C ha yr ), 0.5 is the factor maize, oil seed rape, and winter barley which were org respecting the 50% biomass decaying (see above), and cultivated in 65% of all arable site * years evaluated -1 -1 2.22 Mg C ha yr is the C input from (Table 2). Carbon fixation as mean annual NPP by org org tot decaying belowground residues (see above). main crops and cover crops on arable sites was -1 -1 6.9 ± 2.3 Mg C ha yr (Fig. 1). The values of org Calculation of annual carbon inputs via organic the main crops’ NPP and NPP were specific above below fertilizers and grazing animal excreta for each crop type (Table 2). On average, 74.9 ± 9.7% of NPP on arable sites was in above- tot For arable and grassland sites, the annual C input ground biomass while 25.1 ± 9.7% was allocated to org -1 -1 via organic fertilizers (FER -IN; Mg C ha yr ) roots and rhizodeposition of main crops and cover org org was calculated according to information recorded in crops. Cover crops contributed 3 ± 10% of NPP and tot the questionnaire: were grown in 11% of all arable site * years evaluated. They were most often cultivated after cereals (winter FER IN ¼ FER  DM  C ð16Þ org org FER FER barley, summer barley, winter triticale, winter rye, where FER is the fresh matter amount of the specific winter wheat) or were associated with silage maize org -1 -1 organic fertilizer applied (Mg ha yr ) where a cultivation. In this group of main crops, cover crops -3 density of 1 Mg m was assumed for all liquid were grown on an average of 16% of all site * years organic fertilizers, DM is its dry matter content evaluated (Table S6). Mean annual total C export FER org -1 -1 (Mg Mg ), CF is its C content (Mg Mg dry from arable sites via harvest of main product, harvest FER org -1 matter ) which both were obtained in a broad residues exported as side product and cover crops was -1 -1 literature search (Table S5). 3.7 ± 1.8 Mg C ha yr (Table 2, Fig. 1), of org -1 -1 To estimate the annual C input to soil from which 0.4 ± 0.8 Mg C ha yr was in side org org animal excreta on pastures and mown pastures, the products, such as straw. Harvest residues were number and species of animals on the site were exported as side product in 43% of all arable site * multiplied by excretion rates expected for species, as years evaluated (Table S6). estimated by Rosemann et al. (2017) (Table S3). When On grasslands, mean annual NPP was tot -1 -1 the respective information was not recorded, missing 5.9 ± 2.9 Mg C ha yr , which was on average org data were replaced by dividing the number and species lower than on arable sites (Fig. 1). However, NPP below of animals grazing on the entire farm (as given in all of grassland sites, which was estimated with a fixed -1 -1 cases) by the amount of grassland grazed on the farm. value of 2.2 Mg C ha yr , contributed to a larger org The annual C input to the soil via grazing animals share (average 43 ± 14% of NPP ) to NPP than on org tot tot -1 -1 excreta (FER -IN; Mg C ha yr ) was calcu- arable sites. Mean annual C export was ani org org -1 -1 lated as: 3.0 ± 2.3 Mg C ha yr (Fig. 1) of which org -1 -1 1.9 ± 1.4 Mg C ha yr was via cutting of org FER  IN ¼ FER  C ð17Þ ani ani FER meadows and mown pastures and 1.1 ± 2.2 Mg C org -1 -1 ha yr was taken up by grazing animals. Meadows 123 Nutr Cycl Agroecosyst (2020) 118:249–271 261 Table 2 Share of main crops cultivated of annual fluxes of input; values are the mean and standard deviation (SD) -1 -1 organic carbon (C ;Mg C ha yr ) as net primary calculated from the multiplication of sites and years (site * org org production (NPP) for main crops (total and belowground) and years) recorded within the German Agricultural Soil Inventory cover crops, C export via main product and via harvest and are given for crops with a minimum share of 1% across all org residues exported as side products, and plant-derived C records org Crop Share of NPP C export C input org org site * years Main crop Main crop Cover crop Main Side Fertilizer Total (%) (NPP ) (NPP ) product product total belowground Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Arable Winter wheat 26.4 7.2 1.4 1.8 0.4 0.3 0.9 3 0.6 0.8 1.0 0.3 0.7 4 1.6 Silage maize 14.1 7.7 1.7 1.5 0.3 0.3 1 5.9 1.3 0 0 1.2 1 3.2 1.4 Oil seed rape 12.2 6.8 1.5 2.0 0.4 0.1 0.4 2.2 0.5 0.1 0.3 0.3 0.6 4.9 1.3 Winter barley 11.9 6.1 1.3 1.4 0.3 0.6 1.1 2.7 0.6 0.8 0.9 0.4 0.8 3.5 1.6 Winter rye 5.9 4.7 1.8 1.1 0.4 0.4 1 1.9 0.7 0.8 0.8 0.3 0.7 2.7 1.6 Summer barley 4 4.8 1.1 1.3 0.3 0.5 1.1 2 0.5 0.5 0.6 0.3 0.6 3 1.4 Sugar beet 3.9 8.7 1.6 0.4 0.1 0.2 0.7 6.9 1.3 0 0.1 0.6 1.4 2.6 1.6 Grain maize 3.7 10.4 2.7 2.7 0.7 0.1 0.4 4.1 1.1 0.1 0.7 0.5 0.7 6.8 1.8 Winter triticale 3.3 5.5 1.5 1.1 0.3 0.5 1.1 2.3 0.6 1 0.9 0.4 0.6 3.2 1.7 Fallow 3 3.6 0.4 2.1 0.4 0 0.2 1.3 0 0 0 0 0 3.7 0.4 Potato 2.2 5.4 1.3 0.2 0.1 0.2 0.8 4.3 1 0 0 0.4 0.7 1.7 1.1 Grass without 1.4 5.7 2.2 2.5 0.6 0.1 0.5 3 1.5 0 0 0.7 0.8 3.4 1.3 legumes (whole plant) Summer oat 1.4 5.8 1.8 2.0 0.6 0.2 0.8 1.8 0.6 0.9 0.9 0.5 0.8 3.8 1.6 Grain legumes 1.1 3.5 1.8 0.7 0.4 0.3 0.8 1.3 0.7 0 0.1 0.2 0.7 2.6 1.6 Grass with 1.1 5.3 2.1 2.6 1.3 0.1 0.4 2.3 1.1 0 0 0.7 0.9 3.7 1.7 legumes (whole plant) Other crops 4.3 4.9 1.8 1.8 0.7 0.3 0.7 2.3 0.9 0.2 0.3 0.4 0.6 3.2 1.3 Average 6.6 2.1 1.6 0.4 0.3 0.9 3.2 1.7 1.1 1.1 0.5 0.8 3.7 1.8 Grassland Meadow 44.5 5.6 1.4 – – 2.8 1.2 0.0 0.0 0.7 0.9 3.5 1.0 Mown pasture 40.3 6.4 3.3 – – 3.4 2.7 0.0 0.0 1.0 1.0 4.0 1.4 Pasture 15.2 5.6 4.3 – – 2.7 3.5 0.0 0.0 0.7 0.8 3.5 1.5 Average 5.9 2.9 – – 3.0 2.4 0.0 0.0 0.8 1.0 3.7 1.3 ‘Fallow’ is not to be interpreted as bare fallow but as years of non-cultivation during which soil is covered by (volunteer) grass which is not harvested mown up to six times per year were the prevailing Carbon inputs to agricultural soils management type on grasslands (44% of all grassland Total mean annual C input to soils did not differ site * years evaluated), while pastures used only for org -1 -1 grazing represented 15% of all grassland site * years between arable (3.7 ± 1.8 Mg C ha yr ) and org -1 -1 grassland sites (3.7 ± 1.3 Mg C ha yr ) evaluated (Table 2). org (Fig. 2). Across all arable crops, NPP (R = 0.47), tot rather than C input via organic fertilizer (R = 0.11) org 123 262 Nutr Cycl Agroecosyst (2020) 118:249–271 Export or C export (R = 0.03), was the main driver of total org via C input to the soil (Figure S1). org harvest Organic The largest proportion (83 ± 23%; 3.0 ± 1.5 Mg -1 -1 C ha yr ; Fig. 2) of total mean annual C input org org to arable soils was via above- and belowground plant Net primary Input material of the main crop with 1.6 ± 0.7 Mg C org -1 -1 into soil ha yr from roots and rhizodeposition, -1 -1 0.3 ± 0.1 Mg C ha yr from stubbles, and org -1 -1 1.1 ± 1.1 Mg C ha yr from harvest residues 0.5 org Arable land 3.7 left in the field. Cover crops accounted for 5 ± 15% of the total mean annual C input to soil with on average org Main crops 6.6 -1 -1 0.3 ± 0.8 Mg C ha yr . Organic fertilizers org 3.7 accounted for 12 ± 18% of the total mean annual Cover crops 0.3 -1 C input to arable soils with 0.5 ± 0.8 Mg C ha org org -1 yr . They were applied on 71% of all arable sites and 0.8 Grassland 3.0 in 43% of all site * years evaluated and derived mainly (94%) from animals (including biogas digestates). 5.9 Among arable crops, the highest average C input org 3.7 was found for grain maize cultivation, due to very high -1 -1 average NPP (10.4 ± 2.7 Mg C ha yr ) and a tot org -1 -1 Fig. 1 Mean fluxes of organic carbon (C ,MgC ha yr ) org org low portion of C export via harvest (40%, Table 2). org on agricultural soils in Germany calculated for the multiplica- The lowest C input (lower quantile = 1%) was org tion of sites and years recorded within the German Agricultural -1 found for potato cultivation (1.1 ± 0.3 Mg C ha org Soil Inventory (arable: n = 19,987; grassland: n = 7417); for -1 grassland soils, harvest includes biomass uptake of animals and yr ) mainly due to its high harvest index of 0.83. Sites -1 -1 fertilizers include excreta of animals with very high C input ([ 7.6 Mg C ha yr ) org org (upper quantile = 99%) had a regular cover crop cultivation and/or were fertilized with compost and/or manure. As found for arable soils, the largest proportion of total mean annual C input to grassland soils was org again via plant biomass (83 ± 15% or 2.9 ± 0.5 Mg -1 -1 C ha yr ) (Fig. 2) of which the fixed value of org -1 -1 2.2 Mg C ha yr deriving from roots and org rhizodeposition had the largest share. The remaining -1 -1 0.7 ± 0.5 Mg C ha yr derived from above- org ground residues and mulching. Mulching of grassland was recorded for 2% of all grassland site * years evaluated. Organic fertilizers accounted for 17 ± 15% of total mean annual C input to grassland org -1 -1 soils with 0.8 ± 1.0 Mg C ha yr . They were org distributed on 81% of grassland sites and in 45% of all grassland site * years evaluated. This high number reflects the fact that excreta from grazing animals were considered here as organic fertilizers. Meadows Fig. 2 Sources of mean annual input of organic carbon (C )to org arable and grassland soils calculated for the multiplication of received organic fertilizers in 51% of all grassland sites and years recorded within the German Agricultural Soil site * years evaluated. There were only two cases Inventory; mean value and standard deviation. C input via org where organic fertilizers did not derive from animals roots and rhizodeposition in grassland estimated as a fixed value -1 -1 (sewage sludge, potato processing sludge). Sites with (see text for details) of 2.2 Mg ha yr and therefore shown -1 -1 without standard deviation low C input (\ 2.3 Mg C ha yr ) (lower org org 123 Nutr Cycl Agroecosyst (2020) 118:249–271 263 Fig. 3 a Annual total net primary production, organic carbon (C ) export, and total C input, and b C input via cover crops and organic fertilizers of org org org animals’ origin to arable (n = 2097) and grassland (n = 718) soils in Germany, calculated as mean value of sites sampled within the German Agricultural Soil Inventory 264 Nutr Cycl Agroecosyst (2020) 118:249–271 Fig. 3 continued Nutr Cycl Agroecosyst (2020) 118:249–271 265 Fig. 4 Spatial distribution of crop cultivation on arable land in Germany, shown as proportion of the specific crop in the crop rotation, calculated for sites sampled within the German Agricultural Soil Inventory 266 Nutr Cycl Agroecosyst (2020) 118:249–271 quantile = 1%) were characterized by low yield level NPP was still visible in the map showing the spatial tot and no organic fertilization. Sites with a high C distribution of C input (Fig. 3a), confirming NPP org org tot -1 -1 input ([ 7.6 Mg C ha yr ) (upper quan- as a strong driver for C input. org org tile = 99%) were pastures with high animal grazing density or received a large amount of organic fertilizer and/or had a high yield level expressed as high number Discussion of cuts per year. More than half of carbon assimilated is exported from Spatial distribution of net primary production German agricultural soils and inputs and exports of organic carbon Based on our method, mean annual NPP on tot arable sites in Germany was estimated 6.9 Mg C org -1 -1 The highest NPP and C export values were ha yr and was slightly higher than on grasslands tot org -1 -1 obtained for north-west and south-east Germany (5.9 Mg C ha yr ) despite the fact that grass- org (Fig. 3a). Figure 4 shows the spatial distribution of lands are characterized by permanent vegetation the crops most often cultivated, i.e., winter wheat, cover and, thus, potentially maximized C-assimila- silage maize, oilseed rape, sugar beet, grain maize, and tion. This is well in line with global estimates of other winter cereals. Each of the crops is preferentially NPP . Using the earth surface model LPJ, Haberl tot grown in certain areas, which partly explains the et al. (2007) estimated mean annual global NPP of tot -1 -1 spatial pattern of NPP found in this study. In 6.1 Mg C ha yr on arable land and 4.9 Mg tot org -1 -1 particular, the distribution of silage maize cultivation C ha yr on grazing land. The higher values we org explains the high values of NPP and C export in obtained in the present study might be due to tot org north-west and south-east Germany. The C input intensive management regime in German agriculture org from cover crops was also highest in these areas and to generally fertile and relatively young soils. (Fig. 3b), most likely driven by high precipitation Management, e.g. fertilization, and differences in (mean annual precipitation of, e.g., 910 mm in pedoclimatic site properties are the most important Bavaria in contrast to the German average of drivers for the differences in NPP between arable tot 771 mm; mean values of 1881–2019 of Deutscher land and grassland. Grasslands in Germany are Wetterdienst 2020) and the specific crop rotation characterized by a range of management intensities, (maize-dominated). North-west and south-east Ger- from unmanaged to intensively managed, whereas many are also areas of high livestock density, arable sites are mostly intensively managed and explaining the high amounts of C input via organic fertilized. Further, a large proportion of permanent org fertilizers (Fig. 3b). Regions with the most fertile grasslands in Germany are established in conditions soils, such as the young moraine soils of north-east that do not favor cultivation of arable crops, e.g., on Germany and the central German chernosem area, wet soils in floodplains, shallow and stony soils, and were dominated by the cultivation of winter wheat and colder mountainous regions. oilseed rape. In these regions, the major source of C On average, 53% of the NPP on arable sites was org tot input to soil was harvest residues left in the field. In the found to be exported each year. Of this exported C org central German chernosem area in particular, but also portion, 11% was in harvest residues which were in large parts of eastern Germany, cover crops did not exported as side products. This fact was strongly crop- play any role in the crop rotation. This can be dependent: Aboveground biomass of crops dedicated explained by the lower annual precipitation, e.g., with for forage or energy production, e.g. silage maize, an average of 566 mm and 600 mm in Brandenburg does not deliver any side products, while harvest and Mecklenburg-Western Pomerania (mean values of residues of cash crops other than cereals, such as 1881–2019 of Deutscher Wetterdienst 2020). More- oilseed rape, sugar beet or potatoes, are completely left over, crop rotations in those areas are winter crop- on the site (Table S6). Among all cereals, 40% of all dominated. arable site * years evaluated, which is equivalent to Finally, C input was more regionally variable 42% of all cereal straw biomass (not shown), was org and site-specific than C assimilation by plants, recorded with an export of straw as side product. This estimated here as NPP . However, the pattern of value is somewhat larger than the 27–38% estimated tot 123 Nutr Cycl Agroecosyst (2020) 118:249–271 267 in a review on biomass potentials in Germany by soils (Hu et al. 2019) on the other hand. However, the Brosowski et al. (2016). Of the C portion exported, type of C serving as C input varies considerably org org org only 15% ended up in organic fertilizers returned to between the two land use systems. The C input to org arable soils as C input. This is comparable to other grassland soils was dominated by root-derived C org org estimates for Europe showing 47% of NPP being and the proportion was on average 1.4 times higher in tot exported via harvest of arable crops and 10% of NPP the grassland than in the arable soils. This is in line tot being returned as organic fertilizers (Schulze et al. with Pausch and Kuzyakov (2018) who reported that 2009). German grasslands are characterized by high annual crops allocate less C belowground (21%) org productivity and a relatively high portion of NPP than grassland specimen (33%). However, it needs to tot being exported (51%). At European scale, it was be noted that we used a fixed value for root-derived estimated that only 37% of grassland NPP is exported C in grasslands (see below). Root-derived C was tot org org via harvest (Schulze et al. 2009), which underlines the reported to contribute more to SOC stabilization as high intensity of German grassland usage. Of the C shoot-derived C for various reasons including org org portion exported, 27% ended up in organic fertilizers higher chemical recalcitrance, physical protection by (including animal excreta) returned to grassland soils as aggregates (Rasse et al. 2005 and papers cited therein) aC input. On a global scale, Haberl et al. (2007) and microbial C-use efficiency (Sokol and Bradford org estimated that the proportion of NPP harvested was 2019). For example, Ka¨tterer et al. (2011) reported a tot 83% on arable land and 19% on grazing land. This 2.3 times higher stabilization rate of roots compared indicates that C export via harvest is subject to with shoots in a Swedish long-term field experiment. org uncertainties and strongly region-specific. Further, in our study, C input to soil via organic org Total organic carbon inputs into soils do not differ fertilizers (mainly animal manure) was 1.6 times between land use systems higher on grassland than on arable sites. Manure was The C input to arable soils estimated by our also reported to build up SOC at a higher rate than org -1 -1 method was slightly higher (3.7 Mg ha yr ) than fresh aboveground harvest residues, e.g. straw, estimated for Swedish arable soils: Andren et al. (Katterer et al. 2011) since the labile C fraction is org (2008) estimated C inputs in a range of 3.3 Mg C preferentially decomposed and already lost during gut org org -1 -1 -1 ha yr in the south of Sweden to 2.6 Mg C ha passage and storage of manure. Straw was found to org -1 yr in the north. Considering the climate advantages have a retention rate of about 10% or less (Lemke et al. for crop cultivation in Germany compared to Sweden, 2010), while manure often reached retention rates of C inputs estimated in the present study were up to 30% (Ka¨tterer et al. 2011) with a global average org comprehensible. Across arable crops, we found that of 12% (Maillard and Angers 2014). C input to soil was strongly driven by NPP , while An adapted method for estimation of organic org tot neither input as organic fertilizer nor C export carbon inputs to soils in Central Europe org correlated with C input. Thus, in the context of The C input estimation method we developed is a org org increasing SOC stocks for climate change mitigation, revised version of allocation coefficients previously maximizing NPP , e.g., by cover crop cultivation, has published (Bolinder et al. 2007; Gan et al. 2009;Li tot a considerable potential to increase C input to soils. et al. 1997) adapted to regional conditions. For arable org We found no difference between mean annual C sites, we used regional harvest indices and the latest org -1 -1 input to arable soils (3.7 Mg C ha yr ) and to findings on rhizodeposition (Pausch and Kuzyakov org -1 -1 grassland soils (3.7 Mg C ha yr ). This was 2018). However, recent studies claim that appyling org surprising, since SOC stock measured in the top yield-dependent ratios of NPP to NPP in C above below org 0–30 cm layer on the sites evaluated here was on input estimation methods might be an average 1.4 times higher in mineral soils under oversimplification. -1 grassland (89 ± 36 Mg C ha ) than under arable Such findings were clear and reliable for grassland org -1 use (62 ± 30 Mg C ha ; for details see Jacobs specimen for which several independent studies org et al. 2018). This difference was often explained by the showed that NPP is not a function of NPP below above reduced physical disturbance (tillage) of grassland in managed grasslands (Ammann et al. 2009; Cong soils which enhances SOC storage (Six et al. 2000)on et al. 2019; Poeplau et al. 2018; Sochorova´ et al. 2016) the one hand and by higher C inputs to grassland and that the ratio of NPP to NPP can vary org above below 123 268 Nutr Cycl Agroecosyst (2020) 118:249–271 greatly upon management intensity and yield. Thus, The size and representativeness of the dataset used the application of a yield-dependent ratio of NPP in this study to estimate management related C above org to NPP would most likely cause large errors for fluxes on German agricultural soils make it unique. below the estimation of NPP (Poeplau 2016). This was Yield data are usually available on strongly aggre- below supported by a recent publication of Taghizadeh- gated scales or for certain crops only or they are gained Toosi et al. (2020) who also claimed that using a fixed from experimental sites that do not reflect commercial value for belowground C input in leys improved agriculture. Field-scale fertilization or residue man- org SOC model simulations for several long-term field agement data are scarcely available at all. Here, we experiments compared to the application of a fixed took the opportunity to comprehensively analyze a ratio of NPP to NPP for the estimation of decade-long dataset obtained directly from about 1% above below belowground C inputs. Thus, for grassland sites, we of all German farmers through a questionnaire. Due to org made a fundamental change regarding the conven- this unique dataset and the region-specific method we tional estimation of belowground C input based on a developed, the present study delivered the first robust org ratio of NPP to NPP : We adopted the estimates of C-assimilation (NPP ) and C inputs above below tot org assumption of a fixed value for NPP and made and exports from German agricultural soils. Anyway, below use of a large German dataset of a related study of results are subject to two sources of uncertainty: one Poeplau et al. (2018). Based on these results, we related to the dataset as such and the other related to assumed a fixed average root-derived C input of assumptions used in the method. We hold that the org -1 -1 2.2 Mg C ha yr . This value is supported by priority for improvement of the method is to continue org Ammann et al. (2009) who measured root C stocks with crop- and site-specific quantification of root org -1 of 2.3 and 2.1 Mg C ha in intensively and biomass in arable land and grasslands, as critical org extensively managed Swiss grassland, respectively. component of total plant-derived C input to soils. org For arable crops, recent findings are less profound: It was shown in two Swiss and one British field trial that maize and wheat have a much stronger above- Conclusions ground than belowground response to fertilization (Hirte et al. 2018; Taghizadeh-Toosi et al. 2016) and a Our study revealed that maximizing plant productiv- fixed root-C input value was regarded more robust ity, measured as NPP, has the greatest potential to org for wheat (Taghizadeh-Toosi et al. 2016). However, at maximize C inputs to soil and thus SOC stocks in org this current point of research, it is impossible to agriculture. Any decrease in plant productivity, e.g. deduce reliable values replacing conventional C due to climate change induced droughts, threatens org allocation coefficients by fixed root-C input for current SOC stocks. Surprisingly, total C inputs did org org arable crops. Such values are not available for the not vary between grasslands and croplands, suggesting majority of crops but crop types differ strongly in that large differences in SOC stocks usually observed physiology. Thus, we decided to stick to the conven- between both land use types cannot be explained by tional assumption well proven by Bolinder et al. differences in total C inputs. Quality and allocation org (2007) and provided regionally sound mean values of of C input matter and point toward a pivotal role of org NPP (equal root-C input) as a starting point for roots for building SOC. A more profound understand- below org future research. A SOC modeling study on German ing of the stabilization rates and pathways of various arable long-term monitoring sites using five different C input sources is thus necessary. We recommend org C input estimation methods (Riggers et al. 2019) using the method and data presented here for Central org supported this procedure: C input estimated by the European agricultural soils as it complies the up-to- org here presented regional approach led to lower model date data sources available for this region. Yet, more errors than the original one of Bolinder et al. (2007). field studies are needed to further improve C input org This is most likely because the latter summarized estimates. For example, the role of different pedocli- studies mainly from North America. To summarize, matic regions as well as cultivars on allocation the C inputs we calculated for German arable and coefficients and C input estimates are widely org org grassland soils can be regarded as most reliable. neglected to date. The latter might be especially relevant for comparisons between organic and 123 Nutr Cycl Agroecosyst (2020) 118:249–271 269 Weihenstephan. https://www.lfl.bayern.de/mam/cms07/ conventional farms, since organic agriculture uses ipz/dateien/bayernplan_einsatz_von_biogas_zum_ersatz_ with different cultivars. The role of breeding on von_gaskraftwerken_ag1.pdf. Accessed 29 March 2018 allocation coefficients and, thus, root derived C org Baldauf S, Bergmeister S (2006) Abbauverhalten von aus- input is poorly understood. The C input to soil is a gewa¨hlten organischen Schadstoffen in org Kla¨rschlammkomposten bei vera¨nderten Rotteparametern. large C-flux that is directly controlled by agricultural Diploma, Ho¨here Technische Bundeslehr- und Versuch- management. All efforts to maintain or increase SOC sanstalt Dornbirn stocks can only be successful when we understand the Bayrische Landesanstalt fu¨r Landwirtschaft (LfL) (2011) Inte- effects of agricultural management of this flux in grierter Pflanzenbau–Zwischenfruchtanbau. https://www. lfl.bayern.de/mam/cms07/publikationen/daten/ detail. informationen/p_28819.pdf. Accessed 18 Dec 2017 BIOS Bioenergies GmbH (2018) Biomass. http://www.ieabcc. Acknowledgements This study was funded by the German nl/database/biomass.php. Accessed 29 March 2018 Federal Ministry of Food and Agriculture in the framework of Bolinder MA, Janzen HH, Gregorich EG, Angers DA, Van- the German Agricultural Soil Inventory. 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Exports and inputs of organic carbon on agricultural soils in Germany

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Nutr Cycl Agroecosyst (2020) 118:249–271 https://doi.org/10.1007/s10705-020-10087-5(0123456789().,-volV)(0123456789().,-volV) ORIGINAL ARTICLE Exports and inputs of organic carbon on agricultural soils in Germany . . . . Anna Jacobs Christopher Poeplau Christian Weiser Andrea Fahrion-Nitschke Axel Don Received: 16 January 2020 / Accepted: 28 July 2020 / Published online: 8 October 2020 The Author(s) 2020 Abstract The quantity and quality of organic carbon agricultural soils in Central Europe. Mean total NPP (C ) input drive soil C stocks and thus fertility and calculated for arable and grassland soils was 6.9 ± 2.3 org org -1 -1 climate mitigation potential of soils. To estimate and 5.9 ± 2.9 Mg C ha yr , respectively, of org fluxes of C as net primary production (NPP), which approximately half was exported. On average, org exports, and inputs on German arable and grassland total C input calculated did not differ between org -1 -1 soils, we used field management data surveyed within arable (3.7 ± 1.8 Mg ha yr ) and grassland soils -1 -1 the Agricultural Soil Inventory (n = 27.404 cases of (3.7 ± 1.3 Mg ha yr ) but C sources were org sites multiplied by years). Further, we refined the different: Grasslands received 1.4 times more C org concept of yield-based C allocation coefficients and from root material than arable soils and we suggest org delivered a new regionalized method applicable for that this difference in quality rather than quantity drives differences in soil C stocks between land use org systems. On arable soils, side products were exported Electronic supplementary material The online version of in 43% of the site * years. Cover crops were cultivated this article (https://doi.org/10.1007/s10705-020-10087-5) con- in 11% of site * years and contributed on average 3% tains supplementary material, which is available to authorized users. of the mean annual total NPP. Across arable crops, total NPP drove C input (R = 0.47) stronger than org A. Jacobs (&)  C. Poeplau  C. Weiser  2 organic fertilization (R = 0.11). Thus, maximizing A. Fahrion-Nitschke  A. Don plant growth enhances C input to soil. Our results org Thu¨nen Institute of Climate-Smart Agriculture, Bundesallee 65, 38116 Brunswick, Germany are reliable estimates of management related C org e-mail: anna.jacobs@thuenen.de fluxes on agricultural soils in Germany. A. Jacobs Keywords Carbon sequestration  Manure  Net Coordination Unit Soil of Thu¨nen Institute, Bundesallee primary productivity  Carbon balance  Net biome 49, 38116 Brunswick, Germany productivity Present Address: C. Weiser Fachagentur Nachwachsende Rohstoffe e. V, Hofplatz 1, 18276 Gu¨lzow-Pru¨zen, Germany Introduction Present Address: A. Fahrion-Nitschke The content or stock of soil organic carbon (SOC) in Niedersa¨chsische Landesforsten, Forstplanungsamt, agricultural soils is regarded as the key parameter Forstweg 1A, 38302 Wolfenbu¨ttel, Germany 123 250 Nutr Cycl Agroecosyst (2020) 118:249–271 sustaining soil fertility and health. Moreover, the being closely linked to SOC dynamics. The absolute carbon (C) cycle of agricultural systems plays a role in magnitude of the major management-related annual climate change mitigation: since the more C is stored fluxes of C on agricultural soils, i.e. NPP ,C org tot org as organic C (C ) in the soil and the longer it is stored export from the site, and C input from external org org for, the less it contributes to climate change as the sources are generally not well quantified. Estimates of major greenhouse gas CO (Minasny et al. 2017). It is C input to soil, e.g. when modeling SOC dynamics 2 org widely acknowledged that farming practices can within the context of greenhouse gas reporting, are influence SOC levels to a certain extent (Freibauer thus often derived from national or regional agricul- et al. 2004). On field scale, SOC stocks are strongly tural yield statistics (Andren et al. 2008). These correlated with the amount of C input, which is the statistics are than combined with plant-specific harvest org almost exclusive source of SOC (Ka¨tterer et al. 2012). indices and C allocation coefficients which are org However, on a national scale, there are very few data published for the major crops, forages (wheat, barley, available on the amount of C input to agricultural oat, triticale, oil seed rape, grain maize, silage maize, org soils. potato, sugar beet, mustard, some legumes) and The quantity, and also the quality, of organic inputs grasslands (Bolinder et al. 2007, 2015; Gan et al. play an important role in SOC build-up and dynamics. 2009). Manure application rates can be roughly For example, recent studies suggested that root- and estimated from the number of animals reported in a manure-derived C has stronger effects on SOC specific region, while harvest residue management is org stocks than straw-derived C (Ka¨tterer et al. 2011; not given in agricultural yield statistics. However, org Rasse et al. 2005). Both the quantity and quality (e.g. residue management is somewhat important for C org C to nitrogen ratio of organic material) of C input input to soil since some harvest residues are removed org org to soil are controlled by the farmer through the choice from the field, e.g., for bioenergy provision and some of crop rotation, amount and type of mineral and are left in situ. organic fertilizers applied, and harvest residue man- Apart from obvious uncertainties in agricultural agement. The farmer also determines total net primary activity data, another major source of uncertainty is -1 -1 production (NPP ;Mg C ha yr ), the fraction of the use of C allocation coefficients and harvest tot org org NPP that is harvested as the main product, and the indices derived from global reviews. However, C org amount of C ultimately returned to the soil. There allocation coefficients are needed to convert yield data org are five main pathways of C input to agricultural into root- and shoot-derived C input. Keel et al. org org soils, governed by: (1) type and amount of above- (2017) and Riggers et al. (2019) demonstrated that the ground harvest residues if left in the field, stubbles choice of allocation coefficients used for C input org always remaining in the field or mulch if left in the estimation strongly influences the SOC trends mod- field, (2) type and amount of organic fertilizers eled. Region-specific up-to-date allocation coeffi- applied, (3) type and amount of excreta produced by cients and harvest indices are required to minimize grazing animals, (4) cover crops used for green this source of error. So far, region-specific allocation manure, and (5) belowground biomass as dead roots coefficients are not applied for estimates of C input org and rhizodeposition. This implies that agricultural although validated values for, e.g., crop-specific soils have C-sink potential and that implementation of harvest indices are available. certain management practices could help mitigate The specific aims of this study were to climate change (Minasny et al. 2017). (1) establish a sound method for estimation of mean To understand, predict, and report SOC stock annual NPP ,C inputs, and C exports tot org org changes in agricultural systems, information on man- from arable and grassland sites under Central agement and related C fluxes from and to the soil is org European environmental conditions. of critical importance. In addition, knowledge on the (2) quantify and compare mean annual NPP ,C tot org regional distribution of harvest exports and inputs of inputs and C exports across land use systems org C to soil is required for development of climate- org in Germany. smart and sustainable solutions in agriculture. How- (3) determine the spatial distribution of C input org ever, field-specific data are often not available at and its sources in Germany. national scales preventing ‘C management’ from org 123 Nutr Cycl Agroecosyst (2020) 118:249–271 251 Data from the first German Agricultural Soil grassland sites for the evaluation. These values were Inventory were used in the analysis. These comprised multiplied by the site-specific management years, and 10 years of management data, including crop type, thus a total of 19,987 arable site * years and 7417 yield, fertilization practices, harvest residue manage- grassland site * years in the period 2001–2016 were ment, field operations, and other key variables such as evaluated as cases in the present study. If not stated livestock density, for each of 3104 arable and grass- otherwise, results are shown as mean of site * years. land sites surveyed within the Agricultural Soil Inventory. Based on this ‘first-hand’ dataset and on Method’s development: Organic carbon allocation regional harvest indices, we estimated NPP on coefficients for arable crops grown under Central tot arable and grassland sites, total C export via harvest European conditions org of main products, and sources of C input across org Germany. Based on crop-specific harvest indices and on a set of coefficients of C allocation among crop compart- org ments taken from the literature, we derived C org Materials and methods allocation factors specific for cultivation conditions in Central Europe in order to estimate annual C input org -1 -1 Database of agronomic and grassland management (Mg C ha yr ) to soil based on yield information. org The concept of C allocation, as described in detail org The German Agricultural Soil Inventory collected by Bolinder et al. (2007), is based on the assumption samples of soils under agricultural land use in a that the sum of C within all plant compartments org -1 -1 8km 9 8 km grid across Germany (Jacobs et al. equals NPP (Mg C ha yr ) and that all C tot org org 2018) accompanied by collection of arable and allocation factors add up to 1. permanent grassland management data through a For arable crops, we applied the following five, questionnaire sent to the farmers on whose sites soil crop-specific C allocation factors (CA ): org x sampling was performed. Thereby, for the definition of CA þ CA þ CA þ CA þ CA ¼ 1 MP HR ST R RD ‘permanent grassland’ (referred to as ‘grassland’ in the ð1Þ following), we referred to the one used in agricultural practice where a grassland is permanent after five where MP is the main product, HR is the harvest years of continuous grassland use. Farmers were asked residues, ST is stubbles as the part of HR always to record type of crop rotation, fresh matter yield of the remaining in the field, R is dead roots, and RD is main product, harvest residues management regimes, rhizodeposition. cover crops management regimes, and the amount and We calculated the C allocation factors for arable org type of organic fertilizers used. For grassland sites, main products, harvest residues, and stubbles based on farmers were asked to record dry matter yield, number C content, dry matter content, harvest index, and a org of cuts per year, mulching, amount and type of organic stubble index for arable crops obtained in a literature fertilizers used, and number and species of grazing search prioritizing German references (Table 1). The animals. If possible, farmers were supposed to deliver selection criteria for the search were, in descending the respective data on the previous decade of man- order: (1) agricultural management representative of agement, if possible. However, in the present analysis, commercial farming in Germany, (2) factors quotable, we had to exclude some records (site * years) from the and (3) factors consistent with each other. We data set due to incomplete information especially on generally took the mean value when more than one (1) crops and cover crops indicated as ‘unknown’ or value was available. There are generally no data ‘unspecified’ (n = 79 and 247, respectively), (2) data available specifically for cultivars used in organic entries with no information on harvest residues agriculture although it is known that the physiology, management (n = 485), (3) data entries on use of and thus C allocation, of these cultivars differs from org organic fertilizer that did not state the amount or type that of cultivars used in conventional agriculture. In (n = 45), and (4) data entries on pastures with no this study, only 5% of the arable sites evaluated were information on grazing animals or farm’s livestock under organic management and we ignored this (n = 631). This left 2097 arable sites and 718 123 252 Nutr Cycl Agroecosyst (2020) 118:249–271 Table 1 Harvest index (HI = yield of main product/(yield of main pro- suggested to be the same than of HR), index for the amount of HR remaining in the -1 duct ? biomass of harvest residues)), dry matter (DM; (Mg DM Mg fresh field as stubble (stubble index = SI) when HR were exported, and allocation -1 -1 -1 matter )), and organic carbon content (C; (Mg C Mg DM ) of main product coefficients for organic carbon (CA) within crops (R = roots, RD = rhizodeposition) harvested (MP) and aboveground harvest residues (HR) (C of stubbles (ST) was calculated as described in the text Crop DM C C HI SI CA CA CA CA CA Comments, suggestions made MP MP HR MP HR ST R RD -1 -1 -1 (Mg Mg ) (Mg Mg ) (Mg Mg ) 1 3 2,3,4,5,6 1,2 9 9,10,11 Winter wheat 0.86 0.46 0.46 0.55 0.15 0.417 0.284 0.050 0.190 0.059 1 3,5 2,3,4,5,6 1,2 9 9,10 Winter barley 0.86 0.47 0.46 0.57 0.15 0.444 0.279 0.049 0.174 0.054 1 3 2,3,4,5 1,2 9 Spring barley 0.86 0.46 0.46 0.57 0.15 0.422 0.268 0.047 0.200 0.062 CA : mean of all cereals 1 3,5 2,3,4 1 9 Winter rye 0.86 0.47 0.47 0.53 0.15 0.404 0.308 0.054 0.178 0.055 CA : mean of all winter cereals 1 5 2,5 1 9 9 Winter triticale 0.86 0.45 0.46 0.53 0.15 0.421 0.326 0.058 0.149 0.046 1 2,5,6 1 9 9,10 Oat 0.86 0.46 0.45 0.48 0.15 0.312 0.288 0.051 0.267 0.083 C : as spring barley MP Other winter cereals 0.86 0.46 0.46 0.55 0.15 0.423 0.292 0.052 0.178 0.055 mean of all winter cereals 1 9 Other spring cereals 0.86 0.46 0.46 0.57 0.15 0.422 0.268 0.047 0.200 0.062 HI, DM ,C ,C : as spring barley; MP MP HR CA : mean of all cereals 1,2 5 2,6 1,2 9 9,10 Corn, sweet corn 0.86 0.48 0.43 0.50 0.10 0.396 0.315 0.035 0.194 0.060 1,7,8 2,6 9 9 Silage maize, 0.31 0.43 1 0.05 0.772 0 0.039 0.145 0.045 HI = 1 for total biomass harvest sorghum 1,8 5 9 9,10 10 Clover (whole plant) 0.20 0.41 1 0.25 0.455 0 0.114 0.329 0.102 HI = 1 for total biomass harvest; in ref ‘stem’ is equal the MP; CA ,CA : for R RD annual cultivation only, otherwise see text 1 6 1 9,10 Clover (seeds) 0.91 0.47 0.11 0.15 0.063 0.430 0.076 0.329 0.102 C : value for ‘herbaceous and agricultural MP biomass’; SI: as cereals; CA ,CA : for R RD annual cultivation only, otherwise see text 1 6 2,5 1,2 9 9,11 Fodder and 0.86 0.47 0.45 0.47 0.10 0.380 0.321 0.040 0.166 0.052 C = value for ‘herbaceous and MP vegetable legumes agricultural biomass’; CA ,CA : for R RD (grains) annual cultivation only, otherwise see text 1,2 2,4,5,6 9 9,10 Fodder legumes 0.20 0.46 1.00 0.25 0.455 0.000 0.114 0.329 0.102 HI = 1 for total biomass harvest; CA : MP (whole plant) in ‘stem’ is equal the MP; CA ,CA : R RD for annual cultivation only, otherwise see text 1 3 2,3,4,6 1,2 11 Oilseed rape 0.91 0.63 0.47 0.38 0.15 0.320 0.332 0.059 0.222 0.069 SI: as cereals 1 6 6 1 10,12 Potatoes 0.22 0.47 0.47 0.83 0.00 0.798 0.160 0.000 0.033 0.010 C ,C : value for ‘herbaceous and MP HR agricultural biomass’; SI = 0 for root crop harvest 1 5 2,9 17 10,12 Sugar beet 0.23 0.45 0.41 0.81 0.00 0.788 0.169 0.000 0.033 0.010 SI = 0 for root crop harvest 1 5 1,17 Fodder beet 0.12 0.45 0.41 0.76 0.00 0.744 0.221 0.000 0.033 0.010 C ,CA : as sugar beet; SI = 0 for root HR R crop harvest Nutr Cycl Agroecosyst (2020) 118:249–271 253 Table 1 continued Crop DM C C HI SI CA CA CA CA CA Comments, suggestions made MP MP HR MP HR ST R RD -1 -1 -1 (Mg Mg ) (Mg Mg ) (Mg Mg ) 1,8 7 9 9 Grass with legumes 0.20 0.40 1 0.15 0.303 0.000 0.045 0.498 0.154 HI = 1 for total biomass harvest; CA , (whole plant) CA : for annual cultivation only, RD otherwise see text 1 4,5,7 9 9,10 Grass without 0.20 0.45 1 0.15 0.533 0.000 0.080 0.295 0.092 HI = 1 for total biomass harvest; CA : MP legumes (whole in ‘stem’ is equal the MP; CA ,CA : R RD plant) for annual cultivation only, otherwise see text 8 6 6 Strawberries 0.10 0.47 0.47 0.50 0 0.302 0.302 0.000 0.302 0.094 HI = own suggestion; C ,C = value MP HR for ‘herbaceous and agricultural biomass’; SI = 0 for no stubble occurrence; CA : own suggestion as MP 66% of biomass is aboveground with HI = 0.5; CA : own estimation as 33% of biomass is belowground 8 6 Asparagus 0.10 0.47 1 0 0.957 0.000 0.000 0.033 0.010 HI = 1 for total biomass harvest; C : MP value for ‘herbaceous and agricultural biomass’; SI = 0 for root crop harvest; CA : mean of potatoes and sugar beet 7 7 2 13 15,16 White cabbage & 0.13 0.51 0.43 0.60 0 0.450 0.246 0.000 0.232 0.072 SI = 0 for no stubble occurrence; CA : ‘other vegetables’ mean value of turnip rape, fodder cabbage, swede, turnip, fodder radish as ‘vegetable-like’ cover crops 7 7 2 13 15,16 Red cabbage 0.13 0.51 0.43 0.54 0 0.409 0.287 0.000 0.232 0.072 SI = 0 for no stubble occurrence; CA : mean value of turnip rape, fodder cabbage, swede, turnip, fodder radish as ‘vegetable-like’ cover crops 7 7 2 13 15,16 Green cabbage 0.13 0.51 0.43 0.74 0 0.536 0.160 0.000 0.232 0.072 SI = 0 for no stubble occurrence; CA : mean value of turnip rape, fodder cabbage, swede, turnip, fodder radish as ‘vegetable-like’ cover crops 7 7 2 13 15,16 Broccoli 0.13 0.51 0.43 0.56 0 0.421 0.276 0.000 0.232 0.072 SI = 0 for no stubble occurrence; CA : mean value of turnip rape, fodder cabbage, swede, turnip, fodder radish as ‘vegetable-like’ cover crops 7 7 2 13 15,16 Cauliflower 0.13 0.51 0.43 0.63 0 0.468 0.228 0.000 0.232 0.072 SI = 0 for no stubble occurrence; CA : mean value of turnip rape, fodder cabbage, swede, turnip, fodder radish as ‘vegetable-like’ cover crops 254 Nutr Cycl Agroecosyst (2020) 118:249–271 Table 1 continued Crop DM C C HI SI CA CA CA CA CA Comments, suggestions made MP MP HR MP HR ST R RD -1 -1 -1 (Mg Mg ) (Mg Mg ) (Mg Mg ) 7 7 2 13 Carrot 0.13 0.51 0.43 0.86 0 0.842 0.115 0.000 0.033 0.010 SI = 0 for no stubble occurrence; CA : mean of potatoes and sugar beet 7 7 2 13 Beetroot 0.13 0.51 0.43 0.77 0 0.769 0.188 0.000 0.033 0.010 SI = 0 for no stubble occurrence; CA : mean of potatoes and sugar beet 7 7 2 13 Small radish 0.13 0.51 0.43 0.88 0 0.855 0.102 0.000 0.033 0.010 SI = 0 for no stubble occurrence; CA : mean of potatoes and sugar beet 7 7 2 13 13 Radish 0.13 0.51 0.43 0.79 0.779 0.178 0.000 0.033 0.010 SI = 0 for no stubble occurrence; CA : mean of potatoes and sugar beet 7 7 2 13 Onion 0.13 0.51 0.43 0.80 0 0.789 0.168 0.000 0.033 0.010 SI = 0 for no stubble occurrence; CA : mean of potatoes and sugar beet 7 7 2 13 15,16 Celeriac 0.13 0.51 0.43 0.83 0 0.817 0.140 0.000 0.232 0.072 SI = 0 for no stubble occurrence; CA : mean value of turnip rape, fodder cabbage, swede, turnip, fodder radish as ‘vegetable-like’ cover crops 7 7 2 13 15,16 Cucumber 0.13 0.51 0.43 0.72 0 0.522 0.174 0.000 0.232 0.072 SI = 0 for no stubble occurrence; CA : mean value of turnip rape, fodder cabbage, swede, turnip, fodder radish as ‘vegetable-like’ cover crops 7 7 2 13 15,16 Pumpkin 0.13 0.51 0.43 0.67 0 0.490 0.206 0.000 0.232 0.072 SI = 0 for no stubble occurrence; CA : mean value of turnip rape, fodder cabbage, swede, turnip, fodder radish as ‘vegetable-like’ cover crops 7 7 2 13 15,16 Salad 0.13 0.51 0.43 0.82 0 0.585 0.111 0.000 0.232 0.072 SI = 0 for no stubble occurrence; CA : mean value of turnip rape, fodder cabbage, swede, turnip, fodder radish as ‘vegetable-like’ cover crops 7 7 2 13 15,16 Spinach 0.13 0.51 0.43 0.75 0 0.543 0.153 0.000 0.232 0.072 SI = 0 for no stubble occurrence; CA : mean value of turnip rape, fodder cabbage, swede, turnip, fodder radish as ‘vegetable-like’ cover crops Herbs 0.20 0.47 1 0.25 0.483 0.000 0.121 0.302 0.094 HI = 1 for total biomass harvest; DM :as MP grass without legumes; C : value for MP ‘herbaceous and agricultural biomass’; SI: as fodder legumes (whole plant); CA : own suggestion as 66% of MP biomass is aboveground with an HI of 1; CA : own suggestion as 33% of biomass is belowground; CA ,CA : for annual R RD cultivation only, otherwise see text Nutr Cycl Agroecosyst (2020) 118:249–271 255 Table 1 continued Crop DM C C HI SI CA CA CA CA CA Comments, suggestions made MP MP HR MP HR ST R RD -1 -1 -1 (Mg Mg ) (Mg Mg ) (Mg Mg ) Cereal silage (whole 0.35 0.47 1 0.05 0.702 0.000 0.035 0.200 0.062 HI = 1 for total biomass harvest; C :as MP plant) winter rye; SI: as silage maize; CA : mean of all cereals 1 6 4,5,7 1 Grass without 0.86 0.47 0.45 0.11 0.15 0.072 0.460 0.081 0.295 0.092 C = value for ‘herbaceous and MP legumes (seeds) agricultural biomass’; SI: as cereals; CA : as grass without legumes (whole plant); CA ,CA : for annual cultivation R RD only, otherwise see text 1 5 5 1 Sunflower & ‘other’ 0.91 0.52 0.44 0.33 0.15 0.264 0.379 0.067 0.222 0.069 SI: as cereals; CA : as oilseed rape oil crops 1 5 5 1 Linseed 0.91 0.52 0.44 0.40 0.15 0.313 0.337 0.059 0.222 0.069 SI: as cereals; CA : as oilseed rape 6 6 Tobacco 0.20 0.47 0.47 0.67 0.00 0.466 0.230 0.000 0.232 0.072 HI: mean of vegetables; DM : as harvest MP residues of sugar beet; SI = 0 for no stubble occurrence; CA : as aboveground vegetables 1 6 Hemp 0.40 0.47 1 0.05 0.772 0.000 0.039 0.145 0.045 HI = 1 for total biomass harvest; SI, CA : as silage maize Fallow 0.20 0.45 1 0.15 0.533 0.000 0.080 0.295 0.092 As grass without legumes (whole plant); not to be interpreted as bare fallow but as years of non-cultivation during which soil is covered by (volunteer) grass which is not harvested 1 2 3 4 5 6 7 Anonymous (2017), Franko et al. (2011), Obernberger et al. (2006), Nordin (1994), BIOS Bioenergiesysteme GmbH (2018), Vassilev et al. (2010), Rynk et al. (1992), 8 9 10 11 12 13 14 15 Zorn et al. (2007), Bolinder et al. (2007), Li et al. (1997), Gan et al. (2009), Bolinder et al. (2015), Feller et al. (2011), Pausch and Kuzyakov (2018), Nordrhein- 16 17 Westfalen (2015), Kuratorium fu¨r Technik und Bauwesen in der Landwirtschaft (KTBL) (2009), Laufer et al. (2016) 256 Nutr Cycl Agroecosyst (2020) 118:249–271 circumstance and applied the mean values we found to below) although there are recent findings that at least all records. wheat has rather a fixed than a yield-dependent The C allocation factor of the main product NPP (Taghizadeh-Toosi et al. 2016). However, org below (CA ) was calculated as: these results were not proven for the broad spectra of MP arable crops we evaluated here and thus we used the AMP  DM  C MP MP CA ¼ ð2Þ conventional concept of C allocation based on MP org NPP tot findings of Bolinder et al. (2007). where A-MP is the fresh matter yield of the main To derive the C allocation factor for rhizodepo- org -1 -1 product of an arable crop (Mg ha yr ), DM is its sition, we used a recent values published in a review MP -1 dry matter content (Mg Mg ), C is the C content by Pausch and Kuzyakov (2018) who concluded that MP org -1 -1 (Mg Mg dry matter ) (Table 1), and NPP (Mg rhizodeposition is 0.31 * root-C for most arable tot org -1 -1 C ha yr ) was calculated as described below. org crops. The term rhizodeposition as used here is equal The C allocation factor of harvest residues to the net rhizodeposition defined by Pausch and org (CA ) was calculated as: HR Kuzyakov (2018) as the part of C remaining longer org in soil since it is not mineralized by soil organisms DM MP AMP  ðÞ 1  HI C ðÞ 1  SI HR HI CA ¼ immediately after being released into the soil. HR NPP tot ð3Þ Calculation of annual net primary production on arable sites where A-MP is the fresh matter yield of the MP of an -1 -1 arable crop (Mg ha yr ), DM is its dry matter MP -1 For arable crops, calculations of annual NPP (Mg tot content (Mg Mg ), HI is the harvest index, C is the HR -1 -1 -1 C ha yr ) for each site * year was based on the org C content of harvest residues (Mg Mg dry org -1 fresh matter yield of the respective main product, matter ), SI is the stubble index as the proportion which in most cases (79% of site * years evaluated) of HR always remaining in the field as stubbles and was recorded by the farmer. Missing values were therefore supposed to be calculated as a separate replaced as accurately as possible by statistical values compartment of the crop (for crops for which MP is in a three-step procedure: (1) If available, the year- total aboveground biomass harvested, it is a proportion -1 -1 specific yield of the main product at site-specific of MP) (Table 1), and NPP (Mg C ha yr ) was tot org NUTS3 level (Landkreis) was used; (2) otherwise, the calculated as described below. year-specific mean value of the respective Federal The C allocation factor for stubbles (CA ) was org ST State was used; (3) if still not available, a statistical calculated as: mean of Germany was used or a rough estimate was DM MP AMP  ðÞ 1  HI SI  C HR made (Graf et al. 2005; Kuratrorium fu¨r Technik und HI CA ¼ ð4Þ ST NPP tot Bauwesen in der Landwirtschaft (KTBL) 2009; Landwirtschaftskammer Niedersachsen 2007, 2014, where A-MP is the fresh matter yield of the main -1 -1 Statistisches Bundesamt (Destatis) 2003–2018, Tech- product of an arable crop (Mg ha yr ), DM is its MP -1 nologie- und Fo¨rderzentrum (TFZ) im Kompetenzzen- dry matter content (Mg Mg ), HI is the harvest trum Nachwachsende Rohstoffe 2007). The statistical index, C is the C content of the harvest residues HR org -1 -1 values of yield of the main product were adjusted to (Mg Mg dry matter ), SI is the stubble index the yield level of the specific farm: For each farm and assuming that stubbles have the same C content as org -1 -1 crop, a ‘recorded:statistical’ factor was calculated harvest residues (Table 1); NPP (Mg C ha yr ) tot org when the respective yield was recorded at least for 2 was calculated as described below. years; otherwise, the factor was calculated as the mean To develop the C allocation factor for roots, we org factor across all crops recorded. If no records were used crop-specific constant ratios of aboveground NPP available, no adjustment was made. (NPP ) to belowground NPP (NPP ) allocation above below If a record indicated that an arable crop was not empirically derived from different studies following harvested and all biomass was tilled into the soil, as the general concept of C allocation (Table 1). We org done for fallow (unharvested grass; 3% of the site * applied the NPP : NPP ratio to NPP (see above below above years evaluated) or after extreme weather events 123 Nutr Cycl Agroecosyst (2020) 118:249–271 257 (0.3% of the site * years evaluated), the yield of the ANPP ¼ðÞ AMP  DM  C above MP MP main product was set as zero. However, in further MP þ AMP  DM   CA MP HR calculations, e.g. NPP , we needed an equivalent to above CA MP the potential yield and estimated it as being about 50% MP þ AMP  DM   CA MP ST of a default fresh matter yield (own suggestions as a CA MP rough estimate based on Graf et al. 2005; Kuratrorium ð6Þ fur Technik und Bauwesen in der Landwirtschaft (KTBL) 2009; Landwirtschaftskammer Niedersach- MP ANPP ¼ AMP  DM   CA below MP R sen 2007, 2014; Statistisches Bundesamt (Destatis) CA MP 2003–2018; Technologie- und Fo¨rderzentrum (TFZ) MP þ AMP  DM   CA MP RD im Kompetenzzentrum Nachwachsende Rohstoffe CA MP -1 2007): fallow: 15 Mg fresh matter ha , grass: ð7Þ -1 15 Mg fresh matter ha , winter rye: 2.5 Mg fresh -1 matter ha , clover (whole plant): 17.5 Mg fresh where A-MP is the fresh matter yield of the main -1 -1 -1 matter ha , grass with legumes (whole plant): product of an arable crop (Mg ha yr ), DM is its MP -1 -1 17.5 Mg fresh matter ha , fodder legumes (whole dry matter content (Mg Mg ), C is its C content MP org -1 -1 -1 plant): 17.5 Mg fresh matter ha , winter wheat: 4 Mg (Mg Mg dry matter ), CA is the C allocation MP org -1 fresh matter ha , fodder legumes (grains): 1.5 Mg factor of the main product, CA is the C allocation HR org -1 fresh matter ha , grass without legumes (grains): 0.5 factor of the harvest residues, CA is the C ST org -1 fresh matter Mg ha , winter oilseed rape: 18 Mg allocation factor of the stubbles, C is the C AR org -1 fresh matter ha . allocation factor of the roots, and CA is the C RD org On arable sites, NPP comprised all aboveground allocation factor of the rhizodeposition (Table 1). tot and belowground biomass compartments of the main crop and the cover crop. For perennial cultivation of Calculation of annual net primary production grass, legumes, and herbs, NPP was calculated as of grassland sites below for permanent grasslands (see below) except in the last -1 -1 year of the cultivation period. For cover crops, yield For grassland sites, annual NPP (Mg C ha yr ) tot org and belowground biomass were not recorded, and was again based on the ‘yield’, which was also were thus estimated based on a literature search and a recorded in the questionnaire. Three different types of -1 -1 default C content of 0.47 Mg Mg dry matter grassland were distinguished and we developed org (‘herbaceous and agricultural biomass’ in Vassilev specific approaches to fill gaps in yield data and to et al. (2010)) to obtain NPP and NPP for estimate NPP for these grassland types: meadows above below above cover crops (Table S1). Rhizodeposition by cover (grassland mown), pastures (grassland grazed) and crops was set at 0.31 * root-C (Pausch and mown pastures (grassland grazed and mown). org Kuzyakov 2018). Missing yield data for meadows (42% of site * -1 -1 The annual NPP (Mg C ha yr ) on arable years recorded) were replaced with statistical values, tot org sites (A-NPP ) was calculated as the sum of NPP in the same way as for arable crops, to derive the tot above and NPP of the main product and the cover crop amount of biomass exported. However, for meadows, below (CC-) (Eq. 5). For A-NPP and A-NPP ,C the average values obtained from NUTS3 statistics did above below org allocation factors were applied to the fresh matter not distinguish between different management inten- yield (Eqs. 6, 7).: sities. The biomass exported from meadows is corre- lated to the number of cuts per year which is also an ANPP ¼ ANPP þ ANPP tot above below indicator for management intensity. Wendland et al. þ CCNPP þ CCNPP ð5Þ above below (2018), representing the agricultural extension service in Bavaria, published a linear relationship (y = 16.2 ? 25; R = 0.99) for intensively managed meadows for the use of official fertilization recom- mendations. Based on these long term experiences, we 123 258 Nutr Cycl Agroecosyst (2020) 118:249–271 adjusted the statistical values as follows: We assumed The calculation of annual NPP on grassland above -1 -1 that the statistical grassland yield values reflect a sites (G-NPP ;Mg C ha yr ) was the sum of above org common number of cuts, which we set equal to the all grassland biomass grown on the site (for exact country-wide average number of cuts (2.66) recorded calculation, see Table S4): in the Agricultural Soil Inventory database. We then GNPP ¼ GMP þ GMP þ MU  1:215 above up adjusted the statistical grassland main product by the 0:45 number of cuts recorded using specific factors ð8Þ (Table S2), based on a linear relationship between yield and number of cuts derived from field observa- where G-MP is the dry matter yield of the main -1 -1 tion (Wendland et al. 2018). Thus, for meadows with product of the grassland site (Mg ha yr ), G-MP up two or fewer cuts, we reduced the statistical yield, -1 -1 is the biomass taken up by animals (Mg ha yr ), -1 -1 while for meadows with of three or more cuts we MU is the biomass mulched (Mg ha yr ), the increased it. factor 1.215 represents the part of biomass that grows For pastures, yield data recorded were assumed to each year after the last cut or before/after grazing be an estimate of total uptake by grazing animals, period of animals which is about 30% of the biomass which we refer to as grassland main product taken-up. measured as G-MP or G-MP or MU (Christensen up When no yield for pastures was recorded, biomass et al. 2009) and of which 50% decays within the year uptake was calculated from recorded livestock units evaluated (Poeplau 2016), and 0.45 is the C content org -1 -1 grazing on the site and mean biomass uptake values for (Mg Mg dry matter ) of the aboveground biomass all cattle specimen used in the German National (Bolinder et al. 2007). Inventory Report (Ro¨semann et al. 2017). This was the Grassland specimen were lately proven to be case for 23% of all site * years recorded for pastures. extremely variable in the ratio of NPP to NPP above be- Missing data on livestock units grazing were replaced (also known as ‘root:shoot ratio’) with increasing low by dividing the number, species, and days of animals values due to management intensity, especially due to grazing recorded for the entire farm by the total fertilization (Ammann et al. 2009; Cong et al. 2019; pasture area recorded for the farm. This was the case Poeplau 2016; Sochorova et al. 2016). Meanwhile, the for 71% of all site * years recorded for pastures. The studies cited showed that belowground biomass of major assumption in this approach was that grazing grassland specimen was rather unaffected by manage- animals were equally distributed over the total pasture ment. In accordance to that, an earlier study (Poeplau area of the farm. Default values used to calculate et al. 2018), in which seven different long-term species-specific grassland main product taken up are fertilized grassland experiments in Germany were given in Table S3. sampled, we statistically proved that NPP was below For mown pastures, the yield recorded was divided unaffected by fertilization and site. The average root- into main product yield and biomass taken up in the C stock to a depth of 100 cm in that study was org -1 following way and as a rough approximation (for 3.38 ± 1.15 Mg C ha . Within the dataset used for org details, see Table S4): If one cut was performed, it the present study, the entire range of fertilization accounted for 25% of the total yield, two cuts intensity was represented and the application of C org accounted for 50%, and more than two cuts accounted allocation as a ratio of NPP to NPP would above below for 75% of the yield, while the rest was assigned to have caused large errors. Thus, we made use of our biomass taken up. When the yield was not recorded for data published in Poeplau et al. (2018) and established mown pastures, we calculated the biomass taken up as a fixed and yield-independent value to estimate described for pastures and multiplied the number of NPP as it appeared advisable according to latest below -1 cuts recorded by 1.7 Mg dry matter ha as the best publications. Based on the root-C stock of 3.38 Mg org -1 estimate of yield, based on the equation given above. C ha found by Poeplau et al. (2018), we assumed org This was the case for 38% of the records evaluated for an average annual root turnover of 50% (Gill and pastures. Jackson 2000) and an additional 31% of annual root- If not stated otherwise, we assumed that a record C produced being allocated belowground as rhi- org indicating mulching was one cut of 1.7 Mg dry matter zodeposition (Pausch and Kuzyakov 2018). The -1 ha remaining in the field. 123 Nutr Cycl Agroecosyst (2020) 118:249–271 259 grassland’s NPP was thus fixed to 2.2 Mg C NPP is the NPP of the cover crop (Mg C below org above above org -1 -1 -1 -1 ha yr , assuming that the assessment of root ha yr ), and 0.75 is the factor for the part of CC- biomass to a depth of 100 cm approximately captured biomass exported. the total root biomass. For grassland sites, the total annual C export (G- org -1 -1 EX ;Mg C ha yr ) occurs via the yield as the tot org Calculation of annual carbon export from arable main product on meadows and mown pastures, and via land and grassland biomass uptake as the main product on pastures and mown pastures. It was calculated as: -1 For arable sites, total annual C export (Mg C ha org org GEX ¼ GMP þ GMP  0:45 ð13Þ -1 tot up yr ) occurs via the main product harvested, harvest residues when exported as side products, and cover where G-MP is the dry matter yield of the main -1 -1 crops when harvested for fodder or energy use. If a product of the grassland site (Mg ha yr ), G-MP up -1 -1 record indicated that a main product was not harvested is the biomass taken up by animals (Mg ha yr ), -1 -1 and all biomass was tilled into the soil, as done for 0.45 is the C content (Mg Mg dry matter )of org fallow (grass unharvested) or after extreme weather aboveground biomass (Bolinder et al. 2007). events, C export was set to zero. Information on org whether harvest residues and/or cover crops were Calculation of plant-derived annual carbon inputs exported from the field was retrieved from the farmer on arable and grassland soils questionnaire. If the use of a cover crop was not recorded, it was assumed here that its biomass was not On arable sites, the plant-derived annual C input to org -1 -1 exported, since this is estimated to be applied soil (Mg C ha yr ) occurs via harvest residues if org in [ 80% of cases. left in the field (as recorded in the questionnaire), Total annual C export from arable sites (A-EX ; org tot stubbles which always remain in the field, roots, -1 -1 Mg C ha yr ) was calculated as the sum of C org org rhizodeposition, and cover crops. For this study, it was export via main product, harvest residues and cover not differentiated in which soil depth the C was org crops (CC-) harvested (Eq. 9). For export via main incorporated by tillage since the focus was rather on product and harvest residues, C allocation factors org the amount of C left on the site. If a cover crop was org were applied to NPP of the arable site (Eqs. 10, 11). tot recorded as being exported, it was assumed that 25% For cover crops which were exported from the site it of its NPP was left in the field as stubbles above was suggested that export accounts for 75% of the (Bolinder et al. 2007). biomass only (Bolinder et al. 2007) (Eq. 12). The total C input to arable soils (A-IN ;Mg C org tot org -1 -1 ha yr ) was calculated as (although sources of AEX ¼ AEX þ AEX þ CCEX ð9Þ tot MP HR plant-derived C input are shown separately): org AEX ¼ ANPP  CA ð10Þ MP tot MP AIN ¼ðÞ ANPP  AEX ð14Þ tot tot tot AEX ¼ ANPP  CA ð11Þ where A-NPP is the NPP of the arable site (Mg HR tot HR tot tot -1 -1 C ha yr ) and A-EX is the C export from the org tot org -1 -1 CCEX ¼ CCNPP  0:75 ð12Þ above site (Mg C ha yr ). org On grassland sites, the plant-derived annual C org where A-EX is the C export via the arable main MP org -1 -1 input to soil occurs via mulch, decaying aboveground, crop (Mg C ha yr ), A-EX is the C export org HR org -1 and belowground residues of the main product. of the harvest residues as side products (Mg C ha org -1 Decaying aboveground residues were suggested to yr ), CC-EX is the C export via the cover crop org -1 -1 comprise 50% of the biomass produced that was not harvested (Mg C ha yr ), A-NPP is the NPP org tot tot -1 -1 harvested or grazed (Poeplau 2016). The C input org of the arable site (Mg C ha yr ), CA is the org MP from decaying belowground residues (roots and C allocation factor of the main product, CA is the org HR rhizodeposition) was equal to NPP (2.2 Mg C below org C allocation factor of the harvest residue, CC- org -1 -1 ha yr ). This was based on the notion that in a 123 260 Nutr Cycl Agroecosyst (2020) 118:249–271 mature permanent grassland, annual root biomass where FER is the dry matter amount of grazing an growth and turnover are in a steady state. -1 -1 animals excreta (Mg ha yr ) and C is its C FER org The annual C input to grassland soils (G-IN ; -1 -1 org tot content (Mg Mg dry matter ; Table S5). -1 -1 Mg C ha yr ) was calculated as: org GIN ¼½ MU  0:45þ ½ðGNPP tot above ð15Þ Results GEX ðÞ MU  0:45Þ 0:5þ 2:22 tot where MU is the dry matter biomass mulched Net primary production on and export of organic -1 -1 -1 (Mg ha yr ), 0.45 is the C content (Mg Mg carbon from arable and grassland sites org -1 dry matter ) of aboveground biomass (Bolinder et al. 2007), G-NPP is the NPP of the grassland site The majority of crops cultivated on German arable above above -1 -1 (Mg C ha yr ), G-EX is the C export from soils between 2001 and 2015 were winter wheat, silage org tot org -1 -1 the grassland site (Mg C ha yr ), 0.5 is the factor maize, oil seed rape, and winter barley which were org respecting the 50% biomass decaying (see above), and cultivated in 65% of all arable site * years evaluated -1 -1 2.22 Mg C ha yr is the C input from (Table 2). Carbon fixation as mean annual NPP by org org tot decaying belowground residues (see above). main crops and cover crops on arable sites was -1 -1 6.9 ± 2.3 Mg C ha yr (Fig. 1). The values of org Calculation of annual carbon inputs via organic the main crops’ NPP and NPP were specific above below fertilizers and grazing animal excreta for each crop type (Table 2). On average, 74.9 ± 9.7% of NPP on arable sites was in above- tot For arable and grassland sites, the annual C input ground biomass while 25.1 ± 9.7% was allocated to org -1 -1 via organic fertilizers (FER -IN; Mg C ha yr ) roots and rhizodeposition of main crops and cover org org was calculated according to information recorded in crops. Cover crops contributed 3 ± 10% of NPP and tot the questionnaire: were grown in 11% of all arable site * years evaluated. They were most often cultivated after cereals (winter FER IN ¼ FER  DM  C ð16Þ org org FER FER barley, summer barley, winter triticale, winter rye, where FER is the fresh matter amount of the specific winter wheat) or were associated with silage maize org -1 -1 organic fertilizer applied (Mg ha yr ) where a cultivation. In this group of main crops, cover crops -3 density of 1 Mg m was assumed for all liquid were grown on an average of 16% of all site * years organic fertilizers, DM is its dry matter content evaluated (Table S6). Mean annual total C export FER org -1 -1 (Mg Mg ), CF is its C content (Mg Mg dry from arable sites via harvest of main product, harvest FER org -1 matter ) which both were obtained in a broad residues exported as side product and cover crops was -1 -1 literature search (Table S5). 3.7 ± 1.8 Mg C ha yr (Table 2, Fig. 1), of org -1 -1 To estimate the annual C input to soil from which 0.4 ± 0.8 Mg C ha yr was in side org org animal excreta on pastures and mown pastures, the products, such as straw. Harvest residues were number and species of animals on the site were exported as side product in 43% of all arable site * multiplied by excretion rates expected for species, as years evaluated (Table S6). estimated by Rosemann et al. (2017) (Table S3). When On grasslands, mean annual NPP was tot -1 -1 the respective information was not recorded, missing 5.9 ± 2.9 Mg C ha yr , which was on average org data were replaced by dividing the number and species lower than on arable sites (Fig. 1). However, NPP below of animals grazing on the entire farm (as given in all of grassland sites, which was estimated with a fixed -1 -1 cases) by the amount of grassland grazed on the farm. value of 2.2 Mg C ha yr , contributed to a larger org The annual C input to the soil via grazing animals share (average 43 ± 14% of NPP ) to NPP than on org tot tot -1 -1 excreta (FER -IN; Mg C ha yr ) was calcu- arable sites. Mean annual C export was ani org org -1 -1 lated as: 3.0 ± 2.3 Mg C ha yr (Fig. 1) of which org -1 -1 1.9 ± 1.4 Mg C ha yr was via cutting of org FER  IN ¼ FER  C ð17Þ ani ani FER meadows and mown pastures and 1.1 ± 2.2 Mg C org -1 -1 ha yr was taken up by grazing animals. Meadows 123 Nutr Cycl Agroecosyst (2020) 118:249–271 261 Table 2 Share of main crops cultivated of annual fluxes of input; values are the mean and standard deviation (SD) -1 -1 organic carbon (C ;Mg C ha yr ) as net primary calculated from the multiplication of sites and years (site * org org production (NPP) for main crops (total and belowground) and years) recorded within the German Agricultural Soil Inventory cover crops, C export via main product and via harvest and are given for crops with a minimum share of 1% across all org residues exported as side products, and plant-derived C records org Crop Share of NPP C export C input org org site * years Main crop Main crop Cover crop Main Side Fertilizer Total (%) (NPP ) (NPP ) product product total belowground Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Arable Winter wheat 26.4 7.2 1.4 1.8 0.4 0.3 0.9 3 0.6 0.8 1.0 0.3 0.7 4 1.6 Silage maize 14.1 7.7 1.7 1.5 0.3 0.3 1 5.9 1.3 0 0 1.2 1 3.2 1.4 Oil seed rape 12.2 6.8 1.5 2.0 0.4 0.1 0.4 2.2 0.5 0.1 0.3 0.3 0.6 4.9 1.3 Winter barley 11.9 6.1 1.3 1.4 0.3 0.6 1.1 2.7 0.6 0.8 0.9 0.4 0.8 3.5 1.6 Winter rye 5.9 4.7 1.8 1.1 0.4 0.4 1 1.9 0.7 0.8 0.8 0.3 0.7 2.7 1.6 Summer barley 4 4.8 1.1 1.3 0.3 0.5 1.1 2 0.5 0.5 0.6 0.3 0.6 3 1.4 Sugar beet 3.9 8.7 1.6 0.4 0.1 0.2 0.7 6.9 1.3 0 0.1 0.6 1.4 2.6 1.6 Grain maize 3.7 10.4 2.7 2.7 0.7 0.1 0.4 4.1 1.1 0.1 0.7 0.5 0.7 6.8 1.8 Winter triticale 3.3 5.5 1.5 1.1 0.3 0.5 1.1 2.3 0.6 1 0.9 0.4 0.6 3.2 1.7 Fallow 3 3.6 0.4 2.1 0.4 0 0.2 1.3 0 0 0 0 0 3.7 0.4 Potato 2.2 5.4 1.3 0.2 0.1 0.2 0.8 4.3 1 0 0 0.4 0.7 1.7 1.1 Grass without 1.4 5.7 2.2 2.5 0.6 0.1 0.5 3 1.5 0 0 0.7 0.8 3.4 1.3 legumes (whole plant) Summer oat 1.4 5.8 1.8 2.0 0.6 0.2 0.8 1.8 0.6 0.9 0.9 0.5 0.8 3.8 1.6 Grain legumes 1.1 3.5 1.8 0.7 0.4 0.3 0.8 1.3 0.7 0 0.1 0.2 0.7 2.6 1.6 Grass with 1.1 5.3 2.1 2.6 1.3 0.1 0.4 2.3 1.1 0 0 0.7 0.9 3.7 1.7 legumes (whole plant) Other crops 4.3 4.9 1.8 1.8 0.7 0.3 0.7 2.3 0.9 0.2 0.3 0.4 0.6 3.2 1.3 Average 6.6 2.1 1.6 0.4 0.3 0.9 3.2 1.7 1.1 1.1 0.5 0.8 3.7 1.8 Grassland Meadow 44.5 5.6 1.4 – – 2.8 1.2 0.0 0.0 0.7 0.9 3.5 1.0 Mown pasture 40.3 6.4 3.3 – – 3.4 2.7 0.0 0.0 1.0 1.0 4.0 1.4 Pasture 15.2 5.6 4.3 – – 2.7 3.5 0.0 0.0 0.7 0.8 3.5 1.5 Average 5.9 2.9 – – 3.0 2.4 0.0 0.0 0.8 1.0 3.7 1.3 ‘Fallow’ is not to be interpreted as bare fallow but as years of non-cultivation during which soil is covered by (volunteer) grass which is not harvested mown up to six times per year were the prevailing Carbon inputs to agricultural soils management type on grasslands (44% of all grassland Total mean annual C input to soils did not differ site * years evaluated), while pastures used only for org -1 -1 grazing represented 15% of all grassland site * years between arable (3.7 ± 1.8 Mg C ha yr ) and org -1 -1 grassland sites (3.7 ± 1.3 Mg C ha yr ) evaluated (Table 2). org (Fig. 2). Across all arable crops, NPP (R = 0.47), tot rather than C input via organic fertilizer (R = 0.11) org 123 262 Nutr Cycl Agroecosyst (2020) 118:249–271 Export or C export (R = 0.03), was the main driver of total org via C input to the soil (Figure S1). org harvest Organic The largest proportion (83 ± 23%; 3.0 ± 1.5 Mg -1 -1 C ha yr ; Fig. 2) of total mean annual C input org org to arable soils was via above- and belowground plant Net primary Input material of the main crop with 1.6 ± 0.7 Mg C org -1 -1 into soil ha yr from roots and rhizodeposition, -1 -1 0.3 ± 0.1 Mg C ha yr from stubbles, and org -1 -1 1.1 ± 1.1 Mg C ha yr from harvest residues 0.5 org Arable land 3.7 left in the field. Cover crops accounted for 5 ± 15% of the total mean annual C input to soil with on average org Main crops 6.6 -1 -1 0.3 ± 0.8 Mg C ha yr . Organic fertilizers org 3.7 accounted for 12 ± 18% of the total mean annual Cover crops 0.3 -1 C input to arable soils with 0.5 ± 0.8 Mg C ha org org -1 yr . They were applied on 71% of all arable sites and 0.8 Grassland 3.0 in 43% of all site * years evaluated and derived mainly (94%) from animals (including biogas digestates). 5.9 Among arable crops, the highest average C input org 3.7 was found for grain maize cultivation, due to very high -1 -1 average NPP (10.4 ± 2.7 Mg C ha yr ) and a tot org -1 -1 Fig. 1 Mean fluxes of organic carbon (C ,MgC ha yr ) org org low portion of C export via harvest (40%, Table 2). org on agricultural soils in Germany calculated for the multiplica- The lowest C input (lower quantile = 1%) was org tion of sites and years recorded within the German Agricultural -1 found for potato cultivation (1.1 ± 0.3 Mg C ha org Soil Inventory (arable: n = 19,987; grassland: n = 7417); for -1 grassland soils, harvest includes biomass uptake of animals and yr ) mainly due to its high harvest index of 0.83. Sites -1 -1 fertilizers include excreta of animals with very high C input ([ 7.6 Mg C ha yr ) org org (upper quantile = 99%) had a regular cover crop cultivation and/or were fertilized with compost and/or manure. As found for arable soils, the largest proportion of total mean annual C input to grassland soils was org again via plant biomass (83 ± 15% or 2.9 ± 0.5 Mg -1 -1 C ha yr ) (Fig. 2) of which the fixed value of org -1 -1 2.2 Mg C ha yr deriving from roots and org rhizodeposition had the largest share. The remaining -1 -1 0.7 ± 0.5 Mg C ha yr derived from above- org ground residues and mulching. Mulching of grassland was recorded for 2% of all grassland site * years evaluated. Organic fertilizers accounted for 17 ± 15% of total mean annual C input to grassland org -1 -1 soils with 0.8 ± 1.0 Mg C ha yr . They were org distributed on 81% of grassland sites and in 45% of all grassland site * years evaluated. This high number reflects the fact that excreta from grazing animals were considered here as organic fertilizers. Meadows Fig. 2 Sources of mean annual input of organic carbon (C )to org arable and grassland soils calculated for the multiplication of received organic fertilizers in 51% of all grassland sites and years recorded within the German Agricultural Soil site * years evaluated. There were only two cases Inventory; mean value and standard deviation. C input via org where organic fertilizers did not derive from animals roots and rhizodeposition in grassland estimated as a fixed value -1 -1 (sewage sludge, potato processing sludge). Sites with (see text for details) of 2.2 Mg ha yr and therefore shown -1 -1 without standard deviation low C input (\ 2.3 Mg C ha yr ) (lower org org 123 Nutr Cycl Agroecosyst (2020) 118:249–271 263 Fig. 3 a Annual total net primary production, organic carbon (C ) export, and total C input, and b C input via cover crops and organic fertilizers of org org org animals’ origin to arable (n = 2097) and grassland (n = 718) soils in Germany, calculated as mean value of sites sampled within the German Agricultural Soil Inventory 264 Nutr Cycl Agroecosyst (2020) 118:249–271 Fig. 3 continued Nutr Cycl Agroecosyst (2020) 118:249–271 265 Fig. 4 Spatial distribution of crop cultivation on arable land in Germany, shown as proportion of the specific crop in the crop rotation, calculated for sites sampled within the German Agricultural Soil Inventory 266 Nutr Cycl Agroecosyst (2020) 118:249–271 quantile = 1%) were characterized by low yield level NPP was still visible in the map showing the spatial tot and no organic fertilization. Sites with a high C distribution of C input (Fig. 3a), confirming NPP org org tot -1 -1 input ([ 7.6 Mg C ha yr ) (upper quan- as a strong driver for C input. org org tile = 99%) were pastures with high animal grazing density or received a large amount of organic fertilizer and/or had a high yield level expressed as high number Discussion of cuts per year. More than half of carbon assimilated is exported from Spatial distribution of net primary production German agricultural soils and inputs and exports of organic carbon Based on our method, mean annual NPP on tot arable sites in Germany was estimated 6.9 Mg C org -1 -1 The highest NPP and C export values were ha yr and was slightly higher than on grasslands tot org -1 -1 obtained for north-west and south-east Germany (5.9 Mg C ha yr ) despite the fact that grass- org (Fig. 3a). Figure 4 shows the spatial distribution of lands are characterized by permanent vegetation the crops most often cultivated, i.e., winter wheat, cover and, thus, potentially maximized C-assimila- silage maize, oilseed rape, sugar beet, grain maize, and tion. This is well in line with global estimates of other winter cereals. Each of the crops is preferentially NPP . Using the earth surface model LPJ, Haberl tot grown in certain areas, which partly explains the et al. (2007) estimated mean annual global NPP of tot -1 -1 spatial pattern of NPP found in this study. In 6.1 Mg C ha yr on arable land and 4.9 Mg tot org -1 -1 particular, the distribution of silage maize cultivation C ha yr on grazing land. The higher values we org explains the high values of NPP and C export in obtained in the present study might be due to tot org north-west and south-east Germany. The C input intensive management regime in German agriculture org from cover crops was also highest in these areas and to generally fertile and relatively young soils. (Fig. 3b), most likely driven by high precipitation Management, e.g. fertilization, and differences in (mean annual precipitation of, e.g., 910 mm in pedoclimatic site properties are the most important Bavaria in contrast to the German average of drivers for the differences in NPP between arable tot 771 mm; mean values of 1881–2019 of Deutscher land and grassland. Grasslands in Germany are Wetterdienst 2020) and the specific crop rotation characterized by a range of management intensities, (maize-dominated). North-west and south-east Ger- from unmanaged to intensively managed, whereas many are also areas of high livestock density, arable sites are mostly intensively managed and explaining the high amounts of C input via organic fertilized. Further, a large proportion of permanent org fertilizers (Fig. 3b). Regions with the most fertile grasslands in Germany are established in conditions soils, such as the young moraine soils of north-east that do not favor cultivation of arable crops, e.g., on Germany and the central German chernosem area, wet soils in floodplains, shallow and stony soils, and were dominated by the cultivation of winter wheat and colder mountainous regions. oilseed rape. In these regions, the major source of C On average, 53% of the NPP on arable sites was org tot input to soil was harvest residues left in the field. In the found to be exported each year. Of this exported C org central German chernosem area in particular, but also portion, 11% was in harvest residues which were in large parts of eastern Germany, cover crops did not exported as side products. This fact was strongly crop- play any role in the crop rotation. This can be dependent: Aboveground biomass of crops dedicated explained by the lower annual precipitation, e.g., with for forage or energy production, e.g. silage maize, an average of 566 mm and 600 mm in Brandenburg does not deliver any side products, while harvest and Mecklenburg-Western Pomerania (mean values of residues of cash crops other than cereals, such as 1881–2019 of Deutscher Wetterdienst 2020). More- oilseed rape, sugar beet or potatoes, are completely left over, crop rotations in those areas are winter crop- on the site (Table S6). Among all cereals, 40% of all dominated. arable site * years evaluated, which is equivalent to Finally, C input was more regionally variable 42% of all cereal straw biomass (not shown), was org and site-specific than C assimilation by plants, recorded with an export of straw as side product. This estimated here as NPP . However, the pattern of value is somewhat larger than the 27–38% estimated tot 123 Nutr Cycl Agroecosyst (2020) 118:249–271 267 in a review on biomass potentials in Germany by soils (Hu et al. 2019) on the other hand. However, the Brosowski et al. (2016). Of the C portion exported, type of C serving as C input varies considerably org org org only 15% ended up in organic fertilizers returned to between the two land use systems. The C input to org arable soils as C input. This is comparable to other grassland soils was dominated by root-derived C org org estimates for Europe showing 47% of NPP being and the proportion was on average 1.4 times higher in tot exported via harvest of arable crops and 10% of NPP the grassland than in the arable soils. This is in line tot being returned as organic fertilizers (Schulze et al. with Pausch and Kuzyakov (2018) who reported that 2009). German grasslands are characterized by high annual crops allocate less C belowground (21%) org productivity and a relatively high portion of NPP than grassland specimen (33%). However, it needs to tot being exported (51%). At European scale, it was be noted that we used a fixed value for root-derived estimated that only 37% of grassland NPP is exported C in grasslands (see below). Root-derived C was tot org org via harvest (Schulze et al. 2009), which underlines the reported to contribute more to SOC stabilization as high intensity of German grassland usage. Of the C shoot-derived C for various reasons including org org portion exported, 27% ended up in organic fertilizers higher chemical recalcitrance, physical protection by (including animal excreta) returned to grassland soils as aggregates (Rasse et al. 2005 and papers cited therein) aC input. On a global scale, Haberl et al. (2007) and microbial C-use efficiency (Sokol and Bradford org estimated that the proportion of NPP harvested was 2019). For example, Ka¨tterer et al. (2011) reported a tot 83% on arable land and 19% on grazing land. This 2.3 times higher stabilization rate of roots compared indicates that C export via harvest is subject to with shoots in a Swedish long-term field experiment. org uncertainties and strongly region-specific. Further, in our study, C input to soil via organic org Total organic carbon inputs into soils do not differ fertilizers (mainly animal manure) was 1.6 times between land use systems higher on grassland than on arable sites. Manure was The C input to arable soils estimated by our also reported to build up SOC at a higher rate than org -1 -1 method was slightly higher (3.7 Mg ha yr ) than fresh aboveground harvest residues, e.g. straw, estimated for Swedish arable soils: Andren et al. (Katterer et al. 2011) since the labile C fraction is org (2008) estimated C inputs in a range of 3.3 Mg C preferentially decomposed and already lost during gut org org -1 -1 -1 ha yr in the south of Sweden to 2.6 Mg C ha passage and storage of manure. Straw was found to org -1 yr in the north. Considering the climate advantages have a retention rate of about 10% or less (Lemke et al. for crop cultivation in Germany compared to Sweden, 2010), while manure often reached retention rates of C inputs estimated in the present study were up to 30% (Ka¨tterer et al. 2011) with a global average org comprehensible. Across arable crops, we found that of 12% (Maillard and Angers 2014). C input to soil was strongly driven by NPP , while An adapted method for estimation of organic org tot neither input as organic fertilizer nor C export carbon inputs to soils in Central Europe org correlated with C input. Thus, in the context of The C input estimation method we developed is a org org increasing SOC stocks for climate change mitigation, revised version of allocation coefficients previously maximizing NPP , e.g., by cover crop cultivation, has published (Bolinder et al. 2007; Gan et al. 2009;Li tot a considerable potential to increase C input to soils. et al. 1997) adapted to regional conditions. For arable org We found no difference between mean annual C sites, we used regional harvest indices and the latest org -1 -1 input to arable soils (3.7 Mg C ha yr ) and to findings on rhizodeposition (Pausch and Kuzyakov org -1 -1 grassland soils (3.7 Mg C ha yr ). This was 2018). However, recent studies claim that appyling org surprising, since SOC stock measured in the top yield-dependent ratios of NPP to NPP in C above below org 0–30 cm layer on the sites evaluated here was on input estimation methods might be an average 1.4 times higher in mineral soils under oversimplification. -1 grassland (89 ± 36 Mg C ha ) than under arable Such findings were clear and reliable for grassland org -1 use (62 ± 30 Mg C ha ; for details see Jacobs specimen for which several independent studies org et al. 2018). This difference was often explained by the showed that NPP is not a function of NPP below above reduced physical disturbance (tillage) of grassland in managed grasslands (Ammann et al. 2009; Cong soils which enhances SOC storage (Six et al. 2000)on et al. 2019; Poeplau et al. 2018; Sochorova´ et al. 2016) the one hand and by higher C inputs to grassland and that the ratio of NPP to NPP can vary org above below 123 268 Nutr Cycl Agroecosyst (2020) 118:249–271 greatly upon management intensity and yield. Thus, The size and representativeness of the dataset used the application of a yield-dependent ratio of NPP in this study to estimate management related C above org to NPP would most likely cause large errors for fluxes on German agricultural soils make it unique. below the estimation of NPP (Poeplau 2016). This was Yield data are usually available on strongly aggre- below supported by a recent publication of Taghizadeh- gated scales or for certain crops only or they are gained Toosi et al. (2020) who also claimed that using a fixed from experimental sites that do not reflect commercial value for belowground C input in leys improved agriculture. Field-scale fertilization or residue man- org SOC model simulations for several long-term field agement data are scarcely available at all. Here, we experiments compared to the application of a fixed took the opportunity to comprehensively analyze a ratio of NPP to NPP for the estimation of decade-long dataset obtained directly from about 1% above below belowground C inputs. Thus, for grassland sites, we of all German farmers through a questionnaire. Due to org made a fundamental change regarding the conven- this unique dataset and the region-specific method we tional estimation of belowground C input based on a developed, the present study delivered the first robust org ratio of NPP to NPP : We adopted the estimates of C-assimilation (NPP ) and C inputs above below tot org assumption of a fixed value for NPP and made and exports from German agricultural soils. Anyway, below use of a large German dataset of a related study of results are subject to two sources of uncertainty: one Poeplau et al. (2018). Based on these results, we related to the dataset as such and the other related to assumed a fixed average root-derived C input of assumptions used in the method. We hold that the org -1 -1 2.2 Mg C ha yr . This value is supported by priority for improvement of the method is to continue org Ammann et al. (2009) who measured root C stocks with crop- and site-specific quantification of root org -1 of 2.3 and 2.1 Mg C ha in intensively and biomass in arable land and grasslands, as critical org extensively managed Swiss grassland, respectively. component of total plant-derived C input to soils. org For arable crops, recent findings are less profound: It was shown in two Swiss and one British field trial that maize and wheat have a much stronger above- Conclusions ground than belowground response to fertilization (Hirte et al. 2018; Taghizadeh-Toosi et al. 2016) and a Our study revealed that maximizing plant productiv- fixed root-C input value was regarded more robust ity, measured as NPP, has the greatest potential to org for wheat (Taghizadeh-Toosi et al. 2016). However, at maximize C inputs to soil and thus SOC stocks in org this current point of research, it is impossible to agriculture. Any decrease in plant productivity, e.g. deduce reliable values replacing conventional C due to climate change induced droughts, threatens org allocation coefficients by fixed root-C input for current SOC stocks. Surprisingly, total C inputs did org org arable crops. Such values are not available for the not vary between grasslands and croplands, suggesting majority of crops but crop types differ strongly in that large differences in SOC stocks usually observed physiology. Thus, we decided to stick to the conven- between both land use types cannot be explained by tional assumption well proven by Bolinder et al. differences in total C inputs. Quality and allocation org (2007) and provided regionally sound mean values of of C input matter and point toward a pivotal role of org NPP (equal root-C input) as a starting point for roots for building SOC. A more profound understand- below org future research. A SOC modeling study on German ing of the stabilization rates and pathways of various arable long-term monitoring sites using five different C input sources is thus necessary. We recommend org C input estimation methods (Riggers et al. 2019) using the method and data presented here for Central org supported this procedure: C input estimated by the European agricultural soils as it complies the up-to- org here presented regional approach led to lower model date data sources available for this region. Yet, more errors than the original one of Bolinder et al. (2007). field studies are needed to further improve C input org This is most likely because the latter summarized estimates. For example, the role of different pedocli- studies mainly from North America. To summarize, matic regions as well as cultivars on allocation the C inputs we calculated for German arable and coefficients and C input estimates are widely org org grassland soils can be regarded as most reliable. neglected to date. The latter might be especially relevant for comparisons between organic and 123 Nutr Cycl Agroecosyst (2020) 118:249–271 269 Weihenstephan. https://www.lfl.bayern.de/mam/cms07/ conventional farms, since organic agriculture uses ipz/dateien/bayernplan_einsatz_von_biogas_zum_ersatz_ with different cultivars. The role of breeding on von_gaskraftwerken_ag1.pdf. Accessed 29 March 2018 allocation coefficients and, thus, root derived C org Baldauf S, Bergmeister S (2006) Abbauverhalten von aus- input is poorly understood. The C input to soil is a gewa¨hlten organischen Schadstoffen in org Kla¨rschlammkomposten bei vera¨nderten Rotteparametern. large C-flux that is directly controlled by agricultural Diploma, Ho¨here Technische Bundeslehr- und Versuch- management. All efforts to maintain or increase SOC sanstalt Dornbirn stocks can only be successful when we understand the Bayrische Landesanstalt fu¨r Landwirtschaft (LfL) (2011) Inte- effects of agricultural management of this flux in grierter Pflanzenbau–Zwischenfruchtanbau. https://www. lfl.bayern.de/mam/cms07/publikationen/daten/ detail. informationen/p_28819.pdf. Accessed 18 Dec 2017 BIOS Bioenergies GmbH (2018) Biomass. http://www.ieabcc. Acknowledgements This study was funded by the German nl/database/biomass.php. Accessed 29 March 2018 Federal Ministry of Food and Agriculture in the framework of Bolinder MA, Janzen HH, Gregorich EG, Angers DA, Van- the German Agricultural Soil Inventory. We thank the field and denBygaart AJ (2007) An approach for estimating net laboratory teams of the German Agricultural Soil Inventory for primary productivity and annual carbon inputs to soil for their thorough and persistent work. Special thanks also to all common agricultural crops in Canada. Agric Ecosyst farmers taking part within the Agricultural Soil Inventory. Environ 118:29–42. https://doi.org/10.1016/j.agee.2006. 05.013 Open Access This article is licensed under a Creative Com- Bolinder MA, Katterer T, Poeplau C, Borjesson G, Parent LE mons Attribution 4.0 International License, which permits use, (2015) Net primary productivity and below-ground crop sharing, adaptation, distribution and reproduction in any med- residue inputs for root crops: potato (Solanum tuberosum ium or format, as long as you give appropriate credit to the L.) and sugar beet (Beta vulgaris L.). Can J Soil Sci original author(s) and the source, provide a link to the Creative 95:87–93. https://doi.org/10.4141/cjss-2014-091 Commons licence, and indicate if changes were made. The Brosowski A, Thran D, Mantau U, Mahro B, Erdmann G, Adler images or other third party material in this article are included in P, Stinner W, Reinhold G, Hering T, Blanke C (2016) A the article’s Creative Commons licence, unless indicated review of biomass potential and current utilisation: status otherwise in a credit line to the material. If material is not quo for 93 biogenic wastes and residues in Germany. included in the article’s Creative Commons licence and your Biomass Bioenergy 95:257–272. https://doi.org/10.1016/j. intended use is not permitted by statutory regulation or exceeds biombioe.2016.10.017 the permitted use, you will need to obtain permission directly Chenu C, Angers DA, Barre´ P, Derrien D, Arrouays D, Bales- from the copyright holder. 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