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To gain insight in the environmental impacts of crop, soil and nutrient management, an integrated model framework INITIATOR was developed predicting: (i) emissions of ammonia (NH3) and greenhouse gases (GHG) from agriculture, including animal husbandry and crop production and (ii) accumulation, leaching and runoff of carbon, nutrients (nitrogen, N, phosphorus, P, and base cations) and metals in or from soils to groundwater and surface water in the Netherlands. Key processes in soil are included by linear or non-linear process formulations to maintain transparency and to enable data availability for spatially explicit application from field up to national level. Calculated national trends in nutrient losses over 2000–2020 compared well with independent estimates and showed a reduction in N and P input of 26 to 33 %, whereas the surplus declined by 33 % for N and 86 % for P due to increased crop yields and reduced inputs. This was accompanied by a reduction of 30–35 % in atmospheric emissions of ammonia and nitrous oxide as well a decline in N and P runoff of 35 and 10 %, respectively, whereas the emission of methane increased with 4 %. Model results compared well with (i) large scale observations of ammonia concentrations in air and nitrate concentrations in upper groundwater and ditch water, (ii) with nitrous oxide emissions and phosphorus adsorption in experiments at field scale and (iii) with metal adsorption in large scale soil datasets. Various mitigation measures were evaluated in view of policy ambitions for climate, soil and environmental quality for 2030, i.e. a reduction of 50 % for NH3, 11–17 % for GHG, 20 % for N runoff and 40 % for P runoff and an ambition of 50 % GHG emission reduction for 2050. The measures focused on a combination of animal feeding, low emission housing and application technologies, improved crop, soil and nutrient management, all being applied with an effectiveness of 100 % and 50 %, respectively. In addition, we evaluated impacts of 50 % livestock reduction, and combination scenarios of measures and livestock reduction. Full implementation of all measures can reduce NH3 emission, N leaching and N runoff by approximately 40–50 % and GHG emissions by approximately 30 %, but there is less potential to reduce P runoff, being

The main hurdle in instrumentalizing agricultural soils to sequester atmospheric carbon is the development of methods to measure soil carbon stocks which are robust, scalable, and widely applicable. Our objective is to develop an approach that can help overcome these hurdles. In this paper, we present the Wageningen Soil Carbon STOck pRotocol (SoilCASTOR). SoilCASTOR uses a novel approach fusing satellite data, direct proximal sensing-based soil measurements, and machine learning to yield soil carbon stock estimates. The method has been tested and applied in the USA on fields with agricultural land use. Results show that the estimates are precise and repeatable and that the approach could be rapidly scalable. The precision of farm C stocks is below 5% enabling detection of soil organic carbon changes desired for the 4 per 1000 initiative. The assessment can be done robustly with as few as 0.5 sample per hectare for farms varying from 20 to 150 hectares. These findings could enable the structural implementation of carbon farming.

There is a global need to improve the environmental performances and circularity of livestock production systems. This relates also to poultry production systems in China, however, the benefits of optimized, more circular systems have not been quantified. Here, we applied a substance flow analysis to estimate the reactive nitrogen (Nr) losses and greenhouse gas (GHG) emissions from housing, manure processing and manure application to cropland in a conventional decoupled and an optimized coupled crop-poultry system. We hypothesized that an optimized coupled system has lower Nr losses and GHGs emissions, and a higher economic return for farmers. We used data from experimental measurements, a farm survey, literature and local market prices to estimate the farm performance for both systems. In the conventional system the manure was only partly (58%) utilized and the remaining 42% was wasted and discharged into the environment. In the optimized system a series of emission mitigation measures was adopted, including low-protein feeding, manure composting with additives and a partial replacement of synthetic fertilizers by manure. The optimized system produced 24% more products per 100 units of N input, leading to a whole-system nitrogen use efficiency (NUE) increase from 33% to 50%. The Nr losses per unit of product-N decreased by 55%, whereas the GHG emissions (N2O and CH4) decreased by 35%. Moreover, the net economic benefit increased by 21%. Evidently, the optimized and more circular system had significant economic and environmental benefits compared to the conventional one. These benefits will be drivers for the transformation to more sustainable production systems, but governmental policy incentives will be needed to remove current cultural and institutional barriers.

The crucial role of healthy soil in achieving sustainable food production and environment is increasingly recognized, as is the importance of proper assessment of soil quality. We introduce a new framework, open soil index (OSI), which integrally evaluates soil health of agricultural fields and provides recommendation for farming practices. The OSI is an open-source modular framework in which soil properties, functions, indicators and scores, and management advice are linked hierarchically. Soil health is evaluated with respect to sustainable crop production but can be extended to other ecosystem functions. The OSI leverages the existing knowledge base of agronomic research and routine laboratory data, enabling its application with limited cost. The OSI is a generic framework that can be adopted for specific regions with specific objectives. As a proof of concept, the OSI is implemented for all (>700,000) Dutch agricultural fields and illustrated with 11 pairs ("good"and "poor") of local fields and 32 fields where soil quality and crop yield have been monitored. The OSI produced reasonable evaluation for most pairs when soil physical functions were refined with on-site soil visual assessment. The soil functions are sufficiently independent and yet together reflect complex multidimensionality of soil quality. The framework can facilitate designing sustainable soil management programs by bridging regional targets to field-level actions.

Agricultural management practices have multiple impacts on farming systems, including crop yield, soil fertility parameters such as soil organic carbon (SOC), and environmental quality. Agricultural decision support tools (DSTs) are key in sustainable farm strategies to optimize yield and minimize environmental losses because both the current agroecosystem properties as well as the effectiveness of management practices are highly variable in time and space. Here, we introduce a highly data-driven framework focusing on the evaluation of agronomic measures to reach agronomic and environmental targets. We demonstrate the potential of this approach by a proof of principle for 81 selected farm types across Europe, focusing on measures with respect to crop rotation, fertilization and soil tillage. Synthesizing data from long-term experiments and meta-analytical models, we estimated the impact of these measures on crop yield, SOC and N surpluses, while accounting for site-specific properties for the current and desired situation. The impacts of these measures on all farm types have been quantified, and optimum sets of agronomic measures have been selected in order to maximize crop yield and SOC levels and minimize N surpluses to reach the critical values for NO3− concentrations in groundwater. Our results, quantifying trade-offs among sustainability indicators that have traditionally been analyzed separately, illustrate that the suitability of measures varies by soil, climate and crop types within Europe. Our approach is promising for mapping region-specific management recommendations and evaluating the effectiveness of agronomic measures over multiple environmental goals and targets. Highlights: We find a lack of empirical-based DSTs holistically assessing agronomic practices and indicators. Meta-analytical models were used to assess impacts of best fertilizer, tillage and crop measures. Our multi-criteria analysis shows impacts vary with crop, soil and climate in European regions. We demonstrate our developed framework focusing on crop yield, soil carbon and nitrogen losses.

Enhanced nitrogen (N) and phosphorus (P) fertilizer applications have strongly elevated agricultural productivity, but also caused significant soil acidification (by N) and increased N and P losses to water bodies leading to eutrophication. There is an urgent need to integrate soil acidification amendment and nutrient management strategies to stimulate sustainable soil use and minimize environmental risks. This study aimed to derive the optimal combination of fertilizer, manure and lime to mitigate soil acidification and minimize nutrient losses by assessing the impacts of different nutrient management strategies on soil pH and nutrient budgets at a field level. The dynamic soil acidification model VSD+ was calibrated on measured pH changes in a long-term fertilization experiment (1990–2018), in which variable amounts of inorganic N, P and potassium (K), lime (L) and organic manure (M) were applied annually to a maize-wheat rotation on red soil. Adding NPK inorganic fertilizers only sharply decreased the soil pH by 1.5 units within 10 years. The pH remained relatively constant, however, in the experiment in which 70% of the N given by fertilizer was replaced by manure (NPKM) while lime addition after 20 years of NPK addition (NPKL) increased the pH by approximately 1.5 units. Historic soil pH changes were well reconstructed by VSD+. The model quantified that nitrogen transformations contributed up to 89% of the total acidity production in the NPK treatment, which could be fully neutralized by replacing 70% of the total N fertilizer input with manure. Scenarios were assessed to explore the future impacts of adapted nutrient management on soil acidification and nutrient surplus. Balancing the N and P input with crop demand (BNP) significantly reduces the N and P surplus but hardly affects the acidification rate compared to Business as Usual (BAU, equal to the NPK treatment). Balancing the N input and substituting N fertilizer with manure (BM) counteract acidification and maintain the optimal soil pH of 6.5 but strongly increase the annual P surplus. An optimized combination of fertilizer, manure and lime (OPT) was thus identified to minimize acidification and unnecessary P accumulation in soils, by balancing crop N, P and base cation (BC) demands and unavoidable N and BC leaching. We conclude that the VSD+ model can be used as a sustainable nutrient and acid management tool to derive optimal application rates of fertilizer, manure and lime in agricultural systems.

Soil carbon sequestration (SCS) refers to the uptake of carbon (C) containing substances from the atmosphere and its storage in soil C pools. Soil microbial community (SMC) play a major role in C cycling and their activity has been considered as the main driver of differences in the potential to store C in soils. The composition of the SMC is crucial for the maintenance of soil ecosystem services, as the structure and activity of SMC also regulates the turnover and delivery of nutrients, as well as the rate of decomposition of soil organic matter (SOM). Quantifying the impact of agricultural practices on both SMC and SCS is key to improve sustainability of soil management. Hence, we discuss the impact of farming practices improving SCS by altering SMC, SOM, and soil aggregates, unraveling their inter-and intra-relationships. Using quantitative and process driven insights from 197 peer-reviewed publications leads to the conclusion that the net benefits from agricultural management to improve SCS would not be sustainable if we overlook the role of soil microbial community. Reintroduction of the decayed microbial community to agricultural soils is crucial for enhancing long-term C storage potential of soils and stabilize them over time. The interactions among SMC, SOM, soil aggregates, and agricultural activities still require more knowledge and research to understand their full contribution to the SCS.

Human activities have drastically increased nitrogen (N) deposition onto forests globally. This may have alleviated N limitation and thus stimulated productivity and carbon (C) sequestration in aboveground woody biomass (AGWB), a stable C pool with long turnover times. This 'carbon bonus' of human N use partly offsets the climate impact of human-induced N2 O emissions, but its magnitude and spatial variation are uncertain. Here we used a meta-regression approach to identify sources of heterogeneity in tree biomass C-N response (additional C stored per unit of N) based on data from fertilization experiments in global forests. We identified important drivers of spatial variation in forest biomass C-N response related to climate (potential evapotranspiration), soil fertility (N content) and tree characteristics (stand age), and used these relationships to quantify global spatial variation in N-induced forest biomass C sequestration. Results show that N deposition enhances biomass C sequestration in only one-third of global forests, mainly in the boreal region, while N reduces C sequestration in 5% of forests, mainly in the tropics. In the remaining 59% of global forests, N addition has no impact on biomass C sequestration. Average C-N responses were 11 (4-21) kg C per kg N for boreal forests, 4 (0-8) kg C per kg N for temperate forests and 0 (-4 to 5) kg C per kg N for tropical forests. Our global estimate of the N-induced forest biomass C sink of 41 (-53 to 159) Tg C yr-1 is substantially lower than previous estimates, mainly due to the absence of any response in most tropical forests (accounting for 58% of the global forest area). Overall, the N-induced C sink in AGWB only offsets ~5% of the climate impact of N2 O emissions (in terms of 100-year global warming potential), and contributes ~1% to the gross forest C sink.

Widespread adoption of improved cropland management measures is advocated to increase soil organic carbon (SOC) levels, thereby improving soil fertility and mitigating climate change. However, spatially explicit insight on management impacts is limited, which is crucial for region-specific and climate-smart practices. To overcome these limitations, we combined global meta-analytical results on improved management practices on SOC sequestration with spatially explicit data on current management practices and potential areas for the adoption of these measures. We included (a) fertilization practices, i.e., use of organic fertilizer compared to inorganic fertilizer or no fertilizer, (b) soil tillage practices, i.e., no-tillage relative to high or intermediate intensity tillage, and (c) crop management practices, i.e., use of cover crops and enhanced crop residue incorporation. We show that the estimated global C sequestration potential varies between 0.44 and 0.68 Gt C yr-1 , assuming maximum complementarity among all measures taken. A more realistic estimate, not assuming maximum complementarity, is from 0.28 to 0.43 Gt C yr-1 , being on the lower end of the current range of 0.1-2 Gt C yr-1 found in the literature. One reason for the lower estimate is the limited availability of manure that has not yet been recycled. Another reason is the limited area for the adoption of improved measures, considering their current application and application limitations. We found large regional differences in carbon sequestration potential due to differences in yield gaps, SOC levels, and current practices applied. The highest potential is found in regions with low crop production, low initial SOC levels, and in regions where livestock manure and crop residues are only partially recycled. Supporting previous findings, we highlight that to encourage both soil fertility and SOC sequestration, it is best to focus on agricultural soils with large yield gaps and/or where SOC values are below levels that may limit crop production.

Maize production in Zambia is characterized by significant yield gaps attributed to nutrient management and climate change threatens to widen these gaps unless agronomic management is optimized. Insights in the impacts of climate change on maize yields and the potential to mitigate negative impacts by crop management is currently lacking for Zambia. Using five Global Circulation models and the WOFOST crop model, we assessed expected climate change and the impacts on maize yields at a 0.5° × 0.5° spatial resolution for RCP 4.5 and RCP 8.5 scenarios. Impacts were assessed for two future periods (i.e. near future: 2035–2066 and far future: 2065–2096) in comparison with a reference period (1971–2001). The average surface temperature and summer days (above 30°C) are projected to increase strongly in the southern and western regions. Precipitation is expected to decline, except in the northern regions while the number of wet days decline everywhere, indicating a shortening growing season. The risk of crop failure in western and southern regions increases due to dry spells and heat stress while crops in the northern regions will be threatened by flooding or waterlogging due to heavy precipitation. The simulated decline in the water limited and water- and nutrient- limited maize yields varied from ca 15–20% in the near future and from ca 20–40% in the far future, mainly due to the expected temperature increases. Optimizing management by adjusting planting dates and maize varieties can counteract these impacts by 6–29%. Quantitatively, the existing gaps between water limited yields and nutrient limited maize yields are substantially larger than the expected yield decline due to climate change. Improved nutrient management is therefore crucial to avoid crop yield decline and might even increase crop yields in Zambia.

Tillage is a common agricultural practice and a critical component of agricultural systems that is frequently employed worldwide in croplands to reduce climatic and soil restrictions while also sustaining various ecosystem services. Tillage can affect a variety of soil-mediated processes, e.g., soil carbon sequestration (SCS) or depletion, greenhouse gas (GHG) (CO2, CH4, and N2O) emission, and water pollution. Several tillage practices are in vogue globally, and they exhibit varied impacts on these processes. Hence, there is a dire need to synthesize, collate and comprehensively present these interlinked phenomena to facilitate future researches. This study deals with the co-benefits and trade-offs produced by several tillage practices on SCS and related soil properties, GHG emissions, and water quality. We hypothesized that improved tillage practices could enable agriculture to contribute to SCS and mitigate GHG emissions and leaching of nutrients and pesticides. Based on our current understanding, we conclude that sustainable soil moisture level and soil temperature management is crucial under different tillage practices to offset leaching loss of soil stored nutrients/pesticides, GHG emissions and ensuring SCS. For instance, higher carbon dioxide (CO2) and nitrous oxide (N2O) emissions from conventional tillage (CT) and no-tillage (NT) could be attributed to the fluctuations in soil moisture and temperature regimes. In addition, NT may enhance nitrate (NO3−) leaching over CT because of improved soil structure, infiltration capacity, and greater water flux, however, suggesting that the eutrophication potential of NT is high. Our study indicates that the evaluation of the eutrophication potential of different tillage practices is still overlooked. Our study suggests that improving tillage practices in terms of mitigation of N2O emission and preventing NO3− pollution may be sustainable if nitrification inhibitors are applied.

Sustainable agricultural management implies optimization of resources for crop production while minimizing adverse impacts on the environment. This requires a better understanding of the synergies and trade-offs of agronomic management while accounting for the controlling effects of site-specific factors (covariates). We systematically evaluated 113 meta-analytical studies assessing impacts of crop management measures (rotation, cover cropping, residue retention), soil and water measures (irrigation, tillage), soil amendments (enhanced efficiency, biochar), fertilizer use (organic, mineral, combined organic-mineral) and “4R'” fertilizer strategies (right source, rate, timing, placement) on sustainability indicators. These indicators include crop yield, crop N and P (content, uptake, and use efficiency), soil quality indicators (soil organic C, N and P contents, compaction), soil emissions of ammonia (NH3) and greenhouse gases (CO2, N2O), and nutrient losses to water (N and P surplus or leaching). Nutrient management, including 4R practices as well as enhanced efficiency amendments, had the largest impact, increasing crop yields and N uptake while reducing N2O and NH3 emissions as well as N surplus, whereas effects on CO2 emissions were variable. Although all measures positively impacted soil C, the largest effect was due to biochar, followed by organic fertilizer input. Biochar positively impacted crop yield, diminished N2O and NH3 emissions as well as N surplus, and increased CO2 emissions. Within crop management, only cover cropping had a significant positive effect on crop yield, while both cover crops and rotation slightly enhanced N uptake and the sequestration of C and N in soil, thus reducing N2O emissions and N surplus. Minimal tillage practices generally increased SOC, while results for crop yield, N surplus and N2O emissions were variable. Site-specific factors had substantial impacts on the evaluated impacts of measures, most importantly climate, crop type, soil texture, soil pH, soil organic C, N dose, and experimental duration. Considering the variation among meta-analytical protocols followed, we recommend that field studies and meta-analytical work adhere to harmonized guidelines with respect to the reporting of site-level data, experimental design, and the statistical procedures used. This will ensure data comparability between studies, improve the quality of meta-analysis results, and give better insights into currently uncertain or unknown impacts of agronomic measures.

Liming is a long-established and widely used agricultural practice to ameliorate soil acidity and improve crop production. Sustainable liming strategies for regional applications require information on both lime requirements and liming intervals given land use and soil dependent acidification rates. We developed a method to optimize lime requirements and liming intervals at regional level. Lime requirements were based on soil pH buffering capacity and liming intervals were estimated by ongoing soil acidity production, derived from major cations and anions balances in cropland systems. About 66% of croplands in Qiyang required liming to raise soil pH to 6.5, with a total lime requirement of 2.4 × 105 t CaCO3, with an average rate of 2.4 t ha−1 for paddy soils and 2.6 t ha−1 for upland soils. The remaining 34% were mainly calcareous soils. Nutrient management practices and crop rotations, affecting N transformation and crop removal, were the main drivers controlling the spatial variation in total acid production in non-calcareous soils, on average contributing 73% and 25%, respectively. Under current soil acidification rates, 33% of Qiyang's croplands would need liming within 30 years after raising the soil pH to 6.5. Averaged liming interval was 20 years, and 6.8 t ha−1 would be required to maintain soil pH ranges between 5.5 and 6.5. Areas with high soil acidification risk were mostly located in the southeast of Qiyang.

Functional genes involved in nitrogen (N) cycling regulate soil nitrification, denitrification and N2O emissions. However, the general patterns and variability of N functional genes in response to N addition, and their association with N2O emission have not been synthesized for terrestrial ecosystems. We synthesized 2068 observations from 144 papers to explore the impact of N addition on the abundance and diversity of N functional genes, and their relationship to N2O emissions in croplands, grasslands and forests on a global scale. In croplands, N addition increased N2O emissions (109%), the abundance of ammonia-oxidizing archaea (AOA) (19%), ammonia-oxidizing bacteria (AOB) (95%), nirK (52%), nirS (40%) and nosZ (41%), and the diversity of AOB (15%), nirS (12%) and nosZ (11%). In grassland, N addition increased AOB abundance (130%) and decreased the abundance of nirS (−99%) and nosZ (−58%) genes, but in forests, significant effects were only found for the abundance of AOA (35%) and AOB (121%). N2O emission was negatively correlated with the abundance of nosZ, but positively correlated with the abundance of AOA and AOB. Apart from the abundance of functional AOA, AOB and nosZ genes, climate variables (precipitation and temperature), and available N concentrations were the main factors explaining the variation in N2O emission with N addition, as shown by random forest analysis. These findings indicate that impacts on N functional genes that encode enzymes involved in nitrification (AOA, AOB) and in the transformation of N2O to N2 (nosZ) are the main mechanisms behind the effect on N fertilizer-induced N2O emissions.

Towards the end of 2017, the ministry of Economic Affairs organized a hackathon to produce smart solutions for the manure problem in the Netherlands. The winning team came up with an innovative concept that utilizes the innovative powers of entrepreneurs by means of smart, area directed management of manure and minerals. The concept is named MaxiMi, short for ‘Maximal environmental performance by Minimal (government) effort’. MaxiMi has the ambition to renew the present input directed manure policy by means of a result oriented approach, in which the quality of water (both in the soil and on its surface) directs agricultural management. This means a shift from Compliance to Environmental Performance and at the same time a shift from public to private direction (control and maintenance) with possibilities for horizontal supervision by authorities. The approach uses sensors and a data based (and self-learning) machine learning system, which couples parcel properties, soil management and fertilization (read: measures) to water quality in the area. In this way, MaxiMi offers a fact based action perspective to the entrepreneur and stimulates sustainable management. Besides the data will be available for advisory services directed at effective management decisions. In this way the innovation power of the agricultural sector will be deployed to integrate agricultural enterprise objectives with water quality objectives for the area. Eind 2017 heeft het ministerie van EZ een hackathon georganiseerd om slimme oplossingen te bedenken voor het mestprobleem in Nederland. Het winnende team kwam met een innovatief concept dat de innovatiekracht van ondernemers benut met slim gebiedsgericht beheer van mest en mineralen. Het concept heet MaxiMi, een afkorting voor ‘Maximale Milieuprestatie met Minimale (overheids)inspanning’. MaxiMi heeft de ambitie om de huidige input gestuurde mestaanpak te vernieuwen via een resultaatgestuurde benadering, waarbij de waterkwaliteit (voor zowel grond als oppervlaktewater) sturend is voor het agrarisch management. Dit betekent een verschuiving van Compliance naar Environmental Performance en tevens van publieke naar private sturing (controle en handhaving), met mogelijkheden voor horizontaal toezicht door de overheid. De aanpak maakt gebruik van sensoren én een op data gebaseerd (en zelflerend) machine learning systeem waarmee perceelskenmerken, bodembeheer en bemesting (lees: maatregelen) gekoppeld worden aan de waterkwaliteit in het gebied. MaxiMi biedt zo een op feiten gebaseerd handelingsperspectief voor de ondernemer en stimuleert duurzaam management. De data zijn daarnaast beschikbaar voor adviesdiensten gericht op effectieve managementbeslissingen. Zo wordt de innovatiekracht van de sector ingezet om landbouwkundige bedrijfsdoelen te integreren met gebiedsdoelen voor waterkwaliteit.

Extractable organic matter (EOM) fractions have been used to assess the capacity of soils to supply nitrogen (N), but their role in N mineralization and their potential to improve agricultural fertilizer management are still under debate. This paper shows evidence that the relationship between EOM and soil N supply is an indirect relationship reflecting the soils' organic matter content. Data from 59 published experiments were re-analyzed using multivariate PLS modelling. Nitrogen mineralization was primarily related to the size of total and extractable organic matter fractions whereas variables reflecting soil texture and organic matter quality were less important. All EOM fractions reflected the soil organic matter content of the soil rather than a specific bioavailable fraction. There is strong need for research that explores the biochemical basis for relationships among total organic matter, extractable organic matter and soil N mineralization using mechanistic approaches.

Amino acids can interfere with NH4+ in spectrophotometric NH4+ determination hampering accurate quantification of the fate of NH4+ and dissolved organic N in soils. Serious interference has been reported for soils rich in organic matter, and for soils that have been fumigated, oven-dried or fertilized where between 5 and 60% of the NH4+ detected could be attributed to amino acid interference. We investigated whether a combination of gas diffusion and the classical Berthelot method can eliminate this interference, increasing the selectivity of the NH4+ analysis. We tested this approach using synthetic amino acid solutions and a large set of terrestrial samples (n = 353), including pore water samples, (fumigated or dried) soil extracts, and extracts of manures, composts and crop residues. The evaluated method produced accurate (recovery > 99.7%) and reproducible (standard error = 2.2%) NH4+ concentrations, eliminating any interference between amino acids and NH4+ (interference

Distinct extractable organic matter (EOM) fractions have been used to assess the capacity of soils to supply nitrogen (N). However, substantial uncertainty exists on their role in the N cycle and their functional dependency on soil properties. We therefore examined the variation in mineralizable N and its relationship with EOM fractions, soil physical and chemical properties across 98 agricultural soils with contrasting inherent properties and management histories. Mineralizable N was determined by aerobic incubation at 20 °C and optimum moisture content for 20 weeks. We used multivariate statistical modelling to account for multi-collinearity, an issue generally overlooked in studies evaluating the predictive value of EOM fractions. Mineralization of N was primarily related to the size of OM pools and fractions present; they explained 78% of the variation in mineralizable N whereas other soil variables could explain maximally 8%. Both total and extractable OM expressed the same soil characteristic from a mineralization perspective; they were positively related to mineralizable N and explained a similar percentage of the variation in mineralizable N. Inclusion of mineralizable N in fertilizer recommendation systems should be based on at least one OM variable. The most appropriate EOM fraction can only be identified when the underlying mechanisms are known; regression techniques are not suitable for this purpose. Combination of single EOM fractions is not likely to improve the prediction of mineralizable N due to high multi-collinearity. Inclusion of texture-related soil variables or variables reflecting soil organic matter quality may be neglected due to their limited power to improve the prediction of mineralizable N.

Accurate estimation of mineralizable nitrogen (N) from soil organic matter is essential to improve fertilizer management in agricultural systems. Mineralizable N refers to the amount of N in soil that is released during a certain period (ranging from 1 week to the length of a growing season). It has been estimated from increases in inorganic N during incubation or from N uptake by plants grown in a greenhouse or field. Many chemical soil tests measuring extractable organic N (EON) fractions have been proposed to predict mineralizable N. We evaluated the predictive value of these soil tests, using 2068 observations from 218 papers. Meta-analysis was used to find the best soil test, to analyse differences between field and laboratory experiments, and to determine whether their predictive value is affected by extraction intensity (% of total soil N that is extracted). The concentration of EON was positively related to mineralizable N, explaining on average 47% of the variation. It did not, however, explain more of the variation than total N. Best predictions (57%

International audience; The release of dissolved organic matter (DOM) from agricultural land can have a large impact on the transport of N and phosphorus (P) to surface waters leading to water quality impairment. The speciation of DOM in agricultural grassland soils has received little attention thus far. Quantification of DOM speciation can improve our knowledge of its fate in these soils. Furthermore, the influence of temperature on DOM concentration and composition is still ambiguous. In this study, we determined the concentration and composition of water-extractable organic carbon (EOC), water-extractable organic N (EON), and water-extractable organic P (EOP) before and after incubation of sand, peat, and clay grassland soils at different temperatures (1.5 °C, 10 °C, and 20 °C) for 35 days. Extracted organic compounds were fractioned in three operationally defined fractions: humic acids (HA), fulvic acids (FA), and hydrophilic (Hy) compounds using a recently developed batch fractionation method. Both EON and EOP formed a major fraction of total N and P. Concentrations of EOC, EON, and EOP were different among the sand, peat, and clay soils, but their speciation was remarkably similar. The EOC and EON were mainly present in the hydrophobic form (HA and FA), whereas EOP was mainly present in the Hy fraction. An increase in temperature generally resulted in a decrease of the total EOC, EON, and EOP concentrations, whereas the speciation remained constant. The effect of temperature on the dynamics of DOM is not necessarily related to net changes in pool size of the HA, FA, and Hy fractions. Insight into the influence of incubation temperature on the dynamics of EOC, EON, and EOP can only be achieved when the processes responsible for the consumption and the production of dissolved organic nutrients are quantified.

An important source of nitrogen (N) for crops is mineralization of soil organic matter during the growing season. Awareness is growing that dissolved organic nitrogen (DON) plays an important role in mineralization and plant uptake. We studied the influence of temperature and time on extractable organic nitrogen (EON) levels, which is a measure of DON, and their relationship with N mineralization. Aerobic incubation experiments were conducted in the laboratory for five soils at different temperatures (4 20, and 30 °C) and different time intervals with optimal water content (60% of its water-holding capacity). Net N mineralization ranged between 14 and 155 mg kg-1 within 84 days and was correlated with the initial amount of EON. Net N mineralization among the soils, time, and incubation temperatures was linearly related to the square root of time multiplied by temperature, with mineralization rate k being independent of time and temperature. Because initial EON values were also related to these kvalues, we were able to describe the net N mineralization at different temperatures based on an analysis of initial EON. Preliminary validation with results from pot experiments in the literature suggests that the approach is promising, although the proposed model needs to be calibrated with more soils

Determination of the isotopic signature of dissolved organic nitrogen (DON) is important to assess its dynamics in terrestrial ecosystems. Analysis of (15)N-DON, however, has been hindered by the lack of simple, reliable, and established methods. We evaluate three off-line techniques for measuring the (15)N signature of DON in the presence of inorganic N using a persulfate digestion followed by microdiffusion. The (15)N-DON signature is calculated from the difference between total dissolved (15)N ((15)N-TDN) and inorganic (15)N. We quantified the (15)N recovery and signature of DON, NH(4)(+), and NO(3)(-) in a series of inorganic N/DON mixtures (with a TDN concentration of 10 mg N L(-1)) for three lab protocols. Phenylalanine was used as a model compound for DON. The best lab protocol determined the concentration of inorganic N and TDN prior to diffusion using improved spectrophotometric techniques. An accuracy of 88% for (15)N-DON should be routinely possible; coefficient of variation was2.9%. Hence, reliable (15)N-DON values are obtained over an DON concentration range of 2.3-10 mg L(-1). High levels of DON could influence the accuracy of (15)N-NO(3)(-) mainly at DON:NO(3)(-) ratios above 0.4. Evaluation of alternative NO(3)(-) measurements is still necessary. Our method is applicable for soil solution samples and soil extracts and has no risk of cross-contamination. Potential applications are large, in particular for (15)N tracer studies, and will increase our insight in DON behavior in soils.

Extractable Organic N (EON) or Dissolved Organic Nitrogen (DON) pools are often analyzed to predict N mineralisation, N leaching, and to evaluate agricultural (nutrient) management practices. Size and characteristics of both pools, however, are strongly influenced by methodology. Quantifying the influence of methodology can increase the accuracy of soil tests to predict N mineralisation, improve model simulations, and can help to quantify the contribution of the EON and DON pools to soil N cycling. We estimated the relative impact of methodological, management, and environmental factors on EON and DON, using a meta-analysis approach based on 127 studies. Our results indicate that the EON and DON pools are neither similar in size nor controlled by the same factors. The influence of factors controlling EON generally decreased in the order of methodology (Δ10–2400%), followed by environment (Δ11–270%) and management (Δ16–77%). DON concentrations were primarily controlled by management factors: different land use and fertilisation caused a variation of 37–118%. Seasonal variations in DON concentrations were generally smaller than variations in EON, suggesting that high mineralisation and sorption rates buffer DON. The large range in EON as affected by different methodology emphasizes the importance of using appropriate and standardized methods for the determination of EON. The determination of DON can be useful to estimate leaching losses. EON, however, can be used to assess the impact of soil management practices on the turnover rate of labile soil organic matter pools.