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Background: Earthworms are important for maintaining soil ecosystem functioning and serve as indicators of soil fertility. However, detection of earthworms is time-consuming, which hinders the assessment of earthworm abundances with high sampling density over entire fields. Recent developments of mobile terrestrial sensor platforms for proximal soil sensing (PSS) provided new tools for collecting dense spatial information of soils using various sensing principles. Yet, the potential of PSS for assessing earthworm habitats is largely unexplored. This study investigates whether PSS data contribute to the spatial prediction of earthworm abundances in species distribution models of agricultural soils., Methodology/principal Findings: Proximal soil sensing data, e.g., soil electrical conductivity (EC), pH, and near infrared absorbance (NIR), were collected in real-time in a field with two management strategies (reduced tillage / conventional tillage) and sandy to loam soils. PSS was related to observations from a long-term (11 years) earthworm observation study conducted at 42 plots. Earthworms were sampled from 0.5 x 0.5 x 0.2 m³ soil blocks and identified to species level. Sensor data were highly correlated with earthworm abundances observed in reduced tillage but less correlated with earthworm abundances observed in conventional tillage. This may indicate that management influences the sensor-earthworm relationship. Generalized additive models and state-space models showed that modelling based on data fusion from EC, pH, and NIR sensors produced better results than modelling without sensor data or data from just a single sensor. Regarding the individual earthworm species, particular sensor combinations were more appropriate than others due to the different habitat requirements of the earthworms. Earthworm species with soil-specific habitat preferences were spatially predicted with higher accuracy by PSS than more ubiquitous species., Conclusions/significance: Our findings suggest that PSS contributes to the spatial modelling of earthworm abundances at field scale and that it will support species distribution modelling in the attempt to understand the soil-earthworm relationships in agroecosystems.

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

• MAOM-C content was modeled for arable fields with different management. • Organic fertilization, crop rotation, and soil texture define MAOM-C content. • A POM-C/MAOM-C ratio indicator was developed and tested. • This indicator contains information on MAOM-C saturation deficits. • POM-C/MAOM-C ratio indicators might support climate mitigation strategies. Soil organic matter (SOM) is indispensable for soil health and, in the context of climate change, is considered a significant CO 2 sink. Improving agricultural management to increase long-term soil organic carbon (SOC) stocks for mitigating climate change requires tools that estimate short and long-cycling SOM pools. In this study, we analyzed changes in fast-cycling particulate organic matter (POM) and slow-cycling mineral-associated organic matter (MAOM) induced by common management practices, i.e., fertilization and crop rotation in topsoils from 25 Central European long-term field experiments. When relating MAOM-C contents to recent MAOM-C saturation levels, estimated sequestration potentials were only met in coarse-textured soils under appropriate agricultural management or fine-textured soils under extreme organic fertilization. Soil texture, organic fertilization, and below-ground OC inputs through root exudates and root biomass were decisive for estimating MAOM-C, allowing for calibration of a mixed-effects model (Nakagawa's: marginal R2 m = 0.6, conditional R2 c = 0.89). While the models containing soil texture and organic fertilization parameters can be validated and generalized (R2 = 0.43), the below-ground OC input predictor substantially decreases the generalizability of the validated models (R2 = 0.14). According to quantile regression models, we estimate the average difference in MAOM-C concentration between well-managed and control site (without organic fertilization) topsoils to 4.1 mg g−1 soil. In dependence on the soil bulk density, this amounts to 1.38 – 1.84 t ha−1 MAOM-C stocks or 5.06 – 10.1 t ha−1 CO 2 -equivalents. POM-C was difficult to predict (R2 = 0.28), presumably due to strong POM dynamics. The POM-C / MAOM-C ratio can inform on the effects of agricultural practices in before/after management change comparisons. Under increasing SOC concentration, an increasing POM-C / MAOM-C ratio indicates that the effects of organic fertilization do not transfer to real effects on long-term SOC sequestration. Because MAOM-C depends on soil texture, this ratio is also a covariate of soil texture, limiting it for comparisons between sites with different textures. However, our data indicate that agricultural long-term field experiment soils constantly approximate MAOM-C saturation when the POM-C/MAOM-C ratio is >0.35. This ratio might be used as a management goal to prevent organic over-fertilization and N loss, especially on coarse-textured soils. Thereby, the POM-C / MAOM-C ratio can help to optimize SOC management and sequestration on agricultural soils and support climate change mitigation strategies in Central Europe. [ABSTRACT FROM AUTHOR]

Abstract: Since earthworms are of functional importance in soils, understanding their sensitivity to tillage is of importance for the design of sustainable management systems. The effect of reduced, ploughless tillage on earthworm abundance was explored during a 10-year observational study on a producer’s field on sandy soil. The analysis of tillage effects is complicated by the fact that earthworms are not only affected by tillage but also by soil properties. We analyzed the spatial distribution pattern of earthworms (Lumbricidae) in a heterogeneous 74ha field in Northeast Brandenburg, Germany. Earthworm populations were assessed by means of handsorting along 4 transects on 42 permanent plots which were partly under conventional, partly under reduced tillage. Different earthworm activity parameters were calculated for each plot and related to soil properties such as soil texture and organic carbon in 0 to 15cm. In addition, paired plots were analyzed at both sides of the dividing line between the tillage systems. The analysis of paired plots indicated that finer textured soils react more positively to tillage reduction than sandy soils. State-space analysis confirmed that soil texture was important in all cases for estimating earthworm parameters along the transects. Organic carbon in 0 to 15cm, indicative of the tillage system, was an especially important predictor for maximal abundances of earthworms in the year 2000. Our observations also suggest higher spatial variability of earthworm abundances and closer relationships between earthworms and soil texture under reduced tillage. For separating soil from management effects in landscape scale studies, approaches are promising which take into account the spatial variability of soil properties and soil biota. [Copyright &y& Elsevier]

Agricultural management can influence soil organic carbon (SOC) stocks and thus may contribute to carbon sequestration and climate change mitigation. The soil depth to which agricultural management practices affect SOC is uncertain. Soil depth may have an important bearing on soil carbon dynamics, so it is important to consider depth effects to capture fully changes in SOC stocks. This applies in particular to the evaluation of carbon farming measures, which are becoming increasingly important due to climate change. We sampled and analysed the upper metre of mineral cropland soils from ten long-term experiments (LTEs) in Germany to quantify depth-specific effects on SOC stocks of common agricultural management practices: mineral nitrogen (N) fertilisation, a combination of N, phosphorus (P) and potassium (K) fertilisation, irrigation, a crop rotation with preceding crops (pre-crops), straw incorporation, application of farmyard manure (FYM), liming, and reduced tillage. In addition, the effects of soil compaction on SOC stocks were examined as a negative side effect of agricultural management. Results showed that 19 ± 3 % of total management effects on SOC stocks were found in the upper subsoil (30–50 cm) and 3 ± 4 % in the lower subsoil (50–100 cm), including all agricultural management practices with significant topsoil SOC effects, while 79 ± 7 % of management effects were in the topsoil (0–30 cm). Nitrogen and NPK fertilisation were the treatments that had the greatest effect on subsoil organic carbon (OC) stocks, followed by irrigation, FYM application and straw incorporation. Sampling down to a depth of 50 cm resulted in significantly higher SOC effects than when considering topsoil only. A crop rotation with pre-crops, liming, reduced tillage and soil compaction did not significantly affect SOC stocks at any depth increment. Since approximately 20 % of the impact of agricultural management on SOC stocks occurs in the subsoil, we recommend soil monitoring programs and carbon farming schemes extend their standard soil sampling down to 50 cm depth to capture fully agricultural management effects on SOC. • Ten 32- to 112-year-old long-term experiments were sampled down to 100 cm depth. • Sampling only topsoil ignores 20 % of agricultural management effects on SOC stocks. • Mineral fertilisation had the greatest effect on subsoil organic carbon stocks. • None of the agricultural measures had significant effects deeper than 50 cm. • Standard soil sampling should therefore be extended to 50 cm depth. [ABSTRACT FROM AUTHOR]

• Arable measures bear high potential to affect topsoil SOC stocks. • Mineral and organic fertilization, straw incorporation caused major SOC gain. • Liming and reduced tillage had little or even negative effects on SOC storage. • Sandy soils exhibited the largest relative response to management options. • Up to 10‰ SOC accrual per year were reached by combination of measures. Crop production often leads to soil organic carbon (SOC) losses. However, under good management practice it is possible to maintain and even re-accumulate SOC. We evaluated how different cropland management techniques affected SOC stocks in the topsoil (0–30 cm depth) of 10 long-term experiments (LTE) in Germany. We found that SOC stocks were particularly enhanced by mineral fertilization and organic amendments like straw incorporation and to a smaller degree by irrigation, but only slightly affected by the choice of preceding crops. In agreement with global meta -analyses, liming and reduced tillage had little or even negative effects on SOC storage, but effects also depended on fertilization. Management effects on SOC stocks were dependent on soil texture: sandy soils showed the lowest SOC stocks of 20.9 ± 2.3 (standard error of the mean) Mg ha−1, but exhibited the largest relative response to different management options. Annual changes in SOC stocks ranged from −3.0 ‰ with no mineral N fertilization, to + 6.1 ‰ with farmyard manure application, using the mineral-fertilized and limed treatment as reference. Even higher rates of up to + 10.6 ‰ yr−1 were reached with the combination of irrigation and straw incorporation. Note that the contribution of organic amendments to SOC accrual and thus to climate change mitigation must be adjusted for reduction in SOC at sites from which straw was removed. Overall, the potential of agricultural management to influence and enhance SOC stocks is significant. This potential is controlled by soil type and land-use duration, is largest for sandy soils with overall lowest SOC stocks, and is characterized by antagonistic and synergistic effects of different management practices. [ABSTRACT FROM AUTHOR]