It has long been established that earthworms beneficially affect plant growth. This is to a large extent due to the high fertility of their casts. However, it is not clear how fertile casts are ...compared to bulk soil, and how their fertility varies between earthworm feeding guilds and with physico-chemical soil properties. Using meta-analysis, we quantified the fertility of earthworm casts and identified its controlling factors. Our analysis included 405 observations from 81 articles, originating from all continents except Antarctica. We quantified cast fertility by determining the enrichment of earthworm casts relative to the bulk soil (“relative cast fertility”; RCF) for total organic carbon (TOC), total phosphorus (P) and total nitrogen (N) concentrations, as well as for plant available pools of N (total mineral N) and P (available P: P-Olsen, P-Bray or comparable metrics), C-to-N ratio and microbial biomass C. In addition to these response variables, we studied four additional ones closely related to soil fertility: pH-H2O, clay content, cation exchange capacity (CEC), and base saturation. With the exception of C-to-N ratio, microbial C and clay content, all studied response variables were significantly increased in casts compared to the bulk soil. Increases in total elemental concentrations (TOC, total P and total N), which are the result of preferential feeding or concentration processes, were comparable and ranged between 40 and 48%. Nutrient availability, which is to a large extent the result of (bio)chemical transformation processes in the earthworm gut, was increased more strongly than total elemental concentrations (241% and 84% for mineral N and available P, respectively). Increases in pH (0.5 pH units), cation exchange capacity (40%), and base saturation (27%) were also large and significant. None of the soil-related possible controlling factors could satisfactorily explain the variation in RCF; plant presence (or other sources of organic C input such as residue application) was the only controlling factor that consistently increased RCF across soil properties. With the exception of available P, none of the studied response variables could be linked to earthworm feeding guild. Our results show that earthworm casts are much more fertile than bulk soil for almost all analysed cast fertility properties. However, these positive RCFs are to a large extent dependent upon the presence of plants. In general, earthworm feeding guild or specific physico-chemical soil properties could not explain the large variability in RCF for the various response variables. Therefore, we hypothesize that RCF effects depend on intricate interactions between earthworm species traits and specific soil properties. Understanding these interactions requires trait-based approaches combined with mechanistic modelling of biochemical processes in the earthworm gut and casts.
•We analysed fertility of earthworm casts using a meta-analysis of 81 articles.•Casts contain on average 40–48% more total P, total N and organic C than bulk soil.•Available N and available P are even more increased (241% and 84%, respectively).•Relative Cast Fertility (RCF) is strongly dependent on presence of plants or residues.•A combination of trait-based analysis and modelling is needed to better predict RCF.
Global society faces serious “phosphorus challenges” given the scarcity, essentiality, unequal global distribution and, at the same time, regional excess of phosphorus (P). Phosphorus flow studies ...can be used to analyze these challenges, providing insight into how society (re)uses and loses phosphorus, identifying potential solutions.
Phosphorus flows were analyzed in detail for EU-27 and its Member States. To quantify food system and non-food flows, country specific data and historical context were considered. The sectors covered were crop production (CP), animal production (AP), food processing (FP), non-food production (NF) and consumption (HC).
The results show that the EU-27 imported 2392GgP in 2005, half of which accumulated in agricultural soils (924Gg) and half was lost as waste (1217Gg). Net accumulation was 4.9kgP/ha/year ranging between +23.2 (Belgium) and −2.8 (Slovakia). From the system losses, 54% was lost from HC in diverse waste flows and 28% from FP, mainly through incinerated slaughter residues. The largest HC losses (655Gg) were wastewater (55%), food waste (27%), and pet excreta (11%). Phosphorus recycling rates were 73% in AP, 29% in FP, 21% in HC and ~0% in NF. The phosphorus use efficiencies showed that, relative to sector input, about 70% was taken up by crops (CP), 24% was retained in animals (AP), 52% was contained in food products (FP), 76% was stored in non-food materials (NF), and 21% was recycled (HC).
Although wide-ranging variation between countries, generally phosphorus use in EU-27 was characterized by relatively (1) large dependency on (primary) imports, (2) long-term accumulation in agricultural soils, especially in west European countries, (3) leaky losses throughout entire society, especially emissions to the environment and sequestered waste, (4) little recycling with the exception of manure, and (5) low use efficiencies, because of aforementioned issues, providing ample opportunities for improvement.
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•Phosphorus (P) flows were analyzed in detail for EU-27 and its Member States.•The food consumption–production–waste chain and non-food flows were considered.•The EU-27 is characterized by large P-rock import and long-term P soil accumulation.•Large P losses exist, especially emissions to the environment and sequestered waste.•The relatively low recycling and efficiency provide opportunities for improvement.
Soil quality evaluation as a decision-making tool to improve understanding of soil quality is essential for grading croplands and adopting proper agricultural practices. Various methods of soil ...quality evaluation have been developed, which have occasionally generated inconsistent evaluation results between differing soil types. The applicability of these techniques is seldom tested before implementing an evaluation method on a specific soil region. Fluvisol is an important soil resource for agriculture in China, especially for irrigation districts along the lower Yellow River. In the present study, the soil quality of two typical agricultural counties (Yucheng and Kenli) along the lower Yellow River was evaluated using four commonly utilized methods. In the two counties, the overall spatial patterns of soil quality derived from the four methods were similar, with differences in details existing among these methods. The soil quality in Yucheng, ranging from moderate to high, is superior to that observed in Kenli, where salinity is the primary limiting factor. In addition, the applicability of soil quality evaluation methods on the Fluvisol was investigated. It was found that the integrated quality indexing-linear scoring (IQI–LS) and the Nemoro indexing-linear scoring (NQI–LS) methods were the most accurate and practical of the four methods studied. These methods, which are based on the total data set of indicators, show better performance for soil quality evaluation on a Fluvisol. Further, different evaluation methods based on the minimum data set of indicators were compared, considering both the accuracy of the evaluation and the economic cost of obtaining the soil data. The results from the present study indicate that the IQI–LS method based on the minimum data set of indictors is recommended for large-scale soil quality evaluations.
•Four soil quality evaluation methods were compared for a Fluvisol.•IQI–LS and NQI–LS methods performed better in soil quality evaluations.•For large-scale studies, the IQI–LS based on a minimum data set is recommended.
The improvement in the agricultural production through continuous and heavy nutrient input like nitrogen fertilizer under the upland red soil of south China deteriorates soil quality, and this ...practice in the future could threaten future food production and cause serious environmental problems in China. This research is initiated with the objectives of evaluating the impacts of long-term chemical nitrogen fertilization on soil quality, crop yield, and greenhouse gas emissions, with insights into post-lime application responses. Compared to sole application of chemical nitrogen fertilization, combined application with lime increased soil indicators (pH by 6.30 %-7.76 %, Ca2+ by 90.06 %-252.77 %, Mg2+ by 184.47 %-358.05 %, available P by 5.05 %-30.04 %, and soil alkali hydrolysable N by 23.49 %-41.55 %. Combined application of chemical nitrogen fertilization with lime (NPCa (0.59), NPKCa (0.61), and NKCa (0.27) significantly improved soil quality index compared to the sole application of chemical nitrogen fertilization (NP (0.31), NPK (0.36), and NK (0.16). Compared to sole application of chemical nitrogen fertilization, combined application with lime increased grain yield by 48.36 %-61.49 %. Structural equation modeling elucidated that combined application of chemical nitrogen fertilization and lime improved wheat grain yield by improving soil quality. Exchangeable Ca2+, exchangeable Mg2+, pH, and exchangeable Al3+ were the most influential factors of wheat grain yield. Overall, the combined application of chemical nitrogen fertilization and lime decreased global warming potential (calculated from N2O and CO2) by 16.92 % emissions compared to the sole application of chemical nitrogen fertilization. Therefore, liming acidic soil in upland red soil of South China is a promising management option for improved soil quality, wheat grain yield, and mitigation of greenhouse gas emissions.The improvement in the agricultural production through continuous and heavy nutrient input like nitrogen fertilizer under the upland red soil of south China deteriorates soil quality, and this practice in the future could threaten future food production and cause serious environmental problems in China. This research is initiated with the objectives of evaluating the impacts of long-term chemical nitrogen fertilization on soil quality, crop yield, and greenhouse gas emissions, with insights into post-lime application responses. Compared to sole application of chemical nitrogen fertilization, combined application with lime increased soil indicators (pH by 6.30 %-7.76 %, Ca2+ by 90.06 %-252.77 %, Mg2+ by 184.47 %-358.05 %, available P by 5.05 %-30.04 %, and soil alkali hydrolysable N by 23.49 %-41.55 %. Combined application of chemical nitrogen fertilization with lime (NPCa (0.59), NPKCa (0.61), and NKCa (0.27) significantly improved soil quality index compared to the sole application of chemical nitrogen fertilization (NP (0.31), NPK (0.36), and NK (0.16). Compared to sole application of chemical nitrogen fertilization, combined application with lime increased grain yield by 48.36 %-61.49 %. Structural equation modeling elucidated that combined application of chemical nitrogen fertilization and lime improved wheat grain yield by improving soil quality. Exchangeable Ca2+, exchangeable Mg2+, pH, and exchangeable Al3+ were the most influential factors of wheat grain yield. Overall, the combined application of chemical nitrogen fertilization and lime decreased global warming potential (calculated from N2O and CO2) by 16.92 % emissions compared to the sole application of chemical nitrogen fertilization. Therefore, liming acidic soil in upland red soil of South China is a promising management option for improved soil quality, wheat grain yield, and mitigation of greenhouse gas emissions.
Sampling and analysis or visual examination of soil to assess its status and use potential is widely practiced from plot to national scales. However, the choice of relevant soil attributes and ...interpretation of measurements are not straightforward, because of the complexity and site-specificity of soils, legacy effects of previous land use, and trade-offs between ecosystem services. Here we review soil quality and related concepts, in terms of definition, assessment approaches, and indicator selection and interpretation. We identify the most frequently used soil quality indicators under agricultural land use. We find that explicit evaluation of soil quality with respect to specific soil threats, soil functions and ecosystem services has rarely been implemented, and few approaches provide clear interpretation schemes of measured indicator values. This limits their adoption by land managers as well as policy. We also consider novel indicators that address currently neglected though important soil properties and processes, and we list the crucial steps in the development of a soil quality assessment procedure that is scientifically sound and supports management and policy decisions that account for the multi-functionality of soil. This requires the involvement of the pertinent actors, stakeholders and end-users to a much larger degree than practiced to date.
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•We review soil quality and related concepts in terms of definitions and assessment.•The most common indicators are organic matter, pH, available P and water storage.•Biological/biochemical indicators are under-represented but show great potential.•Soil quality assessment should specify targeted soil threats, functions and ecosystem services.•Increasingly interactive assessment tools must be developed with target users.
•Minimum data set includes four factors, which reflect the integrated soil function.•Significant differences in soil quality between different productivity.•The significant positive correlation ...between SQI and wheat yield.•Available N, SOM and microbial biomass N to total N ratio were limiting factors.
The double-cropping of winter wheat and summer maize is a major grain production system in China which occupies more than half the double-cropping systems of the country’s dryland area. This cropping system has experienced a decreased crop yield and soil quality and the limiting factors are poorly known. The goal of this study was to conduct a systematic evaluation of wheat yield and soil quality from 132 fields along a regional scale in China. The specific objectives were (i) to establish a minimum data set (MDS) in wheat phase under the wheat-maize cropping system (ii) to evaluate soil quality of the wheat field and determine the factors limiting wheat productivity. The wheat-maize cropping system was partitioned into three productivity levels (high, medium and low) according to the wheat yield. Twenty-six soil indicators, including soil microbiological, chemical and physical factors were measured and analyzed. Using Pearson correlation analysis we identified eight key soil indicators that determine wheat yield. We then used principal component analysis to determine an MDS, which included soil organic matter, alkali-hydrolyzable nitrogen, the ratio of microbial biomass nitrogen to total nitrogen, and available zinc. One-way analysis of variance based on the individual contribution of each MDS indicators under three productivity, revealed available nitrogen, soil organic matter and the ratio of microbial biomass nitrogen to total nitrogen was the most important indicators on limiting wheat yield. A soil quality index (SQI) based on scoring and weighting of MDS indicators was integrated as a tool for assessing farmland soil quality. Based on the MDS, high (HP), medium (MP) and low (LP) productivity received mean SQI of 0.55, 0.48 and 0.39, respectively. The significant positive correlation between SQI and wheat yield suggests that this is a good representative of the MDS for the wheat-maize cropping system in China. We conclude that our SQI may be an effective and practical tool to guide a strategic, regional goal with respect to sustainable high yields.
•Organic input can improve soil quality by the interaction of soil properties.•Use animal-derived organic fertilizer had better soil quality than plant-derived.•AP, AN, GP and AK were selected as a ...minimum data set for evaluating soil quality.•Information from soil indicators is integrated into a standardization framework.•Appropriate methods of scoring and weighting are determined in the framework.
Organic fertilizer applications can increase soil fertility and productivity and reduce chemical fertilizer use. However, few experimental studies have focused on effects of organic fertilizers on soil quality in a field ecosystem. The overarching goal of this study was to develop a soil quality index (SQI) for fertilization management in red soil farmland in China. The specific objectives were to determine 1) appropriate soil quality indicators, 2) a suitable weight assignment method (PCA, principal component analysis or MRA, multiple regression analysis) and 3) the optimal scoring function (standard or linear or non-linear). We analyzed 40 soil physical, chemical, biochemical and biological properties under nine fertilization treatments (CK (no fertilizer), CF (chemical fertilizer), RF (60% chemical fertilizer), CFS (chemical fertilizer + straw), RFS (60% chemical fertilizer + straw), CFB (chemical fertilizer + biochar), RFB (60% chemical fertilizer + biochar), RFP (60% chemical fertilizer + pig manure), RFV (60% chemical fertilizer + vermicompost)) as potential soil quality indicators. Principal component analysis and correlation analysis were applied to determine the indicators responsive to management and for the confirmation of the six SQIs. Available phosphorous, nitrogen, potassium and gram-positive bacteria were chosen as the minimum data set from the total of 40 soil indictors. Management of organic and inorganic fertilizers affected each soil property in different ways, and the index based on the minimum data set, calculated using standard scoring function and weight assignment method of multiple regression analysis, was most accurate and sensitive. Application of a pig manure or vermicompost significantly increased SQI values relative to other treatments, followed by straw or biochar treatments which were higher than a single application of chemical fertilizer. These results indicate that the addition of organic fertilizers will not only improve soil quality, but also enhance rapeseed and sweet potato yield compared to chemical fertilizers. Additionally, the SQI method can provide a practical and quantitative tool for the evaluation of soil quality.
Soil organisms are a crucial part of the terrestrial biosphere. Despite their importance for ecosystem functioning, few quantitative, spatially explicit models of the active belowground community ...currently exist. In particular, nematodes are the most abundant animals on Earth, filling all trophic levels in the soil food web. Here we use 6,759 georeferenced samples to generate a mechanistic understanding of the patterns of the global abundance of nematodes in the soil and the composition of their functional groups. The resulting maps show that 4.4 ± 0.64 × 10
nematodes (with a total biomass of approximately 0.3 gigatonnes) inhabit surface soils across the world, with higher abundances in sub-Arctic regions (38% of total) than in temperate (24%) or tropical (21%) regions. Regional variations in these global trends also provide insights into local patterns of soil fertility and functioning. These high-resolution models provide the first steps towards representing soil ecological processes in global biogeochemical models and will enable the prediction of elemental cycling under current and future climate scenarios.
Amazonian Dark Earths (ADE) are anthropic soils that are enriched in carbon (C) and several nutrients, particularly calcium (Ca) and phosphorus (P), when compared to adjacent soils from the Amazon ...basin. Studies on ADE empower the understanding of complex pre-Columbian cultural development in the Amazon and may also provide insights for future sustainable agricultural practices in the tropics. ADE are highly variable in size, depth and soil physico-chemical characteristics. Nonetheless, the differentiation between ADE and the adjacent soils is not standardized and is commonly done based on visual field observations. In this regard, the pretic horizon has been recently proposed as an attempt to classify ADE systematically. Spatial modelling techniques can be of great use to study the structure of the spatial variation of soil properties in highly variable areas. Here, we predicted the carbon and nutrients stocks in ADE by applying spatial modelling techniques using an environmental covariate (i.e. expected anthropic enrichment gradient) in our model. In addition, we used the pretic horizon criteria to classify pretic and non-pretic areas and evaluate their relative contribution to the total stocks. In this study, we collected soil samples from five 20-cm soil layers at n = 53 georeferenced points placed in a grid of about 10 to 60 m spacing in a study area located in Central Amazon (~9.4 ha). Ceramic fragments were weighed and quantified. Samples were analysed for: Total C, Total Ca, Total P, Exchangeable Ca + Mg, Extractable P, soil pH, potential CEC (pH = 7.0) and the clay content. The use of the pretic horizon criteria allowed us to clearly distinguish two unambiguous areas with a sharp transition, rather than a smooth continuum, in contrast to previous studies in ADE. Depth- and profile-wise linear regression model parameters indicated a greater importance of the chosen environmental covariate (i.e. expected anthropic enrichment gradient) to explain the spatial variation of Total Ca and Total P stocks than Total C stocks. The overall Total Ca and Total P stocks were twice as large in the pretic area when compared to the non-pretic area.
•Carbon and nutrients stocks in ADE were predicted using an environmental covariate.•Total Ca and P contents exhibited better fit to our model than Total C content.•Pretic horizon criteria enabled the differentiation of two unambiguous areas.•Pretic relative contribution was higher for Total Ca and P than Total C stocks.
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