Abstract
In this paper we present effects of four paired agricultural management practices (organic matter (OM) addition versus no organic matter input, no-tillage (NT) versus conventional tillage, crop rotation versus monoculture, and organic agriculture versus conventional agriculture) on five key soil quality indicators, i.e., soil organic matter (SOM) content, pH, aggregate stability, earthworms (numbers) and crop yield. We have considered organic matter addition, no-tillage, crop rotation and organic agriculture as “promising practices”; no organic matter input, conventional tillage, monoculture and conventional farming were taken as the respective references or “standard practice” (baseline). Relative effects were analysed through indicator response ratio (RR) under each paired practice. For this we considered data of 30 long-term experiments collected from 13 case study sites in Europe and China as collated in the framework of the EU-China funded iSQAPER project. These were complemented with data from 42 long-term experiments across China and 402 observations of long-term trials published in the literature. Out of these, we only considered experiments covering at least five years. The results show that OM addition favourably affected all the indicators under consideration. The most favourable effect was reported on earthworm numbers, followed by yield, SOM content and soil aggregate stability. For pH, effects depended on soil type; OM input favourably affected the pH of acidic soils, whereas no clear trend was observed under NT. NT generally led to increased aggregate stability and greater SOM content in upper soil horizons. However, the magnitude of the relative effects varied, e.g. with soil texture. No-tillage practices enhanced earthworm populations, but not where herbicides or pesticides were applied to combat weeds and pests. Overall, in this review, yield slightly decreased under NT. Crop rotation had a positive effect on SOM content and yield; rotation with ley very positively influenced earthworms’ numbers. Overall, crop rotation had little impact on soil pH and aggregate stability − depending on the type of intercrop; alternatively, rotation of arable crops only resulted in adverse effects. A clear positive trend was observed for earthworm abundance under organic agriculture. Further, organic agriculture generally resulted in increased aggregate stability and greater SOM content. Overall, no clear trend was found for pH; a decrease in yield was observed under organic agriculture in this review.
Highlights
Soil is increasingly recognized as a non-renewable resource on a human life scale because, once degraded it’s regeneration is an extremely slow process (Camarsa et al, 2014; Lal, 2015)
Understanding interacting effects of agricultural management practices on soil quality indicators (SQI) is essential for the development of SQAPP. Such effects can be best analysed from data of agricultural long-term experiments (LTE), where soils are experimentally manipulated to identify the key drivers of soil change
Effects of management practices on the selected soil quality indicators were assessed on the basis of both the iSQAPER LTE data (Supplementary Table S1), and the data extracted from the literature review including analytical results from the LTEs of China (Supplementary Table S2)
Summary
Soil is increasingly recognized as a non-renewable resource on a human life scale because, once degraded it’s regeneration is an extremely slow process (Camarsa et al, 2014; Lal, 2015). To manage the use of agricultural soils well, decision-makers need sciencebased, easy-to-apply and cost-effective tools to assess changes in soil quality and function. Understanding interacting effects of agricultural management practices on soil quality indicators (SQI) is essential for the development of SQAPP. Such effects can be best analysed from data of agricultural long-term experiments (LTE), where soils are experimentally manipulated to identify the key drivers of soil change. These trials allow to study changes over time of soil properties under various types of treatment (e.g. plough/no-tillage) and their respective intensities (e.g. ploughing frequency). Our hypothesis was that sufficient data for promising soil quality indicators can be extracted in order to show trends over time as a basis for further, generic decision-making on recommended agricultural practices
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