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Nutrient Cycling in Agroecosystems

, Volume 111, Issue 2–3, pp 103–125 | Cite as

The long-term role of organic amendments in building soil nutrient fertility: a meta-analysis and review

  • Yongshan Chen
  • Marta Camps-Arbestain
  • Qinhua Shen
  • Balwant Singh
  • Maria Luz Cayuela
Original Article

Abstract

An exhaustive meta-analysis of 132 long-term (≥ 10 years) studies worldwide was carried out to determine the effects of the use of organic amendments (OA) and OA + inorganic fertiliser (IF) on soil nutrient fertility. The responses of (1) crop yield [over the whole duration of the period (yieldm) and at the end of the experiment (yieldf)], (2) soil organic carbon (OC), (3) size of microbial biomass, and (4) Olsen phosphorus (P) to OA and OA + IF compared with IF only (standard control) and no fertilisation (nil control) were investigated. The overall effect of OA alone on yield was significant when compared with the nil control, but not when compared with the standard control. Only when OA and IF were added to soils that met specific conditions (low initial fertility, sandy texture, near-neutral pH values, under tropical climate) they rendered a significantly greater yieldf than the corresponding standard controls. The continuous application of manure caused greater relative and absolute gains in soil OC than straw + IF but did not produce significant greater yields while causing a considerable increase in Olsen P over time. The use of OA and OA + IF increased the resilience of agronomic systems over that of IF alone, as inferred from the smaller coefficient of variation of crop yield over time. We conclude that while the use of OA along with IF provides some additional benefits on yields as compared with IF application alone (especially under the above-mentioned conditions), the selection of the OA type and application rate should be carefully considered in order to maximise the nutrient use efficiency and minimise any undesirable effects to the environment.

Keywords

Meta-analysis Crop yield Organic amendment Inorganic fertiliser 

Introduction

The “green revolution” brought about by industrial agriculture—i.e., the introduction of chemical fertilisers, synthetic herbicides and pesticides, advent of high yielding varieties, and mechanisation that took place during the twentieth century—has enhanced the capacity for food production from a given land area, which has been the key to feeding a growing global population (Tilman 1998; Khush 2001). This has come, however, at environmental consequences (Tilman 1998; Khush 2001), as industrial agriculture (1) is energy-intensive and fossil fuel-based, (2) relies on genetically homogeneous monoculture crops, which are less resilient to hazards (Altieri et al. 2015), and (3) has grossly altered the biogeochemical flows of nitrogen (N) and phosphorus (P) (Sharpley et al. 1994; Ledgard et al. 2000), which now exceed regional-level boundaries (Steffen et al. 2015). Whereas arable and productive land remains limited, global food demand to meet food security keeps increasing. It has been estimated that by 2050 the world will need 70–100% more food to feed an estimated 9 billion people (World Bank 2007; Baulcombe et al. 2009). Therefore, pressure on land’s productivity—and thus on the environment—will continue to rise (Godfray et al. 2010; FAO 2011). The FAO’s state of land and water report (FAO 2011) forecasts that in 2020 only 0.20 ha of arable and productive land will be available per person, which is less than half the amount that was available in 1960 (i.e., 0.43 ha). It is thus essential to acquire a better understanding on how to achieve greater yields from a given land area (i.e., closing the yield gap) with minimal environmental impacts (i.e., by sustainably intensifying agriculture within planetary boundaries) while meeting the sustainable development goal of ending extreme poverty and hunger (Godfray et al. 2010). For this, it is crucial to increase our knowledge of how different production practices influence crop yields and the environment.

In recent years there has been a renewed interest in using organic amendments (OA) to agricultural soils as partial or full substitutes for inorganic fertilisers (IF) in order to manage nutrients more cost effectively (Quilty and Cattle 2011), decrease our dependence on non-renewable resources (for example, P from phosphate rock) (Withers et al. 2015), reduce and recycle waste that would otherwise be disposed to landfill (Misselbrook et al. 2012), and increase soil organic matter (OM) (Bruce et al. 1999). However, the additional yield effect, defined as any effect of OA beyond that of the supply of macronutrients (Janssen 2002; cited in Hijbeek et al. 2017) is still a topic of debate. The combined application of OA and IF has been reported to give significantly higher yields than either IF or OA applied alone (Edmeades 2003; Dawe et al. 2003; Mao et al. 2015; Qin et al. 2015; Wei et al. 2016) or have no effect compared with only IF, especially when sufficient nutrients are supplied with both types of amendments (Hijbeek et al. 2017). Based on the results from the long-term experiments at Rothamsted (Johnson 1986, 1994, 1997; cited in Edmeades 2003). Edmeades (2003) suggested that very large differences in OM were required before any additional benefits beyond those of the supply of nutrients on crop yield were observed. This has led to questioning by some whether an increase in soil OM represents a winwin situation for food security and climate change mitigation (Hijbeek et al. 2017). Adding OA to soils might also cause negative effects, such as an unbalanced addition of nutrients and/or an increase in the risk of nutrient loses to water bodies (Sharpley et al. 1994; Ledgard et al. 2000), contributing to the alteration of the biogeochemical flows of N and P. In order to allow crops maximise their agronomic productivity as well as minimising the losses of nutrients, more information is needed on the long-term effect of OA on the building-up of soil nutrient fertility for sustainable crop production.

Most long-term studies on the effect of OA and OA + IF on soil nutrient fertility carried out to date have focused on crop yield measurements without simultaneously considering the changes that the amendments have caused to other soil properties linked to soil nutrient fertility, such as soil OM, microbial biomass (MB), or concentration of available nutrients (e.g., Olsen P) in soil. Soil OM contributes both to the retention of plant-available nutrients and water, and to soil structure, among other potential agronomic benefits. Microbial biomass is not only the agent of nutrient mineralisation (Cayuela et al. 2009), but also represents an important labile pool of essential plant nutrients (Brookes 2001), and controls, to a great extent, N gaseous losses (Zechmeister-Boltenstern et al. 2001). Estimates of soil available nutrients after the long-term application of OA not only provide information on soil nutrient fertility, as per definition, but also on their use efficiency, and the risk of losses to water bodies (e.g., N, P) (Pote et al. 1996; McDowell and Sharpley 2001) and to the atmosphere (e.g., N) (Freney 1997). Information on these soil properties is thus needed, as such knowledge can contribute to a better understanding of the underlying causes for which a specific yield effect is observed under a specific pedo-climatic condition and specific management practices, as well as of associated environmental risks, allowing to maximise the benefits of OA and OA + IF while minimising any negative impact. The present work aims to investigate the effect of OA and OA + IF additions on soil nutrient fertility by carrying out a meta-analysis based on results from 132 long-lasting fertility trials (≥ 10 years) worldwide. In this study, the responses of crop yield—along with those of soil organic carbon (OC), size of MB, and plant-available P (i.e., Olsen P)—to OA and OA + IF relative to IF alone (standard control) and no fertilisation (nil control) are determined.

Materials and methods

Data collection

We collected data from relevant peer-reviewed publications. The publications were identified using the online database ISI Web of Science (http://apps.isiknowledge.com) within the period 1997–2017. Publications were searched using the keywords “organic amendment” and the results were refined using additional words—“long-term”, “yield”, “manure”, “compost”, “Olsen P”, and “microbial biomass”. Additionally, articles cited in review papers which had analysed data from long-term agricultural studies (≥ 10 years) were also included in the dataset. For microbial biomass, Kallenbach and Grandy (2011) kindly provided their data from which 10 additional long-term studies were incorporated in our dataset. We selected studies that reported crop yield, soil OC, MB and/or plant-available P data for at least two types of treatments: (a) those that did not receive any fertiliser (‘nil control’); OR (b) those where only inorganic NPK fertiliser (IF, ‘standard control’) was applied, AND (c) where OA with or without supplemental IF was used. We defined OA as raw or composted materials derived from animals (e.g., manure), plant (e.g., straw) and municipal waste (e.g., sludge). The standard control did not always receive equivalent nutrient rates to those in OA and OA + IF treatments.

Altogether, we reviewed over 1300 studies, without limiting our search to either cropping system, soil type or location, and selected 132 that met the above-mentioned criteria (studies included in the meta-analysis are marked with an asterisk in the cited literature). From these 132 studies, we used 541 observations in the meta-analysis. We extracted meta-data from each of the selected publication, including climatic, temporal, soil chemical, physical and biological data, measurement units, treatment, and analytical methods. For the studies where the data were only available in graphs, we used Plot Digitizer 2.6.2 (Huwaldt 2012) to extract data points from figures.

Data treatment and definition of categories

Crop yield data were included only for wheat, barley, corn, and rice grain in order to minimise differences in (1) nutrient needs—those of these specific cereal crops are relatively similar (IPNI 2017), and (2) rooting systems—i.e., tuber crops have been reported to benefit more from OA than cereals (Hijbeek et al. 2017); perennial crops tend to have more developed rooting systems than annuals and are thus more able to synchronise plant demand with nutrient mineralisation (Seufert et al. 2012). Datasets on soil OC, MB, and plant-available P included additional crops such as potatoes, sunflower, sugar-beet, rape, and legumes. We identified specific categorical variables that are known to influence crop yield, soil OC, MB, and plant-available P. Two different datasets were considered for crop yield: (1) the mean of a specific crop yield over the whole duration of a particular long-term experiment (yieldm), and (2) the yield of a specific crop in the final year of the study (yieldf). Climate categories were obtained from the experimental locations according to the Köppen climate classification system. Soil texture was grouped into one of the four categories: (1) sandy (sand, loamy sand, and sandy loam), (2) silty (silty loam and silt), (3) loam (sandy clay loam, medium loam, clay loam, and silty clay loam), or (4) clay (clay, sandy clay, and silty clay). Soils were classified at the highest category (order) according to the Soil Taxonomy (Soil Survey Staff 2014); soils that were under rice cropping (either under continuous rice–rice cropping or in a rice rotation with other crops) were referred to “Paddy soils” and their soil order was disregarded. The sampling depth across all studies ranged from 7 to 30 cm, with more than 90% of the soil samples being taken to a depth of 15–20 cm. Soil pH values were converted to pHCaCl2 following Conyers and Davey (1988) and Miller and Kissel (2010). Other initial soil properties considered were soil OC, total nitrogen (TN), plant-available P (harmonised to that extracted by Olsen method) and plant-available K (as extracted by NaHCO3 solution). Microbial biomass size was estimated from MB carbon (fumigation extraction and fumigation incubation methods) and total phospholipid fatty acids (PLFA) measurements. A description of the functions used for harmonisation of soil pH, OC, MB, and Olsen P datasets is provided in the Supplementary Information (SI). Organic amendments were grouped into five categories: (1) manure (farmyard manure, livestock manure, manure-based materials such as composts), (2) straw (crop straw, straw husk, straw compost), (3) green manure (green manure crops such as rape crop, lantana and some leguminous plants), (4) biosolids (sewage sludge, sludge compost), and (5) biowaste (compost from domestic organic waste, organic household waste). When more than one OA had been applied at a specific site, e.g., straw + manure, the treatment was classified based on the ingredient that had the highest nutrient content (manure in this example). Organic amendment application rates were considered on a dry weight (DW) basis; where only wet weight basis was reported and no additional information could be gathered from the authors, DWs were calculated following the criteria described in the SI. The experiment duration was divided into two groups: 10–20 and ≥ 20 years.

Studies included in the dataset represented a range of geographical and environmental characteristics. The experimental locations were from 122 sites in 20 countries (Fig. 1). Soil pHCaCl2 values ranged from 3.9 to 9.0. Initial soil OC concentrations ranged from 2.7 to 52.0 g kg−1 and initial soil TN from 0.3 to 11.0 g kg−1. Initial soil Olsen P concentrations ranged from 1.6 to 110.0 mg kg−1 and initial plant-available K from 8.6 to 380.0 mg kg−1. Organic amendment applications occurred over the course of 10–110 years, at input rates between 0.2 and 271 t ha−1 year−1 (median 6.8 t ha−1 year−1) (DW basis).
Fig. 1

Map of experimental sites from the peer-reviewed literature used in the current meta-analysis.

This map was personalised from Google My Maps (accessed July 2017)

Meta-data analysis

The meta-analysis was performed according to Hedges et al. (1999) and Cayuela et al. (2014) using MetaWin 2.0 software (Rosenberg et al. 2000). The relative changes in crop yield, soil OC, MB, and Olsen P due to OA and OA + IF were determined compared with (1) the nil control, and/or (2) the standard control. Absolute changes in soil OC and Olsen P relative to the nil and the standard controls were also determined. Relative and absolute changes were calculated using the following Eqs. (1) and (2), respectively.
$${\text{R}} = \left( {{\text{XE/XC}}-1} \right) \times 100$$
(1)
$$\Delta {\text{OC or }}\Delta {\text{Olsen}}\,{\text{P}} = {\text{XE}}-{\text{XC}}$$
(2)
where R is the relative change of either crop yield, soil OC, MB, or Olsen P between treatment and control; XE is the mean values of either crop yield, soil OC, MB, or Olsen P from the experimental observation, and XC is the corresponding mean values for the control observation (nil control or standard control) under the same experimental conditions (i.e. study); ∆ is the mean difference between either soil OC or Olsen P concentration under treatment and that under control (∆OC, g/kg; ∆Olsen P, mg/kg; i.e., absolute change).
The effect sizes (responses) of soil OC, MB, and Olsen P were calculated using a categorical random effects model, where the effect size is weighted by the inverse of the variance (Adams et al. 1997). For the studies that did not include a measure of variance, efforts were made to contact the corresponding authors to obtain these data. If such information was not provided, the studies were excluded from the meta-analysis. For the yield (yieldm and fieldf) we used a non-parametric function, based on using the sample size for weighting (Adams et al. 1997). We chose this function instead of the variance because most studies did not report a measure of variance for yield. The sample size weight function used here was:
$${\text{Weight}} = \frac{{{\text{N}}_{\text{E}} \times {\text{N}}_{\text{C}} }}{{{\text{N}}_{\text{E}} + {\text{N}}_{\text{C}} }}$$
(3)
where NE is the number of replicates of the experimental observation and NC is the number of replicates of the control observation (nil control or standard control) within the same experimental conditions (i.e. study). The pooled variance of the yield (yieldm and yieldf) was less than or equal to zero, for which Meta-Win 2.0 software automatically switched from a categorical random model to a categorical fixed model.

Mean effect sizes of each category and the 95% confidence intervals (CI) generated by bootstrapping (999 iterations) were calculated with MetaWin 2.0 Statistical software (Rosenberg et al. 2000). The overall response ratio was determined as the mean of R and ∆ values from individual observations and was considered to be significant if the CIs did not overlap with one another. The overall mean of the effect size was considered to be significantly different from zero if the 95% CI did not overlap with zero (Gurevitch and Hedges 2001). A minimum of nine direct comparisons (i.e., n ≥ 9) was used to represent each level of the categorical variables. When n < 9, the corresponding dataset was dropped from the analysis or regrouped. In the latter case, this was indicated when done, e.g., tropical and subtropical type climate datasets were grouped in some instances with the corresponding change in the labelling of the group.

Variability of yield over time

The coefficient of variation (CV) of crop (i.e., wheat, barley, corn, and rice grain) yield over time for treatments receiving OA and OA + IF was calculated using the mean of the annual mean yields for years y1 to yn (\(\bar{x}\)) and the corresponding standard deviation (s), i.e., \({\text{C}}_{\text{v}} { = }\frac{\text{s}}{{\bar{x}}}\). These were then compared with the equivalent CV of crop yield for the nil control (107 studies) and standard control (143 studies) and the statistical significance of their means was tested by using a one-way ANOVA using the SPSS 20.0 software for Windows (IBM SPSS Statistics 2011).

Results

Yield

The results showed a significant relative mean increase in yieldm of 81 ± 15% (Bootstrap CI 95%) when using OA or OA + IF (Fig. 2a) and of 102 ± 27% for yieldf (Bootstrap CI 95%) (SI Fig. S1a) as compared with the nil control. However, the change in yield relative to the standard control was only significant (P < 0.05) for yieldf, with a mean increase of 5.3 ± 5.1% (Bootstrap CI 95%) (SI Fig. S1b); the mean change in yieldm was 0.4 ± 2.4% (Bootstrap CI 95%) (Fig. 2b).
Fig. 2

Percent changes in plant yield over the whole duration of the long-term experiment (yieldm) for each level of the individual categories over nil control (a) and standard control (b). Levels are considered to be significantly different from each other when their Bootstrap CIs do not overlap. CIs that overlap with the ‘zero’ line indicate no change in plant yield due to OA or OA + IF. Since the percent change was derived from the response ratio, it can also be interpreted as the magnitude and direction of change in response to a particular variable. Only groups with at least 9 observations are shown. The observations in the groups of tropical and subtropical were merged as a class since the observations of each group was less than 9. The red dotted lines represent the overall mean change in crop yield among all studies combined

Nil control

The variables that had the greatest influence on both yieldm and yieldf responses when compared with the nil control were those related to the soil initial fertility and chemical conditions, i.e., initial available P (Olsen P), N, OC, and pH, followed by the additional amount of mineral N applied with the OA, and soil texture (Fig. 2; SI Fig. S1). The duration of OA and OA + IF application, climate, and type of OA had a greater contribution to the variation in yieldm than to that to yieldf. The rest of categorical variables considered (soil order, OA amount, and crop type) had a smaller contribution to the variance.

We examined different levels of the categorical variables that had the greatest influence on yieldm and yieldf when compared with the nil control (Fig. 2a; SI Fig. S1a). When the initial available P concentration was ≤ 5 mg kg−1, mean yieldm and yieldf increases were > 430 and > 580%, respectively. The responses were smaller at higher initial available P concentrations, with a mean yield increase from ~ 80 to 100% at concentrations between 5 and 10 mg kg−1, and ~ 40–50% mean yield increases at concentrations > 10 mg kg−1. Likewise, the mean yieldm and yieldf increases when the initial total N concentration was ≤ 1 g kg−1 were > 260 and > 180%, respectively. The yield responses dropped to < 70% increases at initial total N concentrations between 1 and 2 g kg−1, and to < 5% at initial N concentrations > 2 g kg−1. The initial soil OC content was also an important factor in explaining the source of yield response variation, with soils with an initial OC ≤ 10 g kg−1 having a mean increase in yieldm and yieldf > 150%; this dropped to a < 100% increases in yield at OC > 10 g kg−1 and to < 50% for soil OC of > 20 g kg−1. Initial soil pH values ranging from 6.6 to 7.3 led to the greatest yieldm and yieldf increases (> 240%) followed by the soils with a pH > 7.3 with mean yield increases < 120%, and the soils with a pH ≤ 6.6 had the smallest mean yield increases (< 70%).

The amount of inorganic N fertiliser added to the soil along with the OA also had an important effect on yield, particularly on the yieldm, with the largest relative increase (> 170%) when the inorganic N application rates were between 100 and 200 kg ha−1 year−1, followed by those above and below this application rate range (Fig. 2a; SI Fig. S1a). Soils with clayey texture had the greatest yieldm and yieldf response with mean yield increases of > 120 and > 210%, respectively, whereas silty soils had the smallest yield increases (< 25 and 70% increase, respectively) (Fig. 2; SI Fig. S1a).

The type of OA also contributed to the variation of the yieldm response, with the straw amendment causing a mean yield increase > 160% whereas for the other OA the increases were < 100% (n of the different groups differed widely—a paired comparison of straw and manure is provided in the discussion section). Relative mean yieldm increased by > 90% with a longer duration (> 20 years) of OA and OA + IF application to soil compared to < 60% for a shorter duration (10–20 years) (Fig. 2a). Soils under tropical and subtropical climates had significantly greater responses in yieldm (112%) than in those under humid temperate-type climate (42%), with the response of soils under continental-type climate showing no significant differences from the former climate types (Fig. 2a). Yieldf and yieldm responses of the Entisol/Inceptisol soil order groups to OA and OA + IF were the greatest (> 140 and 80%, respectively) among all the soil orders considered (Fig. 2), although only significant when compared with the Alfisol order. Application of OA and OA + IF had a considerably smaller effect (< 40%) on yieldm for barley than for the other crops considered (> 60%) (Fig. 2a).

Standard control

Despite the lack of mean yieldm response of OA and OA + IF when compared with the standard control (Fig. 2b), some categorical variables had a significant influence on yieldm. Precisely, the addition of OA and OA + IF caused > 10% decrease in mean yieldm when biosolids was used as OA; likewise, when the OA was added to a soil in which barley was grown. Large differences in mean yieldm were observed between climatic groups, with a positive effect size of > 12% with the addition of OA and OA + IF under tropical climate and a negative effect size > 8% under humid-temperate climate. Interestingly, our results showed that the addition of OA without IF had a significant negative effect on yieldm (Fig. 2b; under “N application rate” categorical variable, grouped as “none”), with a mean effect size of − 7.7 ± 4.6% (Bootstrap CI 95%).

The tenuous mean yieldf response to the addition of OA and OA + IF compared to the standard control was mostly associated with specific categorical variables. For initial Olsen P, total N, and soil OC (SI Fig. S1b) similar trends were observed as under the nil control Fig. S1a), but at a much smaller scale. At low initial soil concentrations for these three categorical variables relative yieldf increases were between 24 and 28%, whereas the rest of groups within these variables had little influence, with increases < 6%, if existent. Other categorical variables for which there was a mean yieldf increase > 10% were tropical climate, sandy texture, an initial soil pH between 6.6 and 7.3, the use of straw as OA, and a N application rate at 100–200 kg ha−1 year−1 along with that of OA (SI Fig. S1b). The addition of OA without IF (SI Fig. 1b; under “N application rate” categorical variable, grouped as “none”) did not cause any significant effect on yieldf when compared with the standard control (mean effect of − 5.4 ± 9.1%; Bootstrap CI 95%).

Yield variability over time

In this study, a smaller mean Cv was detected in the yields of OA-treated soils over time when compared with both controls, which was significant at P < 0.01 when compared with the nil control (mean Cv of treatment = 0.19 ± 0.03; mean Cv of control = 0.31 ± 0.08; n = 107; CI 95%) and at P < 0.10 when compared with the standard control (mean Cv of treatment = 0.17 ± 0.01; mean Cv of control = 0.20 ± 0.03; n = 143; CI 95%).

Soil organic carbon

Overall there was a significant mean relative increase in soil final OC content, with 49 ± 3% (95% CI) and 29 ± 2% (95% CI) with the use of OA and OA + IF as compared to the nil and standard controls, respectively (Fig. 3a, b). The variables that explained the greatest variation in OC when compared with either nil or standard controls were (1) initial soil OC, (2) climate, (3) initial total N, (4) soil texture, (5) soil order, and (6) initial soil pH (Fig. 3a, b). The type, rate, and duration of OA application, as well as the inorganic N application rate added along with the OA also explained a considerable amount of OC variation. Fewer categorical variables contributed to absolute changes in soil OC, with initial soil OC and initial TN levels becoming less relevant (SI Fig. S2a, b).
Fig. 3

Percent changes in soil organic carbon (OC) for each level of the individual categories over nil control (a) and standard control (b). Levels are considered to be significantly different from each other when their 95% CIs do not overlap. CIs that overlap with the ‘zero’ line indicate no change in OC due to OA or OA + IF. Since the percent change was derived from the response ratio, it can also be interpreted as the magnitude and direction of change in response to a particular variable. Only groups with at least 9 observations are shown. The red dotted lines represent the overall mean change in OC among all studies combined

The relative effect size of OA and OA +IF amendments on soil OC at the end of the studies, compared with either the nil or standard controls, was largest when the initial soil OC and total N contents were small, rendering a mean relative increase of > 70 and > 30%, respectively (Fig. 3a, b). For both categorical variables (regardless of the control used), the effect size was considerably reduced when the initial soil OC was > 20 g kg−1 and the initial total N content > 2 g kg−1 (Fig. 3a, b). Trends were different when considering the absolute increase in the final soil OC, with soils with lowest initial OC and total N contents generally having the smallest gain (Fig. S2a, b).

Initial soil pH also had a role, with the greatest relative increase in soil OC in soils with near-neutral pH values (89% when compared with the nil control and 46% when compared with the standard control, respectively). These were followed by the soils with pH values > 7.4, and then by those with pH values ≤ 6.5 (Fig. 3a, b). Interestingly, soils with an initial pH at near-neutral values (6.6–7.3) were low in initial soil OC content (≤ 10 g kg−1); this group of soils (pH 6.6–7.3) also had the greatest absolute increase in soil final OC (9.8 and 7.5 g kg−1 over the nil control and standard control, respectively; SI Fig. S2a, b).

The addition of OA and OA + IF amendments to soils located in warm regions (Mediterranean/sub-arid/arid, tropical and semi-tropical) had the greatest relative increases in soil final OC (> 50% when compared with the nil control and > 30% when compared with the standard control), whereas relative increases were below these threshold values in soils under humid-temperate and continental-type climates (Fig. 3a, b). The differences in absolute gains in soil final OC between climatic groups were less pronounced, but these tend to be greatest in the warm regions as well (SI Fig. S2a, b). Trends on soil final OC based on soil texture were influenced by the inclusion of “Paddy soils” and the consideration of relative versus absolute effects (data not shown). However, there was a common trend in all of the combinations considered, with silty soils having the smallest response and this being significant when considering the relative effect size. Among the soil orders considered, Alfisols had the greatest relative increase in soil OC (> 50% regardless of the type of control considered), whereas the rest of soil orders (Entisols/Inceptisols, Mollisols and the soils grouped as “Paddy soils”) had a relative soil OC increase < 50% (Fig. 3a, b). Trends were different when considering the absolute gain in OC, as Mollisols had the greatest increase (10.0 and 4.5 g kg−1 relative to the nil and the standard controls, respectively; SI Fig. S2a, b).

The mean relative increase in soil OC under the longer-term application of OA and OA + IF (> 20 years) (57 and 37% compared to the nil and standard controls, respectively) almost doubled compared to soils where these amendments were added for 10–20 years (32 and 23% increase for nil and standard controls, respectively), regardless of the type of control considered (Fig. 3a, b). Mean absolute changes in soil OC were not significant, but trends were similar with an absolute increase of 7.3 and 4.5 g kg−1 for longer–term studies (nil and standard control, respectively) versus 5.5 and 3.9 g kg−1 for shorter-term studies (nil and standard control, respectively) (SI Fig. S2a, b). Organic amendments that rendered the greatest relative increase in soil OC were those with a low C:N ratio (manures and biosolids) (> 50 and 40%, when comparing with the nil and the standard control, respectively; Fig. 3a, b). A similar trend was obtained for the absolute gain in soil OC, with low C:N ratio amendments rendering the greatest increases (i.e., manure: 7.6 and 4.8 g kg−1, for the nil and standard controls, respectively) (SI Fig. S2a, b). Increasing application rates of OA and OA + IF caused significant relative increases in soil OC (up to a mean effect size of 59 and 33%, when compared with the nil and standard controls, respectively) (Fig. 3a, b). Absolute gains in soil OC followed similar trends (with a maximum of 8.3 and 5.2 g kg−1, for the nil and standard controls, respectively), although increases were not always significant (SI Fig. 2a, b).

Finally, when considering the additional application rates of inorganic N, both relative and absolute values had a similar response when compared with the nil control, although this was only significant (at P < 0.05) for the former (Fig. 3a; SI Fig. S2a). The smallest gain in soil OC (33% and 4.2 g kg−1, respectively) occurred with inorganic low N application rates (< 100 kg ha−1 year−1). This gain was, in fact, smaller than that of OA only. Inorganic N application rate > 100 kg ha−1 year−1 caused > 55% and > 8.3 g kg−1 increases in relative and absolute soil OC, respectively. These trends were not evident (for the relative change) when compared with the standard control (Fig. 3b; SI Fig. S2b).

Microbial biomass size

The long-term application of OA and OA + IF caused an overall increase in the size of the soil MB, which was significant regardless of the control used. The relative increase was larger when comparing with the nil control (50 ± 7%; 95% CI) than with the standard control (30 ± 5%; 95% CI) (Fig. 4a, b). Climate was the only variable that had a significant influence on the variability of the MB responses for both standard and nil controls. The use of OA and OA + IF led to a higher relative increase of MB size in studies located in tropical and subtropical regions, whereas the studies in continental-type climate (nil control) and Mediterranean, arid and semiarid-type climate (standard control) experienced the least increases in MB size. Other categorical variables also had an effect size, which was more evident when comparing with the nil control. Among these, the following best explained the variation in the MB response: (1) the initial soil pH, (2) soil texture, (3) the initial soil OC, and (4) the years of application.
Fig. 4

Percent changes in microbial biomass (MB) for each level of the individual categories over nil control (a) and standard control (b). Levels are considered to be significantly different from each other when their 95% CIs do not overlap. CIs that overlap with the ‘zero’ line indicate no change microbe biomass due to OA or OA + IF. Since the percent change was derived from the response ratio, it can also be interpreted as the magnitude and direction of change in response to a particular variable. Only groups with at least 9 observations are shown. The red dotted lines represent the overall mean change in MB among all studies combined

Similarly to the findings for soil OC response, soils with near-neutral or basic pH and soils with the lowest initial soil OC (< 10 mg C kg−1 soil) had the greatest relative increase in the MB size when comparing with the nil control (82 and 88% for neutral and basic soils and 70% for low OC soils) (Fig. 4a). As opposed to soil OC, the soil order that had the smallest relative response compared with the nil control was that of Alfisols (26%), while no significant differences were detected between the other soil types. No particular effect of soil order was detected when comparing with the standard control. Clayey and sandy soils were more responsive to the use of OA than silty soils, as for the other variables investigated (Fig. 4).

Studies with longer periods of application (> 20 years) led to larger increases in the relative MB size, fact that was more evident for the nil control. OA amount and type could not explain the variance in MB response (Fig. 4); however, we performed a parallel meta-analysis where treatments with extra mineral fertilizer (OA + IF) were excluded, and in this case straw addition gave lower MB response (14 ± 47%; 95% CI) compared to manures (43 ± 20%; 95% CI) or biosolids (36 ± 35%; 95% CI).

Olsen P

Overall there was a significant relative mean increase in Olsen concentration of 190 ± 35% (95% CI) and of 60 ± 13% (95% CI) with OA and OA + IF application as compared with the nil and standard controls, respectively (Fig. 5). The categorical variable that most consistently influenced the final Olsen P concentrations was the type of OA, with those from animal origin having a relative mean increase of 232 and 93% in Olsen P concentration as compared with their corresponding nil and standard controls, respectively. Plant-derived OA caused a mean increase of 120% in Olsen P levels as compared with the nil control, and had no significant effect as compared with their standard controls (Fig. 5). The trend was even more evident when the absolute change in final Olsen P was considered, with a mean increase of 26 and 5 mg kg−1 from the addition of animal-derived OA and plant-derived OA, respectively, as compared with the nil control (SI Fig. S3a), and of 21 mg kg−1 for the animal-derived OA, as compared with the standard control (SI Fig. S3b). The largest OA application rates (> 10 t ha−1 year−1) caused the greatest relative increase in the final Olsen P concentrations (~ 250 and ~ 100% as compared with the nil control and standard control, respectively) (Fig. 5), which corresponded to a mean absolute increase of Olsen P of 34 and 21 mg kg−1, respectively (SI Fig. S3a, b). The duration of OA and OA + IF application had no significant effect (P < 0.05) (Fig. 5a, b), although trends showed generally greater relative and absolute increases in Olsen P with longer duration of OA application to the soil (Fig. 5; SI Fig. S3).
Fig. 5

Percent changes in Olsen P for each level of the individual categories over nil control (a) and standard control (b). Levels are considered to be significantly different from each other when their 95% CIs do not overlap. CIs that overlap with the ‘zero’ line indicate no change in Olsen P concentration due to OA or OA + IF. Since the percent change was derived from the response ratio, it can also be interpreted as the magnitude and direction of change in response to a particular variable. Only groups with at least 9 observations are shown. The red dotted lines represent the overall mean change in Olsen P among all studies combined

The relative effect size of OA and OA + IF on the final Olsen P concentration was influenced by the initial soil Olsen P levels as comparing with the nil control, the greatest effect (413% increase) was observed at the lowest initial Olsen P values (< 5 mg kg−1) (Fig. 5; SI Fig. S3). The effect of initial soil Olsen P levels on the absolute increase in the final Olsen P concentrations was not significant. Initial soil pH value had a strong effect on the absolute changes in Olsen P as compared with the nil control (not all categorical groupings were available for the comparison with the standard control), with a mean increase in Olsen P > 60 mg kg−1 for the soils with initial pH range from 6.6 to 7.3, as compared to the soils with pH values above and below this range, where the mean increase in Olsen P was < 20 mg kg−1 (SI Fig. S3). Similar trends were evident in relative terms but less accentuated (Fig. 5).

Discussion

This study evaluates the yield response to OA and OA + IF use when considering (1) a mean of a specific crop yield over the whole duration of a particular long-term experiment (yieldm), and (2) the crop yield in the final year of the study (yieldf). There was a greater mean response of yieldf than yieldm, given that yieldm was masked by the inclusion of the means of crop yields of trials over long duration; therefore, it did not truly reflect the final outcome, that is, the ultimate cumulative effect of OA and OA + IF. The apparent increase in yield over time (as inferred from yieldf > yieldm) might reflect the combined effects of (1) the use of new varieties, and improved weed and pest control (Evenson and Gollin 2003; Qin et al. 2015), (2) nutrient impoverishment of the nil control soil, and/or (3) the benefits of the continuous use of OA (Wei et al. 2016). Yieldf values, on the other hand, might have been more vulnerable to the specific weather conditions and/or pests on that specific final year of the trial. To increase the robustness of meta-analyses of the long-term trials data, more information, including the mean value and the standard deviation for each specific year, will be required.

Influence of inherent soil fertility

Yield and soil property responses relative to unfertilised (nil) control

The results obtained showed that the response was strongly dependent on the initial fertility of the soil and the rate at which soils could provide available nutrients to plants; specifically, on the initial soil Olsen P, total N, OC, and pH values. The data clearly revealed the existence of nutrient concentration thresholds for P (Olsen P ≤ 5 mg kg−1) and N (total N ≤ 1 g kg−1) below which plant growth was strongly impaired, whereas no clear threshold was found for K. Soils with low Olsen P and total N were thus generally most responsive to the addition of OA and OA + IF and this response declined as the initial soil fertility increased (Fig. 2a; SI Fig. S1a). Soils with near-neutral pH values (pH range between 6.6 and 7.3) generated greater yield responses (Fig. 2a; SI Fig. S1a) than those with more acidic or more alkaline pH values. This supports the well-known influence of pH on nutrient availability and, most specifically, that of P (Bohn et al. 1985). This was also evident in the meta-analysis for final Olsen P concentrations, as the largest response—in both relative (Fig. 5a) and absolute terms (SI Fig. S3a) when compared with the nil control—occurred within the near-neutral pH range, although high Olsen P values originate from only two studies where manure was added at intermediate to high rates and thus the information should be read with care.

Nutrient availability is also dependent on OM content, given that OM mineralisation is one of the main pathways through which nutrients become plant available, particularly N and P. Organic matter also helps retain nutrient cations at exchange sites, promotes soil structure and improves water holding capacity, among other potential agronomic benefits. Soils with initial low OC concentrations (< 10 g kg−1) were those that had the greatest relative response in yield (yieldm and yieldf), OC content, and MB to the addition of OA and OA + IF (Figs. 2, 3, 4; SI Fig. S1a). Interestingly, the greatest increase in soil OC from OA and OA + IF addition over time (both in relative and absolute terms), and of MB response (in relative terms), occurred in the soils with near-neutral pH values (Fig. 5; SI Fig. S3); yet most of the soils within this pH range had initial low soil OC contents.

Yield and soil property responses relative to the standard control

The tenuous but significant relative increase in yieldf (mean 5.3 ± 5.1%; Bootstrap CI 95%) with OA and OA + IF application as compared with the standard control was to some extent related to the inherent soil nutrient fertility; the greatest responses (between 19 and 28% relative increases) were observed at low initial Olsen P, total N, and soil OC concentrations and at near-neutral pH values (Fig. 2b; SI Fig. S1b). Yet the OA treatment without IF (Fig. 2b; SI Fig. S1b, under the categorical variable “N application rate”, grouped as “none”) had no effect (− 5.4 ± 9.1%; Bootstrap CI 95%) on yieldf when compared with IF treatment (standard control). These results are consistent with the findings of Hijbeek et al. (2017), who reported no additional effect of OA on crop yield beyond that of the provision of plant macronutrients. Greater benefits of OA on the yield of tuber and perennial crops as compared with cereals have been reported (Hijbeek et al. 2017; Seufert et al. 2012). This has been attributed to the greater vulnerability of tubers to poor soil physical properties, and the greater ability of the more developed root systems of perennials to synchronise between the slow release of nutrients from OM and plant demand (Seufert et al. 2012). Long-term experiments on the effect of OA using perennial crops are thus needed if the benefits of OA in agricultural systems are to be maximised.

Influence of other soil properties and environmental conditions

Texture

Fine textured soils had the greatest mean response of yieldm and yieldf to OA and OA + IF compared with the nil control, but the opposite trend was observed for yieldf when compared with the standard control. In a study using European soils, Hijbeek et al. (2017) observed a greater positive effect of OA on yield in sandy soils and a neutral or negative effect on yield on clayey soils compared with standard controls and attributed these results to the effect on improved soil structure and water retention in the sandy soils. The apparent contrasting results obtained by Hijbeek et al. (2017) could be explained by the fact that, in the absence of nutrient limitation or adequate nutrient supply (i.e., comparison with standard control), the contribution of OA to soil physical properties is more evident in the sandy soils. When comparing with the nil control, nutrients in OA were probably the key factor contributing to the positive response, and these are better retained in clayey soils given their greater cation exchange capacity (CEC). Silty soils were less responsive to OA and OA + IF additions for yield, OC (with the effect being more evident when “Paddy soils” were excluded; data not shown), and MB. This could be explained by the above reasoning—not being so susceptible to water stress as sandy soils and not having the same ability as clayey soils to retain nutrients—among other factors.

Soil type

The soils under study included Entisols, Inceptisols, Mollisols, Alfisols, Andisols, Ultisols, Oxisols and Aridisols soil orders, but only for the first four was n large enough to consider them as groups. In addition, soils under paddy crop were grouped as “Paddy soils” to minimise the masking effects associated with the prevailing anoxic conditions occurring during most of the rice growing season. Among the soil groups considered, there was a greater yieldm and yieldf effect in less developed or young soils (Entisol/Inceptisols) compared with OM-rich soils (Mollisols) or more evolved soils (Alfisols), with “Paddy soils” having an intermediate response. However, more data is needed to be able to generalise from these results. This is also true for the relative and absolute increases in OC, which were greatest in Alfisols and Mollisols, respectively, and for the relative response of MB size, which was not consistent with that of OC.

Climate

Crop trials under tropical and subtropical climate resulted in a greater yieldm and yieldf response than those under humid-temperate conditions and this could be, to some extent, attributed to more favourable conditions for crop production in the humid-warm regions than in the humid temperate regions. The greater relative yield response under tropical conditions was paralleled by that in soil OC and MB, which is consistent with the fact that in tropical soils there is a smaller soil OC pool than in those under humid-temperate climate due to the larger turnover rate of OM (Santruckova et al. 2000). However, part of these effects could have been masked by geo-economic conditions, as the “humid-temperate” group had a large number of sites in developed countries with historical high application of fertilisers and accumulation of P (Sattari et al. 2012; Schoumans et al. 2015) and other nutrients, whereas the opposite occurred under the tropical/subtropical climate group. Indeed, we noted that the initial Olsen P values, when available for the humid-temperate group, were always > 15 mg kg−1. Soils under the humid-temperate group also had the smallest relative increase in OC compared with the other climate groups, which could be attributed to their relatively greater OC contents (69% of the soils considered had an initial OC > 15 g kg−1 compared with that of 32% of soils under the subtropical group), yet the lower yield response could also have played a role by contributing to smaller new C inputs.

Influence of management practices

Addition of inorganic N + OA

The yearly application of inorganic N fertiliser in addition to OA had a strong influence on yieldm and yieldf with the effect size peaking at inorganic N application rates of 100–200 kg ha−1 year−1 (Fig. 2; SI Fig. S1), In the absence of inorganic N, effects of the OA alone on yield compared with that of the standard control were negligible (yieldf; mean − 5.4%) or even negative (yieldm; mean − 7.7%), revealing the better synchronisation of N availability with plant demand, when N was timely applied as IF. Nitrogen application rates > 200 kg ha−1 year−1 caused a reduction in the response on yieldm and yieldf compared with the apparent optimal application rate of 100–200 kg ha−1 year−1. This could be largely attributed to a stimulation of tillering or greater vegetative growth due to high N levels without the production of spikes (Baethgen et al. 1995); however, other undesirable effects, such as lodging and osmotic stress, could have also contributed to it (Goyal and Huffaker 1984). Interestingly, the trends observed in the relative and absolute response of OC content at the end of the experimental period suggests that the simultaneous addition of OA with small rates of inorganic N fertiliser (< 100 kg inorganic N ha−1 year−1) caused an apparent enhanced OM decomposition compared with OA only, which was not outpaced by OM inputs from growing crops. Larger rates of inorganic N (> 100 kg inorganic N ha−1 year−1) did not contribute to significant greater OC contents compared with OA alone, although a tenuous increasing trend was detected (SI Fig. S2) and was associated with increased crop yields.

Type of OA

The greater response of straw than manure on crop yield—significant for yieldm when compared with the nil control—was unexpected. It should be noted that (1) the number of observations for straw was much smaller than the number of manure observations (n = 28 vs. n = 95); (2) also, > 90% of the straw-treated soils received additional application of IF compared with 71% of those treated with manure applied soils. In fact, when we considered the 24 studies where data for paired straw and manure treatments were available, there was no significant difference between the two OA, with mean yieldm increases of 98 ± 58% (CI 95%) and 104 ± 60% (CI 95%) for manure and straw, respectively. Wei et al. (2017) suggested that an enhanced hydrolysis of organic P due to the greater phosphatase activity under straw treatment contributed to a greater yield than the manure treatment. In contrast, Zhao et al. (2009) reported a greater phosphatase activity under manure than under straw (both amendments were combined with chemical fertilisers), but proposed the use of straw along with inorganic fertilisers to improve soil physical and biological properties.

When considering the relative and absolute response of the type of OA on soil OC concentrations at the end of the study, the residues with high C:N ratio (e.g., straw) had a significantly smaller effect than the low C:N ratio residues (e.g., manure), as reported by others (Persson and Kirchmann 1994; Zhao et al. 2009). Recent studies hypothesise that under similar pedo-climatic conditions soil OC preservation is controlled by microbial use efficiency (MUE) (Cotrufo et al. 2013; Rumpel et al. 2015; Paetsch et al. 2016), which is defined as the ratio of the substrate that becomes assimilated by microbes over the amount that becomes mineralised. This is based on the evidences that microbial-processed and microbial-derived OM have a greater ability to interact with soil mineral surfaces (Kleber et al. 2015; Rumpel et al. 2015). Hobbie (2005) also suggested that microbes might be energetically more efficient when using organic N instead of inorganic N as a source of N, in line with a possible greater MUE of microbes as the C:N ratio of the substrate decreases. Therefore, in our study, it is possible that a greater MUE of microbes in manure-amended soils than in those amended with straw explained, to some extent, the differences in soil OC over time. It should be noted that the relative mean increase in soil OC upon the continuous application of manure as compared with the standard control was 38.7 ± 4.4% (CI 95%)—equivalent to a mean absolute gain of 4.8 ± 0.7 g kg−1, which was ~ 50% larger to the one reported by Maillard and Angers (2014) in a meta-analysis study that also included studies from 3 to 26 years duration: 25 ± 14% (CI 95%).

OA application rate

This categorical variable had no influence in crop yield and MB, but considerably influenced changes in soil OC and Olsen P. The substantial increases in Olsen P of 11.9 ± 10.8, 33.1 ± 10.1, and 44.2 ± 9.8 mg kg−1 (CI 95%; n = 9, 12, and 12, respectively) when manure was applied at rates ≤ 5, 5–10, and > 10 t ha−1 year−1, respectively (data not shown), without any apparent mean effect of manure application on yield when compared with the standard control (Fig. 2), suggests the need to judiciously apply this OA. In many countries, the application of organic wastes to a given area is stringently regulated—e.g. in the EU it is limited to 170 kg N ha−1 year−1 (91/676/CEE) and 30 kg P ha−1 year−1 (calculated as a 3-year average), with a limit on the total application of 6, 7 and 8 t year−1 in the Netherlands, Denmark, and Austria (DW basis; calculated as a several years average; Barth 2003). The current results suggest that further refinement of the maximum application rate allowance of animal-derived wastes based on their total P contents might be needed, especially when applied to soils where residual P has accumulated.

Duration of the experiment and variability of yield over time

Our results suggest that longer period applications of OA to the soil resulted in greater crop yieldm when compared with the nil control, but not when considering the standard control. The results from the long-term experiments in Rothamsted showed a clear increase in yield over time from the use of OA relative to IF (Johnston 1986, 1994, 1997; cited in Edmeades 2003), but this was attributed to their high manure inputs—beyond current regulations (e.g., The Netherlands, Denmark, Austria)—over long periods of time thus rendering very large differences in soil OM contents (Edmeades 2003). Bi et al. (2009) and Pan et al. (2009) reported a decrease in the coefficient of variation (Cv) of crop yields over time in soils with OA compared with the corresponding controls, and attributed this to the buffering effect that these additions exert against extreme hazards. This study also showed that the use of OA and OA + IF to soils increased the resilience of agricultural systems, that is, their ability to buffer less favourable conditions. This could be attributed, at least in part, to the observed enrichment in OC, MB, and Olsen P (although this was not always significant at P < 0.05), which may have contributed to increased water-holding capacity, the presence of a more diverse soil biota (Maeder et al. 2002), and/or the better synchrony between nutrient release and plant uptake (Seufert et al. 2012).

Finally, it is important to note that this global meta-analysis on the effects of OA and OA + IF on soil nutrient fertility had a few limitations such as the fact that: (1) the analyses were not completely independent because many studies included multiple comparisons with the nil and/or standard control (e.g., different application rates of a specific OA), and (2) the amounts of nutrients added in the OA and OA + IF were not always adjusted to those in the IF only treatment (standard control), and even when they were, the supply rate of nutrients was unknown, which complicated the adjustments when done.

Conclusions

The results obtained in this study when evaluating the effects of OA and OA + IF on yield, OC, MB and Olsen P as compared with the nil control were useful to achieve a better understanding of how agricultural soils respond to these amendments. However, business-as-usual agriculture generally involves the use of IF, with or without OA, thus the conclusions drawn from this study mostly address those that were also relevant when compared with the standard control.
  1. 1.

    The addition of OA and OA + IF produced a greater cereal crop yield in soils with low inherent fertility (i.e., initially low soil TN, Olsen P, and OC). This could be associated to either (1) the provision of nutrients by OA that are not supplied by IF, and/or (2) the better synchronisation of nutrient release with the use of both OA and IF. The use of OA in soils with adequate inherent soil fertility did generally not contribute to additional cereal crop yield as compared with IF only.

     
  2. 2.

    The results suggest that the greatest benefit in yield, Olsen P and OC from the use of OA and OA + IF occurs in soils with near neutral pH values (6.6–7.3). While we acknowledge the potential influence of an unbalanced dataset on the results, we hypothesise that the generally lower initial OC content in the soils with a pH > 6.6 compared with those more acidic, along with the fact that P solubility is greatest within the 6.6–7.3 pH range, might have contributed to it. The near neutral pH range is also optimum for the availability of most other plant nutrients that might have contributed to improved yields.

     
  3. 3.

    When the inherent nutrient fertility of the soil was low, cereal crop yield was more responsive to OA and OA + IF in clayey soils, but when there was no nutrient limitation, it was more responsive in sandy soils. This was attributed to the effect of these amendments on soil physical properties, which became more evident when nutrients supply was adequate.

     
  4. 4.

    Only crops grown in soils under tropical climate showed a significantly positive yield effect to OA and OA + IF addition, as compared with the standard control. To some extent, this could be associated with their low OC content in soils (these soils had the greatest relative increase in OC and MB upon receiving OA) and more favourable conditions for plant growth under tropical climate. Yet geo-economic circumstances may have also influenced; i.e., soils in the “humid-temperate conditions” had a large number of sites in developed countries, where there is historical high application and accumulation of P.

     
  5. 5.

    The use of OA along with the application of inorganic N fertiliser when added at the suitable rate (100–200 kg ha−1 year−1) significantly increased yield compared with the standard control (IF only), the OA alone, and that of OA + inorganic N fertiliser at smaller or larger rates, thus revealing the synergies of combining these two amendments and using them at the right rates. This not only allowed a better synchronisation of N supply to plants, but also minimised deleterious effects on cereals (e.g., lodging).

     
  6. 6.

    While the continuous application of animal-based residues rendered greater gains in soil OC than that of plant-based residues (these were added along with IF), they did not contribute to a greater yield. In contrast, they caused a considerable increase in Olsen P (and most probably that of other less labile P forms). This alerts on the need to judiciously apply animal-based OA to soils, as an excess of P from large application rates might contribute to their loss to fresh waters and associated environmental problems.

     
  7. 7.

    The use of OA and OA + IF in soils increases the resilience of the agronomic systems, offering a greater buffering effect when conditions are less favourable.

     

Notes

Acknowledgements

The authors are grateful to R. Albiach, D.K. Benbi, Z. Bin, G. Blanchet, G. Borgesson, S.L. Brown, E.H. Chang, F. Davide A. Fliessbach, S. Ghosh, N. Harada, K. Inubushi, T. Kätterer, J. Ladha, J. Magid, B. Marschner, S. Monaco, W. Qin, B. Ramakrishnan, Z. Ruifu, S. Sinaj, A.Takeda, E. Tatti, R. Tripathi, Z. Weijian, B. Zhang, R.F. Zhang, W.J. Zhang, who were contacted and kindly supplied any relevant missing information necessary for the meta-analysis. The authors are very grateful to K.J. van Groenigen for his sensible advice with Metawin and Prof. M. Hedley for the constructive discussions on soil nutrient fertility. The authors are also grateful to C. Kallembach who generously shared her MB dataset. M.L. Cayuela was supported by a Ramón y Cajal contract and acknowledges funding through the Project CTM2015–67200–R from the Ministry of Economy and Competitiveness. Y.S. Chen is grateful to the China Scholarship Council (CSC) for the financial support as visiting scholar at Massey University.

Supplementary material

10705_2017_9903_MOESM1_ESM.docx (665 kb)
Supplementary material 1 (DOCX 665 kb)

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Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  • Yongshan Chen
    • 1
    • 2
  • Marta Camps-Arbestain
    • 1
  • Qinhua Shen
    • 1
  • Balwant Singh
    • 3
  • Maria Luz Cayuela
    • 4
  1. 1.Institute of Agriculture and EnvironmentMassey UniversityPalmerston NorthNew Zealand
  2. 2.School of Resources and Environmental ScienceQuanzhou Normal UniversityQuanzhouChina
  3. 3.Centre for Carbon, Water and Food, School of Life and Environmental SciencesUniversity of SydneySydneyAustralia
  4. 4.Department of Soil and Water Conservation and Organic Waste ManagementCEBAS-CSICMurciaSpain

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