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Article

The Use of Pruning Residue Mulch and Spontaneous Groundcovers to Control Erosion and Carbon Loss in Olive Orchards

by
Miguel A. Repullo-Ruibérriz de Torres
1,2,*,
Francisco Pérez-Serrano
3,
Manuel Moreno-García
4,
Rosa M. Carbonell-Bojollo
4,
Rafaela Ordóñez-Fernández
4 and
Antonio Rodríguez-Lizana
3
1
European Conservation Agriculture Federation (ECAF), 1040 Brussels, Belgium
2
Higher Technical School of Agricultural and Forestry Engineering (ETSIAM), University of Córdoba, 14071 Córdoba, Spain
3
Area of Agroforestry Engineering, Department of Aerospace Engineering and Fluid Mechanics, University of Seville, Ctra. de Utrera, Km. 1, 41013 Seville, Spain
4
Natural Resources and Forestry Area, Andalusian Institute for Research and Training in Agriculture and Fishing (IFAPA), Alameda del Obispo Centre, 14004 Córdoba, Spain
*
Author to whom correspondence should be addressed.
Agriculture 2025, 15(7), 677; https://doi.org/10.3390/agriculture15070677
Submission received: 25 February 2025 / Revised: 17 March 2025 / Accepted: 19 March 2025 / Published: 22 March 2025
(This article belongs to the Section Agricultural Soils)
Browse Figures
Versions Notes

Abstract

:
Many olive orchards are rainfed and located on poor and sloping soil. Tillage is the most common soil management system, leaving the soil vulnerable to erosion. Pruning is a frequently used field operation in olive orchards that generates biomass; thus, pruning residue can be shredded and used as mulch to cover and nourish the soil. Several strategies using pruning residue mulch and spontaneous groundcovers were established to study their effect on controlling runoff, erosion and soil organic carbon (SOC) loss under simulated rainfall. The simulation trials were conducted under two different intensity rainfalls: high-intensity rainfall and medium-intensity rainfall, which averaged 36.8 and 16.4 mm/h, respectively. A tillage system was compared to spontaneous vegetation using two doses of pruning residue mulch, 10 and 30 t/ha, and a mixture of 10 t/ha of pruning residue applied on spontaneous vegetation. Runoff was reduced to a higher degree with spontaneous groundcovers as infiltration was favoured. Soil loss was reduced by more than 95% and SOC loss by more than 85% regarding tillage with any type of groundcover for both rainfall intensities. Spontaneous vegetation with a pruning residue mulch system kept the soil protected to a greater degree against erosive processes, making the system more sustainable.

1. Introduction

The olive tree is the most widely cultivated woody crop in the world, covering an area of approximately 11 Mha [1], primarily in regions with Mediterranean climates, including parts of North and South America, as well as Asia and Australia. However, most of its cultivation is concentrated in the Mediterranean basin. Spain stands as the leading olive-producing country, where olives are the most important crop, covering over 2.79 million hectares [2], with 60% of this area located in Andalusia [2]. In this region, olive cultivation holds significant economic and social importance in the areas where it is practiced.
In the Mediterranean region, a significant proportion of olive cultivation is situated on land with slopes exceeding 15% [3]. This distribution is largely due to historical factors, with low-density farming systems where olives were planted on marginal lands [4]. More recently, systems of increasing intensity have been implemented, transitioning from intensive to super-intensive cultivation [5], characterized by much higher planting densities [6], which require relatively flat terrain to facilitate the operation of harvesting machinery [7]. Although their adoption is expanding, these systems are not yet widely adopted as they require a high initial investment.
Water erosion, one of the most significant threats to soil in Europe, also represents a major concern for olive groves situated on slopes [8]. Historically, the slope of the terrain could be modified by constructing terraces; however, the construction and maintenance is very costly. Alternative methods include the use of geotextiles or the reduction or elimination of tillage practices [9,10], with the latter option often combined by herbicide application. However, this practice can lead to soil compaction and water contamination from these chemicals [11].
In the 1980s, the use of living vegetation as groundcovers was proposed as a strategy to manage soil loss and reduce runoff. Over the years, numerous studies have analyzed the ecosystem services provided by groundcovers, including protection against soil and water loss due to runoff [12], reduction in water contamination by dissolved nutrients [13,14,15] and herbicides [16], carbon sequestration [17,18], soil fertility enhancement [19], and reduction in CO2 emissions through minimized tillage [20].
In addition to groundcovers, another alternative is to shred pruning residues and leave them on the surface [21], either as the sole mulch or to complement the existing vegetation. According to the recent Law 7/2022 of April 8 on waste and contaminated soils for a circular economy [22], these residues are prohibited from being burned, except in cases authorized by specific exceptions. These residues can be used for energy production, although this option presents significant limitations [23]. Their use as an inert cover is one of the objectives of the Common Agricultural Policy 2023–2027, which recently came into effect (Official State Bulletin, number 308, 24 December 2024, Spain) [24]. Consequently, an increase in the area of olive groves managed with pruning mulch is expected. The mulch derived from shredded pruning residues is a byproduct of the pruning, which is typically carried out on an annual or biennial basis in olive cultivation.
Pruning residue mulch can serve as an excellent alternative for protecting the soil while simultaneously enhancing its physical, chemical, and biological properties [25,26,27]. Mulching has long been explored and adopted as an effective best management practice to reduce runoff and water erosion [9]. In comparison with herbaceous groundcovers, pruning residues do not consume water. Rodríguez-Lizana et al. [28] demonstrated the protective capacity of olive pruning residues on the soil, reporting that they are effective and provide a more sustained protective effect compared to herbaceous groundcovers [27].
Furthermore, this wood-based mulch contributes to controlling ruderal flora and reducing the reliance on herbicides [29]. Furthermore, the application of pruning mulch, or its combined use with spontaneous grasses, promotes greater heterogeneity and abundance of beneficial arthropods, which are essential for biological pest management [30].
There are various types of olive groves, which yield highly variable amounts of pruned material. Pruning can produce up to 3 tonnes of biomass annually per hectare of extensive olive grove [31]. Gil-Ribes et al. [7] reported pruning amounts ranging from 25 to 30 kg per tree in traditional olive orchards. Rodríguez-Lizana et al. [32] documented pruning amounts of 37.2 ± 2.51 kg per tree in a farm with a quincunx planting pattern and trees spaced 12.5 m apart. Super-intensive olive orchards produce higher pruning amounts, with values ranging from 10.5 to 17.6 t/ha [5].
Additionally, the pruning amount varies significantly within the field in traditional plantations [32], with dry pruning weights ranging from 7.6 to 76 kg per tree. This variability has implications for soil protection from a spatial perspective. This variability has led authors such as Petratou et al. [33] to suggest that prioritizing residue application as mulch in specific locations is necessary. However, such decisions are not typically made at the farm scale as this would require transporting residues, which would result in additional costs.
Rainfall simulation is a valuable method for measuring water, sediments, soil organic carbon (SOC) and nutrient losses, as it enables repeated experiments and precise control over rainfall intensity, duration and distribution [34,35]. Some studies using rainfall simulation focus on the effects of soil management and tillage practices [36].
To the best of our knowledge, no studies have been conducted on the effect of applying different amounts of pruning residues as mulch in olive orchards, nor on its combination with spontaneous groundcovers concerning erosion, runoff, and carbon loss. Given that this practice is growing in olive cultivation, it is of interest to explore the effects of these practices as well as establishing a comparison with management systems commonly used by olive growers such as tillage and spontaneous vegetation.
On the basis on the above, the objectives of the present study are as follows: (i) to evaluate the effect of two doses of pruning residues on soil, water, and SOC losses, and (ii) to assess the effect of integrating pruning residues with spontaneous groundcovers on the aforementioned variables. For enhanced comparison and parameter control, these evaluations are carried out under two different rainfall intensities conducted using a rainfall simulator.

2. Materials and Methods

2.1. Study Site and Experimental Plots

The study was performed in an olive orchards located in the “Alameda del Obispo” experimental station (37°51′40″ N, 4°47′58″ W) belonging to the Andalusian Institute for Research and Training on Agriculture, Fishing and Food (Regional Ministry of Agriculture). The olive trees were the “Hojiblanca” variety of twelve years old, and they were planted with a 6 × 5 m2 plantation frame on a 20% slope hill. Five 5 × 10 m2 plots were set up with the longest dimension (10 m) oriented in the slope direction. In the middle of each plot, there were two olive trees placed at a distance of 3 and 9 m from the bottom (Figure 1).
Soil samples within the five plots were taken at the beginning of the trials to determine some soil parameters (Table 1). The soil has a loam textural class and belongs to the Typic calcixerept subgroup [37].
Each 5 × 10 m2 plot corresponds to a treatment of the trials with different soil managements:
▪
The tillage plot was managed with a rototiller at a 20 cm depth before the beginning of the trials. Before each replication, the soil was raked to break the superficial crust left by the previous rainfall simulation.
▪
Spontaneous (Spon) vegetation groundcover at full field was left to grow in the plot. The dominant species identified in the previous season were Bromus madritensis, Calendula arvensis, Avena sterilis, Sorghum halepense and Hordeum murinum.
▪
Pruning residue mulch with an amount of 10 t/ha (PR-10) was used. The pruning residues were applied on a strip of 2 m width corresponding to the common width of shredding machines. Figure 1 shows a scheme of the pruning residue mulches within the plot. The shredded residues were applied homogeneously on the marked strip.
▪
Pruning residue mulch with an amount of 30 t/ha (PR-30) applied on a 2 m wide strip was placed within the plot similarly to PR-10. This treatment represents the doses applied on the ground after more severe pruning or bigger trees in size.
▪
Mixture of spontaneous vegetation groundcover at full field and pruning residue mulch at a dose of 10 t/ha (Spon + PR-10) applied on a 2 m wide strip.
In Figure 1, shaded stripes represent the surface occupied by pruning residue mulch. To avoid the splash effect, a half pruning residue mulch strip was established at the bottom of the plot, where the channel for collecting the flow was placed. Before the application of the shredded pruning residues, the herbs of plots with only pruning residues (treatments PR-10 and PR-30) were treated with systemic herbicide, maintaining the bare soil.

2.2. Rainfall Simulator and Simulation Trials

The rainfall simulator consisted of six sectorial sprinklers located 2.5 m outside each plot, with three on each side joined with a pipeline. The sprinklers were placed at a height of 3 m with extensive supporters. Each pipeline connecting three sprinklers of each plot side had a manifold and a manometer that allowed a range of hydraulic pressures to vary the discharge and, therefore, the rainfall intensity.
At the bottom of each plot, there was a channel to collect the flow of runoff and sediments. The flow was led through a pipeline through a runoff gauge consisting of a tipping bucket similar to that of Barfield and Hirschi [38].
The rainfall simulations were run during September–October 2022 for two different intensity rainfalls:
-
High-intensity rainfall (HIR): ranged between 35.7 and 39.4 mm/h. This rainfall intensity was obtained with a pressure of 200 kPa and sprinklers with 4 mm nozzles. The return period in the zone for rainfall of 40 mm/h during 90 min is 18 years [35].
-
Medium-intensity rainfall (MIR): ranged between 15.8 and 17.4 mm/h. The rainfall intensity was obtained with the pressure established in 180 kPa and sprinklers with 3 mm nozzles. A precipitation of 15 mm/h during 3 h has a return period of 4.4 years in the area [35].
The simulations with each rainfall intensity were replicated three times, with one replication per week. A day before each simulation, the plots were irrigated to reach saturation. Each simulation had a duration of 1 h and 30 min.

2.3. Soil Sampling and Meassurements

Rainfall uniformity tests were carried out before the start of the trials; nevertheless, during the rainfall simulations, eight rainfall gauges were placed uniformly across the plot and the rainfall was measured three times per simulation (every 30 min).
Before each rainfall simulation, soil samples were taken at 0–5, 5–20, 20–40 and 40–60 cm depths to determine the initial soil moisture using the gravimetric method. The soil samples were taken at three positions of each plot (top, middle and bottom) with an Edelman auger. The soil samples were weighed and placed in an oven until a constant weight was reached. Cylinder cores of known volume were used to measure the bulk density and calculate the soil volumetric moisture.
The soil cover in each plot was determined through the subjective evaluation per sector method [25]. This was determined before each simulation with a 0.25 m2 frame in ten different points of the plot covering all plot surface.
The total runoff during the 90 min simulation was determined through the flow gauge. This was equipped with a sensor that registered the number of overturns and the time, thereby enabling the development of a hydrograph. In previous tests on the gauge, each overturn of the tipping bucket had a volume of 0.4 L. Flow samples (approximately 1 L) were taken each 10–20 min depending on the changes in the flow. The sediment load in each flow sample was determined by evaporation. The load of sediments per liter in a determined period of the simulation was extrapolated to the total runoff volume of that period, measured with the number of overturns of the gauge, to estimate the soil loss. Additionally, the sediments accumulated in the collecting flow channel were collected at the conclusion of the simulation, weighed, and added to the soil loss estimated.
A subsample from the soil samples taken at topsoil (0–5 cm) for soil moisture were air-dried and sieved for subsequent soil organic carbon (SOC) content analysis. Similarly, sediments collected were also analysed to determine the SOC loss through erosion. SOC was analysed by the Walkley–Black chromic acid wet oxidation method in a hot mixture of K2Cr2O7 and H2SO4 [39].

2.4. Data Analysis

To know the uniformity of rainfall in each simulation, the Christiansen uniformity coefficient (CUC) [40] was used through the following formula:
C U C = 100 × 1 − ∑ x − X n × X
where x is the rainfall depth measured in each rainfall gauge, X the average depth, and n the number of rainfall gauges.
Percentages of reduction in total runoff, soil and SOC losses were calculated for each rainfall intensity.
The SOC content in the dragged sediments was related to the SOC content in the soil samples at topsoil to determine the SOC enrichment ratio:
S O C   E n r i c h m e n t   R a t i o = S O C s e d S O C s o i l
where SOCsed indicates the organic carbon content in the sediment and the SOCsoil indicates the SOC content at topsoil (0–5 cm). SOC content in sediments and SOC enrichment ratio were represented against the soil loss.
Statistical analysis was performed through an analysis of variance with three replications. The homogeneity of variance, the random distribution of residuals and the normal distribution of errors were tested. The subsequent comparison of means was conducted by the Least Significant Difference (LSD) test at p ≤ 0.05.

3. Results

3.1. Rainfall, Soil Moisture and Soil Cover

Table 2 shows the rainfall rate obtained during each simulation, including those that did not differ statistically (p = 0.21 HIR and p = 0.25 MIR) within each rainfall rate with an average of 36.8 mm/h for high intensity and 16.4 mm/h for medium intensity. The homogeneity of rainfall, expressed with the CUC, was higher generally under HIR where there were no significant differences among treatments. The simulations run under MIR on PR-30 and Spon + PR-10 had lower CUC, but the rainfall rate obtained was similar to the other treatments.
The soil moisture tested at the beginning of each simulation was similar under HIR. However, lower values were observed for tillage and spontaneous vegetation under MIR despite all plots receiving the same irrigation in the rainfall simulation trials.
The average of the soil cover measures taken in each plot is indicated in Table 2. The soil cover in the tillage plot was very low with less than 5% soil coverage. The treatments with pruning residue mulch had soil covered only in the mulch strip; therefore, the soil cover intra-plot was less uniform. The averages, standard deviations and ANOVA shown in the table were calculated from the three replications conducted per treatment and intensity.
The treatments with spontaneous vegetation showed a slight increase in soil cover with MIR as the rainfall simulations were performed three weeks after the simulations under HIR and the plants grew.

3.2. Runoff, Soil and SOC Losses

The differentiated soil management system and the different treatments studied showed clear differences in water, soil and SOC losses through the runoff–erosion process (Table 3). The tillage plot showed the highest losses, predominantly under HIR, with a soil loss of more than 0.5 t/ha in 90 min events. The differences were clearer for runoff soil loss.
In general terms, treatments with herbaceous vegetation provided better reductions in runoff by improving infiltration. This effect was not observed for soil loss under MIR, in which PR-30 provided a lower value than Spon. Runoff with HIR was significatively higher in the tillage plot, followed by PR-10, PR-30, Spon and Spon + PR-10. Under HIR, runoff generated by PR-30 was not statistically different from that produced by the PR-10 plot and the treatments with spontaneous vegetation. Under MIR, the runoff produced in all plots was statistically similar except in the tillage plot. Likewise, the ANOVA conducted for soil and SOC losses provided similar results between the treatments with any type of groundcover for both intensities.
The pruning residue mulch and the herbaceous groundcovers were more efficient at reducing erosion than runoff. The differences with respect to the tillage system were higher for soil loss. The percentage of reduction in runoff in respect to the tillage system ranged between 42 and 95% for HIR and 77 and 98% for MIR. The pruning residue treatments provided the lowest percentage of reduction. However, all percentages of soil loss reduction regarding tillage were higher than 95% for both intensities.
Figure 2 shows the relationship between the individual data of runoff and soil loss. The fit of the data to an exponential model indicates that soil loss with tillage, especially with HIR, has a greater difference with the other treatments than the differences in runoff.
SOC loss through the eroded sediments was proportional to the soil loss, but the differences with respect to the tillage system were lower. Percentages of reduction in SOC loss regarding tillage were lower than those obtained for soil loss in each treatment. The organic carbon contents in the sediments from the tillage plot were generally lower than those from treatments with spontaneous groundcovers, pruning residue mulch or mixture (Figure 3). Thus, the differences in SOC loss between treatments were reduced (Table 3).

3.3. Soil Cover, Soil and SOC Loss Relationships

The soil protection provided by the treatments with spontaneous vegetation, pruning residue mulch and mixtures had a clear effect on erosion control. Spon + PR-10 was the treatment with the highest soil cover and the lower losses. On the contrary, the poor soil protection of the tillage system produced the highest soil loss (Figure 4a). Similar values were obtained between Spon and pruning residue mulch.
The effect of soil cover on SOC loss was similar to soil loss, but the loss values were lower (Figure 4b).

3.4. SOC Enrichment Ratio

The enrichment ratio is usually represented against the soil loss to demonstrate that the more erosive the rainfall events, the lower the enrichment ratios. Figure 5 shows the enrichment ratio of all treatments and the soil loss for the individual data of each replication. Normally, the SOC enrichment ratio values are higher than 1, indicating that the SOC content in sediments dragged into the flow is higher than that measured in the soil at the beginning of the simulation.

4. Discussion

4.1. Rainfall Simulation Performance

The rainfall simulations performed demonstrated a comparison between treatments. The rainfall rates obtained in each repetition were statistically similar within each intensity (HIR, MIR). Likewise, the homogeneity of rainfall was acceptable with CUC > 85% for HIR and CUC > 69% for MIR (Table 2). The recorded values were in the range obtained by Laguna and Giraldez [41] for 5 × 15 m plots. The use of a rainfall simulator allowed us to control the rainfall rate and duration for treatment comparison in similar conditions such as slope and soil conditions. This method has been widely used for soil loss studies [34,35,41,42]. Portable rainfall simulators are more commonly used [43] but they are limited by their small size, usually <1.5 m2 [44]. Kinnell [45] points out that runoff plots bigger than 10 m long are recommended to increase representativity. In 5 × 10 m plots like those used in this research, achieving the uniformity of rainfall can be challenging.
The higher pressure and volume in the HIR simulations increased the uniformity, with similar rainfall rate values obtained according to the ANOVA (Table 2). Conversely, under MIR, PR-30 and Spon + PR-10 treatments had worse uniformity than tillage and Spon. Outdoor rainfall simulation trials are susceptible to the influence of wind, a factor that is not present in indoor simulators [46,47]. This could affect the rainfall uniformity, although the simulations were conducted with wind speeds < 3 m/s.
The soil moisture just before each rainfall simulation was tested. It provided information on the ponding time and the effect on runoff and losses and initial soil moisture is strongly related to the runoff volume [48]. Nevertheless, all plots received the same amount of irrigation; therefore, the differences in the initial soil moisture are attributed to the effect of the several treatments. On the one hand, the tillage with bare soil is more exposed to evaporation than residue mulch [49]. The capacity of infiltration might also be reduced in untilled soil when the soil type is prone to surface sealing [44]. In addition, treatments with spontaneous vegetation increase the infiltration capacity due to the root system, but this leads to an increase in water consumption. It must be pointed out that the trials were conducted at the beginning of the season (September–October) with the spontaneous groundcover already established but with a low height. The trials under HIR were carried out before those under MIR, which could affect the soil moisture in the MIR set as the experimental plots had received a greater amount of water and radiation by the sun and evaporation was decreasing as time progressed. In fact, statistical differences were found under MIR, where tillage and Spon treatments showed lower soil moisture contents.

4.2. Runoff and Soil Loss

The soil protection provided by the groundcovers and the pruning residue mulch reduced water and soil losses in comparison to the tillage system (Table 3). Runoff and erosion were reduced with a higher soil cover [12]. The results agreed with those found by other authors in studies with a portable rain simulator on olive orchards and vineyards [50,51].
Mulching reduces soil loss intensity and runoff through various mechanisms, such as decreasing raindrop-induced splash erosion and surface sealing. Improvements in soil structure and coverage by the groundcovers, whether living or as residue mulch, also protect the soil from crusting, a common phenomenon in Mediterranean areas that exacerbates the harmful effects of extreme rainfall events [52]. It also reduces the velocity of surface flow and its connectivity, as well as the shear force exerted by runoff on soil detachment [53,54]. The effect of mulch depends on a variety of specific factors for a given climate and mulch type, such as soil type, residue density, length, slope, coverage provided [55], application pattern [47], and the time that the mulch covers the soil [56], among others. In olive orchards, significant variability in residue density over time is not expected, as the mulch is applied after pruning and consists of lignified materials that persist for several years [27].
The presence of groundcovers adds organic matter to the zone between tree rows and modifies surface flow by increasing random roughness [57]. Nevertheless, the root systems of the living groundcovers improved water infiltration [35] in comparison to the pruning residue mulch (Table 3). Spon was more effective than PR-30 at reducing runoff and erosion under HIR; however, PR-30 produced slightly lower soil loss than Spon under MIR, despite its higher initial soil moisture. The treatment with a higher dose of pruning residues (PR-30) was more effective in reducing losses, as the density of applied residues generally curbs the runoff generation and reduces erosion [47,58]. Wang et al. [59] points out that the impact of mulch on reducing runoff and soil loss intensity diminishes as the amount of residue increases, following a law of diminishing marginal returns. Furthermore, the soil and water conservation effectiveness of pruned branches generally decreases with rainfall intensity [58].
The results of this study agreed with those found in scientific literature. Comparable results in terms of water and soil losses were found in studies under natural rainfall [60,61,62,63] and performed with a rainfall simulator [35,36,58] when soil managements were compared.
Soil loss represented against runoff volume fitted an exponential model (Figure 2), indicating that the tillage plot was more erodible than other treatments. A similar trend was observed by Pan et al. [58]. Likewise, the sediment concentration in the runoff flow was higher for tillage treatment than for others. Treatments with groundcovers, either spontaneous vegetation, pruning residue mulch or a combination, were more effective in reducing soil losses than runoff volume, similarly to results obtained in previous studies [35,46,64,65,66].
Soil cover was the determinant factor in controlling water and soil losses. The inverse relationship between soil loss and soil cover shown in Figure 4a is similar to that found in the literature [12,55,63,67,68]. Often, the amount of biomass or mulch rate is represented instead of soil cover with a similar trend [67,69]. In treatments with any type of groundcover in this study, the soil cover was always above 55% and was key to significantly reducing the losses against tillage. This threshold of 55% was recommended by Snelder and Bryan [70] to protect the soil from storm events. Other authors recommend a similar value of 60% to keep the soil well protected and a minimum of 30% soil cover year-round [71]. A soil cover of 40% is also recommended by others as the minimum threshold for pruning residue mulches [25,28] and by Sastre et al. [63] for herbaceous groundcovers.

4.3. SOC Loss and Enrichment Ratio

The SOC loss pattern was similar to that for soil loss; like other studies, SOC and soil losses are positively correlated [35,72]. However, the differences with tillage were lower than those found for soil loss (Figure 4a,b). This is due to the lower SOC content of tilled plots [73], which can induce a smaller SOC loss than other richer soils [35]. Figure 3 shows the decreasing relationships of soil loss and SOC concentration of the dragged sediments. The high SOC content of the sediments from pruning residue plots is consistent with the high increase in SOC that the practice of mulching with shredded pruning residue can achieve [27].
The SOC enrichment ratios were generally greater than 1, and the trend was inversely related to soil loss (Figure 5). This is consistent with the preferential loss of finer particles in the runoff–erosion processes [14]. This selectivity in SOC is partially attributed to the sediments transported in the runoff flow that are richer in silt and clay particles than the soil from which they were dragged [74]. Higher aggregate stability in soil with groundcovers [75] and the increase in physically protected organic carbon fractions [76] influence the particle-size distribution in sediments. Higher aggregate stability may reduce its breakdown by precipitation impact, thus the labile SOC keeps protected [77]. The higher the rainfall intensity, the higher the sediment yield rate [54]; thus, more erosive rainfall events can mix surface and subsurface soil layers, reducing the SOC concentration of eroded sediments [74]. Particles larger than 63 μm are less likely to be eroded as they have a higher threshold shear stress and need more energy to detach and mobilize compared to smaller particles [78]. Therefore, the degree of selectivity is reduced with highly erosive events.
In scientific literature, enrichment ratios >1 are also reported [65,72,74,78,79]. Generally, the amount of soil loss has more influence on SOC enrichment than the soil cover [78,79]. Likewise, enrichment ratios of protected and non-protected organic carbon fractions did not differ significantly between managements in the study carried out by López-Vicente et al. [79].

5. Conclusions

The use of any type of groundcover, including herbaceous spontaneous vegetation, pruning residue mulch or a mixture, was effective at reducing loss associated with erosion processes. The soil loss was reduced by more than 95% and SOC loss by more than 85% regarding tillage. Runoff was better controlled with the treatments with spontaneous vegetation as the root system improved infiltration.
The system that combines spontaneous vegetation and shredded pruning residue mulch provided the best results as the soil cover was significatively higher. The soil cover was inversely related to the soil and SOC losses. The low degree of soil protection in the tillage system increased the losses, especially under HIR.
The soil loss implies the loss of SOC in the sediments dragged into the runoff flow; therefore, the losses associated with erosion have environmental and agronomical consequences. In less erosive events, generally, richer sediments are dragged, highlighting the characteristic selectivity of erosion processes.
The clear improvement in reduction in runoff, soil and SOC losses associated with erosion processes regarding tillage demonstrates that the groundcover system is environmentally and agronomically more sustainable than tillage-based systems.

Author Contributions

Conceptualization, A.R.-L. and R.O.-F.; methodology, F.P.-S. and R.M.C.-B.; software, M.A.R.-R.d.T. and M.M.-G.; validation, A.R.-L. and R.M.C.-B.; formal analysis, M.A.R.-R.d.T.; investigation, F.P.-S., M.A.R.-R.d.T. and A.R.-L.; resources, F.P.-S.; data curation, M.A.R.-R.d.T.; writing—original draft preparation, M.A.R.-R.d.T. and A.R.-L.; writing—review and editing, M.A.R.-R.d.T. and A.R.-L.; visualization, R.M.C.-B. and M.M.-G.; supervision, R.O.-F. and A.R.-L.; project administration, A.R.-L. and R.O.-F.; funding acquisition, A.R.-L. All authors have read and agreed to the published version of the manuscript.

Funding

We gratefully acknowledge the “Fondo Europeo de Desarrollo Regional (FEDER) y a la Consejería de Transformación Económica, Industria, Conocimiento y Universidades de la Junta de Andalucía, dentro del Programa Operativo FEDER 2014–2020” for the financial support provided for the project “Avance multidisciplinar en la gestión y conocimiento de las cubiertas de restos de poda en olivar a escala árbol, parcela y explotación” (US-1380979). F.P.-S.’s work was conducted on the basis of a contract (INV-02-2022-I-067) funded by this research project.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author/s.

Acknowledgments

The authors would like to thank the field and laboratory staff from the soil physics and chemistry team of the IFAPA Alameda del Obispo Centre for their collaboration in this study.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. FAO Agricultural Statistics. Available online: https://www.fao.org/faostat/es/#data/QCL (accessed on 24 June 2024).
  2. Ministerio de Agricultura Pesca y Alimentación. Encuesta Sobre Superficies y Rendimientos de Cultivos. Resultados Nacionales y Autonómicos. Available online: https://www.mapa.gob.es/es/estadistica/temas/estadisticas-agrarias/boletin20231_tcm30-690544.pdf (accessed on 16 June 2024).
  3. Junta de Andalucía. Consejería de Agricultura y Pesca. El Olivar Andaluz; Servicio de Publicaciones y Divulgación. D. Legal: SE-48-2003. IDEAS, Exclusivas y Publicidad S.L.: Sevilla, Spain, 2003; p. 134. Available online: https://www.juntadeandalucia.es/export/drupaljda/1337165631El_Olivar.pdf (accessed on 16 June 2024).
  4. Taguas, E.V.; Gómez, J.A. Vulnerability of olive orchards under the current CAP (Common Agricultural Policy) regulations on soil erosion: A study case in Southern Spain. Land Use Policy 2015, 42, 683–694. [Google Scholar] [CrossRef]
  5. Díez, C.M.; Moral, J.; Cabello, D.; Morello, P.; Rallo, L.; Barranco, D. Cultivar and Tree Density as Key Factors in the Long-Term Performance of Super High-Density Olive Orchards. Front. Plant Sci. 2016, 7, 1226. [Google Scholar] [CrossRef] [PubMed]
  6. Taguas, V.; Marín-Moreno, V.; Barranco, D.; Rafael, P.; García-Ferrer, A. Opportunities of Super High-Density Olive Orchard to Improve Soil Quality: Management Guidelines for Application of Pruning Residues. J. Environ. Manag. 2021, 293, 112785. [Google Scholar] [CrossRef] [PubMed]
  7. Gil-Ribes, J.A.; López-Giménez, F.J.; Blanco-Roldán, G.L.; Castro-García, S. Mecanización. In El Cultivo del Olivo; Barranco, D., Fernández, R., Rallo, L., Eds.; Mundi-Prensa: Madrid, Spain, 2017; pp. 1–995. [Google Scholar]
  8. Panagos, P.; Borrelli, P.; Poesen, J.; Ballabio, C.; Lugato, E.; Meusburger, K.; Montanarella, L.; Alewell, C. The New Assessment of Soil Loss by Water Erosion in Europe. Environ. Sci. Policy 2015, 54, 438–447. [Google Scholar] [CrossRef]
  9. Fan, D.; Jia, G.; Wang, Y.; Yu, X. The Effectiveness of Mulching Practices on Water Erosion Control: A Global Meta-Analysis. Geoderma 2023, 438, 116643. [Google Scholar] [CrossRef]
  10. Prosdocimi, M.; Tarolli, P.; Cerdà, A. Mulching Practices for Reducing Soil Water Erosion: A Review. Earth Sci. Rev. 2016, 161, 191–203. [Google Scholar] [CrossRef]
  11. Saavedra, M.; Pastor, M. Sistemas de Cultivo en Olivar. Manejo de Malas Hierbas y Herbicidas; Editorial Agrícola Española: Madrid, Spain, 2002. [Google Scholar]
  12. Espejo-Pérez, A.J.; Rodríguez-Lizana, A.; Ordóñez, R.; Giráldez, J.V. Soil Loss and Runoff Reduction in Olive-Tree Dry-Farming with Cover Crops. Soil Sci. Soc. Am. J. 2013, 77, 2140–2148. [Google Scholar] [CrossRef]
  13. Rodríguez-Lizana, A.; Ordóñez, R.; Espejo-Pérez, A.J.; González, P. Plant Cover and Control of Diffuse Pollution from P in Olive Groves. Water Air Soil Pollut. 2007, 181, 17–34. [Google Scholar] [CrossRef]
  14. Ordóñez-Fernández, R.; Rodríguez-Lizana, A.; Espejo-Pérez, A.J.; González-Fernández, P.; Saavedra, M.M. Soil and Available Phosphorus Losses in Ecological Olive Groves. Eur. J. Agron. 2007, 27, 144–153. [Google Scholar] [CrossRef]
  15. Durán-Zuazo, V.H.; Rodríguez-Pleguezuelo, C.R.; Martin-Peinado, F.J.; de Graaff, J.; Francia-Martínez, J.R.; Flanagan, D.C. Environmental Impact of Introducing Plant Covers in the Taluses of Terraces: Implications for Mitigating Agricultural Soil Erosion and Runoff. CATENA 2011, 84, 79–88. [Google Scholar] [CrossRef]
  16. Hermosin, M.C.; Calderon, M.J.; Real, M.; Cornejo, J. Impact of Herbicides Used in Olive Groves on Waters of the Guadalquivir River Basin (Southern Spain). Agric. Ecosyst. Environ. 2013, 164, 229–243. [Google Scholar] [CrossRef]
  17. Repullo-Ruibérriz de Torres, M.A.; Carbonell-Bojollo, R.; Alcántara-Braña, C.; Rodríguez-Lizana, A.; Ordóñez-Fernández, R. Carbon Sequestration Potential of Residues of Different Types of Cover Crops in Olive Groves under Mediterranean Climate. Span. J. Agric. Res. 2012, 10, 649–661. [Google Scholar] [CrossRef]
  18. Parras-Alcántara, L.; Díaz-Jaimes, L.; Lozano-García, B. Organic Farming Affects C and N in Soils Under Olive Groves in Mediterranean Areas. Land Degrad. Dev. 2015, 26, 800–806. [Google Scholar] [CrossRef]
  19. Repullo-Ruibérriz de Torres, M.A.; Carbonell-Bojollo, R.M.; Moreno-García, M.; Ordóñez-Fernández, R.; Rodríguez-Lizana, A. Soil Organic Matter and Nutrient Improvement through Cover Crops in a Mediterranean Olive Orchard. Soil Tillage Res. 2021, 210, 104977. [Google Scholar] [CrossRef]
  20. Govaerts, B.; Verhulst, N.; Castellanos-Navarrete, A.; Sayre, K.D.; Dixon, J.; Dendooven, L. Conservation Agriculture and Soil Carbon Sequestration: Between Myth and Farmer Reality. Crit. Rev. Plant Sci. 2009, 28, 97–122. [Google Scholar] [CrossRef]
  21. Calatrava, J.; Franco, J.A. Using pruning residues as mulch: Analysis of its adoption and process of diffusion in Southern Spain olive orchards. J. Environ. Manag. 2011, 92, 620–629. [Google Scholar] [CrossRef] [PubMed]
  22. BOE (Official State Bulletin of Spain), Law 7/2022, of April 8th, on Waste and Contaminated Soils for a Circular Economy. Available online: https://www.boe.es/eli/es/l/2022/04/08/7/con (accessed on 17 December 2024).
  23. Manzanares, P.; Ruiz, E.; Ballesteros, M.; Negro, M.J. Residual Biomass Potential in Olive Tree Cultivation and Olive Oil Industry in Spain: Valorization Proposal in a Biorefinery Context. Span. J. Agric. Res. 2017, 15, e0206. [Google Scholar] [CrossRef]
  24. BOE (Official State Bulletin of Spain), Law 03/2022, of December 24th, on Management System for the Common Agricultural Policy and Other Related Matters. Available online: https://www.boe.es/eli/es/l/2022/12/23/30 (accessed on 17 December 2024).
  25. Moreno-García, M.; Repullo-Ruibérriz de Torres, M.A.; Carbonell-Bojollo, R.M.; Ordóñez-Fernández, R. Management of Pruning Residues for Soil Protection in Olive Orchards. Land Degrad. Dev. 2018, 29, 2975–2984. [Google Scholar] [CrossRef]
  26. Ordóñez-Fernández, R.; Repullo-Ruibérriz de Torres, M.A.; Román-Vázquez, J.; González-Fernández, P.; Carbonell-Bojollo, R. Macronutrients Released during the Decomposition of Pruning Residues Used as Plant Cover and Their Effect on Soil Fertility. J. Agric. Sci. 2015, 153, 615–630. [Google Scholar] [CrossRef]
  27. Repullo, M.A.; Carbonell, R.; Hidalgo, J.; Rodríguez-Lizana, A.; Ordóñez, R. Using Olive Pruning Residues to Cover Soil and Improve Fertility. Soil Tillage Res. 2012, 124, 36–46. [Google Scholar] [CrossRef]
  28. Rodríguez-Lizana, A.; Espejo-Pérez, A.J.; González-Fernández, P.; Ordóñez-Fernández, R. Pruning Residues as an Alternative to Traditional Tillage to Reduce Erosion and Pollutant Dispersion in Olive Groves. Water Air Soil Pollut. 2008, 193, 165–173. [Google Scholar] [CrossRef]
  29. Henry, G.M.; Hoyle, J.A.; Beck, L.L.; Cooper, T.; Montague, T.; Mckenney, C. Evaluation of Mulch and Preemergence Herbicide Combinations for Weed Control in High-Density Olive (Olea europaea L.) Production. HortScience 2015, 50, 1338–1341. [Google Scholar] [CrossRef]
  30. González-Ruiz, R.; Gómez-Guzmán, A.; Martínez-Rojas, M.; García-Fuentes, A.; Cordovilla, M.; Sainz-Pérez, M.; Sánchez-Solana, A.; Rodríguez-Lizana, A. The Influence of Mixed Green Covers, a New Trend in Organic Olive Growing on the Efficiency of Predatory Insects. Agriculture 2023, 13, 785. [Google Scholar] [CrossRef]
  31. Ordóñez-Fernández, R.; Gonzalez-Fernández, P.; Pastor, M. Cubiertas Inertes: Los Restos de Poda como Protección y Mejora de las Propiedades del Suelo; Rodríguez-Lizana, A., Ordoñez-Fernández, R., Gil-Ribes, J., Eds.; Junta de Andalucía: Sevilla, Spain, 2007; p. 168. [Google Scholar]
  32. Rodríguez-Lizana, A.; Ramos, A.; Pereira, M.J.; Soares, A.; Ribeiro, M.C. Assessment of the Spatial Variability and Uncertainty of Shreddable Pruning Biomass in an Olive Grove Based on Canopy Volume and Tree Projected Area. Agronomy 2023, 13, 1697. [Google Scholar] [CrossRef]
  33. Petratou, D.; Nunes, J.P.; Guimarães, M.H.; Prats, S. Decision-Making Criteria to Shape Mulching Techniques for Fire-Prone Landscapes. Landsc. Ecol. 2023, 38, 3405–3425. [Google Scholar] [CrossRef]
  34. Iserloh, T.; Ries, J.B.; Arnáez, J.; Boix-Fayos, C.; Butzen, V.; Cerdà, A.; Echeverría, M.T.; Fernández-Gálvez, J.; Fister, W.; Geißler, C.; et al. European small portable rainfall simulators: A comparison of rainfall characteristics. CATENA 2013, 110, 100–112. [Google Scholar] [CrossRef]
  35. Repullo-Ruibérriz de Torres, M.A.; Ordónez-Fernández, R.; Giráldez, J.V.; Márquez-García, J.; Laguna, A.; Carbonell-Bojollo, R. Efficiency of four different seeded plants and native vegetation as cover crops in the control of soil and carbon losses by watererosion in olive orchards. Land Degrad. Dev. 2018, 29, 2278–2290. [Google Scholar] [CrossRef]
  36. Franklin, D.H.; Truman, C.C.; Potter, T.L.; Bosch, D.D.; Strickland, T.C.; Jenkins, M.B.; Nuti, R.C. Nutrient losses in runoff from conventional and no-till pearl millet on pre-wetted Ultisols fertilized with broiler litter. Agric. Water Manag. 2012, 113, 38–44. [Google Scholar] [CrossRef]
  37. Soil Survey Staff. Keys to Soil Taxonomy, 12th ed.; USDA-Natural Resources Conservation Service: Washington, DC, USA, 2014. [Google Scholar]
  38. Barfield, B.J.; Hirschi, M.C. Tipping bucket flow measurements on erosion plots. Trans. ASAE 1986, 29, 1600–1604. [Google Scholar] [CrossRef]
  39. Walkley, A.; Black, I.A. An examination of the Degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil Sci. 1934, 37, 29–38. [Google Scholar] [CrossRef]
  40. Christiansen, J.E. Irrigation by Sprinkling; University of California Agricultural Experimental Station: Berkley, CA, USA, 1942; Volume 670, Available online: https://www.researchgate.net/profile/Abdelkader-Bouaziz/post/Can_anyone_help_me_finding_this_article/attachment/61e45b5cf5675b211b1e8c36/AS%3A1112933983621120%401642355547947/download/Irrigation+by+Sprinkling.pdf (accessed on 3 January 2025).
  41. Laguna, A.; Giráldez, J.V. The description of soil erosion through a kinematic wave model. J. Hydrol. 1993, 145, 65–82. [Google Scholar] [CrossRef]
  42. Rodrigo-Comino, J.; Giménez-Morera, A.; Panagos, P.; Pourghasemi, H.R.; Pulido, M.; Cerdà, A. The potential of straw mulch as a nature-based solution for soil erosion in olive plantation treated with glyphosate: A biophysical and socioeconomic assessment. Land Degrad. Dev. 2020, 31, 1877–1889. [Google Scholar] [CrossRef]
  43. Alves Sobrinho, T.A.; Gómez-Macpherson, H.; Gómez, J.A. A portable integrated rainfall and overland flow simulator. Soil Use Manag. 2008, 24, 163–170. [Google Scholar] [CrossRef]
  44. Gómez, J.A.; Giráldez, J.V.; Pastor, M.; Fereres, E. Effects of tillage method on soil physical properties, infiltration and yield in an olive orchard. Soil Tillage Res. 1999, 52, 167–175. [Google Scholar] [CrossRef]
  45. Kinnell, P.I.A. A review of the design and operation of runoff and soil loss plots. CATENA 2016, 145, 257–265. [Google Scholar] [CrossRef]
  46. Gholami, L.; Sadeghi, S.H.; Homaee, M. Straw mulching effect on splash erosion, runoff, and sediment yield from eroded plots. Soil Sci. Soc. Am. J. 2013, 77, 268–278. [Google Scholar] [CrossRef]
  47. Abrantes, J.R.C.B.; Prats, S.A.; Keizer, J.J.; de Lima, J.L.M.P. Effectiveness of the application of rice straw mulching strips in reducing runoff and soil loss: Laboratory soil flume experiments under simulated rainfall. Soil Tillage Res. 2018, 180, 238–249. [Google Scholar] [CrossRef]
  48. Gholami, L.; Banasik, K.; Sadeghi, S.H.; Darvishan, A.K.; Hejduk, L. Effectiveness of straw mulch on infiltration, splash erosion, runoff and sediment in laboratory conditions. J. Water Land Dev. 2014, 22, 51–60. [Google Scholar] [CrossRef]
  49. Klocke, N.L.; Currie, R.S.; Aiken, R.M. Soil Water Evaporation and Crop Residues. Trans. ASABE 2009, 52, 103–110. [Google Scholar] [CrossRef]
  50. Rodrigo-Comino, J.; Iserloh, T.; Lassu, T.; Cerdà, A.; Keestra, S.D.; Prosdocimi, M.; Brings, C.; Marzen, M.; Ramos, M.C.; Senciales, J.M.; et al. Quantitative comparison of initial soil erosion processes and runoff generation in Spanish and German vineyards. Sci. Total Environ. 2016, 565, 1165–1174. [Google Scholar] [CrossRef]
  51. Rodrigo-Comino, J.; Taguas, E.; Seeger, M.; Ries, J.B. Quantification of soil and water losses in an extensive olive orchard catchment in Southern Spain. J. Hydrol. 2018, 556, 749–758. [Google Scholar] [CrossRef]
  52. Ries, J.B.; Hirt, U. Permanence of Soil Surface Crusts on Abandoned Farmland in the Central Ebro Basin/Spain. CATENA 2007, 72, 282–296. [Google Scholar] [CrossRef]
  53. Rahma, A.E.; Wang, W.; Tang, Z.; Lei, T.; Warrington, D.N.; Zhao, J. Straw Mulch Can Induce Greater Soil Losses from Loess Slopes than No Mulch under Extreme Rainfall Conditions. Agric. For. Meteorol. 2017, 232, 141–151. [Google Scholar] [CrossRef]
  54. Sadeghi, S.H.; Kiani Harchegani, M.; Asadi, H. Variability of Particle Size Distributions of Upward/Downward Splashed Materials in Different Rainfall Intensities and Slopes. Geoderma 2017, 290, 100–106. [Google Scholar] [CrossRef]
  55. Prats, S.A.; Martins, M.A.d.S.; Malvar, M.C.; Ben-Hur, M.; Keizer, J.J. Polyacrylamide Application versus Forest Residue Mulching for Reducing Post-Fire Runoff and Soil Erosion. Sci. Total Environ. 2014, 468–469, 464–474. [Google Scholar] [CrossRef]
  56. Cai, T.; Zhang, C.; Huang, Y.; Huang, H.; Yang, B.; Zhao, Z.; Zhang, J.; Jia, Z. Effects of Different Straw Mulch Modes on Soil Water Storage and Water Use Efficiency of Spring Maize (Zea mays L.) in the Loess Plateau of China. Plant Soil Environ. 2015, 61, 253–259. [Google Scholar] [CrossRef]
  57. Dunkerley, D. Organic Litter: Dominance over Stones as a Source of Interrill Flow Roughness on Low-Gradient Desert Slopes at Fowlers Gap, Arid Western NSW, Australia. Earth Surf. Process. Landf. 2003, 28, 15–29. [Google Scholar] [CrossRef]
  58. Pan, D.; Zhao, X.; Gao, X.; Song, Y.; Dyck, M.; Wu, P.; Li, Y.; Ma, L. Application Rate Influences the Soil and Water Conservation Effectiveness of Mulching with Chipped Branches. Soil Sci. Soc. Am. J. 2018, 82, 447–454. [Google Scholar] [CrossRef]
  59. Wang, C.; Ma, J.; Wang, Y.; Li, Z.; Ma, B. The Influence of Wheat Straw Mulching and Straw Length on Infiltration, Runoff and Soil Loss. Hydrol. Process. 2022, 36, e14561. [Google Scholar] [CrossRef]
  60. Francia, J.R.; Durán-Zuazo, V.H.; Martínez-Raya, A. Environmental impact from mountainous olive orchards under different soil management systems (SE Spain). Sci. Total Environ. 2006, 358, 46–60. [Google Scholar] [CrossRef]
  61. Gómez, J.A.; Llewellyn, C.; Basch, G.; Sutton, P.B.; Dyson, J.S.; Jones, C.A. The effects of cover crops and conventional tillage on soil and runoff loss in vineyards and olive groves in several Mediterranean countries. Soil Use Manag. 2011, 27, 502–514. [Google Scholar] [CrossRef]
  62. Kairis, O.; Karavitis, C.; Kounalaki, A.; Salvati, L.; Kosmas, C. The effect of land management practices on soil erosion and land desertification in an olive grove. Soil Use Manag. 2013, 29, 597–606. [Google Scholar] [CrossRef]
  63. Sastre, B.; Barbero-Sierra, C.; Bienes, R.; Marques, M.J.; García-Díaz, A. Soil loss in an olive grove in Central Spain under cover crops and tillage treatments, and farmer perceptions. J. Soils Sediments 2017, 17, 873–888. [Google Scholar] [CrossRef]
  64. Biddoccu, M.; Ferraris, S.; Opsi, F.; Cavallo, E. Long-term monitoring of soil management effects on runoff and soil erosion in sloping vineyards in Alto Monferrato (North-West Italy). Soil Tillage Res. 2016, 155, 176–189. [Google Scholar] [CrossRef]
  65. Martínez-Mena, M.; Carrillo-López, E.; Boix-Fayos, C.; Almagro, M.; García-Franco, N.; Díaz-Periera, E.; Montoya, I.; de Vente, J. Long-term effectiveness of sustainable land management practices to control runoff, soil erosion, and nutrient loss and the role of rainfall intensity in Mediterranean rainfed agroecosystems. CATENA 2020, 187, 104352. [Google Scholar] [CrossRef]
  66. Liu, R.; Thomas, B.W.; Shi, X.; Zhang, X.; Wang, Z.; Zhang, Y. Effects of ground cover management on improving water and soil conservation in tree crop systems: A meta-analysis. CATENA 2021, 199, 105085. [Google Scholar] [CrossRef]
  67. Podwojewski, P.; Janeau, J.L.; Valentin, C.; Lorentz, S.; Chaplot, V. Influence of grass soil cover on water runoff and soil detachment under rainfall simulation in a sub-humid South African degraded rangeland. Earth Surf. Process. Landf. 2011, 36, 911–922. [Google Scholar] [CrossRef]
  68. Keesstra, S.D.; Rodrigo-Comino, J.; Novara, A.; Giménez-Morera, A.; Pulido, M.; Di Prima, S.; Cerdà, A. Straw mulch as a sustainable solution to decrease runoff and erosion in glyphosate-treated clementine plantations in Eastern Spain. An assessment using rainfall simulation experiments. CATENA 2019, 174, 95–103. [Google Scholar] [CrossRef]
  69. Shi, Z.H.; Yue, B.J.; Wang, L.; Fang, N.F.; Wang, D.; Wu, F.Z. Effects of mulch cover rate on interrill erosion processes and the size selectivity of eroded sediment on steep slopes. Soil Sci. Soc. Am. J. 2013, 77, 257–267. [Google Scholar] [CrossRef]
  70. Snelder, D.J.; Bryan, R.B. The use of rainfall simulation tests to assess the influence of vegetation density on soil loss on degraded rangelands in the Baringo District, Kenya. CATENA 1995, 25, 105–116. [Google Scholar] [CrossRef]
  71. González-Sánchez, E.J.; Veroz-González, O.; Blanco-Roldan, G.L.; Márquez-García, F.; Carbonell-Bojollo, R. A renewed view of conservation agriculture and its evolution over the last decade in Spain. Soil Tillage Res. 2015, 146, 204–212. [Google Scholar] [CrossRef]
  72. Gómez, J.A.; Guzmán, M.G.; Giráldez, J.V.; Fereres, E. The influence of cover crops and tillage on water and sediment yield, and on nutrient, and organic matter losses in an olive orchard on a sandy loam soil. Soil Tillage Res. 2009, 106, 137–144. [Google Scholar] [CrossRef]
  73. Repullo-Ruibérriz de Torres, M.A.; Veroz-González, Ó.; Sánchez-Ruiz, F.; Moreno-García, M.; Ordónez-Fernández, R.; González-Sánchez, E.J.; Carbonell-Bojollo, R.M. Carbon Sequestration Through Groundcovers and Pruning Residues in Sustainable Olive Orchards Under Different Edaphoclimatic Conditions. Agriculture 2024, 14, 2118. [Google Scholar] [CrossRef]
  74. Martínez-Mena, M.; López, J.; Almagro, M.; Albaladejo, J.; Castillo, V.; Ortiz, R.; Boix-Fayos, C. Organic carbon enrichment in sediments: Effects of rainfall characteristics under different land uses in a Mediterranean area. CATENA 2012, 94, 36–42. [Google Scholar] [CrossRef]
  75. Sastre, B.; Antón-Iruela, O.; Moreno-Delafuente, A.; Navas, M.J.; Marques, M.J.; González-Canales, J.; Martín-Sanz, J.P.; Ramos, R.; GarcíaDíaz, A.; Bienes, R. Groundcovers Improve Soil Properties in Woody Crops Under Semiarid Climate. Agriculture 2024, 14, 2288. [Google Scholar] [CrossRef]
  76. Pareja-Sánchez, E.; Domouso, P.; Gómez-Muñoz, B.; Heras-Linares, M.T.; García-Ruíz, R. Conservation Practices Boost Soil-Protected Organic Carbon Stocks in Olive Orchards. Agriculture 2024, 14, 1354. [Google Scholar] [CrossRef]
  77. Almagro, M.; de Vente, J.; Boix-Fayos, C.; García-Franco, N.; Melgares de Aguilar, J.; González, D.; Solé-Benet, A.; Martínez-Mena, M. Sustainable land management practices as providers of several ecosystem services under rainfed Mediterranean agroecosystem. Mitig. Adapt. Strateg. Glob. Change 2016, 21, 1029–1043. [Google Scholar] [CrossRef]
  78. Koiter, A.J.; Owens, P.N.; Petticrew, E.L.; Lobb, D.A. The role of soil surface properties on the particle size and carbon selectivity of interrill erosion in agricultural landscapes. CATENA 2017, 153, 194–206. [Google Scholar] [CrossRef]
  79. López-Vicente, M.; Gómez, J.A.; Guzmán, G.; Calero, J.; García-Ruiz, R. The role of cover crops in the loss of protected and non-protected soil organic carbon fractions due to water erosion in a Mediterranean olive grove. Soil Tillage Res. 2021, 213, 105119. [Google Scholar] [CrossRef]
Agriculture 15 00677 g001
Figure 1. Scheme of an experimental plot with shredded pruning residue treatment. Shaded stripes represent surface occupied by pruning residue mulch.
Figure 1. Scheme of an experimental plot with shredded pruning residue treatment. Shaded stripes represent surface occupied by pruning residue mulch.
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Figure 2. Relationship between runoff and soil loss and fit to an exponential model. Spon: spontaneous vegetation; PR-10 (30): pruning residue 10 (30) t/ha.
Figure 2. Relationship between runoff and soil loss and fit to an exponential model. Spon: spontaneous vegetation; PR-10 (30): pruning residue 10 (30) t/ha.
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Figure 3. Relationship between SOC contents of the eroded sediments and the soil loss represented on logaritmic scale. Spon: spontaneous vegetation; PR-10 (30): pruning residues 10 (30) t/ha.
Figure 3. Relationship between SOC contents of the eroded sediments and the soil loss represented on logaritmic scale. Spon: spontaneous vegetation; PR-10 (30): pruning residues 10 (30) t/ha.
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Figure 4. Relationship between soil erosion and soil cover (a) and between SOC loss and soil cover (b) on semi-logaritmic scale. Spon: spontaneous vegetation; PR-10 (30): pruning residue 10 (30) t/ha.
Figure 4. Relationship between soil erosion and soil cover (a) and between SOC loss and soil cover (b) on semi-logaritmic scale. Spon: spontaneous vegetation; PR-10 (30): pruning residue 10 (30) t/ha.
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Figure 5. Relationship between soil erosion and SOC enrichment ratio on semi-logaritmic scale. Spon: spontaneous vegetation; PR-10 (30): pruning residue 10 (30) t/ha.
Figure 5. Relationship between soil erosion and SOC enrichment ratio on semi-logaritmic scale. Spon: spontaneous vegetation; PR-10 (30): pruning residue 10 (30) t/ha.
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Table 1. Physicochemical characteristics of the soil of the experimental plots.
Table 1. Physicochemical characteristics of the soil of the experimental plots.
DepthpHpHECCO32−CECPKSandSiltClayTextural Class
cm(H2O)(CaCl2)dS/m%cmol/kgmg/kgmg/kg%%%
0–208.67.80.1220.715.215.0447.047.834.218.0Loamy
20–408.67.90.2223.214.210.6317.248.831.120.1Loamy
40–608.67.90.2220.515.011.5266.049.532.018.4Loamy
EC: electrical conductivity; CEC: cationic exchangeable capacity; P: available phosphorus; K: exchangeable potassium.
Table 2. Rainfall rate, Christiansen uniformity coefficient (CUC), initial soil moisture and soil cover of the several treatments for high-intensity rainfall (HIR) and medium-intensity rainfall (MIR). Different letters within each intensity indicate significant differences among treatments according to LSD test at p ≤ 0.05. Spon: spontaneous vegetation; PR-10 (30): pruning residue 10 (30) t/ha; (±SD): standard deviation.
Table 2. Rainfall rate, Christiansen uniformity coefficient (CUC), initial soil moisture and soil cover of the several treatments for high-intensity rainfall (HIR) and medium-intensity rainfall (MIR). Different letters within each intensity indicate significant differences among treatments according to LSD test at p ≤ 0.05. Spon: spontaneous vegetation; PR-10 (30): pruning residue 10 (30) t/ha; (±SD): standard deviation.
IntensityTreatmentRainfall Rate (mm/h)CUC (%)Initial Soil Moisture (%)Soil Cover (%)
HIRTillage35.78(±2.73)a86.60(±4.66)a22.39(±0.57)a4.15(±0.55)d
Spon39.44(±0.45)a92.99(±3.00)a21.97(±2.41)a66.35(±1.43)b
PR-1035.72(±3.49)a87.76(±1.17)a21.24(±1.72)a60.75(±2.33)c
PR-3036.92(±3.21)a88.50(±2.65)a23.64(±4.04)a70.78(±0.88)b
Spon+PR-1036.07(±3.44)a89.69(±6.51)a25.31(±1.55)a93.34(±3.86)a
MIRTillage17.35(±0.60)a88.70(±1.88)a19.39(±2.95)b3.05(±0.00)d
Spon16.44(±0.52)a88.86(±2.67)a19.44(±1.70)b68.87(±4.65)b
PR-1016.26(±1.48)a71.84(±9.40)ab23.53(±1.00)a60.75(±2.33)c
PR-3015.91(±0.04)a69.80(±0.80)b23.73(±1.08)a70.78(±0.88)b
Spon+PR-1015.80(±0.99)a69.69(±3.10)b25.40(±1.27)a94.98(±3.71)a
Table 3. Runoff, soil loss and soil organic carbon (SOC) loss of several treatments for high-intensity rainfall (HIR) and medium-intensity rainfall (MIR). Different letters within each intensity indicate significant differences among treatments according to LSD test at p ≤ 0.05. Spon: spontaneous vegetation; PR-10 (30): pruning residues 10 (30) t/ha; (±SD): standard deviation.
Table 3. Runoff, soil loss and soil organic carbon (SOC) loss of several treatments for high-intensity rainfall (HIR) and medium-intensity rainfall (MIR). Different letters within each intensity indicate significant differences among treatments according to LSD test at p ≤ 0.05. Spon: spontaneous vegetation; PR-10 (30): pruning residues 10 (30) t/ha; (±SD): standard deviation.
IntensityTreatmentRunoff (m3/ha)Soil Loss (kg/ha)SOC Loss (kg/ha)
HIRTillage49.38(±14.42)a519.40(±303.16)a9.15(±4.49)a
Spon5.42(±1.75)c3.76(±1.01)b0.13(±0.04)b
PR-1028.27(±6.25)b12.99(±4.03)b0.78(±0.27)b
PR-3018.99(±9.23)bc7.39(±2.48)b0.41(±0.21)b
Spon+PR-102.19(±2.75)c1.96(±2.12)b0.07(±0.07)b
MIRTillage8.54(±6.85)a48.84(±34.48)a0.506(±0.38)a
Spon0.65(±0.16)b0.94(±0.18)b0.031(±0.00)b
PR-101.04(±1.31)b1.44(±1.00)b0.062(±0.04)b
PR-301.90(±2.49)b0.67(±0.38)b0.028(±0.01)b
Spon+PR-100.13(±0.06)b0.33(±0.14)b0.010(±0.01)b
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Repullo-Ruibérriz de Torres, M.A.; Pérez-Serrano, F.; Moreno-García, M.; Carbonell-Bojollo, R.M.; Ordóñez-Fernández, R.; Rodríguez-Lizana, A. The Use of Pruning Residue Mulch and Spontaneous Groundcovers to Control Erosion and Carbon Loss in Olive Orchards. Agriculture 2025, 15, 677. https://doi.org/10.3390/agriculture15070677

AMA Style

Repullo-Ruibérriz de Torres MA, Pérez-Serrano F, Moreno-García M, Carbonell-Bojollo RM, Ordóñez-Fernández R, Rodríguez-Lizana A. The Use of Pruning Residue Mulch and Spontaneous Groundcovers to Control Erosion and Carbon Loss in Olive Orchards. Agriculture. 2025; 15(7):677. https://doi.org/10.3390/agriculture15070677

Chicago/Turabian Style

Repullo-Ruibérriz de Torres, Miguel A., Francisco Pérez-Serrano, Manuel Moreno-García, Rosa M. Carbonell-Bojollo, Rafaela Ordóñez-Fernández, and Antonio Rodríguez-Lizana. 2025. "The Use of Pruning Residue Mulch and Spontaneous Groundcovers to Control Erosion and Carbon Loss in Olive Orchards" Agriculture 15, no. 7: 677. https://doi.org/10.3390/agriculture15070677

APA Style

Repullo-Ruibérriz de Torres, M. A., Pérez-Serrano, F., Moreno-García, M., Carbonell-Bojollo, R. M., Ordóñez-Fernández, R., & Rodríguez-Lizana, A. (2025). The Use of Pruning Residue Mulch and Spontaneous Groundcovers to Control Erosion and Carbon Loss in Olive Orchards. Agriculture, 15(7), 677. https://doi.org/10.3390/agriculture15070677

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