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Cuban Journal of Agricultural Science

Print version ISSN 0864-0408On-line version ISSN 2079-3480

Cuban J. Agric. Sci. vol.53 no.2 Mayabeque Apr.-June 2019  Epub Apr 01, 2019


Pasture science

Effect of agro-ecosystem and periods of the year upon earthworm population density on silvopastoral systems

H. R. Benavides1  * 

S. Vargas2 

D. Caicedo1 

L. Carvajal1 

D.I. Gutiérrez2 

J. Mina1 

1Universidad Politécnica Estatal del Carchi, Tulcán, Ecuador

2Universidad Central “Marta Abreu” de Las Villas, Carretera a Camajuaní. Km 6. Edificio C-1. Apto 110. Apartado Postal 54830. Santa Clara. Villa Clara. Cuba


A completely randomized design with three treatments (agro-ecosystems): A1 (grasses and Alnus acuminata Kunth); A2 (grasses and Acacia melanoxylon R. Br.) and A3 (Grassland) and four periods of the years (PY): 1-12-2015 (1); 1-6-2016 (2); 1-12-2016 (3) and 1-6-2017 (4) in a factorial analysis was conducted to evaluate the effects of agro-ecosystems (AES) and periods of the years upon the earthworm population density (EPD). There was not interaction (p>0.001) between AES and PY upon the EPD. The agro ecosystem A1 (189 m-2) differed (p<0.001) from A2 and A3 with (117 and 128 m-2) while these were similar in earthworms. The periods of the years effect (p<0.001) upon the EPD was higher in PY1 and PY2 (157 and 188 m-2) without differences between them, meanwhile the PY3 and PY4 were similar (118 and 116 m-2) but differed from the previous periods. The best results in the response variable was achieved in A1 agro-ecosystem which coincided with the better forestry indicators with a mean difference of 1.66 m and 5.84 cm, in height and diameter, respectively. The survival of earthworms and its population density in all agro-ecosystems and periods of the years suggested that EPD is an appropriate bio-indicator to assess the soil health in agroforestry systems and grasslands, closely related with the edaphoclimatic conditions, design and management.

Keywords: agroforestry; soil biota; grassland


Human activities can drastically alter the soil environment and influence earthworm populations directly by physical disturbances and indirectly by altering the physicochemical environment (Curry 2004). In this view, Mahecha and Angulo (2012) evaluating the nutrient management on silvopastoral systems (SPS) in the case study in Colombia, highlighted the higher content of soil organic matter and the improvement of the microclimate (moisture and temperature) due to the presence of trees in SPS, promoting the biological activity of the macro and micro fauna, resulting in a greater mineralization and availability of soil nutrients. These criteria were congruent with Crespo (2015) who assessed the factors influencing on nutrient recycling in permanent grasslands. The effect of earthworms upon the cropping systems have been recently reviewed summarizing the benefits of earthworms for crops and discussed some techniques to increase earthworms abundance (Bertrand et al. 2015). Several studies have been carried out to demonstrate the impact of trees on earthworm communities via leaf litter closely associated with soil characteristics e.g. anecic earthworms were abundant under Acer pseudoplatanus, Fagus sylvatica and Fraxinus excelsior which was related to calcium-rich litter and low soil acidification (Schelfhout et al. 2017). Following that line of research, the effect of the main soil characteristics (soil texture, organic matter, and nutrient contents) on the different mechanisms allowing earthworm to influence plant growth was discussed but the authors argued that it was difficult to predict the strength and direction of the effects of a given earthworm species on a given plant (Laossi et al. 2010). An integrated study of twelve ecological functions were characterized in the managed grassland plots varying in plant species richness. It was demonstrated that the diversity promotes stability across different ecological functions and levels of ecosystem organization in grasslands (Proulx et al. 2010). Moreover, the dynamics of global vegetation models was undertaken to provide a suitable modeling framework to assess grassland dynamics, productivity and the impact on the biogeochemical cycles under five different grassland management schemes at the global scale (Rolinski et al. 2017).

In tropical grasslands, it was evaluated the usefulness of earthworms and soil microbes as indicators of soil quality and how their occurrence, abundance, biomass and activity changed under different pastoral farming practices (Manono 2014). Soil health is defined as the continued capacity of the soil to function as a vital living ecosystem that sustains plants, animals and humans (USDA-NRCS 2018).

On the basis of the presented background, the current study aimed at evaluating the effects of agro- ecosystems, periods of the years and their interaction upon earthworm population density.


Location. The study was conducted in the parish “El Carmelo”, Canton Tulcán, Carchi, Ecuador. It is located in the hydrographic area 230, between 0º 41' and 3" N and 77º 36' and 42' W, altitude 2955 m.a.s.l., (INAMHI 2014). The soil was classified as Andosols, which is distinguished by high content of Fe and Al, melanic horizon andic properties, highly humid organic matter, lower ratio of fulvic/humic acids, blackish (FAO 2014). Soil horizon A1 was thick and well structured, pH 5.5-6.5, soil organic carbon 15-25 %, cation exchange capacity 15-25 meq 100-1 g of soil with predominant amount of Ca in the exchange complex, N ranged from medium to high values, bio-available P was low due to its fixation with humus-Al complexes (Zehetner et al. 2003). The precipitation and temperature (figure 1) during 2016 and partly 2017 were recorded (INAMHI 2016, 2017).

Fig. 1 Means of precipitation and temperature 

Experimental design and procedure. A completely randomized design with three treatments (agro- ecosystems): A1 (grasses and Alnus acuminata Kunth); A2 (grasses and Acacia melanoxylon R. Br.) and A3 (Grassland) and four periods of the years (PY): 1-12-2015 (1); 1-6-2016 (2); 1-12-2016 (3) and 1-6-2017 (4) in a factorial analysis was conducted to evaluate the effects of agro-ecosystems (AES) and periods of the years upon the earthworm population density (EPD). The predominant grasses in all AES were Pennisetum clandestinum L., Lolium perenne L., Holcus lanatus L. and Trifolium repens L. The AES consisted of A1 (grasses and trees of Alder, Alnus acuminata Kunth); A2 (grasses and acacia trees, Acacia melanoxylon B.R.) and A3, (grassland). The trees species were used because of their adaptation to the edaphoclimatic conditions of the Andean Ecuador.

Trees were planted in December 2015, taking into account the contour lines. The total area was divided into three AES. The grazing area managed for dairy cows consisted of 7.50, 4.64 and 6.25 ha in A1, A2 and A3, respectively. The soil quality was previously determined by Rosales et al. (2018). Double electric fences were established both to make paddocks and protect the young trees from animals’ damages. The trees had a population density of 1,000 ha-1, were planted in double rows and separated two meters apart each. Rational grass management in the paddocks of 2,000 m2 was applied by means of electric fences. It allowed to control the resting period of grasses, staying periods of the animals and grazing pressure in a daily striped availability of pastures in the paddocks. Eleven and ten cows with an average of live weight of 445 kg and a stocking rate capacity of 1.46, 1.76 and 2.15 cows’ ha-1 were kept in A1, A3 and A2, respectively. The animals permanently grazed in the paddocks at all time and only were out of them to be milked. The genetic composition of dairy cows was 80 and 20 % of Holstein and crossbreed Holstein x Jersey, respectively.

Earthworms sampling and statistical analysis. Field area to sample was geo-referenced with a global positioning system (Figure 2) and sampled in the same location four times in every subsequent period. The sampling layout was repeated in three transects, taking 10 samples in the high, middle and low relief respectively, accounting 30 soil samples of 0.027 m3 in each AES. In A1 and A2, soil samples were taken separated two meters apart from the trees rows, and soil sampling in A3 was diagonally randomized in the paddocks in zigzag. Earthworms were extracted from a 0.30 m × 0.30 m × 0.30 m block of soil layer dug out using square-headed shovel so that the results were expressed as EPD (numbers of individuals m-2). The soil extracted from the pit was placed onto a plastic sheet and searched for earthworms by crumbling the soil matrix by hand (Edwards and Lofty 1977).

Fig. 2 Images of agro-ecosystem: A1, A2 and A3 

The assumptions of both normality and homogeneity of variance were met with p value greater than 0.05 after performing raw data transformation to root square using Shapiro-Wilk and Levine’s test, IBM-SPSS (2013), respectively. Data were subjected to a factorial analysis using the following mathematical model, with p value of 0.001. A factorial analysis was conducted to evaluate the effects of agro-ecosystems (AES) and periods of the years upon the earthworm population density (EPD). To compare the means, the Tukey (1949) test was used. The statistical package IBM-SPSS (2013) version 22.0 was used. Original values of the amount of earthworms were transformed according to [TeX:] √x + 0.375 (DeCoster 2001).

[TeX:] Yijk = μ + Si + Pj + (S,P)ij+ ҽijk

Where: Yijk observation corresponding to the individual k in the agro-ecosystem i and period of the year j; μ: general mean of the population; S i: effect of the i-esimo agro-ecosystem; Pj: effect of the j-esimo period of the year; (S, P)ij : effect due to the interaction of the i-esimo agro-ecosystem with the j-esimo period of the year and ҽijk: experimental error.

A comparison of forestry indicators between A1: A. acuminate and A2: A. melanoxylon was accomplished. It included variables as height: total height of trees in m, using a metric tape supported by a ruler; diameter: measured at 0.20 m of height in cm, with caliper; AMI-H or AMI-D: annual mean increment either height or diameter divided by 1.5 year, respectively. Data were analyzed by means of the independent samples T-Test, IBM-SPSS (2013), with value of p < 0.05 (table 1).

Table 1 Comparison of forestry indicators in the agro-ecosystems 

n1: 192, n2: 183 (number of trees at 1.5 years after sowing); A1: A. acuminate, A2: A. melanoxylon. Independent samples T-Test, IBM. SPSS (2013), p < 0.05.


Effect of the agro ecosystems. There were highly significant differences among the agro ecosystems (p<0.001) in which earthworm population density (EPD) got the highest amount of individuals (189 m-2) in A1 (table 2). This result could be justified by the appropriate environment created by the effect of A. acuminata trees, where the mean difference (p<0.05) of the forestry indicators was higher compared to A. melanoxylon (table 1). Arteaga et al. (2016) studied the performance upon chemical variables on Andisol subjected to different land uses and concluded that the SOM (soil organic matter) was the variable that better detects the effect of soil use and management using Acacia melanoxylon and Alnus acuminata. This evidence justifies the use of these tree species in the current research with the same classification of soils in which the A. acuminata got better performance (table 1).

Table 2 Effect of the agro ecosystems upon earthworm’s population density m-2 

ab Means without common letter in the row are different at p < 0.001 (Tukey 1949).

( ) Means of original values *** p< 0,001

Earthworms (Lumbricus terrestris L., Annelida: Oligochaeta) comprise roughly 3,000 species grouped into five families. Earthworms are very versatile and are found in nearly all terrestrial ecosystems, and they play an important role in soil improvement. Soil (habitat quality), climate (temperature, precipitation, climatic water balance, time course) and food (nutrient flow) are the three main factors determining the abundance of earthworms in the forest and agro-ecosystems (Zhenjun 2011).

In the current research, it was demonstrated that the SOM had the lowest value in A1 (Rosales et al. 2018). This effect could be explained as the soil organic matter (SOM) rate of production and biodegradation caused by the earthworms which were higher in EPD compared to A2 and A3. It was remarkable, that the SOM in the soil samples collected in all AES had very high values. These are normally found in Andosols, The main problem in the Andean soils is related with the SOM biodegradation (FAO 2015). The missing effects of interactions could be explained due to in the first three years, the fast growing trees removed part of the soil nutrient reserves and did not produce enough litter. However, once the canopy was closed (4-5 years) the trees can act as self-nourishing system via litter production and decay (Kumar et al. 1998). In this sense, Crespo (2015) stated that grassland litter was considered the most important source of nutrient recycling in permanent grasslands, depending on grass species, climate and biological activity of soil. In the present research, from the beginning to 18 months later, the effect of agro ecosystem on the botanical composition showed higher percentage (P<0.05) of Pennisetum clandestinum (A2), Lolium multiflorum (A1), Dactylis glomerata (A1), Holcus lanatus (A2 and A3) and Trifolium repens (A2 and A3) (Chamorro 2018). On the other hand, the storage rate could have affected the EPD because of the agro-ecosystem A2 was 0.39 and 0.69 higher than A3 and A1, respectively. From this point of view, Murgueitio et al. (2006), assessing the impact of the silvopastoral systems on dairy cattle production stated that the SPS increased their stocking rate and milk production, ranging from 87.5-166.6 % and 20-35 %, respectively. On the other hand, Crespo and Martínez (2016) pointed out the increment of SOM in a biomass bank of Cenchrus purpureus (Schumach.) cv. CUBA CT-115 with different exploitation years in which the interactions of soil-plant-animal were highlighted. Moreover, earthworms, as ecosystem engineers, help to mineralize soil organic matter, construct and maintain soil structure, and stimulate plant growth (Marichal et al. 2017).

In another experiment with three years of study it was found higher EPD in protein bank with Leucaena (Leucaena leucocephala) and native grasses compared to Sacharum officinarum AES (Vargas 2013). In the current research were not found differences between A. melanoxylon and grassland (table 2). These findings were congruent with Decaëns et al. (2017) who found that permanent grasslands had higher EPD compared to crops AES.

Period of the years. There were not differences between PY1 and PY2, which were different from PY3 and PY4 (p<0.000), while the latter periods were similar in EPD (table 3). The first samplings of earthworms in all AES were accomplished before introducing the trees and fencing. The EPD was not affected from the first sampling to six months later with more than 150 individuals m-2. The higher response in EPD could be explained because of the existence of permanent grassland with no-tilled practices in the PY1 that contributed to soil preservation (Pelosi et al. 2013, 2016). After one year and one and a half year of rational grass management the EPD was stabilized with lesser amount (116-118) of individual m-2. The population density of trees was the same both in A1 and A2. In this sense, Hoosbeek et al. (2018) demonstrated changes on C, N and P stock with distance from trees in silvopastoral systems composed grasses with isolated trees, in Nicaragua and tree species effect was also pointed out. In the current research, the agro ecosystem with A. acuminata got better forestry indicators and its EPD was higher compared to A. melanoxylon, sown at the same time. Grazing indicators were measured after two months of pasture height stabilization. The average number of rotations per paddocks ranged from 14-18 to all AES, what could also have contributed to increase the SOM via feces and urine. The resting period in the paddocks ranged from 28 -32 days in all AES, and the total average assigned area of pasture was 227, 155 and 189 m2 cow-1 day-1 to A1, A2, and A3, respectively. It was noticeable, the use of strip grazing in which a new portion of grasses was assigned to the cows at 7.00 a.m., 10.30 a.m. and 4.00 p.m. depending on the availability and residues of grasses, calculated with the folding plate pasture meter. The availability of pastures was adjusted every week, and calibrated according to the predominant pastures in the agro-ecosystems (Chamorro 2018).

The accumulated rains in 17 out of 18 months of research time were higher than 50 mm and the temperature mean ranged (10.8-14.2 °C) in the whole research period (figure 1). These temperatures were considered as the optimum range to reproduce the earthworms (Otto 1990).

Table 3 Effect of the periods of the year upon earthworm population density m-2 

ab Means without common letter in the column are different at p < 0.001 (Tukey 1949)

( ) Means of original values

Besides, the other factor that might have influenced on earthworm survival was the shadow. It was found more EPD in A1 in which the trees got better forestry indicators. In addition, Eisenhauer et al. (2014) tested the hypothesis in the field warming experiment at two sites in Minessota, USA by sampling earthworms in closed and open canopy in three temperature treatments and stated that warming induced reductions in soil water content decreasing the earthworm performance. Fisichelli et al. (2013) reported that 93 % of the studied sites showed earthworm activity, and that activity was largely explained by soil pH, precipitation, and litter quality. In the current research, pH was above 5.55 in all AES (p<0.05) but the best performance was obtained by A1 and A2 in which there were the presence of trees (Rosales et al. 2018). Moreover switching from a conventional to an alternative system like agroforestry systems, involves a transition period, from which the system moves towards a new state of equilibrium, encourages nutrient uptake from deep soil horizons, while their litter helps to replenish soil nutrients, maintain organic matter, and supports complex soil food chains (Altieri et al. 2017). In a broader perspective Dollinger and Shibu (2018) reviewed 28 papers that clearly illustrated that agroforestry would enrich soil organic carbon better than monoculture systems, it could improve soil nutrient availability and soil fertility due to the presence of trees in the agro-ecosystems and enhance soil microbial dynamics which would positively influence soil health. Furthermore, Emem-Obong et al. (2015) highlighted the efficacy of earthworms vs. genetically modified substances as a sustainable eco-friendly option constructively engineering soil and human health with minimal environmental and ecological impact. In other study, EPD and its biomass were higher in permanent grasslands than in arable land. Among different abiotic soil parameters, climate related characteristics and water availability affected the distribution of earthworms (Kanianska et al. 2016). In sum, the best results in EPD were achieved in A1 agro-ecosystem, which coincided with the best forestry indicators. The survival of earthworms and its population density in all agro-ecosystems and periods of the years suggested that EPD is an appropriate bio-indicator to assess the soil health in agroforestry systems and grasslands, closely related with the edaphoclimatic conditions, design and management.


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Received: November 21, 2018; Accepted: February 07, 2019

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