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Cuban Journal of Agricultural Science

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

Cuban J. Agric. Sci. vol.54 no.4 Mayabeque Oct.-Dec. 2020  Epub Dec 01, 2020


Pasture Science

Characterization of the edaphic macrofauna in five grassland agroecosystems from Granma province. Richness and abundance

1Instituto de Investigaciones Agropecuarias “Jorge Dimitrov”. Carretera vía Manzanillo km 16 ½, Peralejo, Bayamo, Granma, Cuba

2Instituto de Ciencia Animal, Apartado postal 24, San José de las Lajas, Mayabeque, Cuba


The objective of this study was to evaluate the performance of richness and abundance of edaphic macrofauna in five grassland agroecosystems in Granma province. Samplings were carried out twice a year, once during rainy season and once in dry season, in the period between July 2014 and March 2017. The edaphic macrofauna was collected according to the standard methodology proposed by the Tropical Soil Biology and Fertility (TSBF) and by pitfall traps. An amount of 28,030 individuals was captured in the five agroecosystems, in the three years of research, of them 6,423 in monoliths and 21,607 in pitfall traps. The abundance and richness showed variable performance in both climatic periods in all the studied agroecosystems, with the two sampling methods. During dry season of the second year, a superior performance of macrofauna with respect to rainy period was observed. In Estación de Pastos agroecosystem, the greatest abundance and diversity of edaphic macrofauna was found, which confirms the beneficial effect of silvopastoral systems in this group of edaphic biota. It was concluded that, in the studied grassland agroecosystems, edaphic macrofauna had a heterogeneous performance in the evaluated seasons.

Keywords: monoliths; soil organisms; pitfall traps

The change in land use and its use intensity has a direct impact on the structure of vegetation and physical-chemical properties of soil, and an indirect impact on abundance, richness and diversity of the edaphic macrofauna, as well as on its functional composition. (Tapia et al. 2016 and Silva et al. 2018). Other factors that affect the edaphic macrofauna are type of soil, content of nutrients and organic matter, pH, texture and structure, as well as factors of climatic origin such as rainfall, temperature, wind speed and relative air humidity (Machado et al. 2015).

Absence or reduction of tree stratum in grasslands simplifies plant structure, which leads to litter homogenization, changes in temperature, insolation and organic matter content. All of this causes a decrease in niches and in populations of different groups of macrofauna (Cabrera 2019). Animal grazing may be one of the causes of edaphic macrofauna reduction, in which the response of invertebrates depends on stocking rate and grazing intensity. In addition, the trampling of animals causes a decrease of stability of organo-mineral aggregates, an increase of their compaction and, consequently, less water infiltration and oxygen availability, which limits the activity of this fauna (Bautista et al. 2009). The objective of the present research was to evaluate the performance of richness and abundance of edaphic macrofauna in five grassland agroecosystems in Granma province.

Materials and Methods

The research was developed in five grassland agroecosystems of Granma province, located in the southwestern portion of the eastern region of Cuba. Agroecosystems El Triángulo, El Progreso, Cupeycito, Ojo de agua and Estación de Pastos show contrasting characteristics regarding type of soils, management and productive purpose (table 1).

Table 1 Main characteristics of the studied agroecosystems 

Agroecosystem El Triángulo and El Progreso Cupeycito Ojo de agua Estación de Pastos
Municipality Bayamo Jiguaní Guisa Bayamo
Affiliation UBPC Francisco Suárez Soa Empresa Genética Manuel Fajardo Farm of Rafael Almaguer, CCS Braulio Coroneaux IIA Jorge Dimitrov
Purpose Milk production Rearing Bull fattening Bull fattening
Type of soil Pellic vertisol Carbonated soft brown Carbonated soft brown Fluvisol
Grazing method Continuous Rotational Continuous Rotational
Total grazing area (ha) T:18.5 P: 20.4 14.2 6.7 0.8
Sampling area (ha) and % of total area T: 2 11% P: 2 10% 1.8 13% 1.2 18% 0.8 100%
Predominant type of grass Blue grass (Dichanthium caricosum L. A. Camus) and star grass (Cynodon nlemfuensis Vanderyst.) Guinea grass (Megathyrsus maximus (Jacq.) B. K. Simon & S. W. L. Jacobs) Blue grass (Dichanthium caricosum L. A. Camus) Silvopastoral system with guinea grass and Leucaena leucocephala (Lam.) de Wit
Forage area (ha) Sugar cane (‎Saccharum officinarum L.):2 King grass (Cenchrus purpureus Schumach) Morrón:1.5

  • 1

  • 4

  • 0.5

  • 3.0

Usage time 20 years 10 years 7 years 10 years
Breed and stocking rate (LAU ha-1) Crossbred Siboney 1.5 Criollo 1.7 Crossbred 2.2 Crossbred Siboney 1
General conditions Totally deforested grazing area, without paddocks, with floods during rainy season Good shade per trees and paddocking, highly stony Good shade per trees, without paddocks, relief with slopes and sensitivity to erosion Good shade per trees, area of intense drought

T: El Triángulo P: El Progreso

Experimental period. The study was developed in the period between July 2014 and March 2017. Provincial means of climatic variables are shown in table 2. To facilitate the statistical analysis and characterization of the variables under study, three years were defined: year 1: rainy period (PLL)-2014 and dry period (PPLL)-2015, year 2: PLL-2015 and PPLL-2016 and year 3: PLL-2016 and PPLL-2017.

Table 2 Performance of annual climatic variables in the experimental period 

Variables 2014 2015 2016 2017
Rainfall, mm ⃰ 1335.7 1286.6 1187.3 1510.5
Number of days with rain, U 245 229 197 133
Maximum temperature, ºC 32.1 32.2 32.2 31.9
Minimum temperature, ºC 21.3 21.8 21.4 21.4
Relative humidity, % 76 76 76 76

⃰Data taken from provincial means from the Anuario Estadístico de Cuba (ONEI)

In the rainy period, the months from July to September were used as sampling months and from January to March in dry period, as they were the most representative months of both climatic periods. For this, the criteria of specialists from the Provincial Meteorology Center in Granma were considered.

Sampling and identification of the edaphic macrofauna. Two methods were used: the one recommended by Tropical Soil Biology and Fertility (TSBF) program (Anderson and Ingram 1993) and pitfall traps (Moreira et al. 2012). For the first method, litter was previously cleaned and all kinds of foreign elements were removed, such as stones and plant residues.

In the diagonal of the sampling area, five monoliths were extracted per hectare, measuring 25 x 25 x 20 cm, at a distance of 20 m. In situ macrofauna individuals were manually collected and counted. Worms (Oligochaeta: Haplotaxida) were preserved in 4% formaldehyde, and the remaining invertebrates in 70% ethanol.

For the second sampling method, nine traps were placed in each study area, arranged in the two diagonals, in the shape of a cross, with a trap in its center. Plastic containers, 8 cm in diameter and 10 cm deep, were used, which were buried flush with the ground, trying to damage as little as possible the surrounding area.

Afterwards, an aqueous solution (0.003 %), prepared with LABIOFAM commercial liquid detergent, was added and covered with dry leaves and plant remains typical of each agroecosystem. After seven days, the contents of the traps were collected in glass flasks and transferred to the entomology laboratory from the Provincial Laboratory of Plant Health in Granma. With the use of the stereoscope, individuals were extracted from the solution and counted, and placed in vials with 70% ethanol. Variables number of individuals (abundance) and number of taxonomic units (richness) were defined.

To identify the preserved specimens, keys and taxonomic references of Alayo (1974), Hickman et al. (2001), Brusca and Brusca (2003) and Fontela and Matienzo (2011) were consulted. The entomological collection of the provincial plant health laboratory in Granma was also taken as a reference.

Statistical analysis. The theoretical assumptions of the analysis of variance for variables number of individuals and number of taxonomic units were verified, from Shapiro and Wilk (1965) test for normality of errors and Levene (1960) test for variance homogeneity. As the analyzed variables did not fit with the theoretical assumptions of ANAVA, the transformations √x and √x+1 were used. However, as they did not improve the fulfillment of these assumptions, non-parametric analysis of variance was carried out by Wilcoxon (Mann-Whitney U) method (Lehmann 1975), for independent samples based on the ranges of original observations. Conover (1999) test was applied to compare mean ranges. The statistical program INFOSTAT version 2012 was used (Di Rienzo et al. 2012).

Results and Discussion

An amount of 28,030 individuals was captured in the five agroecosystems, in the experimental period, of them 6,423 in monoliths and 21,607 in pitfall traps. In Estación de Pastos agroecosystem, the largest number of individuals was captured by both sampling methods (figure 1).

Figure 1 Abundance of individuals of the edaphic macrofauna by sampling method in the five studied agroecosystems 

In Estación de Pastos agroecosystem, a greater number of classes/orders (as superior taxonomic units) was observed, with 17 and the highest total number of taxonomic units (73) of the most abundant and diverse edaphic macrofauna (figure 2).

Figure 2 Number of taxonomic units in both sampling methods in the studied agroecosystems 

Other authors have also reported greater diversity and density of edaphic macrofauna in silvopastoral systems, in relation to grass monoculture grasslands (Cabrera et al. 2017 y Ramírez et al. 2018). This fact could be associated with the combination of herbaceous stratum with Leucaena trees, which improves soil conditions, due to quality and quantity of included litter. The litter layer also maintains humidity and temperature of soil, which favors the development of the edaphic macrofauna (Hernández et al. 2008). Likewise, Cabrera (2012) commented that livestock systems with arboreal elements demonstrate richness of groups and an abundance of macrofauna comparable with those of natural ecosystems such as forests, due to the greater availability of resources for refuge and feeding of the edafofauna.

Humidity is essential for the organisms of the edaphic macrofauna, since they have integuments and other structures that need to be kept moist to carry out respiration. Earthworms (Phylum: Annelida), for example, require oxygen dissolved in soil solution to breathe (Cabrera et al. 2019). Maintaining the proper temperature is also very important for these organisms, since its increase leads to exoskeleton molting of insects, causing them to be more exposed to predatory organisms and other environmental factors, including solar radiation.

Abundance (number of individuals) and richness (number of taxonomic units) of the edaphic macrofauna, showed variable performance, in both climatic periods in the two sampling methods (tables 3 and 4). It was not possible to establish the pattern of abundance of this edaphic group in one or another climatic period, that is, there was no constant relationship between season and the studied variables.

Table 3 Seasonal performance of richness and abundance of the edaphic macrofauna determined by the monolith method 

Variables Year 1 Year 2 Year 3
El Triángulo
Number of individuals Number of taxonomic units 11.80† (3.60) SD=6.83 9.20 (3.20) SD=10.12 8.55 (15,80) SD=38.36 12,45 (36.70) SD=33.89 (5.70) 0
p=0.1965 p=0.1278 ---
12.10 (0.60) SD=0.84 8.90 (0.10) SD=0.32 8.15 (1.70) SD=2.45 12.85 (6.00) SD=5.35 (1.40) 0
p=0.1108 p=0.0660 ---
El Progreso
Number of individuals Number of taxonomic units 11.10 (6.20) SD=6.00 9.90 (7.70) SD=13.24 8.40 (9.30) SD=24.34 12.60 (64.10) SD=68.04 13.55 (21.20) SD=23.99 7.45 (2.50) SD=7.91
p=0.6194 p=0.0823 p=0.0093
12.05 (2.50) SD =2.32 8.95 (1.20) SD =1.99 8.10 (1.00) SD =2.00 12.90 (4.80) SD =4.24 13.50 (2.30) SD =2.21 7.50 (0.30) SD =0.95
p=0.1978 p=0.0466 p=0.0101
Number of individuals Number of taxonomic units 8.56 (15.50) SD =20.98 8.44 (11.13) SD =11.49 10.13 (28.88) SD =31.38 6.88 (60.88) SD =71.58 10.00 (13.13) SD =13.23 7.00 (36.13) SD =40.81
p=0.9756 p=0.1866 p=0.2230
8.81 (3.75) SD =4.23 8.19 (2.75) SD =1.49 11.06 (3.88) SD =3.83 5.94 (8.50) SD =4.28 10.19 (2.50) SD =1.93 6.81 (4.38) SD =2.92
p=0.8236 p=0.0295 p=0.1660
Ojo de agua
Number of individuals Number of taxonomic units 4.17 (66.00) SD=54.81 8.83 (16.83) SD=36.43 7.67 (12.83) SD=8.18 5.33 (84.00) SD=101.2 7.25 (12.67) SD=9.46 5.75 (19.33) SD=11.11
p=0.0260 p=0.2879 p=0.5087
4.83 (4.83) SD=2.40 8.17 (2.50) SD=3.08 8.67 (2.50) SD=1.52 4.33 (8.17) SD=4.83 7.92 (4.67) SD=3.44 5.08 (7.17) SD=3.19
p=0.1234 p=0.0390 p=0.2035
Estación de Pastos
Number of individuals Number of taxonomic units 4.25 (41.50) SD=20.24 4.75 (46.50) SD=49.19 4.50 (103.00) SD=51.14 4.50 (116.25) SD=99.79 6.25 (43.75) SD=13.89 2.75 (184.00) SD=121.29
p=0.8857 p>0.9999 p=0.0571
5.50 (5.50) SD=0.58 3.50 (7.75) SD=3.10 5.00 (11.50) SD=4.43 4.00 (16.00) SD=8.98 5.75 (10.00) SD=6.06 3.25 (14.50) SD=4.65
p=0.4000 p=0.6857 p=0.2000

† Mean of assigned ranges, (): mean of original data, SD: standard deviation

Table 4 Seasonal performance of richness and abundance of the edaphic macrofauna determined by the pitfall trap method 

Variables Year 1 Year 2 Year 3
El Triángulo
Number of individuals Number of taxonomic units 7.39† (42.00) SD=57.67 11.61 (5.11) SD=6.15 14.00 (1.56) SD=2.13 5.00 (89.11) SD=133 11.94 (15.11) SD=23.87 7.06 (35.00) SD=38.80
p=0.0944 p<0.0001 p=0.0526
8.61 (1.67) SD=1.12 10.39 (1.33) SD=1.00 14.00 (0.67) SD=0.87 5.00 (9.56) SD=3.21 11.11 (3.00) SD=1.87 7.89 (4.56) SD=2.60
p=0.4871 p<0.0001 p=0.2123
El Progreso
Number of individuals Number of taxonomic units 7.94 (17.89) SD=15.69 11.06 (12.67) SD=21.52 12.11 (55.33) SD=68.81 6.89 (423.00) SD=860.35 5.22 (31.44) SD=14.12 13.78 (6.22) SD=5.93
p=0.2159 p=0.0388 p=0.0001
8.00 (1.33) SD=1.00 11.00 (0.78) SD=1.09 11.61 (3.56) SD=2.51 7.39 (5.89) SD=2.32 6.89 (5.56) SD=1.67 12.11 (3.33) SD=2.78
p=0.2559 p=0.0931 p=0.0340
Number of individuals Number of taxonomic units 7.72 (63.11) SD=73.30 11.28 (27.44) SD=41.66 11.89 (39.33) SD=34.48 7.11 (99.11)SD=72.39 11.28 (95.67) SD=166.33 7.72 (116.89) SD=146.91
p=0.1587 p=0.0594 p=0.1673
6.83 (1.56) SD=0.73 12.17 (0.67) SD=0.71 12.50 (2.78) SD=1.64 6.50 (6.00) SD=3.08 7.50 (5.11) SD=2.26 11.50 (3.44) SD=1.51
p=0.0397 p=0.0159 p=0.1146
Ojo de agua
Number of individuals Number of taxonomic units 6.50 (153.44) SD=169.91 12.50 (30.44) SD=53.38 9.06 (99.89) SD=149.75 9.94 (48.22) SD=19.10 9.44 (86.78) SD=136.80 9.56 (50.44) SD=35.44
p=0.0148 p=0.7463 p>0.9999
7.00 (2.44) SD=1.42 12.00 (1.11) SD=1.05 12.33 (3.22) SD=2.17 6.67 (6.22) SD=2.59 11.50 (3.22) SD=1.79 7.50 (4.78) SD=2.33
p=0.0504 p=0.0188 p=0.1144
Estación de Pastos
Number of individuals Number of taxonomic units 6.11 (250.44) SD=117.26 12.89 (64.33) SD=128.02 8.56 (220.00) SD=226.65 10.44 (110.11) SD=43.90 6.28 (73.89) SD=26.75 12.72 (39.11) SD=23.33
p=0.0053 p=0.4749 p=0.0077
5.67 (1.89) SD=0.78 13.33 (0.44) SD=0.53 11.78 (5.22) SD=1.72 7.22 (7.44) SD=2.74 6.67 (6.44) SD=1.59 12.33 (4.33) SD=1.80
p=0.0014 p=0.0746 p=0.0217

For example, in the monolith method, no significant differences were found in any evaluated year in El Triángulo agroecosystem, although during dry season, corresponding to the third year, the presence of individuals was not observed, from which it is inferred that there was a better performance of the macrofauna in rainy period (table 2). In El Progreso, the number of taxonomic units in the second year was superior during dry season. In the third year, there were differences in the two evaluated variables, with better performance in the rainy season.

In Cupeycito, the number of taxonomic units was also significantly higher in the dry season of the second year. In Ojo de agua, during the first year, the number of individuals was superior in the rainy season, while, in the third year, the number of taxonomic units had better performance in dry season. In Estación de Pastos, no significant differences were detected in any evaluated period for any of the two variables.

In the case of pitfall traps, in El Triángulo agroecosystem, better performance of the two variables under study was evidenced in the dry period of the second year (table 3). In the case of El Progreso, the number of individuals was superior in dry season corresponding to the second year, while, in the third year, the two variables had a better performance in rainy season.

In Cupeycito agroecosystem, significant differences were only found in the number of taxonomic units, in the first and second year. In the first, the indicator had a better performance in the rainy season, while it was superior in the second during dry season. However, in Ojo de agua, significant differences occurred in the number of individuals, in the first year, with a higher value in PLL, while in the second year, a better performance of the variable number of taxonomic units was observed during PPLL.

In Estación de Pastos agroecosystem, significant differences were detected in the indicators studied in the first and third years. In both, the highest values ​​were observed in rainy season.

Several researchers coincide in stating that the highest abundance of individuals of the edaphic macrofauna is observed during rainy period, and they even recommend this period for samplings (Cabrera et al. 2011 and Noguera et al. 2017). According to Souza et al. (2016), the greatest diversity and abundance of edaphic fauna is generally found in the rainy season, since water contributes with vital processes of these organisms such as respiration, reproduction and feeding. Nevertheless, the conditions that promote water excess cause the edaphic communities to decrease, either because they come to the surface or migrate to deep soil strata, in search of more appropriate micro-environments for their establishment (Cabrera and López 2018).

In this sense, Brown et al. (2001), in grasslands of Mexico, verified that density of edaphic macrofauna was two times superior in rainy season compared to dry season, and they related it to the greater presence of earthworms and termites. On the other hand, Hernández et al. (2018) observed superior performance of the edaphic macrofauna in rainy period with respect to dry season in grassland, forage and polyculture areas in Cangrejeras town, Artemisa, Cuba.

The distribution of soil macrofauna depends on several factors such as rainfall or climate seasonality, which, at the same time, define temperature and humidity of soil, since they are the edaphoclimatic variables that influence the most on macrofauna of tropical soils (Cabrera and López 2018). All these factors have wide variability in the climatic region in which the studied agroecosystems are located (Montecelos et al. 2018), which could influence on the variable performance of macrofauna.

In this sense, a very important part of interannual variability of climatic elements in Cuba is explained by the presence of El Niño/Southern Oscillation (ENSO), which tends to favor greater precipitation during dry season (Álvarez et al. 2015 and Montecelos et al. 2018). This phenomenon had an intense manifestation between 2015 and 2016 (Galván et al. 2018), period included in this research. In agroecosystems in which significant differences were found in the studied variables, in the second year (PLL 2015- PPLL 2016) of research, the best performance was observed in dry season. Regarding rainfall, it can be observed (table 2) that in 2015, the frequency of days with rains was higher compared to 2016 and 2017, which directly influenced on soil humidity and, at the same time, on the performance of the edaphic fauna, as stated above.

On the other hand, Cabrera (2019) recognized that any natural or anthropic intervention generates positive or negative impact on dynamics of the edaphic macrofauna, while Kamau et al. (2017) stated that it is more susceptible to environmental changes than other groups of edaphic fauna due to its larger size.

Other factors that could influence on the performance of macrofauna are of edaphic origin, such as type of soil, content of nutrients and organic matter, pH, texture, structure, and edaphic temperature and humidity (Machado et al. 2015). There are also those related to vegetation and anthropic management, which, in the case of the studied agroecosystems, are determined by vegetation cover, type of pasture and weeds, presence of trees, as well as grazing management. Trampling of animals causes the mechanical destruction of microhabitats. According to Lok (2005), compaction of soils used for livestock by a certain stocking rate can reduce the population of edaphic invertebrates.

It is also necessary to point out versatility in the spatial-temporal distribution of soil macrofauna, which depend on specific conditions of soil microhabitat, due to its own heterogeneity. This leads to organisms not to be homogeneously distributed within the soil in a given space and time, but depending on the availability of food resources, which is greater in carbon-rich areas such as rhizosphere of plants, organic detritus from decomposition of litter and animal depositions. In this sense, soil structure and texture also influence, in addition to other physical properties.

In order to explain the variability of results, ecological characteristics of the edaphic macrofauna are added to all above, which has an aggregated spatial distribution. It means that they will explore those optimal microsites in terms of quantity and quality of food, humidity, temperature, pH, aeration, absence of toxic substances and protection from solar radiation (de la Rosa and Negrete 2012 and Rusanov and Bulgakova 2016).

It is concluded that, in the studied grassland agroecosystems, the edaphic macrofauna had a heterogeneous performance in the evaluated climatic periods. A superior performance of the macrofauna was observed during dry period of the second year, which could be related to the atypical performance of total volume of rainfall and/or days with rain of that year.


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Received: May 07, 2020; Accepted: July 24, 2020


Los autores declaran no presentar conflicto de intereses

Los autores declaran presentar contribución igualitaria en la concepción de la investigación, obtención y procesamiento de los datos y redacción del documento

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