Next Article in Journal
Managing Wildfire Risk in Mosaic Landscapes: A Case Study of the Upper Gata River Catchment in Sierra de Gata, Spain
Next Article in Special Issue
Effects of Forest Harvesting Operations on the Recovery of Earthworms and Nematodes in the Hyrcanain Old-Growth Forest: Assessment, Mitigation, and Best Management Practice
Previous Article in Journal
Assessing Susceptibility to Soil Liquefaction Using the Standard Penetration Test (SPT)—A Case Study from the City of Portoviejo, Coastal Ecuador
Previous Article in Special Issue
Carbon Storage in Biomass and Soil after Mountain Landscape Restoration: Pinus nigra and Picea abies Plantations in the Hyrcanian Region
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Land
Volume 11
Issue 4
10.3390/land11040464
land-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Effect of Maize Conservation Crops Associated with Two Vegetal Covers on the Edaphic Macrofauna in a Well-Drained Savanna of Venezuela

by
Jimmy A. Morales-Márquez
1,*,
Raimundo Jiménez-Ballesta
2,
Rosa M. Hernández-Hernández
3,
Gloria K. Sánchez
4,
Zenaida Lozano
5 and
Ignacio Castro
3
1
Ecological World for Life, 28003 Madrid, Spain
2
Department of Geology and Geochemistry, Autonoma University of Madrid, 28049 Madrid, Spain
3
IDECYT, Universidad Simón Rodríguez, Caracas 1050, Venezuela
4
Centro de Estudios Ambientales, Universidad Bolivariana de Venezuela, Caracas 1041, Venezuela
5
Instituto de Edafología, Universidad Central de Venezuela, Caracas 1040, Venezuela
*
Author to whom correspondence should be addressed.
Land 2022, 11(4), 464; https://doi.org/10.3390/land11040464
Submission received: 26 February 2022 / Revised: 18 March 2022 / Accepted: 21 March 2022 / Published: 24 March 2022
(This article belongs to the Special Issue Influence on Soil Quality of Agriculture and Forest Management: Assessment, Mitigation and Best Management Practices)
Browse Figures
Review Reports Versions Notes

Abstract

:
Conventional agricultural in the Venezuelan Llanos has generated gradual soil degradation. Therefore, conservationist agriculture has been proposed. According to several works, this type of management favors soil macrofauna. To test this hypothesis, the response of soil macrofauna to the establishment of conservationist maize crops, associated with Brachiaria dictyoneura (Bd) and Centrosema macrocarpum (Cm), was evaluated. The samples of soil and soil macrofauna were taken per vegetation cover at different climatic season over 2 years and 10 months. For this period and under the conditions studied, the results partially refute the hypothesis; on the one hand, they showed that the soil macrofauna of a natural savanna (NS) is the most diverse and equitable (N1 = 4.5 ± 2.8), followed by the cultivation of maize associated with Cm (N1 = 3.2 ± 1.9) and the least diverse with Bd (N1 = 2.6 ± 2.1). Additionally, some taxonomic groups apparently did not tolerate soil intervention, while Termitidae was favored. On the other hand, the temporal variation of the soil macrofauna did not differ between vegetation covers (F: 1.18; p = 0.37). This variation could be due to the decrease in TP (r = −0.55) and increased BD (r = 0.56).

1. Introduction

In the first decade of the 21st century, Venezuela experienced a demographic increase that raised food demand and pressure on its ecosystems. The savanna of the Venezuelan central llanos recorded, for maize and rice crops, an increase of more than 68% (from 620,869 to 1,043,291 ha) of cultivated hectares [1]. However, the soils of these savannas are well drained and acidic, with high exchangeable aluminum saturation and low organic matter content and nutrients (especially nitrogen and phosphorus) [2], which make them unfavorable for crops [3,4]. Therefore, these agricultural activities have been sustained with an intensive use of fertilizers, pesticides and mechanization under a conventional tillage system [5,6]. These activities, combined with climatic factors (marked drought and strong and erratic rains) and annual pasture fires, have contributed to gradual soil degradation [5,7,8].
This environmental degradation, generated by socio-economic growth, poses one of the most important challenges of today’s society: to meet its nutritional needs while preserving the production capacities of agroecosystems for future generations. For this reason, it is necessary to favor the implement conservation practices, oriented mainly toward minimum tillage and adequate management of crop residues in the soil [7]. This not only maintains the soil’s abiotic properties (organic matter, cation exchange capacity, phosphorus, nitrogen, and others) and their biological characteristics (microbial biomass and fauna) before cultivation, but it can improve them or even recover them from a degradation by a conventional crop [2,9,10].
However, to achieve sustainability, it is necessary to know all the dimensions that converge in conservation agriculture. One of them is soil biota, especially edaphic macrofauna (invertebrates larger than 2 mm [11]). This is due to their role in the functioning of ecosystems, specifically in pedogenesis, soil structure, soil nutrient cycle and its fertility [12,13,14,15]. Knowing this, it is to be assumed that edaphic macrofauna constitute an important component of soil and play a significant role in soil sustainable productivity. At the same time, the close relationship between soil macrofauna and the physical–chemical and biological properties of the soil makes them sensitive to spatio-temporal variations of these edaphic properties [16,17], particularly to porosity, bulk density [18] and nutrient and/or organic matter content [19,20]. This relationship has led to an increasing interest in knowing the biology and ecology of the soil macrofauna and its function [21,22]. This information has been used in several areas, for example in environmental impact studies, as biological indicators [23,24,25], restoration of degraded soils [19,26,27] and biological pest controllers [27,28].
Studies and proposals about conservation agriculture have given special importance to edaphic macrofauna. This is because a minimal disturbance in the soil can affect it and, reciprocally, soil macrofauna can affect soil properties [10,18,29]. Thus, better soil conditions would imply greater availability of food, ecological niches and stability over time [16,30,31]. Consequently, there would be greater diversity and greater biological activity in the soil [32,33], thus affecting its physical, chemical and biological properties and thus its fertility [29,34,35,36].
However, despite the interest in knowledge of edaphic macrofauna [37], several of their biological and ecological aspects are not yet clearly understood [38,39]. This situation limits the generation of sustainable agroecological strategies, which take advantage of the benefits of these organisms and minimize the risks they may present to disturbances in their habitats, for example, certain potentially pest taxonomic groups [40,41]. Therefore, keeping in view the close relationship between the soil macrofauna and the edaphic properties, the aim of this work was to know the response of soil macrofauna to the establishment of maize conservation crops (Zea mays, Linnaeus) associated with Brachiaria dictyoneura (Figari and De Not.) and Centrosema macrocarpum (Benth) in a well-drained savanna of the Venezuelan llanos. It was hypothesized that this agroecological management would favor the community of edaphic macrofauna, manifesting in its ecological attributes: density, richness and diversity of families. To test this hypothesis, the following specific objectives were established: to determine the effects of agroecological management on the taxonomic structure and ecological attributes of the macrofauna of the soil and evaluating possible differences between the communities present in natural savanna soils and cultivated plots by depth and in the temporal gradient; on the other hand, to evaluate the influence of the physical–chemical properties of the soil in these differences.

2. Materials and Methods

2.1. Study Site Description

The experiment was conducted in the experimental station La Iguana, geographically located at 8.3916° and 8.475° N and 65.4675° and 65.3805° W in the southeast savannas of Guárico state, Venezuela, between 80–120 m above sea level [42]. The area was selected due to its importance at points of agricultural production and where the area’s inhabitants depend on the production of maize. The climate is marked by a well-differentiated dry period from November to May and a rainy period between June and October. It has an average annual precipitation of 1369 mm and monthly average temperatures range between 26 °C and 30 °C (isohyperthermy) [43]. The station, which occupies approximately 3000 hectares, has smooth undulation with 0–2% slope and a soil mosaic with a fertility between low and medium levels; it is slightly acidic, which defines the variety of plant units dominated by the grass Trachypogon vestitus (Andersson) [44]. The soil where the research was conducted was classified as Ultisols: Typic Plinthustults [45] with a coarse loam texture and isohyperthermic. A previous study in this area showed that the sand content in these soils is higher than 80%, with a strong acidic reaction, low salinity, low content of organic matter and low nutrient-holding capacity, specially of P and Ca (Table 1) [46]. These areas have been normally used as extensive holdings of low grazing productivity [47].

2.2. Design of the Study

Once the site inside the experimental station was selected, an analysis of the space variability of the soil was made in order to define the size of the study plot, its orientation and the number of samples to make [49]. It was concluded that the plot for the natural savanna (NS) had 2 ha (100 m × 200 m) and that both plots with Brachiaria dictyoneura (Bd) and Centrosema macrocarpum (Cm) had 2.6 ha (350 m × 75 m) [46], each separated by 18 m. Within the plots with Bd and Cm, subplots of 350 m × 18 m were taken for the maize crop without fertilization. In order to have three replicates and generate a stratified random sampling, the plots were in turn subdivided into 3 experimental units of 60 m × 15 m, arranged randomly within the plot, while in the natural savanna was divided equally [48]. Sampling was carried out for climatic seasons over 2 years and 10.5 consecutive months (from 2005 to 2008), synchronizing with climatic periods and with some phases of the maize crop cycle (Table 2). Additionally, for each of the sampling time, samples of mix soil were also taken at different depths in the soil profile, dividing it in depth horizons, with the average wide criteria of the A horizon (0–15 cm) and the E horizon (15–30 cm). From the A horizon, a layer was taken from 0 to 5 cm deep to evaluate the changes in the edaphic properties, product of the litter and root system of the grass. Thereby, the soil depths studied were 0–5, 5–15 and 15–30 cm [4]. A mixed soil sample consisted of 4 soil sampling points per experimental unit. Therefore, per vegetation cover, there were 3 samples of mixed soil (12 sampling points) per each depth.

2.3. Soil Preparation for Crops

The establishment of the coverage introduced was conducted by conventionally preparing the soil with two crossed traverse passes, followed by phosphorus rock (Fosfopoder ®: 33% P2O5) at a rate of 300 kg·ha−1, covering it with a trailing pass. Seeding of Bd seeds was performed at the rate of 4 kg·ha−1 and Cm at 3 kg·ha−1, burying them with a trailing pass. The NS plot was given the proper management of this region, with annual burning (at the beginning of the rainy season) [4,46]. All plots, including Bd and Cm, were grazed with cattle (3 animal units per hectare) twice a year: once at the beginning of the rains and again at the end of the rains [46]. For the cultivation of maize, seeds of the hybrid variety IMECA 3005 were used. The soil of the plots with Bd and Cm was prepared by cutting the coverings flush with the surface of the soil with a rotary and leaving their residues on the ground. Direct seeding was performed with a three-row SEMEATO® machine, at a density of approximately 60,000 plants·ha−1 [48].

2.4. Soil Macrofauna Sampling

Inside each experimental unit, 2 sampling points were selected randomly. According to the Tropical Soil Biology and Fertility Program [50], every sample consisted of a monolith of 25 × 25 × 30 cm divided in the before-mentioned strata (Figure 1) from where the macrofauna were with direct manual sampling techniques [51]. The macrofauna was taken and preserved in ethylic alcohol (70%) vials. This macrofauna was transferred to the Animal Biology Laboratory, Science Faculty—Universidad de Los Andes (Venezuela), where it was separated and classified taxonomically down to the family level. This identification was made using standardized taxonomic keys in the literature (e.g., Triplehorn et al. 2005) [52]. The collected invertebrates belonging to the taxonomic group of winged insects corresponded to organisms in their larvae stages.

2.5. Soil Sampling

Inside each subplot, four mix soil samples were taken in zig-zag in the before-mentioned depths (Figure 2). For the physical analysis (procedures described in [4,53]),non-altered mix soil samples in 5 × 5 cm cylinders were taken.

2.6. Laboratory Analysis

Soil moisture percentage (M) was measured with the gravimetric method. The bulk density (BD) was measured using the method of the cylinder. The pore size was determined with desktops of saturation voltage (TP: total porosity) in a matric potential of −10 kPa (Pmacro: radius of the pores > 15 µm.) The retention’s porosity (Pmicro) was measured as a result of the difference TP—Pmacro [54]. The saturated hydraulic conductivity was measured in a constant charge disc permeameter [55]. For the chemical analysis, according to Lozano et al. (2010) [4], the pH was analyzed, measuring the total acidic-AT and electrical conductivity (EC) in a soil–water reaction of 1:1. The organic matter (OM) was studied with the Heanes method [56], oxidizing the organic carbon of the soil sample with potassium dichromate (K2Cr2O7) in acidic medium (H2SO4) and later analyzed through a spectrophotometer. The available phosphorus (P) in the soil was extracted with the Olsen solution [57] and detected with the colorimetric method.

2.7. Statistical Processes and Calculations

The families’ diversity was analyzed with the N0 (families richness) and N1 from Hill series [58]. To compare the average of the density, richness and diversity values, and the interaction among these factors, the analysis of variance was used. When the result was significant, the differences among the average pairs were determined using the after-test “least significant difference” (LSD) Fischer test [59]. In order to evaluate possible relationships between soil’s physical and chemical variables and edaphic macrofauna, we performed, on the one hand, Pearson’s linear correlations with STATISTIC software, version 6 [60]; and, on the other hand, a multivariate analysis, with the software CANOCO for Windows, version 4.5 [61]. For this, it was decided to use the linear method “redundancy analysis” (RDA), since the maximum “gradient length” was less than 3 [62]. For all RDAs, the density of families was standardized with their error of variance. The Spearman minimum correlation value [63] was used, plotting a circle of significance (rs = 0.38, n = 21 and p < 0.05). In all the studies, only the analysis with a p value less than 0.05 were significant. The assumption of normal distribution of the data was checked with the Shapiro–Wilk test [63]. To adjust the normal distribution of the data, the density and families’ richness data of the soil macrofauna were transformed with the square root of the value (x1/2) and the families’ diversity with the square root of the value plus one sixth (x1/2+ 1/6). In addition, the Pmacro was performed with the square root of the value plus four: (x + 4)1/2; the Ksat with the square root of the value plus one sixteenth: (x + 1/16)1/2; the OM with logarithm of the value plus one (Log10(x + 1)) and the EC with the square root of the logarithm of the value: (log(x))1/2.

3. Results and Discussion

3.1. Effect of Agroecological Management on the Structure of the Edaphic Macroinvertebrate Community

From a global perspective, the abundance and diversity of soil macrofauna found in this study was much lower than reported for humid tropical soils and temperate ecosystems [64,65,66]. This could be explained due to edaphic (poor soils with low moisture retention) and climatic (high temperatures) factors, which could be unfavorable for a large number of soil macrofauna species [18].
The results reveal differences in the taxonomic structure of soil macrofauna communities associated to plant cover, in terms of quantity and composition of orders and families (Table 3). The natural savanna registered 10 orders with 31 families, while the maize crop associated with Bd coverage registered 11 orders with 30 families, and for Cm coverage, 9 orders and 25 families. In Bd, the orders Orthoptera and Psocoptera appeared, which were absent in NS. While Coccinelidae, Dynastidae (Coleoptera), Cecidyomidae (Diptera) and Pieridae (Lepidoptera) were only present in NS.
However, despite these differences between plant cover (NS and agricultural management), the one-way analysis of variance shows that average densities of the main families did not present significant differences between these coverages (p > 0.05). It was the same for the average of the ecological attributes (density, richness and diversity of families) of the entire soil macrofauna community. It is important to note that this analysis considers the average of the whole community and does not consider which families are or are not present in coverage or their relative densities.
In this sense, the community of soil macrofauna in each vegetation cover was analyzed in terms of its taxonomic structure (Figure 3). This allowed us to verify changes in the relative abundance of the edaphic macrofauna orders, regarding the vegetal cover. It is noteworthy that Isoptera goes from being the third most abundant, with 14% in NS being the main in Bd and Cm, with 59% and 42%, respectively. Meanwhile, Coleoptera was the most dominant in NS, followed by Hymenoptera, with 35% and 30%, respectively, becoming second and third in cultivated soils. Furthermore, the order Haplotaxida (in this study, endogeic earthworms) was apparently not as affected by agricultural management compared with the three most dominant orders.

3.2. Effect of Agroecological Management on the Vertical Distribution of Soil Macrofauna

The agricultural management of the savanna also affected the taxonomic structure of soil macrofauna in the vertical gradient. Figure 4 shows that the order of dominance of some taxa is altered with respect to NS and even the absence of some, such as Araneae in the soil layers of 0–5 and 5–15 cm of Bd, and the orders with a density of less than 1.2% in the layer of 5–15 cm of Cm. In this figure it can also be seen that the cultivation of maize associated with Bd had a greater impact, favoring the increase of six and eight times the abundance of Blattodea (Isoptera) in relation to the other orders. While excluding Isoptera, the culture associated with Cm showed a dominance distribution between orders more similar to NS.
The results on the taxonomic structure of soil macrofauna per plant cover suggest that the less favorable conditions for macrofauna were given by the cultivation of maize associated with Bd, while that associated with Cm presented similar traits to NS. The absence of some families of Coleoptera, Diptera and the order Lepidoptera in Bd and Cm could suppose that this group of insects had a high sensitivity to changes in the soil produced by the agroecological activity, while Termitidae was favored by this intervention.
These changes could be associated with variations in some edaphic properties (P and OM). For example, changes in P and OM were found, which presented lower average values (p < 0.05) in NS (p = 2.5 ± 1.7 mg·kg−1, OM = 0.96 ± 0.07) than in Bd (p = 5.28 ±1.34 mg·kg−1, OM = 1.23 ± 0.18%) and even more in Cm (p = 6.15 ± 1.28 mg·kg−1, OM = 1.14 ± 0.18%). This was perhaps due to agricultural management [67,68]: on the one hand, since the P content increased due to the application of phosphate rock in the preparation of the land for crops; on the other hand, to the incorporation of OM to the soil, as a result of the vegetable residues that were left on the soil surface after the harvests. Several studies showed a positive relationship between OM and the soil macrofauna [69,70,71]. In this study, for example, it can be inferred that Termitidae (Blattodea: Isoptera) was widely favored over other invertebrates due to high OM content in cultivated soils. This corresponds to several authors [41,72] who attributed the dominance of Isoptera to the crop residues left on the soil.
Another of the edaphic properties that showed variation between cover vegetal was BD, which presented the highest average value (p <0.05) in NS (1.6 ± 0.07 Mg·m−3) with respect to Bd (1.49 ± 0.06 Mg·m−3) and Cm (1.46 ± 0.05 Mg·m−3). This difference suggests that agroecological management improved this condition, contradicting the reports of several authors [65,73,74,75] who found an increase of compaction of the soil in the plots of cultivation with respect to natural savannas.
However, agroecological management apparently did not have a significant effect on the ecological attributes of the soil macrofauna when their averages were compared between vegetation covers. This result could be due to the high variability of the data (coefficient of variation > 75%) when all sampling times were averaged. Even so, this contradicts previous works: on the one hand, those that report a positive effect of conservation management on soil macrofauna [10,40,76]; on the other hand, those who find a negative effect of conservation management applied in their studies (no tillage) [65,73,74]. On the contrary, when the sampling times were compared significant differences were found between them, which suggests that the climatic conditions exerted a greater effect than the changes produced by the agroecological activity.

3.3. Effect of Agricultural Management on Soil Macrofauna in the Temporal Gradient

As mentioned above, the average density of soil macrofauna was not affected by agricultural management. This was also corroborated by analyzing the effect of the disturbance on this density throughout the sampling times. The two-way analysis of variance, using the “vegetation cover” and “time” categories, indicated that there was no interaction between them (F: 1.18; p = 0.37) (Supplementary Material, Table S1), therefore, the temporal variation of the average soil macrofauna density occurred independently of the vegetation cover. Otherwise, in the analysis of the richness and diversity of families, a significant interaction was found between the categories “time” and “vegetation cover”, so the temporal variation of these attributes was analyzed by discriminating by vegetation cover (Figure 5).
Figure 5 shows the temporal variation of the density (upper part), revealing that in T1 (beginning of the rainy season) the highest values were recorded (p < 0.05) (785.33 ± 643.04 ind·m−2), followed by T3 (dry season, with 371.55 ± 193.16 ind·m−2). The lowest values were recorded in T2 (rainy season), with 32.0 ± 26.2 ind·m−2. In addition, a decrease in density can be observed over time, corroborated through a linear correlation of Pearson (r = −0.43; p < 0.05).
Regarding the temporal variation of richness in each coverage, Figure 3 shows that NS had the highest values; T1 registered the maximum with 14.5 ± 3.05 families, while the lowest was T6 (dry season), with 1.33 ± 1.12 families. In the case of Bd, the temporal variation of richness registered the highest value in T1 (10.52 ± 3.87 families) and the lowest in T2 and T6, both with 0.35 ± 0.33 families. In Cm, unlike NS and Bd, the highest value of richness was recorded in T3, with 8.67 ± 3.05 families, followed by T1 (7.10 ± 2.8 families) and T5 (rainy season), with 3.33 ± 2.8 families. In T2, zero (0) families were recorded, being the sampling time and the vegetation cover where no individual of the soil macrofauna was found.
Concerning the variation of families’ richness and diversity by coverage for each sampling time, Figure 3 shows that, for richness, there were only differences in T2 and T6 times, while diversity of families, in addition to these two times, was also in T1. In T2, NS presented the highest values (p < 0.05) of these attributes (richness: 4.0 ± 1.3 families and diversity: 3.7 ± 1.2 families), while in T6, Cm presented the highest values (richness: 5.0 families and diversity: 4.1 ± 0.6 families). In T1, the diversity of families also presented differences, with NS having the highest value reported (10.6 ± 2.7 families).
The temporary variation of the soil macrofauna could be associated with the decrease (p < 0.05) in TP (r = −0.55), Ksat (r = −0.44) and the increase in Bd (r = 0.56), which was related (p < 0.05) to density of soil macrofauna (TP: r = 0.46; Bd: r = −0.40). This corresponds to the results found by other researchers [12,18,29,34] and is explained by the fact that with lower porosity apparent density increases (r = −0.69; p < 0.05) and hydraulic conductivity decreases (r = 0.65; p < 0.05). These changes in the physical structure of the soil negatively affected the exchange of gases and the infiltration of water with nutrients in the soil, which in turn affected the populations of edaphic invertebrates. It is important to highlight that, although the soil in this study is sandy, without natural compaction problems and with good infiltration capacity and water movement in the soil profile [46], our results suggest that these edaphic properties are sensitive to disturbance. This finding agrees with the observations of other authors [73], so it should be considered when planning agricultural activities on this type of soil.
When comparing the temporal variation of the ecological attributes of the soil macrofauna between the vegetal covers. Our results evidence an important reduction in the ecological attributes of soil macrofauna in the Bd and Cm of T2. This decrease could be associated with the negative impact of the establishment of the maize crop. This could explain the negative relation (p < 0.05) between this property and the ecological attributes of soil macrofauna (density: r = −0.77; family richness: r = −0.75; family diversity: r = −0.76) which contrasts with that reported in other investigation [77]. Likewise, a negative relationship was found between the families’ richness and diversity of soil macrofauna with EC (r = −0.87 and r = −0.88, respectively), suggesting that the macrofauna of this soil is sensitive to its salinity. This result is contrary to that reported in previous studies [78], where a positive relationship was found between this property and the soil macrofauna.

3.4. Relationship of Edaphic Macrofauna with Edaphic Properties

The relationship between the edaphic properties and the density of the soil macrofauna families was evaluated through an RDA (Figure 6). The three main axes of this RDA explained 81% of the total variance. Axis 1 was determined mainly by Carabidae and Staphylinidae and in the opposite direction by Scarabaeidae and Formicidae. Axis 2 was determined by Glossoscolecidae and Formicidae and in the opposite direction by Termitidae. The third axis was determined by Termitidae and Glossoscolecidae and in the opposite direction by Tenthredinidae and Aphodiidae. According to the minimum correlation value, the soil properties that were significantly correlated with the RDA axes were TP, Pmicro and Ksat, EC and P (Supplementary Material, Table S2). Given the proximity between the vectors of these edaphic properties and the vectors of soil macrofauna, it can be infered that TP, Pmicro and Ksat were positively related to Glossoscolecidae, Staphylinidae and Carabidae and negatively related to Tenthredinidae, Tenebrionidae, Miridae and Scarabaeidae (first and second axis of the RDA). Meanwhile, Formicidae correlated positively with Pt and negatively with P, contrary to Termitidae, which correlated positively with P (second and third axes of the RDA).
In Figure 6 it can also be seen that, at least for these three axes, most of the sites tended to be grouped towards the center of the graph, which would indicate that there is a certain homogeneity in the density of the most important families of the Macrofauna. However, the RDA reveals that there was a certain ordering by sampling times, for example: in the dimension formed by axes 2 and 3, sampling time 3 (T3: NS3, Bd3 and Cm3) differed from the rest, being more evident in the negative part of axis 2. These sites were associated with the dominance of Formicidae and Glossoscolecidae and low density of Termitidae. In the same direction, although more towards the center, the T5 sites (NS5, Bd5 and Cm5) were found. These sites from T3 and T5 were associated with elevated EC and TP values. In addition, the grouping of the sites sampled in T7 (Cm7 and Bd7) was found to be associated with a dominance of Termitidae and with high contents of P. In the dimension formed by axes 1 and 2, the NS1 and Bd1 sites were characterized by the predominance of Carabidae and Staphylinidae, associated with relatively high percentages of Pmicro and Ksat. In this same dimension, all the points corresponding to NS, ordered to the negative side of axis 3, were characterized by a relative dominance of Aphodiidae and low contents of P and EC.
Despite the non-interaction between the categories “time” and “vegetation cover”, RDA evidenced a grouping of NS, which suggests a greater environmental homogeneity in these soils over time than in those intervened agroecologically. This phenomenon has also been recorded by other authors [10] who show greater heterogeneity in soils under cultivation as a result of crop rotation, types of cover and fertilizer input.
The correlation between Staphylinidae, Carabidae and Glossoscolecidae with Pmicro, Ksat and TP, and the latter with Formicidae, has also been reported by other authors [34,79,80]. We agree that the activity of these families increases with porosity and, therefore, with Ksat. Likewise, a positive correlation was found between P and CE with Diptera (NI), Hymenoptera (NI) and Termitidae larvae, as reported by several authors [77,78,81,82].
The differences between several of our findings and what has been reported in several works confirm what has been suggested by several authors [10,41,83]. They state that the different results that agricultural management can generate on the biotic and abiotic properties of the soil depend on a multiplicity of factors, such as characteristics of the management used, type of crop, soil, climate, vegetation and history of the use of the land among others. In other words, it is practically impossible to propose a standard management procedure for soil conservation in different ecosystems.

4. Conclusions

Under the conditions of this study and its duration of 2 years and 10 months, it can be concluded that the agricultural management used apparently did not affect the soil macrofauna. However, it favored Termitidae to the detriment of the equity of the community’s taxonomic structure. It is important to highlight the need for longer studies (medium and long term) to evaluate the evolution of the effect of this type of conservation management on soil macrofauna.
Our results suggest that maize cultivation associated with the grass Brachiaria dictyoneura had a greater negative impact on soil macrofauna than maize cultivation associated with the legume Centrasema macrocarpum. Therefore, from the point of view of soil macrofauna, this vegetation cover was the most conservationist.
The fact of having found a temporal variation in the average of the density, richness of families and diversity of families of the soil macrofauna, independently of the vegetation cover, allows us to conclude that the effect of the climatic season was more important than agroecological management. This variation could be due to changes in the soil structure, so for this type of soil, despite being sandy loam, it should be an aspect to consider in the agricultural practices of this ecosystem.
Although there was no significant effect of the plant cover in several of the analyses carried out, a greater environmental homogeneity could be inferred in the soil of the NS. Likewise, the disappearance of Coccinelidae, Dynastidae (Coleoptera), Cecidyomidae (Diptera) and Pieridae (Lepidoptera) and the increase of Termitidae (Blattodea) with the agroecological management was reported, which indicated a high sensitivity of these taxonomic groups of soil macrofauna to this type of edaphic alteration.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/land11040464/s1, Table S1: summary of the effects of factorial ANOVA for the interaction between factors “sampling times” (Times) and “vegetal cover” (COV), using the average density of the soil macrofauna, its families richness and diversity; (https://doi.org/10.5281/zenodo.6299695, accessed on 25 February 2022) Table S2: correlation (r) of the physical-chemical properties of the soil with the axes of RDA, formed through the density of the families of the soil macrofauna of a savanna agroecosystem with maize crop associated with vegetal covers in the La Iguana station; (https://doi.org/10.5281/zenodo.6365727, accessed on 25 February 2022) Values in red indicate significant correlation (p < 0.05; n = 21).

Author Contributions

Conceptualization, J.A.M.-M. and R.M.H.-H.; methodology, J.A.M.-M., Z.L., R.M.H.-H. and R.J.-B.; formal analysis, J.A.M.-M. and G.K.S.; investigation, J.A.M.-M., R.M.H.-H., G.K.S. and I.C.; resources, J.A.M.-M., and G.K.S.; writing—original draft preparation, J.A.M.-M.; writing—review and editing, R.J.-B. and J.A.M.-M.; project administration, R.M.H.-H.; funding acquisition, R.M.H.-H. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Fondo Nacional para la Ciencia Innovación y Tecnología del Ministerio del Poder Popular para la Educación Universitaria, Ciencia y Tecnología of the Bolivarian Republic of Venezuela for the financial support of the project “Manejo Agroecológico de Suelos de Sabanas Bien Drenadas con Unidades de Producción Cereal-Ganado”, grant number G-2002000398”.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

We want to express our gratitude to the “Fondo Nacional para la Ciencia Innovación y Tecnología del Ministerio del Poder Popular para la Educación Universitaria, Ciencia y Tecnología” of the Bolivarian Republic of Venezuela for the financial support of the project “Manejo Agroecológico de Suelos de Sabanas Bien Drenadas con Unidades de Producción Cereal-Ganado”, N° G-2002000398, of which this study is part. Moreover, we thank the technical team of the Biogeochemistral Laboratory of IDECYT- UNERS for their support in the field and in the labs. Finally, we thank Antonio de Ascenção of the Animal Biology Laboratory, Science Faculty—ULA for his help in the identification of samples of macrofauna of the soil.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Gutiérrez, A.; Ordoñez, J. Evolución Reciente y Situación Actual Del Sistema Alimentario Venezolano (SAV); Corporación Parque Tecnológico de Mérida—ULA: Mérida, Venezuela, 2011. [Google Scholar]
  2. Hernández-Hernández, R.M.; López-Hernández, D. El Tipo de Labranza Como Agente Modificador de La Materia Orgánica: Un Modelo Para Suelos de Sabana de Los Llanos Centrales Venezolanos. Interciencia 2002, 27, 529–536. [Google Scholar]
  3. Berroterán, J.L. Modelo de Utilización Cereal-Pasto En Sistemas de Producción de Sabanas Bien Drenadas Con Suelos Ácidos En Venezuela. Intercencia 2000, 25, 203–209. [Google Scholar]
  4. Lozano, Z.; Mogollon, A.; Hernandez, R.M.; Bravo, C.; Ojeda, A.; Torres, A.; Rivero, C.; Toro, M. Cambios En Las Propiedades Químicas De Un Suelo De Sabana Luego De La Introduccion De Pasturas Mejoradas. Bioagro 2010, 22, 135–144. [Google Scholar]
  5. Hernández-Hernández, R.M.; Morros María, E.; Bravo, C.; Lozano, Z.; Herrera, P.; Ojeda, A.; Morales, J.; Birbe, B. La Integración Del Conocimiento Local y Científico En El Manejo Sostenible de Suelos En Agroecosistemas de Sabanas. Interciencia 2011, 36, 104–112. [Google Scholar]
  6. Lopez-Hernández, D. Impact of Agriculture and Livestock Production on Tropical Soils in Latin America. In Global Land Use Change: A Perspective from the Columbian Encounter; Turner, B., Gómez-Sal, A., González Bernáldez, F., di Castri, F., Eds.; Editorial CSIC-CSIC Press: Madrid, Spain, 1995; pp. 405–418. [Google Scholar]
  7. López-Hernández, D.; Hernández-Hernández, R.M.; Brossard, M. Historia Del Uso Reciente de Tierras de Las Sabanas de América Del Sur. Estudios de Casos En Sabanas Del Orinoco. Interciencia 2005, 30, 623–630. [Google Scholar]
  8. de Wit, J.; Oldenbroek, J.K.; van Keulen, H.; Zwart, D. Criteria for Sustainable Livestock Production: A Proposal for Implementation. Agric. Ecosyst. Environ. 1995, 53, 219–229. [Google Scholar] [CrossRef]
  9. Busari, M.A.; Kukal, S.S.; Kaur, A.; Bhatt, R.; Dulazi, A.A. Conservation Tillage Impacts on Soil, Crop and the Environment. Int. Soil Water Conserv. Res. 2015, 3, 119–129. [Google Scholar] [CrossRef] [Green Version]
  10. Bedano, J.C.; Domínguez, A.; Arolfo, R.; Wall, L.G. Effect of Good Agricultural Practices under No-till on Litter and Soil Invertebrates in Areas with Different Soil Types. Soil Tillage Res. 2016, 158, 100–109. [Google Scholar] [CrossRef]
  11. Swift, M.J.; Heal, O.W.; Anderson, J.M. Decomposition in Terrestrial Ecosystems; University of California Press: Oakland, CA, USA, 1979. [Google Scholar]
  12. Lavelle, P.; Decaëns, T.; Aubert, M.; Barot, S.; Blouin, M.; Bureau, F.; Margerie, P.; Mora, P.; Rossi, J.-P. Soil Invertebrates and Ecosystem Services. Eur. J. Soil Biol. 2006, 42, S3–S15. [Google Scholar] [CrossRef]
  13. Chapin, F.S.; Matson, P.A.; Vitousek, P.M. Principles of Terrestrial Ecosystem Ecology, 2nd ed.; Springer: New York, NY, USA, 2011; Volume 21. [Google Scholar]
  14. Nielsen, U.N. Soil Fauna Assemblages; Cambridge University Press: Cambridge, UK, 2019. [Google Scholar] [CrossRef]
  15. Menta, C.; Remelli, S. Soil Health and Arthropods: From Complex System to Worthwhile Investigation. Insects 2020, 11, 54. [Google Scholar] [CrossRef] [Green Version]
  16. Morales, J.; Sarmiento, L. Dynamics of soil macroinvertebrates and Its relationships to vegetation in a secondary succession of the Venezuelan Paramo. Ecotropicos 2002, 15, 99–110. [Google Scholar]
  17. Wu, P.; Liu, S.; Liu, X. Composition and Spatio-Temporal Changes of Soil Macroinvertebrates in the Biodiversity Hotspot of Northern Hengduanshan Mountains, China. Plant Soil 2012, 357, 321–338. [Google Scholar] [CrossRef]
  18. Morales-Márquez, J.A.; Hernández-Hernández, R.M.; Sánchez, G.K.; Lozano, Z.; Castro, I.; Bravo, C.; Ramírez, E.; Jiménez-Ballesta, R. Soil Macroinvertebrates Community and Its Temporal Variation in a Well-Drained Savannah of the Venezuelan Llanos. Eur. J. Soil Biol. 2018, 84, 19–26. [Google Scholar] [CrossRef] [Green Version]
  19. Snyder, B.A.; Hendrix, P.F. Current and Potential Roles of Soil Macroinvertebrates (Earthworms, Millipedes, and Isopods) in Ecological Restoration. Restor. Ecol. 2008, 16, 629–636. [Google Scholar] [CrossRef]
  20. Prescott, C.E.; Frouz, J.; Grayston, S.J.; Quideau, S.A.; Straker, J. Rehabilitating Forest Soils after Disturbance. In Developments in Soil Science. Global Change and Forest Soils; Busse, M., Giardina, C.P., Morris, D.M., Page-Dumroese, D.S., Eds.; Elsevier: Amsterdam, The Netherlands, 2019; Volume 36, pp. 309–343. [Google Scholar] [CrossRef]
  21. Swift, M. Prólogo. In El Arado Natural: Las Comunidades de Macroinvertebrados del Suelo en las Sabanas Neotropicales de Colombia; Jimenez, J., Thomas, R., Eds.; CIAT: Cali, Colombia, 2003; p. vii. [Google Scholar]
  22. Decaëns, T.; Jiménez, J.J.; Gioia, C.; Measey, G.J.; Lavelle, P. The Values of Soil Animals for Conservation Biology. Eur. J. Soil Biol. 2006, 42, S23–S38. [Google Scholar] [CrossRef]
  23. Lavelle, P.; Velasquez, E.; Andrade, M. “Indicating Soil Quality and the GISQ”: Reply to the Comments by Rossi et Al. Soil Biol. Biochem. 2009, 41, 446–447. [Google Scholar] [CrossRef]
  24. Havlicek, E. Soil Biodiversity and Bioindication: From Complex Thinking to Simple Acting. Eur. J. Soil Biol. 2012, 49, 80–84. [Google Scholar] [CrossRef]
  25. Domínguez-Haydar, Y.; Velásquez, E.; Carmona, J.; Lavelle, P.; Chavez, L.F.; Jiménez, J.J. Evaluation of Reclamation Success in an Open-Pit Coal Mine Using Integrated Soil Physical, Chemical and Biological Quality Indicators. Ecol. Indic. 2019, 103, 182–193. [Google Scholar] [CrossRef]
  26. Stanturf, J.A. Landscape Degradation and Restoration. In Soils and Landscape Restoration; Elsevier: Amsterdam, The Netherlands, 2021; pp. 125–159. [Google Scholar] [CrossRef]
  27. Wubs, E.R.J.; Melchers, P.D.; Bezemer, T.M. Potential for Synergy in Soil Inoculation for Nature Restoration by Mixing Inocula from Different Successional Stages. Plant Soil 2018, 433, 147–156. [Google Scholar] [CrossRef] [Green Version]
  28. Eckschmitt, K.; Wolters, V.; Weber, M.; Benckiser, G. Spiders, Carabids and Staphylinids: The Ecological Potential of Predatory Macroarthropods. In Fauna in soil Ecosystems: Recycling Processes, Nutrient Fluxes, and Agricultural Production; Benckiser, G., Ed.; Marcel Derker: New York, NY, USA, 1997; pp. 307–362. [Google Scholar]
  29. Bottinelli, N.; Jouquet, P.; Capowiez, Y.; Podwojewski, P.; Grimaldi, M.; Peng, X. Why Is the Influence of Soil Macrofauna on Soil Structure Only Considered by Soil Ecologists? Soil Tillage Res. 2015, 146, 118–124. [Google Scholar] [CrossRef]
  30. Crespo-Pérez, V.; Kazakou, E.; Roubik, D.W.; Cárdenas, R.E. The Importance of Insects on Land and in Water: A Tropical View. Curr. Opin. Insect Sci. 2020, 40, 31–38. [Google Scholar] [CrossRef] [PubMed]
  31. Sanabria, C.; Lavelle, P.; Fonte, S.J. Ants as Indicators of Soil-Based Ecosystem Services in Agroecosystems of the Colombian Llanos. Appl. Soil Ecol. 2014, 84, 24–30. [Google Scholar] [CrossRef]
  32. Lanfranco, D. Estudios Entomofaunísticos En El Archipiélago Del Cabo de Hornos. An. Inst. Patagon. 1980, 11, 281–291. [Google Scholar]
  33. Jiménez, J. La Biodiversidad del Suelo: La Gran Desconocida. Available online: http://www.aragoninvestiga.org/La-biodiversidad-del-suelo-la-gran-desconocida/ (accessed on 19 February 2016).
  34. Moura, E.G.; Aguiar, A.d.C.F.; Piedade, A.R.; Rousseau, G.X. Contribution of Legume Tree Residues and Macrofauna to the Improvement of Abiotic Soil Properties in the Eastern Amazon. Appl. Soil Ecol. 2015, 86, 91–99. [Google Scholar] [CrossRef]
  35. Anderson, J.M. Spatiotemporal Effects of Invertebrates on Soil Processes. Biol. Fertil. Soils 1988, 6, 216–227. [Google Scholar] [CrossRef]
  36. Coleman, D.C.; Callaham, M.A.; Crossley, D.A. Fundamentals of Soil Ecology, 3rd ed.; Coleman, D.C., Callaham, M.A., Crossley, D., Eds.; Elsevier: Amsterdam, The Netherlands, 2018. [Google Scholar] [CrossRef]
  37. FAO; ITPS; GSBI; SCBD; EC. State of Knowledge of Soil Biodiversity—Status, Challenges and Potentialities, Report 2020; FAO: Rome, Italy, 2020. [Google Scholar] [CrossRef]
  38. Frouz, J. Preface. In Soil Biota and Ecosystem Development in Post Mining Sites; Frouz, J., Ed.; CRC Press: Prague, Czech Republic, 2013; pp. 291–302. [Google Scholar] [CrossRef]
  39. Jiménez, J.J.; Decaëns, T.; Rossi, J.P. Stability of the Spatio-Temporal Distribution and Niche Overlap in Neotropical Earthworm Assemblages. Acta Oecologica 2006, 30, 299–311. [Google Scholar] [CrossRef] [Green Version]
  40. Decaëns, T.; Lavelle, P.; Jiménez, J.J.; Escobar, G.; Rippstein, G.; Schneidmadl, J.; Sanz, J.I.; Hoyos, P.; Thomas, R.J. Impact of Land Management on Soil Macrofauna in the Eastern Savannas of Colombia. In Soil Macroinvertebrate Communities in the Neotropical Savannas of Colombia; Rippstein, G., Escobar, G., Motta, F., Eds.; CIAT: Cali, Colombia, 2001; pp. 111–137. [Google Scholar]
  41. Paul, B.K.; Vanlauwe, B.; Hoogmoed, M.; Hurisso, T.T.; Ndabamenye, T.; Terano, Y.; Six, J.; Ayuke, F.O.; Pulleman, M.M. Exclusion of Soil Macrofauna Did Not Affect Soil Quality but Increased Crop Yields in a Sub-Humid Tropical Maize-Based System. Agric. Ecosyst. Environ. 2015, 208, 75–85. [Google Scholar] [CrossRef]
  42. Riera, J.; Guerrero, I. Caracterización Agroecológica de La Región Oriental de Guárico. In Sub Estación Experimental Valle de La Pascua; FONAIAP: Caracas, Venezuela, 1984; pp. 140–150. [Google Scholar]
  43. Ponce, M.E.; González, V.C.; Brandín, J.; Ponce, M. Análisis de La Vegetación Asociada a Una Toposecuencia En Los Llanos Centro Orientales de Venezuela. Ecotropicos 1994, 7, 11–22. [Google Scholar]
  44. Chacón, P.; Lopez-Hernández, I.D.; Lamotte, M. Le Cycle de l’azote Dans Une Savane à Trachypogon Au Centre Du Venezuela. Rev. D’écologie Biol. Sol 1991, 28, 67–75. [Google Scholar]
  45. U.S. Department of Agriculture. Soil Survey Staff. In Keys to Soil Taxonomy; United States Department of Agriculture, Natural Resources Conservation Service: Washington, DC, USA, 2010. [Google Scholar]
  46. Lozano, Z.; Romero, H.; Bravo, C. Influence of Cover Crops and Grazing on Soil Physical Properties in Savanna Soil. Agrociencia 2010, 44, 135–146. [Google Scholar]
  47. Decaëns, T.; Lavelle, P.; Jiménez, J.J.; Escobar, G.; Rippstein, G.; Schneidmadl, J.; Sanz, J.; Hoyos, P.; Thomas, R. Impacto Del Uso de La Tierra En La Macrofauna Del Suelo de Los Llanos Orientales de Colombia. In El Arado Natural: Las Comunidades de Macroinvertebrados del Suelo en las Sabanas Neotropicales de Colombia; Jiménez, J., Thomas, R., Eds.; CIAT: Cali, Colombia, 2003; pp. 21–45. [Google Scholar]
  48. Hernández, R.M.; Lozano, Z.; Toro, M.; Bravo, C.; Morales, J.; Rivero, C.; Salazar, J.; Ojeda, A.; Ramírez, E.; Cáchica, H.; et al. Manejo Agroecológico de Suelos de Sabanas Bien Drenadas Con Unidades de Producción Cereal-Ganado. Informe Final—Proyecto G-2002000398; IDECYT, Universidad Nacional Experimental Simón Rodriguez: Caracas, Venezuela, 2011. [Google Scholar]
  49. Carpenter, S.R. The Need for Large-Scale and Experiments of Predict the Response to Perturbation Ecosystems. In Success, Limitations, and Frontiers in Ecosystem Science; Pace, M.L., Groffman, P.M., Eds.; Springer: New York, NY, USA, 1998; Volume 1, pp. 287–312. [Google Scholar]
  50. Anderson, J.M.; Ingram, J.S.I. Tropical Soil Biology and Fertility: A Handbook of Method, 2nd ed.; CAB International: Oxford, UK, 1993. [Google Scholar]
  51. ISO 23611-5:2011; Soil Quality—Sampling of Soil Invertebrates. Part 5: Sampling and Extraction of Soil Macro-Invertebrates. International Organization for Standardization: Geneva, Switzerland, 2011; p. 12.
  52. Triplehorn, C.A.; Johnson, N.F.; Borror, D.J. Borror and DeLong’s Introduction to the Study of Insects, 7th ed.; Thompson Brooks/Cole: Belmont, CA, USA, 2005. [Google Scholar]
  53. Vera, S.; Lozano, Z.; Lobo, D.; Bravo, C.; Hernández, R. Propiedades Físicas Del Suelo y Distribución de Raíces de Maíz Bajo Diferentes Tipos de Cobertura y Fertilización En Un Sistema Conservacionista Cereal-Ganado. Rev. Fac. Agron. 2012, 38, 49–63. [Google Scholar]
  54. Blake, G.R.; Hartge, K.H. Bulk Density. In Methods of Soil Analysis: Part 1—Physical and Mineralogical Methods; Klute, A., Ed.; ACSESS-Alliance of Crop, Soil, and Environmental Science Societies: Madison, WI, USA, 1986; pp. 363–375. [Google Scholar] [CrossRef]
  55. Plá, I. Metodología Para La Caracterización Física Con Fines de Diagnóstico de Problemas de Manejo y Conservación de Suelos En Condiciones Tropicales. Rev. Alcance. Fac. Agron. UCV 1983, 32, 91. [Google Scholar]
  56. Heanes, D. Determination of Total Organic-C in Soil by an Improved Chromic Acid Digestion and Spectrophotometric Procedure. Comm. Soil Sci. Plant Anal. 1984, 15, 1191–1213. [Google Scholar] [CrossRef]
  57. Olsen, S.R.; Cole, C.V.; Watanabe, F.S.; Dean, L.A. Estimation of Available Phosphorus in Soils by Extraction with Sodium Bicarbonate; U.S. Department of Agriculture: Washington, DC, USA, 1954; pp. 1–19.
  58. Hill, M.O. Diversity and Evenness: A Unifying Notation and Its Consequences. Ecology 1973, 54, 427–432. [Google Scholar] [CrossRef] [Green Version]
  59. Williams, L.J.; Abdi, H. Fisher’s Least Significant Difference (LSD) Test. Encycl. Res. Des. 2010, 218, 840–853. [Google Scholar]
  60. StatSoft. STATISTICA (Data Analysis Software System), Version 6; Statsoft Europe: Hamburg, Germany, 2001. [Google Scholar]
  61. Ter Braak, C.J.F.; Smilauer, P. CANOCO Reference Manual and CanoDraw for Windows User’s Guide: Software for Canonical Community Ordination (Version 4.5); Microcomputer Power: Ithaca, NY, USA, 2002. [Google Scholar]
  62. Leps, J.; Smilauer, P. Multivariate Analysis of Ecological Data Using CANOCO; Cambridge University Press: Cambridge, UK, 2003. [Google Scholar] [CrossRef]
  63. Verzani, J. Using R for Introductory Statistics, 2nd ed.; Chapman & Hall/CRC The R Series; CRC Press: Boca Ratón, FL, USA, 2014. [Google Scholar]
  64. Lavelle, P.; Bignell, D.; Lepage, M.; Wolters, W.; Roger, P.; Ineson, P.; Heal, O.W.; Dhillion, S. Soil Function in a Changing World: The Role of Invertebrate Ecosystem Engineers. Eur. J. Soil Biol. 1997, 33, 159–193. [Google Scholar]
  65. de Aquino, A.M.; Ferreira da Silva, R.; Mercante, F.M.; Fernandes Correia, M.E.; de Fátima Guimarães, M.; Lavelle, P. Invertebrate Soil Macrofauna under Different Ground Cover Plants in the No-till System in the Cerrado. Eur. J. Soil Biol. 2008, 44, 191–197. [Google Scholar] [CrossRef]
  66. Fierer, N.; Strickland, M.S.; Liptzin, D.; Bradford, M.A.; Cleveland, C.C. Global Patterns in Belowground Communities. Ecol. Lett. 2009, 12, 1238–1249. [Google Scholar] [CrossRef]
  67. Castro, I. Disponibilidad y Conservación Del N y C En Agroecosistemas de Sabanas Bien Drenadas Cultivados Con Maíz. Ph.D. Thesis, Universidad Central de Venezuela, Caracas, Venezuela, 2016. [Google Scholar]
  68. Ramírez, E. Sincronización de Los Componentes Suelo-Planta-Animal En Agroecosistemas de Sabanas Bien Drenadas. Ph.D. Thesis, Universidad Central de Venezuela, Caracas, Venezuela, 2015. [Google Scholar]
  69. Palm, C.; Blanco-Canqui, H.; DeClerck, F.; Gatere, L.; Grace, P. Conservation Agriculture and Ecosystem Services: An Overview. Agric. Ecosyst. Environ. 2014, 187, 87–105. [Google Scholar] [CrossRef] [Green Version]
  70. Shao, Y.; Xie, Y.; Wang, C.; Yue, J.; Yao, Y.; Li, X.; Liu, W.; Zhu, Y.; Guo, T. Effects of Different Soil Conservation Tillage Approaches on Soil Nutrients, Water Use and Wheat-Maize Yield in Rainfed Dry-Land Regions of North China. Eur. J. Agron. 2016, 81, 37–45. [Google Scholar] [CrossRef]
  71. Zhang, X.; Xin, X.; Zhu, A.; Zhang, J.; Yang, W. Effects of Tillage and Residue Managements on Organic C Accumulation and Soil Aggregation in a Sandy Loam Soil of the North China Plain. CATENA 2017, 156, 176–183. [Google Scholar] [CrossRef]
  72. Ayuke, F.O.; Pulleman, M.M.; Vanlauwe, B.; de Goede, R.G.M.; Six, J.; Csuzdi, C.; Brussaard, L. Agricultural Management Affects Earthworm and Termite Diversity across Humid to Semi-Arid Tropical Zones. Agric. Ecosyst. Environ. 2011, 140, 148–154. [Google Scholar] [CrossRef] [Green Version]
  73. Domínguez, A.; Bedano, J.C.; Becker, A.R. Negative Effects of No-till on Soil Macrofauna and Litter Decomposition in Argentina as Compared with Natural Grasslands. Soil Tillage Res. 2010, 110, 51–59. [Google Scholar] [CrossRef]
  74. Domínguez, A.; Bedano, J.C.; Becker, A.R. Cambios En La Comunidad de Lombrices de Tierra (Annelida: Lumbricina) Como Consecuencia Del Uso de La Técnica de Siembra Directa En El Centro-Sur de Córdoba, Argentina. Cienc. Suelo 2009, 27, 11–19. [Google Scholar]
  75. Piccoli, I.; Schjønning, P.; Lamandé, M.; Furlan, L.; Morari, F. Challenges of Conservation Agriculture Practices on Silty Soils. Effects on Soil Pore and Gas Transport Characteristics in North-Eastern Italy. Soil Tillage Res. 2017, 172, 12–21. [Google Scholar] [CrossRef]
  76. Decaëns, T.; Galvis, J.H.; Amézquita, E. Propiedades de Las Estructuras Construidas Por Los Ingenieros Del Ecosistema En La Superficie Del Suelo de Una Sabana Colombiana1 Materiales y Métodos. In El Arado Natural: Las Comunidades de Macroinvertebrados del Suelo en las Sabanas Neotropicales de Colombia; Jiménez, J.J., Thomas, R.J., Eds.; CIAT: Cali, Colombia, 2003; pp. 171–197. [Google Scholar]
  77. Vasconcellos, R.L.F.F.; Segat, J.C.; Bonfim, J.A.; Baretta, D.; Cardoso, E.J.B.N.B.N. Soil Macrofauna as an Indicator of Soil Quality in an Undisturbed Riparian Forest and Recovering Sites of Different Ages. Eur. J. Soil Biol. 2013, 58, 105–112. [Google Scholar] [CrossRef]
  78. Tao, H.-H.; Slade, E.M.; Willis, K.J.; Caliman, J.-P.; Snaddon, J.L. Agriculture, Ecosystems and Environment Effects of Soil Management Practices on Soil Fauna Feeding Activity in an Indonesian Oil Palm Plantation. Agric. Ecosyst. Environ. 2016, 218, 133–140. [Google Scholar] [CrossRef] [Green Version]
  79. Bottinelli, N.; Henry-des-Tureaux, T.; Hallaire, V.; Mathieu, J.; Benard, Y.; Duc Tran, T.; Jouquet, P. Earthworms Accelerate Soil Porosity Turnover under Watering Conditions. Geoderma 2010, 156, 43–47. [Google Scholar] [CrossRef]
  80. Lavelle, P.; Dangerfield, M.; Fragoso, C.; Eschenbrenner, V.; Lopez-Hernandez, D.; Pashanasi, B.; Brussaard, L. The Relationship between Soil Macrofauna and Tropical Soil Fertility. In The Biological Management of Tropical Soil Fertility; Woomer, P.L., Swift, M.J., Eds.; Tropical Soil Biology and Fertility Programme; C. Sayce Publishing: Dublin, OH, USA, 1994; pp. 137–169. [Google Scholar]
  81. Rückamp, D. Role of Termites for the Distribution Patterns of Carbon and Phosphorus Fractions and the Genesis of Tropical Soils, Brazil. Ph.D. Thesis, University of Bonn, Bonn, Germany, 2011. [Google Scholar]
  82. Umeh, V.C.; Ivbijaro, M.F.; Ewete, F.K. Relationship Between Characteristics of Macrotermes Spp. Mound Materials and Their Surrounding Soils. Int. J. Trop. Insect Sci. 1999, 19, 251–255. [Google Scholar] [CrossRef]
  83. Pelosi, C.; Pey, B.; Hedde, M.; Caro, G.; Capowiez, Y.; Guernion, M.; Peigné, J.; Piron, D.; Bertrand, M.; Cluzeau, D. Reducing Tillage in Cultivated Fields Increases Earthworm Functional Diversity. Appl. Soil Ecol. 2014, 83, 79–87. [Google Scholar] [CrossRef]
Land 11 00464 g001 550
Figure 1. Extraction of the soil monolith and representation of the sampling unit.
Figure 1. Extraction of the soil monolith and representation of the sampling unit.
Land 11 00464 g001
Land 11 00464 g002 550
Figure 2. Mix soil sample preparation.
Figure 2. Mix soil sample preparation.
Land 11 00464 g002
Land 11 00464 g003 550
Figure 3. Relative density (%) of the orders of the soil macrofauna for every vegetation cover: natural savanna, maize crop associated with Brachiaria dictyoneura and Centrosema macrocarpum in the La Iguana station, Guárico state, Venezuela. Every color indicates a different taxon. Size of the circle represents the sum of the average density of every vegetation cover. Other: groups with average density less than 4 ind·m−2.
Figure 3. Relative density (%) of the orders of the soil macrofauna for every vegetation cover: natural savanna, maize crop associated with Brachiaria dictyoneura and Centrosema macrocarpum in the La Iguana station, Guárico state, Venezuela. Every color indicates a different taxon. Size of the circle represents the sum of the average density of every vegetation cover. Other: groups with average density less than 4 ind·m−2.
Land 11 00464 g003
Land 11 00464 g004 550
Figure 4. Relative abundance (%) of the soil macrofauna orders by soil depth (0–5, 5–15 and 15–30 cm) and by vegetation cover: natural savanna, maize crop associated with Brachiaria dictyoneura and Centrosema macrocarpum. Each color indicates a different taxon. Other: groups with relative average abundance less than 1.2%.
Figure 4. Relative abundance (%) of the soil macrofauna orders by soil depth (0–5, 5–15 and 15–30 cm) and by vegetation cover: natural savanna, maize crop associated with Brachiaria dictyoneura and Centrosema macrocarpum. Each color indicates a different taxon. Other: groups with relative average abundance less than 1.2%.
Land 11 00464 g004
Land 11 00464 g005 550
Figure 5. Average density of soil macrofauna without discrimination by coverings, regarding sampling times—T— (upper part); richness (middle) and diversity of families (lower part): natural savanna (NS), maize crop associate with Brachiaria dictyoneura (Bd) and Centrosema macrocarpum (Cm). Uppercase letters indicate differences (p < 0.05) between every vegetation cover for a same time (T), lowercase letters indicate differences between times for a same vegetation cover. Climatic seasons are indicated.
Figure 5. Average density of soil macrofauna without discrimination by coverings, regarding sampling times—T— (upper part); richness (middle) and diversity of families (lower part): natural savanna (NS), maize crop associate with Brachiaria dictyoneura (Bd) and Centrosema macrocarpum (Cm). Uppercase letters indicate differences (p < 0.05) between every vegetation cover for a same time (T), lowercase letters indicate differences between times for a same vegetation cover. Climatic seasons are indicated.
Land 11 00464 g005
Land 11 00464 g006 550
Figure 6. Ordering of the sampling sites (vegetation cover: natural savanna (NS)), maize crop associate with Brachiaria dictyoneura (Bd) and Centrosema macrocarpum (Cm) by sampling time (e.g., Bd1, NS3… BdX, CmX or NSX; differentiated by color) according to the average density of the families of the soil macrofauna (italic writing) and their correlation with soil properties (blue vector) through an RDA. Axis 1 and 2: upper part; Axis 2 and Axis 3: lower part. Center circle: minimum correlation value (r = 0.38). Families with a density greater than 2 ind·m−2 were considered. NI: Unidentified. EC: electric conductivity; P: available phosphorus; Pmacro: macroporosity; Pmicro: microporosity; TP: total porosity; BD: bulk density; M: percentage of humidity; Ksat: hydraulic conductivity.
Figure 6. Ordering of the sampling sites (vegetation cover: natural savanna (NS)), maize crop associate with Brachiaria dictyoneura (Bd) and Centrosema macrocarpum (Cm) by sampling time (e.g., Bd1, NS3… BdX, CmX or NSX; differentiated by color) according to the average density of the families of the soil macrofauna (italic writing) and their correlation with soil properties (blue vector) through an RDA. Axis 1 and 2: upper part; Axis 2 and Axis 3: lower part. Center circle: minimum correlation value (r = 0.38). Families with a density greater than 2 ind·m−2 were considered. NI: Unidentified. EC: electric conductivity; P: available phosphorus; Pmacro: macroporosity; Pmicro: microporosity; TP: total porosity; BD: bulk density; M: percentage of humidity; Ksat: hydraulic conductivity.
Land 11 00464 g006
Table
Table 1. Initial physicochemical characteristics of soil studied (n = 108 per deep) at the La Iguana experimental station, Guárico state, Venezuela.
Table 1. Initial physicochemical characteristics of soil studied (n = 108 per deep) at the La Iguana experimental station, Guárico state, Venezuela.
ParameterDepth (cm)
0–55–1515–30
Clay [<2 µm] † (%)2.50 ± 0.38 ‡2.94 ± 0.0910.00 ± 1.20
Silt [2–5 µm] (%)12.51 ± 1.1511.00 ± 0.9812.00 ± 1.02
Very fine sand [50–100 µm] (%)6.99 ± 0.323.17 ± 0.8910.00 ± 1.92
Fine sand [100–250 µm] (%)48.91 ± 5.1529.05 ± 2.1336.00 ± 3.16
Medium sand [250–500 µm] (%)25.29 ± 1.1244.59 ± 3.3222.93 ± 2.16
Coarse sand [500–1000 µm] (%)3.29 ± 0.787.98 ± 1.128.20 ± 0.32
Very coarse sand [1000–2000 µm] (%)0.51 ± 0.111.27 ± 0.080.78 ± 0.10
Textural classLoamy SandLoamy SandSandy Loam
Reaction of the soil (pH in H2O)5.01 ± 0.184.81 ± 0.254.75 ± 0.24
Total acidity (cmol+·kg−1)0.46 ± 0.210.83 ± 0.581.18 ± 0.73
Interchangeable aluminum (cmol+·kg−1)0.16 ± 0.090.34 ± 0.230.50 ± 0.31
Interchangeable hydrogen (cmol+·kg−1)0.30 ± 0.180.49 ± 0.420.67 ± 0.53
Electrical conductivity (µS·cm−1)27.53 ± 1.3223.62 ± 3.2622.77 ± 3.62
CEC (cmol+·kg−1)2.21 ± 0.541.94 ± 0.661.90 ± 0.82
Organic matter (%)1.33 ± 0.301.23 ± 0.261.04 ± 0.27
Total nitrogen (%)0.039 ± 0.0070.032 ± 0070.028 ± 0.007
Inorganic nitrogen (mg·kg−1)21.34 ± 11.1817.23 ± 8.4515.73 ± 9.54
Phosphorus (mg·kg−1)11.30 ± 0.3010.01 ± 3.628.67 ± 3.26
Potassium (mg·kg−1)29.94 ± 14.1019.51 ± 7.3111.53 ± 4.40
Calcium (mg·kg−1)89.64 ± 25.2163.15 ± 27.8738.11 ± 14.76
Magnesium (mg·kg−1)51.35 ± 16.9447.19 ± 12.0739.11 ± 14.66
Sodium (mg·kg−1)2.09 ± 1.332.40 ± 1.653.11 ± 1.86
Iron (mg·kg−1)44.61 ± 22.0753.36 ± 25.0354.38 ± 24.96
Copper (mg·kg−1)0.71 ± 0.440.90 ± 0.601.07 ± 0.57
Manganese (mg·kg−1)7.76 ± 3.603.52 ± 2.642.63 ± 1.73
Zinc (mg·kg−1)1.07 ± 0.570.86 ± 0.370.79 ± 0.39
† Size of the aggregates. ‡ Standard deviation. Adapted from Hernández et al., 2011 [48].
Table
Table 2. Distribution of sampling times for the study of soil macrofauna and soil of a natural savanna and maize crop associated with Brachiaria dictyoneura and Centrosema macrocarpum in La Iguana station, Guárico state, Venezuela.
Table 2. Distribution of sampling times for the study of soil macrofauna and soil of a natural savanna and maize crop associated with Brachiaria dictyoneura and Centrosema macrocarpum in La Iguana station, Guárico state, Venezuela.
DescriptorSampling Times
Days after initiation0761883634616781035
Climate seasonStart of rainy seasonRainy seasonDry seasonStart of rainy seasonRainy seasonDry seasonDry season
Chronological orderT1T2T3T4T5T6T7
Table
Table 3. Density (ind·m−2) of orders and families, average density, richness, diversity of families of the soil macrofauna of the natural savanna (NS) and maize crop associate with Brachiaria dictyoneura (Bd) and Centrosema macrocarpum (Cm) in the La Iguana station, Guárico state, Venezuela.
Table 3. Density (ind·m−2) of orders and families, average density, richness, diversity of families of the soil macrofauna of the natural savanna (NS) and maize crop associate with Brachiaria dictyoneura (Bd) and Centrosema macrocarpum (Cm) in the La Iguana station, Guárico state, Venezuela.
OrderVegetation CoverFamilyVegetation Cover
NSBdCm NSBdCm
Ind·m−2 Ind·m−2
Blattodea (Isoptera)30.5 ± 46.4 †162.3 ± 158.392.6 ± 89.3Termitidae30.5 ± 46.4161.5 ± 159.292.6 ± 89.3
Coleoptera77.5 ± 52.848.4 ± 47.745.1 ± 38.1Carabidae18.5 ± 18.320.2 ± 18.110.7 ± 10.2
Staphylinidae12.2 ± 16.38.6 ± 8.17.4 ± 7.9
Scarabaeidae13.7 ± 17.05.3 ± 8.13.8 ± 5.2
Aphodiidae5.5 ± 8.94.6 ± 4.411.8 ± 9.9
Tenebrionidae5.1 ± 6.92.3 ± 4.13.4 ± 5.2
Rutelidae4.0 ± 6.52.7 ± 4.31.9 ± 3.4
Elateridae3.6 ± 5.51.9 ± 3.31.5 ± 2.8
Chrysomelidae3.4 ± 5.60.2 ± 0.41.7 ± 3.1
Hydroscaphidae2.1 ± 3.81.7 ± 2.90.8 ± 1.5
Lampyridae2.9 ± 4.60.2 ± 0.40
Cerambycidae1.7 ± 3.101.0 ± 1.7
Coccinelidae2.3 ± 4.100
Geotrupidae1.0 ± 1.801.1 ± 2.1
Dynastidae1.5 ± 2.800
Curculionidae00.8 ± 1.50
Hymenoptera66.5 ± 64.125.5 ± 24.945.1 ± 41.9Formicidae57.7 ± 71.323.8 ± 22.528.8 ± 27.3
Haplotaxida Tenthredinidae7.2 ± 11.01.0 ± 1.711.8 ± 10.9
Larva (NI) ‡1.5 ± 2.80.8 ± 1.54.6 ± 4.8
Glossoscolecidae19.8 ± 23.019.2 ± 12.917.5 ± 16.5
Diptera9.9 ± 12.36.9 ± 10.47.8 ± 13.0Muscidae6.9 ± 10.43.0 ± 5.53.2 ± 3.9
Larva (NI)1.5 ± 2.83.0 ± 5.52.3 ± 4.1
Sciaridae0.8 ± 1.50.8 ± 1.52.3 ± 1.4
Cecidyomidae0.8 ± 1.500
Hemiptera5.1 ± 7.84.0 ± 6.54.0 ± 6.9Miridae3.6 ± 5.91.0 ± 1.74.0 ± 5.9
Cercopidae1.1 ± 2.13.2 ± 5.60.8 ± 1.5
Lygaeidae1.5 ± 2.83.0 ± 5.50
Araneae Pentatomidae00.8 ± 1.50
6.5 ± 9.32.3 ± 3.92.5 ± 4.2Paratropididae4.2 ± 6.41.5 ± 2.82.5 ± 4.2
Dipluridae2.3 ± 4.10.8 ± 1.50
Chilopoda1.5 ± 2.80.8 ± 1.52.3 ± 3.9Cryptopidae1.5 ± 2.80.8 ± 1.51.5 ± 2.8
Scolopendridae000.8 ± 1.5
Solifugae Ammotrechidae2.1 ± 3.81.7 ± 1.90
Blattodea Blattelidae00.8 ± 1.51.5 ± 2.8
Lepidoptera Pieridae0.8 ± 1.500
Orthoptera Gryllotalpidae00.8 ± 1.50
Psocoptera Psocidae00.8 ± 1.50
Density 221.3 ± 166.6276.6 ± 266.5205.5 ± 155.4
Families
Richness 6.0 ± 3.94.2 ± 3.64.6 ± 3.0
Diversity 4.5 ± 2.82.6 ± 2.13.2 ± 1.9
† Standard deviation. ‡ Larva Unidentified.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Morales-Márquez, J.A.; Jiménez-Ballesta, R.; Hernández-Hernández, R.M.; Sánchez, G.K.; Lozano, Z.; Castro, I. Effect of Maize Conservation Crops Associated with Two Vegetal Covers on the Edaphic Macrofauna in a Well-Drained Savanna of Venezuela. Land 2022, 11, 464. https://doi.org/10.3390/land11040464

AMA Style

Morales-Márquez JA, Jiménez-Ballesta R, Hernández-Hernández RM, Sánchez GK, Lozano Z, Castro I. Effect of Maize Conservation Crops Associated with Two Vegetal Covers on the Edaphic Macrofauna in a Well-Drained Savanna of Venezuela. Land. 2022; 11(4):464. https://doi.org/10.3390/land11040464

Chicago/Turabian Style

Morales-Márquez, Jimmy A., Raimundo Jiménez-Ballesta, Rosa M. Hernández-Hernández, Gloria K. Sánchez, Zenaida Lozano, and Ignacio Castro. 2022. "Effect of Maize Conservation Crops Associated with Two Vegetal Covers on the Edaphic Macrofauna in a Well-Drained Savanna of Venezuela" Land 11, no. 4: 464. https://doi.org/10.3390/land11040464

APA Style

Morales-Márquez, J. A., Jiménez-Ballesta, R., Hernández-Hernández, R. M., Sánchez, G. K., Lozano, Z., & Castro, I. (2022). Effect of Maize Conservation Crops Associated with Two Vegetal Covers on the Edaphic Macrofauna in a Well-Drained Savanna of Venezuela. Land, 11(4), 464. https://doi.org/10.3390/land11040464

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop