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Article

Land Use Changes Influence Tropical Soil Diversity: An Assessment Using Soil Taxonomy and the World Reference Base for Soil Classifications

by
Selvin Antonio Saravia-Maldonado
1,2,
Beatriz Ramírez-Rosario
3,
María Ángeles Rodríguez-González
3 and
Luis Francisco Fernández-Pozo
3,*
1
Doctoral Program in Sustainable Territorial Development, International Doctoral School, Universidad de Extremadura–UEx, 06006 Badajoz, Spain
2
Faculty of Earth Sciences and Conservation, Universidad Nacional de Agricultura–UNAG, Catacamas 16201, Honduras
3
Environmental Resources Analysis (ARAM) Research Group, Universidad de Extremadura–UEx, 06006 Badajoz, Spain
*
Author to whom correspondence should be addressed.
Agriculture 2025, 15(17), 1893; https://doi.org/10.3390/agriculture15171893
Submission received: 10 July 2025 / Revised: 27 August 2025 / Accepted: 4 September 2025 / Published: 5 September 2025
(This article belongs to the Special Issue Factors Affecting Soil Fertility and Improvement Measures)

Abstract

The transformation of natural ecosystems into agroecosystems due to changes in land use/land cover (LULC) has been shown to significantly affect soil characterization and classification. The impact of LULC on soil taxonomy was assessed in a primary forest located in central–eastern Honduras, which had been deforested approximately forty years prior to the study. Morphological, physical, and physicochemical analyses were performed by describing 10 representative profiles, applying the Soil Taxonomy (ST) and World Reference Base for Soil Resources (WRB) nomenclatures. LULC resulted in physical degradation in agricultural areas, as evidenced by lighter-colored horizons (P02), reduced granular structure (P01, P02, P05), higher bulk densities (≤1.73 Mg m−3), and surface crusting (P02, P05); this phenomenon was also observed in pastures (P06–P09). SOC loss was 62% in croplands, 47–53% in agroforestry systems (P03) and fruit tree plantations (P04), and 25% in pastures. All profiles exhibited pH values between 6.5 and 8.4 and complete base saturation (BS), except for P08 and P09, which had pH values below 5.5, high levels of Al3+, and reduced BS (50–60%). Mollic epipedons and variability in the endopedons were also observed. According to the ST of the System of Soil Classification (SSC), the soils were classified as Mollisols, Entisols, Vertisols, and Alfisols; and as Phaeozems, Fluvisols, Gleysols, Anthrosols, Gypsisols, and Plinthosols by the WRB. We advocate for the inclusion of Anthropogenic Soils as a distinct Order within Soil Taxonomy (ST). The implementation of sustainable agricultural practices, in conjunction with the formulation of regulatory frameworks governing land use based on capacity and suitability, is imperative, particularly within the context of fragile tropical systems.

1. Introduction

Land use and land cover change (LULC), along with agricultural intensification—particularly in tropical regions—are driven by the growing global demand for food, feed, fiber, and biofuels, and rank among the most pressing challenges of this century [1]. These changes play a fundamental role in soil evolution, as they affect the nutrient cycle, hydrological processes, and erosion [2], as well as influencing biogeochemistry and global climate [3]. Consequently, LULC can cause significant changes in soil properties, intensifying its impact on ecosystems.
Numerous international organizations are paying close attention to this issue and coordinating efforts to monitor changes in tropical resources and produce reports on the factors that affect them (such as agriculture in relation to deforestation), with the aim of developing new scientific and political interventions, in line with one of the objectives—specifically Goal #15—of the 2030 Agenda for Sustainable Development [4].
Tropical forests exhibit certain similarities on a global scale—such as high productivity, rapid nutrient renewal, severe soil erosion, and low pH—although they also display considerable diversity in soils and associated plant communities [5]. Factors such as parent material, climate, and geology influence soil properties at both regional and continental scales [6]. At the local level, land use has a direct influence on numerous ecosystem processes, functions, and services [7]. Additionally, management practices can modify local heterogeneity and the distribution of soil properties by altering interactions with the microclimate, microtopography, vegetation, and edaphic biota [8].
Furthermore, the intensive use of agricultural machinery, chemical fertilizers, pesticides, and other inputs to increase agricultural yields can generate various environmental problems and, above all, redirect soil development toward anthropogenic soils [9,10]. Prolonged fertilization can cause significant changes in the chemical, physical, and biological properties of the soil, as well as accelerated acidification, reduced agricultural productivity, and intensified mineral weathering [11]. Similarly, soil carbon reserves—which buffer pH over geological time scales—can disappear completely in just a few decades [12].
The recognition and mapping of soil characteristics are essential for the development of management plans aimed at optimizing soil resources, as well as for implementing practices that promote sustainable agricultural production, the rehabilitation of degraded ecosystems, and the assessment of soil fertility [13]. Human activity can act as a formative factor by modifying erodibility, altering horizon thickness and mixing, organic matter content (SOM), structural stability, salt content, and even leading to the formation of anthropogenic parent material or the complete transformation of the landscape [14]. Therefore, soil classification emerges as an essential tool for understanding the nature, characteristics, dynamics, and functions of soil as part of landscapes and ecosystems [15].
Currently, Soil Taxonomy (ST) and the World Reference Base for Soil Resources (WRB) are the two most widely used soil classification systems globally. The Soil Taxonomy system, developed by the United States Department of Agriculture (USDA), uses a six-level hierarchy comprising order, suborder, great group, subgroup, family, and series [16]. In contrast, the WRB, established by the Food and Agriculture Organization of the United Nations (FAO), employs a two–level classification system, comprising Reference Soil Groups (RSGs) and RSGs combined with their respective qualifiers [17].
In this context, several efforts have been made to compare soil classification under both systems across different conditions, including anthropogenic soils [18], urban and industrial soils [19], calcareous and gypsiferous soils [20], soils with lithological discontinuities and abrupt textural changes [21], and the differences and similarities among soils in arid and semi-arid zones [22]. More recently, studies have focused on rice soils [23] and purple soils [24]. These studies show that the WRB system has made significant efforts to simplify classification criteria. Moreover, WRB places greater emphasis on clay activity, hydromorphism, and the influence of human activity on soil formation. In contrast, the ST system places more emphasis on temperature and moisture regimes, and at the family level prioritizes properties related to soil mineral composition [21].
In Central America—specifically in Honduras—soil cover fragmentation has increased due to land use transitions, driven by deforestation for agricultural and livestock expansion, industrial development, and urbanization. Additionally, soil studies in the region remain limited, particularly those related to soil classification.
Within this framework, we hypothesize that LULC is a highly significant factor influencing the diversity of tropical soils. Anthropogenic activity has a significant impact on soil. Given that the “non-use” of soil contributes to the provision of ecosystem services, any intervention alters these services and, consequently, affects the ecosystem and its inhabitants. In our case, the transformation of primary forest into agricultural and livestock areas can be evaluated through changes in soil classification. Therefore, we have chosen to classify the affected soils two genetic classification systems (ST and WRB), which group soils based on their origin, formation processes, and profile characteristics. To evaluate this premise, we set out to (i) describe the morphological, physical, and physicochemical characteristics of soils cultivated over the last four decades; (ii) determine the effect of agricultural use on the spatial variability of soil properties; and (iii) classify soils according to the two main systems: ST and WRB. To this end, we selected as a reference site a primary forest in central–eastern Honduras, whose deforestation marked the beginning of its conversion to agricultural production.

2. Materials and Methods

2.1. Characteristics of the Study Area

The study site is in a valley adjacent to the Talgua river basin, specifically within the municipality of Catacamas, in the central–eastern region of Honduras (Figure 1).
Elevation ranges from 350 to 370 m above sea level. The reference coordinates are approximately 14°49′30.50″ to 14°49′45.61″ N latitude and 85°49′59.63″ to 85°50′44.24″ W longitude, covering an area of approximately 313 hectares. According to Holdridge’s classification, the predominant life zone is Dry Tropical Forest (bs–T) [25]. This ecosystem is characterized by an annual precipitation of 1271 ± 209 mm and an average temperature of 25 °C, with minimum and maximum values of 18 °C and 35 °C, respectively. The climate exhibits marked seasonality, with well-defined dry and wet periods [26]. The topography varies from flat to steep slopes (Figure 1).

2.2. Influence of the Talgua River Basin on the Study Area

Geologically, the Talgua river basin (Figure 1) is underlain by karst formations composed of evaporites such as halite, anhydrite, gypsum, limestone, and, in smaller proportions, quartzite. Additionally, siliciclastic sedimentary rock deposits (Qsed) in the valley area (the study site) also influence the genesis and evolution of local soils. [27], which favor the formation of well-developed, very deep soils (>120 cm), predominantly with loam, sandy loam, and silty loam textures [28].
On the other hand, the water network of the Talgua river basin gives rise to the Talgua river (Figure 1), and its flow—which supplies water for agricultural, livestock, and industrial activities in the study area—plays an important role in soil formation processes by contributing alluvial materials and influencing local soil dynamics.
Prior to field sampling, general information about the site was collected, including climate, lithology, relief, and land use. A field survey was then conducted, and test pits were opened following the genetic–geographical method, based on the delineation of cartographic soil units according to their formation factors and processes, including anthropogenic influence [29].

2.3. Description and Soil Profile Sampling

Soil sampling and fieldwork were carried out in the first half of 2023, followed by laboratory analysis.
Ten test pits were excavated in different areas delineated according to the established cartographic units (Figure 1), each measuring 2 × 2 × 1.5 m (length × width × depth). The soil profiles and horizons were described in situ using the Field Book for Describing and Sampling Soils [30], the Guide to Soil Description [28], and the Munsell® soil color charts (Munsell Color Company, Grand Rapids, MI, USA). Bulk density (Bd) was determined using a core sampler. After sampling, the soil was dried in an oven at 105 °C for 24 h until constant weight was achieved [31].
To assess spatial variability, additional samples were collected through auger observations and complementary test pits. Given that the study areas were primarily productive—mainly agricultural and reference plots ranging from 1 to 50 hectares—a detailed mapping scale was used (1:1000 a 1:10,000).

2.4. Soil Sample Preparation and Laboratory Analysis

Samples from each horizon were taken to the laboratory, air-dried, sieved to 2 mm, and ground for subsequent analysis.
Particle size distribution was determined using the Bouyoucos method, after the removal of organic matter with H2O2 and carbonates with HCl [32].
Soil pH was measured potentiometrically using a 1:1 soil-to-water ratio (weight/volume). Electrical conductivity (EC) was determined in saturated soil paste, and available phosphorus (Av–P) by the Olsen method [33]. Cation Exchange Capacity (CEC) and exchangeable bases were determined using a 1 M NH4OAc solution buffered at pH 7. Potassium (K+) and sodium (Na+) were quantified by flame photometry, and calcium (Ca2+) and magnesium (Mg2+) by atomic absorption spectrometry (AAS) [33].
Soil organic carbon (SOC) was determined according to the Walkley–Black procedure and total nitrogen (TN) obtained at a rate of 5% of organic matter [34]. Aluminum (Al3+) and interchangeable acidity (Al3+ + H+) were determined by extraction with a 1M KCl solution [35].
Derived parameters were also calculated, including the effective cation exchange capacity (eCEC), obtained by adding exchangeable aluminum (Al3+) to the sum of exchangeable bases. Base saturation percentage (BS) was calculated as (ΣB/CEC) × 100.
Based on the results obtained, the soils were classified according to the Soil Taxonomy (ST) [16] and the World Reference Base for Soil Resources (WRB) classification systems [17].

3. Results and Discussion

3.1. Site Characterization and Description of Soil Profiles

The study area shows marked diversity in terms of land use: agricultural areas (P01, P05, P06), agroforestry systems (P02, P03, and P04), grasslands (P06, P07, P08, and P09), and a primary forest (P10), which serves as a reference (Figure 1). The distribution and description of each profile by land use are detailed in Table 1.
To exploit the richness of both Soil Taxonomy (ST) [16] and the World Reference Base for Soil Resources (WRB) classification [17], each of the two schemes has been applied, as shown in Figure S1 (Supplementary Material).
The studied profiles are in a valley with gentle slopes, composed of very deep (>120 cm), well-drained soils, except for P04, which presented a water table at 90 cm. Table 2 presents the morphological descriptions of the studied profiles.
Profiles P01, P02, P05, P06, P07, P08, P09, and P10 developed from the weathering of siliciclastic sedimentary rocks [27], whereas P03 and P04 originated from unconsolidated alluvial materials (boulders, pebbles, gravel, sand, silt, and clay) transported by the Talgua river (Figure 1). The profiles presented A(p) horizons (due to agricultural and livestock activity), B(t, g, l, k, y) horizons (due to clay illuviation –t–, redox processes –g, l–, or the presence of carbonates and secondary gypsum –k, y–), and C horizons resulting from weathered or soft bedrock. They exhibited predominantly diffuse boundaries with smooth shapes, except for profiles P02, P06, and P08, which showed gradual boundaries with undulating or irregular shapes, as shown in Figure S1 (Supplementary Material).
In general, the described morphological characteristics reflect soil formation processes notably influenced by land use and land cover (LULC), particularly in some profiles. These processes include anthrosolization, haploidization, edaphoturbation, humification, melanization, redoximorphic processes, gleyization, ferralitization, laterization, lessivage (illimerization or argilluviation), vertisolization, neoformation, podzolization, eluviation/illuviation, carbonation/decarbonation, basification/debasification, gypsification, littering, sorption/desorption, erosion, densification, and compaction. These interpretations are supported by the comparison between profiles P01 to P09 and the reference profile P10, representing the original forest before deforestation.
The differences in horizon boundaries between profiles may indicate variations in pedogenic processes and, to some extent, anthropogenic effects. In agricultural areas (P01, P02, and P05), a clear influence was observed in the A horizon, attributable to intensive tillage and fertilization (soil disturbance), likely promoting haploidization processes such as horizon mixing and thickness alteration. Additionally, humification and melanization were evident in the first subsurface horizon of P01.
In terms of color, surface horizons exhibited darker tones with lower values and chroma, indicative of higher soil organic matter (SOM) content—particularly in P10. In contrast, subsurface horizons displayed greater chromatic variability, likely reflecting reduced SOM, differences in parent material, drainage conditions, and land use dynamics.
In agreement with Sharma et al. [36], chroma values >2 suggest deep water tables, while values >3 are associated with low SOM content. Gleying processes were noted in profiles P02, P04, and P05. The above mentioned also state that reddish and brown tones indicate well-drained, aerated soils with sesquioxide accumulation—evidence of ferralitization, as seen in P09. Meanwhile, red, yellow, and brown tones in P01, P03, P06, P07, P08, and P10 suggest intermittent waterlogging. The considered LULC types appear not to significantly alter that condition.
Other color variations, such as those in P02, P04, P05, P06, P08, and P09, may be attributed to redox processes, as shown in Table S1; Figure S1 (Supplementary Material), derived from wetting and drying cycles that affect clays and Fe/Mn oxides [37]. Field observations also noted accumulations of Fe and Mn oxides in P01, P04, P05, P06, P07, P09, and P10, further evidencing redox dynamics influenced by local geomorphology.
In the study area, horizon lightening mainly reflects SOM loss, as well as the eluviation of fine particles and nutrients. Color variation may also indicate significant alterations in the physical, chemical, and biological properties of the soil, potentially impacting fertility and productivity.
Surface horizons showed predominantly granular and angular/subangular blocky structures. Biological activity and biostructures were evident in P10 and also observed in agroforestry, fruit tree, and pasture systems (P03, P04, and P06–P07), likely due to the decomposition and incorporation of SOM, as well as biomass and root exudates. Subsurface horizons showed greater structural variability, with the presence of slickensides and clayskins, suggesting morphological transitions associated with reduced SOM, increased clay content, and lower root density—as described by Yitbarek et al. [38]—as well as cementing agents such as Fe/Al oxides, hydroxides, and calcium carbonates, as shown in Table 2 and Figure S1 (Supplementary Material).
Soil consistency ranged from very friable in P03 and P04 to extremely hard in the subsurface horizons of P05 and P08. P10 exhibited intermediate consistency, consistent with Dinssa and Elias [39], who related such characteristics to decreased SOM and increased clay content.
Porosity followed a vertical gradient, with fine to medium pores, tubular and irregular in shape, decreasing with depth. Root distribution correlated with surface porosity, Table S1 (Supplementary Material), showing greater variability in P03, P04, and P10. This suggests a combined influence of biological activity and LULC on pore architecture, indicating that these systems maintain conditions similar to P10 in this regard.
However, in agricultural areas P01 and P02—and more notably in P05—evidence of structural degradation and surface crust formation was observed, alongside increased bulk density in the first subsurface horizon. Similar patterns were observed in pastures (P06, P07, P08, and P09), suggesting the formation of a plow pan. These findings indicate that forest conversion to agriculture or pasture significantly alters soil physical properties, leading to decreased porosity, compaction, and restricted root growth and biological activity. Such alterations contribute to the progressive degradation of soil quality and productivity.
These observations highlight the need for soil management strategies that aim to preserve or improve soil quality—particularly through SOM incorporation, fallow periods, and green cover—to prevent further soil degradation.

3.2. Physical Properties of the Horizons

Table 3 shows particle size, texture class, rock fragments, bulk density, and silt/clay ratio, as well as the SOC/clay and SOC/SOCExp ratios (see Table S1) used as degradation indices for each horizon and profile.
In all cases, the sand fraction predominates, resulting in medium-texture classes ranging from loam to loamy clay. Slight increases in clay content (exceeding 40%) occur in subsurface horizons compared to surface horizons—consistent with Mulugeta and Sheleme [40], who note that clay increases with depth due to eluviation/illuviation processes or in situ pedogenesis.
Higher sand content in surface horizons likely stems from erosion or lateral migration via lessivage (argilluviation), and in specific cases from maximum eluviation associated with lateralization or podzolization (e.g., P08, P09). These patterns are evident both in the undisturbed site (P10) and in anthropogenically influenced profiles (P01–P02–P05, P03, P08–P09) (Table 3).
Clayskins were observed in the subsurface horizons of P05 (slickensides) and P08 (slickensides and clayskins). In P05, variations in clay content may relate to intensive tillage and flood irrigation, promoting clay translocation—consistent with Yitbarek et al. [41]. Encrustation and deep, widely spaced surface cracks also occurred in P05, and to a lesser extent in P02 and P08, indicative of vertisolization and phyllosilicate transformation. P08 shows dominant laterization or podzolization processes.
Granulometry in P03 and P04 reflects their floodplain origin, yet eluvial/illuvial processes may still occur in P03. The silt/clay ratio indicates advanced weathering in P05, P02, and P08, especially in subsurface horizons, reflecting neoformation or transformation of primary minerals. High coarse fragment content in P08 and P09, including surface stone lines at 18–25 cm (P03) and 10–14 cm (P09), is noted (Table 2 and Table 3, Figure S1).
Bulk density (Bd) is lower in surface horizons (<1.3–1.6 Mg m−3 typical), but higher in agricultural and pasture profiles (P05, P07, P08, P09). In contrast, agroforestry, fruit, shrub, and forest profiles (P03, P04, P10) show lower Bd, suggesting higher SOM, porosity, biological activity, and aggregation [42]. Subsurface horizons of P02, P05–P09 show increased Bd up to 1.73 Mg m−3, likely due to agricultural compaction and plow pan formation. Although tillage can temporarily reduce Bd (as seen in P01), continued conventional management may lead to compaction. Bd increases with depth even in forest profiles like P10, confirming that land conversion increases Bd.
In addition, the primary causes of soil degradation in grasslands due to compaction are trampling from livestock grazing and machinery traffic [43]. The pressure exerted forces soil aggregates closer together, deforming the structure and reducing porosity, which leads to an increase in bulk density and restricts both oxygen (O2) diffusion and hydraulic conductivity [44]. These effects are generally reported at shallow depths. In our study, however, they were evident at 20–50 cm depth (P06–P09), associated with changes in porosity and the presence of fine and very fine roots (see Table S1). Such alterations may explain the genesis of Ap horizons in these systems. Consequently, these effects can disturb horizon thickness and the dynamics of pedogenetic processes by influencing humification, erosion, eluviation/illuviation of organo-mineral particles, and redox reactions.
SOC/clay ratios [45] in surface horizons (0.49–0.09) range from very good to moderate protection, especially in P10 and pasture sites. Agricultural P05 shows moderate protection, indicating advanced degradation; subsurface horizons similarly reveal degradation. However, first subsurface horizons in P01, P04, and P08 maintain favorable ratios, matching their SOC levels—although P08’s C layer shows low weathering (Table S1).
Fine clay and silt promote SOC stabilization and aggregation. SOC/SOCExp ratios (<0.65) across all horizons indicate degradation, with exponential SOC decline with depth as expected (Table S1).

3.3. Physicochemical Properties of the Profiles

Table 4 presents physicochemical data; in situ pH and carbonate values can be found in Table S1. Soil pH generally increases with depth (neutral to moderately alkaline) [30]. Interestingly, P09 is acidic (<5.5), as are some horizons in P08—a variability attributed to anthropogenic activity, vegetation, and geology. Long-term use of bicarbonate-rich Talgua river water (pH 8.0–8.4) [46] has promoted carbonation.
Acidity in P08 and P09 also reflects karst dissolution and Fe/Al oxide concentration due to decarbonation and ferralitization [47]. Debasification in surface horizons (especially pastures) and basification at depth are evident in P08. SOM decomposition—catalyzed by Fe/Mn and Al oxides—may contribute to H+ release and soil acidification.
SOC is the highest in surface P10, followed by pastures (P06, P08, P09), with P10 retaining an organic layer (0–3 cm) indicative of littering accumulation. Pastures accumulate SOM via roots and excreta; agricultural plots gain SOC through incorporated residues and fertilization [48]. SOC generally decreases with depth, though P03 shows subsurface increases (illuviation). Profiles P01–P02–P04–P05–P07 show evidence of SOM degradation and leaching, with melanization in P01 and P06 subsurfaces.
SOC dynamics suggest that conservation strategies must address vulnerability in subsoil horizons, as deforestation has led to up to 62% SOC loss in surface layers (except in pastures).
Available phosphorus (Av–P) is the highest in surface horizons, decreasing with depth. Agricultural and pasture soils (P01, P05, P07) show elevated Av–P; P08 and P09 are the lowest—possibly due to low SOM, acidity, Fe/Al oxide sorption, or calcareous parent material causing phosphate precipitation [49]. These behaviors mirror those observed in unaltered soils like P10.
High Ca2+ predominates among exchange bases, exceeding 25 cmolc kg−1 in subsurface P05, P08, and P10. Mg2+ is highest in P05 and P09, lowest in P08; K+ is generally low; Na+ appears in some horizons (not sodic). Elevated Ca2+ derives from parent material, fertilizers, and irrigation; higher subsurface Ca2+ in P08/P09 results from gypsification (anhydrite/gypsum) verified in field (Table S1). Debasification and basification cycles are evident.
Forest P10 shows greatest surface Mg2+; agricultural zones have low Mg2+ and K+ despite fertilization, suggesting leaching. Na+ in agroforestry (P03) likely originates from alluvium; in agricultural zones from fertilizers/irrigation; in P08/P09, halite accumulation is implicated.
Exchangeable Al3+ and acidity are high in P08/P09 due to low pH, demonstrating anthropogenic influences on acidity. EC is generally low—except moderate salinity in irrigated/fertilized areas (P01–P05) and moderate conditions in P08/P09, posing potential risk to sensitive crops.
CEC varies; subsurface P08 records highest CEC. CEC decreases with depth in P01–P02–P04–P06–P07 but increases in P03–P05–P08–P09–P10. High CEC aligns with colloidal content; P03/P04’s sandy texture contributes to lower nutrient retention.
Most profiles reached full base saturation at depth, due to carbonate lithology. Agricultural practices (P01, P02, P05) maintained chemical fertility; only P08/P09 show BS < 70% in surface horizons due to acidity and Al3+.
In tropical systems, soil physicochemical dynamics reflect intrinsic factors (weathering, mineralization, erosion, deposition, etc.) and extrinsic land use factors (mechanization, fertilization, grazing). These interactions govern horizon differentiation and soil functionality.

3.4. Soil Classification

Anthrosolization, resulting from territorial anthropization, is not merely a disruptive or additive factor—it significantly influences soil-forming processes, generating distinctive pedogenic patterns, particularly in fragile tropical environments. Human activities can alter the soil inventory, with both the intensity and nature of intervention determining the extent of the impact. This section addresses anthropogenic influences on pedogenesis, providing evidence of how human intervention affects soil composition, structure, and functionality. Therefore, it is essential to adopt integrated approaches that consider the multifunctionality and natural capacity of soils to ensure their sustainable use and long–term conservation.
Table 5 presents soil classifications based on Soil Taxonomy (ST, 2022) [16] and the World Reference Base for Soil Resources (WRB, 2022) [17]. Table S2 (Supplementary Material) provides additional information on epipedons, endopedons, diagnostic horizons, and materials, according to both systems, for all studied profiles.
In the reference area, the forest site (P10) exhibits characteristics representative of natural edaphogenetic soil development and is classified as a Mollisols under ST and a Phaeozems under WRB. More than 40 years after deforestation and fragmentation of the primary forest, and the subsequent development of intense anthropogenic activity, several edaphogenetic processes have been modified, enhanced, or altered—primarily those involving the addition, transformation, loss, or accumulation of soil materials.
In agricultural profiles (P01, P02, and P05), diagnostic horizons have been extensively modified or destroyed, with current pedogenesis strongly influenced by human intervention. Land use and cover changes, tillage practices, irrigation, and nutrient inputs (e.g., fertilization and organic amendments) have significantly altered the original properties of these soils. According to ST, P01 and P02 remain Mollisols, whereas P05 has undergone vertisolization and is now classified as a Vertisol, due to the neoformation of expansive clays evidenced by seasonal cracking. Under WRB, P01 and P05 are classified as Anthrosols, while P02 retains its original classification, though vertic properties and altered horizons are already evident. If current management practices persist, further taxonomic changes are likely in the medium to long term. Notably, P05 meets all WRB criteria for classification as a Vertisol. However, its current characteristics are not inherited from the original soil-forming environment but are the result of anthropogenic processes such as those previously described.
In P01 and P02, eluviation/illuviation of colloids in horizon B has led to the development of E horizons in P01. Processes such as melanization have masked these features, darkening the color and enhancing aggregation. In P05, the formation of shallow calcareous horizons has been observed, attributed to fertilization and prolonged flood irrigation with bicarbonate-rich water from the Talgua river, contributing to carbonation and gleyization.
Profiles P03 and P04 are influenced by sediment deposition and particle transport. These are classified as Entisols under ST, and as Fluvisols and Gleysols under WRB, respectively. The Talgua river supplies basic organo-mineral particles that modify soil pH. Eluviation/illuviation and buried horizons are evident in P03, whereas P04 is characterized by gleying associated with water saturation. Road construction has caused topographic fragmentation in the area, reflected in textural differences: P03 (higher elevation) has sandy soils, stone lines, and buried A horizons, while P04 (lower elevation) has silty textures and a shallow water table. These differences influenced taxonomic classifications at lower hierarchical levels under ST (from the suborder level) and at WRB reference group levels.
Profiles P06 and P07 are classified as Mollisols (ST) and Phaeozems (WRB). Despite their use as pastures, both retain their original classification. Properly managed grassland areas tend to preserve characteristics inherited from the parent material. The main limitations in these sites relate to physical fertility, particularly compaction in the upper subsurface horizon.
Profiles P08 and P09, used as hayfields and grazing lands, show significant anthropogenic alteration. P08 is classified as an Alfisol (ST) and as a Gypsisol (WRB), reflecting processes of debasification/basification, nutrient uptake, and acidification. P09, also classified as an Alfisol under ST, is categorized as a Plinthosol under WRB, due to laterization, ferralitization, and debasification. Like P06 and P07, both P08 and P09 show evidence of compaction in the first subsurface horizon.
Several studies highlight the significant impact of anthropogenic activities on soil evolution and taxonomic classification within the ST and WRB systems. Dazzi and Monteleone [18], evaluating a 22–year chronosequence in Italy, demonstrated that human intervention can markedly alter soil development and classification. More recently, Lee et al. [23], studying rice paddy soils with varying degrees of drainage in South Korea, proposed adapted criteria based on characteristics such as redox status and the presence of mottling to better reflect local conditions. Simultaneously, Meng et al. [24] and Hao et al. [50] in China emphasized the necessity of incorporating categories linked to human activity, suggesting the inclusion of orders such as Anthrosols and suborders of anthropogenic soils. Considering the above assessments, it is essential to recognize that human intervention leads to transformations in soil due to socioeconomic pressures. Rapid urban growth increases the demand for food and infrastructure, intensifying competition for agricultural and livestock land. Consequently, fertile soils are being lost due to the expansion of agricultural, livestock, industrial, and urban activities, as well as degradation or occupation of soils in edaphically unfavorable environments.
In this context, soils play a vital role in providing food, water, biodiversity, and in supporting key ecosystem services (ESs), such as provisioning, regulation, cultural, and supporting services [51,52]. Soils are widely acknowledged as essential providers of supporting services due to their inherent properties and ongoing pedogenic processes. They also contribute to provisioning services through biomass and raw material production; to regulating services through nutrient cycling, pollutant remediation and storage, flood mitigation, carbon sequestration, and pest control; and to cultural services through recreation, aesthetics, and preservation of cultural heritage [53].
This dynamic leads to the progressive consumption and modification of soil resources. The recovery of these soils will likely require intensive and large-scale interventions. Looking ahead, soil anthropization from a restoration perspective will be indispensable. A comprehensive approach should combine physical, chemical, and biological strategies tailored to local soil conditions. These should include (i) the incorporation of organic amendments to improve fertility and structure, (ii) the establishment of cover crops to prevent erosion, (iii) decompaction via mechanical or vegetative methods, and (iv) adequate irrigation and drainage to maintain soil health.
It is also necessary to implement land use regulations based on land capability and suitability. Less productive soils should be prioritized for recovery, while areas of ecological or cultural value should be reserved for conservation. These actions are essential to restore soil functionality and ensure the provision of ecosystem services.

4. Conclusions

After more than four decades of deforestation and the implementation of agricultural and livestock production systems, there have been significant changes in soil properties, affecting edaphogenic processes.
There have been reductions in SOC: 62% in agricultural areas, 53% in agroforestry systems, 47% in fruit tree systems, and 25% in pastures.
Despite this, chemical fertility has been preserved or even enhanced (increased pH and nutrient levels). However, physical properties have deteriorated, as evidenced by plow pans and surface crusts—indicating signs of physical soil degradation in these agroecosystems.
Anthropogenic activities have profoundly impacted soil development, accelerating and redirecting pedogenic processes far beyond natural pathways. These impacts are clearly reflected in taxonomic reclassifications across all hierarchical levels in both ST and WRB systems. In this context, with the original primary forest soil classified as Mollisol/Phaeozem (ST/WRB), anthropogenic activity results in the classification of soils as follows: (1) Mollisols/Phaeozems; (2) Entisols/Fluvisols and Gleysols; (3) Vertisols/Anthrosols that meet the criteria for Phaeozems and Vertisols; and (4) Alfisols/Gypsisols and Plinthosols. In this regard, we advocate for the inclusion of anthropogenic soils at the order level in soil taxonomy.
Given the vulnerability of tropical ecosystems, it is essential to promote sustainable land management beyond traditional conservation strategies. These efforts should prioritize improving soil quality as a starting point for maintaining the security of ecosystem services in tropical agroecosystems.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/agriculture15171893/s1: Table S1: Complementary properties corresponding to the representative profiles studied. Table S2: Horizons (epipedons, endopedons), characteristics and diagnostic properties according to ST/WRB in the soils studied. Figure S1: Images of the 10 representative soils classified according to the Soil Taxonomy, 2022 and WRB, 2022 systems.

Author Contributions

Conceptualization, Formal analysis, Funding acquisition, Resources, Visualization, S.A.S.-M., M.Á.R.-G. and L.F.F.-P.; Project administration, L.F.F.-P. and M.Á.R.-G.; Supervision, L.F.F.-P., M.Á.R.-G. and B.R.-R.; Data curation, Investigation, Methodology, Validation, Writing—original draft, Writing—review and editing, Writing—review and editing, S.A.S.-M., M.Á.R.-G., B.R.-R. and L.F.F.-P. All authors have read and agreed to the published version of the manuscript.

Funding

This study has been co-financed 85% by the European Union, European Regional Development Fund, and the Regional Government of Extremadura, Managing Authority, Ministry of Finance (Exp GR24153).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The authors confirm that the data is contained within the article or Supplementary Material. The original contributions presented in this study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author.

Acknowledgments

The authors express their gratitude to the Universidad de Extremadura—UEx (Spain), and the Universidad Nacional de Agricultura—UNAG (Honduras).

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
LULC Land Use/Land Cover
STSoil Taxonomy
WRBWorld Reference Base for Soil Resources
RSGsReference Soil Groups
SDGsSustainable Development Goals
cv.Cultivate
AUAnimal Unit

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Figure 1. Illustration of the Talgua river basin, showing the location of the study site, the diversity of land use/land cover, and slope characteristics.
Figure 1. Illustration of the Talgua river basin, showing the location of the study site, the diversity of land use/land cover, and slope characteristics.
Agriculture 15 01893 g001
Table 1. Characteristics of representative profiles, together with heterogeneity in LULC and a primary forest.
Table 1. Characteristics of representative profiles, together with heterogeneity in LULC and a primary forest.
ProfileCoordinatesElevation SlopeGeoforms
1st; 2nd Level
Slope PositionErosion/
Deposition
Drainage ClassLand Use/Land Cover
P0114°28′35.89″ N
85°50′53.10″ W
367 m5%Lands at level; plainUpper partNo erosionWell-drainedAgriculture
After the primary forest was cleared, Zea mays and Oryza sativa were established between 1982 and 1984, and gravity irrigation and flooding were implemented starting in 1985. From 2007 to the present, the system has been modernized with mechanization and fertigation for horticultural production in rotation with Z. mays and Phaseolus vulgaris.
P0214°50′3.76″ N
85°51′8.82″ W
375 m2%Lands at level; plainMiddle partNo erosionWell-drainedAgropastoral
After the primary forest was cleared, Z. mays was cultivated between 1982 and 1984. From 1993 to the present, the area has been managed as an integrated crop and livestock system (cattle, sheep, and goats), with practices that include soil preparation, fertilization, and weed control.
P0314°49′53.95″ N
85°50′53.65″ W
369 m3%Lands at level; plainMiddle partWater depositionWell-drainedAgroforestry
After the primary forest was cleared, it was used for horticultural production between 1984 and 1988. Subsequently, it was implemented as an agroforestry system, which includes Cordia alliodora, Tabebuia ochracea, Swietenia macrophylla, Cedrela odorata, Acacia mangium, and Salix alba, with native grass cover.
P0414°49′39.30″ N
85°50′52.85″ W
363 m7%Lands at level; plainMiddle partWater depositionPoorly drainedTree crops (fruit trees)
After the deforestation of the primary forest, from 1983 to the present day, it has been managed as a fruit production system: Mangifera indica, Psidium guajava, Citrus x sinensis, Persea americana, Anacardium occidentale, Averrhoa carambola, Passiflora edulis, Carica papaya, Cocos nucifera, and Z. mays, with native grass cover.
P0514°49′28.21″ N
85°50′47.23″ W
355 m6%Lands at level; plainUpper partLaminar erosion, lightPoorly drainedAgriculture under flooding
After the deforestation of the primary forest, Z. mays and O. sativa were established between 1982 and 1985. From 1986 to 2002, gravity irrigation and flooding were used. From 2003 to the present, grains and cereals are produced: O. sativa under flooding and Sorghum bicolor, Z. mays, and P. vulgaris on ridges under flooding.
P0614°49′22.91″ N
85°50′36.52″ W
360 m6%Lands at level; plainMiddle partNo erosionWell-drainedPasture for forage
After the primary forest was cleared, it was used as natural pasture between 1984 and 1996.. In 1996, it was converted into a managed grazing system established with hybrid cultivars of Brachiaria (Mulato II and CIAT BR02/1794) and Panicum maximum cv. Mombasa. In addition, between 6 and 7 harvests per year are carried out using agricultural machinery, rest periods of 45 to 50 days are implemented, and occasional application of NPK fertilizers
P0714°49′33.95″ N
85°50′30.90″ W
356 m5%Lands at level; plainMiddle partLaminar erosion, lightWell-drainedGrazing pasture
After the primary forest was cleared, it was used as natural pasture between 1984 and 1988. In 1992, improved pastures were installed and have been maintained to date: Brachiaria brizantha cv. (Marandú, MG-4, Xaraes MG-5, and decumbens). In addition, the area has been managed as a rotational grazing system with a stocking rate of approximately 1.5–2 AU ha−1 year−1, with only weed control practices implemented.
P0814°49′18.45″ N
85°49′56.43″ W
360 m2%Lands at level; plainMiddle partNo erosionWell-drainedPasture for forage
After the primary forest was cleared, it was used as natural pasture between 1987 and 1988. In 1989, pastures for cutting were established and have been maintained to this day: Brachiaria brizantha cv. (MG-4). In addition, between 6 and 7 harvests per year are carried out using agricultural machinery, rest periods of 45 to 50 days are implemented, and no fertilization practices are applied.
P0914°49′22.61″ N
85°50′2.90″ W
373 m8%Lands at level; plainMiddle partLaminar erosion, lightWell-drainedGrazing pasture
After the primary forest was cleared, it was used as natural pasture between 1984 and 1986. In 1988, it was established as improved pasture and has been maintained to this day: Brachiaria brizantha cv. (decumbens). In addition, the area has been managed as a rotational grazing system with a stocking rate of approximately 2–2.5 AU ha−1 year−1, with only weed control practices implemented.
P1014°49′30.14″ N
85°50′16.51″ W
372 m5%Lands at level; plainMiddle partNo erosionWell-drainedDry Tropical Forest
Primary forest without human disturbance, preserving its natural state and evolution, also used as a reference area in this study.
Table 2. Morphological characteristics of the representative profiles in the study area.
Table 2. Morphological characteristics of the representative profiles in the study area.
ProfileHorizon
(ST–WRB)
Horizon
Depth (cm)
Horizon
Boundary a
Soil Color Structure b
Grade; Type; Size
Consistency c
DryMoistDryMoistWet
P01Ap0–35D, S10YR 5/210YR 3/2MO; AS, GR; ME, FISHAFRSSS, SPP
AE35–50D, S10YR 4/210YR 2/2MO; AS; CO, MEHAFISSS, SPP
Bt150–75D, S10YR 5/310YR 4/3MO; AB, GR; CO, MESOFRSST, SPL
Bt275–100D, S10YR 5/310YR 4/2MO; AB, GR; CO, ME,SHAFRSST, SPL
Bt3100–155D, S10YR 6/310YR 5/3MO; AB; CO, MESHAFRSST, SPL
P02Ap0–50, 0–30D, W10YR 3/110YR 2/1MO; AS; CO, ME, FIVHAFISST, SPL
Eg50–70, 30–75D, W10YR 4/110YR 3/1MO; AB; CO, MEEHAEFISSS, SPP
Btg–Btl70–135, 75–135D, W10YR 5/110YR 4/1MO; AB; CO, MEEHAEFISSS, SPP
P03Ap0–18D, S10YR 6/210YR 5/2WE; AS, GR; ME, FI, VFSOVFRNST, NPL
2E125–70D, SWhitish sands and siltsMALOLONST, NPL
2E270–100D, SWhitish sands and siltsMALOLONST, NPL
3Ab1100–127D, SReddish sandsMALOLONST, NPL
3Ab2127–145D, S10YR 7/310YR 6/3WE; AS; ME, FI, VFSOVFRNST, NPL
P04Ap0–17D, S10YR 6/210YR 5/2MO; GR; ME, FISOVFRNST, NPL
2Cg1–2Cg17–30D, S10YR 6/210YR 5/1WE; SG; ME, FISHAFRNST, NPL
2Cg2–2Cl130–47D, S5Y 6/25Y 5/2MASOVFRNST, NPL
2Cg3–2Cl247–90+D, S5Y 7/15Y 7/2MASOVFRNST, NPL
P05Ap0–28D, S10YR 3/210YR 2/2ST; AS; CO, ME, FIEHAEFISSS, SPP
Btg28–60D, S5Y 7/15Y 5/1ST; AS; VC, COEHAEFIVST, VPL
Bssg–Bil60–95D, S5Y 5/25Y 4/3ST; AS, WEG; EC, VCEHAEFIVST, VPL
Bkssg–Bkil95–155D, S5Y 5/15Y 4/1ST; AS, WEG; EC, VCEHAEFIVST, VPL
P06Ap0–28D, S10YR 3/210YR 2/2ST; GR, AS; ME, FIHAFISST, SPL
Bt128–55, 28–65D, W10YR 5/210YR 4/2MO; AS; CO, MEHAFISST, SPL
Bt255–85, 65–85D, W10YR 6/310YR 5/3MO; AS; CO, MEHAFISST, SPL
Bt385–107D, S10YR 6/410YR 5/4MO; AS; CO, MEHAFISST, SPL
BCk107–150D, S10YR 6/410YR 5/4MO; AS; CO, MESHAFRSST, SPL
P07Ap0–23D, S10YR 5/210YR 4/2MO; GR, AS; ME, FIHAFISST, SPL
Bt123–50D, S10YR 5/310YR 4/3MO; AS; CO, MEHAVFISST, SPL
Bt250–75D, S10YR 6/310YR 5/3MO; AS; CO, MEHAVFISST, SPL
Bt375–116D, S10YR 6/410YR 5/4MO; AS; CO, MEHAVFISST, SPL
BCk116–140D, S10YR 7/410YR 6/4MO; AS; CO, MEHAVFISST, SPL
P08Ap0–13, 0–18G, S10YR 5/210YR 4/2ST; GR; CO, MESOVFRSST, SPL
2Cr–2C13–30, 18–57D, I10YR 3/210YR 2/2SG. WE; GR; ME, FILOLNST, NPL
3BEg30–70, 57–70D, I5Y 4/15Y 3/1MO; AB; CO, MESHAFRSSS, SPP
3Byn170–105D, S2.5Y 6/42.5Y 5/4ST; AS, WE; EC, VCEHAEFIVST, VPL
3Byn2105–150+D, S2.5Y 6/42.5Y 5/4ST; AS, WE; EC, VCEHAEFIVST, VPL
P09Ap0–10G, S10YR 5/210YR 4/2ST; GR, AS; ME, FISHAFRSST, SPL
BEg14–70D, S2.5Y 6/42.5Y 5/4MO; AS; CO, MEEHAEFIVST, VPL
Cr/Bsv–C/Bsv70–130D, S2.5Y 7/42.5Y 6/4MO; AS; CO, MEHAFISST, SPL
P10A0–22D, S7.5YR 4/27.5YR 3/2ST; GR, AS; ME, FISHAVFRSST, SPL
E22–54D, S7.5YR 5/47.5YR 4/3MO; AS; CO, MEHAFRSST, SPL
Bt154–97D, S10YR 5/310YR 4/3MO; AS; CO, ME, HAFRSST, SPL
Bt297–117D, S10YR 5/310YR 4/3MO; AS; CO, MEHAFRSST, SPL
Btk117–147+D, S10YR 6/310YR 5/3MO; AS; CO, ME, HAFISSS, SPP
a: distinctness (G: gradual, D: diffuse); topography (S: smooth, W: wavy, I: irregular). b: grade (WE: weak, MO: moderate, ST: strong); type (AS: angular and subangular blocky, AB: angular blocky, GR: granular, WE: wedge, SG: single grain, MA: massive); size (EC: extremely coarse, VC: very coarse, CO: coarse, ME: medium, FI: fine, VF: very fine). c: dry (LO: loose, SO: soft, SHA: slightly hard, HA: hard, VHA: very hard, EHA: extremely hard); moist (LO: loose, VFR: very friable, FR: friable, FI: firm, VFI: very firm, EFI: extremely firm); wet–adhesiveness (NST: non-adherent, SST: slightly adherent, SSS: slightly adherent to adherent, VST: very adherent), wet plasticity (NPL: non-plastic, SPL: slightly plastic, SPP: slightly plastic to plastic, VPL: very plastic).
Table 3. Physical characteristics and field reaction of representative profiles in the study area.
Table 3. Physical characteristics and field reaction of representative profiles in the study area.
ProfileHorizon
(ST–WRB)
Depth
(cm)
Sand
(%)
Silt
(%)
Clay
(%)
Silt/
Clay
Rf
(%)
Texture aBd
(Mg m−3)
Ap0–3538.444.017.62.5-L1.24
AE35–5079.416.04.63.5-SL1.38
P01Bt150–7526.047.826.21.8-L1.41
Bt275–10032.443.024.61.8-L1.68
Bt3100–15525.848.026.21.8-L1.71
Ap0–50, 0–3046.028.225.81.1-L1.37
P02Eg50–70, 30–7569.619.610.81.81.5SL1.57
Btg–Btl70–135, 75–13534.433.032.61.03.7CL1.73
Ap0–1820.061.618.43.4-SIL1.07
2E125–7067.428.04.66.1-SL1.10
P032E270–10051.440.68.05.1-SL1.00
3Ab1100–12752.835.012.22.9-SL1.09
3Ab2127–14537.847.215.03.2-L1.15
Ap0–1752.033.814.22.4-SL1.24
2Cg1–2Cg17–3035.250.414.43.5-SIL1.32
P042Cg2–2Cl130–4732.450.017.62.8-SIL1.32
2Cg3–2Cl247–90+33.650.216.23.1-SIL0.97
Ap0–2848.434.217.42.02.0L1.44
P05Btg28–6018.043.438.61.12.0SICL1.62
Bssg–Bil60–9524.437.638.01.03.0CL1.65
Bkssg–Bkil95–15530.434.435.21.02.5CL1.71
Ap0–2862.430.86.84.5-SL1.19
Bt128–55, 28–6534.043.222.81.9-L1.50
P06Bt255–85, 65–8518.853.627.61.9-SICL1.41
Bt385–10737.243.629.81.5-L1.69
BCk107–15034.450.615.03.418.4SIL1.57
Ap0–2355.034.210.83.2-SL1.48
Bt123–5045.634.020.41.7-L1.59
P07Bt250–7536.438.025.61.5-L1.60
Bt375–11624.046.229.81.6-CL1.52
BCk116–14030.243.626.21.715.4L1.60
Ap0–13, 0–1840.037.822.21.719.2L1.41
2Cr–2C13–30, 18–5771.620.08.42.481.0SL1.31
P083BEg30–70, 57–7030.464.05.611.461.5SIL1.79
3Byn170–10525.231.643.20.73.0C1.58
3Byn2105–150+26.835.038.20.92.5CL1.70
Ap0–1066.427.46.24.410.8SL1.43
P09BEg14–7039.655.45.011.154.3SIL1.73
Cr/Bsv–C/Bsv70–13037.058.74.313.758.4SIL1.53
A0–2252.830.616.61.8-L1.27
E22–5470.020.29.82.1-SL1.43
P10Bt154–9738.435.626.01.4-L1.50
Bt297–11740.836.023.21.6-L1.60
Btk117–147+40.835.024.21.524.9L1.74
Rf: rock fragments, -: no rock fragments (>2 mm), a: L: loam, SL: sandy loam, SIL: silt loam, CL: clay loam, SICL: silty clay loam, C: clay and Bd: bulk density.
Table 4. Physicochemical characteristics of the representative profiles in the study area.
Table 4. Physicochemical characteristics of the representative profiles in the study area.
ProfileHorizon
(ST–WRB)
Depth
(cm)
pH
(H2O)
SOC
(%)
Av–P
(mg kg−1)
Interchangeable Bases (cmolc kg−1)Al3+ CEC
(cmolc kg−1)
BS
(%)
Ca2+Mg2+K+Na+
P01Ap0–357.202.123315.091.240.37ndnd13.4Sat
AE35–507.491.771115.061.000.18ndnd12.8Sat
Bt150–757.750.6259.170.770.13ndnd6.2Sat
Bt275–1007.560.1287.970.860.12ndnd6.6Sat
Bt3100–1557.630.2597.820.740.120.15nd5.6Sat
P02Ap0–50, 0–306.282.53719.262.260.44ndnd15.0Sat
Eg50–70, 30–756.910.62112.942.110.26ndnd16.295
Btg–Btl70–135, 75–1357.150.31211.582.170.18ndnd13.4Sat
P03Ap0–188.122.091427.560.690.170.08nd9.6Sat
2E125–708.260.29912.630.660.07ndnd4.2Sat
2E270–1008.230.451115.680.270.130.16nd5.4Sat
3Ab1100–1278.300.521117.060.280.09ndnd6.2Sat
3Ab2127–1458.260.911323.310.300.11ndnd10.0Sat
P04Ap0–178.071.871229.322.320.17ndnd9.8Sat
2Cg1–2Cg17–308.191.62927.291.690.13ndnd8.0Sat
2Cg2–2Cl130–478.220.88521.490.420.07ndnd6.2Sat
2Cg3–2Cl247–90+8.260.85626.640.120.08ndnd4.0Sat
P05Ap0–287.141.501821.761.580.370.07nd12.6Sat
Btg28–607.590.57215.531.670.260.32nd15.2Sat
Bssg–Bil60–957.680.30117.133.360.350.14nd17.6Sat
Bkssg–Bkil95–1558.230.19131.213.720.35ndnd16.6Sat
P06Ap0–286.662.991318.211.540.16ndnd11.8Sat
Bt128–55, 28–657.111.52210.011.780.16ndnd10.0Sat
Bt255–85, 65–857.230.42210.111.630.04ndnd7.6Sat
Bt385–1077.430.2329.061.550.06ndnd6.6Sat
BCk107–1508.280.16223.370.440.03ndnd4.0Sat
P07Ap0–236.631.621816.090.650.16ndnd14.0Sat
Bt123–507.200.741313.121.530.22ndnd11.4Sat
Bt250–758.120.462612.792.180.34ndnd11.0Sat
Bt375–1168.140.311917.120.710.21ndnd12.2Sat
BCk116–1408.380.211026.631.080.19ndnd7.4Sat
P08Ap0–13, 0–185.053.0566.090.820.13nd1.5010.666
2Cr–2C13–30, 18–575.121.9845.201.060.07nd1.1012.054
3BEg30–70, 57–705.240.62123.522.400.112.310.5020.4Sat
3Byn170–1056.360.04131.693.650.146.80nd21.6Sat
3Byn2105–150+6.830.10128.882.800.137.09nd19.6Sat
P09Ap0–105.203.0164.451.640.12nd0.1011.256
BEg14–705.040.45137.263.180.082.300.3012.6Sat
Cr/Bsv–C/Bsv70–1305.180.21225.336.950.132.340.5018.0Sat
P10A0–226.813.98817.243.820.19ndnd8.0Sat
E22–546.900.75310.782.340.15ndnd13.2Sat
Bt154–977.080.35210.984.110.13ndnd14.2Sat
Bt297–1177.190.35414.632.780.17ndnd15.2Sat
Btk117–147+8.270.23230.551.660.13ndnd15.4Sat
SOC: soil organic carbon, Av–P: available phosphorus, nd: not detected, CEC: cation exchange capacity, BS: base saturation and Sat: saturated.
Table 5. Classification of the soils studied according to the Soil Taxonomy, 2022 and WRB, 2022.
Table 5. Classification of the soils studied according to the Soil Taxonomy, 2022 and WRB, 2022.
Profile Classification System
Soil Taxonomy (2022)World Reference Base for Soil Resources (2022)
P01Typic ArgiustollsPachic Irragric Anthrosols (Pantoloamic, Abruptic, Differentic)
P02Vertic HaplustollsProtovertic Phaeozems (Anoloamic, Endogleyic, Albic, Differentic)
P03Typic UstipsammentsAlbic Pantofluvic Fluvisols (Loaminovic, Calcaric, Litholinic, Panpaic, Someromollic)
P04Typic EpiaquentsCalcaric Pantofluvic Gleysols (Pantoloamic, Drainic, Reductigleyic, Someromollic)
P05Typic CalciustertsCalcic Hydragric Anthrosols (Endoclayic, Loamic, Abruptic, Anthromollic, Gleyic, Vertic)
P06Typic HaplustollsHaplic Phaeozems (Pantoloamic, Cambic, Mollic)
P07Typic HaplustollsHaplic Phaeozems (Pantoloamic, Cambic, Mollic)
P08Vertic HaplustalfsProtovertic Skeletic Gypsisols (Endoclayin, Loamic, Abruptic, Cutanic, Someromollic)
P09Typic PlinthustalfsSkeletic Plinthosols (Pantoloamic, Litholinic, Plinthic, Someromollic)
P10Typic CalciustollsCalcaric Phaeozems (Pantoloamic, Albic, Cambic, Mollic)
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Saravia-Maldonado, S.A.; Ramírez-Rosario, B.; Rodríguez-González, M.Á.; Fernández-Pozo, L.F. Land Use Changes Influence Tropical Soil Diversity: An Assessment Using Soil Taxonomy and the World Reference Base for Soil Classifications. Agriculture 2025, 15, 1893. https://doi.org/10.3390/agriculture15171893

AMA Style

Saravia-Maldonado SA, Ramírez-Rosario B, Rodríguez-González MÁ, Fernández-Pozo LF. Land Use Changes Influence Tropical Soil Diversity: An Assessment Using Soil Taxonomy and the World Reference Base for Soil Classifications. Agriculture. 2025; 15(17):1893. https://doi.org/10.3390/agriculture15171893

Chicago/Turabian Style

Saravia-Maldonado, Selvin Antonio, Beatriz Ramírez-Rosario, María Ángeles Rodríguez-González, and Luis Francisco Fernández-Pozo. 2025. "Land Use Changes Influence Tropical Soil Diversity: An Assessment Using Soil Taxonomy and the World Reference Base for Soil Classifications" Agriculture 15, no. 17: 1893. https://doi.org/10.3390/agriculture15171893

APA Style

Saravia-Maldonado, S. A., Ramírez-Rosario, B., Rodríguez-González, M. Á., & Fernández-Pozo, L. F. (2025). Land Use Changes Influence Tropical Soil Diversity: An Assessment Using Soil Taxonomy and the World Reference Base for Soil Classifications. Agriculture, 15(17), 1893. https://doi.org/10.3390/agriculture15171893

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