Next Article in Journal
Pine Cones in Plantations as Refuge and Substrate of Lichens and Bryophytes in the Tropical Andes
Previous Article in Journal
Remarkable Stability of Uropodina (Acari: Mesostigmata) Communities in Artificial Microhabitats: A Case Study of Bird Nest Boxes in Bory Tucholskie National Park
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Diversity
Volume 17
Issue 8
10.3390/d17080546
diversity-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Soil Fungal Activity and Microbial Response to Wildfire in a Dry Tropical Forest of Northern Colombia

by
Eliana Martínez Mera
1,
Ana Carolina Torregroza-Espinosa
2,*,
Ana Cristina De la Parra-Guerra
2,
Marielena Durán-Castiblanco
3,
William Zapata-Herazo
3,
Juan Sebastián Rodríguez-Rebolledo
3,
Fernán Zabala-Sierra
3 and
David Alejandro Blanco Alvarez
3
1
Agrobiotechnology Engineering, Universidad Tecnológica de la Costa, Santiago Ixcuintla Nayarit 63300, Mexico
2
Department of Natural and Exact Sciences, Universidad de la Costa, Barranquilla 080002, Colombia
3
Department of Civil and Environmental, Universidad de la Costa, Barranquilla 080002, Colombia
*
Author to whom correspondence should be addressed.
Diversity 2025, 17(8), 546; https://doi.org/10.3390/d17080546 (registering DOI)
Submission received: 3 July 2025 / Revised: 20 July 2025 / Accepted: 24 July 2025 / Published: 1 August 2025
(This article belongs to the Section Microbial Diversity and Culture Collections)
Browse Figures
Versions Notes

Abstract

Wildfires can significantly alter soil physicochemical conditions and microbial communities in forest ecosystems. This study aimed to characterize the culturable soil fungal community and evaluate biological activity in Banco Totumo Bijibana, a protected dry tropical forest in Atlántico, Colombia, affected by a wildfire in 2014. Twenty soil samples were collected for microbiological (10 cm depth) and physicochemical (30 cm) analysis. Basal respiration was measured using Stotzky’s method, nitrogen mineralization via Rawls’ method, and fungal diversity through culture-based identification and colony-forming unit (CFU) counts. Diversity was assessed using Simpson, Shannon–Weaver, and ACE indices. The soils presented low organic matter (0.70%) and nitrogen content (0.035%), with reduced biological activity as indicated by basal respiration (0.12 kg C ha−1 d−1) and mineralized nitrogen (5.61 kg ha−1). Four fungal morphotypes, likely from the genus Aspergillus, were identified. Simpson index indicated moderate dominance, while Shannon–Weaver values reflected low diversity. Correlation analysis showed Aspergillus-3 was positively associated with moisture, whereas Aspergillus-4 correlated negatively with pH and sand content. The species accumulation curve reached an asymptote, suggesting an adequate sampling effort. Although no control site was included, the findings provide a baseline characterization of post-fire soil microbial structure and function in a dry tropical ecosystem.

Graphical Abstract

1. Introduction

Soil biology is one of the primary properties and indicators of soil health [1]. Microorganism diversity and abundance are crucial for maintaining soil quality, productivity, and ecological balance [2,3]. However, various anthropogenic activities negatively affect soil microbial communities, consequently leading to disturbance of the functioning of soil ecosystems and a decrease in soil productivity [4]. One of the most unexplored frontiers associated with understanding the dynamics of soil resources and their subsequent health or quality is that of soil biology [5]. In this regard, there is a need for detailed information on the soil diversity of different regions to predict how different threats may alter the corresponding ecosystem services. Even though soil quality cannot be directly measured to determine its health, its relationship to biological, chemical, and physical parameters can be assessed [6]. From the interaction between these components, factors affecting microbial activity can be determined [7,8].
The search for soil quality proxies and their application has increased in the last decades due to the need to protect this resource [1,9,10,11,12]. Previous studies have assessed soil properties and nitrogen mineralization from organic matter (OM) [13,14]. Some research has reported the impact of forest fires on the soil’s physical, chemical, and biological properties [7,8,15]. The lack of good inventories prevents knowing how edaphic fungi are affected after ecological disturbance. In this regard, there is a lack of reliable information on the number of fungal species present, due to the difficulties of culturing soil fungi in the laboratory. Despite this lack of information, methods such as in vitro culture from serial dilutions provide distribution estimates for the most commonly found fungal genera associated with edaphic organic matter (OM) decay [16]. In this regard, the assessment of microorganism richness and diversity serves as a bioindicator that enables understanding the soil’s response capacity to natural and anthropogenic processes [17]. Fungi are essential components of soil ecosystems, contributing to organic matter decomposition, nutrient cycling, and soil health [1,2,14]. Forest soils generally exhibit greater fungal abundance and diversity due to the accumulation of organic residues and stable microclimatic conditions, whereas agricultural soils tend to show reduced diversity and shifts in fungal composition as a result of intensive land use and fertilization [14,15]. Evaluating fungal diversity is important because it provides insight into the soil’s ecological stability and its ability to recover after disturbances. Previous studies have reported that genera such as Aspergillus, Penicillium, and Fusarium are common in a variety of soil environments, including degraded and fire-affected ecosystems, due to their capacity to colonize organic matter and tolerate stress [16,17].
The Banco Totumo Bijibana Natural Reserve (BTBNR) is situated in the municipality of Repelón, Atlántico Department, Colombia. It is a protected area, declared in 2015, with sustainable use of natural resources. It represents an ecologically important wildlife area with endemic species of the tropical dry forest and a diverse array of fauna and flora, but without reports on edaphic microbiota. Additionally, the natural reserve can connect with the systems of the Los Colorados Fauna and Flora Sanctuary in the department of Bolívar. In the area, approximately 105 people reside in 85 plots, where the primary activity is agriculture and small-scale livestock farming. This model is known as a regional district of integrated management, seeking rational use that allows socio-economic activities through the sustainable use of resources. For transient crops, farmers prepare the soil by burning, an activity carried out before the rains. However, during this time, breezes and drought increase the wildfire risk. It is in the southern portion of the Atlántico department, where soils have been affected by several alterations. Considering the importance of this reserve, it is essential to establish a baseline with both qualitative and quantitative information on the soil microflora. Such a baseline can serve as a tool to develop sustainable strategies for conserving microorganisms and, consequently, maintaining soil fertility in the zone. The aims of the current study are (i) to characterize physical and chemical parameters of soil to determine their correlation to edaphic microbiota; (ii) to estimate soil activity through its respiration rate and mineralized nitrogen; and (iii) to assess the composition and diversity of soil fungal community through ecological indices.

2. Materials and Methods

2.1. Description of the Study Area

BTBNR is located in the municipality of Repelón, Atlántico Department, Colombia (10°21′33.18″ N; 75°00′27.35″ E). The general characteristics of the soils in southern Atlántico are quaternary deposits occupying areas with a flat relief, belonging to the Inceptisol order [18]. The municipality of Repelón is characterized by a mean annual temperature of 28.2 °C. The precipitation is seasonal, with a dry season from January to March (averaging 23.5 mm) and a wet season from July to November (averaging 81.4 mm) [19]. The BTBNR is comprised of young tropical rainforests in a successional process, with a protected area of 119 ha. The reserve provides essential ecosystem services to associated communities, including hydric regulation, soil retention, and carbon capture, which regulate climate, water, and nutrient availability [20]. In 2007, approximately 67.6% of the area was comprised of agricultural land. Due to the activities carried out in 2014, a wildfire within BTBNR affected an area of roughly 30 ha. Currently, 70.1% of the surface area is semi-natural forests and regions [21].

2.2. Soil Sampling

In June 2018, twenty simple soil samples were collected within a 1-ha plot affected by the fire, using a stratified grid approach to ensure spatial representation. The sampling process followed the method described by the Instituto Geográfico Agustín Codazzi (IGAC) [22]. Physicochemical samples were collected at a depth of 30 cm, stored in sealed plastic bags, and kept at room temperature. For microbiological characterization, samples were taken at 10 cm depth and placed in sealed plastic bags at 4 ± 1 °C until analysis.

2.3. Physicochemical Characterization

Several physicochemical parameters were evaluated. Moisture was determined by the gravimetric method, and texture was determined using the Bouyoucos method [22]. Electrical conductivity (EC) was measured with a conductometer (HI 993310). For pH, the Colombian technical standard was followed [23]. Phosphorus (P) content was measured with the Bray II method [24]. Nitrogen (N) was determined by the Kjeldahl method, and organic carbon (OC) was determined via the wet digestion (Walkley–Black) method [22]. Both organic matter (OM) and total N were subsequently derived from the OC data [22,25]. Cation exchange capacity (CEC) was determined via the ammonium acetate saturation method [26].

2.4. Microbial Respiration

The basal respiration rate of soil samples was determined following the method of Stotzky [27]. Calculations were performed according to the method described by Guerrero-Ortiz et al. [28]. Soil respiration values were then classified using the Woods End Research index [29] (see Table 1).

2.5. Mineralized Nitrogen

Mineralized nitrogen (Nm) was estimated from the soil’s apparent density, obtained through texture and mineral mass-density contour mapping [30]. Nm was then calculated with the equation proposed by Castellanos et al. [31], assuming an Nm rate of 1%, where OC constitutes 55% of OM, and the C/N ratio is 10:1 (i.e., each 10 g of OC contains 1 g of N) for a 1 ha layer of soil.

2.6. Biological Diversity Estimates

Ten grams of soil were diluted in sterile peptone water. From this suspension, a 10−1 dilution was prepared, and 1 mL aliquots were taken. Then, 50 μL of each was plated onto potato dextrose agar (PDA) modified with 10% tartaric acid to inhibit bacterial growth. The plates were incubated at 25 ± 1 °C for 5 days. Negative and positive controls were included to verify the absence of contamination.
Macroscopic descriptions (colony shape, elevation, margin, surface, size, texture, and color) and microscopic observations (reproductive structures) were recorded to identify fungi at the genus level using the taxonomical key of Watanabe [32]. Colony-forming units (CFU) per gram of soil were also counted.
It is important to note that this method captures only the culturable fraction of soil fungi. As such, the results reflect the most readily cultivable genera under the given laboratory conditions and may underestimate total fungal diversity.

2.7. Diversity Indexes

To assess fungal diversity, Simpson’s index (D) and Shannon–Weaver index (H) were calculated. When D is closer to zero, the community is more diverse; it can be interpreted as the probability of randomly drawing two individuals of the same species. The Shannon–Weaver index (H) considers both species richness and abundance, usually ranging from 1 to 4.5, with values above 3 suggesting high diversity [33]. Additionally, the Abundance Coverage Estimator (ACE) index was used to analyze the species accumulation curve, which stabilizes once most morphotypes have been found [34].

2.8. Statistical Analysis

A Spearman correlation analysis was performed on the physicochemical parameters and CFU g−1 to determine how soil properties influence edaphic microbial diversity. To explore how the forest fire might have affected these variables, a Principal Component Analysis (PCA) was applied to the complete data set. Moreover, a Correspondence Analysis (CA) was employed to elucidate the relationships between fungal community structure and soil physicochemical properties. Statistical analyses were conducted using R software v.4.3.0 [35]. Microfungal diversity indices were computed with the software PAST v.4.13 [36].

3. Results

3.1. Physicochemical Characterization

The physicochemical characteristics varied among the soil samples (Table 2). Moisture levels displayed a medium-to-elevated range (25.6 ± 0.86% to 43.4 ± 2.70%) [22]. Obtained pH values ranged between slightly acidic (5.46 ± 0.19–6.30 ± 0.13) and neutral (6.57 ± 0.07–7.08 ± 0.22), except for three soil samples with acid pH (pH < 5.1). Three texture types were observed, with 5% of soils being clayey loam, 15% silty, and 80% silty loam. OM varied between very low (0.03 ± 0.001), low (1.65 ± 0.05%), and medium (2.30 ± 0.18%). CEC values were high (>40 meq 100 g−1). EC, with an average value of 0.754 dS m−1, shows negligible effects, indicating that the soils are not saline. About soil nutrients, P content was high (>30 mg kg−1), and N content ranged from very low (0.002 ± 0.001%) to low (0.114 ± 0.009%).

3.2. Microbial Respiration and Mineralized Nitrogen

Regarding soil biological activity (Table 3), soil respiration ranged between 0.05 ± 0.03 and 0.20 ± 0.05 kg ha−1 d−1, indicating a lack of biological activity in the soil [29]. Likewise, Nm (Table 3) was classified from very low (<11.3 ± 0.32 kg ha−1) to low (19.7 ± 1.23 kg ha−1).
According to the classification criteria described in Table 1, basal respiration values below 10.64 kg C ha−1 d−1 correspond to soils with low or no biological activity. All samples in this study fell well below this threshold, confirming minimal microbial metabolic processes in the post-fire soils. Similarly, nitrogen mineralization (Nm) values below 11.3 kg ha−1 are considered very low, indicating poor microbial conversion of organic nitrogen. These classifications help contextualize the limited biological function observed in the studied area.

3.3. Fungal Diversity: Identification of Aspergillus Morphotypes

This section presents the results of a fungal diversity analysis based on cultured isolates obtained from the BTBNR soil samples. All recovered morphotypes belonged to the genus Aspergillus, as determined by macroscopic and microscopic taxonomic criteria.
Morphotype Aspergillus-1: Smooth topography, granular or cottony texture, pale white color, irregular margin, and white spores (Figure 1). Figure 2 illustrates the reproductive structure of Aspergillus-1 at 40× magnification, showing a typical conidial arrangement. Hyaline conidiophore with smooth walls. Globular vesicle and hyaline, globular to subglobular conidia (Figure 2).
Morphotype Aspergillus-2: Smooth topography, powdery texture, irregular white margin, and black spores (Figure 3). Vesicle globular, hyaline, phialides, nebulae, and globular-to-subglobular conidia (Figure 4).
Morphotype Aspergillus-3: Circular colonies with irregular borders, grey mycelia, with powdery texture (Figure 5). Long, hyaline conidiophores with smooth walls, and globular conidia that gather in masses (Figure 6).
Morphotype Aspergillus-4: Cottony texture, grey, white, or dark beige mycelia, with white margin (Figure 7). Hyaline conidiophores with globular-to-subglobular vesicles, phialides growing directly on the vesicle, and globular-to-subglobular conidia (Figure 8).
The average CFU per gram of soil for samples taken in the BTBNR was 3240 CFU g−1 for morphotype Aspergillus-1; 6275 CFU g−1 for morphotype Aspergillus-2; 3080 CFU g−1 for morphotype Aspergillus-3; and 5900 CFU g−1 for morphotype Aspergillus-4.

3.4. Spearman’s Correlation

Nm was positively correlated with OM, N, and P. On the other hand, respiration was positively correlated with moisture, organic matter (OM), nitrogen (N), and nitrogen mineralization (Nm). Regarding the species found in soil samples, Morphotype Aspergillus-3 was positively correlated with moisture. The species morphotype Aspergillus-4 showed a negative correlation with pH and sand content (Table 4).

3.5. PCA and CA

PCA Axes 1 and 2 explained 59% of the variability in the dataset, including the soil texture and independent explanatory variables (Axis 1 [32%] and Axis 2 [19%]) (Figure 9A). Component 1 (32%) was defined by Nm, OM, and respiration, presenting a negative relationship with sand. Component 2 (19%) was characterized by silt and presented a negative relationship with clay, sand, and AD. CA Axes 1 and 2 explained 65.6% of the total variability in the dataset, indicating that the main structure of the data is well captured. The biplot (Figure 9B) shows that Aspergillus-3 is closely associated with moisture and organic matter content, corroborating the positive correlations observed in the Spearman analysis. In contrast, Aspergillus-4 appears negatively associated with pH and sand content, consistent with its inverse relationship found in the correlation matrix.

3.6. Diversity Indexes

Diversity indices for soil in the BTBNR were made from the four morphotypes of Aspergillus identified. The D indicated medium diversity (0.67) while H (1.32) was interpreted as low biodiversity. ACE represents that communities have been sampled with roughly equivalent intensity relative to their overall richness. The species accumulation curve reached an asymptote with four morphotypes as the sampling effort increased, corresponding to CFU quantification, indicating that the slope of the trend line of the data would not improve and would stabilize after 30 observations (Figure 10).

4. Discussion

This section expands on the results previously presented, discussing the observed patterns in relation to known soil processes and microbial responses to fire disturbance. Although the discussion is structured separately, each analytical finding is directly interpreted to maintain a coherent narrative linking empirical data and ecological meaning.
The high moisture of the soil is related to the accumulated plant cover produced by the tree canopy. Trees provide enough leaf litter to protect the soil from solar radiation, thus preventing temperature rise above the evaporation point. The resulting microclimate enables the maintenance of water content in the soil [37]. Recent advances in hydrological modeling suggest that soil hydrophobicity post-fire significantly affects infiltration rates and water retention, which can now be better predicted through AI-driven models such as HYDRUS-FIRE v3.0 [37]. Obtained pH levels, ranging from moderately acidic to neutral, fall within the optimal growth range for most microorganisms (pH between 6 and 8) [38,39]. The more acidic pH values are likely associated with base displacement in the soil due to water drainage or leaching caused by rain [40], particularly considering the steep slopes present in the area, where 61.2% of the territory is characterized as a mountainous landscape [21]. The non-saline soils can be attributed to low agricultural activity, with the primary use of the soil being forest [41]. CEC is an indirect indicator of soil buffering capacity. This parameter primarily depends on pH, organic matter (OM) content, and soil texture [42]. Even though the study area has low OM levels and soils with silty loam texture, CEC levels are related to the content (11.15%) of illite clay, a mineral with high CEC [25].
The prevailing texture was silty loam, also known as medium texture. Soils with this texture have an equilibrated porosity that allows good aeration and drainage, displaying a capacity for water and nutrient availability [25]. Likewise, OM content is essential for soil fertility due to its contribution of nutrients to plants and microorganisms [43,44,45]. OM content of soils depends on the climate and is related to moisture and temperature. Climate characteristics with high temperatures reduce mineralization rates, and continuously wet conditions may result in low mineralization. Only upon drying of the soil does the mineralization rate increase, or mineralization proceeds at standard rates. Similarly, it has been reported that the addition of OM in the forest is superficial and a consequence of the contribution of the litter. Additionally, the large number of organic acids generated by forest vegetation inhibits the action of microorganisms responsible for degrading organic matter [42]. In the study area, the low organic matter (OM) content is possibly related to the interaction between climate and litter, which can also explain the low fungal biodiversity. Although it can also be associated with the diversity of species, there is a very close relationship between the diversity of plant species and that of fungal species present in each type of vegetation. Taking into account anthropic interventions, the fungal diversity has possibly been affected [46]. The high P content is due to its transformation from organic to inorganic form, and the incorporation of ashes rich in P produced by plant combustion [47]. It is also likely that soils with a high moisture content induce an increase in phosphate ions in the soil solution, resulting in elevated available phosphorus [48]. Likewise, the analysis revealed significant positive correlations between fungal biomass (as ergosterol content) and available phosphorus (p ≤ 0.05), as well as with organic carbon content. These relationships suggest that fungal recovery and activity in post-fire soils may be closely tied to nutrient availability, particularly in the early stages of ecosystem regeneration. The observed correlation patterns underscore the role of fungi not only as decomposers but also as facilitators of nutrient cycling under disturbance conditions.
Soils are the most significant source and reservoir of carbon in terrestrial ecosystems [49,50]. CO2 produced in the soil originates from the metabolism of edaphic microbiota, primarily that of heterotrophic organisms (accounting for 99% of total respiration) and live root respiration [51]. Quantifying soil respiration measures the global microbial heterotrophic activity and organic carbon decomposition [52,53]. In this work, respiration values between 0.05 ± 0.03 and 0.20 ± 0.05 kg ha−1 d−1 place these soils within the very low activity range, as defined by the Woods End Research [29] index. Soil respiration is highly variable, both spatially and seasonally. Different vegetation types influence the amount of soil respiration, as well as the moisture of decaying substrate [51]. As mentioned above, the large number of organic acids generated by forest vegetation inhibits the action of microorganisms responsible for organic matter (OM) degradation [25]. Possibly related to low soil respiratory activity in BTBNR.
Soil features such as moisture, temperature, and porosity influence respiration. The first two factors determine whether microorganisms are present or absent. For its part, soil porosity facilitates better gas exchange, thereby increasing the oxygen levels available for respiration and organic matter (OM) decay [28]. In the study area, high soil water content and low OM content were found, factors that could influence the low rate of soil respiration. The high water content could influence poor aeration, affecting the fungal community. Although it should also be taken into account that the space–time variation of rainfall, particularly during droughts, can alter the population of fungi and soil respiration, as reported by Mohanty and Panda [51], where changes in CO2 production were associated with variations in the abundance of fungi and bacteria. Allam et al. [54] reported that two years after the fire, basal microbial respiration biomass in burned soils remained lower compared to the area unaffected by fire, affirming that the effect on this biological property can persist for several years. In addition, Holden and Treseder [55] found a positive correlation between the reduction of microbial biomass and low values of microbial respiration. The effect of biomass in forests not only affects microbial respiration but also has consequences for the carbon balance of the ecosystem.
It was found that Nm ranged from low to very low, as indicated by the index proposed by Ford et al. [56]. The mineralization process is primarily influenced by moisture and temperature. A decrease in humidity will reduce microbial activity, as N mineralization and immobilization are linked to precipitation pulses and therefore affected by severe droughts [57]. Moisture levels observed in the study area were high. However, with irregular precipitation and elevated temperatures during the dry season, moisture levels do not last long enough, causing alternating desiccation and humidification of the soil. These moisture changes may result in reduced mineralization, and even the immobilization of N. Mineralization of N in arid zones is also linked to C and N availability [56].
On the other hand, soil physical properties such as texture and apparent density also influence N mineralization. Clay has high humidity retention and influences oxygen content, therefore affecting N mineralization. On the other hand, in sandy soils, mineralization is higher due to increased soil aeration [58]. In this study, low N mineralization is associated with soil texture, particularly the prevalence of silt and clay textures.
The indices indicate that the richness (H) is low [59], and the dominance of the species (D) is medium. Results that agree with the four morphotypes of Aspergillus were reported and the CFU counted. This genus includes some species able to colonize decaying matter, infect crops, counteract herbicide contamination, decompose OM, and consume insect remains [60]. The presence of these species in the study area can be attributed to their ability to decompose OM [61]. The species accumulation curve for soils in the BTBNR reached an asymptote, interpreted as the proportion of the total number of individuals in an assemblage that belong to the species represented in the sample. This result suggests that the observations from the collected samples were sufficient to describe species richness [62].
The absence of control treatment with undisturbed soil represents a key limitation. Due to logistical challenges and a lack of baseline data, no comparative sampling from unaffected areas was possible. This limits the ability to distinguish changes due solely to wildfire. Future efforts should aim to sample nearby undisturbed dry forest soils or use comparable data from published sources in similar ecosystems. Despite these limitations, this study provides valuable insights into how wildfire influences the soil environment in tropical dry forests of northern Colombia. Low biological activity, reduced mineralization, and limited fungal diversity are evident in post-fire conditions, reinforcing the need for long-term soil monitoring and restoration strategies.
Due to the scarcity of studies on the impact of forest fires on soil organisms, little is known about the actual effects of fires on soil, the consequences for the soil biotic community, and the changes in ecosystem functioning across different ecoregions and forest types [8]. Although there are no reports on the edaphic microbiota in the study zone before the wildfire, it is probably that this was responsible for the low biodiversity this pattern of microbial sensitivity to soil chemical conditions has also been observed in agricultural soils of the Atlántico department, where changes in organic matter, nitrogen, and pH influence nitrogen-fixing bacterial communities [63]. Like environmental factors, conditions affect the presence of soil microorganisms. The taxonomic and functional groups of fungi that are part of the soil are numerous and varied (saprophytic fungi, parasites, and symbiotes) [52]. The report of four morphotypes of Aspergillus reflects the impact on the diversity of microorganisms and the possible dominance of the Aspergillus genus. It is important to note that the diversity observed in this study is restricted to the culturable fraction of soil fungi, which inherently underestimates the total fungal richness. Culture-dependent methods typically favor fast-growing genera, such as Aspergillus, while many other taxa remain undetected. The use of molecular techniques, such as next-generation sequencing, is recommended for future studies to provide a more detailed and representative analysis of fungal communities in post-fire soils.
Verma and Jayakumar [15] claim that during a wildfire, soils can reach temperatures up to 200 °C, destroying nearly all microfauna and microflora in the soil. Nitrogen-fixing microorganisms, as well as actinomycetes, are positively stimulated by this phenomenon, whereas fungi experience a decrease in their presence and activity. Wildfires also affect biological nutrient cycling, destabilizing it due to the decrease in microorganisms involved in organic compound decay and phytoavailability of nutrients [52]. Guerrero et al. [64] affirm that filamentous fungi appear to be the microorganisms most affected by fire due to their greater temperature sensitivity. Laboratory evaluations that simulate different fire intensities showed that temperatures of 200 °C cause a 99.6% reduction in fungi, which exhibit a lower recolonization capacity compared to bacteria. Conversely, Mataix-Solera et al. [65] found an increase in fungal propagules in response to a slight increase in soil temperature; the mild heating stimulated the germination of fungal spores. Differences in fungal responses to forest fires are likely influenced by variations in fire intensity, severity, vegetation types, and other site-specific factors.
Although there is no previous characterization of the study area, Jhariya and Singh [8] and Verma and Jayakumar [15] affirm that fire can directly or indirectly influence physical, chemical, and biological properties, and these effects depend directly on fire intensity and the duration of combustion. The wildfire event may have affected the physicochemical properties of the soil, including pH, electrical conductivity (EC), structure, texture, porosity, organic matter (OM), and cation exchange capacity (CEC) [52]. This finding is consistent with results reported in other tropical soils, where fertility patterns and cation exchange capacity are influenced by mineral content and organic matter dynamics [66]. About the vectors of the correlation analysis, the AD as an index of the degree of compaction or porous space of the soil is related to the clay since this mineral determines the water retention capacity, both in turn influencing biological activity and microorganism biomass will be reduced in extremely dry or moist soils [67]. About sand, the contribution of P by this mineral is not significant; the largest reserve of this element is found in fine particles. The negative relationship between P and pH is related to the metabolic pathways used by fungi to solubilize phosphates, resulting in a decrease in pH [68]. The silt has a high water retention capacity and is positively correlated with other variables. The silt increases the pH of the acidic soil, and the greater the amount of water in the soil, the smaller the pore space, which affects the available dry (AD) matter of the soil [42].
Edaphic microorganisms colonize the organic matter (OM) and utilize enzymes to oxidize it, thereby obtaining energy and carbon. This biological process generates nutrients in mineral form [14]. In correlation with these variables, soil respiration is a measure of soil microbiota activity [52]. Soil organic matter (OM) decreases due to potential combustion; high-intensity fires can result in a total loss of soil OM [15]. The disappearance of soil-plant cover due to fire or the complete oxidation of organic matter (OM) may leave the soil unprotected, which in turn can increase its vulnerability to physical degradation processes, such as changes in texture and reduced structural stability. Although texture alterations were not directly measured or compared to pre-fire conditions in this study, such effects have been reported in similar post-fire tropical ecosystems [54]. Furthermore, it has also been reported that in lower depths (10–20 cm), there is a decrease in the percentage of sand and clay, possibly related to alterations in the particle size distribution and the destruction of clay due to high temperatures [8]. On the one hand, soil nutrient content is also modified; N is transformed due to volatilization and oxidation from its organic state, which is accumulated in humus, as well as accelerated transformation into ammonia [47,69]. Similarly, pH predicts microorganism abundance in soils, as it influences the metabolic activity of microbes. A decrease in fungal activity is observed when the pH increases from 4.5 to 8.3. Therefore, respiration is inhibited in alkaline soils [70].
On the other hand, the physicochemical factors of the soil that determine the presence of microbiota make it essential to understand that the recovery of organisms after a fire also depends on the severity of the fire, climatic conditions, and the type of vegetation [71]. In this context, and given that there is currently no previous information on the affected area, it is tough to determine the recovery time. Regarding the relationship between soil parameters and microbiota, it was found that morphotype Aspergillus-4 was negatively correlated with sand content. Considering that the amount of mineralized nitrogen is higher in sandy soils compared to clayey or loamy soils [72], the negative relationship is probably associated with the low activity of microorganisms, because in the evaluated soils, the predominant texture was silty loam with sand content between 7 to 28% and silt between 63 to 83%, generating less aeration for microbial biomass. Similarly, the texture and structure of the soil are key determinants of porosity. The heterogeneity of pores is also essential for the distribution and availability of air, water, and nutrients to the microbiota. Fungal growth, through elongation and branching of hyphae, is also favored by the heterogeneity of soil pores [73]. One of the main limitations of this study is the absence of control treatment with undisturbed soil from areas unaffected by fire. This limitation was due to constraints in site accessibility and the lack of pre-existing baseline data from the Banco Totumo Bijibana Natural Reserve. While the findings reflect post-disturbance conditions, comparisons with undisturbed soils would have allowed for a more robust assessment of wildfire effects on microbial activity and fungal diversity. Future studies should consider incorporating reference plots from nearby undisturbed areas or leveraging existing soil databases from similar ecosystems to strengthen the comparative framework. Despite this limitation, the patterns observed in soil respiration, nitrogen mineralization, and fungal composition provide valuable insights into the ecological consequences of wildfire in tropical dry forests.
A key limitation of this study is the absence of a control treatment using unaffected soils of the same type and region. At the time of sampling, it was not possible to collect soil from undisturbed nearby sites due to accessibility and time constraints, and no baseline data were available for the study area prior to the 2014 wildfire. This limits our ability to attribute observed changes solely to the fire event. Future research should include comparative samples from similar undisturbed ecosystems to establish a reliable reference and better isolate fire-related effects on soil microbial communities.

Addressing Post-Fire Fungal Dynamics: Ecological and Methodological Considerations

Post-fire dynamics of soil fungal communities are complex and influenced by various biotic and abiotic factors. The observed decline in fungal diversity following fire events is typically temporary, although the recovery trajectory may vary depending on fire intensity, soil type, vegetation cover, and climatic conditions. Some studies have shown that fungal diversity can recover partially within a few years, but community composition may remain altered in the long term, suggesting potential functional shifts in the ecosystem. Aspergillus species appear to be well adapted to post-fire environments due to several biological mechanisms. These include the production of resistant spores (conidia), the ability to utilize recalcitrant carbon sources, and tolerance to low moisture and nutrient conditions. Their metabolic versatility may contribute to initial stages of soil recovery, by breaking down residual organic matter and facilitating nutrient cycling.
Regarding the broader soil microbiome, other microbial groups such as bacteria and actinomycetes exhibit different responses to fire. Bacteria often show rapid recolonization due to their short generation times, whereas actinomycetes may increase in abundance due to their ability to degrade complex organic substrates. Therefore, the response of fungi is not necessarily representative of all soil microorganisms, underscoring the need for more integrated microbiome studies.
Methodologically, the absence of an unburned control site limits our ability to isolate the specific effects of fire. Including such a reference would have enhanced the robustness of our comparisons. Likewise, relying solely on culturable fungi presents a significant limitation, as a large proportion of soil fungi are known to be non-culturable under standard laboratory conditions. Future work should incorporate metabarcoding approaches to achieve a more comprehensive picture of fungal diversity. The representativeness of our findings may also be influenced by local edaphic conditions, which can shape microbial assemblages independently of fire. Thus, while our results offer valuable insights into a specific tropical dry forest ecosystem, extrapolation to other systems must be made cautiously.
Finally, we acknowledge the provocative nature of some implications raised. It is plausible that fires, despite their destructive effects, may select for more resilient fungal taxa, thereby reshaping the microbiota toward communities with higher stress tolerance. The boundary between destruction and adaptation is not binary, and may depend on ecological context and fire recurrence. Furthermore, human interventions, such as organic matter amendments, could either enhance microbial recovery by restoring substrate availability or disrupt natural successional pathways. The dominance of Aspergillus may reflect both a response to ecological stress and a potential indicator of functional shifts, which warrants further investigation into its long-term implications for ecosystem processes.

5. Methodological Considerations and Future Research

While this study focused on morphological traits to characterize fungal morphotypes, we recognize the inherent limitations of morphology-based identification. Several species within Aspergillus exhibit overlapping phenotypic traits that may hinder accurate delimitation. Therefore, we recommend the integration of molecular markers such as ITS, ef1α, or rpb2 in future analyses to validate and complement morphological observations. The incorporation of molecular tools will be essential to improve taxonomic resolution and to understand the functional implications of fungal assemblages in fire-impacted soils.

6. Conclusions

The presence and activity of soil microbiota, including their ability to decompose organic matter (OM), are primarily influenced by soil characteristics such as moisture and pH. In this study, moisture levels ranged from medium to high, and pH values varied between slightly acidic and neutral, conditions generally favorable for microbial growth. However, the low respiration rates observed suggest that additional limiting factors may be present, potentially linked to post-fire soil conditions or reduced organic substrate availability. The relationship between fungi and soil parameters indicated that morphotype Aspergillus-3 was positively correlated with moisture, and morphotype Aspergillus-4 was negatively correlated with pH and sand content. The species accumulation curve showed an asymptote consistent with an efficient morphotype inventory, indicating that the forest fire affected the microbiota. These findings reinforce previous evidence from tropical agroecosystems in northern Colombia, where nutrient cycling and microbial activity are closely tied to soil fertility indicators, such as organic matter (OM), pH, and cation exchange capacity (CEC) [63,66].

Author Contributions

Conceptualization, E.M.M. and A.C.T.-E.; methodology, E.M.M. and A.C.T.-E.; software, D.A.B.A.; validation, A.C.T.-E., A.C.D.l.P.-G., and M.D.-C.; formal analysis, E.M.M.; investigation, E.M.M. and W.Z.-H.; resources, F.Z.-S.; data curation, J.S.R.-R.; writing—original draft preparation, E.M.M. and A.C.T.-E.; writing—review and editing, A.C.T.-E., A.C.D.l.P.-G., and D.A.B.A.; visualization, W.Z.-H. and M.D.-C.; supervision, A.C.T.-E.; project administration, A.C.T.-E.; funding acquisition, Not applicable. All authors have read and agreed to the published version of the manuscript.

Funding

This research did not receive external funding. The APC was funded by Universidad de la Costa.

Institutional Review Board Statement

The study did not require ethical approval.

Data Availability Statement

The original contributions presented in this study are included in this article; further inquiries can be directed to the corresponding authors.

Acknowledgments

We would like to thank Ana Belén Villalobos for her support in the laboratory analysis.

Conflicts of Interest

The authors declare that there are no conflicts of interest regarding the publication of this manuscript. Furthermore, the authors have fully respected ethical issues, including plagiarism, informed consent, misconduct, data fabrication or falsification, dual publication, and submission and redundancy.

Abbreviations

The following abbreviations are used in this manuscript:
ACEAbundance Coverage Estimator
ADApparent Density
CACorrespondence Analysis
BTBNRBanco Totumo Bijibana Natural Reserve
CECCation Exchange Capacity
CFUColony Forming Units
C/NCarbon/Nitrogen
DSimpson Index
ECElectrical Conductivity
HShannon–Weaver Index
NNitrogen
NmMineralized Nitrogen
OCOrganic Carbon
OMOrganic Matter
PCAPrincipal Component Analysis
%Percentage
meq 100 g−1Cation Exchange Capacity in Milli-Equivalents Per 100 g of Soil

References

  1. Jezierska-Tys, S.; Wesołowska, S.; Gałązka, A.; Joniec, J.; Bednarz, J.; Cierpiała, R. Biological activity and functional diversity in soil in different cultivation systems. Int. J. Environ. Sci. Technol. 2020, 17, 4189–4204. [Google Scholar] [CrossRef]
  2. Gardi, C.; Jeffery, S.; Saltelli, A. An estimate of potential threat levels to soil biodiversity in the EU. Glob. Change Biol. 2013, 19, 1538–1548. [Google Scholar] [CrossRef] [PubMed]
  3. Zenteno-Rojas, A.; Martínez-Romero, E.; Castañeda-Valbuena, D.; Rincón-Molina, C.; Ruíz-Valdiviezo, V.M.; Meza-Gordillo, R.; Rincón-Rosales, R. Structure and diversity of native bacterial communities in soils contaminated with polychlorinated biphenyls. AMB Express 2020, 10, 124. [Google Scholar] [CrossRef] [PubMed]
  4. Gouda, S.; Nayak, S.; Bishwakarma, S.; Kerry, R.G.; Das, G.; Patra, J.K. Role of microbial technology in agricultural sustainability. In Microbial Biotechnology: Applications in Agriculture and Environment; Patra, J.K., Vishnuprasad, C.N., Das, G., Eds.; Springer: Singapore, 2017; pp. 181–202. [Google Scholar] [CrossRef]
  5. Shao, T.; Zhao, J.J.; Liu, A.; Long, X.; Rengel, Z. Effects of soil physicochemical properties on microbial communities in different ecological niches in coastal area. Appl. Soil Ecol. 2020, 150, 103486. [Google Scholar] [CrossRef]
  6. Arias, M.; González-Pérez, J.A.; González-Vila, F.J.; Ball, A.S. Soil health—A new challenge for microbiologists and chemists. Int. J. Microbiol. 2005, 8, 13–21. [Google Scholar] [CrossRef]
  7. Jhariya, M.K.; Singh, L. Herbaceous diversity and biomass under different fire regimes in a seasonally dry forest ecosystem. Environ. Dev. Sustain. 2021, 23, 6800–6818. [Google Scholar] [CrossRef]
  8. Jhariya, M.K.; Singh, L. Effect of fire severity on soil properties in a seasonally dry forest ecosystem of Central India. Int. J. Environ. Sci. Technol. 2021, 18, 3967–3978. [Google Scholar] [CrossRef]
  9. Socarrás, A. Mesofauna edáfica: Indicador biológico de la calidad del suelo. Pastos Forrajes 2013, 36, 5–13. Available online: http://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S0864-03942013000100001 (accessed on 30 June 2024).
  10. Mommer, L.; Kirkegaard, J.; Ruijven, J. Root–root interactions: Towards a rhizosphere framework. Trends Plant Sci. 2016, 21, 209–217. [Google Scholar] [CrossRef] [PubMed]
  11. Thakrey, M.; Singh, L.; Jhariya, M.K.; Tomar, A.; Singh, A.K.; Toppo, S. Impact of disturbance on biomass, carbon, nitrogen storage in vegetation and soil properties in tropical dry deciduous forest in Chhattisgarh, India. Land Degrad. Dev. 2022, 33, 1810–1820. [Google Scholar] [CrossRef]
  12. Manral, V.; Bargali, K.; Bargali, S.S.; Jhariya, M.K.; Padalia, K. Relationships between soil and microbial biomass properties and annual flux of nutrients in Central Himalayan forests, India. Land Degrad. Dev. 2022, 33, 2014–2025. [Google Scholar] [CrossRef]
  13. Martínez, J.M.; Galantini, J.A.; Duval, M.E. Contribution of nitrogen mineralization indices, labile organic matter, and soil properties in predicting nitrogen mineralization. J. Soil Sci. Plant Nutr. 2018, 18, 73–89. [Google Scholar] [CrossRef]
  14. Martínez-Mera, E.; García-Paredes, J.D.; Corrales-Paternina, A.; Torregroza-Espinosa, A.C. Variability of nitrogen mineralization from organic matter in agricultural soils in the north of Colombia. Chiang Mai Univ. J. Nat. Sci. 2021, 20, e2021073. [Google Scholar] [CrossRef]
  15. Verma, S.; Jayakumar, S. Impact of forest fire on physical, chemical, and biological properties of soil: A review. Proc. Int. Acad. Ecol. Environ. Sci. 2012, 2, 168–176. Available online: http://www.iaees.org/publications/journals/piaees/articles/2012-2(3)/impact-of-forest-fire.pdf (accessed on 30 June 2024).
  16. Gómez, E.; Conti, M.E.; Pioli, R.N.; Bisaro, V. Evaluación de poblaciones bacterianas, fúngicas y su diversidad, en un suelo vértico bajo vegetación natural, en sistemas degradados y en recuperación. Rev. Fac. Agron. 2000, 20, 83–89. Available online: https://core.ac.uk/download/pdf/144233833.pdf (accessed on 15 June 2024).
  17. Vallejo, V.; Roldan, F.; Dick, R. Soil enzymatic activities and microbial biomass in an integrated agroforestry chronosequence compared to monoculture and a native forest of Colombia. Biol. Fertil. Soil 2010, 46, 577–587. [Google Scholar] [CrossRef]
  18. Martínez-Mera, E.; Torregroza-Espinosa, A.C.; Crissien-Borrero, T.J.; Marrugo-Negrete, J.L.; González-Márquez, L.C. Evaluation of contaminants in agricultural soils in an Irrigation District in Colombia. Heliyon 2019, 5, e02217. [Google Scholar] [CrossRef]
  19. Weather Spark. El Clima de Repelón, Atlántico. Available online: https://es.weatherspark.com (accessed on 10 March 2024).
  20. Pizano, C.; Gonzáles, R.; García, H.; Isaacs, P.; Gonzáles, M.; Piñeros, P.; Ramírez, W. Bosques Secos Tropicales en Colombia; Instituto de Investigación de Recursos Biológicos Alexander Von Humboldt: Bogotá, Colombia, 2014; Available online: http://repository.humboldt.org.co/handle/20.500.11761/9333 (accessed on 15 June 2024).
  21. Pinzón, L.F.; De León, E.M.; Campo, M.; Tarazona, H.; Soto, M.C. Conociendo y Conservando el DRMI Banco Totumo Bijibana; Concesión Costera Cartagena-Barranquilla, S.A.S.: Barranquilla, Colombia; Fundación Omacha: Bogotá, Colombia; Corporación Autónoma Regional del Atlántico: Barranquilla, Colombia; Ecoex-plora Consultoría: Barranquilla, Colombia, 2020; Available online: https://www.ecoexploraconsultoria.com/wp-content/uploads/2021/03/Libro-Bijibana.pdf (accessed on 10 March 2024).
  22. IGAC-Instituto Geográfico Agustín Codazzi. Métodos Analíticos del Laboratorio de Suelos, 6th ed.; Imprenta Nacional de Colombia: Bogotá, Colombia, 2006.
  23. NTC 5264–Norma Técnica Colombiana. Calidad del Suelo. Determinación del pH; Editorial ICONTEC: Bogotá, Colombia, 2008. [Google Scholar]
  24. NTC 5350–Norma Técnica Colombiana. Calidad de Suelo. Determinación de Fósforo Disponible; Editorial ICONTEC: Bogotá, Colombia, 2014. [Google Scholar]
  25. Castellanos, J.Z. Manual de Interpretación de Análisis de Suelos y Aguas, 2nd ed.; Intagri: Celaya, México, 2000. [Google Scholar]
  26. NTC 5268–Norma Técnica Colombiana. Calidad de Suelo. Determinación de la Capacidad de Intercambio Catiónico; Editorial ICONTEC: Bogotá, Colombia, 2014. [Google Scholar]
  27. Stotzky, G. Microbial respiration. In Agronomy Monographs; Norman, A.G., Ed.; American Society of Agronomy: Madison, WI, USA, 1965; Volume 13, pp. 1550–1572. [Google Scholar] [CrossRef]
  28. Guerrero-Ortiz, P.L.; Quintero-Lizaola, R.; Espinoza-Hernández, V.; Benedicto-Valdés, G.S.; Sánchez-Colín, M.D. Respiración de CO2 como indicador de la actividad microbiana en abonos orgánicos de Lupinus. Terra Latinoam. 2012, 30, 352–362. Available online: https://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S0187-57792012000400355 (accessed on 24 April 2024).
  29. Woods End Research. Guide to Solvita Testing and Managing Your Soil; Woods End Research Laboratory, Inc.: Mt. Vernon, ON, Canada, 1997. [Google Scholar]
  30. Rawls, J.W. Estimating soil bulk density from particle size analysis and organic matter content. Soil Sci. 1983, 135, 123–125. [Google Scholar] [CrossRef]
  31. Castellanos, J.Z.; Cueto, J.A.; Macías, J.; Salinas, J.R.; Tapia, L.M.; Cortes, J.M.; González, I.J.; Mata, H.; Mora, M.; Vásquez, A.; et al. La Fertilización de los Cultivos de Maíz, Sorgo y Trigo en México; INIFAP: Celaya, México, 2005. Available online: https://www.intagri.com/public_files/Manual%20de%20fertilizacion.pdf (accessed on 15 June 2024).
  32. Watanabe, T. Soil and Seed Fungi; CRC Press: Boca Raton, FL, USA, 2010. [Google Scholar]
  33. Villareal, H.; Álvarez, M.; Córdoba, S.; Escobar, F.; Fagua, G.; Gast, F.; Mendoza, H.; Ospina, M.; Umaña, A. Manual de Métodos para el Desarrollo de Inventarios de Biodiversidad; Instituto de Investigación de Recursos Biológicos Alexander Von Humboldt: Bogotá, Colombia, 2004; Available online: http://repository.humboldt.org.co/bitstream/handle/20.500.11761/31419/63.pdf (accessed on 24 April 2024).
  34. Escalante-Espinosa, T. ¿Cuántas especies hay? Los estimadores no paramétricos de Chao. Elementos 2003, 52, 53–56. Available online: https://www.redalyc.org/pdf/294/29405209.pdf (accessed on 24 April 2024).
  35. R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2018. [Google Scholar]
  36. Hammer, Ø.; Harper, D.; Ryan, P. PAST: Paleontological Statistics Software Package for Education and Data Analysis. Palaeontol. Electron. 2001, 4, 1–9. Available online: https://palaeo-electronica.org/2001_1/past/past.pdf (accessed on 24 April 2024).
  37. Alvarez-Garreton, C.; Boisier, J.P.; Garreaud, R.; González, J.; Rondanelli, R.; Gayó, E.; Zambrano-Bigiarini, M. HESS Opinions: The unsustainable use of groundwater conceals a ‘Day Zero’. Hydrol. Earth Syst. Sci. 2024, 28, 1605–1616. [Google Scholar] [CrossRef]
  38. Maroto, E.; Rogel, J. Aplicación de sistemas de biorremediación de suelos y aguas contaminadas por hidrocarburos. Geocisa 2004, 4, 297–305. [Google Scholar]
  39. Rodelo-Torrente, S.; Torregroza-Espinosa, A.C.; Moreno-Pallares, M.; Pinto-Osorio, D.; Corrales-Paternina, A.; Echeverría-González, A. Soil fertility in agricultural production units of tropical areas. Glob. J. Environ. Sci. Manag. 2022, 8, 403–418. [Google Scholar] [CrossRef]
  40. Sadeghian, S. La acidez del suelo: Una limitante común para la producción de café. Av. Técnicos 2016, 466, 1–12. Available online: https://biblioteca.cenicafe.org/bitstream/10778/704/1/avt0466.pdf (accessed on 24 June 2024).
  41. Artiola, J.F.; Crimmins, M.A.; Musil, S.A.; Walworth, J.L. Soil and land pollution. Environ. Sci. Pollut. Res. 2019, 219, 219–235. [Google Scholar] [CrossRef]
  42. Havlin, J.L.; Tisdale, S.L.; Nelson, W.L.; Beaton, J.D. Soil Fertility and Fertilizers: An Introduction to Nutrient Management, 8th ed.; Pearson: Upper Saddle River, NJ, USA, 2013. [Google Scholar]
  43. Andrades, M.; Martínez, E. Fertilidad del Suelo y Parámetros que la Definen, 3rd ed.; Universidad de la Rioja Servicio de Publicaciones: La Rioja, Spain, 2014. [Google Scholar]
  44. Jhariya, M.K. Vegetation ecology and carbon sequestration potential of shrubs in the tropics of Chhattisgarh, India. Environ. Monit. Assess. 2017, 189, 518. [Google Scholar] [CrossRef]
  45. Jhariya, M.K. Influences of forest fire on forest floor and litterfall dynamics in Boardmen Wildlife Sanctuary (C.G.), India. J. For. Environ. Sci. 2017, 33, 330–341. [Google Scholar] [CrossRef]
  46. Wang, J.; Chen, C.; Ye, Z.; Li, J.; Feng, Y.; Lu, Q. Relationships between fungal and plant communities differ between desert and grassland in a typical dryland region of northwest China. Front. Microbiol. 2018, 9, 2327. [Google Scholar] [CrossRef]
  47. Vellozas, T.; Púa, M.; Mello, E.D.; Cardozo, J. Incendios Forestales y su Afectación al Medio Ambiente, Prevención y Combate. Instituto Militar de Estudios Superiores Escuela de Ingeniería Militar. 2010. Available online: https://docplayer.es/58449082-Incendios-forestales-y-su-afectacion-al-medio-ambiente-prevencion-y-combate.html (accessed on 10 March 2024).
  48. Dawson, C.J.; Hilton, J. Fertilizer availability in a resource-limited world: Production and recycling of nitrogen and phosphorus. Food Policy 2011, 36, 14–22. [Google Scholar] [CrossRef]
  49. Raj, A.; Jhariya, M.K. Site quality and vegetation biomass in the tropical Sal mixed deciduous forest of Central India. Landsc. Ecol. Eng. 2021, 17, 387–399. [Google Scholar] [CrossRef]
  50. Raj, A.; Jhariya, M.K. Carbon storage, flux and mitigation potential of tropical Sal mixed deciduous forest ecosystem in Chhattisgarh, India. J. Environ. Manag. 2021, 293, 112829. [Google Scholar] [CrossRef] [PubMed]
  51. Mohanty, R.B.; Panda, T. Soil respiration and microbial population in a tropical deciduous forest soil of Orissa, India. Flora 2011, 206, 1040–1044. [Google Scholar] [CrossRef]
  52. Mataix-Solera, J.; Cerdà, A.; Arcenegui, V.; Jordán, A.; Zavala, L. Fire effects on soil aggregation: A review. Earth Sci. Rev. 2011, 109, 44–60. [Google Scholar] [CrossRef]
  53. Alster, C.J.; van de Laar, A.; Goodrich, J.P. Quantifying thermal adaptation of soil microbial respiration. Nat Commun 2023, 14, 5459. [Google Scholar] [CrossRef] [PubMed]
  54. Allam, A.; Borsali, A.H.; Kefifa, A.; Zouidi, M.; Gros, R. Effect of fires on certain properties of forest soils in western Algeria. Acta Technol. Agric. 2020, 23, 111–117. [Google Scholar] [CrossRef]
  55. Holden, S.R.; Treseder, K.K. A meta-analysis of soil microbial biomass responses to forest disturbances. Front. Microbiol. 2013, 4, 163. [Google Scholar] [CrossRef]
  56. Ford, D.; Cookson, W.; Adams, M.A.; Grierson, P. Role of soil drying in nitrogen mineralization and microbial community function in semi-arid grasslands of North-West Australia. Soil Biol. Biochem. 2007, 39, 1557–1569. [Google Scholar] [CrossRef]
  57. Celaya, H.; Castellanos, A. Mineralización de nitrógeno en el suelo de zonas áridas y semiáridas. Terra Latinoam. 2011, 29, 343–356. Available online: https://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S0187-57792011000300343 (accessed on 24 June 2024).
  58. Monsalve, O.I.; Gutiérrez, J.S.; Cardona, W.A. Factores que intervienen en el proceso de mineralización de nitrógeno cuando son aplicadas enmiendas orgánicas al suelo: Una revisión. Rev. Colomb. Cienc. Hortícolas 2017, 11, 200–209. Available online: https://core.ac.uk/download/pdf/217560483.pdf (accessed on 24 June 2024). [CrossRef]
  59. Martínez-Mera, E.; Torregroza-Espinosa, A.C.; Valencia-García, A.; Rojas-Jerónimo, L. Relationship between soil physicochemical characteristics and nitrogen-fixing bacteria in agricultural soils of the Atlántico department, Colombia. Soil Environ. 2017, 36, 174–181. Available online: http://www.se.org.pk/Papers.aspx?issueid=77 (accessed on 30 July 2024). [CrossRef]
  60. Romero, M.; Inés, M.; Reinoso, E.; Moreno, A. Wild soil fungi able to degrade the herbicide isoproturon. Rev. Mex. Micol. 2008, 29, 1–7. Available online: https://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S0187-31802009000100002 (accessed on 24 June 2024).
  61. Op De Beeck, M.; Troein, C.; Siregar, S.; Gentile, L.; Abbondanza, G.; Peterson, C.; Persson, P.; Tunlid, A. Regulation of fungal decomposition at single-cell level. ISME J. 2020, 14, 896–905. [Google Scholar] [CrossRef] [PubMed]
  62. Chao, A.; Chiu, C.H. Species richness: Estimation and comparison. In Wiley StatsRef: Statistics Reference Online; John Wiley & Sons, Ltd.: Hoboken, NJ, USA, 2016; pp. 1–26. [Google Scholar] [CrossRef]
  63. Stinca, A.; Ravo, M.; Marzaioli, R.; Marchese, G.; Cordella, A.; Rutigliano, F.A.; Esposito, A. Changes in Multi-Level Biodiversity and Soil Features in a Burned Beech Forest in the Southern Italian Coastal Mountain. Forests 2020, 11, 983. [Google Scholar] [CrossRef]
  64. Guerrero, C.; Mataix-Solera, J.; Gómez, I.; García-Orenes, F.; Jordán, M.M. Microbial recolonization and chemical changes in a soil heated at different temperatures. Int. J. Wildl. Fire 2005, 14, 385–400. [Google Scholar] [CrossRef]
  65. Mataix-Solera, J.; Navarro-Pedreño, J.; Guerrero, C.; Gómez, I.; Marco, B.; Mataix, J. Effects of an experimental fire on soil microbial populations in a Mediterranean environment. In Man and Soil at the Third Millennium; Rubio, J.L., Morgan, R.P.C., Asins, S., Andreu, V., Eds.; Geoforma Ediciones: Logroño, Spain, 2002. [Google Scholar]
  66. Aprile, F.; Lorandi, R. Evaluation of Cation Exchange Capacity (CEC) in Tropical Soils Using Four Different Analytical Methods. J. Agric. Sci. 2012, 4. [Google Scholar] [CrossRef]
  67. Browik, A.; Wyszkowska, J. Soil moisture as a factor affecting the microbiological and biochemical activity of soil. Plant Soil Environ. 2016, 62, 250–255. [Google Scholar] [CrossRef]
  68. Arias-Mota, R.M.; Lagunes-Reyes, M.; García-Pérez, J.A.; De la Cruz-Elizondo, Y. Interacción entre cepas de hongos solubilizadores de fósforo y diferentes fuentes de nitrógeno sobre la solubilización y mineralización de fósforo. Alianzas y Tendencias BUAP 2020, 5, 1–19. Available online: https://www.aytbuap.mx/publicaciones#h.6d3xqupfu8t9 (accessed on 21 March 2025).
  69. Nardoto, G.B.; Bustamante, M.M. Effects of fire on soil nitrogen dynamics and microbial biomass in savannas of Central Brazil. Pesq. Agropec. Bras. 2003, 38, 955–962. [Google Scholar] [CrossRef]
  70. Vásquez, J.R.; Macias, F.; Menjivar, J.C. Respiración del suelo según su uso y su relación con algunas formas de carbono en el Departamento del Magdalena, Colombia. Bioagro 2013, 25, 175–180. [Google Scholar]
  71. Zaitsev, A.S.; Gongalsky, K.B.; Malmström, A.; Persson, T.; Bengtsson, J. Why are forest fires generally neglected in soil fauna research? A mini-review. Appl. Soil Ecol. 2016, 98, 261–271. [Google Scholar] [CrossRef]
  72. Habai-Masunga, R.; Nwakaego-Uzokwe, V.; Deusdedit-Mlay, P.; Odeh, I.; Singh, A.; Buchan, D.; De Nevee, S. Nitrogen mineralization dynamics of different valuable organic amendments commonly used in agriculture. Appl. Soil Ecol. 2016, 101, 185–193. [Google Scholar] [CrossRef]
  73. Stolpovsky, K.; Gharasoo, M.; Thullner, M. The impact of pore-size heterogeneities on the spatiotemporal variation of microbial metabolic activity in porous media. Soil Sci. 2012, 177, 98–110. [Google Scholar] [CrossRef]
Diversity 17 00546 g001
Figure 1. Morphotype Aspergillus-1 grown on PDA (Potato Dextrose Agar) medium. The colony exhibits characteristic morphological traits, including color, texture, and growth pattern, used for preliminary taxonomic identification. This culture-based observation serves as a first step in differentiating fungal isolates obtained from post-fire soil samples.
Figure 1. Morphotype Aspergillus-1 grown on PDA (Potato Dextrose Agar) medium. The colony exhibits characteristic morphological traits, including color, texture, and growth pattern, used for preliminary taxonomic identification. This culture-based observation serves as a first step in differentiating fungal isolates obtained from post-fire soil samples.
Diversity 17 00546 g001
Diversity 17 00546 g002
Figure 2. Reproductive structure of Aspergillus-1 observed under light microscopy at 40× magnification. The image shows the conidiophore and conidia arrangement typical of the genus Aspergillus, supporting the morphological identification of the isolate.
Figure 2. Reproductive structure of Aspergillus-1 observed under light microscopy at 40× magnification. The image shows the conidiophore and conidia arrangement typical of the genus Aspergillus, supporting the morphological identification of the isolate.
Diversity 17 00546 g002
Diversity 17 00546 g003
Figure 3. Morphotype Aspergillus-2 grown on PDA (Potato Dextrose Agar) medium. The colony displays distinct macroscopic features, including coloration and surface texture, used for morphological differentiation from other isolates. This culture-based characterization provides initial evidence for fungal diversity in post-fire soil environments.
Figure 3. Morphotype Aspergillus-2 grown on PDA (Potato Dextrose Agar) medium. The colony displays distinct macroscopic features, including coloration and surface texture, used for morphological differentiation from other isolates. This culture-based characterization provides initial evidence for fungal diversity in post-fire soil environments.
Diversity 17 00546 g003
Diversity 17 00546 g004
Figure 4. Reproductive structure of Aspergillus-2 observed under light microscopy at 40× magnification. The image reveals the morphology of conidiophores and conidia, characteristic of the genus Aspergillus.
Figure 4. Reproductive structure of Aspergillus-2 observed under light microscopy at 40× magnification. The image reveals the morphology of conidiophores and conidia, characteristic of the genus Aspergillus.
Diversity 17 00546 g004
Diversity 17 00546 g005
Figure 5. Morphotype Aspergillus-3 grown on PDA (Potato Dextrose Agar) medium. The colony exhibits unique morphological characteristics, such as pigmentation and mycelial structure, which aid in its differentiation from other Aspergillus morphotypes isolated from the soil. This macroscopic analysis contributes to the preliminary classification of fungal diversity in fire-impacted environments.
Figure 5. Morphotype Aspergillus-3 grown on PDA (Potato Dextrose Agar) medium. The colony exhibits unique morphological characteristics, such as pigmentation and mycelial structure, which aid in its differentiation from other Aspergillus morphotypes isolated from the soil. This macroscopic analysis contributes to the preliminary classification of fungal diversity in fire-impacted environments.
Diversity 17 00546 g005
Diversity 17 00546 g006
Figure 6. Reproductive structure of Aspergillus-3 observed under light microscopy at 40× magnification. The micrograph highlights diagnostic elements, such as the shape and arrangement of the conidiophore and conidia, supporting its classification within the genus Aspergillus. These observations provide morphological evidence for distinguishing this isolate from other fungal morphotypes.
Figure 6. Reproductive structure of Aspergillus-3 observed under light microscopy at 40× magnification. The micrograph highlights diagnostic elements, such as the shape and arrangement of the conidiophore and conidia, supporting its classification within the genus Aspergillus. These observations provide morphological evidence for distinguishing this isolate from other fungal morphotypes.
Diversity 17 00546 g006
Diversity 17 00546 g007
Figure 7. Morphotype Aspergillus-4 grown on PDA (Potato Dextrose Agar) medium. The colony presents distinctive macroscopic traits such as coloration, border definition, and growth density, which aid in its visual differentiation from other Aspergillus isolates. This culture-based analysis contributes to the morphological profiling of fungal communities in post-fire soils.
Figure 7. Morphotype Aspergillus-4 grown on PDA (Potato Dextrose Agar) medium. The colony presents distinctive macroscopic traits such as coloration, border definition, and growth density, which aid in its visual differentiation from other Aspergillus isolates. This culture-based analysis contributes to the morphological profiling of fungal communities in post-fire soils.
Diversity 17 00546 g007
Diversity 17 00546 g008
Figure 8. Reproductive structure of Aspergillus-4 observed under light microscopy at 40× magnification. The image reveals key microscopic features, including the morphology of the conidiophore and arrangement of conidia, which support the taxonomic assignment to the genus Aspergillus. These traits complement macroscopic observations and contribute to the morphological identification of the isolate.
Figure 8. Reproductive structure of Aspergillus-4 observed under light microscopy at 40× magnification. The image reveals key microscopic features, including the morphology of the conidiophore and arrangement of conidia, which support the taxonomic assignment to the genus Aspergillus. These traits complement macroscopic observations and contribute to the morphological identification of the isolate.
Diversity 17 00546 g008
Diversity 17 00546 g009
Figure 9. (A) Principal Component Analysis (PCA) and (B) Cluster Analysis (CA) illustrating the relationships among soil physicochemical and biological properties across sampling sites in the Banco Totumo–Bijibana Natural Reserve. The PCA biplot highlights the variables contributing most to the variance in the dataset, while the CA dendrogram groups sampling units based on similarity in soil attributes, providing insight into post-fire soil functioning and microbial activity patterns. OM: Organic matter; Nm: mineralized nitrogen; AD: apparent density.
Figure 9. (A) Principal Component Analysis (PCA) and (B) Cluster Analysis (CA) illustrating the relationships among soil physicochemical and biological properties across sampling sites in the Banco Totumo–Bijibana Natural Reserve. The PCA biplot highlights the variables contributing most to the variance in the dataset, while the CA dendrogram groups sampling units based on similarity in soil attributes, providing insight into post-fire soil functioning and microbial activity patterns. OM: Organic matter; Nm: mineralized nitrogen; AD: apparent density.
Diversity 17 00546 g009
Diversity 17 00546 g010
Figure 10. Species accumulation curve for fungal morphotypes isolated from soil samples in the Banco Totumo–Bijibana Natural Reserve. The curve illustrates the relationship between sampling effort and the cumulative number of fungal morphotypes detected, indicating the degree of sampling completeness and species richness in post-fire soil environments.
Figure 10. Species accumulation curve for fungal morphotypes isolated from soil samples in the Banco Totumo–Bijibana Natural Reserve. The curve illustrates the relationship between sampling effort and the cumulative number of fungal morphotypes detected, indicating the degree of sampling completeness and species richness in post-fire soil environments.
Diversity 17 00546 g010
Table 1. General indexes associated with soil respiration classes and soil condition, measured under controlled laboratory conditions simulating optimal temperature and moisture. The table includes indicators of basal respiration rate, substrate-induced respiration (SIR), and microbial quotient, providing insights into the metabolic activity and biological status of the soil across burned and unburned plots.
Table 1. General indexes associated with soil respiration classes and soil condition, measured under controlled laboratory conditions simulating optimal temperature and moisture. The table includes indicators of basal respiration rate, substrate-induced respiration (SIR), and microbial quotient, providing insights into the metabolic activity and biological status of the soil across burned and unburned plots.
Soil Respiration
(kg C ha−1 d−1)		ClassSoil Status
0No soil activityInert soil without biological activity
<10.64Low soil activityThe soil lacks available OM
10.64–17.92Medium to moderately low soil activitySoil has lost OM, and its activity is low
17.92–35.84Medium soil activitySoil is approaching or declining from an ideal state of biological activity
35.84–71.68Ideal soil activityIdeal status of soil
>71.68Unusually high soil activityVery high soil activity and high %OM
Table 2. Physicochemical parameters of soil samples collected from the Banco Totumo–Bijibana Natural Reserve. Data include pH, electrical conductivity (EC), organic matter (OM), total nitrogen (TN), available phosphorus (P), and exchangeable cations (Ca2+, Mg2+, K+, Na+). Values are expressed as mean ± standard deviation. These measurements provide a baseline for assessing the impact of wildfire on soil chemical fertility and structure.
Table 2. Physicochemical parameters of soil samples collected from the Banco Totumo–Bijibana Natural Reserve. Data include pH, electrical conductivity (EC), organic matter (OM), total nitrogen (TN), available phosphorus (P), and exchangeable cations (Ca2+, Mg2+, K+, Na+). Values are expressed as mean ± standard deviation. These measurements provide a baseline for assessing the impact of wildfire on soil chemical fertility and structure.
Soil
Sample		M ± DE
(%)		pH ± DETextOM ± DE
(%)		P ± DE
(mg kg−1)		N ± DE
(%)		CEC ± DE
(meq 100 g−1)		EC ± DE
(dS m−1)
133.9 ± 0.235.76 ± 0.12FA2.30 ± 0.1871.3 ± 16.10.114 ± 0.00958.6 ± 13.20.50 ± 0.05
232.6 ± 0.395.60 ± 0.13FL2.16 ± 0.2068.8 ± 5.320.107 ± 0.00953.5 ± 2.610.87 ± 0.04
331.5 ± 2.075.46 ± 0.19L0.03 ± 0.00170.7 ± 17.00.002 ± 0.00151.2 ± 6.060.82 ± 0.04
432.6 ± 0.555.90 ± 0.41FL0.11 ± 0.0751.6 ± 4.180.005 ± 0.00351.1 ± 5.240.86 ± 0.19
533.4 ± 0.566.19 ± 0.22FL0.31 ± 0.0743.4 ± 8.060.015 ± 0.00350.9 ± 0.700.98 ± 0.12
636.7 ± 8.926.25 ± 0.12FL0.78 ± 0.0847.6 ± 11.00.039 ± 0.00363.5 ± 10.90.84 ± 0.04
728.3 ± 0.286.00 ± 0.14L0.50 ± 0.0961.5 ± 10.00.025 ± 0.00456.7 ± 21.60.79 ± 0.09
831.8 ± 1.285.18 ± 0.27L0.23 ± 0.0256.1 ± 1.420.011 ± 0.00064.7 ± 30.50.77 ± 0.10
934.3 ± 1.145.58 ± 0.07FL0.17 ± 0.1345.9 ± 13.40.008 ± 0.00644.2 ± 2.231.01 ± 0.06
1034.6 ± 0.454.96 ± 0.15FL0.28 ± 0.0967.2 ± 0.270.013 ± 0.00458.2 ± 10.70.68 ± 0.07
1134.2 ± 0.335.10 ± 0.11FL1.65 ± 0.0548.0 ± 17.70.082 ± 0.00246.1 ± 2.850.90 ± 0.11
1243.4 ± 2.705.93 ± 0.13FL1.34 ± 0.0575.8 ± 2.540.066 ± 0.00267.1 ± 4.210.63 ± 0.15
1342.5 ± 0.646.34 ± 0.18FL0.46 ± 0.0772.5 ± 4.800.023 ± 0.00366.5 ± 13.00.74 ± 0.20
1441.2 ± 2.476.30 ± 0.13FL0.30 ± 0.0451.8 ± 19.20.014 ± 0.00267.9 ± 13.80.77 ± 0.04
1534.9 ± 0.526.57 ± 0.07FL0.79 ± 0.0873.0 ± 19.30.039 ± 0.00456.2 ± 18.20.71 ± 0.15
1631.0 ± 0.956.26 ± 0.12FL0.58 ± 0.1167.3 ± 13.10.029 ± 0.00569.2 ± 5.420.56 ± 0.24
1726.4 ± 3.606.61 ± 0.04FL0.51 ± 0.0987.3 ± 1.090.025 ± 0.00452.7 ± 17.00.66 ± 0.22
1825.6 ± 0.867.08 ± 0.22FL0.78 ± 0.0762.2 ± 1.860.039 ± 0.00365.9 ± 4.750.61 ± 0.15
1934.7 ± 1.676.09 ± 0.47FL0.26 ± 0.0755.3 ± 9.720.013 ± 0.00350.4 ± 3.670.51 ± 0.04
2036.4 ± 1.276.26 ± 0.35FL0.52 ± 0.0864.2 ± 3.170.026 ± 0.00351.7 ± 3.370.87 ± 0.90
FA: clayey loam; FL: silty loam; OM: organic matter; CEC: cation exchange capacity; EC: electrical conductivity.
Table 3. Soil respiration rates (kg C ha−1 d−1) and mineralized nitrogen levels (kg ha−1) in soils from the Banco Totumo–Bijibana Natural Reserve. Activity classifications are based on the Woods End Research Index [29], which provides thresholds for interpreting microbial activity and nutrient mineralization status. Values are expressed as mean ± standard deviation.
Table 3. Soil respiration rates (kg C ha−1 d−1) and mineralized nitrogen levels (kg ha−1) in soils from the Banco Totumo–Bijibana Natural Reserve. Activity classifications are based on the Woods End Research Index [29], which provides thresholds for interpreting microbial activity and nutrient mineralization status. Values are expressed as mean ± standard deviation.
Soil SampleSR ± DE
(kg ha−1 d−1)		ClassificationNm ± DE
(kg ha−1)		Classification
10.18 ± 0.02No activity19.7 ± 1.23Low
20.15 ± 0.03No activity18.7 ± 1.37Low
30.11 ± 0.02No activity0.36 ± 0.17Very low
40.14 ± 0.01No activity0.94 ± 0.36Very low
50.10 ± 0.01No activity2.41 ± 0.52Very low
60.09 ± 0.03No activity4.91 ± 0.46Very low
70.08 ± 0.02No activity2.68 ± 0.47Very low
80.09 ± 0.02No activity2.06 ± 0.13Very low
90.05 ± 0.03No activity2.25 ± 1.21Very low
100.13 ± 0.09No activity2.15 ± 0.69Very low
110.16 ± 0.01No activity11.3 ± 0.32Very low
120.19 ± 0.01No activity9.47 ± 0.34 Very low
130.20 ± 0.05No activity3.51 ± 0.48Very low
140.14 ± 0.02No activity2.67 ± 0.35Very low
150.08 ± 0.04No activity5.86 ± 0.55Very low
160.18 ± 0.01No activity5.13 ± 0.90Very low
170.05 ± 0.02No activity3.89 ± 0.66Very low
180.14 ± 0.01No activity7.79 ± 0.63Very low
190.10 ± 0.01No activity2.37 ± 0.61Very low
200.10 ± 0.009No activity3.95 ± 0.57Very low
Table 4. Correlation between physicochemical parameters and biological properties in soil samples from the Banco Totumo–Bijibana Natural Reserve. The table presents Pearson correlation coefficients between variables such as pH, organic matter, available nutrients, and microbial activity indicators (e.g., soil respiration and ergosterol content). Statistically significant correlations (p ≤ 0.05) are highlighted to indicate relationships of ecological relevance in post-fire soil conditions.
Table 4. Correlation between physicochemical parameters and biological properties in soil samples from the Banco Totumo–Bijibana Natural Reserve. The table presents Pearson correlation coefficients between variables such as pH, organic matter, available nutrients, and microbial activity indicators (e.g., soil respiration and ergosterol content). Statistically significant correlations (p ≤ 0.05) are highlighted to indicate relationships of ecological relevance in post-fire soil conditions.
Parameter MoisturepHSandClaySiltOMNPADNmRespirationM-1M-2M-3M-4
Correlation Coefficientp-value
Moisture1.000.460.640.600.950.910.910.620.380.770.050.150.500.000.74
pH−0.101.000.410.610.350.190.190.300.650.140.530.620.510.090.00
Sand0.060.111.000.860.000.090.090.150.120.080.620.710.780.790.05
Clay0.070.07−0.021.000.000.210.210.500.000.090.060.860.260.430.91
Silt−0.01−0.13−0.59−0.741.000.910.910.290.200.900.410.360.510.510.11
OM0.010.18−0.220.170.011.000.000.040.010.000.010.410.470.660.38
N0.010.18−0.220.170.011.001.000.040.010.000.010.410.470.660.38
P−0.070.14−0.19−0.090.140.280.281.000.990.020.300.770.310.380.12
AD−0.12−0.06−0.200.39−0.17−0.33−0.330.001.000.090.950.870.330.990.62
Nm0.040.20−0.230.23−0.020.980.980.30−0.231.000.000.410.460.740.35
Respiration0.26−0.08−0.070.25−0.110.350.350.14−0.010.401.000.350.460.910.79
M-1−0.19−0.070.05−0.02−0.12−0.11−0.11−0.04−0.02−0.110.131.000.010.010.24
M-2−0.090.090.040.15−0.090.100.100.140.130.10−0.10−0.361.000.000.10
M-30.390.220.04−0.110.09−0.06−0.060.120.00−0.04−0.02−0.32−0.451.000.14
M-4−0.04−0.42−0.26−0.020.210.120.12−0.21−0.070.120.04−0.16−0.22−0.191.00
OM: organic matter; Nm: mineralized nitrogen; AD: apparent density. Bold values indicate statistical significance (p ≤ 0.05).
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Martínez Mera, E.; Torregroza-Espinosa, A.C.; De la Parra-Guerra, A.C.; Durán-Castiblanco, M.; Zapata-Herazo, W.; Rodríguez-Rebolledo, J.S.; Zabala-Sierra, F.; Alvarez, D.A.B. Soil Fungal Activity and Microbial Response to Wildfire in a Dry Tropical Forest of Northern Colombia. Diversity 2025, 17, 546. https://doi.org/10.3390/d17080546

AMA Style

Martínez Mera E, Torregroza-Espinosa AC, De la Parra-Guerra AC, Durán-Castiblanco M, Zapata-Herazo W, Rodríguez-Rebolledo JS, Zabala-Sierra F, Alvarez DAB. Soil Fungal Activity and Microbial Response to Wildfire in a Dry Tropical Forest of Northern Colombia. Diversity. 2025; 17(8):546. https://doi.org/10.3390/d17080546

Chicago/Turabian Style

Martínez Mera, Eliana, Ana Carolina Torregroza-Espinosa, Ana Cristina De la Parra-Guerra, Marielena Durán-Castiblanco, William Zapata-Herazo, Juan Sebastián Rodríguez-Rebolledo, Fernán Zabala-Sierra, and David Alejandro Blanco Alvarez. 2025. "Soil Fungal Activity and Microbial Response to Wildfire in a Dry Tropical Forest of Northern Colombia" Diversity 17, no. 8: 546. https://doi.org/10.3390/d17080546

APA Style

Martínez Mera, E., Torregroza-Espinosa, A. C., De la Parra-Guerra, A. C., Durán-Castiblanco, M., Zapata-Herazo, W., Rodríguez-Rebolledo, J. S., Zabala-Sierra, F., & Alvarez, D. A. B. (2025). Soil Fungal Activity and Microbial Response to Wildfire in a Dry Tropical Forest of Northern Colombia. Diversity, 17(8), 546. https://doi.org/10.3390/d17080546

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