182 RBCIAMB | v.58 | Jun 2023 | 182-191 - ISSN 2176-9478 A B S T R A C T Anthropogenic activities in any natural ecosystem cause changes that affect the physical and biological environment, causing degradation. Likewise, these activities can cause significant changes in the chemical and physical factors of the soil, also impacting the microbiological community. The study aimed to evaluate the influence of soil biochemical and physicochemical characteristics on the development of fungal communities in three different soils of the Pampa biome. The soil types selected were: native forest, Eucalyptus plantation and pasture area, in two distinct periods: hot and cold. Microbiological, physicochemical and biochemical analyses of the soils were carried out. The following genera and species of fungi were identified: Aspergillus sp., Aspergillus niger, Fusarium sp., Geotrichum sp., Isaria sp., Penicillium sp., Scedosporium sp., Trichoderma sp., Verticillium sp. The results showed that the fungal community is being affected by soil composition characteristics, regardless of the sampled areas. Aspergillus sp. is associated with higher amounts of manganese, boron and the Ca+Mg/K ratio in the soil, while A. niger and Trichoderma sp. have a negative relationship with these variables. Aspergillus sp. showed a high ability to tolerate Mn. The most diverse area was pasture in the warm period, and the least diverse was Eucalyptus plantation in the cold period. The analyzed taxa had a reduction in the cold period compared to the warm one, except for Aspergillus sp. in the Eucalyptus area, which presented a greater amount in the cold period compared to the hot period. It can be seen that the use of soil in the Pampa biome for planting monocultures or for generating pastures interferes with its characteristics and distinctly affects the fungal community. Keywords: soil management; physicochemical aspects of the soil; soil biochemistry; soil microorganisms. R E S U M O As atividades antropogênicas em qualquer ecossistema natural causam modificações que afetam o ambiente físico e biológico, gerando degradação. Da mesma forma, essas atividades podem causar modificações significativas nos fatores químicos e físicos do solo, impactando também a comunidade microbiológica. O estudo objetivou avaliar a influência de características bioquímicas e físico-químicas do solo sobre o desenvolvimento de comunidades fúngicas em diferentes solos do bioma Pampa. Os tipos de solo selecionados foram: área de floresta nativa, área de plantação de eucalipto e área de pastagem, em dois períodos distintos: quente e frio. Foram realizadas análises microbiológicas, físico-químicas e bioquímicas dos solos. Identificaram-se os seguintes gêneros e espécie de fungos: Aspergillus sp., Aspergillus niger, Fusarium sp., Geotrichum sp., Isaria sp., Penicillium sp., Scedosporium sp., Trichoderma sp., Verticillium sp. Os resultados mostraram que a comunidade fúngica está sendo afetada pela composição das características do solo, independentemente das áreas amostradas. Aspergillus sp. está associado a maiores quantidades de manganês, boro e da relação Ca+Mg/K no solo, enquanto A. niger e Trichoderma sp. têm relação negativa com essas variáveis. Aspergillus sp. mostrou elevada capacidade de tolerância ao Mn. A área mais diversa foi a de pastagem no período quente, e a menos diversa foi a área de eucalipto no período frio. Os táxons analisados tiveram redução no período frio em relação ao período quente, com exceção de Aspergillus sp. na área de eucalipto, que apresentou maior quantidade em período frio em relação ao período quente. Pode-se constatar que a utilização do solo no bioma Pampa, para plantação de monoculturas ou para a geração de pastagens, interfere em suas características e afeta distintamente a comunidade fúngica. Palavras-chave: manejo do solo; aspectos físico-químicos do solo; bioquímica do solo; microrganismos do solo. Influence of different soil uses in the Pampa biome, southern Brazil, on fungal communities Influência de diferentes usos de solo do bioma Pampa, sul do Brasil, nas comunidades fúngicas Amanda Luisa Stroher1 , Thais Müller1 , Daiane Heidrich1 , Guilherme Liberato da Silva1 , Claudete Rempel1 , Mônica Jachetti Maciel1 1Universidade do Vale do Taquari – Lajeado (RS), Brazil. Correspondence address: Thais Müller – Avelino Tallini, 171 – Bairro Universitario – CEP: 95914-014 – Lajeado (RS), Brasil. E-mail: mthais@universo.univates.br Conflicts of interest: the authors declare that there are no conflicts of interest. Funding: none. Received on: 02/02/2023. Accepted on: 06/19/2023 https://doi.org/10.5327/Z2176-94781550 Revista Brasileira de Ciências Ambientais Brazilian Journal of Environmental Sciences Revista Brasileira de Ciências Ambientais Brazilian Journal of Environmental Sciences ISSN 2176-9478 Volume 56, Number 1, March 2021 This is an open access article distributed under the terms of the Creative Commons license. https://orcid.org/0000-0003-4279-8279 https://orcid.org/0000-0001-7366-9678 https://orcid.org/0000-0002-1010-5215 https://orcid.org/0000-0001-6619-6622 https://orcid.org/0000-0001-8573-0237 https://orcid.org/0000-0002-6863-2181 mailto:mthais@universo.univates.br https://doi.org/10.5327/Z2176-94781550 http://www.rbciamb.com.br http://abes-dn.org.br/ Influence of different soil uses in the Pampa biome, southern Brazil, on fungal communities 183 RBCIAMB | v.58 | Jun 2023 | 182-191 - ISSN 2176-9478 Introduction The Pampa biome is located in South America and extends over an area of approximately 700,000 km2, being present in Argentina, Uruguay and Brazil, where it exclusively occupies the state of Rio Grande do Sul. Its vegetation is quite characteristic, being composed of pastures, undergrowth, grasses and riparian forests. This biome is known for its rich diversity and has an abundant geological com- position, formed by several microecosystems (Bolzan et  al., 2016). The microbial biodiversity of the Pampa biome has not yet been suffi- ciently explored, and probably several species of microorganisms can still be found (Daniel Junior et al., 2018). Despite its abundant diversity, the Pampa biome is still little known and studies about its communities are scarce. In recent years, the Pampa has been degraded to favor livestock and agricultural expansion, cattle breeding, and planting of soybean, corn and exotic tree species (Lupati- ni et al., 2013). This biome has one of the smallest networks of protected areas in the world and the smallest in Brazil (Lima et al., 2020). Soil fungi play important roles for the ecosystem, as they are re- sponsible for the decomposition of organic waste and xenobiotics, make biological control, establish symbiotic relationships, promote soil aggregation, mineralization of nutrients and cause diseases (Tortora et al., 2017). According to Moreira and Siqueira (2006), several factors affect soil organisms, so populations vary depending on the type of soil, vegetation and climatic conditions. Thus, large microbial varia- tions can be found between distinct ecosystems in the same region or in different geographic regions. Soil degradation and lack of vegetation cover affects the growth of macro and microbial communities, since they cause changes in food availability, soil temperature and humidity. Species resistant to envi- ronments with low availability of nutrients are selected and cause re- duction of carbon cycling, soil aeration and disintegration of organic matter, resulting in decreased microbial biomass (Granada et al., 2019). Considering the hypothesis that soils used in different activities may present different physicochemical and biochemical conditions, possibly influencing the fungal community, this study aimed to evalu- ate the influence of biochemical and physicochemical soil characteris- tics on the development of fungal communities in different soils of the Pampa biome. Material and Methods Collection of the samples Soil samples were collected in the city of Pantano Grande/RS, in the Pampa biome domain. Three different areas of land use were selected: native forest area, Eucalyptus plantation area and pasture area (Figure 1) — the native forest belonging to the Atlantic Forest biome. The Eucalyptus area has silvicultural practices of prepara- tion and soil fertilization and was under cultivation for seven years. The pasture area was previously used in the plantation of monocul- tures and had not been interfered with in approximately five years. In each area, three collection points were defined, sampled in triplicate. The soil was collected with the aid of a modified Auger at a depth of 5 cm with 10 cm in diameter and sieved in buckets previously disinfected with 70 GL alcohol. After that, the sample was placed in Stomacher hermetic bags and stored in a thermal box for temperature preservation. For the collection, at each point a 1 m2 quadrant was defined, from which nine points were randomly selected to compose the final sample. The coordinates of each sampled site can be found in Chart 1. The collection was performed in two distinct periods, winter and summer. Samples from the cold peri- od (mean temperature of 15°C) were collected in July 2017 and the hot period (mean temperature of 30°C) was collected in December 2019. Figure 1 – Demarcation of the three collection points in the areas of native forest, Eucalyptus plantation and pasture selected for soil collection. N: North. P1: Pasture 1; P2: Pasture 2; P3: Pasture 3; E1: Eucalyptus 1; E2: Eu- calyptus 2; E3: Eucalyptus 3; N1: Native 1; N2: Native 2; N3: Native 3. Source: Adapted from Google Earth. Chart 1 – Coordinates of the sampled points for each land use area: native vegetation, Eucalyptus plantation and pasture*. *Geographical coordinates of the three collection points of the different areas of land use analyzed in this study, native vegetation, pasture and Eucalyptus plantation. Collection points Latitude Longitude Pasture 1 6655441.00 m S 360302.00 m E Pasture 2 6655427.70 m S 360339.44 m E Pasture 3 6651137.00 m S 356770.00 m E Eucalyptus 1 6650246.00 m S 367850.00 m E Eucalyptus 2 6650251.00 m S 367810.00 m E Eucalyptus 3 6650306.83 m S 367871.16 m E Native 1 6644258.02 m S 355770.85 m E Native 2 6643880.08 m S 355960.58 m E Native 3 6644681.81 m S 357534.26 m E Stroher, A.L. et al. 184 RBCIAMB | v.58 | Jun 2023 | 182-191 - ISSN 2176-9478 Microbiological analyses After soil collection, the samples were taken to the Microbiology Laboratory to be analyzed. For the extraction of fungi present in the soil, the decimal dilution technique was performed. 10 g of soil was weighed and 90 mL of saline peptone water was added. After one min- ute stirring in the homogenizer, decimal dilution was performed up to 10-5. An aliquot of 0.1 mL was removed from each dilution and plat- ed in a petri dish containing Sabouraud agar with chloramphenicol to prevent bacterial growth. The plates were incubated at 25°C for five days. After this period the count of Colony Forming Units (CFU)/ g of soil was performed. The colonies that showed growth after five days of incubation were isolated with the aid of a magnifying glass and inoc- ulation loops in petri dishes with Sabouraud agar. The identification of genera was made by microculture. In a glass petri dish were placed two blades with two agar cubes with the fungus sown between them, a supporting blade and a cotton ball moistened. The microcultures were incubated at 25°C for seven days for growth of fungal structures. After this period, the slides were stained with lactophenol and KOH 20% and visualized under a microscope. The identification was based on the macro and micromorphological characteristics of the isolates. In the macroscopic study the reverse was observed of the colonies, such as in  diameter, color of conidia and mycelium, texture, presence of ex- udates and soluble pigments. Microscopic structures such as conidio- phores, conidiogenic cells and conidia were analyzed. For the identifi- cation of genera and species, the following literature was used: Domsch et al. (2007). The following isolates were identified: Aspergillus sp., As- pergillus niger, Fusarium sp., Geotrichum sp., Isaria sp., Penicillium sp., Scedosporium sp., Trichoderma sp., Verticillium sp. After being identi- fied, the fungi were stored in test tubes with Sabouraud agar inclined to room temperature and in skim milk 10% in Eppendorf frozen at -20°C. Physicochemical and biochemical analyses In addition to the microbiological analyses, the following chemical analyses of clay, pH by the method SMP, potassium, phosphorus, per- centage of organic matter, calcium, aluminum, magnesium, chlorine, copper, zinc, boron, sulfur and manganese were performed; and also physical analysis of sand, clay and silt. All these analyses were per- formed by an outsourced laboratory member of the Official Network of Soil Analysis Laboratories of the States of Rio Grande do Sul and Santa Catarina (ROLAS) and also a member of the Quality Control Program of Fertility Laboratories coordinated by the Embrapa System of Soil Analysis (PAQLF). Physicochemical analyses of moisture, pH, granulometry and nitrogen were performed. To determine the humidity, a soil sample was placed in a Becker of known mass, weighed and left in the green- house for 24 hours. Then, the sample was placed in a desiccator and weighed again. The mass of the second weighing of the mass of the first weighing was discounted, thus obtaining the percentage of mois- ture present in the soil. The pH analysis was performed following the methodology of Embrapa (1997), adding 25 mL of distilled water in 10 g of soil and measuring with a pH meter after one hour rest. The granulometry aimed to characterize the amounts of silt, sand and clay present in the soil, as well as to determine its classification, and was performed according to the methodology proposed by Van Raij (2001). Nitrogen was quantified by protein tube digestion and distillation by the Kjeldahl method, following the Embrapa protocol (1997). Biochemical analyses included microbial biomass, basal respira- tion and microbial quotient. The microbial biomass was determined by soil irradiation method and titration with ferrous ammoniacal sulfate 0.03 mol/L, according to the methodology described by Mendonça and Matos (2005). Basal respiration was performed following a protocol proposed by Stotzky (1965), where the soil rested for 40 days in her- metic pots with sodium hydroxide for analysis and was then titrated with hydrochloric acid PA. The microbial quotient (qMIC) was cal- culated following Anderson and Domsch (1993), using the values of microbial biomass and soil organic carbon. Statistical analysis of the data A restricted (canonical) ordering was performed through redun- dancy analysis based on distance — db-RDA (Legendre and Anderson, 1999). The distance was chosen according to the Bray-Curtis method. This analysis allowed evaluating the degree of association between the range of environmental variables and the taxonomic diversity of fungi found in the analyses in a multidimensional space. To conduct the db- RDA, the matrix of fungal taxa was standardized using the Hellinger method, while the matrix of environmental variables was standardized using the “standardize” method. A multicollinearity analysis involving the environmental analyzes performed was developed in order to verify and exclude possible vari- ables strongly correlated with the other predictor variables. This anal- ysis was performed using the variance inflation factor (VIF) method through the vifstep function of the Uncertainty Analysis for Species Distribution Models — USDM package (Naimi et al., 2014). To eval- uate if there was variation of fungal growth in hot and cold periods, two cluster analyses were made using spreadsheets (winter and sum- mer) standardized by the Hellinger method, later transformed into Euclidean distance matrices. Afterwards, hierarchical groupings were conducted using the method of weighted peer groups with arithmetic mean (UPGMA). This procedure was visualized as grouped heat maps using the pheatmap function of the homonymous package (Kolde et al., 2012). All statistical analyses were performed in R programming language (Ihaka and Gentleman, 1996; R Core Team, 2018). Results and Discussion The results of the physicochemical and biochemical analyses of the three different areas of use of the studied soils, native vegetation, Influence of different soil uses in the Pampa biome, southern Brazil, on fungal communities 185 RBCIAMB | v.58 | Jun 2023 | 182-191 - ISSN 2176-9478 pasture and Eucalyptus plantation, of the two periods analyzed (hot and cold), are presented in Table 1. The area with native vegetation showed higher humidity in the cold period than the other areas studied and periods analyzed. This same area also showed greater basal respi- ration, but in the hot period. Góes et  al. (2021), in their study of the edaphic fauna of the Pampa biome, also observed that the soil with the highest moisture content was native vegetation. The higher values of humidity in areas of native vegetation can be justified by the greater coverage of the soil in relation to the other areas, because in field or crop, the soil covers are lower and deficient, leaving it exposed to the incidence of solar radiation, thus facilitating water loss by evaporation. Araújo et al. (2020b) demonstrated in their study that areas with native vegetation cover had greater biomass and carbon stock capacity com- pared to anthropic areas or areas in the process of anthropogenic change. In addition, as the vegetation regeneration stage advances, there is an increase in the amount of carbon and biomass. Basal respiration, high- er in this area in the warm period compared to other areas, may also be related to greater soil cover, observed in places with native vegetation. According to Canei et  al. (2018), basal respiration is one of the most used microbiological indicators to evaluate the activity of the soil het- erotrophic microbiota and represents the CO2 produced by the mi- crobial biomass during the processes of decomposition and mineral- ization of soil organic matter. The same study (Canei et al., 2018) also found higher values of basal respiration in native forest and araucaria forest than in pastures of the Pampa biome. The pasture area showed higher pH (in the cold period) and higher microbial biomass (in the hot period) than the other areas. Eucalyp- tus plantation showed higher average microbial quotient (qMIC) in the hot period. The high pH in the soil indicates alkalization and can be a result of the addition of basic components such as limestone (liming), used in the preparation of the soil for pasture (Bernardi et  al., 2018). According to Novak et al. (2022), soil biomass is an important nutrient cycling parameter in ecosystems and represents the fraction of organ- ic matter that is most rapidly decomposed. In contrast to the present study, this author reported a greater amount of biomass in soil with native vegetation than in soil with agricultural cultivation. This is prob- ably because the forest is not stable, it is still under stress. The chemical analysis of the soil composition of the three types of stud- ied areas showed that the pasture presents a higher mean in the cold period compared to the hot period (Table 2). Phosphorus is found in inorganic, organic and microbial forms in soils and its dynamics can be controlled by a combination of chemical and biological properties. Phosphorus is highly limited in tropical soils, thus the renewal of organic P and the rapid recy- cling of P from litter are the main processes to provide this macronutrient to plants in natural ecosystems (Soltangheisi et  al., 2019). Groppo et  al. (2015) also reported higher amounts of phosphorus in agricultural soils, such as pastures, in relation to the amounts found in native vegetation soils. The cold period showed even more phosphorus and potassium than the hot period. This occurs due to the higher fertilization that occurs in this period, as a strategy to improve the quantity and quality of the pasture, affected by low temperatures and frost (Pazeto et al., 2015). In relation to potassium, the highest levels in the soil under pasture may occur due to the immobilization of this micronutrient in the biomass of the trees and the export through crops, mainly grain. In the pasture, the non-renewal of the soil and the addition of residues (vegetables and animals) provide higher concentration of K in the surface layer of the soil. The animals influence the redistribution of nutrients by consumption, through defoliation of pas- ture, and their return to the soil via excretion (Assis et al., 2019). The analysis of variance, Anova 1 criterion, showed no statistical difference when comparing the physicochemical, chemical and bio- chemical variables of the soil of the three areas studied (native vegeta- tion, Eucalyptus plantation and pasture) in both periods, hot and cold. Table 1 – Mean of the physicochemical and biochemical variables of the three collection points in the areas of Eucalyptus, native vegetation and pasture in the hot and cold periods*. *Arithmetic mean of the analyses of the physicochemical and biochemical variables of the three soil collection points in the areas of Eucalyptus, pasture and native vegetation in the hot and cold periods of the Pampa biome analyzed in this study. Variables Eucalyptus Native Pasture Cold Hot Cold Hot Cold Hot Humidity (%) 12.41 16.20 11.60 24.10 12.53 18.20 pH 5.44 5.60 5.78 5.41 6.59 7.35 Silt (%) 9.99 8.90 10.74 7.16 11.65 10.5 Clay (%) 39.24 25.71 24.43 24.25 35.54 18.68 Sand (%) 50.76 65.38 64.82 69.67 52.79 70.95 Nitrogen (g/Kg) 10.23 12.36 15.76 12.83 13.23 12.83 Microbial biomass (μg/g of C in the soil) 456.81 404.85 379.6 348.69 924.86 343.16 Basal respiration (μg CO2/g soil/hour) 0.63 0.40 0.74 0.48 0.60 0.72 Microbial quotient (%) 2.13 2.34 1.26 1.62 1.60 1.86 Stroher, A.L. et al. 186 RBCIAMB | v.58 | Jun 2023 | 182-191 - ISSN 2176-9478 Regarding the fungi found in the three areas studied, in the hot and cold periods (Table 3), it can be observed that 265 fungi were sampled, distributed in eight genera and one species. The hot period obtained a total of 206 fungi and the cold period a total of 59, that is, there was a reduction of approximately 71.35% (or 147 individuals) of the fungal community sampled in the cold period. In relation to the total of specimens sampled in each area, the pasture area (n = 134) showed to be richer in fungi, followed by native vegetation (n = 79) and Eucalyptus plantation (n = 52). When analyzing the species richness in relation to hot and cold periods, the highest richness was found in the pasture area in the warm period (n = 101), followed by the area with native vegetation in the warm period (n = 63) and the pasture area in the cold period (n = 33). The Eucalyptus plantation area in the hot period showed an n = 42, and the area with native veg- etation in the cold period showed an n = 16. The area with Eucalyptus plantation in the cold period was the one with the lowest richness, with an n = 10. Regarding fungal diversity, the pasture area presented eight taxa in total, one species and nine fungal genera. Of these, eight were found in the hot period and four in the cold period, demonstrating a 50% reduction in diversity in the cold period. The native vegetation area presented seven taxa in total, seven in the hot period and three in the cold period, showing a reduction of 58% in the cold period compared to the hot one. The area with Eucalyptus plantation showed six taxa in the hot period and three in the cold period, with a reduction of 50% of diversity in the cold period. The Shannon-Weaver diversity index ranged from 1.15 in the area with native vegetation in the cold peri- od to 1.54 in the area of Eucalyptus plantation in the warm period. Table 2 – Mean of chemical variables from soil analyses of the three areas studied in each type of plant formation, Eucalyptus, native and pasture of the Pampa biome*. *Arithmetic mean of the chemical variables of the three soil collection points in the areas of Eucalyptus, pasture and native vegetation in the hot and cold periods of the Pampa biome analyzed in this study. Variables Eucalyptus Native Pasture Cold Hot Cold Hot Cold Hot pH SMP 6.03 5.37 6.17 5.07 6.40 6.57 Phosphorus (mg/L) 3.53 6.93 4.33 18.30 54.70 64.97 Potassium (mg/L) 94.33 63.00 88.33 57.67 128.67 359.67 Organic matter (%) 3.40 3.10 4.77 3.23 3.27 3.27 Aluminum (cmolcL-1) 0.60 0.50 0.17 1.47 0.53 0.00 Calcium (cmolcL-1) 3.20 5.03 2.63 1.37 4.07 7.27 Magnesium (cmolcL-1) 0.90 1.40 1.03 0.50 1.67 2.63 H+Al (cmolcL-1) 4.47 9.13 3.87 13.40 1.67 2.33 CTC (cmolcL-1) Effective 4.90 7.07 4.07 3.50 8.13 10,80 pH 7.0 8.83 15.67 7.73 15.37 9.80 13.13 % Saturation CTC Al 15.67 7.30 4.27 44.50 0.00 0.00  Bases 48.87 41.87 49.73 12.77 83.13 82.00 K 2.73 1.00 2.80 1.00 3.90 6.97 Ca/Mg Ratio 3.37 3.77 2.57 2.70 2.50 2.77 Ca/K Ratio 12.53 31.50 14.30 8.67 14.57 8.00 Mg/K Ratio 3.63 8.53 5.33 3.10 5.83 2.87 (Ca+Mg)/K Ratio 16.17 40.03 19.63 11.77 20.40 10.87 Sum of bases (cmolcL-1) 4.30 6.53 3.90 2.03 8.13 10.80 Sulfur (mg/L) 6.43 18.87 6.83 19.57 6.57 9.47 Zinc (mg/L) 2.33 9.23 3.03 55.97 6.90 24.53 Copper (mg/L) 1.17 1.10 1.40 2.00 2.17 2.97 Boron (mg/L) 0.50 0.70 0.59 0.93 0.60 1.12 Manganese (mg/L) 22.67 68.00 11.00 35.67 2.67 22.33 Iron (%) 0.00 0.16 0.00 0.20 0.00 0.29 Sodium (mg/L) 0.00 7.00 0.00 5.33 0.00 15.67 Influence of different soil uses in the Pampa biome, southern Brazil, on fungal communities 187 RBCIAMB | v.58 | Jun 2023 | 182-191 - ISSN 2176-9478 The pasture area obtained an index of 1.34 and the native vegetation area of 1.17 (both for the hot period). The area with Eucalyptus plan- tation and the pasture area of the cold period obtained indexes of 1.49 and 1.29, respectively. The Shannon-Weaver diversity index considers equal weight between rare and abundant species and the lower the in- dex value, the lower the diversity of the sample (Furtado and Vieira, 2020); thus, the most diverse area was pasture in the hot period and the least diverse was the Eucalyptus area in the cold period. The mean of taxa found in the three studied areas ranged from 3.2 in the Eucalyptus plantation area to 8.8 in the pasture area, the mean of the native vegetation area being 8.0. The standard deviation was 4.28 in the Eucalyptus area, 15.85 in the area with native vegetation and 16.51 in the pasture area. The three most abundant taxa found in the total of the three ar- eas analyzed in this study were Aspergillus sp., Aspergillus niger e Fu- sarium sp. The genus Aspergillus stands out as an excellent producer of secondary metabolites of industrial and environmental interest. This genus is part of a group of non-pathogenic microorganisms capable of producing enzymes and has been widely researched. They are filamentous fungi that stand out for their ease of cultivation and secretion of enzymes directly in the production medium (Na- scimento et  al., 2014). Correa et  al. (2023), in their study with fungi, showed that most isolates of the genera Penicillium, Aspergillus and Trichoderma used the herbicide glyphosate as a source of nutrients, de- grading it and decreasing its concentration in the environment. A. niger is a species of Aspergillus sp. used in the development of an inoculant that promotes plant growth. This microorganism has the ability to solubilize mineral phosphates and is considered safe in food produc- tion (Araújo et al., 2020a). According to Nascimento et al. (2021), A. niger grows rapidly and sporulates well in common culture media. In addition, this microorganism does not present specificity for host plants, thus being advantageous in relation to symbiotic microbes, for which the produc- tion of inoculants can be complex. For Daniel Junior et  al. (2018), the genus Fusarium, the third most abundant taxon in this study, is one of the most cited genera in studies related toproduction of bioherbicides. This genus has herbicidal activity against different species of grasses. This study analyzed 35 environmental variables, but the variance inflation factor (VIF) showed which were correlated with each other. After model selection, only eight variables were maintained in the final db-RDA model, as shown in Table 4. The proportion of inertia (i.e. mean quadratic contingency coefficient) explained that the variability in the composition of fungi as a function of their relationship with the environmental variables of the soil was 63%, while 37% of the variabil- ity was not explained. The first two axes explained 51% (1º = 41.1%; 2º = 10.7%). The quality of the db-RDA model was relevant (R2 = 0.70) and significant (Anova, F[8.9] = 1.90, p-value = 0.02). Table 3 – Quantities of fungi found in areas of native vegetation, Eucalyptus plantation and pasture, in the hot and cold periods, of the Pampa biome*. *Species or genera of fungi, with their respective quantities, found in the three areas analyzed: pasture, native and Eucalyptus plantation, in the two periods: hot and cold in the Pampa biome. Areas Fungi Hot period Cold period Total area Eucalyptus Aspergillus sp. 4 8 52 Aspergillus niger 24 1 Fusarium sp. 3 1 Isaria sp. 1 0 Scedosporium sp. 1 0 Trichoderma sp. 9 0 Native Aspergillus sp. 39 12 79 Aspergillus niger 13 3 Fusarium sp. 4 1 Trichoderma sp. 4 0 Geotrichum sp. 1 0 Penicillium sp. 1 0 Scedosporium sp. 1 0 Pasture Aspergillus sp. 34 20 134 Aspergillus niger 29 8 Fusarium sp. 15 3 Geotrichum sp. 1 2 Isaria sp. 1 0 Penicillium sp. 3 0 Trichoderma sp. 17 0 Verticillium sp. 1 0 Total (hot and cold): 206 59 Table 4 – Variance inflation factor analysis displaying 12 variables retained and fit for the following narrow-order analyses#. #Variance inflation factor, of the 12 variables retained and suitable for restric- ted ordering analyses; *variables retained in the final db-RDA model. Environmental variables (soil) VIF 1. Silt 1.69 2. Clay* 2.02 3. (Ca + Mg)/ K Ratio* 2.40 4. Basal respiration* 2.74 5. Colony forming units (CFU) 2.79 6. Microbial quotient* 2.98 7. Total nitrogen* 3.33 8. Manganese* 3.34 9. Copper* 3.74 10. pH 3.80 11. Sulfur 3.82 12. Boron* 4.75 Stroher, A.L. et al. 188 RBCIAMB | v.58 | Jun 2023 | 182-191 - ISSN 2176-9478 When comparing the values of soil variables of the three areas studied, it can be seen that although the three areas analyzed, native vegetation, pasture and Eucalyptus plantation did not differ among themselves in the composition of the community of fungi, Table 4 shows the variation in soil components for each of them. Thus, qMIC, clay percentage, (Ca + Mg)/K ratio, manganese and copper seem to be higher in Eucalyptus plantation areas (Table 5). According to De Morais et al. (2021), the substitution of natural vegetation in the local biome for the production of forest crops can cause changes in quantita- tive and qualitative carbon stocks, in the microbial biomass of the soil and, consequently, in soil quality. The higher qMIC is related to the lower carbon accumulation by microorganisms in this location, often due to the lower availabili- ty of substrate. With the addition of quality organic matter or when there are no stress situations, there is an increase in microbial bio- mass and, consequently, an increase in qMIC (Gonçalves et al., 2019). For Oliveira et al. (2022), in their study with Eucalyptus crops, the pro- longed cultivation time of this plant caused increases in litter accumu- lation, organic matter and soil organic carbon. The soils with pasture showed a mean rate of basal respiration and boron content above the other two areas studied. The values of the basal respiration rate are directly related to the increase or reduction of C available in the soil. A higher basal respiration rate may mean the release of nutrients in the soil, since the decomposition of plant material may make nutrients available to plants (Quirino et al., 2020). Alves et  al. (2022), in their study, also obtained higher mean basal respiration in pastures. According to these authors, these areas pro- mote a high availability of organic matter and have dense root mass, favoring the formation of microbial biomass in the rhizosphere. Basal soil respiration is considered the main measure to evaluate microbial activity and consists of the total sum of all metabolic functions, of which CO2 is produced. Caumo et al. (2021), in their study with plant communities, found that the areas with pastures presented higher species richness and that the presence of dry material in the soil is higher in non-pastured ar- eas. The presence of herbivores is relevant in the recycling of vegetative material, changing the dynamics of nutrient cycling by accelerating the process. Finally, total nitrogen seems to be, on average, more represented in soils with native vegetation (Table 5). According to Dalal et al. (2021), in the last 70 years, there has been an increase in the deposition of var- ious forms of nitrogen in the soil, even in soil with native vegetation. According to redundancy analysis, it can be observed that the fungal community is affected distinctly by the composition of the soil characteristics (Table 6), regardless of the areas sampled, as previously shown by the Permanova. The genus Aspergillus sp. is more associated with higher amounts of manganese, boron and Ca+Mg/K ratio in soil (Figure 2 on the right), while taxa such as A. niger and Trichoderma sp. have a negative relation- ship with these variables. Thus, the latter will be absent or less frequent when these characteristics are predominant in the environment (Figure 2 on the left). According to Mohanty et al. (2017), in their study on fun- gus-assisted manganese bioleaching, Aspergillus sp. showed a high ability of tolerance to this micronutrient under various optimization conditions. Vera et al. (2021) found that the dose of B and the type of soil manage- ment have a significant effect on the structure of the fungal community, observing higher abundances of Aspergillus sp. Penicillium sp. and Con- larium sp. in soils with traditional agriculture and high levels of boron. It should be noted that other species of the genus Aspergillus may have a behavior quite different from A. niger, considering that both taxonomic entities were diametrically opposed to each other and thus responding to soil components differently. In con- trast, both A. niger and Trichoderma sp. appear to occur in great- er abundance in soil types where there is a higher concentration of clay and where basal respiration is more intense (Figure 2 left). Table 5 – Mean values of the soil variables kept in the final model of the db-RDA restricted ordering analysis by type of vegetation depending on the sampled area*. *Mean values with their respective standard deviations (between parentheses) of the soil variables kept in the final model of the analysis restricted db-RDA ordering by type of vegetation depending on the sampled area. Vegetation Eucalyptus Native Pasture Clay 32.4 (09.1) 24.3 (14.4) 27.1 (11.1) (Ca+Mg)/ K Ratio 28.1 (14.5) 15.7 (08.3) 15.6 (05.5) Basal respiration 0.51 (0.17) 0.61 (0.21) 0.66 (0.18) Microbial quotient 2.23 (1.29) 1.44 (0.99) 1.73 (0.98) Total nitrogen 11.3 (4.0) 14.3 (5.7) 13.0 (2.9) Manganese 45.3 (34.4) 23.3 (25.6) 12.5 (11.6) Copper 1.13 (0.22) 1.70 (0.51) 2.56 (0.85) Boron 0.60 (0.16) 0.75 (0.29) 0.86 (0.32) Table 6 – Scores for restricted variables with correlations between pattern of fungal composition and soil composition*. *Scores for the restricted variables according to the db-RDA model showing the cor- relations between the fungal composition pattern and the soil composition pattern. Environmental variables (soil) CAP1 CAP2 Clay -0.57 0.18 (Ca + Mg)/ K Ratio 0.40 0.06 Basal respiration -0.44 0.22 Microbial quotient -0.01 0.12 Total nitrogen -0.04 -0.15 Manganese 0.75 0.24 Copper 0.03 -0.57 Boron 0.45 -0.21 Influence of different soil uses in the Pampa biome, southern Brazil, on fungal communities 189 RBCIAMB | v.58 | Jun 2023 | 182-191 - ISSN 2176-9478 Figure 3 – (A) Heatmaps grouped based on matrices standardized by the Hellinger method of fungal diversity sampled in three areas of the Pampa biome during a warm (upper) and a cold (lower) period. (B) Procrustes analysis showing the agreement between the two heatmaps grouped in A*. *Cophenetic correlation coefficients: 0.81 (hot) and 0.99 (cold). In B, the empty points indicate the position (proximity or distance) of fungal taxa according to the similarity (grouping) observed during the warm period. Now, the ar- rowheads indicate the corresponding change (displacement) when the cold period is analyzed. The length of the residues indicated by the straight lines sho- ws how concordant (in this case, the absence thereof ) are both configurations (clusters) after the ideal Procrustes fit. The genus Trichoderma has a phytostimulating effect on plants, with direct and indirect impacts, improving its growth and productivity. This genus has also shown potential in the growth and productivi- ty of various crops (Sani et  al., 2020). Utomo et  al. (2016) demon- strated an association between Trichoderma sp. and higher levels of organic carbon and soil organic matter. Organic matter and organic carbon may be associated with increased basal respiration of the soil, explaining the correlation observed in the present study. The genus Fusarium showed a correlation with higher amounts of copper in the soil as opposed to the remaining community of fungi (Figure 2). Ragasa et al. (2021) also reported the presence of species of the genus Fusarium in soil with high concentrations of copper. Copper is known to be an essential micronutrient. However, high concentrations associated with agricultural waste are highly toxic to most organisms. Through redundancy analysis, it is possible to infer that the occur- rence of organisms such as Geotrichum sp., Verticillium sp., Penicillium sp., Scedosporium sp. and Isaria sp., when positioned near the origin (x and y axes equal to 0.0), is poorly explained by any of the soil variables. Regarding the periods studied, according to the clusters gen- erated, there is a change in the pattern formed in the hot pe- riod when compared to the cold period (Figure 3A, higher). For example, while A. Niger, Fusarium sp., Trichoderma sp. and Isaria sp. are grouped next to each other, suggesting a change of individuals com- parable along the areas sampled (Eucalyptus, native and pasture), Asper- gillus sp. aligns with Geotrichum sp., indicating a pattern of modification of individuals more analogous to each other than to the taxa previously mentioned (Figure 3A, top). In the cold period, A. Niger, Fusarium sp. and Isaria sp. have reduced abundance of individuals, but maintain the same pattern of changes along the areas along with Aspergillus sp., while Tricho- derma sp. modifies considerably, not presenting any individual in this pe- riod (Figure 3A, bottom). It should also be noted that all taxa analyzed in this study had a reduction in the cold period compared to the hot period, except for Aspergillus sp. in the area of Eucalyptus, with greater quantity in the cold period compared to the hot period. This is probably because this genus of fungus has numerous biological characteristics that allow its survival in regions that have extreme conditions (Verweij et al., 2016). The Procrustes analysis showed that there was no agreement be- tween the order generated between one period and another, suggesting that the pattern of diversity found in the hot period (point) will not be the same as the cold period, as indicated by the head of the arrow in Figure 3B (M2 = 0.82, correlation = 0.41, p-value = 0.52). The size of the residues (length of the arrows) in the Procrustes analysis indicates great modifications from one period to another, with the exception of Fusarium sp., which has a very corresponding proportion of change between each of the areas in both periods, as indicated by the smaller size of its residue in Figure 3B. Figure 2 – Distance-based redundancy analysis (Bray-Curtis) showing the correlation between the fungal community and soil characteristics (gradients) of three areas with distinct vegetation in the Pampa biome. (i) Each fungal taxon is represented by a centroid (weighted mean) where it is most likely to occur or is more abundant, surrounded by the most representa- tive sampling points (black) of its occurrence; (ii) The arrows (in red) point in the direction where the taxa were more abundant; (iii) The origin, direction, and size of the arrows indicate, respectively, the sign and correlation with the axes of db-RDA (importance for ordination), thus displaying their association with the variability in fungal community composition and how each organism responds (positive or negative relationship) to soil environmental variables; (iv) The poly- gons encompass the outermost sampling points of each area with native vege- tation, Eucalyptus, or pasture, while (v) The larger colored points within them show the centroid of each group. Genera such as Penicillium sp., Scedosporium sp., and Isaria sp. are located closer to the center of the graph, overlapping with the environmental variables of microbial quotient and total nitrogen. Stroher, A.L. et al. 190 RBCIAMB | v.58 | Jun 2023 | 182-191 - ISSN 2176-9478 Conclusion The three most abundant taxa found in the analyzed areas were Aspergillus sp., Aspergillus niger and Fusarium sp. Shannon’s diver- sity index demonstrated that the area with the greatest diversity of fungi is pasture in the hot period, and the least diverse is Eu- calyptus in the cold period. Of 35 environmental variables, eight showed correlation with the fungal composition in the studied areas. This study showed that the fungal community did not dif- fer in the areas studied, native vegetation, pasture and Eucalyptus plantation, but was affected by the soil composition characteristics in all areas analyzed. The genus Aspergillus sp. is more associated with higher amounts of manganese, boron and Ca+Mg/K ratio in soil, while A. niger and Trichoderma sp. have a negative relation- ship with these variables. Regarding the periods studied, all taxa had a reduction in the cold period compared to the hot period, except for Aspergillus sp., which demonstrated the opposite for the Eucalyptus plantation. It can be seen that the use of soil in the Pampa biome for planting monocultures of the Eucalyptus type or for the generation of pastures interferes with its characteristics and distinctly affects the fungal community. Contribution of authors: STROHER, A. L.: Conceptualization; Investigation; Visualization; Writing – original draft. MÜLLER, T.: Conceptualization; Data curation; Visualization; Writing – original draft; Writing – review & editing. HEIDRICH, D.: Conceptualization; Data curation; Formal Analysis; Investigation; Methodology; Supervision; Validation. MACIEL, M. 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