A higher altitude enclave of humid forest in the semi-arid of Brazil holds a diversity of conidial fungi on leaf-litter

ABSTRACT

Brejos de Altitude are enclaves of higher altitude humid forests in the semiarid lowlands of the North-eastern of Brazil. They present unique characteristics in terms of soil and air humidity, temperature, vegetation cover, and biodiversity. Due to these conditions, many cattle ranchers and farmers develop activities that have caused habitat loss and fragmentation of biodiversity. In this study, we aimed to describe the diversity of conidial fungi that occur in the leaf litter of the riparian vegetation in a Brejo de Altitude in Pernambuco, Brazil. Decomposing leaf material was collected from the forest floor in the dry and rainy periods of 2019, incubated in moist chambers and observed daily for fungal structures, for up to 45 days, under dissecting microscope and light microscope. Eighty-four taxa of fungi were identified, totaling 335 occurrences. The air and soil temperature, and precipitation showed an influence on the fungal community. Species richness was greater in the dry period and abundance was greater in the rainy period. The multivariate analyses revealed differences in the conidial fungi community between the dry and rainy periods. A high richness of leaf litter conidial fungal was uncovered in this area of humid forest surrounded by the semiarid vegetation of Caatinga.

Keywords:
Asexual Ascomycota; Atlantic Forest; taxonomy; diversity; ecology

Introduction

Tropical rainforests are found in Africa, Asia, and Central and South America. In Brazil, these forests are divided between the Amazon rainforest, considered the largest tropical forest in the world covering 40 % of South America (Müller 2020), and the Atlantic Forest that is the second-largest tropical forest in South America (Marques et al. 2021).

The Atlantic Forest includes varied ecosystems such as ombrophilous forests (dense, mixed, and open), seasonal semi-deciduous and seasonal deciduous forests, mangroves, coastal tablelands, associated altitude fields, and humid altitude forests called “Brejos de Altitude”. The latter are Atlantic Forest enclaves or islands surrounded by the semiarid vegetation of the Caatinga (Serviço Florestal Brasileiro 2010).

The Brejos present significant heterogeneity in the physical environment (Svenning 2001) [dry and wet, flat or hilly, wind-driven or wind-protected, hot and cold, sunny and shaded sites (Valencia et al. 2004; Russo et al. 2005)]. Therefore, a very diverse community of plants and animals has evolved in this area. Due to the privileged environmental conditions of the Brejos, many ranchers and farmers have been attracted to these regions for cattle breeding and cultivation of banana, coffee, manioc and other vegetables, for example. These activities have caused habitat fragmentation and biodiversity loss (Silva & Tabarelli 2000; de Medeiros & Cestaro 2020).

The importance of these islands of humid forest surrounded by semiarid vegetation is not limited to their biological richness and endemism, but it also includes what they can offer in terms of food, water, and other natural resources. Some Brejos regions have river springs and small streams that contribute to the maintenance of the humid forest characteristics and favor biological diversity. Where springs and streams are found, riparian forests connect ecological processes, performing extremely important functions in maintaining water quality and stability of margin soils. The riparian forest also regulates the exchange processes between terrestrial and aquatic systems, and allows circulation of animals and gene flow of species, besides being considered a preferred habitat for many species. However, riparian forests have been degraded in many areas, mainly due to the advanced agricultural practices along streams (Rodrigues & Nave 2001; Castro 2012).

Despite the poor fertility of the soil (Kaspari et al. 2008), the microbial community decomposing leaf litter is responsible for nutrient cycling and facilitating nutrients availability from the leaf litter which is the main source of organic matter (Costa et al. 2010; Stahl et al. 2013; Albuquerque et al. 2018). Fungi, especially conidial fungi, are capable of decomposing leaf litter. These fungi produce spores of asexual origin, called conidia, whose main function is dispersion that guarantees the survival of the species and colonization of fresh substrates (Seifert et al. 2011).

In addition, conidial fungi have an important role in promoting nutrient cycling in different terrestrial and aquatic habitats (Mueller et al. 2004; Cavalcanti & Milanez 2007; Seifert et al. 2011). When leaves fall to the ground, they are colonized by several species simultaneously or successively, which contribute to the degradation of various substrates and release of substances, thus enriching the soil (Castro et al. 2011; Kirk et al. 2013). Despite their importance, taxonomic studies on conidial fungi in leaf litter in Brazil are as yet insufficient, as very few research groups are dedicated to this group of fungi (Grandi & Silva 2006; Magalhães et al. 2011; Santa-Izabel et al. 2011; Monteiro et al. 2019) and only limited studies have been carried out in Brejos (Costa et al. 2016a; b; c; Santa-Izabel & Gusmão 2018; da Silva et al. 2019).

Therefore, the study of leaf litter colonizers in the Brejos is much needed and can aid the understanding of fungal diversity and community structure in the tropical forests during the dry and rainy periods, and obtaining a deeper knowledge on biotic and abiotic factors affecting community assemblage.

In this context, we addressed the following questions: (i) Are there differences in the composition and structure of the conidial fungal community on leaf litter between the dry and rainy periods in Brejos? (ii) What variables most influence changes in the fungal community in Brejos? The main aim of this study was to describe the diversity of conidial fungi associated with the leaf litter decomposition in the riparian vegetation of an Atlantic Forest formation known as Brejo de Altitude, Brazil. Consequently, we will contribute to the knowledge of these fungi in the semiarid region of Northeast Brazil and in the Neotropics.

Materials and methods

Study area

The Professor João Vasconcelos Sobrinho Municipal Natural Park (PJVS), 08°21'20.92''S and 36°1'42.98''W (entrance), is located in a region known as Serra dos Cavalos, an Integral Conservation Unit that includes two municipalities (Caruaru and Altinho) in the Agreste region of Pernambuco. With an area of 359 ha, it shelters an exuberant and diversified forest. Most of the park is covered by Dense Ombrophilous Montane Forest (Tavares et al. 2000) containing large trees, besides lianas, epiphytes and ferns distributed on the windward slope (Barros & Fonseca 1996).

Due to its rugged topography, with contour lines that vary from 800 to 950 m, a reasonably well defined drainage occurs, with two main water courses: the Chuchu and Capoeirão creeks (Braga et al. 2002). Within the park there are three large dams, Serra dos Cavalos, Guilherme de Azevedo and Jaime Nejaim, which serve as a strategic reserve for the region's public supply system, serving 387,000 inhabitants (Braga et al. 2002). The region of the park is located on the geological layer of the crystalline basement, with a small thickness of soils formed by processes of weathering (Braga et al. 2002; EMBRAPA 2006). In the park one can find variations of soil-Yellow Argissolos, and associated Red-Yellow Argissolos and Neossolos Litholithos, and Red-Yellow Argissolos (EMBRAPA 2001; 2006).

High temperatures in most of the year with intense heat strokes favor evaporation (Pinheiro-Filho 2019). Air and soil temperature were measured at the collection points with a digital thermometer, while accumulated precipitation data were provided by the Pernambuco water agency APAC (http://www.sirh.srh.pe.gov.br/apac/).

Sample characterization

Four collection expeditions of decomposing leaf material on the forest floor were conducted from May 2019 to November 2019 in PJVS. The six sampling points (Table 1) are located along the Chuchu stream, before it flows into the Guilherme de Azevedo reservoir, 4.5 m from the watercourse bank and about 100 m apart from each other. At each point, a frame (25 cm²) was randomly cast three times and the framed leaves were collected into plastic bags, taken to the laboratory and placed into three perforated plastic containers inside a tray, positioned at a 45° angle below the faucet and the running water falling in the tray but not directly on the leaves. This gentle washing for 30 minutes is to eliminate debris and nematodes (Castañeda-Ruiz et al. 2016). The leaves were next air dried on newspaper or paper towel for about 10 minutes and were cut with scissors into fragments of approximately 7 cm² to be placed in Petri dishes lined with a filter paper moist with sterile distilled water (moist chamber) for taxonomic analysis of fungi. Each moist chamber held 3 leaf fragments and six chambers were mounted for each sampling point. These plates were incubated in a styrofoam box that contained a 1 cm layer of water at the bottom, at room temperature. A few drops of glycerin were added to break the surface tension of the water. After 72 hours, the incubated material was observed with a stereomicroscope and light microscope, and the analysis continued for 45 days. Fungal structures were mounted on semi-permanent slides with 90 % lactic acid and permanent slides with polyvinyl alcohol in lactoglycerol (PVLG) for identification of the conidial fungi according to the literature such as Ellis (1971; 1976), Matsushima (1971; 1975; 1985; 1993), Seifert et al. (2011). The new species records were deposited in the Herbarium Pe. Camille Torrend - URM (University of Recife Mycology). Fungal structures were documented using a Nikon Eclipse Ni-U microscope with DIC optics and a Nikon DS-Fi2 digital camera.

Table 1
Geographic position of the sampling points at the Parque Natural Municipal Professor João Vasconcelos Sobrinho (Serra dos Cavalos), Pernambuco, Brazil.

Points (P)	Latitude (N)	Longitude (W)	Altitude (m)
P1	8° 21' 46"	36° 1' 53"	843.06
P2	8° 21' 48"	36° 1' 51"	817.96
P3	8° 21' 48"	36° 1' 43"	852.56
P4	8° 21' 49"	36° 1' 46"	851.84
P5	8° 21' 47"	36° 1' 48"	828.77
P6	8° 21' 51"	36° 1' 38"	830.21

A total of 144 plates (moist chambers) were analyzed, with three fragments per plate, six plates per collection point, six collection points in the area, and four expeditions, resulting in 432 leaf fragments.

Ecological indices for analyses of the fungal community

The frequency of occurrence of conidial fungi (F) was calculated according to the formula: F = n × 100/N, where n = number of samples in which a species was recorded, and N = total number of samples (144 moist chambers). The following frequency classes were established: F ≤ 10% = sporadic; 10 < F ≤ 30% = infrequent; 30 < F ≤ 70% = frequent; and F > 70% = very frequent (Dajoz, 1983).

For the constancy of the detected species, the following formula was applied: C= p.100/P, where: p = number of expeditions in which a fungal species was found and P = total number of expeditions (4). The taxa were divided according to the following constancy categories: C ≤ 25% accidental, 25% < C ≤ 50% accessory and C > 50% = constant (Dajoz 1983).

For Shannon-Wiener’s diversity index (H'), we used H’ = - ∑ pi (ln pi), where pi = ni/N; N = total number of individuals sampled; ni = number of individuals sampled from the taxonomic group; ln = neperian logarithm. Pielou's equitability (J) was calculated using the formula: J = H’/ H’_max, where H’_max is the maximum possible diversity that can be observed if all species of conidial fungi have equal abundance. H’_max = log S, where S = total number of species of conidial fungi sampled. Berger-Parker’s dominance was calculated using the formula: d = N_max / N_t where N_max is the number of occurrences of the most abundant species and Nt is the total number of occurrences in the sample. Shannon-Wiener's Diversity (H’), Pielou's equitability (J) and Berger-Parker’s dominance indices were calculated using the program PAST 3.18c (Hammer et al. 2013). The maximum species richness of conidial fungi in the sampling area was calculated using the Chao 1 (1st order) estimator (Santos 2003).

Statistical analyses

Pearson's correlation analysis was performed using R (R Development Core Team 2018) to identify whether there was correlation between the occurrence of fungi and the abiotic variables (precipitation, air and soil temperature) regarding the wet and dry season. The classification of the resulting r values was: r= 0.1-0.3 (weak correlation), r= 0.4-0.6 (moderate correlation) and r= 0.7-1 (strong correlation) (Dancey & Reidy 2006).

The conidial fungal species composition of the community was compared between the dry and rainy periods using the multivariate statistical method NMDS (Nonmetric Multidimensional Scaling), based on the Bray-Curtis dissimilarity matrix (Kruskal 1964). The one way ANOSIM test was used to verify dissimilarity of the groups formed in the NMDS (Clarke 1993).

The similarity index between sampling periods was calculated from binary data, using the Morisita-Horn’s coefficient and the dendrogram was constructed using the UPGMA grouping method and the SPSS Statistics software (version 22.0, International Business Machines Corp., Armonk, NY).

Principal Component Analysis - PCA (Turk & Pentland 1991) was applied to test whether the composition of the leaf litter conidial fungi community differs between sampling periods and if any of the abiotic variables interfere with this change using PAST 3.18c (Hammer et al. 2013).

Results

Air and soil temperature and precipitation

Four variables were used to test whether there were differences between the wet and dry seasons. The Shapiro-Wilk’s test confirmed the normal distribution of the data: occurrence of taxa (p = 0.429), pluviometric precipitation (p = 0.273), air temperature (p = 0.478) and soil temperature (p = 0.899). Therefore, parametric statistics were applied.

According to the results of the univariate analysis, the number of taxa was not influenced by environmental factors such as soil and air temperature or pluviometric precipitation (Figure 1). The temperature range for growth of most fungi is between 20 °C and 30 °C. During the sampling months, the soil temperature varied from 20 °C to 24.5 °C and the air temperature from 21 °C to 28 °C (Figure 1). Regarding the pluviometric precipitation, it was observed that the greater occurrence of fungi coincided with the greater precipitation (148 mm) in July, 2019. When the precipitation was lower (14.2 mm) in November, 2019, the occurrence of fungi decreased compared to the previous collection period (September, 2019), but it was not the lowest occurrence (Figure 1).

It was observed that sampling points 1, 2 and 3, closer to the dam, had denser vegetation and larger amounts of leaf litter, and the area was, in general, more humid. From sampling point 4 onwards, there was a decrease in the leaf litter on the ground, and the vegetation was drier in points 5 and 6 (closer to the local unpaved road).

Figure 1
Distribution of precipitation, temperature variation (air and soil) and occurrence of taxa between sampling periods in the Parque Natural Municipal Professor João Vasconcelos Sobrinho - Serra dos Cavalos, PE-Brazil.

Occurrence and richness of taxa

Eighty-four species were identified in 432 leaf fragments. These species belong to 68 genera of which 33 were incertae sedis, 32 families and six classes (Sordariomycetes, Dothideomycetes, Leotiomycetes, Eurotiomycetes, Orbiliomycetes and Tritirachiomycetes). Among these taxa, two are new species; three are new records to the Neotropics and two to South America (Table 2).

Table 2
Occurrence of conidial fungi, frequency and category of constancy in decomposing leaf litter detected in four sampling expeditions to the Parque Natural Municipal Professor João Vasconcelos Sobrinho-Serra dos Cavalos, PE-Brazil. *Ingoldian fungi; ** Aeroaquatic hyphomycetes; *** Coelomycetes; ● Sexual ascomycetes; 0 = No occurrence; □ New species; △ First record to the Neotropics; ◇ First record to South America. W1-W2 = collection wet periods and D1-D2 = collection dry periods.

FAMILY	TAXA	W1	W2	D1	D2	Freq.	Class of Freq.	Constancy %
Incertae sedis	Acremonium sp	0	0	0	1	0.7	sporadic	accidental
Incertae sedis	Acumispora verruculosa Heredia, R.F. Castañeda & R.M. Arias	0	0	1	0	0.7	sporadic	accidental
Cordycipitaceae	Akanthomyces lecanii (Zimm.) Spatafora, Kepler & B. Shrestha	0	0	0	2	1.4	sporadic	accidental
Pleosporaceae	Alternaria alternata (Fr.) Keissl	0	2	0	0	1.4	sporadic	accidental
Venturiaceae	Anungitopsis speciosa R.F. Castañeda & W.B. Kendr.	0	0	1	0	0.7	sporadic	accidental
Incertae sedis	Bactridium flavum Kunze	0	1	2	0	2.1	sporadic	accidental
Beltraniaceae	Beltrania querna Harkn.	0	4	4	4	8.3	sporadic	constant
Beltraniaceae	Beltrania rhombica Penz	13	5	0	5	16.0	infrequent	constant
Beltraniaceae	Beltraniella portoricensis (F. Stevens) Piroz. & S.D. Patil	4	3	0	7	9.7	sporadic	constant
Beltranieaceae	Beltraniopsis esenbeckiae Bat. & J.L. Bezerra	0	2	2	2	4.2	sporadic	constant
Nectriaceae	Calonectria ovata D. Victor & Crous	0	0	0	1	0.7	sporadic	accidental
Cancellidiaceae	**Cancellidium applanatum Tubaki	0	0	2	0	1.4	sporadic	accidental
Castanediellaceae	Castanediella cagnizarii (R.F. Castañeda & W.B. Kendr.) Crous, Hern.-Restr. & M.J. Wingf.	1	0	0	0	0.7	sporadic	accidental
Microascaceae	Cephalotrichum microsporum (Sacc.) P.M. Kirk	1	0	0	0	0.7	sporadic	accidental
Chaetomiaceae	Chaetomium sp	1	0	0	0	0.7	sporadic	accidental
Hamatocanthoscyphaceae	Chalara aurea (Corda) S. Hughes	2	0	0	0	1.4	sporadic	accidental
Xylariaceae	Circinotrichum flexuosum K.G. Karand., S.M. Kulk. & Patw	0	0	0	2	1.4	sporadic	accidental
Xylariaceae	Circinotrichum maculiforme Nees	0	0	0	3	2.1	sporadic	accidental
Xylariaceae	Circinotrichum olivaceum (Speg.) Piroz.	0	0	0	2	1.4	sporadic	accidental
Incertae sedis	Cladosporiella cercosporicola Deighton	0	0	0	2	1.4	sporadic	accidental
Cladosporiaceae	Cladosporium cladosporioides (Fresen.) G.A. de Vries	0	0	0	1	0.7	sporadic	accidental
Glomerellaceae	***Colletotrichum sp	0	0	0	1	0.7	sporadic	accidental
Cordycipitaceae	Cordyceps sp	1	0	0	0	0.7	sporadic	accidental
Chaetosphaeriaceae	Cryptophiale kakombensis Piroz.	0	1	0	2	2.1	sporadic	accessory
Nectriaceae	Cylindrocladium ellipticum Alfieri, C.P. Seym. & Sobers	0	0	2	0	1.4	sporadic	accidental
Orbiliaceae	Dactylella candida (Nees) de Hoog	0	0	1	0	0.7	sporadic	accidental
Torulaceae	Dendryphion comosum Wallr.	1	0	2	0	2.1	sporadic	accessory
Torulaceae	Dendryphion vinosum (Berk. & M.A. Curtis) S. Hughes	0	1	0	0	0.7	sporadic	accidental
Chaetosphaeriaceae	Dictyochaeta assamica (Agnihothr.) Aramb., Cabello & Mengasc.	3	0	5	0	5.6	sporadic	accessory
Chaetosphaeriaceae	Dictyochaeta fertilis (S. Hughes & W.B. Kendr.) Hol.-Jech.	0	1	0	0	0.7	sporadic	accidental
Chaetosphaeriaceae	Dictyochaeta triseptata (Matsush.) R.F. Castañeda	0	0	1	0	0.7	sporadic	accidental
Chaetosphaeriaceae	***Dinemasporium lanatum Nag Raj & R.F. Castañeda	2	0	0	0	1.4	sporadic	accidental
Incertae sedis	Ellisembia bawanglingensis S.C. Ren & X.G. Zhang	1	0	1	0	1.4	sporadic	accessory
Nectriaceae	Fusarium sp	0	0	1	0	0.7	sporadic	accidental
Incertae sedis	Guarroa acutispora (Matsush.) Heredia & R.F. Castañeda	0	0	1	0	0.7	sporadic	accidental
Incertae sedis	Gyrothrix verticiclada (Goid.) S. Hughes & Piroz.	0	3	0	0	2.1	sporadic	accidental
Xylariaceae	Hansfordia pulvinata (Berk. & M.A. Curtis) S. Hughes	0	0	0	4	2.8	sporadic	accidental
Chaetosphaeriaceae	△ Menisporopsis multisetulata C.K.M. Tsui, Goh, K.D. Hyde & Hodgkiss (URM 94402)	0	6	0	0	4.2	sporadic	accidental
Chaetosphaeriaceae	Menisporopsis theobromae S. Hughes	3	9	4	0	11.1	infrequent	constant
Chaetosphaeriaceae	Menisporopsis pirozynskii Varghese & V.G. Rao	0	0	3	0	2.1	sporadic	accidental
Magnaporthaceae	Mycoleptodiscus terrestris (Gerd.) Ostaz.	0	0	4	2	4.2	sporadic	accessory
Stachybotryaceae	Myrothecium inundatum Tode	0	5	0	0	3.5	sporadic	accidental
Stachybotryaceae	Myrothecium verrucaria (Alb. & Schwein.) Ditmar	0	0	0	3	2.1	sporadic	accidental
Ophioceraceae	● Ophioceras leptosporum (S.H. Iqbal) J. Walker	1	3	0	1	3.5	sporadic	constant
Incertae sedis	Paraceratocladium polysetosum R.F. Castañeda	1	0	0	0	0.7	sporadic	accidental
Stachybotryaceae	Paramyrothecium roridum (Tode) L. Lombard & Crous	1	3	4	0	5.6	sporadic	constant
Aspergillaceae	Penicillium sp	0	1	2	0	2.1	sporadic	accessory
Periconiaceae	Periconia byssoides Pers	0	0	3	0	2.1	sporadic	accidental
Mycosphaerellaceae	Periconiella ilicis P.M. Kirk	1	0	0	0	0.7	sporadic	accidental
Pestalotiopsidaceae	***Pestalotiopsis trachycarpicola Yan M. Zhang & K.D. Hyde	0	0	0	2	1.4	sporadic	accidental
Incertae sedis	Phaeodactylium biseptatum R.F. Castañeda, Iturr. & Rob. Fernández	0	0	0	2	1.4	sporadic	accidental
Incertae sedis	Physalidiella elegans (Luppi Mosca) Rulamort	0	0	1	2	2.1	sporadic	accessory
Incertae sedis	□ Pleurotheciopsis sp	1	0	1	2	2.8	sporadic	constant
Incertae sedis	Polyscytalum ciliatum J.A. Cooper	0	1	3	0	2.8	sporadic	accessory
Nectriaceae	Pseudonectria buxi (DC.) Seifert, Gräfenhan & Schroers	2	0	1	0	2.1	sporadic	accessory
Didymellaceae	Pseudopithomyces chartarum (Berk. & M.A. Curtis) Jun F. Li, Ariyaw. & K.D. Hyde	0	0	1	0	0.7	sporadic	accidental
Incertae sedis	Repetophragma fasciatum (R.F. Castañeda) R.F. Castañeda, Gusmão & Saikawa	4	8	8	7	18.8	infrequent	constant
Incertae sedis	Repetophragma filiferum (Piroz.) R.F. Castañeda, Gusmão & Heredia	2	0	0	0	1.4	sporadic	accidental
Herpotrichiellaceae	Rhinocladiella cristaspora Matsush.	2	0	2	0	2.8	sporadic	accessory
Cochlearomycetaceae	◇ ***Satchmopsis sacciformis R.F. Castañeda (URM 94403)	1	5	4	0	6.9	sporadic	constant
Sympoventuriaceae	Scolecobasidium humicola G.L. Barron & L.V. Busch	1	0	0	0	0.7	sporadic	accidental
Incertae sedis	Solosympodiella clavata Matsush.	0	0	0	1	0.7	sporadic	accidental
Wiesneriomycetaceae	Speiropsis pedatospora Tubaki	0	1	0	0	0.7	sporadic	accidental
Wiesneriomycetaceae	Speiropsis scopiformis Kuthub. & Nawawi	2	0	0	0	1.4	sporadic	accidental
Incertae sedis	◇ ● Stellosetifera malaysiana Matsush.(URM 94405)	0	1	3	0	2.8	sporadic	accessory
Pleosporaceae	Stemphylium botryosum Wallr.	0	0	3	0	2.1	sporadic	accidental
Incertae sedis	Subulispora procurvata Tubaki	0	1	0	0	0.7	sporadic	accidental
Tetraplosphaeriaceae	Tetraploa aristata Berk. & Broome	0	2	0	0	1.4	sporadic	accidental
Chaetosphaeriaceae	Thozetella cristata Piroz. & Hodges	0	0	2	5	4.9	sporadic	accessory
Chaetosphaeriaceae	Thozetella pinicola S.Y. Yeung, Jeewon & K.D. Hyde	0	6	1	0	4.9	sporadic	accessory
Chaetosphaeriaceae	△ Thozetella serrata Whitton, K.D. Hyde & McKenzie (URM 94404)	4	0	0	0	2.8	sporadic	accidental
Chaetosphaeriaceae	Thozetella submersa F.R. Barbosa & Gusmão	0	0	2	0	1.4	sporadic	accidental
Chaetosphaeriaceae	□ Thozetella sp	0	0	2	0	1.4	sporadic	accidental
Torulaceae	Torula herbarum (Pers.) Link	1	0	0	0	0.7	sporadic	accidental
Hypocreaceae	Trichoderma sp	0	0	3	0	2.1	sporadic	accidental
Incertae sedis	*Triscelophorus deficiens (Matsush.) Matsush.	0	0	0	1	0.7	sporadic	accidental
Tritirachiaceae	Tritirachium oryzae (Vincens) de Hoog	0	1	0	0	0.7	sporadic	accidental
Vermiculariopsiellaceae	Vermiculariopsiella immersa (Desm.) Bender	0	3	0	0	2.1	sporadic	accessory
Plectosphaerellaceae	Verticillium sp	1	2	0	0	2.1	sporadic	accessory
Cainiaceae	Vesiculozygosporium echinosporum Bunting & E.W. Mason	0	0	0	3	2.1	sporadic	accidental
Nectriaceae	Volutella ciliata (Alb. & Schwein.) Fr.	0	0	4	5	6.3	sporadic	accessory
Wiesneriomycetaceae	Wiesneriomyces laurinus (Tassi) P.M. Kirk	3	14	5	4	18.1	infrequent	constant
Incertae sedis	△ Yuccamyces purpureus Gour, Dyko & B. Sutton (URM 94401)	1	5	0	0	4.2	sporadic	accidental
Zygosporiaceae	Zygosporium oscheoides Mont.	0	0	0	2	1.4	sporadic	accidental
	OCCURRENCE	62	100	92	81	335
	RICHNESS	29	29	37	30

In four sampling expeditions, 335 occurrences were recorded. Repetophragma fasciatum, was the highest detected taxa (27 times), followed by Wiesneriomyces laurinus (26 times) and Beltrania rhombica (23 times). Regarding the class of frequency, there was a predominance of sporadic (95.23 %) and infrequent (4.76 %) taxa (Figure 2). Relating to the constancy of taxa, 68 % were accidental, 19 % accessory and 13 % constant (Figure 2).

Figure 2
Constancy and frequency of occurrence of taxa of conidial fungi in leaf litter undergoing decomposition in the Parque Natural Municipal Professor João Vasconcelos Sobrinho-Serra dos Cavalos, PE-Brazil.

Pearson's correlation analysis between the occurrence of conidial fungi, precipitation, air, and soil temperature resulted in moderate correlation between occurrence and precipitation, and strong negative correlation between occurrence and air or soil temperatures. As expected, air and soil temperatures had a strong positive correlation (Table 3).

Table 3
Pairwise Pearson’s correlation between fungal occurrence, precipitation, air, and soil temperatures in the Parque Natural Municipal Professor João Vasconcelos Sobrinho-Serra dos Cavalos, PE-Brazil, according to the sampling periods.

	Occur. of fungi	Precipitation	Air temperature	Soil temperature
Occur. of fungi	1
Precipitation	0.52	1
Air temperature	-0.73	-0.94	1
Soil temperature	-0.94	-0.75	0.87	1

• If r = 0, there is no relationship between the two variables. Values closer to 1 or -1 indicate a perfect correlation between the two variables.

Diversity indices for the leaf litter conidial fungi community

Based on the data of species richness of conidial fungi identified in the PJVS, a rarefaction curve was constructed using the Chao 1 index (1^st order), representing the estimate of maximum local richness of conidial fungi. The rarefaction curve of the observed species did not reach the asymptote, showing that there is still a tendency to increase the detected species richness if samplings of leaf litter conidial fungi in the region were to be continued. The rarefaction curve in this study estimated that the maximum species richness to be found is 101, and 84 species were found, therefore 83.1 % of the estimated taxa was uncovered (Figure 3).

Figure 3
Rarefaction curve of conidial fungi in decomposing leaf litter in the Parque Natural Municipal Professor João Vasconcelos Sobrinho-Serra dos Cavalos, PE-Brazil, and richness estimates using the nonparametric estimator Chao 1 (black line), SObs: observed richness (grey line).

The distribution of species detected in the sampling periods revealed greater richness in the 3^rd sampling (dry period), while abundance was greater in the 2^nd sampling (wet period) (Table 4). The diversity index was higher in the 3^rd sampling. The equitability was high in all sampling periods, with variation from 0.89 to 0.95 between the 1^st (wet period) and 3^rd sampling (dry period). The dominance was higher in the wet season (Table 4). In general, significant differences were found between the wet and dry seasons for the indices of diversity, equitability, and dominance; however, for richness there was no significant difference (Table 4).

Table 4
Ecological indices regarding the species of conidial fungi collected in the Parque Natural Municipal Professor João Vasconcelos Sobrinho-Serra dos Cavalos, PE-Brazil.

ECOLOGICAL INDICES	WET SEASON**		DRY SEASON**		Perm p (eq)
	W1 (May/2019)	W2 (Jul/2019)	D1 (Sep/2019)	D2 (Nov/2019)
Richness (R)	29	29	37	30	0,09
Occurrence (O)	62	100	92	81	0*
Shannon-Wiener (H')	3.02	3.05	3.43	3.22	0.002*
Equitability (J')	0.89	0.90	0.95	0.94	0.003*
Berger-Parker’s Dominance	0.07	0.06	0.03	0.04	0.002*

• Perm p(eq): probability of having equal diversities. If p(eq) is greater than 0.05, there is no significant difference. *Significant difference. **D and W = collection periods.

Changes in the structure of the leaf litter conidial fungi community between seasonal periods

Multidimensional scaling ordination of samples based on occurrence of conidial fungi species separated them by both dry and wet periods. This trend is confirmed when observing the result obtained by ANOSIM analysis, which revealed a significant difference between the communities in the dry and wet periods (R= 0.4954, p = 0.0053) (Figure 4). One cluster was formed between the communities detected in 1^st and 2^nd sampling (wet period), showing structuring according to sampling events and good separation between the dry and wet periods. General similarity between wet and dry seasons was ≅ 45 %; however, the community in 4^th sampling (dry period, D2) was less similar (≅ 35 %) (Figure 5). The principal component analysis (PCA), including frequency of occurrence of fungi, air and soil temperature, and rainfall, is shown in Figure 6. PC1 and PC2 explained 83.6 % of variance, separating the six points in the dry period (D1-D6) from the same six points in the wet period (W1-W6). Air and soil temperatures were the variables that most contributed to this separation.

Figure 4
Non-metric multidimensional scaling (NMDS) ordination plot illustrating the conidial fungi communities of decomposing leaf litter in six sampling points in the wet (WP1-WP6) and dry (DP1-DP6) periods in the Parque Natural Municipal Professor João Vasconcelos Sobrinho-Serra dos Cavalos, PE-Brazil. Stress = 0.18.

Figure 5
Similarity of the conidial fungi community associated with leaf litter in decomposition on the fores floor, over the dry and wet seasons in the Parque Natural Municipal Professor João Vasconcelos Sobrinho - Serra dos Cavalos. The dendrogram is an UPGMA Morisita-Horn analysis. Cophenetic correlation coefficient = 0.80. Sampling periods are indicated as D1-D2 (dry) e W1-W2 (wet).

Figure 6
Principal Components Analysis of the fungi community in six sampling points in the Parque Natural Municipal Professor João Vasconcelos Sobrinho-Serra dos Cavalos, PE-Brazil over the dry (DP1-DP6) and wet seasons (WP1-WP6).

Discussion

In this study, we observed that soil and air temperatures are within optimal levels for the development of fungi (Maia 1983) (Figure 1). In these ecosystems, temperatures do not vary greatly, and the water regime plays a key role in soil microbial dynamics (Lodge et al. 1994). Therefore, rainfall has apparently influenced the increase in the number of fungi in the decomposing leaves. Rainfall has an influence on leaf litter production because it can induce the fall of senescent leaves (Liu 2012). In addition, non-senescent leaves can also be shed due to heavy rainfall at some times of the year (Scheer 2009) and, consequently there will be an increase in colonization by the fungi and boost fungal richness (Swaty et al. 1998). The largest deposits of leaf litter in humid forests occur in the dry season, and that increases the intensity of leaf litter decomposition in the wet season (Delitti 1984; Barbosa & Faria 2006).

In this study, the Class Sordariomycetes (42) showed the greatest richness, followed by Dothideomycetes (12) (Table 2). Sordariomycetes is the second-largest class of the Ascomycota phylum (Kirk et al. 2008; Hyde et al. 2013) and has a cosmopolitan distribution (Zhang et al. 2006). These representatives are found in a variety of habitats, mostly terrestrial taxa and several freshwater taxa (Cai et al. 2002; Jones et al. 2015). Some species are pathogens and endophytes of various plants, others cause diseases in arthropods and mammals (Maharachchikumbura et al. 2015; Hyde et al. 2016). The majority of species are saprobes and are linked in nutrient cycling, and some species are fungicolous (Zhang et al. 2006; PeiGui et al. 2000).

Beltrania rhombica (Table 2) is considered cosmopolitan and commonly found associated with leaf litter in taxonomic studies, but also in diversity and succession studies of fungi in Brazil (Maia 1983; Castro et al. 2012; Magalhães et al. 2013), Japan (Milagres et al. 2018), India (Pirozynski & Patil 1970), Cuba (Delgado-Rodriguez et al. 2002), and United States (Heredia-Abarca 1994). Likewise, Wiesneriomyces laurinus has a cosmopolitan distribution and the taxon is reported in studies in Brazil (Gusmão & Grandi 1997; Silva & Grandi 2008), Australia (Paulus et al. 2007), Myanmar (Thaung 2008), and Canada (Pratibha et al. 2015), among others. Although Wiesneriomyces laurinus is collected in terrestrial environment, it also has a wide distribution in aquatic environment (Sridhar & Kaveriappa 1989; Rajashekhar & Kaveriappa 2000; 2003). Since W. laurinus produces sporodochium with pointed setae, these structures can become attached to submerged plant substrates (Goh & Hyde 1996); moreover, many terrestrial conidial fungi called immigrant fungi, can be found in association with submerged plant substrates (Park 1972), which may explain the wide occurrence of this fungus in association with aquatic environment as well. Repetophragma fasciatum has distribution restricted to neotropical region, mainly Central and South America, and was the taxon with the highest occurrence in this study. This species was found in studies of fungal diversity on decaying leaves of an unidentified plant (Castañeda-Ruiz et al. 2006; Santos et al. 2018).

The data on the frequency of occurrence of fungi (Figure 2) are in accordance with other studies carried out in Brazil, in which most of the fungi is sporadic and infrequent (Magalhães et al. 2011; Monteiro et al. 2019).The predominance of accidental species (Figure 2) was also verified in other studies of richness of conidial fungi that decompose leaf litter in the Atlantic Forest (Marques et al. 2008; Barbosa et al. 2009; Santana et al. 2017), and Brejos (Santa-Izabel & Gusmão 2018). The data in these studies show that the predominance of accidental taxa of conidial fungi leaf litter can be influenced by environmental factors such as humidity and temperature, and nutritional factors during decomposition. The constant taxa suffer less influence from these conditions (Table 3). In this study, small numbers of constant and frequent taxa were observed; a fact that reinforces the analyses of the authors mentioned above in tropical forests. The small number of constant species can be the result of several factors, such as large number of tree species per hectare making available numerous substrates in different periods (Santana et al. 2017). Also, the high percentage of sporadic species found in this study matches results from Atlantic Forest areas (Santana et al. 2017). Similarly, climate changes (Suseela & Tharayil 2018), the stage in which the substrate decomposes and trichomes (Parungao et al. 2002) in the leaves are related to the presence of sporadic species.

In tropical forests, where environmental conditions such as humidity and temperature are optimal for the development of microfungi (Ferreira & Chauvet 2011; Geraldes et al. 2012), changes in temperature can inhibit fungi activity, consequently, it promotes drastic changes in leaf litter decomposition (Bärlocher et al. 2013; Gonçalves et al. 2013). Moreover, other conditions such as the preference for a specific vegetal substrate is related to nutritional factors and secondary metabolites offered by the substrates (Rambelli et al. 2004).

The data in this study show that the rarefaction curve continues to rise (Figure 3), indicating that the number of samples may not have been sufficient to adequately characterize the hyphomycetes community in the leaf litter of the investigated area. Due to the increasing number of fungi at each sampling, scientists have been encouraged to use various approaches to estimate species richness, such as accumulation curves, parametric and non-parametric estimators to describe mycological communities (Unterseher et al. 2005; Lindner et al. 2006). Studies of microfungi in humid forests have achieved lower (Costa & Gusmão 2015) or similar (Unterseher et al. 2008) coverages than the found in this study using non-parametric richness estimators. Although the data showed that the curve did not reach the asymptote, it is considered a good sampling effort. It is very difficult to observe the stabilization of the curve, especially in tropical regions, due to microbiota instability revealed as new species are added to the list every time a new sample is collected (Colwell & Coddington 1994; Costa & Gusmão 2015; Costa et al. 2010; Ferreira et al. 2020).

The analysis of the diversity indices between the wet and dry periods showed significant variation (Table 4); however, species richness did not differ significantly. The availability of water or nutrients, besides plant heterogeneity and other factors may have influenced this result, so that seasonal changes have not affected the number of species occurring in the leaf litter. Plant heterogeneity is greatest in tropical forests (Wright 2002). A higher diversity of plant species found at a site may be a consequence of considerable environmental heterogeneity, as observed in this study and by Heredia-Abarca (1994).

There was no significant variation of diversity among sampling points, although occurrence in point 1 was significantly higher. This fact can be explained by some peculiar features of each point: points 1, 2 and 3 had larger amount of leaf litter and the area was more humid. From point 4 onwards, there was a decrease in the leaf litter, and the vegetation was drier in points 5 and 6. Other factors such as plant composition may also have contributed to the taxa variations between sampling points. Environment heterogeneity aggregates a series of parameters such as physical and chemical features, humidity, temperature, seasonality, decomposition stages of the leaf litter, wind, luminosity, and others that may have influenced the richness of taxa (Takyu et al. 2002).

The number of taxa in the dry period was higher than in the wet period in this study, in agreement with the results presented by Kodsueb & Lumyong (2019). Few studies suggest seasonal changes as a factor that influences the conidial fungi community in tropical forests (Lodge et al. 2004; Nikolcheva & Bärlocher 2005; Costa & Gusmão 2015). In contrast, many studies consider the seasonal factor as active in shaping the community of conidial fungi in temperate regions, as there are more significant changes in temperature, humidity, and rainfall (Gessner 1977; Kuter 1986; Thongkantha et al. 2008). Despite these reports, it is not possible to state that seasonality can affect the community (Kodsueb et al. 2008) because other abiotic factors (humidity, nutrient availability) can also influence the composition and structure of conidial fungi communities (Polishook et al. 1996; Ormeño et al. 2006; Paulus et al. 2007; Allegrucci et al. 2014).

The nMDS and ANOSIM analyses showed separation of the fungal communities between dry and wet periods in the 1-2 axis (Figure 4). Similar results were also found by Costa & Gusmão (2015). Their ANOSIM analysis indicated a significant difference in community of fungi between seasons (R = 0.8, P = 0.0004), and the nMDS analysis revealed a strong separation between samples collected during the wet and dry periods.

The hierarchical clustering analysis using UPGMA showed a low similarity (Figure 5) between the collection periods (wet and dry) of conidial fungi. The conidial fungi that colonize mixed leaf litter or several substrates (leaves, branches, bark, and petioles) can present low similarity between sampling points of the same collection area. This is due to differences in the leaf litter constituents such as cellulose, lignin, secondary metabolites and other components (Voříšková & Baldrian 2013) that are related to different plant species and environment characteristics.

For the variables analyzed in this study, there is a structure in the fungal community in the two (seasonal) sampling periods (Figure 6). The rainfall variable separated the samples from the wet period and the air and soil temperature variables separated the samples corresponding to the dry period along the x axis. Prihatini et al. (2015) found no correlation between fungal communities and temperature using a PCA; however, these authors consider that rainfall is a significant environmental variable influencing fungal community. Bärlocher (1992) reported that in some forests the leaves accumulate in the soil until the beginning of the rainy season, ensuring the development of fungi. This fact may also explain the unpredictable behavior of the fungal community in tropical forests and, in addition, clarify the difference in the species composition for these fungi. The structural complexity in forests may create more microhabitats and microclimates for fungi, providing more resources and surfaces to be exploited (Lodge & Cantrell 1995).

This study of the conidial fungi community in an area that corresponds to about 1 % of the preserved area (359 ha) in the park revealed high richness of taxa. We contributed to the knowledge of the diversity of conidial fungi associated with leaf litter in the riparian zone of a humid forest formation inserted in a semi-arid region, adding new registers to the Northeast Brazil, South America and the Neotropics. The data indicates that there is still a great diversity to be uncovered in this park, and one can predict that the same is true to other areas in the semi-arid of the Northeast.

We confirmed the differences between dry and wet periods, with temperature variation and rainfall favoring substrate colonization by conidial fungi in a tropical forest, and rainfall influencing frequency of occurrence of the conidial fungi. However, even though univariate and multivariate analysis showed separation of the community between dry and wet seasons, it is not possible to affirm that the abiotic factors analyzed in this work are the only ones to have influence over this fungi community. Therefore, it is important to increase the number of variables analyzed in the studies to better understand how these influence the community of conidial fungi in humid forests and other ecosystems.

Acknowledgements

The authors are grateful to the Fundação de Amparo a Ciência e Tecnologia do Estado de Pernambuco (FACEPE) for financial support (process BFP-0128-2.03/18), the Department of Mycology at Universidade Federal de Pernambuco (UFPE), for the use of facilities and the Parque Natural Municipal Professor João Vasconcelos Sobrinho (PJVS) for allowing the sampling expeditions, especially the manager Moisés Alves, the biologist Raul Alves, the former manager João Domingos, and the eco-guides (Aristo and João).

References

• Albuquerque AS, Freire FJ, Barbosa MD, Marangon LC, Feliciano ALP. 2018. Efficiency of biological utilization of micronutrients by forests species in hypoxerophytic Caatinga. Floresta e Ambiente 25: e20170925
• Allegrucci N, Bucsinszkya AM, Arturi M, Cabello MN. 2014. Communities of anamorphic fungi on green leaves and leaf litter of native forests of Scutia buxifolia and Celtis tala: Composition, diversity, seasonality and substrate specificity. Revista Iberoamericana de Micología 32: 71-78.
• Barbosa FR, Maia LC, Gusmão LFP. 2009. Fungos conidiais associados ao folhedo de Clusia melchiorii Gleason e C. nemorosa G. Mey. (Clusiaceae) em fragmento de Mata Atlântica, BA, Brasil. Acta Botanica Brasilica 23: 79-84.
• Barbosa JHC, Faria SM. 2006. Aporte de serapilheira ao solo em estágios sucessionais florestais na reserva biológica de Poço das Antas, RJ, Brasil. Rodriguésia 57: 461-476.
• Bärlocher F, Kebede YK, Gonçalves AL, Canhoto C. 2013. Incubation temperature and substrate quality modulate sporulation by aquatic hyphomycetes. Microbial Ecology 66: 30-39.
• Bärlocher F. 1992. Recent developments in stream ecology and their relevance to aquatic mycology. In: Bärlocher F. (ed.) The ecology of aquatic Hyphomycetes. Berlin, Springer. p. 16-32.
• Barros ICL, Fonseca ER. 1996. Lycopodiaceae Myrbel de Brejo dos Cavalos-Caruaru-Pernambuco, Broteria. Boletim da Sociedade Broteriana 67: 263-270.
• Braga RAP, Cabral JSP, Montenegro SMGL, Perrier-Júnior GS. 2002. Conservação dos recursos hídricos em brejos de altitude: o caso de Brejo dos Cavalos, Caruaru, PE. Revista Brasileira de Engenharia Agrícola e Ambiental 6: 539-546.
• Cai L, Tsui CKM, Zhang KQ, Hyde KD. 2002. Aquatic fungi from Lake Fuxian, Yunnan, China. Fungal Diversity 9: 57-70.
• Castañeda-Ruiz RF, Gusmão LFP, Heredia-Abarca G, Saikawa M. 2006. Some hyphomycetes from Brazil. Two new species of Brachydesmiella, two new combinations for Repetophragma, and new records. Mycotaxon 95: 261-270.
• Castañeda-Ruiz RF, Heredia G, Gusmão LFP, Li DW. 2016. Fungal diversity of Central and South America. In: Li DW. (ed) Biology of Microfungi. Berlin, Springer . p. 197-217.
• Castro D. 2012. Práticas para restauração da mata ciliar. Porto Alegre: Catarse Coletivo de Comunicação.
• Castro NEA, Silva MLN, Freitas DAF, Carvalo GJ, Marques RM, Gontijo-Neto GF. 2011. Plantas de cobertura no controle da erosão hídrica sob chuvas naturais. Bioscience Journal 27: 775-785.
• Castro CC, Gutiérrez AH, Sotão HMP. 2012. Fungos conidiais em Euterpe oleracea Mart. (açaizeiro) na Ilha do Combu, Pará-Brasil. Acta Botanica Brasilica 26: 761-771.
• Cavalcanti MS, Milanez AI. 2007. Hyphomycetes from water and soil at the Dois Irmãos Forest Reserve, Recife, Pernambuco State, Brazil. Acta Botanica Brasilica 21: 857-862.
• Clarke KR. 1993. Non-parametric multivariate analyses of changes in community structure. Australian Journal of Ecology 18: 117-143.
• Colwell RK, Coddington JA. 1994. Estimating terrestrial biodiversity through extrapolation. Philosophical Transactions Biological Sciences 345: 101-118.
• Costa CCA, Camacho RGV, Macedo ID, Silva PCM. 2010. Análise comparativa da produção de serrapilheira em fragmentos arbóreos e arbustivos em área de caatinga na Flona de Açu-RN. Revista Árvore 34: 259-265.
• Costa LA, Gusmão LFP. 2015. Characterization saprobic fungi on leaf litter of two species of trees in the Atlantic Forest, Brazil. Brazilian Journal of Microbiology 46: 1027-1035.
• Costa P, Barbosa MA, Araújo MAG, Malosso E, Castañeda-Ruiz RF. 2016a. Phaeodactylium cymbisporum sp. nov. from the Brazilian Atlantic Forest. Mycotaxon 131: 435-438.
• Costa P, Barbosa MA, Araújo MAG, Malosso E, Castañeda-Ruiz RF. 2016b. Stachybotryna longispiralis sp. nov. from the Brazilian Atlantic Forest. Mycotaxon 131: 429-433.
• Costa P, Barbosa MA, Malosso E, Castañeda-Ruiz RF. 2016c. Anaverticicladus uncinatus gen. & sp. nov. from decaying leaves from Brazil. Mycotaxon 131: 687-691.
• Dajoz R. 1983. Ecologia geral. Petrópolis, Vozes.
• Da Silva GVR, Castañeda-Ruiz RF, Malosso E. 2019. Comparison of aquatic hyphomycetes communities between lotic and lentic environments in the Atlantic rain forest of Pernambuco, Northeast Brazil. Fungal Biology 123: 660-668.
• Dancey CP, Reidy J. 2006. Análise de correlação: o r de Pearson. In: Dancey CP, Reidy J. (eds.) Estatística sem matemática para psicologia. Porto Alegre, Artemed.
• De Medeiros JF, Cestaro LA. 2020. As diferentes abordagens utilizadas para definir Brejos de Altitude, áreas de exceção do Nordeste Brasileiro. Sociedade e Território 31: 97-119.
• Delgado-Rodriguez G, Mena-Portales J, Calduch M, Decock C. 2002. Hyphomycetes (hongos mitosporicos) del area protegida mil cumbres, Cuba Occidental. Cryptogamie, Mycologie 23: 277-293.
• Delitti WBC. 1984. Aspectos comparativos da ciclagem de nutrientes minerais na mata ciliar, no campo cerrado e na floresta implantada de Pinus elliottii Engelm var elliottii PhD Thesis. Universidade de São Paulo, Brazil.
• Ellis MB. 1971. Dematiaceous Hyphomycetes. London, Common wealth Mycological Institute.
• Ellis MB. 1976. More Dematiaceous Hyphomycetes. London, Common wealth Mycological Institute .
• EMBRAPA SOLOS. 2006. Sistema Brasileiro de Classificação de Solos. 2nd. edn. Rio de Janeiro, Embrapa.
• EMBRAPA SOLOS. 2001. ZAPE Digital. Zoneamento Agroecológico do Estado de Pernambuco. Recife, Embrapa Solos.
• Ferreira MC, De Assis JCS, Rosa LH. 2020. Diversity of endophytic fungi associated with Carapichea ipecacuanha from a native fragment of the Atlantic Rain Forest, South African. Journal of Botany 134: 225-229.
• Ferreira V, Chauvet E. 2011. Synergistic effects of water temperature and dissolved nutrients on litter decomposition and associated fungi. Global Change Biology 17: 551-564.
• Geraldes P, Pascoal C, Cássio F. 2012. Effects of increased temperature and aquatic fungal diversity on litter decomposition. Fungal Ecology 6: 734-740.
• Gessner RV. 1977. Seasonal occurrence and distribution of fungi associated with Spartina alterniflora from a Rhode Island estuary, Mycologia 69: 477-491.
• Goh TK, Hyde KD. 1996. Biodiversity of freshwater fungi. Journal of Industrial Microbiology & Biotechnology 17: 328-345.
• Gonçalves AL, Graça MAS, Canhoto C. 2013. The effect of temperature on leaf decomposition and diversity of associated aquatic hyphomycetes depends on the substrate. Fungal Ecology 6: 546-553.
• Grandi RAP, Silva TV. 2006. Fungos Anamorfos decompositores do folhedo de Caesalpinia echinata Lam. Revista Brasileira de Botânica 29: 275-287.
• Gusmão LFP, Grandi RAP. 1997. Hyphomycetes com conidioma dos tipos esporodóquio e sinema associados a folhas de Cedrela fissilis (Meliaceae), em Maringá, PR, Brasil. Acta Botanica Brasilica 11: 123-134.
• Hammer Ø, Harper DAT, Ryan PD. 2013. PAST: Paleontological statistics software package for education and data analysis. Palaeontologia Electronica 4: 1-9.
• Heredia-Abarca G. 1994. Hifomicetes dematiaceos en bosque mesofilo de montana. Registros nuevos para Mexico. Acta Botánica Mexicana 27: 15-32.
• Hyde KD, Udayanga D, Manamgoda DS et al 2013. Incorporating molecular data in fungal systematics: a guide for aspiring researchers. Current Research in Environmental & Applied Mycology 3: 1-32.
• Hyde KD, Hongsanan S, Jeewon R et al 2016. Fungal diversity notes 367-491: taxonomic and phylogenetic contributions to fungal taxa. Fungal Diversity 80: 1-270.
• Jones EBG, Suetrong S, Sakayaroj J, Bankali AH, Abdel-Wahab MA, Boekhout T, Pang KL. 2015. Classification of marine Ascomycota, Basidiomycota, Blastocladiomycota and Chytridiomycota. Fungal Diversity 73: 1-72.
• Kaspari M, Garcia MN, Harms KE, Santana M, Wright SJ, Yavitt JB. 2008. Multiple nutrients limit litterfall and decomposition in a tropical forest. Ecology Letters 11: 35-43.
• Kirk P, Cannon PF, Minter DW, Stalpers JA. 2008. Ainsworth & Bisby’s Dictionary of the Fungi. Wallingford, CAB International.
• Kirk PM, Stalpers JA, Braun U et al 2013. A without-prejudice list of generic names of fungi for protection under the International Code of Nomenclature for algae, fungi and plants. IMA Fungus 4: 381-443.
• Kodsueb R, Lumyong S. 2019. Diversity of Saprobic Fungi on Magnolia garrettii: Do Collecting Sites and Seasons Affect the Fungal Community? Sains Malaysiana 48: 2437-2449.
• Kodsueb R, McKenzie EHC, Lumyong S, Hyde KD. 2008. Fungal succession on woody litter of Magnolia liliifera (Magnoliaceae). Fungal Diversity 30: 55-72.
• Kuter GA. 1986. Microfungal populations associated with the decomposition of sugar maple leaf of litter. Mycologia 78: 114-126.
• Kruskal JB. 1964. Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika 29: 1-27.
• Lindner DL, Burdsall Jr HH, Stanosz GR. 2006. Species diversity of polyporoid and corticioid fungi in northern hardwood forests with differing management histories. Mycologia 98: 195-217.
• Liu L. 2012. Patterns of litterfall and nutrient return at different altitudes in evergreen hardwood forests of Central Taiwan. Annals of Forest Science 69: 877-886.
• Lodge DJ, Ammirati J, O’Dell TE, Mueller GM. 2004. Collecting and describing macrofungi. In: Mueller GM, Bills GF, Foster MS. (eds.). New Biodiversity of Fungi: Inventory and Monitoring Methods. New York, Academic Press. p. 123-168.
• Lodge DJ, Cantrell S. 1995. Fungal communities in wet tropical forests: variation in time and space. Canadian Journal of Botany 73: 1391-1398.
• Lodge DJ, McDowell WH, McSwiney CP. 1994. The importance of nutrient pulses in tropical forests. Trends in Ecology & Evolution 9: 384-387.
• Magalhães DMA, Luz EDMN, Magalhães AF, Santos MVO, Bezerra JL. 2013. Fungos conidiais em plantas endêmicas da Mata Atlântica: novos registros para a Bahia. Agrotrópica 25: 109-116.
• Magalhães DMA, Newman EDM, Magalhães AF, Santos-Filho LP, Loguercio LL, Bezerra JL. 2011. Riqueza de fungos anamorfos na serapilheira de Manilkara maxima, Parinari alvimii e Harleyodendro nunifoliolatum na Mata Atlântica do Sul da Bahia. Acta Botanica Brasilica 25: 899-907.
• Maia LC. 1983. Sucessão de fungos em folhedo de floresta tropical úmida. MSc Thesis. Recife, Editora da UFPE.
• Maharachchikumbura SSN, Hyde KD, Jones EBG et al 2015. Towards a natural classification and backbone tree for Sordariomycetes. Fungal Diversity 72: 199-301.
• Marques MCM, Trindade W, Bohn A, Grelle CEV. 2021. The Atlantic Forest: an introduction to the megadiverse forest of Southern America. In: Marques MCM, Grelle CEV. (eds.). The Atlantic Forest: history, biodiversity, threats and opportunities of the megadiverse forest. Switzerland, Springer.
• Marques MFO, Gusmão LF, Maia LC. 2008. Riqueza de espécies de fungos conidiais em duas áreas de Mata Atlântica no Morro da Pioneira, Serra da Jibóia, BA, Brasil. Acta Botanica Brasilica 22: 954-961.
• Matsushima T. 1971. Microfungi of the Solomon Islands and Papua-New Guinea. Kobe, Published by the author.
• Matsushima T. 1975. Icones Microfungorum a Matsushima Lectorum. Kobe, Published by the author .
• Matsushima T. 1985. Matsushima Mycological Memoirs n. 4. Kobe, Published by the author .
• Matsushima T. 1993. Matsushima Mycological Memoirs n. 7. Kobe, Published by the author .
• Milagres CA, Azevedo DMQ, Pereira OL, Furtado GQ. 2018. Epitypification, characterization and phylogenetic positioning of Pseudobeltrania cedrelae, the causal agent of Pseudobeltrania spot on Cedrela fissilis Forest Pathology 48: e12434.
• Monteiro JS, Sarmento PSM, Sotão HMP. 2019. Saprobic conidial fungi associated with palm leaf litter in eastern Amazon, Brazil. Anais da Academia Brasileira de Ciências 91: e20180545.
• Mueller GM, Bills GF, Foster MS. (eds.). 2004. Biodiversity of fungi: inventory and monitoring methods. Amsterdam, Elsevier Academic Press.
• Müller C. 2020. Brazil and the Amazon Rainforest - Deforestation, Biodiversity and Cooperation with the EU and International Forums. Luxembourg, European Parliament.
• Nikolcheva LG, Bärlocher F. 2005. Seasonal and substrate preferences of fungi colonizing leaves in streams: traditional versus molecular evidence. Environmental Microbiology 7: 270-280.
• Ormenõ E, Baldya V, Ballinia C, Larchevêque M, Périssol C, Fernandez C. 2006. Effects of environmental factors and leaf chemistry on leaf litter colonization by fungi in a Mediterranean shrubland. Pedobiologia 50: 1-10.
• Parungao MM, Fryar SC, Hyde KD. 2002. Diversity of fungi on rainforest litter in North Queensland, Australia. Biodiversity and Conservation 11: 1185-1194.
• Park D. 1972. On the ecology of heterotrofic micro-organisms in freshwater. Transactions of the British Mycological Society 58: 291-299.
• Paulus BC, Gadek P, Hyde K. 2007. Successional Patterns of Microfungi in Fallen Leaves of Ficus pleurocarpa (Moraceae) in an Australian Tropical Rain Forest. Biotropica 38: 42-51.
• PeiGui L, DoiY X, Hua W, QingBin W. 2000. The Hypocreaceae of China III. Some fungicolous species of the genusHypocrea Mycosystema 19: 317-327.
• Pinheiro-Filho JD. 2019. Da Serra dos Cavalos ao Vale do Ipojuca (Caruaru/PE): águas e história ambiental no semiárido brasileiro. Halac 9: 237-262.
• Pirozynski KA, Patil SD. 1970. Some setose Hyphomycetes of leaf litter in south India. Canadian Journal of Botany 48: 567-581.
• Polishook JD, Bills GF, Lodge DJ. 1996. Microfungi from decaying leaves of two rain forest trees in Puerto Rico. Journal of Industrial Microbiology 17: 284-294.
• Pratibha J, Nguyen HDT, Mel’nik VA, Bhat DJ, White GP, Seifert KA. 2015. Lectotypification, epitypification, and molecular phylogeny of the synnematous hyphomycete Pseudogliophragma indicum, the second genus in the Wiesneriomycetaceae. Mycoscience 56: 387-395.
• Prihatini I, Glen M, Wardlaw TJ, Ratkowsky DA, Mohammed CL. 2015. Needle fungi in young Tasmanian Pinus radiata plantations in relation to elevation and rainfall. New Zealand Journal of Forestry Science 45: 25.
• Rajashekhar M, Kaveriappa KM. 2000. Effects of temperature and light on growth and sporulation of aquatic hyphomycetes. Hydrobiologia 441: 149-153.
• Rajashekhar M, Kaveriappa KM. 2003. Diversity of aquatic hyphomycetes in the aquatic ecosystems of the Western Ghats of India. Hydrobiologia 501: 167-177.
• Rambelli A, Mulas B, Pasqualetti M. 2004. Comparative studies on microfungi in tropical ecosystems in Ivory Coast forest litter: behaviour on different substrata. Mycological Research 108: 325-336.
• R Development Core Team. 2018. R: A Language and Environment for Statistical Computing. Vienna, R Foundation for Statistical Computing.
• Rodrigues RR, Nave A. 2001. Heterogeneidade florística das matas ciliares. In: Rodrigues RR, Leitão-Filho HF. (eds.). Matas ciliares: conservação e recuperação. São Paulo, EDUSP- FAPESP. p. 45-71
• Russo D, Cistrone L, Jones G. 2005. Spatial and temporal patterns of roost use by tree-dwelling barbastelle bats,Barbastella barbastellus Ecography 28: 769-776.
• Santa-Izabel TS, Gusmão LFP. 2018. Richness and diversity of conidial fungi associated with plant debris in three enclaves of Atlantic Forest in the Caatinga biome of Brazil. Plant Ecology and Evolution 151: 35-47.
• Santa-Izabel TS, Santos DS, Almeida DAC, Gusmão LFP. 2011. Fungos conidiais do bioma Caatinga II. Novos registros para o continente americano, Neotrópico, América do Sul e Brasil. Rodriguésia 62: 229-240.
• Santana MV, Andrade JP, Monteiro JS, Gusmão LFP, Bezerra JL. 2017. Microfungos associados à serapilheira na Mata Atlântica e Caatinga, Bahia, Brasil. Revista Brasileira de Biociências 15: 135-142.
• Santos AJ. 2003. Estimativas de riqueza em espécies. In: Rudran R, Cullen L, Valladares-Padua C. (eds.), Métodos de estudo em biologia da conservação e manejo da vida Terrestre. Curitiba, Editora da UFPR. p. 19-41
• Santos RF, Sotão HMP, Monteiro JS, Gusmão LFP, Gutiérre AH. 2018. Conidial fungi associated with leaf litter of red cedar (Cedrela odorata) in Belém, Pará (eastern Brazilian Amazon). Acta Amazonica 48: 230-238.
• Scheer MB. 2009. Fluxo de nutrientes pela precipitação pluviométrica em dois trechos de floresta ombrófila densa em Guaraqueçaba, Paraná. Revista Floresta 39: 117-130.
• Seifert K, Morgan-Jones G, Gams W, Kendrick B. 2011. The Genera of Hyphomycetes. Utrecht, CBS-KNAW Fungal Biodiversity Centre.
• Serviço Florestal Brasileiro. Ministério do Meio Ambiente. 2010. Florestas do Brasil em resumo: dados de 2005/2010. https://www.academia.edu/6795788/Livro_de_bolso_sfb_mma_2010_web_95
  » https://www.academia.edu/6795788/Livro_de_bolso_sfb_mma_2010_web_95
• Silva JMC, Tabarelli M. 2000. Tree species impoverishment and the future flora of the Atlantic forest of northeast Brazil. Nature 404: 72-74.
• Silva P, Grandi RAP. 2008. Hyphomycetes on leaf litter ofCaesalpinia echinataLam. with two new records from Brazil. Hoehnea 35: 477-488.
• Sridhar KR, Kaveriappa KM. 1989. Colonization of leaves by water-borne hyphomycetes in a tropical stream. Mycological Research 92: 392-396.
• Stahl J, Ernani PR, Gatiboni LC, Chaves DM, Neves CU. 2013. Produção de massa seca e eficiência nutricional de clones de Eucalyptus dunnii e Eucalyptus benthamii em função da adição de doses de fósforo ao solo. Ciência Florestal 23: 287-295.
• Suseela V, Tharayil N. 2018. Decoupling the direct and indirect effects of climate on plant litter decomposition: Accounting for stress-induced modifications in plant chemistry. Global Change Biology 24: 1428-1451.
• Svenning J-C. 2001. Evironmental heterogeneity, recruitment limitation and the mesoscale distribution of palms in a tropical montane rain forest (Maquipucuna, Ecuador). Journal of Tropical Ecology 17: 97-113.
• Swaty RL, Gehring CA, Van Ert M, Theimer TC, Keim P, Whitham TG. 1998. Temporal variation in temperature and rainfall differentially affects ectomycorrhizal colonization at two contrasting sites. New Phytologist 139: 733-739.
• Tavares MC, Rodal MJN, Melo AL, Lucena MFA. 2000. Fitossociologia do component arbóreo de um trecho de Floresta Ombrófila Montana do Parque Ecológico João Vasconcelos-Sobrinho, Caruaru, Pernambuco. Naturalia 25: 17-32.
• Takyu M, Aiba SI, Kitayama K. 2002. Effects of topography on tropical lower montane forests under different geological conditions on Mount Kinabalu, Borneo. Plant Ecology 159: 35-49.
• Thaung MM. 2008. A list of hypomycetes (and agonomycetes) in Burma. Australasian Mycologist 27: 149-172.
• Thongkantha S, Lumyong S, McKenzie EHC, Hyde KD. 2008. Fungal saprobes and pathogens occurring on tissues of Dracaena lourieri and Pandanus spp. in Thailand. Fungal Diversity 30: 149-169.
• Turk MA, Pentland AP. 1991. Face Recognition Using Eigenfaces. In: Proceedings of IEEE Computer Vision and Pattern Recognition. p. 586-591. doi: 10.1109/CVPR.1991.139758
  » https://doi.org/10.1109/CVPR.1991.139758
• Unterseher M, Otto P, Morawetz W. 2005. Species richness and substrate specificity of lignicolous fungi in the canopy of a temperate, mixed deciduous forest. Mycological Progress 4: 117-132. doi: 10.1007/s11557-006-0115-7
  » https://doi.org/10.1007/s11557-006-0115-7
• Unterseher M, Schnittler M, Dormann C, Sickert A. 2008. Application of species richness estimators for the assessment of fungal diversity. FEMS Microbiology Letters 282: 205-213.
• Valencia R, Foster RB, Villa G et al 2004. Tree species distributions and local habitat variation in the Amazon: large forest plot in eastern Ecuador. Journal of Ecology 92: 214-229. doi: 10.1111/j.0022-0477.2004.00876.x
  » https://doi.org/10.1111/j.0022-0477.2004.00876.x
• Voříšková J, Baldrian P. 2013. Fungal community on decomposing leaf litter undergoes rapid successional changes. ISME Journal 7: 477-486. doi: 10.1038/ismej.2012.116
  » https://doi.org/10.1038/ismej.2012.116
• Wright SJ. 2002. Plant diversity in tropical forests: A review of mechanisms of species coexistence. Oecologia 130: 1-14. doi: 10.1007/s004420100809
  » https://doi.org/10.1007/s004420100809
• Zhang N, Castlebury LA, Miller AN et al 2006. An overview of the systematics of the Sordariomycetes based on a four-gene phylogeny Mycologia 98: 1076-1087. doi: 10.1080/15572536.2006.11832635
  » https://doi.org/10.1080/15572536.2006.11832635

Publication Dates

• Publication in this collection
  21 Nov 2022
• Date of issue
  2022

History

• Received
  11 Feb 2022
• Accepted
  14 Oct 2022