Environmental Factors Shaping the Culturable Freshwater Fungi Diversity of Four Lakes in Yunnan Province, China

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This manuscript presents an important and comprehensive study on the diversity of culturable freshwater fungi in four lakes in Yunnan Province, China, and examines the environmental factors influencing this diversity. The research is thorough, and the data collected provide valuable insights into the fungal communities in these plateau lakes. However, several areas need significant improvement before the manuscript can be accepted for publication.

The manuscript is generally well-written but would benefit from a thorough language edit to improve readability and flow.

The introduction provides a good background on the geographical and ecological context of Yunnan Province. However, it would benefit from a more detailed discussion on the importance of freshwater fungi in aquatic ecosystems. Consider adding more recent studies that highlight the ecological roles of these fungi.

Explain why certain physicochemical parameters were selected for analysis. Are these parameters known to be particularly influential on fungal communities based on previous studies?

The description of the statistical analyses (e.g., CCA) is too brief. Please expand on how these analyses were conducted and interpreted.

Ensure all figures and tables are referenced appropriately in the text.

Can you provide more detail on the potential ecological roles of the most abundant genera (e.g., Fusarium, Penicillium, Aspergillus) identified in your study?

What measures were taken to ensure the accuracy of species identification? Were any taxonomic experts consulted?

How do you explain the lack of significant seasonal and regional differences in fungal diversity? Could there be methodological factors affecting this result?

Comments on the Quality of English Language

The manuscript is generally well-written but would benefit from a thorough language edit to improve readability and flow.

Author Response

First question: This manuscript presents an important and comprehensive study on the diversity of culturable freshwater fungi in four lakes in Yunnan Province, China, and examines the environmental factors influencing this diversity. The research is thorough, and the data collected provide valuable insights into the fungal communities in these plateau lakes. However, several areas need significant improvement before the manuscript can be accepted for publication.

Response: Thank you for the comment. We value your feedback and input and believe that it will enhance the overall quality of the paper. We improved the manuscript as per the suggestions.

 

Second question:The manuscript is generally well-written but would benefit from a thorough language edit to improve readability and flow.

Response: Thank you for the comment. We have made overall improvements to the language of the manuscript.

 

Third question:The introduction provides a good background on the geographical and ecological context of Yunnan Province. However, it would benefit from a more detailed discussion on the importance of freshwater fungi in aquatic ecosystems. Consider adding more recent studies that highlight the ecological roles of these fungi.

Response: Thank you for the comment. Your valuable comments allowed us to improve the quality of the manuscript, and we have added relevant content to the introduction section.

Line 71-86

Recent studies have increasingly highlighted the multifaceted ecological roles of freshwater fungi, shedding light on their importance in aquatic ecosystems. For instance, Powers et al. (2021) demonstrated that freshwater fungi significantly influence the decomposition rates of leaf litter and wood in streams, affecting nutrient release and cycling. Their study found that fungal-driven decomposition processes contribute to the overall nutrient dynamics and energy flow within stream ecosystems. Gulis et al. (2022) explored how freshwater fungi modify woody debris in streams, enhancing its palatability for aquatic invertebrates. The study revealed that fungal degradation of wood increases its nutritional value for detritivores, thus impacting food web dynamics and invertebrate populations. Kahl et al. (2023) investigated the role of freshwater fungi in shaping stream habitats by decomposing submerged plant material. Their findings highlight how fungal activity creates microhabitats that support diverse aquatic communities, illustrating the fungi's role in habitat complexity and biodiversity. Barton et al. (2023) showed that freshwater fungi influence water quality by decomposing organic matter and recycling nutrients. Their study emphasized the fungi's role in maintaining balanced nutrient levels and promoting overall ecosystem health.

 

Fourth question:Explain why certain physicochemical parameters were selected for analysis. Are these parameters known to be particularly influential on fungal communities based on previous studies?

Response: Thank you for the comment. Your valuable suggestions have inspired us a lot. We have discussed these environmental factors and improved the quality of our discussion sections.

The answers to your questions are as follows:

The selection of physicochemical parameters for analyzing fungal communities often stems from their known impacts on microbial ecosystems and their roles in influencing fungal growth, diversity, and activity. A lake is a complex ecosystem, and the physicochemical parameters often measured for the water body are pH, temperature, etc. In this study, we used 11 representative water physicochemical parameters to get more detailed research results.

Line 509-544

The community composition and diversity of aquatic fungi are influenced by various environmental factors, such as altitude, temperature, pH, UV radiation, various organic and inorganic compounds, other fungal populations, aquatic flora and fauna, and anthropogenic disturbances in the surrounding environment (Wurzbacher et al., 2010; Brandão et al., 2011; Krauss et al., 2011; Su et al., 2016).

 

PH, as an environmental factor of aquatic habitats, has a certain influence on the diversity of aquatic fungi. Research indicates that aquatic hyphomycetes tend to prefer slightly acidic to neutral environments. However, the abundance and diversity of aquatic fungi do not show a clear linear correlation with PH (Baudoin et al., 2008; Bärlocher, 2011; Su et al., 2016). Nevertheless, the community composition of freshwater fungi is closely related to PH.

 

Temperature is a crucial environmental factor in aquatic habitats. Variations in water temperature can affect not only the diversity and community composition of microorganisms but also their metabolic functions (Eaton & Scheller, 1996; Chauvet & Suberkropp, 1998). Although factors such as riparian vegetation, pollution, river conditions, and research methods may influence the diversity of freshwater lignicolous fungi, the overall trend shows that the diversity of freshwater fungi is higher in tropical and subtropical regions (Hyde et al., 2015). Research has indicated that fungal populations exhibit significant differences between subtropical, temperate, and tropical aquatic environments. Fungi in different climate zones have varying optimal growth and reproduction temperatures and different levels of biological activity. The optimal growth temperature for fungi is generally 20–25°C, with tropical fungi able to grow around 25°C. However, tropical fungi show the highest biological activity between 25–30°C (Graca et al., 2015). Therefore, studying the optimal growth temperatures of freshwater fungal populations and determining their peak biological activity conditions provides a theoretical basis for understanding the impact of global climate change on freshwater fungi and their response mechanisms to climate change.

 

 

Fifth question:The description of the statistical analyses (e.g., CCA) is too brief. Please expand on how these analyses were conducted and interpreted.

Response: Thank you for the comment. We provide a detailed description of it in the Materials and Methods section of the manuscript

Line 237-269

 

The NMDS analysis is as follows:

 

The data to be analyzed is a collection of M objects (season, study area) on which a distance function is defined, X_i,j was the abundance of the i_-species and the j_-sample in D objects.

The dissimilarity matrix D will be of size  M x M , The species abundance matrix can be constructed using a variety of distance metrics of Bray-Curtis distance.

d_i,j is the Bray-Curtis distance between sample  i  and sample  j .

X_i,k  and  X_j,k  are the abundances of species  k  in samples  i  and  j , respectively.

p is the total number of species.

these distances are the entries of the dissimilarity matrix D as follow:

Once the samples are positioned, calculate the pairwise Euclidean distances in this low-dimensional space. The distance between samples  i  and  j  is:

k  is the dimension of the low-dimensional space (e.g., 2D, where  k = 2 ).

y_i,m and  y_j,m are the coordinates of samples  i  and  j  in the low-dimensional space.

The goal of NMDS is to adjust the positions of the samples in the low-dimensional space so that the distances  y_ij  resemble the original distances  d_ij  as much as possible. This is achieved by minimizing the stress function:  

 

f(d_ij)  is a monotonic transformation of the original Bray-Curtis distances (since NMDS focuses on rank order rather than absolute values).

The NMDS algorithm iteratively adjusts the positions of the samples, recomputes the stress, and repeats the process until the stress value converges to a sufficiently lowlevel or the maximum number of iterations is reached.

Choose the main columns 1 and 2, and finally get the species distance matrix as follows

Sixth question:Ensure all figures and tables are referenced appropriately in the text.

Response:Thank you for the comment. We have conducted a detailed examination to ensure that all figures and tables were referenced correctly.

Seventh question:Can you provide more detail on the potential ecological roles of the most abundant genera (e.g.,Fusarium, Penicillium, Aspergillus) identified in your study?

Response: Thank you for the comment. Your valuable suggestions have greatly improved us, and we have added relevant supplements to the discussion section.

Line 414-434

Fusarium species play diverse and significant roles in ecosystems, ranging from organic matter decomposition and nutrient cycling to interactions with plants and other microorganisms. Their activities influence ecosystem health, productivity, and stability, highlighting their importance in both freshwater and terrestrial environments. Fusarium species are diverse fungi with various applications across agriculture, industry, and biotechnology. For example, Fusarium solani is known for producing various enzymes, including cellulases and xylanases, which are used in the textile, paper, and biofuel industries. These enzymes help break down cellulose and hemicellulose, enhancing the efficiency of industrial processes(Pai et al. 2021).

However, Penicillium and Aspergillus were also identified in our study, Penicillium has been found in four lakes, while Aspergillus was only isolated in Yangzonghai. Penicillium was widely present in various lakes, with low nutritional requirements and strong adaptability to the environment. Penicillium species produce a range of secondary metabolites, including antibiotics (such as penicillin). These compounds can influence microbial community structure by inhibiting the growth of other microorganisms and shaping microbial interactions.(EI et al. 2020) Aspergillus species are involved in the decomposition of a variety of organic materials, including plant residues and detritus. They contribute to the breakdown of complex polymers into simpler molecules that can be utilized by other organisms, Such as: Aspergillus niger is widely used for the production of industrial enzymes such as amylases, pectinases, and cellulases. These enzymes are utilized in industries like textiles, paper, food processing, and biofuel production.(Cairns et al. 2018)

 

Eighth question:What measures were taken to ensure the accuracy of species identification? Were any taxonomic experts consulted?

Response: Thank you for the comment. For the species identification, we used a combination of morphological and phylogenetic analysis, and consulted experts in fungal taxonomy for verification. Considering the actual situation of our study and in order to ensure the accuracy of the data, we finally decided to present results only at the genus level

 

Ninth question：How do you explain the lack of significant seasonal and regional differences in fungal diversity? Could there be methodological factors affecting this result?

Response: Thank you for the comment. Your valuable suggestions have given us more thought, and we have placed the content in the discussion section. Under your guidance, we have improved the quality of the manuscript.

Line 463-490

The answers to your questions are as follows:

Generalist Species: Some fungal species are highly adaptable and can thrive in a variety of conditions, leading to a more homogeneous diversity across different seasons or regions. These generalist species might dominate, masking potential differences.

Climate and Habitat Stability: In regions with relatively stable climates or habitats, fungal communities might not exhibit strong seasonal or regional variations. For example, in tropical rainforests where conditions are consistently humid and warm, fungal diversity might be less variable compared to temperate regions with more pronounced seasonal changes.

Ecological Interactions: Fungal communities are influenced by complex interactions with other organisms, including plants, animals, and microbes. In some ecosystems, these interactions might buffer against significant seasonal or regional variations in fungal diversity.

Human Impact: Anthropogenic factors such as land use changes, pollution, and climate change can alter fungal communities in ways that might obscure natural seasonal and regional patterns.

 

We think the methodological factors can affect this result, because if the sampling methods are not standardized or if there is insufficient replication, the observed lack of diversity might not accurately reflect the true fungal diversity. For instance, if samples are collected from the same types of habitats or at similar times of the year, this might not capture the full range of fungal diversity; the sensitivity of the methods used to detect and identify fungi can affect the results. For example, traditional culture-based methods might not capture all fungal species, especially those that are rare or not easily cultured. Modern techniques like DNA sequencing provide a broader view but can still be influenced by factors like sequencing depth and the choice of primers; if samples are collected infrequently or over a short period, this might not account for the full seasonal variability. Fungal diversity can exhibit significant changes over different times of the year, and sampling might need to be more frequent to detect these variations; The spatial resolution of sampling could also influence findings. Regional diversity might appear uniform if sampling sites are too close to each other or if the sampling effort does not cover a sufficient range of habitats within the region.

 

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

1. I don't know what Table 3 and Figure 2 mean. How about indicating the fungi that are detected only in winter and summer, respectively?

2. The conclusion is weak. It would be good to include in the conclusion how the results of this study can be used and what they mean.

Author Response

First question: I don't know what Table 3 and Figure 2 mean. How about indicating the fungi that are detected only in winter and summer, respectively?

Response: About Table 3 and Figure 2, In the process of writing the manuscript, we read a large amount of literature and found relevant studies on the distribution of cultivable fungal genera and species. They selected dominant genera or species and used ITS single genes to construct ML or Neighbor-Joining phylogenetic trees. In the initial manuscript, we constructed a phylogenetic tree. However, after careful checks, we realized that the use of only ITS markers to construct the phylogenetic tree doesn’t provide a good resolution to separate species, thus we deleted the phylogenetic tree; this was also suggested by the academic editor. To ensure data accuracy, we decided to present results only at the genus level. Consequently, we have removed Figure 2 and revised the Table 3 accordingly.

Reference:

Mahdieh S. Hosseyni Moghaddam, Naser Safaie, Leho Tedersoo, Niloufar Hagh-Doust. (2021). Diversity, community composition, and bioactivity of cultivable fungal endophytes in saline and dry soils in deserts. Fungal Ecology, Volume 49 , 101019. doi:10.1016/j.funeco.2020.101019.

Ogaki MB, Teixeira DR, Vieira R, Lírio JM, Felizardo JPS, Abuchacra RC, Cardoso RP, Zani CL, Alves TMA, Junior PAS, Murta SMF, Barbosa EC, Oliveira JG, Ceravolo IP, Pereira PO, Rosa CA, Rosa LH. (2020). Diversity and bioprospecting of cultivable fungal assemblages in sediments of lakes in the Antarctic Peninsula. Fungal Biol.(6):601-611. doi: 10.1016/j.funbio.2020.02.015.

Xue WK, Meng HDS, Wang YH, Zhu P, De J, Guo XF. (2022). Relationship between culturable fungal filamentous fungal diversity and environmental factors in Nam Co Lake. Biodivesity Science,30, 21473. doi: 10.17520/biods.2021473

Xu YL, Liu M, Huang H, Zhu J, Bao S. (2013). Diversity of Soil Cultureable Fungi in Bamen Bay Mangrove Forests.  Chinses Journal of Tropical Crops. 34(1):181-187. doi: 10.3969/j.ssn.1000-2561.2023.01.033

Salazar-Cerezo S, Martinez-Montiel N, Cruz-Lopez MDC, Martinez-Contreras RD. (2018). Fungal Diversity and Community Composition of Culturable Fungi in Stanhopea trigrina Cast Gibberellin Producers. Front Microbiol. 9:612. doi: 10.3389/fmicb.2018.00612.

Firstly, our research sampling plan covered spring, summer, and winter, and the relevant analysis was also conducted based on these three seasons. Spring and winter often represent significant climatic changes that can impact fungal communities in distinctive ways. Based on past findings, it is shown that key changes in fungal communities occur during these seasons. We compared winter and summer, but we lack data for spring. We also provided as much relevant data as possible for research.

 

Fungi isolated in summer are higher than in winter.

From the perspective of the diversity index: At the species level, the Shannon index: summer (3.67), winter (3.55); Pielou index: summer (11.3), winter (9.84); Simpson index: summer (1.99), winter (1.9). At the Genus level, Shannon index: summer (3.61), winter (3.19); Pielou index: summer (9.33), winter (6.23); Simpson index: summer (1.64), winter (1.2). At the species level, the diversity index has not changed much, but at the genus level, summer is much higher than winter. Fungi isolated in summer are higher than winter

 

Second question: The conclusion is weak. It would be good to include in the conclusion how the results of this study can be used and what they mean.

Response: Thank you for the comment. We have rewritten the conclusion

Line 546-558 Conclusion part

For the first time, this study analyzed the diversity of culturable freshwater fungi in four representative lakes in Yunnan Province, China. Based on comprehensive analysis to revealed a high species diversity of culturable freshwater fungi in four lakes of Yunnan Province, China. The number of culturable freshwater fungal isolates was highest in water bodies in summer. The significant differences in freshwater fungal species composition and distribution among these lakes are particularly noteworthy. The water environment factors, including temperature, PH, CHa, and DO, have emerged as key influencers, significantly shaping the distribution patterns of these fungi and, thereby, the overall freshwater fungal communities. However, the study has some limitations due to the use of culturable freshwater fungi. In future studies, it is very necessary to combine genomic analysis to study culturable and non-culturable fungi in lakes, so as to obtain more comprehensive and accurate information about the diversity of fungi in lakes.

 

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors promptly responded to all of my inquiries.

Author Response

2024.09.21

Responses to the comments of reviewer

Dear Reviewers,

Thank you very much for your reply regarding our manuscript entitled “Environmental factors shaping the culturable freshwater fungi diversity of four lakes in Yunnan Province, China”. We are grateful for your comments on our work. We have revised and modified the text, according to your critiques to make the content structure more concise. All modifications are marked in the manuscript  These changes have improved the manuscript, and we hope that it can be published without delay.

The description of the statistical analyses (e.g., CCA) is too brief. Please expand on how these analyses were conducted and interpreted.

Academic Editor- L247: Reviewer 1 requested details on the NMDS. However, the provided information is off-topic. The aim was not to present the theoretical approach of NMDS construction but rather to know the tool used, the parameters set, the stress levels, etc.
Response: Thank you very much for your valuable comments.

Fig 1. (a) NMDS Shepard diagram showing spatial distribution by area. (b) NMDS Shepard diagram showing seasonal distribution.

The non-metric multidimensional scaling (NMDS) analysis was conducted using the Scikit-learn package in Python. Prior to analysis, the data were transformed using the ‘wisconsin’ method, followed by the calculation of Bray-Curtis distances. The optimal configuration was selected based on the lowest stress values. The final stress values for the NMDS analysis were 0.0461 for spatial distribution (Fig. 1a) and 0.109 for seasonal distribution (Fig. 1b), indicating a good fit for both dimensions.

 

Line 234-239

The non-metric multidimensional scaling (NMDS) analysis was conducted using the Scikit-learn package in Python. Prior to analysis, the data were transformed using the ‘wisconsin’ method, followed by the calculation of Bray-Curtis distances. The op-timal configuration was selected based on the lowest stress values. The final stress values for the NMDS analysis were 0.0461 for spatial distribution and 0.109 for sea-sonal distribution, indicating a good fit for both dimensions.

Author Response File: Author Response.docx