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Diversity
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Microbial Community Dynamics in Soil Ecosystems
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Microbial Community Dynamics in Soil Ecosystems

A special issue of Diversity (ISSN 1424-2818). This special issue belongs to the section "Microbial Diversity and Culture Collections".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 2758

Special Issue Editor

Dr. Jiao Feng

E-Mail Website
Guest Editor
Department of Ecology, College of Resources and Environment, Huazhong Agricultural University, Wuhan 430070, China
Interests: soil microbial ecology; soil carbon, nitrogen and phosphorus biogeochemical cycles; microorganisms and their ecosystem functions

Special Issue Information

Dear Colleagues,

The soil microbiome represents the most biologically diverse community on Earth, encompassing millions of species across multiple kingdoms, including bacteria, archaea, fungi, viruses, and protists. These microbes assemble through various stochastic and deterministic processes, forming complex communities with different interspecies relationships, such as cooperation and competition. These intricate microbial communities strongly influence multiple ecosystem functions, such as soil organic matter decomposition, soil fertility, plant pathogen control, and greenhouse gas emissions. Previous studies have indicated that soil microbial community structure varies widely across multi-scale soil habitats, as well as along various spatiotemporal gradients. However, despite this evidence, only a few hundred thousand of these microbes have been described and characterized in detail. Many unknown taxonomic groups and their metabolic traits remain unexplored. This complicates the forecasting of dynamics within complex microbial communities under varying environmental conditions, thereby limiting our understanding of their ecosystem functions in the context of global change.

In this Special Issue, we aim to present the latest findings on “Microbial Community Dynamics in Soil Ecosystems”, focusing on the diversity, taxonomy, morphology, interaction, and distribution patterns of soil microorganisms across multiple environmental gradients. We aim to understand the functional characteristics and dynamics of diverse microorganisms in soil ecosystems. Specific topics include, but are not limited to, the following: (1) new methodologies for soil microorganisms; (2) microbial biogeography; (3) microbial responses and adaptations to global change; (4) plant–microbe interactions; (5) microbial roles in soil biogeochemical cycles; and (6) relationships between soil microbial diversity and multifunctionality.

Please do not hesitate to contact us if you are interested in contributing to this Special Issue or if you have any questions. We intend for this Special Issue to serve as a reference work on soil microbial research for both professionals and students.

Dr. Jiao Feng
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diversity is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2100 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • diverse microorganisms
  • soil ecosystems
  • soil microorganisms
  • microbial biogeography
  • soil biogeochemical cycles

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

22 pages, 3827 KiB  
Article
Species Richness of Arbuscular Mycorrhizal Fungi in Heterogenous Saline Environments
by Jahangir A. Malik, Basharat A. Dar, Abdulaziz A. Alqarawi, Abdulaziz M. Assaeed, Fahad Alotaibi, Arafat Alkhasha, Abdelmalik M. Adam and Ahmed M. Abd-ElGawad
Diversity 2025, 17(3), 183; https://doi.org/10.3390/d17030183 - 4 Mar 2025
Viewed by 176
Abstract
Sabkha (inland and coastal—saline beds or saline lands) are widespread in Saudi Arabia and are distinguished by their hypersaline nature. These hypersaline habitats are commonly covered by halophytic vegetation. Moreover, Arbuscular mycorrhizal fungi (AMF) are an essential component of these habitats and exhibit [...] Read more.
Sabkha (inland and coastal—saline beds or saline lands) are widespread in Saudi Arabia and are distinguished by their hypersaline nature. These hypersaline habitats are commonly covered by halophytic vegetation. Moreover, Arbuscular mycorrhizal fungi (AMF) are an essential component of these habitats and exhibit a unique adaptation and contribute significantly to ecosystem variability, diversity, and function. Additionally, AMF from saline habitats are an essential component for the successful rehabilitation of salinity-affected areas. Despite their importance, little is known about the distribution and abundance of AMF along inland and coastal sabkhat of Saudi Arabia. Therefore, the main objective of this study was to investigate the abundance and diversity of AMF in the coastal and inland sabkhat of Saudi Arabia. Five soil samples, each from five randomly selected spots (considering the presence of dominant and co-dominant halophytic species), were collected from every location and were used to assess the AMF abundance and diversity. The study indicated that the highest number of AMF spores was recorded from Jouf, averaging ≈ 346 spores 100 g−1 dry soil, and the lowest from Uqair, averaging ≈ 96 spores 100 g−1 dry soil. A total of 25 AMF species were identified, belonging to eight identified genera viz., Acaulospora, Diversispora, Gigaspora, Scutellospora, Claroideoglomus, Funneliformis, Glomus, and Rhizophagus and five families. Of the total identified species, 52% belonged to the family Glomeraceae. Moreover, the highest number of species was isolated from the sabkha in Qasab. Additionally, Glomeraceae was abundant in all the studied locations with the highest relative abundance in Uqair (48.34%). AMF species Claroideoglomus etunicatum, Funneliformis mosseae, Glomus ambisporum, and Rhizophagus intraradices were the most frequently isolated species from all the Sabkha locations with isolation frequency (IF) ≥ 60%, and Claroideoglomus etunicatum (Ivi ≥ 50%) was the dominant species in all the studied locations. Furthermore, data on the Shannon–Wiener diversity index showed that the highest AMF species diversity was in Qaseem and Qasab habitats. The highest Pielou’s evenness index was recorded in Jouf. Moreover, the soil parameters that positively affected the diversity of identified species included Clay%, Silt%, HCO31−, OM, MC, N, and P, while some soil parameters such as EC, Na+, SO42−, and Sand% had a significant negative correlation with the isolated AMF species. This study revealed that AMF can adapt and survive the harshest environments, such as hypersaline sabkhas, and thus can prove to be a vital component in the potential restoration of salinity-inflicted/degraded ecosystems. Full article
(This article belongs to the Special Issue Microbial Community Dynamics in Soil Ecosystems)
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Figure 1

Figure 1
<p>Map of Saudi Arabia showing the different Sabkha locations (marked as red) assessed for investigating AMF abundance and diversity. Arabic terms denote the names of the different cities as: الرياض = Riyadh; المدينة المنورة = Medina; جدة = Jeddah; مكة المكرمة = Makkah; دبي = Dubai; مسقط = Muscat; صنعاء = Sana’a; دمشق = Damascus.</p> Full article ">Figure 2
<p>AMF spore density in the samples collected from different inland and coastal sabkha locations around Saudi Arabia. The colored bars represent mean values (<span class="html-italic">n</span> = 5), while the error bars indicate the standard error (SE). Different letters above the error bars represent significant difference (<span class="html-italic">p</span> = 0.05) based on Tukey’s test. <span class="html-italic">*** p</span> &lt; 0.0001 (Tukey test).</p> Full article ">Figure 3
<p>Relative abundance of AMF communities at order (<b>A</b>), and family (<b>B</b>) level in the soil samples collected from different sabkha habitats.</p> Full article ">Figure 4
<p>Relative abundance of AMF communities at genus (<b>A</b>) and species (<b>B</b>) level in the soil samples collected from different sabkha habitats.</p> Full article ">Figure 5
<p>The variation in AMF species among different hypersaline sabkha habitats with the Shannon–Wiener diversity index (<b>A</b>); Simpson’s dominance index (<b>B</b>); and Pielou’s evenness index (<b>C</b>) of species. Different letters above the error bars represent significant differences (<span class="html-italic">p</span> = 0.05) based on Tukey’s test. <span class="html-italic">* p</span> &lt; 0.01.</p> Full article ">Figure 6
<p>The similarity index of AMF species between different hypersaline sabkha habitats.</p> Full article ">Figure 7
<p>A correlation heatmap of the relationship between soil parameters and the AMF species isolated along different sabkha habitats. Red colors indicate a strong positive correlation while blue indicates a significant negative correlation between species and soil parameters.</p> Full article ">Figure 8
<p>Principal component analysis (PCA) plot showing the associations between soil physiochemical parameters and AMF species along different sabkha locations.</p> Full article ">
16 pages, 3545 KiB  
Article
Higher Soil Mesofauna Abundance and Microbial Activities Drive Litter Decomposition in Subtropical Forests
by Hong Lin, Qin Kong, Xinyu Xu, Xingbing He, Yonghui Lin, Zaihua He, Yuehong Gao and Xiangshi Kong
Diversity 2024, 16(11), 700; https://doi.org/10.3390/d16110700 - 17 Nov 2024
Viewed by 1179
Abstract
Soil fauna play an important role in litter decomposition and affect the “home-field advantage” (HFA) of litter decomposition. However, how this effect is modulated by the microenvironment needs further investigation. We conducted a reciprocal transplant experiment of litter decomposition using different mesh-size litterbags [...] Read more.
Soil fauna play an important role in litter decomposition and affect the “home-field advantage” (HFA) of litter decomposition. However, how this effect is modulated by the microenvironment needs further investigation. We conducted a reciprocal transplant experiment of litter decomposition using different mesh-size litterbags across litter and soil layers in subtropical coniferous (Pinus massoniana) and broad-leaved (Quercus variabilis) forests. Our results revealed a pronounced HFA in P. massoniana. P. massoniana litter decomposed faster in its home habitat by 40.6% in the litter layer and 10.2% in the soil layer in coarse mesh bags and by 21.8% in the litter layer and 21.4% in the soil layer in fine mesh bags. However, Q. variabilis litter showed faster decomposition in its home soil layer by 10.8% and 4.3% for coarse and fine mesh bags, whereas in the litter layer it decomposed faster in the away habitat by 16.7% and 20.6% for coarse and fine mesh bags, respectively. Higher soil mesofauna abundance and microbial activities in the coniferous forest compared to the broad-leaved forest drive the observed HFA of litter decomposition. Especially in the litter layer, the abundance of mesofauna was 89.8% higher in the coniferous forest. Coarse mesh bags generally facilitated a higher decomposition rate across litter and soil layers, likely due to a better interaction between soil mesofauna and extracellular enzyme activity. The HFA index exhibited distinct seasonal fluctuations, peaking in October for coarse mesh bags and in April for fine mesh bags within the litter layer, while soil layer peaks occurred in August and April. Notably, an increase in Acarina abundance strongly correlated with enhanced decomposition and HFA effects in the litter layer during October. This study revealed the sensitivity of HFA to the soil layer and soil fauna and underscores the complex role of the microclimate in shaping interactions among soil microorganisms, litter quality, and mesofauna, thereby enriching our understanding of litter decomposition dynamics in forest ecosystems. Full article
(This article belongs to the Special Issue Microbial Community Dynamics in Soil Ecosystems)
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Figure 1

Figure 1
<p>Variation in cumulative litter mass loss over time. (<b>a</b>) Coarse mesh-size litterbag in the litter layer; (<b>b</b>) fine mesh-size litterbag in the litter layer; (<b>c</b>) coarse mesh-size litterbag in the soil layer; and (<b>d</b>) fine mesh-size litterbag in the soil layer. PA, <span class="html-italic">P. massoniana</span> litter in the away habitat; PH, <span class="html-italic">P. massoniana</span> litter in the home habitat; QA, <span class="html-italic">Q. variabilis</span> litter in the away habitat; QH, <span class="html-italic">Q. variabilis</span> litter in the home habitat. Values are presented as means ± standard error (<span class="html-italic">n</span> = 3).</p> Full article ">Figure 2
<p>The decomposition rate (<span class="html-italic">k</span> value) of leaf litter at “home” and “away”. (<b>a</b>) Coarse mesh litterbags in the litter layer, (<b>b</b>) fine mesh litterbags in the litter layer, (<b>c</b>) coarse mesh litterbags in the soil layer, (<b>d</b>) fine mesh-size litterbags in the soil layer. PA, <span class="html-italic">P. massoniana</span> litter in the away habitat; PH, <span class="html-italic">P. massoniana</span> litter in the home habitat; QA, <span class="html-italic">Q. variabilis</span> litter in the away habitat; QH, <span class="html-italic">Q. variabilis</span> litter in the home habitat. Different lowercase letters donate significant differences at the 0.05 level.</p> Full article ">Figure 3
<p>Variation in soil microbial respiration in the litter (<b>a</b>) and soil (<b>c</b>) layers of the broad-leaved forest and the litter (<b>b</b>) and soil (<b>d</b>) layers of the coniferous forest over time. Values are presented as means ± standard error (<span class="html-italic">n</span> = 3). Different letters indicate significant difference at the 0.05 level.</p> Full article ">Figure 4
<p>Abundance dynamics of mesofauna order present within litter from the litter and soil layers during decomposition.</p> Full article ">Figure 5
<p>Mean parameter estimates calculated for HFA index in coarse and fine mesh in the litter and soil layers over time. (<b>a</b>) Coarse mesh litterbags in the litter layer, (<b>b</b>) fine mesh litterbags in the litter layer, (<b>c</b>) coarse mesh litterbags in the soil layer, (<b>d</b>) fine mesh-size litterbags in the soil layer. Error bars indicate standard error (mean ± SE, <span class="html-italic">n</span> = 3).</p> Full article ">Figure 6
<p>Correlation heatmap (<b>a</b>) and importance ranking (<b>b</b>) of microbial activity and soil fauna diversity on litter decomposition. SIR, soil respiration rate; CBH, cellobiohydrolase; BG, β-1,4 glucosidase; BX, β-1,4 xylosidase; NR, nitrate reductase; ACP, acid phosphatase; AKP, alkaline phosphatase; URE, urease; F_abu, fauna abundance; F_rich, fauna species richness. The values in the lower left of (<b>a</b>) are the Spearman correlation, and *, **, and *** in the upper right indicate significant differences at the 0.05, 0.01, and 0.001 levels, respectively.</p> Full article ">Figure 7
<p>Principal component analysis (PCA) of soil microbial activity, fauna diversity, and litter decomposition in the litter (<b>a</b>) and soil (<b>c</b>) layers of the broad-leaved forest and the litter (<b>b</b>) and soil (<b>d</b>) layers of the coniferous forest. The abbreviations are the same as in <a href="#diversity-16-00700-f006" class="html-fig">Figure 6</a>.</p> Full article ">
17 pages, 4874 KiB  
Article
Aggregate Size Mediated the Changes in Soil Microbial Communities After the Afforestation of a Former Dryland in Northwestern China
by Deming Zhang, Ling Bai, Wei Wang, Yanhe Wang, Tiankun Chen, Quan Yang, Haowen Chen, Shuning Kang, Yongan Zhu and Xiang Liu
Diversity 2024, 16(11), 696; https://doi.org/10.3390/d16110696 - 13 Nov 2024
Viewed by 945
Abstract
Although the afforestation of former arable lands is a common global land-use conversion, its impact on soil microbial communities at the aggregate scale has not been adequately addressed. In this study, soil samples were categorized into large macroaggregates (LM, >2 mm), small macroaggregates [...] Read more.
Although the afforestation of former arable lands is a common global land-use conversion, its impact on soil microbial communities at the aggregate scale has not been adequately addressed. In this study, soil samples were categorized into large macroaggregates (LM, >2 mm), small macroaggregates (SM, 2–0.25 mm), and microaggregates (MI, <0.25 mm) to assess the changes in microbial composition, diversity, network complexity, and network stability within soil aggregates after the afforestation of a former dryland in northwestern China. The results revealed that afforestation enhanced the relative abundance of Actinobacteriota, Chloroflexi, Ascomycota, and Mortierellomycota within the soil aggregates, suggesting that these phyla may have greater advantages in microbial communities post-afforestation. The Shannon–Wiener and Pielou indices for bacterial communities showed no significant differences between land-use types across all aggregate fractions. However, the alpha diversity of fungal communities within the LM and SM significantly increased after afforestation. Bray–Curtis dissimilarity indices showed that afforestation altered bacterial beta diversity within the LM and MI but had a minimal impact on fungal beta diversity across all three aggregate fractions. The topological features of cross-kingdom microbial co-occurrence networks within the soil aggregates generally exhibited a decreasing trend post-afforestation, indicating a simplification of microbial community structure. The reduced robustness of microbial networks within the LM and SM fractions implies that afforestation also destabilized the structure of microbial communities within the macroaggregates. The composition of the soil microbial communities correlated closely with soil carbon and nitrogen contents, especially within the two macroaggregate fractions. The linkages suggests that improved resource conditions could be a key driver behind the shifts in microbial communities within soil aggregates following afforestation. Our findings indicate that the impact of afforestation on soil microbial ecology can be better understood by soil aggregate fractionation. Full article
(This article belongs to the Special Issue Microbial Community Dynamics in Soil Ecosystems)
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Figure 1

Figure 1
<p>The characteristics of microbial community compositions ((<b>a</b>,<b>c</b>): bacteria; (<b>b</b>,<b>d</b>): fungi) within the soil aggregates of different land-use types. Different uppercase letters indicate significant differences among aggregate fractions within a specific land-use type, whereas different lowercase letters denote significant differences between land-use types within a specific aggregate fraction. DLM, DSM, and DMI represent large macroaggregates, small macroaggregates, and microaggregates in the dryland, respectively, while PLM, PSM, and PMI represent large macroaggregates, small macroaggregates, and microaggregates in the <span class="html-italic">C. korshinskii</span> plantation, respectively.</p> Full article ">Figure 2
<p>Shannon–Wiener and Pielou indices of bacterial (<b>a</b>,<b>b</b>) and fungal communities (<b>c</b>,<b>d</b>) within soil aggregates of different land-use types. Different uppercase letters denote significant differences among aggregate fractions, while asterisks indicate significant differences between land-use types. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001; ns, non-significant.</p> Full article ">Figure 3
<p>Beta diversity of bacterial (<b>a,c</b>) and fungal communities (<b>b,d</b>) within soil aggregates of different land-use types as revealed by principal coordinates analysis and Bray–Curtis dissimilarity. DLM, DSM, and DMI denote large macroaggregates, small macroaggregates, and microaggregates in dryland, respectively, while PLM, PSM, and PMI represent large macroaggregates, small macroaggregates, and microaggregates in <span class="html-italic">C. korshinskii</span> plantation, respectively. Different uppercase letters indicate significant differences between aggregate fractions, while asterisks indicate significant differences between land-use types. *** <span class="html-italic">p</span> &lt; 0.001; ns, non-significant.</p> Full article ">Figure 4
<p>Cross-kingdom co-occurrence networks of microbial taxa within soil aggregates of different land-use types ((<b>a</b>–<b>c</b>): dryland; (<b>d</b>–<b>f</b>): <span class="html-italic">C. korshinskii</span> plantation). Different colors represent different modules, and modules with &lt;5 nodes are represented in gray. LM, SM, and MI represent large macroaggregates, small macroaggregates, and microaggregates, respectively.</p> Full article ">Figure 5
<p>Weighted (<b>a</b>) and unweighted robustness (<b>b</b>) of microbial cross-kingdom co-occurrence networks within the soil aggregates of different land-use types. Error bars represent the standard deviations of the mean. * <span class="html-italic">p</span> &lt; 0.05; *** <span class="html-italic">p</span> &lt; 0.001; ns, non-significant.</p> Full article ">Figure 6
<p>Factors that influenced the compositions of bacterial (<b>a</b>) and fungal communities (<b>b</b>) within the soil aggregates as revealed by the Mantel test. LM, large macroaggregates; SM, small macroaggregates; MI, microaggregates; MP, mass proportion; TOC, total organic carbon; TN, total nitrogen; TP, total phosphorus; C:N, carbon to nitrogen ratio; AN, alkali-hydrolyzable nitrogen; AP, available phosphorus. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">
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