Invasion by Cordgrass Increases Microbial Diversity and Alters Community Composition in a Mangrove Nature Reserve

Abstract

Invasion by exotic plant species can alter ecosystem function and reduce native plant diversity, but relatively little is known about their effects on belowground microbial communities. Here we investigated the effects of exotic cordgrass (Spartina alterniflora) invasion on the distribution of soil bacterial communities in a mangrove nature reserve of the Jiulong River Estuary, southeast China using high-throughput sequencing of 16S rRNA gene and multivariate statistical analysis. Our results showed that S. alterniflora invasion altered soil properties, and significantly increased soil bacterial taxa richness, primarily by stimulating an increase in conditionally rare or rare taxa, and changes in community composition and function. Abundant, conditionally rare and rare subcommunities exhibited similar response patterns to environment changes, with both conditionally rare and rare taxa showing a stronger response than abundant ones. Habitat generalists were detected among abundant, conditionally rare and rare taxa, whereas habitat specialists were only identified among conditionally rare taxa and rare taxa. In addition, we found that vegetation was the key factor driving these patterns. However, our comparative analysis indicated that both environmental selection, and neutral process, significantly contributed to soil bacterial community assembly. These results could improve the understanding of the microbial processes and mechanisms of cordgrass invasion, and offer empirical data of use in the restoration and management of the mangrove wetlands.

Keywords: Spartina alterniflora; bacterial diversity; biological invasion; community assembly; conditionally rare taxa; neutral process.

Figure 1

Comparison of alpha-diversity of the soil bacterial communities among four different types of vegetation zones. Ecotone indicates a transition zone with the distributions of cordgrass and mangrove overlap. The operational taxonomic units (OTUs) were defined at 97% sequence similarity threshold. Significant differences (P < 0.05) between vegetation types are indicated by different letters of the alphabet. Statistical analysis is Student's t-test with Bonferroni correction (n = 4). The ends of the box represent the 25th and 75th percentiles, the whiskers represent minimum and maximum range, and the center lines represent the median.

Figure 2

Comparison of beta-diversity of the soil bacterial communities among different types of vegetation zones. (A) Non-metric multidimensional scaling (NMDS) ordination of soil bacterial communities based on the Bray-Curtis dissimilarity. Points are connected by dash lines according to the progression of time (from spring to winter). (B) Venn diagram showing the number of OTUs (96 abundant OTUs, 7,052 conditionally rare OTUs, 2,042 rare OTUs) that are unique and shared between three different types of vegetation zones. (C) Pairwise Bray-Curtis dissimilarity of bacterial communities among different vegetation types. Mu, mudflat; Co, cordgrass; Ec, ecotone; Ma, mangrove. Significant differences (P < 0.05) between vegetation types are indicated by different letters of the alphabet. Statistical analysis is Student's t-test with Bonferroni correction (n = 16). Data are means ± standard error (error bars).

Figure 3

Pairwise Bray-Curtis dissimilarity of soil bacterial community and its coefficient of variation (CV) measured at different relative abundances, different taxonomic resolutions and different niche breadths. The bacterial community analyses are conducted on four vegetation zones: mudflat (n = 4), cordgrass (n = 4), ecotone (n = 4) and mangrove (n = 4). AT, abundant taxa; CRT, conditionally rare taxa; RT, rare taxa. S, species; G, genus; F, family; O, order; C, class; P, phylum. Ge, generalists; Sp, specialists; St, strict specialists (indicator species). Significance is calculated by nonparametric Mann-Whitney U-test. ^*P < 0.05, ^**P < 0.01. Data are expressed as means ± standard error (error bars).

Figure 4

Habitat specialization of different OTUs based on niche breadth and INDVAL (INDicator VALues) analysis. (A) Distribution of niche breadth values of all selected OTUs. (B) The number of generalists, specialists, and strict habitat specialists (indicators) belonged to abundant, conditionally rare and rare taxa. OTUs with niche breadth value >3 were arbitrarily defined as generalists, whereas those with niche breadth <1.5 were selected as specialists. For the indicators, phylotypes with a P-value < 0.05 and both, a fidelity and specificity value ≥0.8, were considered as a good threshold for strict habitat specialists (Dufrene and Legendre, 1997). AT, abundant taxa; CRT, conditionally rare taxa; RT, rare taxa. Indicators, strict specialists. (C) The number and taxonomic composition of strong indicator taxa for the specific vegetation zones. Four habitats were mudflat, cordgrass, ecotone, and mangrove.

Figure 5

RDA ordination showing the bacterial community composition in relation to significant vegetation and soil properties (P < 0.05). All environmental factors were used in this analysis except those with variance inflation factors higher than 20 (VIF > 20). Cordgrass represents for Spartina alterniflora. TC, total carbon. Inside Venn diagram showed results of variation partitioning analysis, illustrating the effects of environment (E), vegetation (V) and season (S) factors on the community composition of soil bacteria. Values indicate the percentage of variation explained by each fraction, including pure, shared explained and unexplained (U) variability. Note that the fraction of variation values <1% are not shown for simplicity.

Figure 6

The variation in soil bacterial metacommunity explained by neutral model and environmental variables, respectively. (Left) Fit of the neutral model based on the entire bacterial communities from all vegetation zones (n = 9,749). Frequency of occurrence of different OTUs as a function of mean relative abundance based on 10,342 reads per samples in all data sets. Dash lines represent 95% confidence intervals around the model prediction (blue line). OTUs that occur more or less frequently than predicted by the model are shown in different colors. (Right) Comparison of explained community variations between neutral model and environmental factors along the taxonomic ranks. Taxonomy-based compositional variation is calculated based on our database annotation from species to phylum. The soil bacterial community analyses are conducted on 16 samples from Jiulong River estuary.