Mechanisms underlying the succession of plant rhizosphere microbial community structure and function in an alpine open-pit coal mining disturbance zone.

Elucidating the responses and potential functions of soil microbial communities during succession is important for understanding biogeochemical processes and the sustainable development of plant communities after environmental disturbances. However, studies of such dynamics during post-mining ecological restoration in alpine areas remain poorly understood. Microbial diversity, nitrogen, and phosphorus cycle functional gene potential in the Heishan mining area of Northwest China was studied, including primitive succession, secondary succession, and artificial succession disturbed by mining. The results revealed that: (1) The dominant bacteria in both categories (non-remediated and ecologically restored) of mining area rhizosphere soil were Proteobacteria, adopting the r strategy, whereas in naturally occurring soil outside the mining area, the dominant bacteria were actinomycetes and Acidobacteria, adopting the k strategy. Notably, mining perturbation significantly reduced the relative abundance of archaea. (2) After restoration, more bacterial network node connections were observed in mining areas than were originally present, whereas the archaeal network showed the opposite trend. (3) The networks of microbial genes related to nitrogen and phosphorus cycle potential differed significantly, depending on the succession type. Namely, prior to restoration, there were more phosphorus related functional gene network connections; these were also more strongly correlated, and the network was more aggregated. (4) Soil factors such as pH and NO3-N affected both the mining area remediation soil and the soil outside the mining area, but did not affect the soil of the original vegetation in the mining area. The changes in the structure and function of plant rhizosphere microorganisms after mining disturbance can provide a theoretical basis for the natural restoration of mining areas.

Prediction of spatial distribution characteristics of ecosystem functions based on a minimum data set of functional traits of desert plants.

The relationship between plant functional traits and ecosystem function is a hot topic in current ecological research, and community-level traits based on individual plant functional traits play important roles in ecosystem function. In temperate desert ecosystems, which functional trait to use to predict ecosystem function is an important scientific question. In this study, the minimum data sets of functional traits of woody (wMDS) and herbaceous (hMDS) plants were constructed and used to predict the spatial distribution of C, N, and P cycling in ecosystems. The results showed that the wMDS included plant height, specific leaf area, leaf dry weight, leaf water content, diameter at breast height (DBH), leaf width, and leaf thickness, and the hMDS included plant height, specific leaf area, leaf fresh weight, leaf length, and leaf width. The linear regression results based on the cross-validations (FTEIW - L, FTEIA - L, FTEIW - NL, and FTEIA - NL) for the MDS and TDS (total data set) showed that the R2 (coefficients of determination) for wMDS were 0.29, 0.34, 0.75, and 0.57, respectively, and those for hMDS were 0.82, 0.75, 0.76, and 0.68, respectively, proving that the MDSs can replace the TDS in predicting ecosystem function. Then, the MDSs were used to predict the C, N, and P cycling in the ecosystem. The results showed that non-linear models RF and BPNN were able to predict the spatial distributions of C, N and P cycling, and the distributions showed inconsistent patterns between different life forms under moisture restrictions. The C, N, and P cycling showed strong spatial autocorrelation and were mainly influenced by structural factors. Based on the non-linear models, the MDSs can be used to accurately predict the C, N, and P cycling, and the predicted values of woody plant functional traits visualized by regression kriging were closer to the kriging results based on raw values. This study provides a new perspective for exploring the relationship between biodiversity and ecosystem function.

Discriminating ecological processes affecting different dimensions of α- and ß-diversity in desert plant communities.

Understanding the spatial distribution of plant diversity and its drivers are major challenges in biogeography and conservation biology. Integrating multiple facets of biodiversity (e.g., taxonomic, phylogenetic, and functional biodiversity) may advance our understanding on how community assembly processes drive the distribution of biodiversity. In this study, plant communities in 60 sampling plots in desert ecosystems were investigated. The effects of local environment and spatial factors on the species, functional, and phylogenetic α- and ß-diversity (including turnover and nestedness components) of desert plant communities were investigated. The results showed that functional and phylogenetic α-diversity were negatively correlated with species richness, and were significantly positively correlated with each other. Environmental filtering mainly influenced species richness and Rao quadratic entropy; phylogenetic α-diversity was mainly influenced by dispersal limitation. Species and phylogenetic ß-diversity were mainly consisted of turnover component. The functional ß-diversity and its turnover component were mainly influenced by environmental factors, while dispersal limitation dominantly effected species and phylogenetic ß-diversity and their turnover component of species and phylogenetic ß-diversity. Soil organic carbon and soil pH significantly influenced different dimensions of α-diversity, and soil moisture, salinity, organic carbon, and total nitrogen significantly influenced different dimensions of α- and ß-diversity and their components. Overall, it appeared that the relative influence of environmental and spatial factors on taxonomic, functional, and phylogenetic diversity differed at the α and ß scales. Quantifying α- and ß-diversity at different biodiversity dimensions can help researchers to more accurately assess patterns of diversity and community assembly.

Predicting spatial variability of species diversity with the minimum data set of soil properties in an arid desert riparian forest.

Species diversity has spatial heterogeneity in ecological systems. Although a large number of studies have demonstrated the influence of soil properties on species diversity, most of them have not considered their spatial variabilities. To remedy the knowledge gap, a 1 ha (100 m × 100 m) plots of arid desert riparian forest was set up in the Ebinur Wetland Nature Reserve (ELWNR) in the NW China. Then, the minimum data set of soil properties (soil MDS) was established using the Principal Component Analysis (PCA) and the Norm Value Determination to represent the total soil property data set (soil TDS). The Geo-statistics and two models (i.e., Random Forest/RF and Multiple Linear Regression/MLR) were used to measure the spatial variability of species diversity, and predict its spatial distribution by the soil MDS, respectively. The results showed that the soil MDS was composed of soil salt content (SSC), soil total phosphorus (STP), soil available phosphorus (SAP), soil organic carbon (SOC) and soil nitrate nitrogen (SNN); which represented the soil TDS perfectly (R2 = 0.62). Three species diversity indices (i.e., Shannon-Wiener, Simpson and Pielou indices) had a high spatial dependence (C0/(C0+C)< 25%; 0.72 m ≤ range≤ 0.77 m). Ordinary kriging distribution maps showed that the spatial distribution pattern of species diversity predicted by RF model was closer to its actual distribution compared with MLR model. RF model results suggested that the soil MDS had significant effect on spatial distribution of Shannon-Wiener, Simpson and Pielou indices (Varex = 56%, 49% and 36%, respectively). Among all constituents, SSC had the largest contribution on the spatial variability of species diversity (nearly 10%), while STP had least effect (< 5.3%). We concluded that the soil MDS affected spatial variability of species diversity in arid desert riparian forests. Using RF model can predict spatial variability of species diversity through soil properties. Our work provided a new case and insight for studying the spatial relationship between soil properties and plant species diversity.

Characteristics and driving mechanisms of species beta diversity in desert plant communities.

Species dissimilarity (beta diversity) primarily reflects the spatio-temporal changes in the species composition of a plant community. The correlations between ß diversity and environmental factors and spatial distance can be used to explain the magnitudes of environmental filtering and dispersal. However, little is known about the relative roles and importance of neutral and niche-related factors in the assemblage of plant communities with different life forms in deserts. We found that in desert ecosystems, the ß diversity of herbaceous plants was the highest, followed by that of shrubs and trees. The changes in the ß diversity of herbs and shrubs had stronger correlations with the environment, indicating that community aggregation was strongly affected by niche processes. The soil water content and salt content were the key environmental factors affecting species distributions of the herb and shrub layers, respectively. Spatial distance explained a larger amount of the variation in tree composition, indicating that dispersal limitation was the main factor affecting the construction of the tree layer community. The results suggest that different life forms may determine the association between organisms and the environment. These findings suggest that the spatial patterns of plant community species in the Ebinur Lake desert ecosystem are the result of the combined effects of environmental filtering and dispersal limitation.

Structure and driving factors of the soil microbial community associated with Alhagi sparsifolia in an arid desert.

Environmental properties are important factors in structuring soil microbial communities. The primary driving factors vary in different ecosystems. In the present work, we analyzed the microbial communities of rhizosphere and bulk soils associated with the halophyte Alhagi sparsifolia across three salt/water gradients in the desert area around Ebinur Lake Basin, China, using high-throughput sequencing technology. We found that there were significant differences in soil water content (SWC), soil salinity (SAL), total nitrogen (TN), and total phosphorus (TP) contents between the three water/salt gradients. In the L (low water and salt) plot, Actinobacteria was the most abundant bacterial phylum while Ascomycota was the dominant fungal phylum. The relative abundance of Actinobacteria was negatively correlated with soil pH, soil organic carbon (SOC), TP, and available phosphorus (AP). The abundance of Bacteroidetes was significantly positively correlated with soil SOC, SWC, SAL, pH, TN, and TP (P < 0.05). The abundance of fungal phylum Chytridiomycota was significantly positively correlated with pH (P < 0.01), SWC, AP, and sulfate ion (P < 0.05). SOC and nitrate nitrogen were the main factors impacting the bacterial community, while ammonium nitrogen (NH4+) and TP were the main driving forces for the fungal community. Soil nutrients were the main contributors to the dissimilarities in the bacterial and fungal communities, explaining 48.06% and 44.45% of the variation. SWC, SAL, and pH explained only a small percentage of the microbial community dissimilarity. In conclusion, soil microbial community structure was affected by SWC, SAL, pH, and soil nutrients, with soil nutrients as the main driving factors. Nitrogen has a differential effect on the different microbial communities: bacterial communities of Alhagi sparsifolia were mainly affected by nitrate nitrogen, while fungal communities were mainly driven by ammonium nitrogen.

Factors that alter the relative importance of abiotic and biotic drivers on the fertile island in a desert-oasis ecotone.

Dryland vegetation forms a "fertile island effect" due to water and nutrient retention. However, there has been little research on the mechanism underlying C-, N-, P-accumulation and overall fertile island at the community level. We therefore presented the systematic investigation on this issue through the survey in desert-oasis ecotone. The survey covering the vegetation composition, plant height, crown area and vegetation cover. The main parameters measured included soil moisture, soil pH, soil salinity and nine soil indicators related to C, N and P cycling. The results revealed that the effect of fertile island was directly relevant to either soil moisture or pH. This effect was more obvious with the increase of soil moisture and the decrease of pH value. In addition, the plant diversity was believed to be the main biotic driven factor for fertile island. Furthermore, the results also indicated that both the soil moisture and plant diversity would accelerate the accumulation of P and N, while the pH played the negative effect. The other main observation obtained was that the vegetation cover had positive effect on accumulation of C. As a result, the mechanisms related to drought and salinization could drive the difference of C-, N- and P-accumulation. The main findings also provided an effective reference to better understand the mechanism of fertile island and its desertification procedure in desert-oasis ecotone.