Wanxia Peng

Changes in vegetation after 22 years' natural restoration in the Karst disturbed area in northwestern Guangxi, China

Abstract Variations of plant vegetation and spatial distribution were investigated in the areas of 4 types of typical disturbance, which had been under natural restoration for 22 years in the Karst area in northwestern Guangxi while the climax plant community was utilized as control. The slope scale and disturbance theory were used to study the plant diversity in the whole area and selected plots. It is clear that the disturbance had resulted in severe loss of plant species, and only 241 species of vascular plants that belong to 91 families and 206 genera survived in disturbed areas, accounting only for 26.6% of those in the natural reserve area. The consequent succession of 6 types of plant vegetation was sparse grass of rocky desertification, grass, shrub, liana-shrub, deciduous broad-leaved forest and mixed segment of evergreen and deciduous broad-leaved forest. The height, coverage, biomass and species diversity of plants decreased sharply with slope elevating, and the plant density appeared with normal distribution. Compared with the natural reserve area, all indices of plant vegetation in disturbed areas were much worse. Furthermore, different types of disturbance showed various affections on natural vegetative restoration, among which tilling after the whole slope was set on fire caused the worst impact and rocky desertification was the consequence, followed by depasturing after the whole slope was set on fire. Cutting was selective disturbance, and the vegetative restoration in the area with combination of cutting, grazing and setting on fire on the upper slope was relatively fast; however, it was even better in the area with combination of cutting and setting the upper slope on fire. In our studies, 4 strategies for vegetative recovery, using both natural and artificial approaches, were established, which were suitable for the Karst area in northwestern Guangxi.

Spatial pattern of woody plants and their environmental interpretation in the karst forest of southwest China

We investigated the spatial patterns of woody species and their relationships with environmental factors in the karst forest of southwest China. Data for 30 woody plant species with an importance value ≥ 5 and 15 environmental factors in 50 quadrats in a forest plot of 200 m × 100 m were used in this study. Two-way indicator species analysis revealed that the forest communities could be divided into 11 vegetation groups and classified into four ecotypes at the third divisional level. Detrended canonical correspondence analysis demonstrated that the variables significantly related to plant patterns were slope position, slope aspect, percentage of outcropping rocks, organic matter, total phosphorus, available nitrogen, and available phosphorus. Variation partitioning revealed that soil properties accounted for 21.0%, topographical features for 13.2%, and unmeasured variables and spatial processes for 47.7% of the variation in the species pattern, which suggest that both the deterministic factors (i.e., related to niche differentiation) and stochastic processes (i.e., related to dispersal limitation) are substantial determinants of the distribution of woody species. Our analysis suggests that picking the right late-succession species for a particular subregion or increasing soil nutrient content in poor habitats would promote species replacement in karst regions.

Spatial distribution of surface soil water content under different vegetation types in northwest Guangxi, China

Geostatistical and statistical analyses were combined to examine the spatial distribution of soil water content under four vegetation types during the dry season, in the peak-cluster depression in the karst region in northwest Guangxi, southwest China. The soil water content significantly increased from farmland to plantation, secondary forest, and primary forest; whereas the variation coefficients, the sill (C0+C), and total spatial variance increased, although the range decreased. The spatial distribution of soil water content in the different vegetation types had a high spatial autocorrelation. Different models produced a best fit for the semivariograms of the four vegetation types. Elevation and slope position were the primary factors influencing the spatial distribution of soil water content, with other key factors differing between the four vegetation types. Moreover, even though different specific factors influenced soil water content in the four vegetation types, the correlations and degrees of associations between the soil water content and these various factors differed. Therefore, the corresponding strategies for rational usage and management of water resources should be different for the four vegetation types in this region.

Spatial Heterogeneity of Soil Mineral Oxide Components in Depression Between Karst Hills, Southwest China

In karst regions, the spatial heterogeneity of soil mineral oxides and environmental variables is still not clear. We investigated the spatial heterogeneity of SiO2, Al2O3, Fe2O3, CaO, MgO, P2O5, K2O, and MnO contents in the soils of slope land, plantation forest, secondary forest, and primary forest, as well as their relationships with environmental variables in a karst region of Southwest China. Geostatistics, principal component analysis (PCA), and canonical correlation analysis (CCA) were applied to analyze the field data. The results show that SiO2 was the predominant mineral in the soils (45.02%–67.33%), followed by Al2O3 and Fe2O3. Most soil mineral oxide components had a strong spatial dependence, except for CaO, MgO, and P2O5 in the plantation forest, MgO and P2O5 in the secondary forest, and CaO in the slope land. Dimensionality reduction in PCA was not appropriate due to the strong spatial heterogeneity in the ecosystems. Soil mineral oxide components, the main factors in all ecosystems, had greater influences on vegetation than those of conventional soil properties. There were close relationships between soil mineral oxide components and vegetation, topography, and conventional soil properties. Mineral oxide components affected species diversity, organic matter and nitrogen levels.

Plant community characteristics and its coupling relationships with soil in depressions between karst hills, North Guangxi, China: Plant community characteristics and its coupling relationships with soil in depressions between karst hills, North Guangxi, China

Aims Our objective was to study plant community characteristics and coupling relationships between plant and soil properties in different ecosystems in depressions between karst hills. Methods We established 24 sample plots of 20 m × 20 m dimensions in four ecosystems (grassland, scrub, secondary forest and primary forest) in depressions between karst hills. We investigated the species composition and diversity characteristics of these ecosystems. We chose 35 indexes covering plant community and soil properties to study the relationships between plant factors and soil nutrients, soil mineral chemical components and soil microbes using analysis by principal component analysis (PCA) and canonical correlation analysis (CCA). Important findings Along succession from grassland to scrub to secondary forest to primary forest, the maximum number of species, genera and families with importance values (IV) 10.00 and maximum species diversity were in secondary forest, and the optimal community structure was in primary forest. The depressions between karst hills had high landscape heterogeneity, and different ecosystems were influenced by different factors. Soil microbes were the dominant influence in karst fragile ecosystems, followed by scrub. CCA elucidated a close relationship between species diversity and soil nitrogen, Al2O3 , Fe2O3 , microbial biomass carbon (C mic ), fungi and bacteria. Vegetation improvement and management practices should focus on such characteristics of different ecosystems when undertaking restoration and reconstruction of karst fragile ecosystems.

Spatial Patterns and Drivers of Microbial Taxa in a Karst Broadleaf Forest

Spatial patterns and drivers of soil microbial communities have not yet been well documented. Here, we used geostatistical modeling and Illumina sequencing of 16S rRNA genes to explore how the main microbial taxa at the phyla level are spatially distributed in a 25-ha karst broadleaf forest in southwest China. Proteobacteria, dominated by Alpha- and Deltaproteobacteria, was the most abundant phylum (34.51%) in the karst forest soils. Other dominating phyla were Actinobacteria (30.73%), and Acidobacteria (12.24%). Soil microbial taxa showed spatial dependence with an autocorrelation range of 44.4–883.0 m, most of them within the scope of the study plots (500 m). An increasing trend was observed for Alphaproteobacteria, Deltaproteobacteria, and Chloroflexi from north to south in the study area, but an opposite trend for Actinobacteria, Acidobacteira, and Firmicutes was observed. Thaumarchaeota, Bacteroidetes, Gemmatimonadetes, and Verrucomicrobia had patchy patterns, Nitrospirae had a unimodal pattern, and Latescibacteria had an intermittent pattern with low and high value strips. Location, soil total phosphorus, elevation, and plant density were significantly correlated with main soil bacterial taxa in the karst forest. Moreover, the total variation in soil microbial communities better explained by spatial factors than environmental variables. Furthermore, a large part of variation (76.8%) was unexplained in the study. Therefore, our results suggested that dispersal limitation was the primary driver of spatial pattern of soil microbial taxa in broadleaved forest in karst areas, and other environmental variables (i.e., soil porosity and temperature) should be taken into consideration.

Spatial distribution of tree species in evergreen-deciduous broadleaf karst forests in southwest China

Understanding the spatial distribution of tree species in subtropical evergreen-deciduous broadleaf karst forest is fundamental to studying species coexistence and karst species diversity. Here, complete spatial randomness and heterogeneous Poisson process models were used to analyze the spatial distribution patterns of 146 species with at least one individual per ha in a 25-ha plot in southwest China. We used canonical correspondence analysis (CCA) and the torus-translation test (TTT) to explain the distributions of observed species. Our results show that an aggregated distribution was the dominant pattern in Mulun karst forests; the percentage and intensity of aggregated decreased with increasing spatial scale, abundance, mean diameter at breast height (DBH), and maximum DBH. Rare species were more aggregated than intermediately abundant and abundant species. However, functional traits (e.g., growth form and phenological guild) had no significant effects on the distributions of species. The CCA revealed that the four analyzed topographic variables (elevation, slope, aspect, and convexity) had significant influences on species distributions. The TTT showed that not all species have habitat preferences and that 68.5% (100 out of 146 species) show a strongly positive or negative association with at least one habitat. Most species were inclined to grow on slopes and hilltops.

Plant community characteristics and their relationships with soil properties in a karst region of southwest China

In this study, we analyzed plant community characteristics and the relationship between plant and soil properties based on forest successional stages in depressions between karst hills. The secondary forests showed the maximum number of species, genera, and families with important values >5 and the highest species diversity, and primary forest was the optimal community structure. The arboreal layer played a dominant role in determining fragile karst ecosystem status, followed by shrubs, Al2O3, and Fe2O3. A close relationship existed between species diversity and soil organic C, total N, total P, Fe2O3, MnO, microbial biomass C, and microbial biomass P. Plant characteristics could be explained by the soil nutrient factors (21.6%), soil microbes (17.1%), soil mineral components (10.2%), and interactions among these variables (29.3%).