Diverse Patterns of Understory Plant Species across Different Types of Plantations in a Mountainous Ecosystem
China has been carrying out large-scale afforestation activities since the 1980s. Chongli District in Zhangjiakou City, Hebei Province, is a major corridor for wind and sand intrusion into Beijing from the Inner Mongolian Plateau. In order to prevent soil erosion and green the ecological environment of the Beijing–Tianjin area, the government has implemented key national greening projects such as the “Three North Protective Forests” and the construction of the “Saibei Forestry Farm”. After several years of afforestation, the species of artificial forests include spruce, camphor pine, white birch, tufted white birch, five-horned maple, tufted five-horned maple, Mongolian oak, tufted Mongolian oak, Hebei poplar, silver poplar, Beijing poplar, etc., with the heights of the seedlings ranging from 70 cm to 3 m, and the design of afforestation heights ranging from 4 m to 10 m; the shrubs include saffron grass and sandy cypress.
In this research, the mountainous regions situated in North China were chosen as a case study to examine two distinct types of plantation forests: monoculture (MON) and mixed (MIX). We analyzed the differences in plant diversity in different types of plantations in mountainous areas and explored the influencing mechanism of environmental factors on plant diversity under the forest. We evaluated (1) whether there are differences in understory plant diversity between two different types of plantations. (2) What are the differences in the composition of understory vegetation communities between two different types of plantations? (3) Does understory plant diversity respond consistently to environmental variables in pure and mixed forests?
2. Materials and Methods
The study area is located in Chongli District, Zhangjiakou City, Hebei Province (40°47′~41°17′ N, 114°17′~115°34′ E). This is the transition zone between the Inner Mongolian Plateau and the North China Plain, which belongs to the East Asian continental monsoon climate and is in the middle temperate sub-arid zone. The overall temperature in this area is low, the annual average temperature is −2 °C~12 °C, the winter is cold and long, the summer is cool and short, and the temperature difference between day and night is large. Eight percent of the total area of Chongli District is mountainous, with steep mountains, and the altitude ranges from 813 to 2174 m. Due to the protection of forests and artificial afforestation, the overall forest cover of the area exceeds 52%.
2.1. Plantation Situation
2.2. Vegetation Data
2.3. Environmental Factors at the Local Scale
Among the environmental factors at the local scale, because we controlled the other variables such as sunlight and terrain in the selection of plots, only soil physical and human disturbance were selected as local variables. Available phosphorus, soil organic matter, and the distance from the road were selected as key environmental indicators at the local scale. In each plot, the soil was randomly drilled three times with a soil drill, and the topsoil (0–20 cm) was collected, mixed into one soil sample, air-dried, and passed through a 2 mm sieve. The content of total soil organic matter and available phosphorus was determined using an element analyzer.
2.4. Environmental Factors at the Landscape Scale
We used Google remote sensing images with a resolution of 0.2 m in our study area to develop site and plot maps. Using the remote sensing image as the base map with a radius of 1 km around the center of all sample points, digital mapping was carried out according to the site research purpose and the land use composition of the study area on the basis of field verification. Landscapes with a minimum side length greater than 2 m were recorded as patches, and landscapes with a maximum side length of less than 2 m were recorded as linear landscapes or spots. Through manual digitization, the information obtained from the survey was converted into a unified GIS database, and after digitization was completed, layer stitching, correction, and registration were carried out, and the necessary repairs were implemented to obtain a complete spatial vector data layer that met the topological requirements. Three indicators were calculated at each sample site, including the patch density, landscape fragmentation, and Shannon diversity index value.
2.4.1. Landscape Fragmentation
where n is the total number of landscape types, Mi is the number of landscape patches of category i, and LA is the total area of the landscape within the study area.
2.4.2. Patch Shannon Diversity Index (SHDI)
where pi is the ratio occupied by landscape patch type i.
2.5. Biodiversity Index
where S is the number of species in the simple plot and Pi is the proportion of individuals of this species to the total number of individuals.
2.6. Statistical Analyses
In the process of data analysis, the species richness and Simpson diversity indices of plants in the monoculture and mixed forest groups were calculated. One-way ANOVA and the t-test were used to analyze the significance of the difference between the indices of understory plant diversity. NMDS analysis based on the Bray–Curtis distance algorithm was used to analyze the species composition. Stepwise linear regression was utilized to analyze the influence of organic matter and other factors on understory plant diversity. Linear regression analysis was performed on different types of forest understory plant diversity and different environmental variables. PAST 3.0 and SPSS 26.0 software were used for statistical analysis. ArcGIS 10.0 software was employed for the landscape survey and digitization. Fragstats4.0 software was utilized for landscape index calculation. Origin 2021 software was used for mapping.
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