Rhizosphere and endophytic microbiota significantly affect plant growth and development by influencing nutrient uptake and stress tolerance. Herein, root and rhizosphere soil of Acacia species were collected and analyzed to compare the structural differences of the rhizosphere and root endophytic bacterial communities. High-throughput 16S rRNA gene sequencing technology was employed to analyze the rhizosphere and root endophytic bacterial communities. A total of 4249 OTUs were identified following sequence analysis. The rhizosphere soil contained significantly more OTUs than the root soil. Principal component analysis (PCA) and hierarchical cluster analysis indicated that bacterial communities exhibited significant specificity in the rhizosphere and root soil of different Acacia species. The most dominant phylum in the rhizosphere soil was Acidobacteria, followed by Proteobacteria and Actinobacteria, whereas the dominant phylum in the root soil was Proteobacteria, followed by Actinobacteria and Acidobacteria. Among the various Acacia species, specific bacterial communities displayed different abundance. We systematically described the core bacteria in the rhizosphere and root endophytic bacterial communities and predicted their relevant functions. The type and abundance of specific bacteria were correlated with the nutrient absorption and metabolism of the Acacia species. This study addresses the complex host-microbe interactions and explores the rhizosphere and root bacterial community structure of different Acacia species. These results provide new insights into the role of rhizosphere and root endophytic bacterial communities on the growth and reproduction of Acacia, thus informing future efforts towards sustainable development and utilization of Acacia.

The concept of National Forest Park (NFP) is mainly used in mainland China. Originating in 1982, NFP embodies a “top-down” concept and associated program launched by the Chinese government. It is aimed at promoting forest-based tourism and economic development under the premise of protecting forest resources. After 30 years of development, NFPs have made great achievements in protecting specific forest resources, promoting forest-based tourists, promoting regional economic development, and they have gained popularity worldwide. However, due to the fast pace of NFP expansion, lack of predictable planning and innovative thinking, and ineffective governance, some problems like overexploitation, scenic pollution, monotonous development patterns, and ecological degradation associated with NFP constrain its sustainable development. In order to solve these problems effectively, a holistic review of the status of NFPs in China is needed. To help meet this need, the origin, evolution, and current status of NFPs in China were analyzed. The presented research also included retrospective analyses of challenges and opportunities for NFPs sustainable development in China. Results show that from 1982 to 2015, the number of NFPs grew dramatically, and this development occurred in four phases. In addition, NFP development has been unbalanced in regional distribution. When analyzing the evolution of NFPs, the main issues to date have included failure to implement Master Plans in practice, unclear supervisory responsibilities, ambiguous classification, unbalanced distribution, destruction of natural resource and ecosystems, insufficient cultural protection, weak awareness of nature education, lack of resource statistics, monotonous planning, and weak marketing. Study findings can contribute to promoting the sustainable future development of NFPs and support the forest-based tourism industry.

The contradiction between the demand of urban economic development and ecological environmental protection is becoming more and more prominent, and the reasonable construction of ecological corridors is of great significance for the protection of urban ecosystems. Taking Changle District of Fuzhou coastal city as an example, this study proposes an ecological source identification method from the perspective of “structure-function” by combining Morphological Spatial Pattern Analysis (MSPA) and Remote Sensing Ecological Index (RSEI) methods, and constructs and optimizes ecological corridors by means of the model of Minimum Cumulative Resistance (MCR) and Circuit Theory. The results show that: (1) a total of 20 ecological sources were extracted based on MSPA-RSEI; (2) a total of 31 ecological corridors were extracted based on Linkage Mapper, including 8 Level 1 corridors, 13 Level 2 corridors, and 10 Level 3 corridors; (3) the Pinch Point and Barrier Mapper software was utilized to identify 6.01 km² and 2.59 km², respectively, as Level 1 “pinch points” and barrier points within the study area. The land use types of these areas were as follows: The majority of “pinch points” were forested (60.72%), while the majority of barrier points were composed of construction land (55.27%), bare land (17.27%), and cultivated land (13.90%). (4) the optimal width of the corridor was determined by using the buffer zone method and gradient analysis: 30 m for the Level 1 corridor, 60 m for the Level 2 and Level 3 corridors, and the average current density before and after the construction of the eco-corridor was increased from 0.1881 to 0.4992. The results of the study can provide a reference for the decision-making of the ecological construction of the Changle District and the coastal urban areas of eastern China.

Urban street greening is an important part of urban green infrastructure, and Green View Index (GVI) is widely used to assess urban street quality and ecosystem service value as an important indicator to quantify the perception of green street landscape from a pedestrian perspective. However, the distribution of street greenery is imbalanced. Therefore, to explore the differences in street greening levels within urban cities, we crawled streetscape data using the Internet to assess the spatial distribution patterns of urban street GVI using deep learning and spatial autocorrelation, and combined 11 surrounding environmental features with multi-source geographic data to further analyze the key factors influencing the spatial variation of block GVI using ordinary least squares, geographically weighted regression (GWR) models, and multi-scale geographically weighted regression (MGWR) models. The results show that the mean value of GVI in Fuzhou city is low (23.08%), with large differences among neighborhoods and a significant spatial autocorrelation. Among the regression models, MGWR has the best fit with an R² of 0.702, where the variables of NDVI, house price, accessibility of water bodies and parks, and the proportion of built-up land have a greater impact on GVI, and the factors do not have the same spatial effect size. The results can provide a scientific basis for promoting green visual equity in different blocks.

The rapid increase in urbanization has brought about a great deal of ecological problems, and thus the systematic protection of the environment is vital. Ecological security patterns are important for maintaining regional ecological stability and sustainable urban development. Human disturbance is a key factor affecting the stability and sustainable development of ecosystems. This paper constructs an ecological security pattern and evaluates the degree of human disturbance in Fuzhou City. Through a comprehensive analysis of both of these factors, the ecological priority restoration areas in Fuzhou were identified. The study shows that (1) there are 40 ecological source areas in Fuzhou, with a total area of 4556.48 km²; 83 ecological corridors, with a total distance of 179.33 km; and 30 ecological nodes. (2) The human disturbance degree score in the study area is between 0 and 0.8. The degree of human disturbance forms two larger major cores in Cangshan District, Gulou District, and Fuqing City. (3) The scores for the degree of human disturbance with ecological sources range from 0 to 0.42. The high-priority areas in the study area are distributed at the edges of ecological sources and form two high-scoring aggregation areas in Fuqing City and Jinan District. These corridors have a high degree of human disturbance with scores between 0 and 0.56. The I and II priority areas are mostly found in longer corridors in Fuqing City and Cangshan District near coastal or urban centers, and the III priority areas are mainly distributed in ecological corridors near the inland. The human disturbance degree scores of the nodes range from 0.01 to 0.27, and the nodes with higher grades were mainly distributed in the northeast, southeast, northwest and southwest of the study area.

Taking the Fuzhou National Forest Park as the research sample, this study uses the crawler tool to capture the comments of tourists on the network of Fuzhou National Forest Park, and uses ROST6.0 information mining software to analyze the emotional distribution and classification of word frequency. When analysed, the results showed that: (1) On the whole, tourists showed positive emotions towards Fuzhou National Forest Park, and the proportion of their neutral emotions and negative emotions was small. (2) Visitors’ favourite activities were “barbecuing”, “mountain hiking”, “leisure”, “walking”, “sightseeing”, “playing games”, “exercising”, “tourist-visit”, “entertainment” and “picnicking”. (3) Visitors’ favourite scenic spots in turn were “Banyan”, “Sakura blossoms”, “Peach Blossom”, “Bird Language Forest”, “Longtan pond”, “trees”, “Botanical Garden”, “waterfall”, “vegetation”, “reservoir”, “garden”, “museum”, “Bamboo forest” and “Plank road” (4) In the insufficiency aspect, the Fuzhou National Forest Park had the situation where there are too many people queuing up at certain times of the day. Finally, a set of public space management mechanism based on Big Data is summarized, which provides theoretical support for its management and optimization.