The rapid development of tourism in China has also caused a lot of energy consumption and serious environmental problems. In the context of sustainable development, low-carbon tourism has become the consensus of management departments, relevant industries, and academia. In environmental-related fields, DEA is considered as an excellent efficiency analysis tool because of its powerful optimization ability. The final variable of DEA method is weight. In order to avoid the influence of human factors with predetermined weights in tourism analysis, this paper studies the evaluation of tourism ecological efficiency based on DEA model. China’s overall tourism ecological efficiency showed a fluctuating upward trend, rising from 0.853 in 2018 to 0.906 in 2021. The national average efficiency over the past four years is 0.855, which is at a low level, indicating that the construction of tourism ecology is still in its infancy, and there is still much room for improvement in the future. As the tourism industry system involves many aspects, such as natural ecology, humanities, economy, and so on, it is an extremely complex system. The research on the ecological efficiency of tourism cannot simply rely on the knowledge system and thinking of a single discipline. Therefore, combined with the relevant theories and knowledge of tourism, management, industrial economics, regional economics, industrial ecology, and other disciplines, this paper makes a systematic study on the problems and countermeasures of Qiaozhai.

Urban trees play a dual role in enhancing landscape aesthetics and contributing to carbon sequestration. This study evaluated the biomass and carbon storage of eight common urban tree species in Zhengzhou, China, using organ-specific measurements and allometric growth models. The results revealed that biomass and carbon were primarily allocated to the trunk, followed by the roots, branches, and leaves; these results are consistent with previous findings. Acer buergerianum Miq. and Magnolia grandiflora L. demonstrated the highest per-tree carbon storage, while Styphnolobium japonicum (L.) Schott and Salix babylonica L. performed better in carbon storage per unit area. These patterns are linked to variations in species morphology, growth performance, and planting density. The study provides evidence-based recommendations for optimizing urban tree species selection to enhance carbon sink capacity. Future applications include integrating these results into urban planning strategies and long-term carbon monitoring systems, thereby contributing to low-carbon city development.

In the context of ecological civilization construction in China, interregional ancient trees are important natural and cultural resources, and it is vital that they are effectively protected and utilized according to their spatial distribution and regional conditions in order to provide a balance between local economic development and the ecological environment. This article analyzes the spatial heterogeneity of 26,842 ancient trees and explores the underlying natural and human factors by using geoinformatics–based techniques (i.e., the nearest neighbor index, kernel density, spatial autocorrelation, and the geographically weighted regression model) in Henan Province, Central China. The research findings conclude that: (1) The interregional ancient trees show positive spatial autocorrelation, and the aggregation effect in Western Henan is the most significant. (2) The growing environment and elevation exert a more obvious influence on the spatial pattern of interregional ancient trees. (3) The main influencing factors per region are different, for example, historical culture in Western Henan, water source and elevation in Southern Henan, and the growing environment in Eastern Henan, while ancient trees in Northern Henan have a weak relationship with each factor. This research facilitates political strategy making for sustainable development and the protection of interregional ancient trees.

Understory intercropping may improve soils, but its effects on bacterial communities in Idesia polycarpa plantations remain unclear. Five patterns were established in the Yellow River floodplain: pure I. polycarpa and I. polycarpa intercropped with Astragalus membranaceus, Ipomoea batatas, Salvia rosmarinus, or Arachis hypogaea. Soil properties and bacterial communities were assessed using 16S rRNA gene sequencing, LEfSe, FAPROTAX, and redundancy analysis. Intercropping significantly affected soil electrical conductivity, water content, organic matter, alkali-hydrolyzable nitrogen, available phosphorus, and available potassium, but not pH or bulk density. Salvia rosmarinus intercropping had 14.3 g kg⁻¹ organic matter and 123 mg kg⁻¹ available potassium; Arachis hypogaea had 14.5 g kg⁻¹ organic matter and 81.3 mg kg⁻¹ alkali-hydrolyzable nitrogen; and Ipomoea batatas had 11.9% water content and 13.6 mg kg⁻¹ available phosphorus. Alpha diversity did not differ significantly. PCoA suggested differentiation, but PERMANOVA based on Bray–Curtis dissimilarity was nonsignificant (r² = 0.329, p = 0.083); LEfSe identified treatment-associated biomarkers. Chemoheterotrophy and aerobic chemoheterotrophy accounted for 42.6–45.7% and 20.4–26.2%, respectively. Alkali-hydrolyzable nitrogen was associated with genus-level variation (r² = 0.440, p = 0.031). Understory intercropping improved soil conditions and may influence bacterial composition and predicted functional potential.

In the context of sustainable forest resource development, balancing ecological conservation with rational utilization is essential to achieving forest multifunctionality. Longyuwan National Forest Park, located in Luanchuan County, Henan Province, serves as a transitional zone between rural mountainous ecosystems and nearby urban settlements. Increasingly, this area faces urbanization pressures such as tourism expansion, infrastructure development, and intensified land use, which may threaten ecological stability. This study aims to evaluate the ecological sensitivity of the park and optimize its spatial functional zoning. Using the Analytic Hierarchy Process (AHP), we followed four key steps: constructing the hierarchical model, generating the pairwise judgment matrices, computing the weights and conducting the consistency check, and determining the final weights. A hierarchical evaluation framework was constructed using the AHP, incorporating twelve ecological indicators across geomorphological, hydrological, atmospheric, biological, and anthropogenic dimensions. Spatial analysis tools in ArcGIS 10.2, including reclassification and weighted overlay, were employed for single-factor and integrated sensitivity assessments. The results indicated that land-use type, elevation, and water-body distribution were the most influential indicators. Ecological sensitivity across the park was categorized into five levels: extremely high (0.02%), high (11.99%), moderate (73.53%), low (14.19%), and extremely low (0.28%). Based on these findings, four functional zones were delineated: ecological conservation (50.99%), core landscape (22.86%), general recreation (23.94%), and management and service (2.21%). This research provides spatially explicit insights into forest management under anthropogenic stress, offering theoretical support for the sustainable governance of forest–urban interface landscapes.

Understanding trade-offs and synergies among ecosystem services (ESs) along environmental gradients is crucial for sustainable oasis management. This study investigated four key ESs—carbon storage (CS), habitat quality (HQ), water yield (WY), and soil conservation (SC)—in three typical oases along water–heat gradients in arid northwestern China. The InVEST model was used to quantify ESs in 1990, 2005, and 2022, and Pearson correlation, geographically weighted regression, K-means clustering, and random forest models were applied to analyze service relationships, ecosystem service bundles (ESBs), and driving factors. The results showed that CS and HQ maintained strong synergies, while the WY–SC relationship shifted from weak trade-offs under drier conditions to stronger synergies under more favorable water–heat conditions. Geographically weighted regression revealed spatial heterogeneity and directional asymmetry in ES relationships. Four ESB types were identified: ecologically fragile zones, ecological transition or buffer zones, agricultural production zones, and core ecological source zones. Driving-factor analysis indicated that vegetation-related services were mainly associated with land-cover structure and vegetation growth, whereas hydrological and erosion-related services were more closely linked to precipitation, potential evapotranspiration, temperature, and topography. These findings support differentiated oasis management through ecological restoration, development regulation, water-saving agriculture, and strict ecological protection.