Forest tourism is a vital avenue for promoting green consumption and constitutes a significant part of ecotourism in China. Its development offers substantial economic, social, and ecological benefits. Balancing regional economic growth and ecological conservation requires analyzing its spatiotemporal evolutionary patterns and driving factors. This study established a comprehensive and dynamic index system to evaluate the forest tourism development level (FTDL) in 18 prefecture-level cities in Henan Province from 2018 to 2021. Exploratory spatial data analysis and the geographical detector model were employed to examine spatiotemporal evolution patterns and identify the underlying driving mechanisms. The key findings are as follows: (1) the temporal evolution of FTDL in Henan Province exhibited “stratified heterogeneity and small fluctuations”, while its spatial distribution followed a “high in the southwest and low in the east” pattern; (2) over time, the spatial autocorrelation of FTDL in Henan Province shifted from positive to negative, with a gradual decline in correlation strength; and (3) eight dominant drivers categorized into four groups were identified, revealing a shift in the driving forces of forest tourism in Henan Province from environmental to economic factors. This study supports the formulation of political strategies to harmonize ecological conservation and economic development.

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.

As global climate change becomes more severe, forests, as important carbon sinks, are of great significance for mitigating climate change and protecting the ecological environment. The study took typical forest farms in southern China as the research area, constructed a multi-objective forest planning model based on Simulated Annealing Algorithm, and interfaced with geographic information systems. The aim is to achieve long-term scientific and rational arrangement of forest management measures to balance wood production and forest carbon storage. The results confirm that under the constraints of forest classification management and age structure adjustment of artificial forests, different optimization scenarios gradually stabilize corresponding logging intensity and forest resources from year 40 onwards. By assigning weights to the net present value of wood and carbon sequestration in the objective function, this study explores the impact of social preferences on spatial allocation schemes for forest management. When the carbon sequestration weight is 100%, the current savings are greater than those of other optimized scenarios starting in the 35th year, at roughly 8.8 × 10⁴ m³, and the current carbon storage is superior to those of other optimized scenarios starting in the 25th year, at 4.9 × 10⁴ t. In summary, this research can provide a scientific basis for actual forest management decisions, which is beneficial for improving forest carbon sequestration services, maintaining ecological balance, and promoting regional ecological sustainable development.

Forest tourism represents an important pathway for promoting green consumption, with forest parks serving as the primary platform for its development. The coordinated development of forest parks is therefore essential for achieving integrated economic, social, and ecological benefits. Investigating the coordination and coupling between ecological resilience and tourism economy in forest parks of the Yellow River Basin along with driving factors carried substantial practical significance for balancing regional economic development with ecological conservation. The present research developed an indicator system that was comprehensive and dynamic for assessing ecological resilience across forest parks in nine provinces of the Yellow River Basin during 2013–2023. To investigate patterns of spatiotemporal evolution and uncover underlying driving mechanisms, exploratory spatial data analysis was combined with a spatiotemporal geographically weighted regression model. The main findings are as follows: (1) The integrated levels of ecological resilience and tourism economy across the Yellow River Basin showed significant spatiotemporal heterogeneity. From north to south, a high–low–high spatial pattern was exhibited by ecological resilience, while a core concentration and gradient diffusion pattern was demonstrated by the tourism economy. (2) The coupling coordination level between forest park ecosystems and the tourism economy increased, with a growing number of provinces transitioning toward coordinated and near–dysregulated states, although pronounced regional disparities persisted. (3) Kernel density analysis indicated an overall improvement in coordination, accompanied by strong regional differentiation. The upper reaches displayed a unipolar leading pattern, while the middle and lower reaches showed multipolar differentiation and a pronounced “Matthew effect”. (4) Technological innovation emerged as the core driving factor, though its influence varied considerably across regions. Overall, these findings provide theoretical support and empirical evidence for policy formulation aimed at achieving a balance between ecological conservation and economic development in forest park systems.

Based on a balanced panel of nine provincial-level forest-park systems in the Yellow River Basin over 2013–2022 (90 province-year observations), this study measures the tourism eco-efficiency of forest parks and examines its spatiotemporal evolution and determinants. The unit of analysis is the aggregated forest-park system of each province (i.e., all registered forest parks within each province, aggregated to the provincial level), not individual parks. We combine a slacks-based super-efficiency (super-SBM) model—with four inputs, three desirable outputs, and three undesirable outputs—with the global Malmquist–Luenberger (GML) index, standard deviational ellipse (SDE) analysis, and a random-effects panel Tobit model. To remove price effects, monetary variables were deflated to constant 2012 prices; a small number of missing observations were completed by linear interpolation. The results show that: (1) Mean tourism eco-efficiency was 0.778, rising from 0.486 in 2013 to a peak of 1.077 in 2019, declining to 0.897–0.905 in 2020–2021 under the COVID-19 shock, and recovering to 1.143 in 2022. The mean GML index was 1.182, and mean technological change (TC) exceeded mean efficiency change (EC), suggesting that frontier shifts contributed more to measured productivity growth than efficiency change over the study period, although this conclusion rests on the pooled sample and is examined for robustness. (2) Eco-efficiency was spatially heterogeneous, with lower values in the upper reaches and higher values in the middle and lower reaches; the SDE was oriented east–west and its centroid shifted southeast-to-northwest by a modest distance. (3) At the 5–1% level, per capita GDP and tourism revenue share were positively associated with eco-efficiency and forest-park density negatively associated; highway mileage was positively associated only at the 10% level (p = 0.069); forest cover and employee density were not significant. Because the undesirable-output indicators are provincial industrial emissions allocated to forest parks by the tourism-revenue-to-GDP ratio, and because one regressor (tourism revenue share) is mechanically related to a desirable output, the associations reported here should be interpreted as observational, non-causal evidence. Policy implications are drawn accordingly.

Light environments within plantation forests vary significantly with stand degradation. This study investigated how light-related factors change along degradation gradients in Robinia pseudoacacia L. (black locust) plantations and how these changes influence understory herbaceous vegetation and regeneration. An R. pseudoacacia plantation at the Zhongmu State-owned Forest Farm, ZhengZhou, China was studied across three degradation levels (least degraded, moderately degraded, and severely degraded). Integrated analyses were employed to assess light–vegetation relationships under different stand densities. The results indicated that canopy openness (CO), photosynthetically active radiation (PAR), and light transmittance increased significantly with increasing degradation severity, whereas the leaf area index (LAI) declined. Specifically, differences in LAI among degradation levels were observed in all density stands. CO, TDR, and PAR showed degradation-related differences in medium- and high-density stands, while other light variables varied under specific density–degradation combinations. Furthermore, herbaceous biomass declined, canopy cover showed a fluctuation trend, and species diversity increased. Significant correlations were observed between multiple light parameters and herbaceous attributes. Overall, variations in the light environment were closely associated with understory vegetation dynamics. Moderate degradation was linked to higher herbaceous diversity, whereas regeneration density exhibited a non-monotonic response across degradation levels, with the lowest value under moderate degradation rather than a continuous decline under severe degradation.