Revealing the mechanism by which land use influences ecosystem service function in karst urban watersheds is of great significance for social and economic development and ecological environmental protection. In this study, the Nanming River Basin, a typical karst basin in Guizhou Province, was used as an example. The spatiotemporal dynamic changes in land use in the basin during three periods from 2000 to 2020 were analyzed using ArcGIS, and the ecosystem service functions of the different land use types in the basin were evaluated using an integrated valuation of ecosystem services and tradeoffs (InVEST) model. This analysis led to three outcomes. (1) Forest, cultivated land, and grassland make up most of the land uses. The land use change was mostly dependent on the growth of construction land, which expanded by 13.07%. (2) The watershed′s water conservation function was significantly boosted during the study period. In contrast, the carbon stock function became slightly impaired, and the physical quality of both was regionally distributed as high in the northeast and low in the southwest. (3) The contributions of forest to total water conservation and carbon stock of the watershed are always the greatest, exceeding 57%, and the conversions of forest to construction land and cultivated land to forest are the two primary types of land use change in which the ecosystem service function was impaired and strengthened, respectively. The results of this study can provide important data support and scientific reference for land use structure optimization, soil and water resource exploitation, and sustainable ecosystem management in ecologically fragile areas.

Global climate change and human activities continue to threaten watershed ecosystems. The Jinsha River constitutes the upper reaches of the Yangtze River, so studying its ecosystem services (ES) is of great significance for maintaining ecological security and promoting ecological sustainability in the entire Yangtze River Basin. By using the integrated valuation of ecosystem services and trade-offs (InVEST) models and revised universal soil-loss equation (RUSLE) models, we evaluated five ecosystem services of water yield (WY), habitat quality (HQ), soil retention (SR), food supply (FS), and carbon storage (CS) provided by the Jinsha River Basin ecosystem from 2000 to 2020, as well as their spatial-temporal variations and driving factors. The results show three main features of this system. (1) From 2000 to 2020, each ecosystem service in the Jinsha River Basin exhibited different degrees of fluctuation, except for habitat quality, and each ecosystem service basically showed a spatial distribution pattern of high in the southeast and low in the northwest. (2) There were significant synergistic relationships between CS_SR_HQ and WY_SR_FS, and a significant trade-off between WY_CS. (3) The main driving factors of CS_SR_HQ were net primary productivity (NPP) and land-use type (LU), the main driving factors of WY_SR_FS were annual precipitation (PRE), LU, and rainfall erosivity (R), and the main driving factors of WY_CS varied considerably during the study period.

Wetlands are one of the most complex ecosystem types on the planet, and ecological sensitivity assessment is an important foundation for the scientific planning of wetland park systems. The Minjiang River estuary, located in the coastal city of Fuzhou, has outstanding regional characteristics in terms of its ecosystem and biodiversity. The nearby waters are among the richest in marine species in the world and the richest in offshore marine species at that latitude in the northern hemisphere. It has at least four indicators meeting the criteria for internationally important wetlands. In this study, the analytic hierarchy process (AHP) was used to determine the weights of factors, and the comprehensive ecological sensitivity of Minjiang Estuary National Wetland Park was evaluated using the weighted-overlap method by the Remote Sensing (RS) and Geographic Information System (GIS). An ecological sensitivity evaluation index system for wetland parks was constructed using Delphi, and then an ecological sensitivity assessment of Minjiang Estuary National Wetland Park was built. The sensitivities of different areas in the Minjiang Estuary National Wetland Park were divided five ecological sensitivity levels: extremely sensitive, highly sensitive, moderately sensitive, minimally sensitive, and insensitive. The results show that the riverbanks, beaches, canals, ponds, and surrounding areas were in the range of highly and moderately sensitive areas, while insensitive and minimally sensitive areas were distributed in the artificial landscape environments such as woodlands, farmland, and parks.

The lower reaches of the Jinsha River is the main distribution area of hot-dry valleys in China. While it suffers from frequent droughts, the spatiotemporal variation and driving forces of drought in this area under climate change are still unclear. The spatiotemporal variations of Temperature Vegetation Drought Index (TVDI) and drivers of drought were explored using MODIS land surface temperature and NDVI data from 2000 to 2020. The results are fivefold. (1) TVDI was highly correlated with soil moisture content at a depth of 0–7 cm, indicating that it can accurately reflect the drought situation in the study area. (2) The spatial variability of TVDI was highly heterogeneous, with a multi-year average of 0.59, and the drought level was mainly between normal and dry. (3) From 2000 to 2020, TVDI showed a slightly increasing trend. It increased in 63% of the study area, and significantly increased in 21% of the study area. At the same time, the area at the dry level increased by 14.5% in 2020 from the normal level in 2000. (4) Slightly different from the standard phenomenon of “dry gets drier, wet gets wetter”, we found that both dry and wet areas were becoming drier. (5) TVDI was positively correlated with annual mean temperature in 86% of the region, of which 43% of the region showed a significant correlation. The increasing temperature was the main driving force for the increase in drought in the study area. Our results can provide new insights into the spatiotemporally heterogeneous response of drought to climate change in the lower reaches of the Jinsha River.

Night tourism prolongs the activity time of tourism and leisure blocks, while tourism and leisure blocks provide activity places for night tourism. This study introduces the Kano model into the field of satisfaction research, makes improvements according to its advantages and disadvantages, builds an evaluation index system for night tourism satisfaction in tourism and leisure blocks, and combines that system with a questionnaire to determine the priority for optimizing each factor using the main and vice qualities, dispersion degree, and sensitivity comparison analysis. Based on the results, several optimization suggestions are proposed. The results show that: (1) Night tourism in Qinghefang groups mainly involves young people; (2) The overall satisfaction level is relatively high; (3) One attractive factor, seven one-dimensional factors, ten indifference factors, and three reverse factors in four layers (facility, service, experience, and project) were identified; (4) The priority for improvement should be service layer > facility layer > experience layer > project layer; (5) Background music, cultural connotation, festival projects, etc. are favored by visitors; and (6) Transportation, service attitude, and the sense of participation urgently require optimization.

As a pioneer demonstration area of tourism development in China, tourism has become the pillar industry of Hainan Province, and tourism activities have become the main disturbance impacting the socio-ecological system in Hainan Province. Analyzing the evolutionary trend of resilience and factors influencing the TSES in Hainan Province is crucial for exploring the local sustainable tourism development path. To achieve that, we first built the resilience evaluation index system for TSES in Hainan Province. Using the entropy weight method-gray correlation-TOPSIS comprehensive analysis model, an obstruction degree model was used to analyze the evolution of resilience and the factors influencing TSES between 2010 and 2020. The results indicate that the resilience of TSES in Hainan Province showed a steady upward trend from 2010 to 2020, and it has remained in the medium stage. Among the subsystems, the resilience of the social subsystem increased steadily from the low stage to the medium stage. The resilience of the economic subsystem was in the middle stage, rising at first and then declining. The overall resilience of the ecological subsystem declined slowly, showing a trend of downward-upward-downward-upward, and was in the medium stage. In terms of influencing factors among the three subsystems, the social subsystem had the highest degree of obstruction during 2010–2018, while the ecological subsystem had the greatest degree of obstruction in 2019–2020. For the degrees of obstruction by individual factors, there were 11 major factors, including the proportion of the added value of tertiary industry in GDP, and among them the factors belonging to the social subsystem appeared most frequently. Therefore, the resilience of TSES in Hainan Province is in the process of continuous development, but there is still much room for improvement. For improving the resilience of TSES, it is important to effectively identify the obstacles and take corresponding measures in a timely manner.

Based on the theory of resilience, this study utilized the panel data of the four major ancient capital tourist sites in Henan Province from 2009 to 2022 to construct a resilience evaluation index system that includes economic resilience, social resilience, cultural resilience, and ecological resilience. Then, with the help of the entropy-weighted TOPSIS method and an obstacle-degree model, the resilience levels of the ancient capital tourist sites in 2009–2022 were measured and the factors that act as obstacles were identified. The findings can be summarized in terms of Comprehensive Resilience, Subsystem Resilience and Factors Acting as Barriers. (1) Comprehensive resilience: This study reveals disparities in the development of overall resilience in ancient city tourist destinations. Zhengzhou emerges as the leader with the highest overall resilience score of 0.577, followed by Luoyang. In contrast, Kaifeng and Anyang exhibit relatively lower levels of resilience development. (2) Subsystem resilience: Zhengzhou consistently maintains a relatively high level of resilience with minor fluctuations, while Luoyang occupies a mid-range position and exhibits a stable developmental trajectory. Conversely, Kaifeng and Anyang have consistently operated at lower resilience levels, and are characterized by slower developmental progress. (3) Factors acting as barriers: Distinct subsystem indicators exert varying degrees of influence as barriers for resilience within the ancient city tourist destinations, referred to as the “barrier degree”. Economic resilience consistently maintains the highest barrier degree among the subsystems, while social resilience and cultural resilience demonstrate relatively similar barrier degrees. In contrast, ecological resilience exhibits the lowest barrier degree. The factors that obstruct the enhancement of resilience in ancient city tourist destinations exhibit remarkable consistency, with minimal annual fluctuations. Notably, the total tourist growth rate stands out as the primary impediment that constrains resilience development, and it consistently demonstrates a high barrier degree.

The construction and operation of onshore wind farms interfere with the succession of local plant communities, and the impacts on the local ecology and climate are of great concern. The study of the relationships between onshore wind farms and local ecology and climate, as well as the accurate assessment of the impacts of onshore wind farms on local areas, are the foundation for promoting the sustainable development of green energy. In this study, we summarize the existing research methods used for field data monitoring, remote sensing data inversion and numerical model simulation, and found that onshore wind farms have obvious impacts on the local vegetation index, near-surface temperature, wind speed, soil moisture, and other parameters. Onshore wind farms reduce the local soil moisture content, increase the near-surface air temperature, and significantly alter local wind speeds. They also cause a reduction in the local vegetation index, inhibition of plant growth, and an increase in the mortality rates of birds and bats inside the wind farms. However, onshore wind farms have positive effects on the plant communities outside the wind farms, especially in the downwind direction. Overall, there is regional variability in the results and the findings are not generalizable. The mechanisms by which the onshore wind farms influence the local climate, the impact of climate on local ecology, and the direct effects of onshore wind farms on local ecology have not been clearly and accurately explained. Related research is still needed to further improve the precision, accuracy, and continuity of observational data. The construction of modeling systems also needs to incorporate indicators such as land use type, local microclimatic indicators, and plant species. Based on these considerations, this review provides support for macroscopically understanding the impacts of onshore wind farms on climate and ecology.

Regional collaborative governance of the ecological environment is an important way to promote the sustainable development of urbanization, and local government competition is a characteristic institutional factor that is often ignored in the process of regional ecological environmental governance in China. This study selected the panel data of 278 prefecture-level cities from 2006 to 2018 in China, and used the spatial convergence regression model and the mediation effect model to analyze the spatial convergence of urban eco-efficiency (UEE) and its mechanism from the perspective of local government competition. The results show several empirical patterns. First, the UEE follows a tendency of convergence that narrows the regional gap of urban eco-efficiency, and spatial interaction factors are the keys affecting the convergence of UEE. Second, local government competition, as a characteristic institutional factor, plays an important role in promoting the spatial convergence of UEE, and the effect of administrative distance proximity competition is stronger than that of geographical distance proximity competition. The UEE increases by 0.114 percentage points when its degree of competitive pressure increases by 1 percentage point. Third, the competitive pressure leads to strict environmental regulation policies, which generally improve UEE and thus narrow its gap with advanced cities. Finally, local government competition has heterogeneous effects on urban eco-efficiency. Specifically, under the pressure of local government competition, the environmental regulations improve the UEE in the east and key environmental protection cities, while the central and non-key environmental protection cities experience the opposite effect. The results of this study suggest that if UEE is further introduced into the administrative performance evaluation index systems of local officials, the regional gap of environmental and economic development could be narrowed through ecological competition.

Urban agglomerations should meet the dual requirements of economic growth and green development, and there is currently an urgent need to improve the efficiency of green development. Therefore, we analyzed the impact of the Yangtze River Delta Urban Agglomeration (YRDUA) policy on the digital economy (DE) and green total factor productivity (GTFP) using the time-varying difference in difference model (DID). The marginal contribution of this study is an evaluation of the long-term effect of the YRDUA policy on green high-quality development. Based on the perspective of the “Porter Hypothesis”, this study examined the similarities and differences in the impacts of urban agglomeration on DE and GTFP. The results show that the policy promotes the urban DE index, but significantly inhibits urban GTFP. This means that the overall impact of urban agglomeration policy on green high-quality development in the Yangtze River Delta (YRD) is still in the “weak Porter Hypothesis” state, the technological innovation and efficiency improvement stimulated by urban agglomeration policies are not enough to significantly improve GTFP, and the “strong Porter Hypothesis” is not tenable. In addition, the heterogeneity analysis shows that the policy has a more obvious role in promoting the green high-quality development of central cities, large and medium-sized cities and innovative cities. The level of urban public service supply shows a threshold effect. When it develops to a certain scale, the urban agglomeration policy has significant positive impacts on both DE and GTFP.

Improving energy efficiency is crucial for achieving the carbon peaking and carbon neutrality goals. The digital economy, which is characterized by big data, artificial intelligence, the internet of things, and a new generation of mobile Internet, has quietly penetrated all aspects of the economy and society, profoundly changing the means of production and lives of human beings. Digital technologies have great potential to improve the global energy system's security, productivity, efficiency, and sustainability. Based on the panel data of 30 provinces in mainland China from 2006 to 2021, this study divided energy efficiency into total and single factor energy efficiency. The two-way fixed-effect model and the Driscol-Kraay method were used to adjust the standard error test in order to examine the impact of digital technology represented by industrial robots on energy efficiency and its path mechanism. Studies have shown that digital technology can significantly improve total factor energy efficiency and reduce energy intensity per unit of GDP. This conclusion was found to be still valid after the robustness test using feasible generalized least squares, time-varying difference in difference and fixed effect space Durbin model. The results of the mechanism test show that digital technology can improve energy efficiency by increasing the degree of industrial virtual agglomeration and the channels of foreign direct investment. This paper provides a valuable discussion on how information technology advances can improve energy efficiency in the era of the digital economy. The conclusions will help relevant market players to formulate policies and measures and corporate strategies to improve energy efficiency. At the same time, it also deepens the theoretical understanding and mechanism path of digital technology's impact on energy consumption.

With the progressive aging of China's population, the contradiction between the supply and demand of elderly care service facilities is increasingly prominent. This study takes Wuxi City as the research area, and evaluates the accessibility characteristics of the elderly service facilities in Wuxi City by using geographic statistics, buffer analysis, Gaussian two-step mobile search and other methods. It then analyzes the spatial distribution and supply and demand of the elderly service facilities in Wuxi City, and introduces the XGBoost algorithm to calculate the factors influencing the distributions of different types of elderly services. The results show that the distribution of home-based and institutional endowment resources in Wuxi is spatially heterogeneous, but there are problems of mismatch between supply and demand and uncoordinated regional development. The accessibility of endowment services varies greatly in different regions, and the number of hierarchical endowment institutions is relatively small. The distribution of community home care service stations is relatively more equitable, but still does not match the size of the elderly population. There are obvious differences in the factors affecting the distributions of nursing institutions and community home nursing service stations. The distribution of nursing institutions is affected by transportation infrastructure, the size of the elderly population, the number of medical resources, the environment, economic level and other factors; while community home care is mainly affected by the size of the elderly population. In order to better meet the elderly service needs of residents, Wuxi needs to increase its investment in elderly service facilities and take various measures to promote the development and improvement of its elderly service facilities.

This study aims to survey the literature and factual evidence on the nexus between deforestation and agriculture through an assessment of the potential impacts of climate change in the context of the world, India, and the Western Ghats. The Western Ghats region was chosen for this study because of its deep ecological significance. A few underlying themes were created and findings were documented under each theme that ranged from the causes of deforestation, the transformation of forest land for agriculture, the nexus between agriculture, deforestation and climate change, climate-driven agricultural vulnerability and the reconciliation of forest protection with agriculture. These findings suggest that shifting agriculture has been a dominant source of deforestation. The primary climatic impacts on agriculture are seen through crop yield falls. India's arid and semiarid tropical regions have witnessed high climate-driven agricultural sensitivity. This could be on account of the fact that India's tropical forests have witnessed high deforestation. The presence of higher tree densities in areas under Joint Forest Planning and Management in the Western Ghats create the potential for sparing remaining land areas for non-forest uses such as agriculture.

Earthquakes are one of the major natural disaster threats worldwide and directly cause substantial economic losses and many casualties every year. Research on the resource and environmental carrying capacity in earthquake-prone areas is urgently required for regional earthquake relief efforts and post-disaster reconstruction. This study considered Ganzi Tibetan Autonomous Prefecture (Ganzi Prefecture) in Sichuan Province, China, focusing on the impact of the Luding 6.8 Magnitude Earthquake in Ganzi Prefecture in 2022. An evaluation system for the resource and environmental carrying capacity of earthquake-prone areas was established. A total of 23 indicators were selected that cover ecological, social economical, and geological aspects, and the weight of each index was determined by the Analytic Hierarchy Process. The relative ranking of the resource and environmental carrying capacities of each county and city were calculated using the weighted Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Consequently, the post-disaster reconstruction strategy of Ganzi Prefecture was evaluated and analyzed. The results show that the resource and environmental carrying capacities of each administrative area differ regionally. Evidence shows that the resource and environmental carrying capacity in southeastern Ganzi Prefecture is generally higher than in the northwest, owing to the joint influence of the social economy and ecological and geological environment. This study provides carrying capacity assessment data and support methods for earthquake-prone areas.

Ecological security and its patterns are hot topics for regional ecological protection. In the subtropical coast mountainous area with high precipitation, complex topography, and frequent typhoons, does the construction of a Power Transmission Line (PTL) affect local ecological security? Taking Fujian Tangyuan PTL as an example, this study examined changes in the Ecological Security Pattern (ESP) at regional and local scales by using Morphological Spatial Pattern Analysis (MSPA), Minimum Cumulative Resistance (MCR) and the Gravity model. The results showed that within the PTL timelines (before, during and after building the PTL), the ecological source area occupied 14.21%, 11.79% and 14.11% of the whole research region; while the important eco-corridors numbered 20, 21 and 16, respectively; and the eco-nodes numbered 168, 123 and 227, respectively. At the local scale, in the PTL buffer space (2 km from the PTL on either side, i.e., the potential ecological impact zone) within the timelines (before-during-after building the PTL), the ecological source area occupied 39.78 km², 27.44 km² and 29.88 km², respectively, and the eco-corridor lengths were 50.78 km, 44.36 km and 67.18 km with 13, 7 and 25 eco-nodes, respectively. Clearly, during the building of the PTL, the ecological “source-corridor” decreased at first and gradually recovered after the construction, while the challenge to the ecological safety from the PTL occurred at the local scale. The results of this study provide a method for evaluating the ecological integrity disturbance by linear projects and scientific protection strategies are proposed.

The research was conducted within the Kulekhani Watershed with the objective of examining changes in Land Use Land Cover (LULC) dynamics and soil erosion across various LULC categories spanning from 2000 to 2020. The findings regarding the LULC classification in the Kulekhani Watershed revealed a steady rise in forested land, escalating from 60.72% in 2000 to 62.43% in 2010, and ultimately reaching 64.75% of the total area by 2020. The extent of water bodies exhibited a marginal increase from 1.07% in 2000 to 1.08% in 2020. Correspondingly, barren land expanded from 0.21% to 0.26%, eventually reaching 0.35% over the successive time intervals. Conversely, agricultural land dwindled over these periods, comprising 38% in 2000, 36.24% in 2010, and ultimately declining to 33.82% by 2020. The utilization of the Revised Morgan–Morgan–Finney (RMMF) model for soil loss estimation demonstrated a declining trend in weighted average soil loss during the years 2000 to 2010, followed by a slight increase between 2010 and 2020. The calculated soil loss values were recorded as 8.64 t ha^–1 yr^–1, 7.12 t ha^–1 yr^–1, and 7.30 t ha^–1 yr^–1 for the years 2000, 2010, and 2020 respectively. Similarly, the erosion susceptibility map illustrated a rising pattern in the very low-risk soil erosion zone from 2000 to 2020, primarily prominent within forested regions, while exhibiting a low to moderate susceptibility in agricultural zones. Moreover, barren areas displayed a moderate to high susceptibility to soil erosion. To address these concerns, future endeavors are recommended to encompass afforestation initiatives in barren regions, implement conservation farming practices in agricultural areas, and adopt appropriate measures for road stabilization.

The High-Altitude Bhagirathi Valley (HA-BV) in Garhwal Himalaya is a region of significant ecological and cultural importance, which is vulnerable to the impacts of climate change. Community-based approaches to climate change adaptation (CB-CCA) have emerged as an important strategy to build resilience and sustain the local community′s economic and social well-being. This paper aims to examine the CB-CCA and livelihood security initiatives in HA-BV, focusing on the strategies implemented to address the challenges posed by climate change. The paper analyzes the successes and challenges of these approaches and contributes to the discourse on sustainable development in the Himalayan region. The study findings can inform future efforts to build climate resilience and livelihood security in similar contexts. This research demonstrates the potential of CB-CCA to enhance the adaptive capacity of vulnerable communities and provides insights into the co-benefits of sustainable development and climate resilience in HA-BV.

To investigate the potential impact of emission reduction measures on ozone (O3) formation under the carbon neutrality target, we examined the changes in O₃ concentration and their sensitivity to various parameters in the urban and suburban areas of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). In this study, we used the Weather Research and Forecasting (WRF), the Sparse Matrix Operator Kernel Emissions (SMOKE) and the Community Multi-scale Air Quality Modeling system (CMAQ) air quality model to simulate O₃ formation in three key years of 2020, 2030 and 2060, based on the Ambitious-pollution-Neutral-goal scenario data from the Dynamic Projection for Emissions in China (DPEC) model. The decoupled direct method (DDM) module embedded in CMAQ was used to calculate the first-order sensitivity coefficients of O₃ to nitrogen oxides (S_{O3_NOx}) and volatile organic compounds (S_{O3_VOC}). The results show several important trends in the O₃ concentrations and sensitivity. (1) For the changes in O₃ concentrations, in terms of different seasons, the O₃ concentration in the GBA region shows an increasing trend in winter in both 2030 and 2060 compared to 2020. In terms of different cities, the O₃ concentration in Shenzhen shows a significant increasing trend compared to the other cities. (2) For changes in O₃ sensitivity, S_{O3_NOx} shows an increasing trend, with the negative area declining and the positive area increasing. In 2030, the negative absolute value of S_{O3_NOx} is reduced, indicating that the NO_x titration effect will be weakened. In 2060, S_{O3_NOx} becomes positive in most areas of the GBA region. For S_{O3_VOC}, the future scenario shows positive values throughout the study area for all years, but a decreasing trend.

Satellite remote sensing provides the changes information of Earth surface on large spatial scale in a long time series and has been widely used in ecology. However, the possible impact from human activities generally occurs on a smaller spatial scale and could be detected in a longer time, which requires the remote sensing data having the both higher spatial and temporal resolution. Meanwhile, the development of the spatiotemporal data fusion algorithm provides an opportunity for the requirements. In this paper, based on deep learning, we proposed a residual convolutional neural network (Res-CNN) model to improve the fusion result considerably with brand-new network architecture to fuse the NDVI retrievals from Landsat 8 and MODIS images. Experiments conducted in two different areas demonstrate improvements by comparing them with existing algorithms. The model performance was evaluated by a linear regression between predictions and observations and quantified by determination coefficients (R²), regressive ecoefficiency (slope). The two excellent models, ESTARFM and FSDAF, were compared with the new model on their performance. The results showed that the predicted NDVI had the higher exploitational on the variability in the Landsat-based NDVI with the R² of 0.768 and 0.807 at the urban and grassland sites. The predicted NDVI was well consistent with the observations with the slope of 1.01 and 0.989, and the R-RMSE of 95.76% and 93.58% at the urban and grassland sites respectively. This study demonstrated that the Res-CNN model developed in this paper exhibits higher accuracy and stronger robustness than the traditional models. This research is full implications because it not only provides a model on the spatio-temporal data fusion, but also can provide the data of a long time series for the management and utilization of agriculture and grassland ecosystems on the regional scale.

Based on the existing research on natural resource accounting, this study attempts to further enrich the administrative attributes of natural resource accounting. Through the analysis and comparison of previous publications, a mechanism for improving the construction of the natural resources report is proposed, with the dual aims of meeting the Chinese government's supervision and audit demands in resource administration and overcoming the deficiencies of the Natural Resources Balance Sheet (NRBS) in scientific research and actual practice. By analyzing the influences of human factors on natural resources, the information structure and accounting contents of the natural resources report are given. The results demonstrate that the natural resource report system is reasonable and feasible in terms of its logical and theoretical basis. The framework of the system consists of four parts: the statement of the basic situation of natural resources, the statement of the protection and restoration of natural resources, the statement of resource use, and the statement of the degree of destruction of the natural resources. The results of this study provide reference statements for the NRBS, the natural resource quality statement, the protection and restoration policy statement, the protection and restoration funding statement, the natural disaster statement, and the registration form of resource destruction cases. This study provides a reference for the innovation of the natural resource administration system, in which the supervision and administration of natural resources are the main criteria.