Evaluating rural participation in wetland management: A contingent valuation analysis of the set-aside policy in Iran

Cross-regional ecological compensation under the composite index of water quality and quantity: A case study of the Yellow River Basin

The calculation of ecological compensation (EC) constitutes the core element of the EC mechanism, which is related to the practicability of the mechanism. Based on the comprehensive index of water quality and quantity, this study establishes a measurement method for EC across administrative divisions. First, the improved Nemerow pollution index (NPI) is adopted to assess the water quality of specific sections, while the water rights and GDP indicators are employed to characterize the water quantity of each section. Secondly, given the spatial relationship of each region within the basin, two compensation allocation schemes are established referring to the water intake and grey water footprint indicators. Finally, the EC amounts of each region in the Yellow River Basin from 2016 to 2021 are calculated using the proposed method. The results show that: (1) the improved NPI is significantly higher in the upstream than in the downstream, implying better water quality in the upstream region; (2) From 2016 to 2021, both Gansu and Ningxia exhibit negative EC coefficients, suggesting superior water quality in the upper section of these regions, while Henan Province demonstrates the opposite trend; (3) During the same period, Qinghai, Gansu, Shanxi, Shaanxi, and Shandong experience an EC deficit, while Ningxia, Inner Mongolia, Henan, and Yellow River Conservancy Commission exhibit an EC surplus. Using water quality and quantity indicators, this study includes the implementation of basin unification and regional environmental comprehensive management into the scope of responsibility of the basin government, which can effectively solve the drawbacks of unclear responsibilities of stakeholders and ineffective implementation of compensation in the basin EC.

Financial compensation for natural forest logging ban: Standard calculation based on willingness to accept

To alleviate the deteriorating environment and protect biodiversity, China has implemented a natural forest protection system, demonstrating the importance of sustainable forest management for ecological conservation and socio-economic development, including the complete cessation of commercial logging of natural forests. Financial compensation is adopted to increase farmers' enthusiasm within the commercial Logging Ban of Natural Forests framework. This study used the contingent valuation method and the Heckman two-stage model to explore farmers' willingness to participate in the Logging Ban of Natural Forests and the willingness to accept by survey data on 486 farming households. 72% of farmers are willing to join the Logging Ban of Natural Forests. Their willingness to accept is 517.95 yuan/ha per year, higher than the current state subsidy standard (225 yuan/ha per year). The key factors influencing willingness to accept include the education and degree of fragmentation of woodland and village collective willingness to accept. The age of the rural household head, the fragmentation of the forest, and the evaluation of the Logging Ban of Natural Forests policies have inhibited the increase of farmers' compensation. Farmers' assessment of the Logging Ban of Natural Forests policy only impacts the medium level of compensation. The age and the degree of forest fragmentation would affect the higher compensation amount. The results from this study suggest more financial sources and increased compensation standards are needed. The government should also strengthen ecological awareness and adopt different compensation standards for other groups to achieve sustainable forestry.

Inter-regional ecological compensation in the Yellow River Basin based on the value of ecosystem services

Ecological compensation in the Yellow River Basin aims to improve its ecological and environmental management capacity. Based on data on land-use changes in the Yellow River Basin from 2010 to 2020, this study used the equivalent factor method to assess the value of ecosystem services in the basin. This was measured at three spatial scales in the upper, middle, and lower reaches, encompassing; nine provinces and 72 cities. The priority and amount of ecological compensation were determined for the Yellow River Basin regions. Results show that (1) The total value of ecosystem services in the Yellow River Basin increased from 1798.317 billion yuan in 2010 to 1838.259 billion yuan in 2020. Grasslands had the highest total ecosystem service value in 2020, accounting for 46.11%. (2) The value of ecosystem services in the Yellow River Basin region is upstream > midstream > downstream. Qinghai Province has the highest value of ecosystem services among the nine provinces, and the level of economic development in each region is inversely correlated with the value of ecosystem services. (3) The ecosystem service value and the economic development level of the cities in the Yellow River Basin are positively and negatively correlated with the priority of ecological compensation, respectively. Among them, the cities in the upper reaches are the most urgent targets for national ecological compensation. (4) The total ecological compensation in the Yellow River Basin in 2020 was approximately 122.63 billion yuan. Further, the amount of vertical ecological compensation to be paid by the state was approximately 114.673 billion yuan, and the horizontal compensation to be borne between provinces was approximately 7.957 billion yuan. The findings of this study provide novel insights into improving ecological compensation in the Yellow River Basin regions.

Understanding Fishermen's Willingness and Preferences for Eco-compensation of Lake Conservation Projects: A Case Study From Nansi Lake Nature Reserve, China

Lake regions face a tradeoff between water environmental conservation and social development. Although lake conservation projects along with eco-compensation policies are considered the solutions to this problem, it is often controversial and unsustainable. Therefore, it is essential to understand the key stakeholders' willingness to participate in lake conservation projects under the different compensation schemes. In this work, we conducted a choice experiment to estimate fishermen's willingness and preference for the returning fishponds to lake (RFTL) project in the Nansi Lake Nature Reserve (NLNR). Socioeconomic, perception and spatial factors are employed to analyze the preference heterogeneity of fishermen. We employed conditional logit, mixed logit and latent class models to estimates the parameters of factor variables considering the heterogeneous preferences and choice randomness across respondents. The results indicate that on average, fishermen are unwilling to change the status quo and are most concerned about the subsidy amount and contract duration in compensation contracts. However, there is obvious spatial heterogeneity in fishermen's choice preference, mainly manifested in their habitation distance to a town and fishpond location in different zones of the NLNR. Specifically, perceptions of supply and demand for water yield and water quality services significantly influence fishermen's choice, but they have opposite effects. Moreover, we estimated marginal willingness to accept (MWTA) of attributes in compensation contract and measured compensating surplus (CS) to compare different eco-compensation policy scenarios. Our results contribute to designing targeted payment policies, and promote the effective implementation of lake conservation projects and regional sustainable development.

Monitoring and Landscape Dynamic Analysis of Alpine Wetland Area Based on Multiple Algorithms: A Case Study of Zoige Plateau

As an important part of the wetland ecosystem, alpine wetland is not only one of the most important ecological water conservation areas in the Qinghai-Tibet Plateau region, but is also an effective regulator of the local climate. In this study, using three machine learning algorithms to extract wetland, we employ the landscape ecological index to quantitatively analyze the evolution of landscape patterns and grey correlation to analyze the driving factors of Zoige wetland landscape pattern change from 1995 to 2020. The following results were obtained. (1) The random forest algorithm (RF) performs best when dealing with high-dimensional data, and the accuracy of the decision tree algorithm (DT) is better. The performance of the RF and DT is better than that of the support vector machine algorithm. (2) The alpine wetland in the study area was degraded from 1995 to 2015, whereas wetland area began to increase after 2015. (3) The results of landscape analysis show the decrease in wetland area from 1995 to 2005 was mainly due to the fragmentation of larger patches into many small patches and loss of the original small patches, while the 2005 to 2015 decrease was caused by the loss of many middle patches and the decrease in large patches from the edge to the middle. The 2015 to 2020 increase is due to an increase in the number of smaller patches and recovery of original wetland area. (4) The grey correlation degree further shows that precipitation and evaporation are the main factors leading to the change in the landscape pattern of Zoige alpine wetland. The results are of great significance to the long-term monitoring of the Zoige wetland ecosystem.