ABSTRACT As one of the international economic organizations, the G‐7 countries are composed of the world's leading industrialized countries. In addition, the role of the G‐7 countries in global warming is another issue that is constantly debated. Concerns have been raised about these very wealthy nations' capacity to manage their resources sustainably. Examining the factors that contribute to efficient resource management in these nations has grown in significance. The goal of this research is to look at how eco‐friendly innovations, clean energy transition, economic development, and trade affect effective resource management in the G‐7 nations. The material footprint is used as a gauge for efficient resource management. The Method of Moments Quantile Regression (MMQR) approach, which is a novel method, was used in this research to examine the G‐7 nations' yearly data for the years 1990–2019. Eco‐friendly technologies lower the material footprint in the G‐7 nations, according to MMQR findings. Results are statistically significant for the majority of quantile levels (0.1–0.7). Clean energy transition also reduces the material footprint of the G‐7 countries, with statistically significant results at all quantile levels. Economic development increases the material footprints of G‐7 countries; findings are statistically significant at all quantile levels. The material footprint is consequently increased by trade, and the results are statistically significant at various quantile levels (0.5–0.9). Additionally, the research tests robustness using other panel estimators and achieves similar findings. Lastly, the paper offers policy suggestions for G‐7 nations' efficient resource management.

ABSTRACT Trap cropping is a pest management strategy where a grower plants an attractive “trap crop” alongside the primary crop to divert pests away from it. We propose a simple framework for optimizing the proportion of a grower's field or greenhouse allocated to a main crop and a trap crop to maximize agricultural yield. We implement this framework using a model of pest movement governed by trap crop attractiveness, the potential yield threatened by pests, and functional relationships between yield loss and pest density drawn from the literature. Focusing on a simple case, we consider highly mobile pests that move freely across a small field or greenhouse, or within a larger field arranged in a repetitive layout (e.g. rows of trap plants). These pests are assumed to choose plants based solely on their relative attractiveness. We find that allocating 5%–20% of the landscape to trap plants is typically required to maximize yield and achieve effective pest control in the absence of pesticides. For highly attractive trap plants, growers can devote less space because they are more effective; less attractive plants are ineffective even in large numbers. Intermediate attractiveness warrants the greatest investment in trap cropping. However, the results are illustrative rather than prescriptive and could be sensitive to ecological and economic factors not included here, such as pest mortality, reproduction, spatial layout of traps, and additional costs associated with trap cropping. Despite these important caveats, the framework offers a transparent and tractable approach for exploring trade‐offs in pest management and can be extended to incorporate more complex pest behaviors, crop spatial configurations, and economic considerations.

ABSTRACT Land use conversion entails trade‐offs across multiple ecosystem services of wildlife. Wildlife is often characterized by spatiotemporal dynamics that affect this trade‐off. The aim of this paper is to examine the net benefits from changes in the land use composition, given the consequences for the benefits provided by a harvested migratory prey species. The study is applied to land use and roe deer hunting in Sweden. We examine the spatial dynamics of land use, predator populations, prey, and prey hunting, by developing a bioeconomic model that is estimated using a dynamic spatial‐lag model (dynamic SAR). The results show that a conversion of coniferous and broadleaf forests into grazing land increases game harvests and could offset the negative impact of large carnivores on hunting outcomes. Yet, such conversion is likely to be associated with a net social cost. In contrast, there are both increased game harvests and net economic gains from conversion of coniferous forests into broadleaves. Our findings are informative for policymaking on land use and wildlife management.

ABSTRACT Nature tourism based on the observation of sea turtles is a socioeconomic activity that promotes the conservation of endangered species. However, tourism can affect the nesting sites, drastically affecting the ecosystem function. In this study, we propose a socio‐ecological model to describe the interplay between tourists and a turtle population with temperature‐dependent sex determination and an arribada strategy. In the modeling process, we consider that tourists visiting an arribada nesting beach have different behaviors, depending on the region in which they are distributed. The analysis of the model shows that scenarios of sustainable tourism exist when some conditions over the parameters of the model are satisfied. Using numerical simulations of the solutions of the model, we show different scenarios of coexistence of tourists and turtles. However, when the parameters of the model are varied, the solutions of the model might show scenarios of unsustainable tourism. Finally, we discuss the overall results in terms of sustainable or catastrophic scenarios that can occur in the socio‐ecological system.

ABSTRACT The volatility and randomness of wind power generation pose significant challenges to grid integration and dispatching. Accurate wind power forecasting is crucial for ensuring grid security and optimizing dispatching strategies. This study proposes an ultra‐short‐term wind power forecasting model based on Variational Mode Decomposition (VMD) and an adaptive weighting integration mechanism. The model first employs VMD to decompose wind power time series into multiple Intrinsic Mode Functions (IMFs) to extract latent multiscale features. Subsequently, Convolutional Neural Networks (CNN) and Long Short‐Term Memory networks (LSTM) are utilized to independently model the IMFs, capturing spatial features and temporal dependencies. The outputs of CNN and LSTM are then dynamically weighted using an attention mechanism to adaptively enhance the representation of critical features. Finally, the predictions of CNN and LSTM are integrated using a Gradient Boosting Decision Tree (GBDT) meta‐learner to produce the final output. Experimental results on wind farm data from Xinjiang, China, demonstrate that the proposed model significantly outperforms traditional and state‐of‐the‐art forecasting methods in terms of accuracy and robustness, especially in handling the nonlinear and nonstationary characteristics of wind power.

ABSTRACT As human development progresses, the conventional energy systems predominantly reliant on coal and oil have not only facilitated socioeconomic advancement but also imposed substantial ecological pressures on natural ecosystems. The over exploitation and utilization of conventional fossil fuels have exacerbated threats to biodiversity, thereby triggering global environmental issues such as escalated greenhouse gas emissions, deteriorating air quality, and water pollution, which severely disrupt ecological equilibrium. To tackle these challenges, the promotion of a sustainable energy transition has become a worldwide consensus. This study capitalizes on the widespread promotion of clean energy sources such as photovoltaics and wind power to investigate the ramifications of energy transformation on regional human societies and migratory bird systems, employing an analytical framework titled Energy Structure Transformation‐Clean Energy Utilization‐Habitat Modification . Utilizing Geographic Information System (GIS) tools for data collection and analysis, this study evaluates the comprehensive niche width, relative niche width, and niche overlap of migratory bird habitats within the context of energy use transformation using an ecological niche model. Additionally, this study delves into the driving factors behind the impact of energy use transformation on the biodiversity of migratory bird sanctuaries, unveiling the potential implications of adjusting energy use structure for biodiversity conservation. The research findings consist of two main aspects. First, the implementation of a green energy transformation can effectively contribute to carbon reduction and enhance carbon sinks. Second, the utilization of clean energy has positive ecological implications that can facilitate improvements in migratory bird habitats, thereby supporting their nesting and reproductive activities. Based on these findings, the following policy recommendations are proposed. (1) Expand clean energy production capacity to facilitate carbon reduction initiatives. (2) Strengthen education and outreach programs on clean energy utilization to enhance public comprehension of carbon reduction strategies and promote the establishment of additional carbon sinks. (3) Enhance monitoring mechanisms for green electricity carbon sinks, providing incentives such as subsidies to farmers and consumers to advance biodiversity conservation efforts.

ABSTRACTCommunity‐based regulation of common‐pool resources like fish stocks, irrigation, and clean air, depends on establishing rules to prevent over‐exploitation and sanctioning free‐riders. However, persistence of these social arrangements can be challenged when some individuals enjoy greater access to the common‐pool resource because of differences in wealth. Here, we investigated how wealth inequality impacts the management of common‐pool resources in self‐regulating communities that sanction over‐exploiting free‐riders. We used a game theoretic model to isolate the effect of inequality on resource management. Specifically, we employed a model where players decide both how much to contribute to the resource and whether to sanction those who contribute less than the socially agreed‐upon amount. Through Nash equilibrium analysis, our results showed a U‐shaped relationship between wealth inequality and resource sustainability: high sustainable provision of resources was achieved under conditions of both high inequality and high equality. Resources were cooperatively maintained under equality via sanctioning, but maintained solely by the wealthiest individual under high inequality through privatization of resources. Increased severity of imposed sanctions expanded the range of wealth inequality in which resources were managed cooperatively through the voluntary sanctioning mechanism. Conversely, the increased cost of imposing sanctions decreased the range of wealth inequality where voluntary sanctioning was employed. The impact of wealth inequality on community‐management of common‐pool resources appears to defy simple generalizations about there being trade‐offs between equity and efficiency of resource use.

Recommendations for Resource Managers Measurement error in input variables has the potential to significantly affect estimates from systems of whole-stand yield models. Effects can be over- or underestimation of volume yields and financial returns or other forest attributes of interest. Careful crew training is paramount to ensure forest measurements remain consistent with the quality of the data used to fit the models.

Abstract The urban agglomeration in the middle reaches of the Yangtze river (MYRUA) is the second largest national urban agglomeration in China, with an excellent ecological foundation. As the construction of urban agglomerations accelerated towards both extension and connotation, land prices of various cities rose, and the contradiction in the demand and utilization of land resources became acute. Therefore, exploring the spatiotemporal evolution and driving mechanisms of land green utilization efficiency within MYRUA had positive significance. This article focused on 28 prefecture‐level cities in the MYRUA and measured their urban land green use efficiency (ULGUE) from 2006 to 2018 using the super slack‐based measure model with undesirable output (Super‐SBM‐U). Then, the improved Fixed Malmquist–Luenberger index was developed to improve the accuracy of dynamic efficiency analysis. Further, the internal and external driving factors were explored using the index decomposition and the spatial error model with fixed effects. The results showed that the land use mode of the urban agglomeration in the middle reaches of the Yangtze River was relatively green, but efficiency gaps still existed. Although the green total factor productivity of the whole cluster has improved by 3.30% a year on average, the excessive pursuit of technological innovation has led to the stagnation of urban land management in various cities, and there are numerous inherent contradictions in urban development. But at the same time, feasible economic development directions, industrial upgrading, high‐quality employees, land marketization, and positive environmental behaviors are conducive to the green and sustainable development of ULGUE. This article depicted the internal land use characteristics of the MYRUA from the perspective of spatiotemporal evolution and efficiency, providing a theoretical reference for the green development and coordinated management of urban agglomeration land.

Abstract Today, watersheds have changed under the influence of various environmental and human factors, and their expected performance has decreased in terms of meeting human needs, providing natural responses, and reducing environmental risks. However, evaluating health status and its impact on various factors has not been given enough attention. To this end, an attempt has been made to evaluate the health and ecological security of the subwatersheds of the Sharghonj Watershed using the pressure‐state‐response approach emphasizing flood‐related issues in the region. Toward that, 21 preliminary hydrological, anthropogenic, natural, and climatic criteria were selected. The preliminary variables were then finalized based on the results of the collinearity test and the data availability. The final variables were appropriately allocated to pressure, state, and response (PSR) indices, and associated health and ecological security indices were determined at the subwatershed scale. The results showed that the PSR ranged from 0.56 to 0.86, 0.46 to 0.84, and 0.35 to 0.96, respectively. Health and ecological security also varied from 0.53 to 0.83 and 0.27 to 1.01 in different subwatersheds. Eventually, the weighted mean PSR indices for the Sharghonj Watershed were 0.72, 0.67, and 0.73, respectively. The weighted mean health and ecological security indices were 0.70 and 0.68, respectively. The research results indicated that the dynamic of various variables related to floods considerably affects the health of the Sharghonj Watershed. It could be concluded from the results that the Sharghonj Watershed is highly flood‐susceptible, whose health and ecological security status was mainly controlled by the damages due to the destruction of residences and orchards by floods in the past few years. The results of the current study provide an appropriate roadmap to the decision makers and planners for the better management of the watershed resources in the region through allocating adequate financial support and implementation measures to priority subwatersheds.