Ecological conservation red line (ECRL) is gaining increasing academic attention as delimiting the minimum space scope of ecological protection and the bottom line of ecological security. Taking Nanjing as a case study, we divided the territory into ecological and non-ecological redline areas (ERAs and NERAs, respectively). This paper highlights two key research issues based on the 2005, 2010, 2015 and 2018 annual remote sensing data: (i) quantitative analysis of the Ecological Redline Policy (ERP) validity by conducting a horizontal comparison of the ERAs and NERAs; and (ii) exploration of the land-use transitions and spatial pattern changes affecting ecosystem service value (ESV). Results showed that delineating ECRL could effectively slow down the decline rate of ESV. The trend of eco-quality deterioration was greater than eco-quality improvement in Nanjing, presenting an ESV that declined slightly in the whole. According to our findings, we suggest that reasonably increasing eco-lands (woodland and water area) and decreasing construction land will enhance the regional ESV. Meanwhile, promoting the transition from production space to ecological space and depressing the encroachment of living space on other space types, will be instrumental in mitigating the ESV decline. The results of this study are expected to provide valuable implications for spatial planning and sustainable development in Nanjing.

As environmental sustainability pressures intensify and AI technologies rapidly evolve, the integration of AI into green marketing strategies has become increasingly prominent. This systematic review examines the application of artificial intelligence (AI) in green marketing, with a focus on studies published between 2020 and 2024. This review addresses two key research questions: the effectiveness of different types of artificial intelligence in green marketing applications, and the role of AI in supporting enterprise development in this context. A comprehensive search of SpringerLink, Web of Science, and Google Scholar initially identified 200 records. After duplicate removal and multi-stage screening, 47 articles were deemed to meet the inclusion criteria. Only peer-reviewed journal articles in English were included. Study quality was appraised using established evaluation criteria to ensure methodological rigor. Among these, Thinking AI, Mechanical AI and Feeling AI appeared in 45 studies, 23 studies and 15 studies, respectively. The selected studies span 34 journals and 28 countries, reflecting both the rising academic interest and the interdisciplinary character of this emerging field. However, this review also identifies notable deficiencies in the current body of work. This review integrates these AI types with the 4Ps framework to form a concise conceptual mapping of their respective functions. Although AI has been positioned as a powerful driver of green marketing, research remains fragmented, with limited assessment of AI’s sustainability, weak data and ethical safeguards, and insufficient long-term and global perspectives. This underscores the need for a deeper and more systematic understanding of AI to better achieve the goals of green marketing and improve its practices.

The Asia-Pacific Network for Sustainable Forest Management and Rehabilitation (APFNet) Fellowship Program, established in 2008, aims to develop future leaders in sustainable forest management (SFM) within the Asia-Pacific region. This study represents the first systematic evaluation of the APFNet Fellowship Program, focusing on its effectiveness in building capacity for forest conservation and management. A mixed-methods approach was employed, combining quantitative pre- and post-program surveys with qualitative interviews and case studies of fellows. Quantitative analysis of survey data from 57 fellows revealed significant improvements in knowledge and skills related to forest conservation and sustainable development. Paired-sample t-tests showed statistically significant increases in the knowledge and abilities of participants, with an average improvement of 23% across key survey domains (t = 5.24, p < 0.05). The analysis also indicated that 95% of participants perceived the program to be highly relevant to their career goals and sustainable development objectives, with 87% reporting strong satisfaction with the quality of learning opportunities. Qualitative data from semi-structured interviews and focus groups revealed that while fellows appreciated the academic rigor and practical training, challenges such as financial limitations, language barriers, and institutional support issues were prevalent. Despite these challenges, fellows expressed strong commitment to applying their training to sustainable forestry practices in their home countries. This study highlights the critical role of the APFNet program in nurturing the next generation of forestry leaders in the Asia-Pacific region. The findings provide a foundation for future evaluations, highlighting the need for continued program refinement to address the identified challenges and maximize the long-term impact on forest conservation.