The local wisdom of indigenous people in nature conservation plays a critical part in protecting the planet’s biodiversity and the overall health of the ecosystems. However, at the same time, indigenous people and their lands are facing immense threats through modernization and globalization. This study aims to systematically review and analyze the local wisdom of the indigenous people in nature conservation. The present study integrated multiple research designs, and the review was based on the published standard, namely the PRISMA statement (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). This study used Web of Science (WoS) and Scopus as the main databases in searching for the required articles. Through content analysis, this study can be divided into seven main categories: (a) forest management, (b) flora and fauna conservation, (c) food security, (d) water management, (e) land management, (f) weather forecasting, and (g) others. The findings offer some basics on how academics can adopt and adapt the existing local wisdom of indigenous people in nature conservation into the scientific framework and design to answer the Sustainable Development 2030 Agenda.

Despite growing urban electricity consumption, information on actual energy use in the household sector is still limited and causal factors leading to electricity consumption remain speculative due to urban expansion and its growing complexity, particularly in developing countries such as Malaysia. This study aims to examine the critical determinants of household electricity consumption by evaluating the patterns and flows of consumption and analysing relationships and their effects on electricity usage among 620 urban households in Seremban, Malaysia. Results suggest that the average urban household electricity consumption is 648.31 kWh/month; this value continues to grow with the increase in the household monthly income (r = 0.360; p < 0.01) and number of rooms (r = 0.360; p < 0.01) as quality of life improves. A large portion of electricity is allocated for kitchen/home consumption, followed by cooling and lighting. Multiple linear regressions revealed that married households with a high monthly income and living in spacious houses together with three to five people are important predictors of electricity consumption in Seremban. This study empirically identified that the number of rooms is the most critical factor of electricity consumption and strategies to increase energy efficiency, maintain resource sustainability and minimise greenhouse gas threat on the urban ecosystem are vital. Therefore, promoting low carbon initiatives for energy conservation and technology improvement and implementing policies in the domestic sector are essential to achieve the greatest potential energy consumption reduction in urban regions.

New tourism destinations and product supply are increasingly popular strategies among industry players to create competitiveness. The tourism industry has become more vibrant since globalization merged with technological changes, thus influencing human travel movements, lifestyles, and current trends. The purpose of the study was to systematically review and analyse the elements of new tourism destination products and the importance of sustaining the tourism industry. The following five primary methodological steps were used in the review processes: review protocol; formulation of research questions; systematic searching strategies based on identification, screening, and eligibility on Web of Science (WoS) and Scopus databases; quality appraisal and data extraction; analysis. Seven major themes were discovered, based on the thematic analysis: (a) Responsibilities and involvement, (b) Geography and resources, (c) Innovation, (d) Diversification, (e) Trend and travel pattern, (f) Sustainability, and (g) Marketing. The findings provide academics with a basic reference in scientific and design-related frameworks for examining new destinations and tourism products. The study also offers a guide for destination operators and industry stakeholders to be adopted for future destination development and management.

Urban air pollution has been a major concern due to its impact on global public health. Various techniques for monitoring urban air quality have been developed. However, there is currently a dearth of research on how effective bioaccumulators such as lichen are at monitoring urban air pollution. As a result, the purpose of this research is to investigate the use of U. misaminensis as a biological indicator for biomonitoring urban air quality in Malaysia. Three months were spent exposing lichen samples in three Malaysian cities (Kuala Lumpur, Penang, and Johor Bahru). The trace element content and vitality of the lichens were assessed. The results of this study revealed that U. misaminensis is an effective biological indicator for measuring 25 elements of air pollutants in metropolitan areas. They also revealed that all 25 elements accumulated in the urban area sample were greater than in the control sample. The vitality rate of lichens dropped in the urban area sample when compared with the control sample, indicating that an increase in elements in the air will impact the vitality rate of any biological component. In this study, two arguments are made: (a) Lichen is an excellent biological indicator, particularly for urban air pollutants such as potentially toxic elements; and (b) traffic is the primary contributor to urban air pollution; hence, the local government requires a better plan and design for urban areas to decrease air pollutants build-up.

Lichen is a well-documented useful biological indicator for monitoring air pollution using various methods such as the biodiversity of lichens. However, the use of lichen biodiversity to estimate air pollution levels in industrial areas, particularly in Malaysia, is still weak, and the determinants of its diversity are unknown. As a result, the purpose of this research is to analyse air pollution in Malaysia’s industrial urban area using the lichen biodiversity index and its determining factor. This research was carried out at Gebeng, Pahang, Malaysia. A total of 14 sample locations were chosen, each with three replication stations. The Lichen Biodiversity Index (LBI) approach was employed in this study to estimate the degree of air pollution in Gebeng. This study also investigated three potential determinants of lichen biodiversity: carbon monoxide (CO) concentration, relative humidity (%), and vehicle motor frequency (per hour). The LBI was plotted and analysed using the Geographical Information System (GIS) programme ArcGIS 10.8.1, and the determining variables were identified using Pearson’s Correlation Coefficient software PAST 4.03. This study discovered a total of 11 lichen species known as metropolitan lichen. The average LBI across Gebeng is 19.5 (moderate alteration). In the industrial region, CO has an inversely significant relation with lichen biodiversity (r = −0.7433), relative humidity has a significant relation with lichen biodiversity (r = 0.8249), and vehicle motors are not significant as a determining factor for lichen biodiversity (r = 0.2068). This study demonstrates that lichen, with its diversity of species in one place, can be utilised to measure and quantify the degree of air pollution in industrial areas. In addition to that, in the context of an industrial city, vehicle motors do not have a significant impact on lichen biodiversity due to the existence of other pollutants sources from industrial activities. Relative humidity is a sign of clean air and humid surroundings, which is good for lichen growth; meanwhile, higher CO concentration will restrict the growth of sensitive-type lichen and will only allow the resistant type of lichen to grow.

Rapid urbanization in China has reshaped retail spatial structures, creating challenges of accessibility and service equity. This study employs a Geographic Information Systems (GIS)-based analytical framework to examine the spatial distribution and driving mechanisms of retail outlets in Taiyuan, a resource-based transition city in central China. Using 2023 Point of Interest (POI) data and a 2 km × 2 km grid system, kernel density estimation (KDE), Average Nearest Neighbor (ANN) Analysis, Location Quotient (LQ), and spatial autocorrelation were applied to identify clustering patterns and functional specialization. The GeoDetector (Word version, downloaded 2025) model further quantified the explanatory power of twelve natural, social, economic, and transportation variables. Results reveal a polycentric retail structure, with high-density clusters in Yingze and Xiaodian districts and under-supply in Jiancaoping and Jinyuan. Population density, nighttime light (NTL) intensity, and school distribution emerged as the strongest drivers, while topography constrained expansion. By integrating GIS-based spatial statistics with GeoDetector, the study demonstrates a transferable framework for analyzing urban retail spatial patterns. The findings extend retail geography to transition cities and provide practical guidance for optimizing retail allocation, enhancing service equity, and supporting spatial decision-making for sustainable urban development.