Root turnover is a key process of terrestrial ecosystem carbon cycle, which is of great significance to the study of soil carbon pool changes and global climate change. However, because there are many measurement and calculation methods of root turnover, the results obtained by different methods are quite different, and the current research on root turnover of forest ecosystem on the global regional scale is not sufficient, so the change law of root turnover of global forest ecosystem is still unclear. By collecting literature data and unifying the calculation method of turnover rate, this study integrates the spatial pattern of fine root turnover of five forest types in the world, and obtains the factors affecting fine root turnover of forest ecosystem in combination with soil physical and chemical properties and climate data. The results showed that there were significant differences in fine root turnover rate among different forest types, and it gradually decreased with the increase of latitude; the turnover rate of fine roots in forest ecosystem is positively correlated with annual average temperature and annual average precipitation; fine root turnover rate of forest ecosystem is positively correlated with soil organic carbon content, but negatively correlated with soil pH value. This study provides a scientific basis for revealing the law and mechanism of fine root turnover in forest ecosystem.

Agroforestry holds the key in providing alternative economically viable livelihood development and to support mountainous farmers to adapt to climate change. Innovative agroforestry interventions integrating animal production, horticulture etc into cropping systems exist that can help farmers improve yields and build resilience for supporting livelihoods particularly among marginal communities. But, the lack of knowledge, technical know-how and other information among the farmers are major barriers in adoption of agroforestry. Millions of the farmers of mountainous regions are already wrestling with water scarcity, which would be more severe in climate change scenario. The Himalayan regions are have been considered to be highly sensitive to climate change. Indeed, Innovative agroforestry interventions have the potential to conserve natural resources, improve productivity and provide resilience to climate change. The present paper highlights the need for developing innovative agroforestry interventions to promote various alternate livelihood options through diversification, adoption of high yielding varieties and development of innovative products from forest resources.  Of these spice based agroforetry, silvi-medicinal systems, Van silk cultivation, bamboo and ringal cultivation  and development and use of farm resources based products like  bamboo based composite structures, Seabuckthorn herbal tea, Ghingaroo juice  (Crataegus crenulata) and incense products etc holds a promising potential to be explored as better options for future scenario.

Every plant is significantly important in tackling climate change, including Makila (Litsea angulata BI) an endemic wood species found in the forest of Moluccas Provinces. Therefore, this research aimed to examine the role of the Makila plant in tackling climate change by measuring biomass content using constructing an allometric equation. The method used was a destructive sampling, where 40 units of Makila plant at the sampling level were felled, and sorted according to root, stem, branch, rating, and leaf segments. Each segment was weighed both at wet and after drying, followed by a classical assumption test in data processing, and the formulation of an allometric equation. The regression model was examined for normality and suitability in predicting independent variables, ensuring there were no issues with multicollinearity, heteroscedasticity, and autocorrelation. The results yielded a multiple linear regression, namely: Y = −1131.146 + 684.799X₁ + 4.276X₂, where Y is biomass, X₁ is the diameter, and X₂ is the tree height. Based on the results of the t-test: variable X₁ partially affected Y while variable X₂ partially had no effect on Y. The F-test indicated that variables X₁ and X₂ jointly affected Y with R Square: 0.919 or 91.9% and the rest was influenced by other unexplored factors. To simplify biomass prediction and field measurement, a regression equation that used only 1 independent variable, namely tree diameter, was used for the experiment. Allometric equation only used 1 variable, Y = −1,084,626 + 675,090X₁, where X₁ = tree diameter, Y = Total biomass with R = 0.957, and R² = 0.915. Considering the potential for time, cost, and energy savings, as well as ease of measurement in the field, the biomass of young Makila trees was simply predicted by measuring the tree diameter and avoiding the height. This method used the strong relationship between biomass, plant diameter, and height to facilitate the estimation of biomass content accurately by entering the results of field measurements.

The effects of climate change are already being felt, including the failure to harvest several agricultural products. On the other hand, peatland requires good management because it is a high carbon store and is vulnerable as a contributor to high emissions if it catches fire. This study aims to determine the potential for livelihood options through land management with an agroforestry pattern in peatlands. The methods used are field observation and in-depth interviews. The research location is in Kuburaya Regency, West Kalimantan, Indonesia. Several land use scenarios are presented using additional secondary data. The results show that agroforestry provides more livelihood options than monoculture farming or wood. The economic contribution is very important so that people reduce slash-and-burn activities that can increase carbon emissions and threaten the sustainability of peatland.

This paper employs a sample of Chinese A-share listed companies spanning from 2011 to 2022 to empirically investigate the influence of climate policy uncertainty on the corporate cost of debt, based on the theory of financial friction. We find that climate policy uncertainty significantly increases the corporate cost of debt, and the result is supported by robustness tests. To avoid biases arisen from endogeneity, this paper introduces an instrumental variable approach and propensity score matching method for verification. The endogeneity test results support the baseline regression results as well. Finally, this paper also discovers that financing constraints are the potential mechanism behind the impact of climate policy uncertainty on the corporate cost of debt.

Environmental Education (EE) programs are of crucial importance. EE are aimed at global citizenship to generate new knowledge and new, more participatory and conscious ways of acting in the environment. This study, therefore, wants to verify the effectiveness of a training intervention that is based on education on climate change issues and on the active participation of subjects in the dimension of the small psychological group. At the intervention 309 students took part, equally distributed by gender (52.1% males), 64.4% enrolled in primary school, 35.6% enrolled in lower secondary school. A quantitative protocol was administered to evaluate the effectiveness of the intervention. The study shows an increase in pro-environmental behaviors and their stability even after 15–30 days. The intervention seems to be effective in triggering pro-environmental behaviors and maintaining them in the following weeks. The results of this study highlight the need to develop environmental education pro-grams in schools to increase levels of knowledge and awareness on the issue of climate change.