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Forest as a vital natural resource in China plays an irreplaceable important role in safeguarding ecological security and human survival and development. Due to the vast territory, huge population and widespread forest landscape of China, forest management is a complex system involving massive data and various management activities. To effectively implement sustainable forest management, the big data technology has been utilized to analyze China’s forestry resources. Thus, the purpose of this paper is to clarify the role of big data technology in China’s forest management.

In this paper, the authors revisited the roles of big data in forest ecosystem monitoring, forestry management system development, and forest policy implementation.

It demonstrates that big data technology has a great potential in forest ecosystem protection and management, as well as the government’s determination for forest ecosystem protection. However, to deepen the application of big data in forest management, several challenges still need to be tackled.

Thus, enhancing modern science and technology to improve big data, cloud computing, and information technologies and their combinations will contribute to tackle the challenges and achieve wisdom of forest management.

A nature reserve set up in a disaster-stricken area can have various functions, e.g. as a place where biodiversity is favored and sometimes as a memory of a traumatic event. This study presents four different record-breaking disasters during 1992–2014 in Sweden, where the idea of setting up reserves has been advanced in the aftermath, but with slightly different results in relation to attitudes about nature conservation and modes of remembering. The phenomenon is primarily discussed against theory formation around disaster memorials and window of opportunity for change.

This paper uses a comparative case study approach. The cases are described through narratives on the basis of “grey” literature, i.e. documents from Swedish authorities in the form of evaluations, summaries from experience seminars, political decisions on the establishment of nature conservation or information material addressed to the public, and also media reporting.

The nature reserves will be reminiscent of the disasters since the natural regrowth will take decades but may also be accompanied by exhibitions in visitor centers, arts and plays, monuments and bureaucratic documents, all of which contribute to the memory. In all but one case, such artifacts are secondary in relation to the explicit goal of forest conservation. The local population's attitude to the reserve formation plays a big role for the plans to be implemented.

Foundation of nature reserves in the immediate aftermath of a disaster may have different functions for actors, affected people and interested public; some are exemplified and discussed here.

The main objectives of collective forest tenure reform in China are to stimulate rural households to invest in forestry management, protect the ecosystem and improve their livelihood. By constructing the unbalanced panel data of household investment, this study discusses the dynamic changes and influencing factors of household investment, which will lay a foundation for further research and provide a reference for decision-making.

Based on 3,500 samples from rural households in the provinces of Fujian, Hunan, Yunnan, Shaanxi, Jiangxi, Gansu, and Liaoning collected during field investigations from 2010 to 2015, this study conducts an empirical analysis of the household investment in forestry management and its factors with nonbalanced panels.

According to the analysis, the average investment in forestry management per household from 2010 to 2015 fluctuates greatly; the age of the householder, increased forestry area, subsidies, joining professional cooperatives, and forest tenure mortgage show positive effects on achieving the objectives.

The discussions are drawn from the study that supporting policies such as the forest tenure transfer system, professional cooperatives, financial services and subsidies should be further improved to sustain a positive in the forestry industry.

Forest insurance is a popular way to reduce the loss of forest disasters, so it is necessary to actively involve stakeholders. In the multi-agent simulation model, the government, insurance companies and forest farmers participate as three main stakeholders. The purpose of this paper is to mainly simulate the behavior of forest farmers under different environmental variables in order to find the important factors affecting the coverage of forest insurance, so as to improve the ability of forest farmers to resist risks in the face of disasters.

In the simulation process, the decision-making rule of a forest farmer’s purchasing behavior is a binary selection chain, which is created at random. Forest farmer agents who adapt to the environment will remain; on the contrary, those will be eliminated. The eliminated agents will renew their behavior selection chains through learning others’ successful behavior based on genetic algorithm. The multi-agent mode is set up on the Eclipse platform by using Java language.

The adjustment simulation experiments of insurance premium, insurance subsidy and forest area were carried out. According to the result, conclusions and suggestions are as follows: at present, government subsidies are necessary for the implementation of forest insurance; in the future, with the expansion of the insured forest area and the upgrading and large-scale operation of forest farms, forest farmers will be more willing to join forest insurance program, and, then, the implementation of forest insurance no longer requires government subsidies for forest insurance premiums.

This paper explores the impact of three important factors on the implementation of forest insurance.

This study seeks to provide a robust piece of evidence of forest depletion in Ghana and its associated driver intensities to inform national policy decisions towards achieving Sustainable Development Goal (SDG) 15 and beyond.

Using a representative sample size of 733 households, which was obtained with the aid of a structured questionnaire, a descriptive analysis is used to show the evidence of forest depletion. For robustness purposes, the geographic information system (GIS) is used to provide a piece of remote sensing evidence to substantiate the claim. In addition, an ordered probit regression model is estimated given the ranked nature of the responses to determine the drivers of forest depletion.

The results provide evidence that the urban forests in the Greater Accra Region (GAR) of Ghana have been depleted. Overall, 44% argued that the depletion of the forests is high, 30% indicated that the depletion is moderate, while 26% indicated that the depletion is low. Consistent with the literature, the ordered probit regression results show that human behaviour, climate change and institutional failure are the driver intensities of forest depletion in the Region. Besides, the authors find an increasing order effect for all three drivers. Using a descriptive analysis, majority of the respondents posited that human behaviour is the main driver intensity, followed by climate change and then institutional failure. This study recommends the need for education and advocacy, community participation, law enforcement, resource mobilization, modern adaptation strategies and internalization of externalities as a way of controlling the drivers of forest depletion.

The study uses remote sensing techniques to provide empirical evidence of protected forest depletion in the GAR, Ghana. In addition, an ordered probit regression is used to identify the driver intensities that explain the depleted protected forests in the region.

Background: Commodity-driven deforestation is a major driver of forest loss worldwide, and globalisation has increased the disconnect between producer and consumer countries. Recent due-diligence legislation aiming to improve supply chain sustainability covers major forest-risk commodities. However, the evidence base for specific commodities included within policy needs assessing to ensure effective reduction of embedded deforestation.

Methods: We conducted a rapid evidence synthesis in October 2020 using three databases; Google Scholar, Web of Science, and Scopus, to assess the literature and identify commodities with the highest deforestation risk linked to UK imports. Inclusion criteria include publication in the past 10 years and studies that didn't link commodity consumption to impacts or to the UK were excluded. The development of a review protocol was used to minimise bias and critical appraisal of underlying data and methods in studies was conducted in order to assess the uncertainties around results.

Results: From a total of 318 results, 17 studies were included in the final synthesis. These studies used various methodologies and input data, yet there is broad alignment on commodities, confirming that those included in due diligence legislation have a high deforestation risk. Soy, palm oil, and beef were identified as critical, with their production being concentrated in just a few global locations. However, there are also emerging commodities that have a high deforestation risk but are not included in legislation, such as sugar and coffee. These commodities are much less extensively studied in the literature and may warrant further research and consideration.

Conclusion: Policy recommendations in the selected studies suggests further strengthening of the UK due diligence legislation is needed. In particular, the provision of incentives for uptake of policies and wider stakeholder engagement, as well as continual review of commodities included to ensure a reduction in the UK's overseas deforestation footprint.