Exploring Paths for the High-Quality Development of Forest-Based Wel ness Industry:A Case Study of Sichuan Province

The forest-based wellness industry,as a rapidly growing sector that integrates various business forms with extensive coverage and an extended industrial chain,is undergoing rapid development due to the increasing aging population and people's suboptimal health conditions.As a forerunner in developing the forest-based wellness industry,Sichuan province is known for its early development,proactive efforts,diverse models,and significant impact in this industry.It has achieved certain milestones in terms of top-level design,pilot demonstration,standardized guidance,and public awareness campaigns to promote the development of this industry.Therefore,this paper utilizes Sichuan as a case study to systematically summarize and analyze the key practices made by the province in promoting the rapid development of the industry by investigating the development trajectory of the forest-based wellness industry.Additionally,it examines the development trends of this industry from the perspectives of supply,demand,and consumption.Finally,this paper proposes several measures to facilitate the high-quality development of the forest-based wellness industry.These measures encompass nurturing specialized talent in forest-based wellness,enhancing market players'capabilities in this domain,conducting extensive research on technologies that promote this industry,actively seeking support from relevant policies,and promoting integrated development across diverse sectors.

Trends in Markets for Forest-Based Products and Consequences for Selected Countries

The forest sectors in many regions and countries are facing a need to change their structure, due to the development of new markets, emergence of new competitors, and shifts in production and consumption patterns for forest products. This article focuses on recent changes in the trade in these products, on imports and exports of four countries (USA, Sweden, Ukraine and, to a lesser extent, China) during the period from 1995 to 2011. For this purpose we use explanatory data analysis, time series analysis, benchmarking, meta-synthesis and content analysis of scientific and business publications concerning national and global trends in forest product industries. Data sources are various organizations’ databases of international trade in forest-based products in both monetary and physical terms (cubic meters and tons). The results show that the US and Swedish forest sectors are adversely affected by downturns in both their domestic and foreign markets during the study period, while the Ukrainian sector maintains exports of low value-added products at roughly constant levels (except that particle-board exports increase). China maintains production quantities of low value-added forest-based products, but also substantially increases exports of high-value added products. The results may facilitate efforts to forecast future trends and provide useful information and methodological approaches for future studies of interest to industry representatives, policy-makers and researchers.

Assessing the impact of conceptual mineral systems uncertainty on prospectivity predictions

The past two decades have seen a rapid adoption of artificial intelligence methods applied to mineral exploration. More recently, the easier acquisition of some types of data has inspired a broad literature that has examined many machine learning and modelling techniques that combine exploration criteria,or ’features’, to generate predictions for mineral prospectivity. Central to the design of prospectivity models is a ’mineral system’, a conceptual model describing the key geological elements that control the timing and location of economic mineralisation. The mineral systems model defines what constitutes a training set, which features represent geological evidence of mineralisation, how features are engineered and what modelling methods are used. Mineral systems are knowledge-driven conceptual models, thus all parameter choices are subject to human biases and opinion so alternative models are possible.However, the effect of alternative mineral systems models on prospectivity is rarely compared despite the potential to heavily influence final predictions. In this study, we focus on the effect of conceptual uncertainty on Fe ore prospectivity models in the Hamersley region, Western Australia. Four important considerations are tested.(1) Five different supergene and hypogene conceptual mineral systems models guide the inputs for five forest-based classification prospectivity models model.(2) To represent conceptual uncertainty, the predictions are then combined for prospectivity model comparison.(3)Representation of three-dimensional objects as two-dimensional features are tested to address commonly ignored thickness of geological units.(4) The training dataset is composed of known economic mineralisation sites(deposits) as ’positive’ examples, and exploration drilling data providing ’negative’sampling locations. Each of the spatial predictions are assessed using independent performance metrics common to AI-based classification methods and subjected to geological plausibility testing. We find that different conceptual mineral systems produce significantly different spatial predictions, thus conceptual uncertainty must be recognised. A benefit to recognising and modelling different conceptual models is that robust and geologically plausible predictions can be made that may guide mineral discovery.

An overview of proven Climate Change Vulnerability Assessment tools for forests and forest-dependent communities across the globe：a literature analysis

Climate Change Vulnerability Assessment（VA） tools for forest ecosystems and forest-dependent communities are important for making decisions and understanding the impact of climate change on both social and natural systems.However,the tools are poorly coordinated,making it difficult for policymakers to carry out VAs properly.The aim of this study was to analyze VA literature worldwide to find representative case studies in terms of methods and tools applied and which have been successful in performing VAs on forests and forest-dependent communities.All successful VA studies analyzed had common characteristics such as significant funding,data availability and technical capacity.An additional characteristic was the development of an integrated approach that considered the vulnerability of both ecosystems and communities by combining qualitative and quantitative methods.Community members and relevant stakeholders were significantly involved in a participatory process that concluded with the identification of adaptation measures.The case studies also revealed how policymakers need to choose suitable methods and tools to undertake efficient assessment of vulnerabilities.They need to consider several aspects of the VA process such as subject matter,availability of resources,time and scale.

Policy Assessment and Recommendations for Forestry-based Ecological Poverty Alleviation: An Empirical Study from the Prefectures of Nujiang and Aba, Southwestern China

China has adopted a long-term campaign against poverty. In recent decades, there is an increasing understanding that ecological poverty alleviation can meet the dual goals of environmental protection and rural poverty reduction. China is pivoting towards forestry-based poverty reduction in the severely poverty-stricken areas. However, several key factors remain elusive, including the extent to which the poor people benefit from forestry programs, whether they are satisfied with the policies and whether the policies are effective for poverty alleviation. Based on data collected through a questionnaire survey of 79 households in the prefectures of Nujiang and Aba, southwestern China, the analytic hierarchy process(AHP) approach was used to examine the effectiveness of the forestry-based poverty alleviation policy. The results showed that four poverty alleviation pathways, including industry, employment, micro-finance and pairing assistance in villages, had obviously increased the incomes of the filing poor households and solved the problem of "Two Worries-free and Three Guarantees". The poor were satisfied with the forestry-based ecological poverty alleviation policies and these policies had good effects in fighting against poverty. However, there are still some shortcomings, such as a lack of active participation, imperfect targeted identification, lack of funds and limited sources of funds during the policy implementation. Our results highlight the importance of the forestry industry and the public welfare position in the alleviation of poverty in the poverty-stricken areas. Synergies between ecological protection and poverty reduction are possible through sound forestry-based policies. This article recommends five policies to simultaneously realize the potential of poverty alleviation and environment protection through forestry development.

Unsupervised random forest for affinity estimation

This paper presents an unsupervised clustering random-forest-based metric for affinity estimation in large and high-dimensional data.The criterion used for node splitting during forest construction can handle rank-deficiency when measuring cluster compactness.The binary forest-based metric is extended to continuous metrics by exploiting both the common traversal path and the smallest shared parent node.The proposed forest-based metric efficiently estimates affinity by passing down data pairs in the forest using a limited number of decision trees.A pseudo-leaf-splitting(PLS)algorithm is introduced to account for spatial relationships,which regularizes affinity measures and overcomes inconsistent leaf assign-ments.The random-forest-based metric with PLS facilitates the establishment of consistent and point-wise correspondences.The proposed method has been applied to automatic phrase recognition using color and depth videos and point-wise correspondence.Extensive experiments demonstrate the effectiveness of the proposed method in affinity estimation in a comparison with the state-of-the-art.