An Empirical Analysis of Timber Trade in India

Forests are renewable resources that contribute significantly to economic growth. The economic contribution by forest is through the valuable commodities including wood, paper and non-timber forest products. One among this is timber, it has been the primary material for house construction and furnishings of all kinds over the years. Timber plays a vital role in international trade in India. This study was focused on finding growth pattern in export and import of timber using Compound Annual Growth Rate (CAGR). Over the period of 2005-2019, the production of timber has been increased at the rate of 0.07%. The import performance was dominant over the export due to over requirements of raw materials. Although export showed positive growth rate at 0.15%, import of timber shot up at 4.09% from 2005-2019. Therefore, it is necessary to introduce adequate due diligence system to meet domestic demand of timber production in India.

Socio-Economic Determinants of Contributions of Timber Marketing to Income of Timber Merchants in Bodija Sawnwood Market, Ibadan, Nigeria

Forest enterprise has been identified as a means of generating income among people; plays a vital role in enhancing the quality of life of forest-dependent people. Despite the opportunities timber marketing offers the people, the disparities in the income generation of the marketers in the Bodija sawn wood Market and the effect of socio-economic factors on income generation of the marketers is not well understood. This study was conducted to assess the socio-economic determinants of contributions of timber marketing to the income of timber merchants in Bodija sawn-wood Market. One hundred structured questionnaires were administered randomly in five zones of the sawn wood Market to obtain information on the socio-economic background of the sawn wood marketers and the contribution of timber trade to their incomes. The result indicated that 99.0% of the respondents were male while females constituted 1.00%. Seventy-five percent of the marketers had post-primary education and 25% had primary education. Two percent of the marketers had below 10 years of marketing experience, twenty-six percent had between 11 and 20 years, 57.00% had between 21 and 30 years, and 15.00% had more than 30years experience. Fifty-eight percent of the respondents earned between ₦10000-₦60000 (1US$ = 360.00) from timber marketing, thirty-one percent earned between ₦60001 and ₦110000, 7% earned between ₦110001 and ₦160000, while 4% earned above ₦160000 per month. Chi-square analysis of the socio-economic characteristics of the respondents and income generation at α level of 0.05 indicated that ethnicity (0.001) and years of experience (0.009) significantly influenced income while the level of education (0.101), age (0.122), and religion (0.745) had no significant influence on the incomes of marketers. Experience is an important factor in sawn wood marketing and a major determinant of the contribution of timber marketing to the income of timber marketers in Bodija sawn wood Market.

Price Volatility Transmission in China’s Hardwood Lumber Imports

Hardwood lumber is the principal part of the global hardwood timber trade. China has become the largest importer of hardwood lumber in the world. However, China’s hardwood lumber imports are affected by price volatility. Thus, we investigated the price volatility transmission of China’s hardwood lumber imports. We aimed to detect the source, path, and intensity of the volatility transmission in China’s hardwood lumber imports, and reveal the intrinsic interactions between price volatilities. To date, there is little research on the price fluctuations of forest products. This paper provides an empirical analysis on the volatility transmission in China’s forest product imports. We selected four types of major hardwood lumber imports to China; that is, teak (Tectona grandis L.F.), merbau (Merbau), sapele (Entandrophragma), and casla (Terminalia spp.) (The Latin names of tree species are given in parentheses), and used their daily prices from 4 August 2010 to 15 April 2020. The Baba–Engle–Kraft–Kroner (BEKK) multivariate models and dynamic conditional correlation (DCC) models were employed. The empirical results indicate that there is an intrinsic relationship between the price fluctuations in China’s hardwood lumber imports. The volatility transmission chain originates from casla; it is transmitted along the casla→sapele→merbau→teak pathway. The direction of transmission is from lower prices to higher prices. The dynamic conditional correlation of each link in the chain does not exhibit any particular time trend. This suggests that volatility transmission is a crucial price mechanism in China’s hardwood lumber imports. Our findings have important policy implications for hedging timber price risks and designing timber trade policies.

The Shiners’ War: Social Violence in the Ottawa Valley in the 1830s

By late May of 1835, unrest in Bytown had reached unprecedented proportions. All winter, the people of the town, the entrepôt of the Ottawa timber trade, had been bracing themselves, awaiting the annual visitation, the annual affliction, of the raftsmen who came each spring from high up the Valley to roister and riot in the streets of Bytown. Like the freshets in the streams, the raftsmen and social disorder arrived each April and May. But never before had their coming brought such organized violence as it did in 1835. For the Irish timberers, now had a leader, and a purpose. Peter Aylen, run-away sailor, timber king, ambitious schemer, had set himself at the head of the Irish masses, had moulded them into a powerful weapon. He had given them a purpose: to drive the French Canadians off the river and thus guarantee jobs and high wages in the timber camps to the Irish.

Field-Deployable Computer Vision Wood Identification of Peruvian Timbers

Illegal logging is a major threat to forests in Peru, in the Amazon more broadly, and in the tropics globally. In Peru alone, more than two thirds of logging concessions showed unauthorized tree harvesting in natural protected areas and indigenous territories, and in 2016 more than half of exported lumber was of illegal origin. To help combat illegal logging and support legal timber trade in Peru we trained a convolutional neural network using transfer learning on images obtained from specimens in six xylaria using the open source, field-deployable XyloTron platform, for the classification of 228 Peruvian species into 24 anatomically informed and contextually relevant classes. The trained models achieved accuracies of 97% for five-fold cross validation, and 86.5 and 92.4% for top-1 and top-2 classification, respectively, on unique independent specimens from a xylarium that did not contribute training data. These results are the first multi-site, multi-user, multi-system-instantiation study for a national scale, computer vision wood identification system evaluated on independent scientific wood specimens. We demonstrate system readiness for evaluation in real-world field screening scenarios using this accurate, affordable, and scalable technology for monitoring, incentivizing, and monetizing legal and sustainable wood value chains.

Pterocarpus wood identification by independent and complementary analysis of DART-TOFMS, microscopic anatomy, and fluorescence spectrometry

Attention to illegal logging practices and demanding policies in transnational timber trade have driven the need for species-level identification of timber. Historically wood has been identified to genus level using microscopy and anatomical characteristics, however, new chemometric and imaging methods have been developed to increase the speed and precision of timber identification. This study approaches species identification using a combination of complementary methods: Direct Analysis in Real Time–Time-of-Flight Mass Spectrometry (DART-TOFMS), wood anatomy, and fluorescence spectroscopy. Seven commercially and environmentally significant species in Pterocarpus, including P. erinaceus (CITES Appendix II), P. santalinus (CITES Appendix II), P. tinctorius (CITES Appendix II), P. indicus, P. macrocarpus, P. dalbergioides, and P. soyauxii were studied. It was found that DART-TOFMS paired with discriminant analysis of principal components (PCA) could classify species with an accuracy of 95–100%, while anatomy in combination with PCA applied to fluorescence spectra could be used to classify CITES Appendix II species. In the absence of access to DART-TOFMS, a combination of wood anatomy and fluorescence spectrometry can permit more accurate identification than anatomy alone.