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Smell the disease - Developing rapid, high-throughput and non-destructive screening methods for early detection of alien invasive forest pathogens and pests featuring next-generation technologies

XV World Forestry Congress, 2-6 May 2022










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    Article
    Invasive alien plants, insect pests and pathogens in Planted and Natural forests in Nepal: Key lessons from an online survey on distribution and impacts
    XV World Forestry Congress, 2-6 May 2022
    2022
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    Owing to its diverse climatic and topographic condition, Nepal hosts diverse forests and rich biodiversity which provide a variety of ecosystem goods and services. Spread of invasive alien plants, insect pests and pathogens (IAS) has been contributing to degrading forest ecosystem services in Nepal. This study outlined the status, distribution and impact of IAS on forest ecosystem using an online survey among forest officers and forest technicians across Nepal. Invasion and management of pests and diseases is quite limited and under-reported, while the management measures on IAPs are growing. Raising awareness at individual and community levels and capacity building among three levels of government (local, provincial and federal) aids sustainable management of IAS and supports continuous delivery of forest goods and services. Keywords: IAS, biological invasions, severity of damages, control measures, forest health ID: 3486929
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    Satellite remote sensing-based forest resources assessment methods for effective management and sustainable development of forests by generation of information on forests and trees outside forest cover
    XV World Forestry Congress, 2-6 May 2022
    2022
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    Satellite based remote sensing methods have proved to be an effective and scientifically proven method for managing and conserving forest data and resources at periodic time intervals. The forest resources monitoring methods provide useful data to forest managers for sustainable forest management at different scale and forest management units. Over the years the scientific management of forest have been a subject globally discussed incorporating the role of environmentalist, conservationist and communities associated with the forest. It has been an unhidden fact that forests have suffered tremendous pressure in developing countries on the pretext of development. It is through effective monitoring and communication of forest information and knowledge that the concerned provincial governments are forced to take remedial measures for protecting the forests. Apart from the government owned forests, termed as Recorded Forest Areas(RFA) in India, Trees outside forests(TOF) are well acknowledged as an important component of forest resources. The ToF, which basically exist as block, linear and scattered plantations on earth are captured using LISS-III sensor of Indian Remote Sensing Satellite. For the national level scale mapping, all patches of area 1hectare and above are considered for estimation. For mapping of ToF patches of size between 0.1-1hectare, high resolution data from LISSIV sensor(5.8metres resolution) is analyzed. It has been now a well-established fact that trees outside RFAs, although in small proportion, contribute significantly to forest conservation and meeting the demand of people towards minor forest produce, firewood etc. The exercise on forest change detection using a hybrid method, is effective in identification of significant forest change. The assessment of forests and ToFs using satellite data and advance image processing tools may be helpful in effective management and long term sustainability of forests in developing countries. Keywords: [Recorded Forest Area, Trees Outside Forest, National Forest Inventory, FSI, Neural Network, Machine Learning] ID: 3622277
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    Empirical study on the effects of technology training on the forest-related income of rural poverty-stricken house-holds—based on the PSM method
    XV World Forestry Congress, 2-6 May 2022
    2022
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    The implementation of technology training is essential to promote the commercialization of research achievements, and plays a crucial role in poverty alleviation in China. Based on the microcosmic survey data of farmers in four poverty-stricken counties officially assisted by National Forestry and Grassland Administration,the effects of technology training on forest-related income of rural poverty-stricken households is analyzed by using Propensity Score Matching (PSM) method. The study found that after eliminating the deviation from the self-selection and the endogenous issues, the forestry technology training has increased the total forest- related family income and forestry production and operation income by 3.09 times and 2.82 times, respectively. The effect of technology training on income increase is remarkable. Besides, the behavior of poor farmers participating in forestry technology training is significantly affected by the following factors, such as gender, age, family size, managed forestland area, whether they held forest tenure/equity certificate, whether they joined forestry professional cooperatives, and whether they cooperated with forestry enterprises. In order to further improve the effect of technology in poverty alleviation, the following policy recommendations are proposed, including: (1) to encourage poverty-stricken households to actively participate in forestry technology training; (2) to establish a diversified system of forestry technology training; and (3) to ensure the training content is based on the actual needs of the poor. Keywords: rural poverty-stricken household; technology training; forest-related income; PSM method ID: 3487078

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