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An introduction to the sustainable livelihoods approach for the Regional Fisheries Livelihoods Programme (RFLP)










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    Regional Fisheries Livelihoods Programme: Baseline guidance 2010
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    IMM were engaged by RFLP to provide training for regional and national staff from the six collaborating countries on conducting baseline surveys and setting target logical framework indicators in April 2010, immediately before the RFLP inception workshop which was held in Phuket, Thailand
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    FAO RFLP: Sustainable livelihoods approaches (SLA) and baseline survey design 2010
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    IMM were engaged by RFLP to provide training for regional and national staff from the six collaborating countries on the sustainable livelihoods approach (SLA) and on the RFLP baseline survey design in April 2010, immediately before the RFLP inception workshop which was held in Phuket, Thailand
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    National report on current fisheries and aquaculture policies of relevance to the Regional Fisheries Livelihood Programme (RFLP) in Sri Lanka 2010
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    At the start of the programme period, RFLP engaged a national consultant to review the legal framework and government policies of Sri Lanka likely to impact either positively or negatively against the five national level outputs on 1) Co-management; 2) Safety at sea and vulnerability reduction; 3) Post-harvest and marketing of aquatic products; 4) Livelihoods enhancement and diversification; and 5) Micro-finance services. This report presents the findings for Sri Lanka and recommendations for RF LP to consider

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    Global climate studies show that not only temperatures are increasing and precipitation levels are becoming more varied, all projections indicate these trends will continue. It is therefore imperative that we understand changes in climate over agricultural areas and their impacts on agriculture production and food security. This study presents new analysis on the impact of changing climate on agriculture and food security, by examining the evidence on recent climate variability and extremes over agricultural areas and the impact of these on agriculture and food security. It shows that more countries are exposed to increasing climate variability and extremes and the frequency (the number of years exposed in a five-year period) and intensity (the number of types of climate extremes in a five-year period) of exposure over agricultural areas have increased. The findings of this study are compelling and bring urgency to the fact that climate variability and extremes are proliferating and intensifying and are contributing to a rise in global hunger. The world’s 2.5 billion small-scale farmers, herders, fishers, and forest-dependent people, who derive their food and income from renewable natural resources, are most at risk and affected. Actions to strengthen the resilience of livelihoods and food systems to climate variability and extremes urgently need to be scaled up and accelerated.
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    The need to reduce food loss and waste is firmly embedded in the 2030 Agenda for Sustainable Development. Food loss and waste reduction is considered important for improving food security and nutrition, promoting environmental sustainability and lowering production costs. However, efforts to reduce food loss and waste will only be effective if informed by a solid understanding of the problem. This report provides new estimates of the percentage of the world’s food lost from production up to the retail level. The report also finds a vast diversity in existing estimates of losses, even for the same commodities and for the same stages in the supply chain. Clearly identifying and understanding critical loss points in specific supply chains – where considerable potential exists for reducing food losses – is crucial to deciding on appropriate measures. The report provides some guiding principles for interventions based on the objectives being pursued through food loss and waste reductions, be they in improved economic efficiency, food security and nutrition, or environmental sustainability.
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    This publication on artificial intelligence (AI) for agriculture is the fifth in the E-agriculture in Action series, launched in 2016 and jointly produced by FAO and ITU. It aims to raise awareness about existing AI applications in agriculture and to inspire stakeholders to develop and replicate the new ones. Improvement of capacity and tools for capturing and processing data and substantial advances in the field of machine learning open new horizons for data-driven solutions that can support decision-making, facilitate supervision and monitoring, improve the timeliness and effectiveness of safety measures (e.g. use of pesticides), and support automation of many resource-consuming tasks in agriculture. This publication presents the reader with a collection of informative applications highlighting various ways AI is used in agriculture and offering valuable insights on the implementation process, success factors, and lessons learnt.