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DocumentOther documentThe effects of ignoring clustered data structure in allometric biomass models on large forest area biomass estimation
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.The aim of this study was to assess the effects of ignoring the clustered data structure on large area biomass estimation, when model uncertainty is included or not in the biomass prediction process. We used a Monte Carlo error propagation procedure to combine the uncertainty from allometric model predictions with the uncertainty from plot-to-plot variation, to produce estimates of mean AGB per hectare and standard error of the mean. An alternative procedure that ignores model prediction uncertainty was also used, therefore, showing only uncertainty due to differences between plots. Ignoring the clustered data structure, (i.e., fitting allometric models using ordinary least squares), the estimates of mean biomass per hectare were approximately 11% less than the estimates based on mixed effects models (that accounted for the clustered data structure), regardless of including or not the model prediction uncertainty. The estimates of uncertainty were also affected by ignoring the clustered data structure. When including model prediction uncertainty, ignoring the clustered data structure resulted in underestimation of standard error by 30%, whereas when model uncertainty was not included, the underestimation was 13%. Therefore, ignoring the clustered data structure, may affect both, the accuracy and the precision of biomass estimations over large forest areas. Keywords: Monitoring and data collection, Climate change ID: 3616826 -
ArticleJournal articleAllometric models for estimating above ground biomass of Bambusa tulda Roxb. and Melocanna baccifera (Roxb.) Kurz
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.Allometric equations are used to estimate the biomass and carbon stock of forests. There is a dearth of species- specific allometric equations for bamboos growing in Bangladesh. Bambusa tulda and Melocanna baccifera are the two most common bamboo species of commercial importance in Bangladesh. This study reports allometric equations for estimating biomass of bamboo compartments (leaf, branches, and stem) and total above-ground biomass. Data was collected from natural bamboo forests of different locations of Khagrachhari district. A total of 50 bamboos (25 B. tulda and 25 M. baccifera) were sampled following the destructive method. Bamboo leaf, branch, and stem were measured for fresh weight in the field. Sub-samples were collected in sufficient amounts and processed in the laboratory for density and oven-dry weight to derive fresh to oven-dry weight ratio. Commonly used 10 candidate equations were tested using Diameter at Breast Height (DBH), diameter at base (D5), and height (H) as explanatory variables to find the best fitted allometric equation. In total, the study developed 60 models with 10 for each component of the two species. Applying the goodness-of-fit statistics, 4 best-fitted models were selected for estimating stem and total above-ground biomass (TAGB) of the two bamboo species. The best fit allometric biomass models for M. baccifera were, Ys = 0.398*DBH1.542 and Yt = 0.627*DBH1.382, where, Ys = stem biomass and Yt = total above-ground biomass. On the other hand, best fit allometric biomass models for B. tulda were, Ys = 0.041*DBH1.0658*H1.2311, and Yt = 0.235*D5 1.867, where, D5 is diameter at the base (5 cm above the ground). The relationship between the biomass and dendrometric variables in the form of best-fitted models was statistically significant at p < 0.05 levels. The allometric models developed by this study will be useful for better estimation of biomass and sequestered carbon in the plain land homestead forests of Bangladesh. Keywords: Khagrachhari, Bamboo, Carbon sequestration, Bambusa tulda and Melocanna baccifera ID: 3623846 -
ArticleJournal articleAllometric equation for estimating tree above ground biomass modified by ecological environmental factors in tropical dipterocarp forests
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.Tropical Dipterocarp Forest (DF) plays an important role in mitigating climate change thanks to its carbon sequestration capacity. In order to estimate the CO2 absorption capacity of DF as a basis for the development of forest ecological services, a system of biomass equations is needed; while very few models for estimating biomass in DF have been published and have not yet reflected the impact of ecological environmental factors. The purpose of the study was to validate and select the best model for estimating tree above ground biomass (AGB, kg) in DF under the influence of ecological environmental factors, thereby improving the reliability. Twenty-eight 0.25 ha plots in the Central Highlands and one 1 ha plot in the Southeast ecoregion in Viet Nam were measured. A total of 329 trees were destructively sampled to obtain a dataset of AGB; Methods for developing equations were weighted nonlinear fixed/mixed models with/without random effects fit by Maximum Likelihood; Using K-fold cross validation with K = 10, we compared and selected the best model with and without ecological environmental factors. As a result, separate ecological environmental factors did not affect AGB, while the combination of the factors influences the AGB model through the form: AGB = AVERAGE × MODIFIER, AGB = a × Db ×WDd × exp (e2 × (P - 1502) + e3 × (BA - 12.62)) that was significantly more reliable than a model without these factors involved; where D (cm), WD (g / cm3), P (mm year-1) and BA (m2 ha-1) are the diameter at breast height, wood density, averaged annual rainfall and total basal area of forest stand, respectively. Keywords: above ground biomass, dipterocarp forest, ecological factor ID: 3473259
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Book (stand-alone)Technical bookThe future of food and agriculture - Trends and challenges 2017
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No results found.What will be needed to realize the vision of a world free from hunger and malnutrition? After shedding light on the nature of the challenges that agriculture and food systems are facing now and throughout the 21st century, the study provides insights into what is at stake and what needs to be done. “Business as usual” is not an option. Major transformations in agricultural systems, rural economies, and natural resources management are necessary. The present study was undertaken for the quadrennial review of FAO’s strategic framework and for the preparation of the Organization Medium-Term plan 2018-2021. -
BookletHigh-profileFAO Strategy on Climate Change 2022–2031 2022The FAO Strategy on Climate Change 2022–2031 was endorsed by FAO Council in June 2022. This new strategy replaces the previous strategy from 2017 to better FAO's climate action with the Strategic Framework 2022-2031, and other FAO strategies that have been developed since then. The Strategy was elaborated following an inclusive process of consultation with FAO Members, FAO staff from headquarters and decentralized offices, as well as external partners. It articulates FAO's vision for agrifood systems by 2050, around three main pillars of action: at global and regional level, at country level, and at local level. The Strategy also encourages key guiding principles for action, such as science and innovation, inclusiveness, partnerships, and access to finance.
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Book (series)FlagshipThe State of Food Security and Nutrition in the World 2021
Transforming food systems for food security, improved nutrition and affordable healthy diets for all
2021Also available in:
Error: Could not load results for '/discover/search/objects?sort=dc.language.iso,ASC&page=0&size=5&configuration=item&query=(fao.identifier.jobnumber_keyword%3Acb4474*%20OR%20fao.identifier.jobnumber_keyword%3ACB4474*)%20-fao.identifier.jobnumber_keyword%3ACB4474EN%20AND%20archived%3Atrue'.In recent years, several major drivers have put the world off track to ending world hunger and malnutrition in all its forms by 2030. The challenges have grown with the COVID-19 pandemic and related containment measures. This report presents the first global assessment of food insecurity and malnutrition for 2020 and offers some indication of what hunger might look like by 2030 in a scenario further complicated by the enduring effects of the COVID-19 pandemic. It also includes new estimates of the cost and affordability of healthy diets, which provide an important link between the food security and nutrition indicators and the analysis of their trends. Altogether, the report highlights the need for a deeper reflection on how to better address the global food security and nutrition situation.To understand how hunger and malnutrition have reached these critical levels, this report draws on the analyses of the past four editions, which have produced a vast, evidence-based body of knowledge of the major drivers behind the recent changes in food security and nutrition. These drivers, which are increasing in frequency and intensity, include conflicts, climate variability and extremes, and economic slowdowns and downturns – all exacerbated by the underlying causes of poverty and very high and persistent levels of inequality. In addition, millions of people around the world suffer from food insecurity and different forms of malnutrition because they cannot afford the cost of healthy diets. From a synthesized understanding of this knowledge, updates and additional analyses are generated to create a holistic view of the combined effects of these drivers, both on each other and on food systems, and how they negatively affect food security and nutrition around the world.In turn, the evidence informs an in-depth look at how to move from silo solutions to integrated food systems solutions. In this regard, the report proposes transformative pathways that specifically address the challenges posed by the major drivers, also highlighting the types of policy and investment portfolios required to transform food systems for food security, improved nutrition, and affordable healthy diets for all. The report observes that, while the pandemic has caused major setbacks, there is much to be learned from the vulnerabilities and inequalities it has laid bare. If taken to heart, these new insights and wisdom can help get the world back on track towards the goal of ending hunger, food insecurity, and malnutrition in all its forms.