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ArticleJournal articleDeveloping simultaneously modeling systems for improving the reliability of tree aboveground biomass- carbon and its components estimates for Machilus odoratissimus nees in the central highlands, Viet Nam
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.Machilus odoratissimus Nees is a multi-purpose species with, high economic value and environmental protection, so this tree species is commonly used in agroforestry models. In plantation management, it demands modeling systems that predict accurately aboveground biomass- carbon and its components. At the same time, the developed models support computing carbon accumulation of forest trees in agroforestry models for the program of reducing emissions from deforestation and forest degradation (REDD). Twenty-two 300 m2 plots were measured within the full range of 1 to 7 ages in the Central Highlands of VietNam. A total of 22 quadratic mean diameter trees were destructively sampled to obtain a dataset of the dry iomass/carbon of the stem (Bst/Cst), bark (Bba/Cba), branches (Bbr/Cbr), leaves (Ble/Cle), and total tree aboveground biomass/carbon (AGB/AGC). We examined the performance of weighted nonlinear models fit by maximum likelihood and weighted nonlinear seemingly unrelated regression (SUR) fit by generalized least squares for predicting tree aboveground biomass- carbon and its components. The simultaneous estimation of AGB/AGC and its components produced a higher reliability than that of the models of tree components and the total developed separately. The selected forms of modeling systems were AGB = Bst + Bba + Bbr + Ble = a1×(D2H)b1 + a2×(D2H)b2 + a3×Db3 + a4×(D2H)b4 and AGC = Cst + Cba+ Cbr + Cle = a1×(D2H)b1 ++2×(D2H)b2 + a3×Db3 + a4×(D2H)b4 (where D is the diameter at breast height and H is the height of the tree). Keywords: Agroforestry, Machilus odoratissimus, seemingly unrelated regression (SUR), tree biomass- carbon ID: 3472953 -
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 -
ArticleJournal articleThe tropical biomass & carbon project– An app for forest biomass and carbon estimates
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.This article introduces the project called Tropical Biomass & Carbon – TB&C, available on the permanent link www.tropicalbiomass.com. The App requires input attributes of the forest stand or diameter class easily obtained, being: smallest and largest diameters, number of trees ha-1, and parameters of the diameter distribution. The output attributes are at the stand and tree levels. At stand level, the App delivers mean aboveground biomass (AGB) and carbon (AGC), in Mg ha-1, as well as their confidence intervals (CIs) and uncertainties. The tree-level outputs are AGB and diameter for every tree in the stand. The project TB&C comprises four Brazilian forest (and non-forest) formations: Campinarana, Floresta estacional, Floresta ombrofila, and Savana. This article aims to disclose the algorithm written for the TB&C App. This phase counts on a standardized database of 1,428 trees with dry AGB destructively measured. Model uncertainties were incorporated into the modeling process. In addition to its reliability, we cite as great advantages of the TB&C App; (i) simplicity and a user-friendly layout, (ii) AGB and AGC estimates provided along with robust CIs, and (iii) estimates at the stand and tree levels with consistent totals. As a secondary product, the project TB&C delivers a dataset of 64,000 simulated plots, informing dry AGB, tree density, basal area, Lorey’s height, and shape of the diameter distribution. Keywords: Tropical Forest, Aboveground biomass, Uncertainty analysis, Stand- and tree-level, estimates, Web application ID: 3623771
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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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BookletCorporate general interestEmissions due to agriculture
Global, regional and country trends 2000–2018
2021Also available in:
No results found.The FAOSTAT emissions database is composed of several data domains covering the categories of the IPCC Agriculture, Forestry and Other Land Use (AFOLU) sector of the national GHG inventory. Energy use in agriculture is additionally included as relevant to emissions from agriculture as an economic production sector under the ISIC A statistical classification, though recognizing that, in terms of IPCC, they are instead part of the Energy sector of the national GHG inventory. FAO emissions estimates are available over the period 1961–2018 for agriculture production processes from crop and livestock activities. Land use emissions and removals are generally available only for the period 1990–2019. This analytical brief focuses on overall trends over the period 2000–2018. -
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
2021In 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.