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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 -
DocumentOther documentBiomass estimation in mangrove forests: a comparison of allometric models incorporating species and structural information
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.Improved estimates of aboveground biomass are required to improve our understanding of the productivity of mangrove forests to support the long-term conservation of these fragile ecosystems which are under threat from many natural and anthropogenic pressures. To understand how individual species affects biomass estimates in mangrove forests, five species-specific and four genus-specific allometric models were developed. Independent tree inventory data were collected from 140 sample plots to compare the aboveground biomass (AGB) among the species-specific models and seven existing frequently used pan-tropical and Sundarbans-specific generic models. The effect of individual tree species was also evaluated using model parameters for wood densities (from individual trees to the whole Sundarbans) and tree heights (individual, plot average and plot top height). All nine species-specific models explained a high percentage of the variance in tree AGB (R2 = 0.97 to 0.99) with the diameter at breast height (DBH) and total height (H). At the individual tree level, the generic allometric models overestimated AGB from 22% to 167% compared to the species-specific models. At the plot level, mean AGB varied from 111.36 Mg ha-1 to 299.48 Mg ha-1, where AGB significantly differed in all generic models compared to the species-specific models (p < 0.05). Using measured species wood density (WD) in the allometric model showed 4.5% to 9.7% less biomass than WD from a published database and other sources. When using plot top height and plot average height rather than measured individual tree height, the AGB was overestimated by 19.5 % and underestimated by 8.3% (p < 0.05). The study demonstrates that species-specific allometric models and individual tree measurements benefit biomass estimation in mangrove forests. Tree level measurement from the inventory plots, if available, should be included in allometric models to improve the accuracy of forest biomass estimates, particularly when upscaling individual trees up to the ecosystem level. Keywords: Climate change, Monitoring and data collection, Sustainable forest management ID: 3621710 -
DocumentOther documentManaging taxonomic and functional diversity is the key to sustain aboveground biomass and soil microbial diversity: A synthesis from long-term forest restoration of southern China
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.Exploring the biodiversity-ecosystem functioning relationship is one of the central goals of ecological research. Restoration is essential for supporting key ecosystem functions such as aboveground biomass production and managing soil microbial diversity. However, the relative importance of functional versus taxonomic diversity in explaining aboveground biomass and soil microbial diversity during restoration is poorly understood. Here, we used a trait-based approach to test for the importance of multiple plant diversity attributes in regulating aboveground biomass and soil microbial diversity in four 30- years-old restored subtropical forests in southern China. High-throughput Illumina sequencing was applied for detecting fungal and bacterial diversity. We show that both taxonomic and functional diversities are significant and positive regulators of aboveground biomass; however, functional diversity (FD) was more important than taxonomic diversity (TD) in controlling aboveground biomass. FD had the strongest direct effect on aboveground biomass compared with TD, soil properties, and community weighted mean (CWM) traits. Our results further indicate that leaf and root morphological traits and traits related to the nutrient content in plant tissues showed acquisitive resource use strategy which influenced aboveground biomass. In contrast to aboveground biomass, taxonomic diversity explained more of the soil microbial diversity than the FD and soil properties. Prediction of fungal richness was better than that of bacterial richness. In addition, root traits explained more variation of soil microbes than the leaf traits. Our results suggest that both TD and FD play a role in shaping aboveground biomass and soil microbial diversity; but FD is more important in supporting aboveground biomass while TD for belowground microbial diversity. These results imply that enhancing TD and FD is important to restoring and managing degraded forest landscapes. Key words: Biodiversity-Ecosystem functions; soil microbial diversity, taxonomic diversity, functional diversity, forest restoration ID: 3486373
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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. -
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)Technical studyThe impact of climate variability and extremes on agriculture and food security - An analysis of the evidence and case studies
Background paper for The State of Food Security and Nutrition in the World 2018
2020Also available in:
No results found.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.