An assessment of data sources, data quality and changes in national forest monitoring capacities in the Global Forest Resources Assessment 2005-2020

Globally, countries report forest information to the Food and Agriculture Organization of the United Nations (FAO) Global Forest Resources Assessments (FRA) at regular intervals. While the status and trends of national forest monitoring capacities have been previously assessed for the tropics, this has not been systematically done worldwide. In this paper, we assess the use and quality of forest monitoring data sources for national reporting to the FRA in 236 countries and territories. More specifically, we (1) analyze the use of Remote Sensing (RS) for forest area monitoring and the use of National Forest Inventory (NFI) for monitoring forest area, growing stock, biomass, carbon stock, and other attributes in FRA 2005-2020, (2) assess data quality in FRA 2020 using FAO Tier-based indicators, and (3) zoom in to investigate changes in tropical forest monitoring capacities in FRA 2010 - 2020. Globally, the number of countries monitoring forest area using RS at good to very good capacities increased from 55 in FRA 2005 to 99 in FRA 2020. Likewise, the number of countries with good to very good NFI capacities increased from 48 in FRA 2005 to 102 in FRA 2020. This corresponds to ~85% of the global forest area monitored with one or more nationally-produced up-to-date RS products or NFI in FRA 2020. For large proportions of global forests, the highest quality data was used in FRA 2020 for reporting on forest area (93%), growing stock (85% ), biomass (76%), and carbon pools (61%). Overall, capacity improvements are more widespread in the tropics, which can be linked to continued international investments for forest monitoring especially in the context of Reducing Emissions from Deforestation and Forest Degradation in tropical countries (REDD+). More than 50% of the tropical countries with targeted international support improved both RS and NFI capacities in the period 2010-2020 on top of those that already had persistent good to very good capabilities. There is also a link between improvements in national capacities and improved governance measured against Worldwide Governance Indicators (WGI). Our findings – the first global study – suggest an ever-improving data basis for national reporting on forest resources in the context of climate and development commitments, e.g. the Paris Agreement and Sustainable Development Goals

A study of soft tissue sarcomas after childhood cancer in Britain

Among 16 541 3-year survivors of childhood cancer in Britain, 39 soft tissue sarcomas (STSs) occurred and 1.1 sarcomas were expected, yielding a standardised incidence ratio (SIR) of 16.1. When retinoblastomas were excluded from the cohort, the SIR for STSs was 15.9, and the cumulative risk of developing a soft tissue tumour after childhood cancer within 20 years of 3-year survival was 0.23%. In the case–control study, there was a significant excess of STSs in those patients exposed to both radiotherapy (RT) and chemotherapy, which was five times that observed among those not exposed (P=0.02). On the basis of individual radiation dosimetry, there was evidence of a strong dose–response effect with a significant increase in the risk of STS with increasing dose of RT (P<0.001). This effect remained significant in a multivariate model. The adjusted risk in patients exposed to RT doses of over 3000 cGy was over 50 times the risk in the unexposed. There was evidence of a dose–response effect with exposure to alkylating agents, the risk increasing substantially with increasing cumulative dose (P=0.05). This effect remained after adjusting for the effect of radiation exposure

Aboveground forest biomass varies across continents, ecological zones and successional stages: Refined IPCC default values for tropical and subtropical forests

For monitoring and reporting forest carbon stocks and fluxes, many countries in the tropics and subtropics rely on default values of forest aboveground biomass (AGB) from the Intergovernmental Panel on Climate Change (IPCC) guidelines for National Greenhouse Gas (GHG) Inventories. Default IPCC forest AGB values originated from 2006, and are relatively crude estimates of average values per continent and ecological zone. The 2006 default values were based on limited plot data available at the time, methods for their derivation were not fully clear, and no distinction between successional stages was made. As part of the 2019 Refinement to the 2006 IPCC Guidelines for GHG Inventories, we updated the default AGB values for tropical and subtropical forests based on AGB data from &gt;25 000 plots in natural forests and a global AGB map where no plot data were available. We calculated refined AGB default values per continent, ecological zone, and successional stage, and provided a measure of uncertainty. AGB in tropical and subtropical forests varies by an order of magnitude across continents, ecological zones, and successional stage. Our refined default values generally reflect the climatic gradients in the tropics, with more AGB in wetter areas. AGB is generally higher in old-growth than in secondary forests, and higher in older secondary (regrowth &gt;20 years old and degraded/logged forests) than in young secondary forests (20 years old). While refined default values for tropical old-growth forest are largely similar to the previous 2006 default values, the new default values are 4.0-7.7-fold lower for young secondary forests. Thus, the refined values will strongly alter estimated carbon stocks and fluxes, and emphasize the critical importance of old-growth forest conservation. We provide a reproducible approach to facilitate future refinements and encourage targeted efforts to establish permanent plots in areas with data gaps

Aboveground forest biomass varies across continents, ecological zones and successional stages: refined IPCC default values for tropical and subtropical forests

For monitoring and reporting forest carbon stocks and fluxes, many countries in the tropics and subtropics rely on default values of forest aboveground biomass (AGB) from the Intergovernmental Panel on Climate Change (IPCC) guidelines for National Greenhouse Gas (GHG) Inventories. Default IPCC forest AGB values originated from 2006, and are relatively crude estimates of average values per continent and ecological zone. The 2006 default values were based on limited plot data available at the time, methods for their derivation were not fully clear, and no distinction between successional stages was made. As part of the 2019 Refinement to the 2006 IPCC Guidelines for GHG Inventories, we updated the default AGB values for tropical and subtropical forests based on AGB data from >25 000 plots in natural forests and a global AGB map where no plot data were available. We calculated refined AGB default values per continent, ecological zone, and successional stage, and provided a measure of uncertainty. AGB in tropical and subtropical forests varies by an order of magnitude across continents, ecological zones, and successional stage. Our refined default values generally reflect the climatic gradients in the tropics, with more AGB in wetter areas. AGB is generally higher in old-growth than in secondary forests, and higher in older secondary (regrowth >20 years old and degraded/logged forests) than in young secondary forests (20 years old). While refined default values for tropical old-growth forest are largely similar to the previous 2006 default values, the new default values are 4.0-7.7-fold lower for young secondary forests. Thus, the refined values will strongly alter estimated carbon stocks and fluxes, and emphasize the critical importance of old-growth forest conservation. We provide a reproducible approach to facilitate future refinements and encourage targeted efforts to establish permanent plots in areas with data gaps

Aboveground forest biomass varies across continents, ecological zones and successional stages: refined IPCC default values for tropical and subtropical forests

For monitoring and reporting forest carbon stocks and fluxes, many countries in the tropics and subtropics rely on default values of forest aboveground biomass (AGB) from the Intergovernmental Panel on Climate Change (IPCC) guidelines for National Greenhouse Gas (GHG) Inventories. Default IPCC forest AGB values originated from 2006, and are relatively crude estimates of average values per continent and ecological zone. The 2006 default values were based on limited plot data available at the time, methods for their derivation were not fully clear, and no distinction between successional stages was made. As part of the 2019 Refinement to the 2006 IPCC Guidelines for GHG Inventories, we updated the default AGB values for tropical and subtropical forests based on AGB data from >25 000 plots in natural forests and a global AGB map where no plot data were available. We calculated refined AGB default values per continent, ecological zone, and successional stage, and provided a measure of uncertainty. AGB in tropical and subtropical forests varies by an order of magnitude across continents, ecological zones, and successional stage. Our refined default values generally reflect the climatic gradients in the tropics, with more AGB in wetter areas. AGB is generally higher in old-growth than in secondary forests, and higher in older secondary (regrowth >20 years old and degraded/logged forests) than in young secondary forests (⩽20 years old). While refined default values for tropical old-growth forest are largely similar to the previous 2006 default values, the new default values are 4.0–7.7-fold lower for young secondary forests. Thus, the refined values will strongly alter estimated carbon stocks and fluxes, and emphasize the critical importance of old-growth forest conservation. We provide a reproducible approach to facilitate future refinements and encourage targeted efforts to establish permanent plots in areas with data gaps

Comparison between UAV and terrestrial LiDAR scans for high throughput phenotyping of architectural traits of a core collection of apple trees

This article is a Proceedings Paper of the 31st International Horticultural Congress (IHC 2022) / 3rd International Symposium on Mechanization, Precision Horticulture, and Robotics: Precision and Digital Horticulture in Field Environments which has been taking place in Angers, France from the 14th to the 20th of August 2022.International audienceIn a context of climate change, the selection of fruit tree cultivars that perform well under sub-optimal growing conditions becomes essential. Architectural traits must be considered to assess the intrinsic production potential of cultivars, their interactions with the environment and the easiness of management. To phenotype such traits at high throughput on a core-collection of apple trees, we tested an approach based on UAV-LiDARs that allow rapid 3D scanning of an orchard and compared it to our previous approach, based on TLS. With the UAV-LiDAR different acquisition protocols were tested, with varying height or speed for the drone, that resulted in different densities and qualities of points. To process the point clouds, we built a pipeline composed of steps including the identification and removal of undesired elements (soil, pole, etc.), the segmentation of individual trees, and the characterization of architectural traits. For the first step, two methods were tested: CANUPO and RandLA-NET. For the tree segmentation, we used a semi-supervised method of label spreading. The initial seeds for the labels were determined from the GPS location of the trees. Architectural traits such as height, projected leaf area, convex and alpha volume, eccentricity were then determined and their broad sense heritabilities were estimated to assess genotypic variability and measure repeatability. The use of UAV-LiDAR scans was compared and validated with terrestrial LiDAR scans. The influence of the acquisition protocol on the resulting architectural traits was characterized. Correlations greater than or equal to 0.5 were found between the estimated indices from the different protocols, except for eccentricity. Indices from UAV scans (F2, F3) presented values similar to those obtained with the TLS. As a result, indices obtained with TLS can be approximated using UAV-LiDAR

Tropical Forest Cover Change in the 1990s and Options for Future Monitoring.

Abstract not availableJRC.H-Institute for environment and sustainability (Ispra