First mission - towards a global harmonised in-situ data repository for forest biomass datasets validation

Global measurements of forest height, biomass are urgently needed as essential climate and ecosystem variables, but can benefit from greater co-operation between remote sensing (RS) and forest ecological communities. The Forest Observation System - FOS (https://forest-observation-system.net/ [https://forest-observation- system.net/]) is an international cooperation to establish a global in-situ forest biomass database to support earth observation and to encourage investment in relevant field-based observations and science. FOS aims to link the RS community with ecologists who measure forest biomass and estimating biodiversity in the field. The FOS aims to overcome data sharing issues and introduce a standard biomass data flow from tree-level measurement to the plot-level aggregation served in the most suitable form for the RS. Ecologists benefit from the FOS with improved access to global biomass information, data standards, gap identification and potentially improved funding opportunities to address the known gaps and deficiencies in the data. FOS closely collaborate with the CTFS-ForestGEO, the ForestPlots.net (incl. RAfNFOR, AfriTRON and T-FORCES), AusCover, TmFO and the llASA network. FOS is an open initiative with other networks and teams most welcome to join. The online database provides open access for forest plot location, canopy height and above-ground biomass. Plot size is 0.25ha or larger. Comparison of plot biomass data with available global and regional maps (incl. Kindermann et al., 2013; Thurner et al., 2013; Saatchi et al., 2011; Baccini et al., 2012; Avitabile et al., 2016; Hu et al., 2016; Santoro et al., 2018) shows wide range of uncertainties associated with biomass estimation

Guidelines for documenting and reporting tree allometric equations

Given the pressing need to quantify carbon fluxes associated with terrestrial vegetation dynamics, an increasing number of researchers have sought to improve estimates of tree volume, biomass, and carbon stocks. Tree allometric equations are critical tools for such purpose and have the potential to improve our understanding about carbon sequestration in woody vegetation, to support the implementation of policies and mechanisms designed to mitigate climate change (e.g. CDM and REDD+; Agrawal et al. 2011), to calculate costs and benefits associated with forest carbon projects, and to improve bioenergy systems and sustainable forest management (Henry et al. 2013)

Closing a gap in tropical forest biomass estimation : taking crown mass variation into account in pantropical allometries

Accurately monitoring tropical forest carbon stocks is a challenge that remains outstanding. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference model in the coming years. However, this reference model shows a systematic bias towards the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass data set of 673 trees destructively sampled in five tropical countries (101 trees > 100 cm in diameter) and an original data set of 130 forest plots (1 ha) from central Africa to quantify the prediction error of biomass allometric models at the individual and plot levels when explicitly taking crown mass variations into account or not doing so. We first showed that the proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88 %. This proportion was constant on average for trees = 45 Mg. This increase coincided with a progressive deviation between the pantropical biomass model estimations and actual tree mass. Taking a crown mass proxy into account in a newly developed model consistently removed the bias observed for large trees (> 1 Mg) and reduced the range of plot- level error (in %) from [-23; 16] to [0; 10]. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far- from- negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by taking a crown mass proxy for the largest trees in a stand into account, thus suggesting that the accuracy of forest carbon estimates can be significantly improved at a minimal cost

A large-scale species level dated angiosperm phylogeny for evolutionary and ecological analyses.

Phylogenies are a central and indispensable tool for evolutionary and ecological research. Even though most angiosperm families are well investigated from a phylogenetic point of view, there are far less possibilities to carry out large-scale meta-analyses at order level or higher. Here, we reconstructed a large-scale dated phylogeny including nearly 1/8th of all angiosperm species, based on two plastid barcoding genes, matK (incl. trnK) and rbcL. Novel sequences were generated for several species, while the rest of the data were mined from GenBank. The resulting tree was dated using 56 angiosperm fossils as calibration points. The resulting megaphylogeny is one of the largest dated phylogenetic tree of angiosperms yet, consisting of 36,101 sampled species, representing 8,399 genera, 426 families and all orders. This novel framework will be useful for investigating different broad scale research questions in ecological and evolutionary biology

Topography shapes the structure, composition and function of tropical forest landscapes.

Topography is a key driver of tropical forest structure and composition, as it constrains local nutrient and hydraulic conditions within which trees grow. Yet, we do not fully understand how changes in forest physiognomy driven by topography impact other emergent properties of forests, such as their aboveground carbon density (ACD). Working in Borneo - at a site where 70-m-tall forests in alluvial valleys rapidly transition to stunted heath forests on nutrient-depleted dip slopes - we combined field data with airborne laser scanning and hyperspectral imaging to characterise how topography shapes the vertical structure, wood density, diversity and ACD of nearly 15 km2 of old-growth forest. We found that subtle differences in elevation - which control soil chemistry and hydrology - profoundly influenced the structure, composition and diversity of the canopy. Capturing these processes was critical to explaining landscape-scale heterogeneity in ACD, highlighting how emerging remote sensing technologies can provide new insights into long-standing ecological questions

The Importance of Consistent Global Forest Aboveground Biomass Product Validation

Several upcoming satellite missions have core science requirements to produce data for accurate forest aboveground biomass mapping. Largely because of these mission datasets, the number of available biomass products is expected to greatly increase over the coming decade. Despite the recognized importance of biomass mapping for a wide range of science, policy and management applications, there remains no community accepted standard for satellite-based biomass map validation. The Committee on Earth Observing Satellites (CEOS) is developing a protocol to fill this need in advance of the next generation of biomass-relevant satellites, and this paper presents a review of biomass validation practices from a CEOS perspective. We outline the wide range of anticipated user requirements for product accuracy assessment and provide recommendations for the validation of biomass products. These recommendations include the collection of new, high-quality in situ data and the use of airborne lidar biomass maps as tools toward transparent multi-resolution validation. Adoption of community-vetted validation standards and practices will facilitate the uptake of the next generation of biomass products

Closing a gap in tropical forest biomass estimation: taking crown mass variation into account in pantropical allometries

Accurately monitoring tropical forest carbon stocks is a challenge that remains outstanding. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference model in the coming years. However, this reference model shows a systematic bias towards the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass data set of 673 trees destructively sampled in five tropical countries (101 trees > 100 cm in diameter) and an original data set of 130 forest plots (1 ha) from central Africa to quantify the prediction error of biomass allometric models at the individual and plot levels when explicitly taking crown mass variations into account or not doing so. We first showed that the proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88 %. This proportion was constant on average for trees  1 Mg) and reduced the range of plot-level error (in %) from [−23; 16] to [0; 10]. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far-from-negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by taking a crown mass proxy for the largest trees in a stand into account, thus suggesting that the accuracy of forest carbon estimates can be significantly improved at a minimal cost.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Copernicus Publications on behalf of the European Geosciences Union. The published article can be found at: http://www.biogeosciences.net

Height-diameter allometry and above ground biomass in tropical montane forests: Insights from the Albertine Rift in Africa

Tropical montane forests provide an important natural laboratory to test ecological theory. While it is well-known that some aspects of forest structure change with altitude, little is known on the effects of altitude on above ground biomass (AGB), particularly with regard to changing height-diameter allometry. To address this we investigate (1) the effects of altitude on height-diameter allometry, (2) how different height-diameter allometric models affect above ground biomass estimates; and (3) how other forest structural, taxonomic and environmental attributes affect above ground biomass using 30 permanent sample plots (1-ha; all trees ≥ 10 cm diameter measured) established between 1250 and 2600 m asl in Kahuzi Biega National Park in eastern Democratic Republic of Congo. Forest structure and species composition differed with increasing altitude, with four forest types identified. Different height-diameter allometric models performed better with the different forest types, as trees got smaller with increasing altitude. Above ground biomass ranged from 168 to 290 Mg ha-1, but there were no significant differences in AGB between forests types, as tree size decreased but stem density increased with increasing altitude. Forest structure had greater effects on above ground biomass than forest diversity. Soil attributes (K and acidity, pH) also significantly affected above ground biomass. Results show how forest structural, taxonomic and environmental attributes affect above ground biomass in African tropical montane forests. They particularly highlight that the use of regional height-diameter models introduces significant biases in above ground biomass estimates, and that different height-diameter models might be preferred for different forest types, and these should be considered in future studies

LiDAR-based reference aboveground biomass maps for tropical forests of South Asia and Central Africa

Accurate mapping and monitoring of tropical forests aboveground biomass (AGB) is crucial to design effective carbon emission reduction strategies and improving our understanding of Earth’s carbon cycle. However, existing large-scale maps of tropical forest AGB generated through combinations of Earth Observation (EO) and forest inventory data show markedly divergent estimates, even after accounting for reported uncertainties. To address this, a network of high-quality reference data is needed to calibrate and validate mapping algorithms. This study aims to generate reference AGB datasets using field inventory plots and airborne LiDAR data for eight sites in Central Africa and five sites in South Asia, two regions largely underrepresented in global reference AGB datasets. The study provides access to these reference AGB maps, including uncertainty maps, at 100 m and 40 m spatial resolutions covering a total LiDAR footprint of 1,11,650 ha [ranging from 150 to 40,000 ha at site level]. These maps serve as calibration/validation datasets to improve the accuracy and reliability of AGB mapping for current and upcoming EO missions (viz., GEDI, BIOMASS, and NISAR)