Exploring the relation between remotely sensed vertical canopy structure and tree species diversity in Gabon

Mapping tree species diversity is increasingly important in the face of environmental change and biodiversity conservation. We explore a potential way of mapping this diversity by relating forest structure to tree species diversity in Gabon. First, we test the relation between canopy height, as a proxy for niche volume, and tree species diversity. Then, we test the relation between vertical canopy structure, as a proxy for vertical niche occupation, and tree species diversity. We use large footprint full-waveform airborne lidar data collected across four study sites in Gabon (Lopé, Mabounié, Mondah, and Rabi) in combination with in situ estimates of species richness (S) and Shannon diversity (H'). Linear models using canopy height explained 44% and 43% of the variation in S and H' at the 0.25 ha resolution. Linear models using canopy height and the plant area volume density profile explained 71% of this variation. We demonstrate applications of these models by mapping S and H' in Mondah using a simulated GEDI-TanDEM-X fusion height product, across the four sites using wall-to-wall airborne lidar data products, and across and between the study sites using ICESat lidar waveforms. The modeling results are encouraging in the context of developing pan-tropical structure-diversity models applicable to data from current and upcoming spaceborne remote sensing missions

Evaluating the potential of full-waveform lidar for mapping pan-tropical tree species richness

AIM: Mapping tree species richness across the tropics is of great interest for effective conservation and biodiversity management. In this study, we evaluated the potential of full‐waveform lidar data for mapping tree species richness across the tropics by relating measurements of vertical canopy structure, as a proxy for the occupation of vertical niche space, to tree species richness. LOCATION: Tropics. TIME PERIOD: Present. MAJOR TAXA STUDIED: Trees. METHODS: First, we evaluated the characteristics of vertical canopy structure across 15 study sites using (simulated) large‐footprint full‐waveform lidar data (22 m diameter) and related these findings to in‐situ tree species information. Then, we developed structure–richness models at the local (within 25–50 ha plots), regional (biogeographical regions) and pan‐tropical scale at three spatial resolutions (1.0, 0.25 and 0.0625 ha) using Poisson regression. RESULTS: The results showed a weak structure–richness relationship at the local scale. At the regional scale (within a biogeographical region) a stronger relationship between canopy structure and tree species richness across different tropical forest types was found, for example across Central Africa and in South America [R^{2} ranging from .44–.56, root mean squared difference as a percentage of the mean (RMSD%) ranging between 23–61%]. Modelling the relationship pan‐tropically, across four continents, 39% of the variation in tree species richness could be explained with canopy structure alone (R^{2} = .39 and RMSD% = 43%, 0.25‐ha resolution). MAIN CONCLUSIONS: Our results may serve as a basis for the future development of a set of structure–richness models to map high resolution tree species richness using vertical canopy structure information from the Global Ecosystem Dynamics Investigation (GEDI). The value of this effort would be enhanced by access to a larger set of field reference data for all tropical regions. Future research could also support the use of GEDI data in frameworks using environmental and spectral information for modelling tree species richness across the tropics

The number of tree species on Earth

One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknown. Here, based on global groundsourced data, we estimate the total tree species richness at global, continental, and biome levels. Our results indicate that there are 73,000 tree species globally, among which ∼9,000 tree species are yet to be discovered. Roughly 40% of undiscovered tree species are in South America. Moreover, almost one-third of all tree species to be discovered may be rare, with very low populations and limited spatial distribution (likely in remote tropical lowlands and mountains). These findings highlight the vulnerability of global forest biodiversity to anthropogenic changes in land use and climate, which disproportionately threaten rare species and thus, global tree richness

Venom toxicity and composition in three Pseudomyrmex ant species having different nesting modes

We aimed to determine whether the nesting habits of ants have influenced their venom toxicity and composition. We focused on the genus Pseudomyrmex (Pseudomyrmecinae) comprising terrestrial and arboreal species, and, among the latter, plant-ants that are obligate inhabitants of myrmecophytes (i.e., plants sheltering ants in hollow structures). Contrary to our hypothesis, the venom of the ground-dwelling species, Pseudomyrmex termitarius, was as efficacious in paralyzing prey as the venoms of the arboreal and the plant-ant species, Pseudomyrmex penetrator and Pseudomyrmex gracilis. The lethal potency of P. termitarius venom was equipotent with that of P. gracilis whereas the venom of P. penetrator was less potent. The MALDI-TOF MS analysis of each HPLC fraction of the venoms showed that P. termitarius venom is composed of 87 linear peptides, while both P. gracilis and P. penetrator venoms (23 and 26 peptides, respectively) possess peptides with disulfide bonds. Furthermore, P. penetrator venom contains three hetero- and homodimeric peptides consisting of two short peptidic chains linked together by two interchain disulfide bonds. The large number of peptides in P. termitarius venom is likely related to the large diversity of potential prey plus the antibacterial peptides required for nesting in the ground. Whereas predation involves only the prey and predator, P. penetrator venom has evolved in an environment where trees, defoliating insects, browsing mammals and ants live in equilibrium, likely explaining the diversity of the peptide structures

The global forest above-ground biomass pool for 2010 estimated from high-resolution satellite observations

The terrestrial forest carbon pool is poorly quantified, in particular in regions with low forest inventory capacity. By combining multiple satellite observations of synthetic aperture radar (SAR) backscatter around the year 2010, we generated a global, spatially explicit dataset of above-ground forest biomass (dry mass, AGB) with a spatial resolution of 1 ha. Using an extensive database of 110,897 AGB measurements from field inventory plots, we show that the spatial patterns and magnitude of AGB are well captured in our map with the exception of regional uncertainties in high carbon stock forests with AGB > 250 Mg ha-1 where the retrieval was effectively based on a single radar observation. With a total global AGB of 522 Pg, our estimate of the terrestrial biomass pool in forests is lower than most estimates published in literature (426 - 571 Pg). Nonetheless, our dataset increases knowledge on the spatial distribution of AGB compared to the global Forest Resources Assessment (FRA) by the Food and Agriculture Organization (FAO) and highlights the impact of a country’s national inventory capacity on the accuracy of the biomass statistics reported to the FRA. We also reassessed previous remote sensing AGB maps, and identify major biases compared to inventory data, up to 120% of the inventory value in dry tropical forests, in the sub-tropics and temperate zone. Because of the high level of detail and the overall reliability of the AGB spatial patterns, our global dataset of AGB is likely to have significant impacts on climate, carbon and socio-economic modelling schemes, and provides a crucial baseline in future carbon stock changes estimates. The dataset is available at: https://doi.pangaea.de/10.1594/PANGAEA.894711 (Santoro, 2018)

The number of tree species on Earth

One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknown. Here, based on global ground-sourced data, we estimate the total tree species richness at global, continental, and biome levels. Our results indicate that there are ∼73,000 tree species globally, among which ∼9,000 tree species are yet to be discovered. Roughly 40% of undiscovered tree species are in South America. Moreover, almost one-third of all tree species to be discovered may be rare, with very low populations and limited spatial distribution (likely in remote tropical lowlands and mountains). These findings highlight the vulnerability of global forest biodiversity to anthropogenic changes in land use and climate, which disproportionately threaten rare species and thus, global tree richness

A comprehensive framework for assessing the accuracy and uncertainty of global above-ground biomass maps

Over the past decade, several global maps of above-ground biomass (AGB) have been produced, but they exhibit significant differences that reduce their value for climate and carbon cycle modelling, and also for national estimates of forest carbon stocks and their changes. The number of such maps is anticipated to increase because of new satellite missions dedicated to measuring AGB. Objective and consistent methods to estimate the accuracy and uncertainty of AGB maps are therefore urgently needed. This paper develops and demonstrates a framework aimed at achieving this. The framework provides a means to compare AGB maps with AGB estimates from a global collection of National Forest Inventories and research plots that accounts for the uncertainty of plot AGB errors. This uncertainty depends strongly on plot size, and is dominated by the combined errors from tree measurements and allometric models (inter-quartile range of their standard deviation (SD) = 30–151 Mg ha−1). Estimates of sampling errors are also important, especially in the most common case where plots are smaller than map pixels (SD = 16–44 Mg ha−1). Plot uncertainty estimates are used to calculate the minimum-variance linear unbiased estimates of the mean forest AGB when averaged to 0.1∘. These are used to assess four AGB maps: Baccini (2000), GEOCARBON (2008), GlobBiomass (2010) and CCI Biomass (2017). Map bias, estimated using the differences between the plot and 0.1∘ map averages, is modelled using random forest regression driven by variables shown to affect the map estimates. The bias model is particularly sensitive to the map estimate of AGB and tree cover, and exhibits strong regional biases. Variograms indicate that AGB map errors have map-specific spatial correlation up to a range of 50–104 km, which increases the variance of spatially aggregated AGB map estimates compared to when pixel errors are independent. After bias adjustment, total pantropical AGB and its associated SD are derived for the four map epochs. This total becomes closer to the value estimated by the Forest Resources Assessment after every epoch and shows a similar decrease. The framework is applicable to both local and global-scale analysis, and is available at https://github.com/arnanaraza/PlotToMap. Our study therefore constitutes a major step towards improved AGB map validation and improvement

The Forest Observation System, building a global reference dataset for remote sensing of forest biomass [data paper]

Forest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world's forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS- based biomass products while developing new synergies between the RS and ground-based ecosystem research communities