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).

The puzzling ecology of African Marantaceae forests.

Marantaceae forests are tropical rainforests characterized by a continuous understory layer of perennial giant herbs and a near absence of tree regeneration. Although widespread in West-Central Africa, Marantaceae forests have rarely been considered in the international literature. Yet, they pose key challenges and opportunities for theoretical ecology that transcend the borders of the continent. Specifically, we ask in this review whether open Marantaceae forests and dense closed-canopy forests can be considered as one of the few documented examples of alternative stable states in tropical forests. First, we introduce the different ecological factors that have been posited to drive Marantaceae forests (climate, soil, historical and recent anthropogenic pressures, herbivores) and develop the different hypotheses that have been suggested to explain how Marantaceae forests establish in relation with other vegetation types (understory invasion, early succession after disturbance, and intermediate successional stage). Then, we review the underlying ecological mechanisms that can explain the stability of Marantaceae forests in the long term (tree recruitment inhibition, promotion of and resilience to fire, adaptive reproduction, maintenance by megaherbivores). Although some uncertainties remain and call for further empirical and theoretical research, we found converging evidence that Marantaceae forests are associated with an ecological succession that has been deflected or arrested. If verified, Marantaceae forests may provide a useful model to understand critical transitions in forest ecosystems, which is of particular relevance to achieve sustainable forest management and mitigate global climate change.

Unveiling African rainforest composition and vulnerability to global change.

Africa is forecasted to experience large and rapid climate change1 and population growth2 during the twenty-first century, which threatens the world's second largest rainforest. Protecting and sustainably managing these African forests requires an increased understanding of their compositional heterogeneity, the environmental drivers of forest composition and their vulnerability to ongoing changes. Here, using a very large dataset of 6 million trees in more than 180,000 field plots, we jointly model the distribution in abundance of the most dominant tree taxa in central Africa, and produce continuous maps of the floristic and functional composition of central African forests. Our results show that the uncertainty in taxon-specific distributions averages out at the community level, and reveal highly deterministic assemblages. We uncover contrasting floristic and functional compositions across climates, soil types and anthropogenic gradients, with functional convergence among types of forest that are floristically dissimilar. Combining these spatial predictions with scenarios of climatic and anthropogenic global change suggests a high vulnerability of the northern and southern forest margins, the Atlantic forests and most forests in the Democratic Republic of the Congo, where both climate and anthropogenic threats are expected to increase sharply by 2085. These results constitute key quantitative benchmarks for scientists and policymakers to shape transnational conservation and management strategies that aim to provide a sustainable future for central African forests.

Amazon tree dominance across forest strata.

The forests of Amazonia are among the most biodiverse plant communities on Earth. Given the immediate threats posed by climate and land-use change, an improved understanding of how this extraordinary biodiversity is spatially organized is urgently required to develop effective conservation strategies. Most Amazonian tree species are extremely rare but a few are common across the region. Indeed, just 227 'hyperdominant' species account for >50% of all individuals >10 cm diameter at 1.3 m in height. Yet, the degree to which the phenomenon of hyperdominance is sensitive to tree size, the extent to which the composition of dominant species changes with size class and how evolutionary history constrains tree hyperdominance, all remain unknown. Here, we use a large floristic dataset to show that, while hyperdominance is a universal phenomenon across forest strata, different species dominate the forest understory, midstory and canopy. We further find that, although species belonging to a range of phylogenetically dispersed lineages have become hyperdominant in small size classes, hyperdominants in large size classes are restricted to a few lineages. Our results demonstrate that it is essential to consider all forest strata to understand regional patterns of dominance and composition in Amazonia. More generally, through the lens of 654 hyperdominant species, we outline a tractable pathway for understanding the functioning of half of Amazonian forests across vertical strata and geographical locations.

Spatial validation reveals poor predictive performance of large-scale ecological mapping models.

Mapping aboveground forest biomass is central for assessing the global carbon balance. However, current large-scale maps show strong disparities, despite good validation statistics of their underlying models. Here, we attribute this contradiction to a flaw in the validation methods, which ignore spatial autocorrelation (SAC) in data, leading to overoptimistic assessment of model predictive power. To illustrate this issue, we reproduce the approach of large-scale mapping studies using a massive forest inventory dataset of 11.8 million trees in central Africa to train and validate a random forest model based on multispectral and environmental variables. A standard nonspatial validation method suggests that the model predicts more than half of the forest biomass variation, while spatial validation methods accounting for SAC reveal quasi-null predictive power. This study underscores how a common practice in big data mapping studies shows an apparent high predictive power, even when predictors have poor relationships with the ecological variable of interest, thus possibly leading to erroneous maps and interpretations.

A map of African humid tropical forest aboveground biomass derived from management inventories.

Forest biomass is key in Earth carbon cycle and climate system, and thus under intense scrutiny in the context of international climate change mitigation initiatives (e.g. REDD+). In tropical forests, the spatial distribution of aboveground biomass (AGB) remains, however, highly uncertain. There is increasing recognition that progress is strongly limited by the lack of field observations over large and remote areas. Here, we introduce the Congo basin Forests AGB (CoFor-AGB) dataset that contains AGB estimations and associated uncertainty for 59,857 1-km pixels aggregated from nearly 100,000 ha of in situ forest management inventories for the 2000 - early 2010s period in five central African countries. A comprehensive error propagation scheme suggests that the uncertainty on AGB estimations derived from c. 0.5-ha inventory plots (8.6-15.0%) is only moderately higher than the error obtained from scientific sampling plots (8.3%). CoFor-AGB provides the first large scale view of forest AGB spatial variation from field data in central Africa, the second largest continuous tropical forest domain of the world.

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.

The Forest Observation System, building a global reference dataset for remote sensing of forest biomass.

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.

Body size determines soil community assembly in a tropical forest.

Tropical forests shelter an unparalleled biological diversity. The relative influence of environmental selection (i.e., abiotic conditions, biotic interactions) and stochastic-distance-dependent neutral processes (i.e., demography, dispersal) in shaping communities has been extensively studied for various organisms, but has rarely been explored across a large range of body sizes, in particular in soil environments. We built a detailed census of the whole soil biota in a 12-ha tropical forest plot using soil DNA metabarcoding. We show that the distribution of 19 taxonomic groups (ranging from microbes to mesofauna) is primarily stochastic, suggesting that neutral processes are prominent drivers of the assembly of these communities at this scale. We also identify aluminium, topography and plant species identity as weak, yet significant drivers of soil richness and community composition of bacteria, protists and to a lesser extent fungi. Finally, we show that body size, which determines the scale at which an organism perceives its environment, predicted the community assembly across taxonomic groups, with soil mesofauna assemblages being more stochastic than microbial ones. These results suggest that the relative contribution of neutral processes and environmental selection to community assembly directly depends on body size. Body size is hence an important determinant of community assembly rules at the scale of the ecological community in tropical soils and should be accounted for in spatial models of tropical soil food webs.

India Biodiversity Portal: An integrated, interactive and participatory biodiversity informatics platform.

BACKGROUND: This paper describes a growing biodiversity platform, launched in 2008, which organizes knowledge on the biodiversity of India. The main objective and originality of the India Biodiversity Portal (IBP) is to aggregate curated biodiversity data of different kinds (e.g. distribution maps, temporal distribution or life history) in an integrated platform where amateurs and experts can easily interact. NEW INFORMATION: Since its launch, the platform has seen an exceptional increase in both user activity and biodiversity data. Currently the portal has descriptions of over 20,400 species, and has aggregated approximately 1,280,000 observations covering more than 30,000 species, which already constitutes a unique source of information for scientists and stakeholders in conservation. Over 8500 users have registered on the portal. The amount of data generated and to be generated in the next few years by this portal will certainly help the effective implementation of biodiversity conservation and management in one of the most ecologically diverse countries in the world.

Hyperdominance in Amazonian forest carbon cycling.

While Amazonian forests are extraordinarily diverse, the abundance of trees is skewed strongly towards relatively few 'hyperdominant' species. In addition to their diversity, Amazonian trees are a key component of the global carbon cycle, assimilating and storing more carbon than any other ecosystem on Earth. Here we ask, using a unique data set of 530 forest plots, if the functions of storing and producing woody carbon are concentrated in a small number of tree species, whether the most abundant species also dominate carbon cycling, and whether dominant species are characterized by specific functional traits. We find that dominance of forest function is even more concentrated in a few species than is dominance of tree abundance, with only ≈1% of Amazon tree species responsible for 50% of carbon storage and productivity. Although those species that contribute most to biomass and productivity are often abundant, species maximum size is also influential, while the identity and ranking of dominant species varies by function and by region.

Improved allometric models to estimate the aboveground biomass of tropical trees.

Terrestrial carbon stock mapping is important for the successful implementation of climate change mitigation policies. Its accuracy depends on the availability of reliable allometric models to infer oven-dry aboveground biomass of trees from census data. The degree of uncertainty associated with previously published pantropical aboveground biomass allometries is large. We analyzed a global database of directly harvested trees at 58 sites, spanning a wide range of climatic conditions and vegetation types (4004 trees ≥ 5 cm trunk diameter). When trunk diameter, total tree height, and wood specific gravity were included in the aboveground biomass model as covariates, a single model was found to hold across tropical vegetation types, with no detectable effect of region or environmental factors. The mean percent bias and variance of this model was only slightly higher than that of locally fitted models. Wood specific gravity was an important predictor of aboveground biomass, especially when including a much broader range of vegetation types than previous studies. The generic tree diameter-height relationship depended linearly on a bioclimatic stress variable E, which compounds indices of temperature variability, precipitation variability, and drought intensity. For cases in which total tree height is unavailable for aboveground biomass estimation, a pantropical model incorporating wood density, trunk diameter, and the variable E outperformed previously published models without height. However, to minimize bias, the development of locally derived diameter-height relationships is advised whenever possible. Both new allometric models should contribute to improve the accuracy of biomass assessment protocols in tropical vegetation types, and to advancing our understanding of architectural and evolutionary constraints on woody plant development.

High-resolution forest mapping for behavioural studies in the Nature Reserve 'Les Nouragues', French Guiana.

For animals with spatially complex behaviours at relatively small scales, the resolution of a global positioning system (GPS) receiver location is often below the resolution needed to correctly map animals' spatial behaviour. Natural conditions such as canopy cover, canyons or clouds can further degrade GPS receiver reception. Here we present a detailed, high-resolution map of a 4.6 ha Neotropical river island and a 8.3 ha mainland plot with the location of every tree >5 cm DBH and all structures on the forest floor, which are relevant to our study species, the territorial frog Allobates femoralis (Dendrobatidae). The map was derived using distance- and compass-based survey techniques, rooted on dGPS reference points, and incorporates altitudinal information based on a LiDAR survey of the area.

Geological substrates shape tree species and trait distributions in African moist forests.

BACKGROUND: Understanding the factors that shape the distribution of tropical tree species at large scales is a central issue in ecology, conservation and forest management. The aims of this study were to (i) assess the importance of environmental factors relative to historical factors for tree species distributions in the semi-evergreen forests of the northern Congo basin; and to (ii) identify potential mechanisms explaining distribution patterns through a trait-based approach. METHODOLOGY/PRINCIPAL FINDINGS: We analyzed the distribution patterns of 31 common tree species in an area of more than 700,000 km(2) spanning the borders of Cameroon, the Central African Republic, and the Republic of Congo using forest inventory data from 56,445 0.5-ha plots. Spatial variation of environmental (climate, topography and geology) and historical factors (human disturbance) were quantified from maps and satellite records. Four key functional traits (leaf phenology, shade tolerance, wood density, and maximum growth rate) were extracted from the literature. The geological substrate was of major importance for the distribution of the focal species, while climate and past human disturbances had a significant but lesser impact. Species distribution patterns were significantly related to functional traits. Species associated with sandy soils typical of sandstone and alluvium were characterized by slow growth rates, shade tolerance, evergreen leaves, and high wood density, traits allowing persistence on resource-poor soils. In contrast, fast-growing pioneer species rarely occurred on sandy soils, except for Lophira alata. CONCLUSIONS/SIGNIFICANCE: The results indicate strong environmental filtering due to differential soil resource availability across geological substrates. Additionally, long-term human disturbances in resource-rich areas may have accentuated the observed patterns of species and trait distributions. Trait differences across geological substrates imply pronounced differences in population and ecosystem processes, and call for different conservation and management strategies.

Properties of similarity indices under niche-based and dispersal-based processes in communities.

Little is known about the combined impact of habitat filtering and dispersal limitation on species turnover patterns. To gain new insights, we constructed a spatially explicit community model wherein we controlled dispersal distances, the strength of habitat filtering, and the grain of habitat heterogeneity to study the distance decay of several (dis)similarity indices. The impact of habitat filtering is dependent on the ratio between the grain of habitats and the mean dispersal distance. The behavior of (dis)similarity indices varies. First, incidence-based measures of species overlap are less affected by habitat filtering than are abundance-based indices. Second, species identity-based indices, derived from population genetics' F(ST), show interesting capacities to infer dispersal processes under neutrality but are also highly sensitive to habitat filtering. All indices except F(ST)-related indices under neutrality are very sensitive to overall species richness. Hence, community patterns showing contrasted diversity levels should be compared with caution. Partitioning similarity indices within and between habitats appears to be an efficient approach to assess the strength of habitat filtering, and we show that a torus-translation test is powerful for this purpose. We finally highlight the need for further analytical studies to achieve theoretical expectations of similarity decay under dispersal and niche processes.