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).

Development and characterization of nuclear microsatellite markers for the African walnut Coula edulis Baill (Coulaceae).

PREMISE OF THE STUDY: Coula edulis Baill (Coulaceae) is a common tree species in the Guineo-Congolian forests producing an edible fruit known as African walnut, which is an important food and income resource for rural populations. However, the species suffers from a deficit of natural regeneration. We developed here nuclear microsatellite markers for C. edulis to be able to study the genetic structure of its natural populations and gene flow. METHODS AND RESULTS: A genomic library was obtained using the Illumina platform, and 21 polymorphic microsatellite loci were developed. The polymorphic microsatellites displayed eight to 22 alleles per locus (average: 14.2), with a mean expected heterozygosity ranging from 0.33 to 0.72 in five populations from Central and West Africa. CONCLUSIONS: The high polymorphism of the nuclear microsatellite markers developed makes them useful to investigate gene flow and the organization of genetic diversity in C. edulis, and to assess whether particular genetic resources require conservation efforts.

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.

Tectonics, climate and the diversification of the tropical African terrestrial flora and fauna.

Tropical Africa is home to an astonishing biodiversity occurring in a variety of ecosystems. Past climatic change and geological events have impacted the evolution and diversification of this biodiversity. During the last two decades, around 90 dated molecular phylogenies of different clades across animals and plants have been published leading to an increased understanding of the diversification and speciation processes generating tropical African biodiversity. In parallel, extended geological and palaeoclimatic records together with detailed numerical simulations have refined our understanding of past geological and climatic changes in Africa. To date, these important advances have not been reviewed within a common framework. Here, we critically review and synthesize African climate, tectonics and terrestrial biodiversity evolution throughout the Cenozoic to the mid-Pleistocene, drawing on recent advances in Earth and life sciences. We first review six major geo-climatic periods defining tropical African biodiversity diversification by synthesizing 89 dated molecular phylogeny studies. Two major geo-climatic factors impacting the diversification of the sub-Saharan biota are highlighted. First, Africa underwent numerous climatic fluctuations at ancient and more recent timescales, with tectonic, greenhouse gas, and orbital forcing stimulating diversification. Second, increased aridification since the Late Eocene led to important extinction events, but also provided unique diversification opportunities shaping the current tropical African biodiversity landscape. We then review diversification studies of tropical terrestrial animal and plant clades and discuss three major models of speciation: (i) geographic speciation via vicariance (allopatry); (ii) ecological speciation impacted by climate and geological changes, and (iii) genomic speciation via genome duplication. Geographic speciation has been the most widely documented to date and is a common speciation model across tropical Africa. We conclude with four important challenges faced by tropical African biodiversity research: (i) to increase knowledge by gathering basic and fundamental biodiversity information; (ii) to improve modelling of African geophysical evolution throughout the Cenozoic via better constraints and downscaling approaches; (iii) to increase the precision of phylogenetic reconstruction and molecular dating of tropical African clades by using next generation sequencing approaches together with better fossil calibrations; (iv) finally, as done here, to integrate data better from Earth and life sciences by focusing on the interdisciplinary study of the evolution of tropical African biodiversity in a wider geodiversity context.

Multistability of model and real dryland ecosystems through spatial self-organization.

Spatial self-organization of dryland vegetation constitutes one of the most promising indicators for an ecosystem's proximity to desertification. This insight is based on studies of reaction-diffusion models that reproduce visual characteristics of vegetation patterns observed on aerial photographs. However, until now, the development of reliable early warning systems has been hampered by the lack of more in-depth comparisons between model predictions and real ecosystem patterns. In this paper, we combined topographical data, (remotely sensed) optical data, and in situ biomass measurements from two sites in Somalia to generate a multilevel description of dryland vegetation patterns. We performed an in-depth comparison between these observed vegetation pattern characteristics and predictions made by the extended-Klausmeier model for dryland vegetation patterning. Consistent with model predictions, we found that for a given topography, there is multistability of ecosystem states with different pattern wavenumbers. Furthermore, observations corroborated model predictions regarding the relationships between pattern wavenumber, total biomass, and maximum biomass. In contrast, model predictions regarding the role of slope angles were not corroborated by the empirical data, suggesting that inclusion of small-scale topographical heterogeneity is a promising avenue for future model development. Our findings suggest that patterned dryland ecosystems may be more resilient to environmental change than previously anticipated, but this enhanced resilience crucially depends on the adaptive capacity of vegetation patterns.

Exploring the floristic diversity of tropical Africa.

BACKGROUND: Understanding the patterns of biodiversity distribution and what influences them is a fundamental pre-requisite for effective conservation and sustainable utilisation of biodiversity. Such knowledge is increasingly urgent as biodiversity responds to the ongoing effects of global climate change. Nowhere is this more acute than in species-rich tropical Africa, where so little is known about plant diversity and its distribution. In this paper, we use RAINBIO - one of the largest mega-databases of tropical African vascular plant species distributions ever compiled - to address questions about plant and growth form diversity across tropical Africa. RESULTS: The filtered RAINBIO dataset contains 609,776 georeferenced records representing 22,577 species. Growth form data are recorded for 97% of all species. Records are well distributed, but heterogeneous across the continent. Overall, tropical Africa remains poorly sampled. When using sampling units (SU) of 0.5°, just 21 reach appropriate collection density and sampling completeness, and the average number of records per species per SU is only 1.84. Species richness (observed and estimated) and endemism figures per country are provided. Benin, Cameroon, Gabon, Ivory Coast and Liberia appear as the botanically best-explored countries, but none are optimally explored. Forests in the region contain 15,387 vascular plant species, of which 3013 are trees, representing 5-7% of the estimated world's tropical tree flora. The central African forests have the highest endemism rate across Africa, with approximately 30% of species being endemic. CONCLUSIONS: The botanical exploration of tropical Africa is far from complete, underlining the need for intensified inventories and digitization. We propose priority target areas for future sampling efforts, mainly focused on Tanzania, Atlantic Central Africa and West Africa. The observed number of tree species for African forests is smaller than those estimated from global tree data, suggesting that a significant number of species are yet to be discovered. Our data provide a solid basis for a more sustainable management and improved conservation of tropical Africa's unique flora, and is important for achieving Objective 1 of the Global Strategy for Plant Conservation 2011-2020. In turn, RAINBIO provides a solid basis for a more sustainable management and improved conservation of tropical Africa's unique flora.

ConR: An R package to assist large-scale multispecies preliminary conservation assessments using distribution data.

The Red List Categories and the accompanying five criteria developed by the International Union for Conservation of Nature (IUCN) provide an authoritative and comprehensive methodology to assess the conservation status of organisms. Red List criterion B, which principally uses distribution data, is the most widely used to assess conservation status, particularly of plant species. No software package has previously been available to perform large-scale multispecies calculations of the three main criterion B parameters [extent of occurrence (EOO), area of occupancy (AOO) and an estimate of the number of locations] and provide preliminary conservation assessments using an automated batch process. We developed ConR, a dedicated R package, as a rapid and efficient tool to conduct large numbers of preliminary assessments, thereby facilitating complete Red List assessment. ConR (1) calculates key geographic range parameters (AOO and EOO) and estimates the number of locations sensu IUCN needed for an assessment under criterion B; (2) uses this information in a batch process to generate preliminary assessments of multiple species; (3) summarize the parameters and preliminary assessments in a spreadsheet; and (4) provides a visualization of the results by generating maps suitable for the submission of full assessments to the IUCN Red List. ConR can be used for any living organism for which reliable georeferenced distribution data are available. As distributional data for taxa become increasingly available via large open access datasets, ConR provides a novel, timely tool to guide and accelerate the work of the conservation and taxonomic communities by enabling practitioners to conduct preliminary assessments simultaneously for hundreds or even thousands of species in an efficient and time-saving way.

RAINBIO: a mega-database of tropical African vascular plants distributions.

The tropical vegetation of Africa is characterized by high levels of species diversity but is undergoing important shifts in response to ongoing climate change and increasing anthropogenic pressures. Although our knowledge of plant species distribution patterns in the African tropics has been improving over the years, it remains limited. Here we present RAINBIO, a unique comprehensive mega-database of georeferenced records for vascular plants in continental tropical Africa. The geographic focus of the database is the region south of the Sahel and north of Southern Africa, and the majority of data originate from tropical forest regions. RAINBIO is a compilation of 13 datasets either publicly available or personal ones. Numerous in depth data quality checks, automatic and manual via several African flora experts, were undertaken for georeferencing, standardization of taxonomic names and identification and merging of duplicated records. The resulting RAINBIO data allows exploration and extraction of distribution data for 25,356 native tropical African vascular plant species, which represents ca. 89% of all known plant species in the area of interest. Habit information is also provided for 91% of these species.

Pervasive Local-Scale Tree-Soil Habitat Association in a Tropical Forest Community.

We examined tree-soil habitat associations in lowland forest communities at Paracou, French Guiana. We analyzed a large dataset assembling six permanent plots totaling 37.5 ha, in which extensive LIDAR-derived topographical data and soil chemical and physical data have been integrated with precise botanical determinations. Map of relative elevation from the nearest stream summarized both soil fertility and hydromorphic characteristics, with seasonally inundated bottomlands having higher soil phosphate content and base saturation, and plateaus having higher soil carbon, nitrogen and aluminum contents. We employed a statistical test of correlations between tree species density and environmental maps, by generating Monte Carlo simulations of random raster images that preserve autocorrelation of the original maps. Nearly three fourths of the 94 taxa with at least one stem per ha showed a significant correlation between tree density and relative elevation, revealing contrasted species-habitat associations in term of abundance, with seasonally inundated bottomlands (24.5% of species) and well-drained plateaus (48.9% of species). We also observed species preferences for environments with or without steep slopes (13.8% and 10.6%, respectively). We observed that closely-related species were frequently associated with different soil habitats in this region (70% of the 14 genera with congeneric species that have a significant association test) suggesting species-habitat associations have arisen multiple times in this tree community. We also tested if species with similar habitat preferences shared functional strategies. We found that seasonally inundated forest specialists tended to have smaller stature (maximum diameter) than species found on plateaus. Our results underline the importance of tree-soil habitat associations in structuring diverse communities at fine spatial scales and suggest that additional studies are needed to disentangle community assembly mechanisms related to dispersal limitation, biotic interactions and environmental filtering from species-habitat associations. Moreover, they provide a framework to generalize across tropical forest sites.

Testing pairwise association between spatially autocorrelated variables: a new approach using surrogate lattice data.

BACKGROUND: Independence between observations is a standard prerequisite of traditional statistical tests of association. This condition is, however, violated when autocorrelation is present within the data. In the case of variables that are regularly sampled in space (i.e. lattice data or images), such as those provided by remote-sensing or geographical databases, this problem is particularly acute. Because analytic derivation of the null probability distribution of the test statistic (e.g. Pearson's r) is not always possible when autocorrelation is present, we propose instead the use of a Monte Carlo simulation with surrogate data. METHODOLOGY/PRINCIPAL FINDINGS: The null hypothesis that two observed mapped variables are the result of independent pattern generating processes is tested here by generating sets of random image data while preserving the autocorrelation function of the original images. Surrogates are generated by matching the dual-tree complex wavelet spectra (and hence the autocorrelation functions) of white noise images with the spectra of the original images. The generated images can then be used to build the probability distribution function of any statistic of association under the null hypothesis. We demonstrate the validity of a statistical test of association based on these surrogates with both actual and synthetic data and compare it with a corrected parametric test and three existing methods that generate surrogates (randomization, random rotations and shifts, and iterative amplitude adjusted Fourier transform). Type I error control was excellent, even with strong and long-range autocorrelation, which is not the case for alternative methods. CONCLUSIONS/SIGNIFICANCE: The wavelet-based surrogates are particularly appropriate in cases where autocorrelation appears at all scales or is direction-dependent (anisotropy). We explore the potential of the method for association tests involving a lattice of binary data and discuss its potential for validation of species distribution models. An implementation of the method in Java for the generation of wavelet-based surrogates is available online as supporting material.

Spatial decoupling of facilitation and competition at the origin of gapped vegetation patterns.

Spatially periodic vegetation patterns, forming gaps, bands, labyrinths, or spots, are characteristic of arid and semiarid landscapes. Self-organization models can explain this variety of structures within a unified conceptual framework. All these models are based on the interplay of positive and negative effects of plants on soil water, but they can be divided according to whether they assume the interactions to be mediated by water redistribution through runoff/diffusion or by plants' organs. We carried out a multi-proxy approach of the processes operating in a gapped pattern in southwest Niger dominated by a shrub species. Soil moisture within the root layer was monitored in time and space over one month of the rainy season. Soil water recharge displayed no spatial variation with respect to vegetation cover, but the stock half-life under cover was twice that of bare areas. A kernel of facilitation by the aboveground parts of shrubs was parameterized, and soil water half-life was significantly correlated to the cumulated facilitative effects of shrubs. The kernel range was found to be smaller than the canopy radius (81%). This effect of plants on soil water dynamics, probably through a reduction of evaporation by shading, is shown to be a better explanatory variable than potentially relevant soil and topography parameters. The root systems of five individuals of Combretum micranthum G. Don were excavated. Root density data were used as a proxy to parameterize a kernel function of interplant competition. The range of this kernel was larger than the canopy radius (125%). The facilitation-to-competition range ratio, reflecting the above-to-belowground ratio of plant lateral extent, was smaller than 1 (0.64), a result supporting models assuming that patterning may emerge from an adaptation of plant morphology to aridity and shallow soils by means of an extended lateral root system. Moreover, observed soil water gradients had directions opposite to those assumed by alternative mathematical models based on underground water diffusion. This study contributes to the growing awareness that combined facilitative and competitive plant interactions can induce landscape-scale patterns and shape the two-way feedback loops between environment and vegetation.