Vincent Deblauwe

Determinants and dynamics of banded vegetation pattern migration in arid climates

Dense vegetation bands aligned to contour levels and alternating at regular intervals with relatively barren interbands have been reported at the margins of all tropical deserts. Since their discovery in the 1950s, it has been supposed that these vegetation bands migrate upslope, forming a space-time cyclic pattern. Evidence to date has been relatively sparse and indirect, and observations have remained conflicting. Unequivocal photographic evidence of upslope migration (a few decimeters per year) is provided here for three independent dryland areas exhibiting periodic banded pattern: (1) the U.S. northeastern Chihuahuan Desert, (2) the Somalian Haud, and (3) the Mediterranean steppes of eastern Morocco. Migration speeds, averaged through time and space using Fourier cross-spectral analysis, are shown to be directly proportional to pattern scale (wavelength). A sequence of aerial photographs of the Chihuahuan Desert showed that migration was not continuous, but intermittent in response to fluctuating weather regimes. The rates at which bands expanded upslope and contracted downslope were better predicted by the change in annual rainfall than by its average level. However, the migration of banded patterns cannot be considered as systematic because in our observations of three other banded systems located in the Somalian Haud, central Australia, and western New South Wales, migration was undetectable at the available image resolution. In each of the six sites under study, the modal value of band orientation axes was verified to be approximately orthogonal to the steepest slope. Our results underscore the importance of taking both the spatial structure and the past climate sequence into account for understanding vegetation dynamics in arid to semiarid ecosystems. In addition, we show how Fourier spectral analysis applied to historical series of optical images can serve to quantify landscape dynamics at a decadal time scale.

Morph differences and honeybee morph preference in the distylous species Fagopyrum esculentum Moench

The relatively low reproductive success of buckwheat (Fagopyrum esculentum Moench, Polygonaceae) is poorly understood. The question arises as to whether this distylous species is pollen or resource limited. We investigated the reproductive biology of buckwheat under controlled conditions in growth rooms and in the field in central Belgium in order to determine whether floral morph and pollination events may affect its reproductive success. In controlled conditions, flowering phenology and flower morphology of the two floral morphs did not differ. However, thrum flowers produced larger and fewer pollen grains and secreted more nectar, with a higher proportion of sucrose, than pin flowers. In the field, thrum flowers were preferentially visited by honeybees, but fewer pollen grains were deposited on their stigmas. However, numbers of pollen tubes growing in styles, seed set, and seed weight did not differ between morphs. Seed set was low under field conditions and did not increase after hand cross‐pollinations, suggesting that there was no pollen limitation. These results indicate that factors other than floral morph or pollination events were governing female fertility in buckwheat.

Exploring the floristic diversity of tropical Africa

BackgroundUnderstanding 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.ResultsThe 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.ConclusionsThe 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.

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. Pearsons 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.

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

Abstract 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.

Phylogeography of the genus Podococcus (Palmae/Arecaceae) in Central African rain forests: Climate stability predicts unique genetic diversity.

The tropical rain forests of Central Africa contain high levels of species diversity. Paleovegetation or biodiversity patterns suggested successive contraction/expansion phases on this rain forest cover during the last glacial maximum (LGM). Consequently, the hypothesis of the existence of refugia e.g. habitat stability that harbored populations during adverse climatic periods has been proposed. Understory species are tightly associated to forest cover and consequently are ideal markers of forest dynamics. Here, we used two central African rain forest understory species of the palm genus, Podococcus, to assess the role of past climate variation on their distribution and genetic diversity. Species distribution modeling in the present and at the LGM was used to estimate areas of climatic stability. Genetic diversity and phylogeography were estimated by sequencing near complete plastomes for over 120 individuals. Areas of climatic stability were mainly located in mountainous areas like the Monts de Cristal and Monts Doudou in Gabon, but also lowland coastal forests in southeast Cameroon and northeast Gabon. Genetic diversity analyses shows a clear North-South structure of genetic diversity within one species. This divide was estimated to have originated some 500,000years ago. We show that, in Central Africa, high and unique genetic diversity is strongly correlated with inferred areas of climatic stability since the LGM. Our results further highlight the importance of coastal lowland rain forests in Central Africa as harboring not only high species diversity but also important high levels of unique genetic diversity. In the context of strong human pressure on coastal land use and destruction, such unique diversity hotspots need to be considered in future conservation planning.

Spatial pattern analysis as a focus of landscape ecology to support evaluation of human impact on landscapes and diversity

The relation between landscape patterns and ecological processes forms a central hypothesis of landscape ecology. Three types of pattern analysis to assess anthropogenic impacts on landscape ecosystems and biodiversity are presented in this chapter. Firstly, the results of an analysis of Acanthaceae data in Central Africa are presented and compared with phytogeographic theories. Phytogeography data reflect the spatial variability of plant diversity, and constitute therefore a major tool in conservation policy development. We investigated if it was possible to proxy the phytogeographic classifications by the spatial distribution of Acanthaceae only. When combined with a classic landscape pattern analysis, this type of study could provide complementary information for the definition of conservation priorities. Secondly, we present an analysis of periodic vegetations in the Sudan. It can be accepted that through an understanding of the underlying mechanisms of the formation of this unique pattern geometry, the knowledge with regard to the functioning and vulnerability of these ecosystems can be deepened. Using high-resolution remote sensing imagery and digital elevation models, the relation between pattern symmetry and slope gradient was explored. In particular, slope gradients that could condition the transition between spotted and tiger bush pattern types were focused. The influence of other sources of anisotropy was also considered. Finally, a complementary approach to the calculation of landscape metrics to analyse landscape pattern is described, using the spatial processes themselves causing landscape transformation. Landscape ecologists agree that there appears to be a limited number of common spatial configurations that can result from land transformation processes. Ten processes of landscape transformation are considered: aggregation, attrition, creation, deformation, dissection, enlargement, fragmentation, perforation, shift, and shrinkage. A decision tree is presented that enables definition of the transformation process involved using patch-based data. This technique can help landscape managers to refine their description of landscape dynamics and will assist them in identifying the drivers of landscape transformation

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.

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

Abstract 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.

Assessment of Patterns in Ecogeomorphic Systems

Through studying patterns we can come to understand the systematic formulae that generate them. The scale and relative stability of the processes causing dryland degradation are particularly inviting to pattern analysis. The following sections give an overview of the functioning and application of pattern assessment tools including (geo)statistical, spectral and indicator methods and explore the potential of pattern-oriented modelling.