References of "Dauby, Gilles"
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See detailLarge trees drive forest aboveground biomass variation in moist lowland forests accross the tropics
Slik, J. W. Ferry; Paoli, Gary; McGuire, Krista et al

in Global Ecology & Biogeography (2013)

Aim Large trees (d.b.h. 70 cm) store large amounts of biomass. Several studies suggest that large trees may be vulnerable to changing climate, potentially leading to declining forest biomass storage. Here ... [more ▼]

Aim Large trees (d.b.h. 70 cm) store large amounts of biomass. Several studies suggest that large trees may be vulnerable to changing climate, potentially leading to declining forest biomass storage. Here we determine the importance of large trees for tropical forest biomass storage and explore which intrinsic (species trait) and extrinsic (environment) variables are associated with the density of large trees and forest biomass at continental and pan-tropical scales. Location Pan-tropical. Methods Aboveground biomass (AGB) was calculated for 120 intact lowland moist forest locations. Linear regression was used to calculate variation in AGB explained by the density of large trees. Akaike information criterion weights (AICcwi) were used to calculate averaged correlation coefficients for all possible multiple regression models between AGB/density of large trees and environmental and species trait variables correcting for spatial autocorrelation. Results Density of large trees explained c. 70% of the variation in pan-tropical AGB and was also responsible for significantly lower AGB in Neotropical [287.8 (mean) 105.0 (SD) Mg ha-1] versus Palaeotropical forests (Africa 418.3 91.8 Mg ha-1; Asia 393.3 109.3 Mg ha-1). Pan-tropical variation in density of large trees and AGB was associated with soil coarseness (negative), soil fertility (positive), community wood density (positive) and dominance of wind dispersed species (positive), temperature in the coldest month (negative), temperature in the warmest month (negative) and rainfall in the wettest month (positive), but results were not always consistent among continents. Main conclusions Density of large trees and AGB were significantly associated with climatic variables, indicating that climate change will affect tropical forest biomass storage. Species trait composition will interact with these future biomass changes as they are also affected by a warmer climate. Given the importance of large trees for variation in AGB across the tropics, and their sensitivity to climate change, we emphasize the need for in-depth analyses of the community dynamics of large trees. [less ▲]

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See detailDevelopment and characterization of microsatellite loci in Pericopsis elata (Fabaceae) using a cost-efficient approach
Micheneau, Claire; Dauby, Gilles; Bourland, Nils ULg et al

in American Journal of Botany (2011)

Premise of the study : Microsatellite loci were developed in the endangered Pericopsis elata using a combination of low-cost procedures. Methods and Results : Microsatellite isolation was performed ... [more ▼]

Premise of the study : Microsatellite loci were developed in the endangered Pericopsis elata using a combination of low-cost procedures. Methods and Results : Microsatellite isolation was performed simultaneously on three distinct species through a newly available procedure that associates multiplex microsatellite enrichment and next-generation sequencing, allowing the rapid and low-cost development of microsatellite-enriched libraries through the use of a 1/32nd GS-FLX plate. Genotyping using M13-like label- ing in multiplexed reactions allowed additional cost savings. From 72 primers selected for initial screening, 21 positively amplified P. elata , and 11 showed polymorphism with two to 11 alleles per locus and a mean value of 5.4 alleles per locus. Conclusions : These microsatellite loci will be useful to further investigate the level of genetic variation within and between natural populations of P. elata in Africa. [less ▲]

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See detailPredicting alpha diversity of African rain forests: models based on climate and satellite-derived data do not perform better than a purely spatial model
Parmentier, Ingrid; Harrigan, Ryan J.; Buermann, Wolfgang et al

in Journal of Biogeography (2011), 38(6), 1164-1176

Aim Our aim was to evaluate the extent to which we can predict and map tree alpha diversity across broad spatial scales either by using climate and remote sensing data or by exploiting spatial ... [more ▼]

Aim Our aim was to evaluate the extent to which we can predict and map tree alpha diversity across broad spatial scales either by using climate and remote sensing data or by exploiting spatial autocorrelation patterns. Location Tropical rain forest, West Africa and Atlantic Central Africa. Methods Alpha diversity estimates were compiled for trees with diameter at breast height ‡ 10 cm in 573 inventory plots. Linear regression (ordinary least squares, OLS) and random forest (RF) statistical techniques were used to project alpha diversity estimates at unsampled locations using climate data and remote sensing data [Moderate Resolution Imaging Spectroradiometer (MODIS), normalized difference vegetation index (NDVI), Quick Scatterometer (QSCAT), tree cover, elevation]. The prediction reliabilities of OLS and RF models were evaluated using a novel approach and compared to that of a kriging model based on geographic location alone. Results The predictive power of the kriging model was comparable to that of OLS and RF models based on climatic and remote sensing data. The three models provided congruent predictions of alpha diversity in well-sampled areas but not in poorly inventoried locations. The reliability of the predictions of all three models declined markedly with distance from points with inventory data, becoming very low at distances > 50 km. According to inventory data, Atlantic Central African forests display a higher mean alpha diversity than do West African forests. Main conclusions The lower tree alpha diversity in West Africa than in Atlantic Central Africa may reflect a richer regional species pool in the latter. Our results emphasize and illustrate the need to test model predictions in a spatially explicit manner. Good OLS or RF model predictions from inventory data at short distance largely result from the strong spatial autocorrelation displayed by both the alpha diversity and the predictive variables rather than necessarily from causal relationships. Our results suggest that alpha diversity is driven by history rather than by the contemporary environment. Given the low predictive power of models, we call for a major effort to broaden the geographical extent and intensity of forest assessments to expand our knowledge of African rain forest diversity. [less ▲]

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See detailCan Pleistocene refuge theory explain within-species patterns of genetic diversity in African lowland rainforest trees?
Heuertz, Myriam; Savolainen, Vincent; Budde, Katharina et al

Poster (2010)

Pleistocene refuge theory holds that regions which nowadays harbour high numbers of endemic species correspond to forest refuges, where rainforest persisted through periods of adverse climatic conditions ... [more ▼]

Pleistocene refuge theory holds that regions which nowadays harbour high numbers of endemic species correspond to forest refuges, where rainforest persisted through periods of adverse climatic conditions. In order to test this theory, we surveyed geographical patterns of genetic diversity based on chloroplast DNA sequences in 15 rainforest tree species from 12 plant families in Atlantic Equatorial Africa. We found frequent geographic structure in the data sets, but no consistent pattern of genetic structure due to refugia. Species with gravity-dispersed oily seeds display low polymorphism whilst those with divergent lineages or ancient species display high polymorphism. Phylogeographical signals often correspond to taxa with divergent lineages. [less ▲]

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