Browsing by Autor "Roel J. W. Brienen"

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Evolutionary heritage influences Amazon tree ecology
(Royal Society, 2016) Fernanda Coelho de Souza; Kyle G. Dexter; Oliver L. Phillips; Roel J. W. Brienen; Jérôme Chave; David Galbraith; Gabriela López‐González; Abel Monteagudo Mendoza; R. Toby Pennington; Lourens Poorter
Lineages tend to retain ecological characteristics of their ancestors through time. However, for some traits, selection during evolutionary history may have also played a role in determining trait values. To address the relative importance of these processes requires large-scale quantification of traits and evolutionary relationships among species. The Amazonian tree flora comprises a high diversity of angiosperm lineages and species with widely differing life-history characteristics, providing an excellent system to investigate the combined influences of evolutionary heritage and selection in determining trait variation. We used trait data related to the major axes of life-history variation among tropical trees (e.g. growth and mortality rates) from 577 inventory plots in closed-canopy forest, mapped onto a phylogenetic hypothesis spanning more than 300 genera including all major angiosperm clades to test for evolutionary constraints on traits. We found significant phylogenetic signal (PS) for all traits, consistent with evolutionarily related genera having more similar characteristics than expected by chance. Although there is also evidence for repeated evolution of pioneer and shade tolerant life-history strategies within independent lineages, the existence of significant PS allows clearer predictions of the links between evolutionary diversity, ecosystem function and the response of tropical forests to global change.
Floristics and biogeography of vegetation in seasonally dry tropical regions
(Commonwealth Forestry Association, 2015) Kyle G. Dexter; Barry Smart; Cristina Baldauf; Timothy R. Baker; Michael Balinga; Roel J. W. Brienen; Sophie Fauset; Ted R. Feldpausch; L. Ferreira-Da Silva; Jonathan Ilunga Muledi
To provide an inter-continental overview of the floristics and biogeography of drought-adapted tropical vegetation formations, we compileda dataset of inventory plots in South America (n=93), Africa (n=84), and Asia (n=92) from savannas (subject to fire), seasonally dry tropicalforests (not generally subject to fire), and moist forests (no fire). We analysed floristic similarity across vegetation formations within andbetween continents. Our dataset strongly suggests that different formations tend to be strongly clustered floristically by continent, and that among continents, superficially similar vegetation formations (e.g. savannas) are floristically highly dissimilar. Neotropical moist forest,savanna and seasonally dry tropical forest are floristically distinct, but elsewhere there is no clear floristic division of savanna and seasonallydry tropical forest, though moist and dry formations are separate. We suggest that because of their propensity to burn, many formations termed “dry forest” in Africa and Asia are best considered as savannas. The floristic differentiation of similar vegetation formations from differentcontinents suggests that cross-continental generalisations of the ecology, biology and conservation of savannas and seasonally dry tropicalforests may be difficult.
Markedly divergent estimates of <scp>A</scp> mazon forest carbon density from ground plots and satellites
(Wiley, 2014) Edward T. A. Mitchard; Ted R. Feldpausch; Roel J. W. Brienen; Gabriela López‐González; Abel Monteagudo; Timothy R. Baker; Simon L. Lewis; Jon Lloyd; Carlos Alberto Quesada; Manuel Gloor
Pantropical biomass maps are widely used by governments and by projects aiming to reduce deforestation using carbon offsets, but may have significant regional biases. Carbon-mapping techniques must be revised to account for the known ecological variation in tree wood density and allometry to create maps suitable for carbon accounting. The use of single relationships between tree canopy height and above-ground biomass inevitably yields large, spatially correlated errors. This presents a significant challenge to both the forest conservation and remote sensing communities, because neither wood density nor species assemblages can be reliably mapped from space.