728 research outputs found
Patterns of tree species composition and richness across the principal biomes of lowland tropical South America and their underlying environmental drivers
No full textLowland tropical South America encompasses some of the most species-rich and
threatened ecosystems in the world, spanning across countries such as Brazil, Bolivia,
Colombia, Ecuador, Peru and Venezuela, which are known for their biodiversity.
However, due to its incredible environmental and ecological complexity and that
most of its area has yet to be scientifically studied in any depth, controversy
surrounds its biomes’ identities, the limits of their geographic and environmental
distributions and estimates of their tree species richness. The main objective of this
thesis is to study the phytogeography of lowland Tropical South America by delimiting
its biomes through a floristic approach, by investigating these biomes’ environmental
controls and dynamics and by assessing their tree species richness and endemism. In
order to fulfil this objective, we have employed a dataset of thoroughly checked tree
species checklists, the NeoTropTree (NTT) dataset, which covers more than 8000
locations across South, Central and southern North America and encompasses
occurrence records for more than 12000 tree species.
Firstly, I defined and mapped the main biomes in lowland tropical South America
(LTSA) through the means of a hierarchical clustering analysis based on tree species
composition associated with an a priori classification of 4103 NTT sites into
vegetation types. I then proceeded to map these biomes geographically and to assess
their environmental overlaps (both climatic and edaphic) through a classification tree
approach (random forest analysis). I was able to delimit five main biomes in LTSA:
Amazon Forest, Atlantic Forest, Chaco, Savanna and Seasonally Dry Tropical Forest
(SDTF). I also show that there is an important environmental overlap amongst
biomes. Error rates for site classification into biome using solely environmental data
ranged from 19-21% when only climate was considered and 16-18% when I also took
edaphic variables into account. I conclude that it is viable and advisable to use tree
species composition to determine biome identity, at least within individual
continents. In the case of LTSA, there is high biome heterogeneity at small spatial
scales, which explains why it is so challenging to use climatic and/or interpolation
based edaphic data, or remotely-sensed imagery, to map tropical biomes. Because of
this, I then conclude that biome delimitation using floristic information may enable
more efficient biome conservation and management efforts.
Secondly, I investigated the environmental controls distinguishing biome limits for
two regions of LTSA with high biome heterogeneity – eastern Brazil and Bolivia. To
this end, I selected 182 NTT sites in these two regions, collected detailed soil data
from the field and extracted climate and fire data from publicly available GIS data
layers. I assigned these sites to one of three states based on their tree species
composition: moist forest (including both Atlantic and Amazon Forests), SDTF or
savanna. Selected environmental variables were organized into three distinct
categories describing functional environmental regime: water availability, soil fertility
and fire, and their significance as predictors of biome identity was assessed within a
structural equation modelling framework. I found that environmental controls
behind biome distribution differ between the two studied areas and according to the
biomes involved. I concluded that water availability, soil fertility and fire are all
important determinants of biome limits. Amongst the three categories, water
availability was the most important one in determining biome identity at our study
sites, with soil fertility differentiating eastern Brazil SDTFs from the other biomes, and
fire representing an important determinant of savanna’s environmental limits.
Thirdly, I estimated and compared tree species richness and endemism levels of
LTSA’s main biomes using NTT’s tree species checklists and incidence (i.e.,
occurrence) data. To do so, I extracted tree species information for 4540 sites
registered in NeoTropTree distributed across four biomes: Amazon Forest, Atlantic
Forest, Savanna and SDTF. I first compared how tree species accumulated with
number of sites sampled for biomes and then estimated biomes’ total tree species
richness using non-parametric approaches (species extrapolation curves). I also
estimated the number of endemic tree species to these areas with two approaches:
indicator species analyses and absolute unique/shared species counts. I was able to
show that the Amazon Forest is the most tree species-rich environment in LTSA,
followed by the Atlantic Forest, Savannas and then SDTFs. In relation to endemism
levels, the Amazon and Atlantic Forests’ tree flora are mainly composed of endemic
tree species whereas that is not the case for the savanna and SDTF. The estimation
of total tree species richness through extrapolation curves revealed that around 94%
of the tree flora of the Amazon forest, the Atlantic forest and the SDTF have already
been recorded. According to the same analysis, only around 70% of the savannah tree
flora has been recorded. However, this pattern might be related to the high number
of biome intrusions into this biome. The differences in richness and endemism
between the moist (Amazon and Antlantic forests) and drier biomes (savanna and
SDTF) suggest that drought-sensitivity and biogeographic history are drivers of tree
species distribution in LTSA.
Finally, by integrating biome delimitation based on floristic composition with
knowledge on these environments’ environmental correlates and tree species
richness, I was able to describe LTSA’s main phytogeographic features in a way that
has never been done before, drawing attention to its complexities and performing
novel cross-biome comparisons. My study shows that LTSA’s biomes are interspersed
across geographic space, especially in the Dry Diagonal located between the Amazon
and Atlantic Forests, and that environmental controls driving these ecosystems’
distributions can vary according to the biomes being considered and the geographic
location. I also show that LTSA’s most tree species-rich biomes are the ones with the
highest quantity of endemic tree species and that taxonomic expeditions to the
Amazon Forest can potentially lead to more species being described in these
environments. To summarize, I was able to highlight LTSA’s main floristic patterns
and link them to environmental drivers and tree species richness, thereby
substantially transforming how these biomes are perceived by biodiversity scientists
and conservationists
Inga pitmanii (Fabaceae), a New Species from Madre de Dios, Peru
No full textInga pitmanii K. G. Dexter & T. D. Penn., a new species of Inga Mill. from Madre de Dios, Peru, is described for the Fabaceae (Mimosoideae). Morphologically it is closest to I. chartacea Poepp. & Endl., with which it shares a broadly winged rhachis, spicate inflorescence, glabrous leaves, nine to 10 pairs of secondary veins, and similar calyx indumentum. Inga pitmanii differs from I. chartacea in the leaflet number (four pairs vs. usually two or three pairs), the foliar nectaries (cyathiform vs. patelliform), and the larger flowers (with corollas 9–11.5 mm vs. 4.5–7 mm). Phylogenetic analyses show this species belongs to a clade including I. acreana Harms and I. chartacea. This species was discovered during field surveys for an ecological study of the genus Inga at the Los Amigos Biological Station in Madre de Dios, Peru. These field surveys uncovered several potentially novel species of the genus Inga, none of which matched any known species based on vegetative characters and the majority of which are genetically distinct. Here we describe I. pitmanii as this is the only species that was collected in a fertile state. Given current and future limitations in taxonomic expertise and funding, we advocate consideration of nonconventional approaches to species discovery, such as combining biodiversity surveys with large-scale DNA sequencing. This would in turn allow ecologists, who often collect plants in poorly known regions, to make a greater contribution to the species-discovery process
Figure S6 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
No full textFigure S6 (lef). Fractions of duplicated reads per sample.Published as part of Jens J. Ringelberg, Erik J. M. Koenen, Benjamin Sauter, Anahita Aebli, Juliana G. Rando, João R. Iganci, Luciano P. de Queiroz, Daniel J. Murphy, Myriam Gaudeu, Anne Bruneau, Melissa Luckow, Gwilym P. Lewis, Joseph T. Miller, Marcelo F. Simon, Lucas S. B. Jordão, Matías Morales, C. Donovan Bailey, Madhugiri Nageswara-Rao, James A. Nicholls, Oriane Loiseau, R. Toby Pennington, Kyle G. Dexter, Niklaus E. Zimmermann & Colin E. Hughes, 2023, Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time, pp. 2-111 in Science Advances (suppl.) 9 on page 62, DOI: 10.5281/zenodo.787182
Figure S12 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
No full textFigure S12 (lef). Numbers of taxa per alignment.Published as part of Jens J. Ringelberg, Erik J. M. Koenen, Benjamin Sauter, Anahita Aebli, Juliana G. Rando, João R. Iganci, Luciano P. de Queiroz, Daniel J. Murphy, Myriam Gaudeu, Anne Bruneau, Melissa Luckow, Gwilym P. Lewis, Joseph T. Miller, Marcelo F. Simon, Lucas S. B. Jordão, Matías Morales, C. Donovan Bailey, Madhugiri Nageswara-Rao, James A. Nicholls, Oriane Loiseau, R. Toby Pennington, Kyle G. Dexter, Niklaus E. Zimmermann & Colin E. Hughes, 2023, Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time, pp. 2-111 in Science Advances (suppl.) 9 on page 64, DOI: 10.5281/zenodo.787182
pablosanchezmart/Sanchez-Martinez-etal-2024-A-framework-to-study-and-predict-functional-trait-syndromes: A framework to study and predict functional trait syndromes using phylogenetic and environmental data
No full text<p>Code used in the paper titled A framework to study and predict functional trait syndromes using phylogenetic and environmental data published in Methods in Ecology and Evolution by Pablo Sanchez-Martinez, David D. Ackerly, Jordi Martínez-Vilalta, Maurizio Mencuccini, Kyle G. Dexter and Todd E. Dawson.</p>
Figure S34 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
No full textFigure S34. Metachronogram with the names and locations of all subtrees (coloured branches) that were grafed onto the phylogenomic backbone (black branches).Published as part of Jens J. Ringelberg, Erik J. M. Koenen, Benjamin Sauter, Anahita Aebli, Juliana G. Rando, João R. Iganci, Luciano P. de Queiroz, Daniel J. Murphy, Myriam Gaudeu, Anne Bruneau, Melissa Luckow, Gwilym P. Lewis, Joseph T. Miller, Marcelo F. Simon, Lucas S. B. Jordão, Matías Morales, C. Donovan Bailey, Madhugiri Nageswara-Rao, James A. Nicholls, Oriane Loiseau, R. Toby Pennington, Kyle G. Dexter, Niklaus E. Zimmermann & Colin E. Hughes, 2023, Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time, pp. 2-111 in Science Advances (suppl.) 9 on page 74, DOI: 10.5281/zenodo.787182
Figure S35 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
No full textFigure S35. Mimosoid taxon and genus richness per half degree latitude/longitude grid cell.Published as part of Jens J. Ringelberg, Erik J. M. Koenen, Benjamin Sauter, Anahita Aebli, Juliana G. Rando, João R. Iganci, Luciano P. de Queiroz, Daniel J. Murphy, Myriam Gaudeu, Anne Bruneau, Melissa Luckow, Gwilym P. Lewis, Joseph T. Miller, Marcelo F. Simon, Lucas S. B. Jordão, Matías Morales, C. Donovan Bailey, Madhugiri Nageswara-Rao, James A. Nicholls, Oriane Loiseau, R. Toby Pennington, Kyle G. Dexter, Niklaus E. Zimmermann & Colin E. Hughes, 2023, Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time, pp. 2-111 in Science Advances (suppl.) 9 on page 74, DOI: 10.5281/zenodo.787182
Figure S48 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
No full textFigure S48. Speciation rates estimated across the Caesalpinioideae metachronogram under eight scenarios with different fixed extinction rates. Extinction rates are shown above each subfigure, while speciation rates are indicated by branch colours.Published as part of Jens J. Ringelberg, Erik J. M. Koenen, Benjamin Sauter, Anahita Aebli, Juliana G. Rando, João R. Iganci, Luciano P. de Queiroz, Daniel J. Murphy, Myriam Gaudeu, Anne Bruneau, Melissa Luckow, Gwilym P. Lewis, Joseph T. Miller, Marcelo F. Simon, Lucas S. B. Jordão, Matías Morales, C. Donovan Bailey, Madhugiri Nageswara-Rao, James A. Nicholls, Oriane Loiseau, R. Toby Pennington, Kyle G. Dexter, Niklaus E. Zimmermann & Colin E. Hughes, 2023, Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time, pp. 2-111 in Science Advances (suppl.) 9 on page 85, DOI: 10.5281/zenodo.787182
Figure S45 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
No full textFigure S45. Variation partitioning results obtained using the genus-level Mimosoid phylogeny (rather than the metachronogram). See caption Figure 2 for explanation.Published as part of Jens J. Ringelberg, Erik J. M. Koenen, Benjamin Sauter, Anahita Aebli, Juliana G. Rando, João R. Iganci, Luciano P. de Queiroz, Daniel J. Murphy, Myriam Gaudeu, Anne Bruneau, Melissa Luckow, Gwilym P. Lewis, Joseph T. Miller, Marcelo F. Simon, Lucas S. B. Jordão, Matías Morales, C. Donovan Bailey, Madhugiri Nageswara-Rao, James A. Nicholls, Oriane Loiseau, R. Toby Pennington, Kyle G. Dexter, Niklaus E. Zimmermann & Colin E. Hughes, 2023, Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time, pp. 2-111 in Science Advances (suppl.) 9 on page 82, DOI: 10.5281/zenodo.787182
Figure S17 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
No full textFigure S17. Phylogeny of Caesalpinioideae. RAxML species tree based on the nucleotide single-copy genes alignment. Bootstrap support values are only shown for nodes with <100% bootstrap support.Published as part of Jens J. Ringelberg, Erik J. M. Koenen, Benjamin Sauter, Anahita Aebli, Juliana G. Rando, João R. Iganci, Luciano P. de Queiroz, Daniel J. Murphy, Myriam Gaudeu, Anne Bruneau, Melissa Luckow, Gwilym P. Lewis, Joseph T. Miller, Marcelo F. Simon, Lucas S. B. Jordão, Matías Morales, C. Donovan Bailey, Madhugiri Nageswara-Rao, James A. Nicholls, Oriane Loiseau, R. Toby Pennington, Kyle G. Dexter, Niklaus E. Zimmermann & Colin E. Hughes, 2023, Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time, pp. 2-111 in Science Advances (suppl.) 9 on page 66, DOI: 10.5281/zenodo.787182
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