DOI: 10.5061/dryad.gf1vhhmk0
title: Data from: Evolutionary diversity in tropical tree communities peaks at intermediate precipitation

description: Global patterns of species and evolutionary diversity in plants are
 primarily determined by a temperature gradient, but precipitation
 gradients may be more important within the tropics, where plant species
 richness is positively associated with the amount of rainfall. The impact
 of precipitation on the distribution of evolutionary diversity, however,
 is largely unexplored. Here we detail how evolutionary diversity varies
 along precipitation gradients by bringing together a comprehensive
 database on the composition of angiosperm tree communities across lowland
 tropical South America (2,025 inventories from wet to arid biomes), and a
 new, large-scale phylogenetic hypothesis for the genera that occur in
 these ecosystems. We find a marked reduction in the evolutionary diversity
 of communities at low precipitation. However, unlike species richness,
 evolutionary diversity does not continually increase with rainfall.
 Rather, our results show that the greatest evolutionary diversity is found
 in intermediate precipitation regimes, and that there is a decline in
 evolutionary diversity above 1,490 mm of mean annual rainfall. If
 conservation is to prioritise evolutionary diversity, areas of
 intermediate precipitation that are found in the South American ‘arc of
 deforestation’, but which have been neglected in the design of protected
 area networks in the tropics, merit increased conservation attention.
description: We constructed a
 genus-level phylogeny comprising 1,100 angiosperm genera found in lowland
 tropical South America, following protocols developed by Dexter &
 Chave<sup>1</sup>. We used two chloroplast DNA gene regions:
 <i>rbcL</i> and <i>matK</i>. These genes were
 chosen based on their universality, data availability, typical sequence
 quality, degree of genus-level discrimination, sequencing costs and
 because they are recommended for standard DNA barcoding in
 plants<sup>2-4</sup>. We generated 198 novel
 <em>rbcL</em> and 264 novel <em>matK</em>
 sequences from leaf fragments collected during extensive fieldwork across
 South America (all sequences generated in this study have an associated
 voucher; see Appendix 3 for a list of accession numbers and voucher
 information). Further sequences were also obtained through
 Genbank (http://www.ncbi.nlm.nih.gov/), and restricted to
 accessions that had an associated voucher. We had both <i style="text-indent:36pt;">rbcL</i> and <i style="text-indent:36pt;">matK</i> sequences for 808 genera (73%),
 only <i style="text-indent:36pt;">rbcL</i> for 128 genera (12%) and only <i style="text-indent:36pt;">matK</i> for 163 genera (15%). Sequences
 that were unavailable for a single region for a given genus were left as
 missing data. Exploratory sequence alignments and phylogenetic
 reconstructions enabled us to exclude sequences that were likely to
 represent taxonomic misidentifications. The details of DNA extraction,
 PCR, and DNA sequencing protocols can be found in Gonzales
 <i style="text-indent:36pt;">et
 al</i>.<sup style="text-indent:36pt;">5</sup> A list of sampled genera, their respective family and
 GenBank accession numbers are available in Appendix
 3. We conducted multiple
 sequence alignments, separately for each region, using MAFFT
 v.6.822<sup>6</sup>, followed by manual adjustments in
 Mesquite (http://mesquiteproject.org). After manual alignments, we reduced
 remaining alignment issues by removing all sites which were missing data
 for &gt;99% of genera. All <i>rbcL</i> and
 <i>matK</i> sequences were then combined to generate a
 starting maximum likelihood tree using RAxML v.7.2.7 in the CIPRES Science
 Gateway (https://www.phylo.org). A topological
 constraint specifying the major relationships among angiosperm orders was
 imposed based on the Angiosperm Phylogeny Group<sup>7</sup>.
 The early-branching angiosperm <i>Nymphaea alba</i> L.
 (Nymphaeaceae) was specified as an outgroup. This initial phylogeny was
 made ultrametric by using nonparametric rate smoothing
 method<sup>8</sup> implemented in the ape
 package<sup>9</sup> in the R statistical
 environment<sup>10</sup>, and then used as a starting tree in
 a Bayesian Markov Chain Monte Carlo (MCMC) approach to simultaneously
 estimate tree topology and divergence times of
 taxa<sup>11</sup>. These analyses were performed using
 the BEAST software v.1.8.2 on the CIPRES server (https://www.phylo.org).
 An uncorrelated lognormal relaxed molecular clock was implemented, and the
 tree prior was a Birth-Death Incomplete Sampling model of
 speciation<sup>12</sup>. We used 86 previously compiled
 fossil-based age constraints to calibrate node
 ages<sup>13,14</sup>. Internal nodes were constrained using a
 log-normal distribution with a mean value equal to the fossil age, a
 standard deviation of 2 and a hard constraint for a minimum age equal to
 80% of the estimated fossil age. No constraints were placed on the root
 age of the tree. We optimized operator settings before conducting the
 final runs by using a preliminary tree in test runs of
 10<sup>6</sup> generations. We
 carried out three independent MCMC runs for 70.2 x
 10<sup>5</sup>, 80.3 x 10<sup>5 </sup>and 58.6 x
 10<sup>5</sup> generations, under the same estimation
 conditions. We excluded burn-ins of 10<sup>3</sup> and 2 x
 10<sup>3</sup> generations for the first two and third runs,
 respectively. We used LogCombiner to combine the three independent runs
 before sampling 282 trees evenly spaced across the posterior distribution,
 which were used to assemble a consensus tree. The consensus tree was
 assembled following the all compatible consensus rule; i.e., we choose the
 topology of a given node based on the relationship found in a plurality of
 trees from across the posterior distribution. This ensures a fully
 bifurcating topology that represents the most probable relationships of
 taxa. Lastly, we used TreeAnnotator
 (http://beast.bio.ed.ac.uk/treeannotator) to assign branch-lengths and
 divergence times (node heights) as the mean values from across the
 posterior distribution. We also
 generated a species-level phylogeny, using the genus-level phylogeny as a
 basis. This consisted of imputing all 8,174 species in the floristics
 dataset by simulating a random birth-death phylogeny for each genus, using
 a speciation rate of 1 and an extinction rate of 0.9. We conducted these
 simulations in the TreeSim<sup>15</sup> package in
 R<sup>10</sup>. This procedure produced a fully bifurcating
 phylogeny for each genus with the number of tips (i.e. species)
 corresponding to the number of species in the genus in our dataset.
 Importantly, we retained the stem age of the genus as estimated using our
 temporally calibrated phylogeny, while the crown age of genera was a
 product of the simulation (the mean expectation under a coalescent process
 is an age half that of the crown age, but there is variability around this
 expectation). The result of our approach is that the phylogenetic
 diversity represented by an individual species is proportional to the stem
 age of the genus divided by the species richness of the
 genus. <strong>References</strong> 1. Dexter, K. G. & Chave, J. Evolutionary patterns of range size, abundance and species richness in Amazonian trees. <i>PeerJ</i>, 2043v1 (2016). 2. CBOL Plant Working Group. A DNA barcode for land plants. <i>Proc. Natl. Acad. Sci. USA</i> <b>106</b>, 12794-12797 (2009). 3. Kress, W. J. & Erickson D. L. DNA barcodes: methods and protocols. <i>Methods Mol. Biol. </i><b>858</b>, 3-8 (2012). 4. Kress, W. J., Lopez, I. C. & Erickson, D. L. Generating plant DNA barcodes for trees in long-term forest dynamics plots. <i>Methods Mol. </i><i>Biol.</i> <b>858</b>, 441-458 (2012). 5. Gonzalez, M. A. <i>et al.</i> Identification of Amazonian trees with DNA barcodes. <i>PLoS One</i> <b>4</b>, e7483 (2009). 6. Katoh, K., Misawa, K., Kuma, K. & Miyata, T. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. <i>Nucleic Acids Res.</i> <b>30</b>, 3059-3066 (2002). 7. The Angiosperm Phylogeny Group. An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG IV. <i>Bot. J. Linn. Soc.</i> <b>181</b>, 1-20 (2016). 8. Sanderson M. J. Estimating absolute rates of molecular evolution and divergence times: a penalized likelihood approach. <i>Mol. Biol. Evol.</i> <b>19</b>, 101-109 (2002). 9. Paradis, E., Claude, J. & Strimmer, K. APE: analyses of phylogenetics and evolution in R language. <i>Bioinformatics</i> <b>20</b>, 289-290 (2004). 10. R Core Team. R: a language and environment for statistical computing. Version 3.1.0. R Foundation for Statistical Computing, Vienna (2016). Available at: http://www.Rproject.org/ 11. Drummond, A. J. & Rambaut, A. BEAST: Bayesian evolutionary analysis by sampling trees. <em>BMC Evol. Biol.</em> <strong>7</strong>, p. 214 (2007). 12. Stadler, T. On incomplete sampling under birth-death models and connections to the sampling-based coalescent. <i>J. Theor. Biol.</i> <b>261</b>, 58-66 (2009). 13. Baker, T. R. <i>et al.</i> Fast demographic traits promote high diversification rates of Amazonian trees. <i>Ecol. </i><i>Lett.</i> <b>17</b>, 527-536 (2014). 14. Magallon, S., Gomez-Acevedo, S., Sanchez-Reyes, L. L. & Hernandez-Hernandez T. A metacalibrated time-tree documents the early rise of flowering plant phylogenetic diversity. <i>New Phytol.</i> <b>207</b>, 437-453 (2015). 15. Stadler, T. TreeSim: Simulating Phylogenetic Trees. R package version 2.3 (2017). Available at: https://CRAN.R-project.org/package=TreeSim
description: <strong>Genus_phylogeny.tre
 - </strong>Time-calibrated molecular phylogeny of 1,100 angiosperm
 genera found in lowland tree communities of tropical South America.
 Phylogenetic reconstruction based on sequences of rbcL and matK plastid
 regions from plants collected during fieldwork or available in GenBank.
 Tree topology and divergence times of taxa were estimated using a Bayesian
 Markov Chain Monte Carlo approach. Branch lengths were time-scaled using a
 relaxed molecular clock with fossil-based age constraints implemented on
 nodes. <b>Genus_multiphylogeny.tre -
 </b>Set of 100 time-calibrated molecular phylogenies from a
 Bayesian Markov Chain Monte Carlo (MCMC) posterior distribution. Each 
 phylogeny comprises 1,100 angiosperm genera found in lowland tree
 communities of tropical South America. Phylogenetic reconstruction based
 on sequences of rbcL and matK plastid regions from plants collected during
 fieldwork or available in GenBank. Tree topology and divergence times of
 taxa were estimated using a Bayesian MCMC approach. Branch lengths were
 time-scaled using a relaxed molecular clock with fossil-based age
 constraints implemented on nodes.
 <b>Species_phylogeny.tre - </b>Phylogeny of
 angiosperm species found in  lowland tree communities of tropical South
 America, generated using the genus-level phylogeny as a basis (see
 Genus_phylogeny.tree above). This consisted of pruning the genus-level
 phylogeny to 852 genera in the community dataset
 (http://www.neotroptree.info/), and then imputing all 8,174 species in
 this dataset by simulating a random birth-death phylogeny for each genus,
 using a speciation rate of 1 and an extinction rate of 0.9.
 <b>Appendix 3.xlsx - </b>List of 1,100 angiosperm
 genera used in the phylogenetic reconstructions, their respective sources
 of <i>rbcL</i> and <i>matK</i> sequences, GenBank
 accession numbers, eDNA numbers (i.e., internal codes for sequences
 generated at the Royal Botanic Garden Edinburgh), collectors, collector
 numbers and herbaria where vouchers were deposited (when applicable). RBG
 = Royal Botanic Garden Edinburgh. Asterisk indicates the 852 genera used
 in the community phylogenetic analyses.