Tropical biodiversity is immense, under enormous threat, and yet still poorly understood. Global climatic breakdown and habitat destruction are impacting on and removing this diversity before we can understand how the biota responds to such changes, or even fully appreciate what we are losing . This is particularly the case for woody shrubs and trees  and for the flora of tropical Africa .
Helmstetter et al.  have taken a significant step to improve our understanding of African tropical tree diversity in the context of past climatic change. They have done so by means of a remarkably in-depth analysis of one species of the tropical plant family Annonaceae: Annickia affinis . A. affinis shows a distribution pattern in Africa found in various plant (but interestingly not animal) groups: a discontinuity between north and south of the equator . There is no obvious physical barrier to cause this discontinuity, but it does correspond with present day distinct northern and southern rainy seasons. Various explanations have been proposed for this discontinuity, set out as hypotheses to be tested in this paper: climatic fluctuations resulting in changes in plant distributions in the Pleistocene, or differences in flowering times or in ecological niche between northerly and southerly populations. These explanations are not mutually exclusive, but they can be tested using phylogenetic inference – if you can sample variable enough sequence data from enough individuals – complemented with analysis of ecological niches and traits.
Using targeted sequence capture, the authors amassed a dataset representing 351 nuclear markers for 112 individuals of A. affinis. This dataset is impressive for a number of reasons: First, sampling such a species across such a wide range in tropical Africa presents numerous challenges of itself. Second, the technical achievement of using this still relatively new sequencing technique with a custom set of baits designed specifically for this plant family  is also considerable. The result is a volume of data that just a few years ago would not have been feasible to collect, and which now offers the possibility to meaningfully analyse DNA sequence variation within a species across numerous independent loci of the nuclear genome. This is the future of our research field, and the authors have ably demonstrated some of its possibilities.
Using this data, they performed on the one hand different population genetic clustering approaches, and on the other, different phylogenetic inference methods. I would draw attention to their use and comparison of coalescence and network-based approaches, which can account for the differences between gene trees that might be expected between populations of a single species. The results revealed four clades and a consistent sequence of divergences between them. The authors inferred past shifts in geographic range (using a continuous state phylogeographic model), depicting a biogeographic scenario involving a dispersal north over the north/south discontinuity; and demographic history, inferring in some (but not all) lineages increases in effective population size around the time of the last glacial maximum, suggestive of expansion from refugia. Using georeferenced specimen data, they compared ecological niches between populations, discovering that overlap was indeed smallest comparing north to south. Just the phenology results were effectively inconclusive: far better data on flowering times is needed than can currently be harvested from digitised herbarium specimens.
Overall, the results add to the body of evidence for the impact of Pleistocene climatic changes on population structure, and for niche differences contributing to the present day north/south discontinuity. However, they also paint a complex picture of idiosyncratic lineage-specific responses, even within a single species. With the increasing accessibility of the techniques used here we can look forward to more such detailed analyses of independent clades necessary to test and to expand on these conclusions, better to understand the nature of our tropical plant diversity while there is still opportunity to preserve it for future generations.
 Mace, G. M., Gittleman, J. L., and Purvis, A. (2003). Preserving the Tree of Life. Science, 300(5626), 1707–1709. doi: 10.1126/science.1085510
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Dear Andrew, Thomas et al.,
I’ve taken a little time to get back to you on your revised preprint; I was glad to see your use of the reviews to improve the paper but couldn’t quite parse the response to the comments regarding the spatial diffusion analyses. The original reviewer, Miguel Navascués, took an immediate further look and has clarified the point in some detail. The bottom line is that the approach is based on the same kinds of assumptions as its discrete state predecessor (in particular with regard random sampling and in ignoring population structure when calculating the probability of the coalescent tree), and despite its popularity might deliver similarly inaccurate results when those assumptions are violated. My impression is that you sampled in order to best represent the distribution, not to represent populations in proportion to their size, so this at the least does seem potentially problematic. He suggests either to remove the analysis or to include a thorough discussion of its potential problems (in the context of your data, I would add), either of which solutions should be straightforward for you to implement.
I have included some minor further suggestions in the tracked-changes version of the text which I will forward on separately as it seems the upload function here only accepts pdf. I’ll look forward to seeing the revised – and doubtless final – version in due course.
All the best,
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Phylogenomic data reveal how a climatic inversion and glacial refugia shape patterns of diversity in an African rain forest tree species Andrew J. Helmstetter, Biowa E. N. Amoussou, Kevin Bethune, Narcisse G. Kandem, Romain Glèlè Kakaï, Bonaventure Sonké, Thomas L. P. Couvreur 10.1101/807727 version 1
Dear Andrew and coauthors,
Reviewers have responded very positively to your ms. and have made a number of insightful and constructive comments that I am sure you will be able to make good use of. The reviewers’ comments are included (presumably) below (R1 & R2), in a separate pdf (R3) plus in an annotated copy of the pdf to which I have added further points here and there.
The main points raised:
Hypotheses and tests: It always aids the clarity of this kind of analysis to set out in the introduction all the hypotheses, as well as the results with which they could be rejected. As noted by R2 and R3, those corresponding to flowering times and niche differences are currently neglected. R2 suggests ways in which these might be addressed using the current datasets, and also moots the possibility of formal biogeographic model testing using BioGeoBEARS. These would certainly add considerable value to the paper.
Methods and assumptions: I agree with R1 on the use of methods making unrealistic assumptions about gene flow in an analysis within a species using multiple independent markers. A concatenated analysis seems like a bad idea to me in principle, and although I can’t compare the ASTRAL tree to the RAxML one (because the tips aren’t labelled – I would ask for supplementary tree files/fully labelled trees to represent the information presented in such figures) the network structure in the splitstrees result and the short branch lengths in parts of the tree do nothing to assuage my concern that the single ML tree cannot realistically represent phylogeny here. Both topology and branch lengths may be impacted by the model violation, and the strong support could just be a misleading symptom of that. R1 suggests to replace this with analysis based on multispecies coalescent. Similarly R1 suggests replacing the “mugration” approach with those implementing a structured coalescent.
Dataset and processing of SNPs R1 asks for a comparison of the datasets resulting from phylogenomic/population-level processing. I agree this would be enlightening: In addition to these comments, I would like to know how within-individual polymorphic sites are treated for the former (I see no sign of phasing; a general weakness of some pipelines in my view). How might these different ways of treating the same data potentially impact the results?
I would ask that in revision your ms. you copy all these comments into a separate response document and address each individually; ideally I would like to see changes to the ms. in the form of tracking in a word document. Just makes my life easier.
Finally, congratulations on a fine piece of work. I am looking forward to seeing a revised version.
All the best, Mike PirieDownload recommender's annotations