The colonization history of largely isolated habitats
Leaps and bounds: geographical and ecological distance constrained the colonisation of the Afrotemperate by Erica
Recommendation: posted 02 January 2019, validated 02 January 2019
The build-up of biodiversity is the result of in situ speciation and immigration, with the interplay between geographical distance and ecological suitability determining the probability of an organism to establish in a new area. The relative contribution of these factors have long interested biogeographers, in particular to explain the distribution of organisms adapted to habitats that remained largely isolated, such as the colonization of oceanic islands or land waters. The focus of this study is the formation of the afrotemperate flora; patches of temperate vegetation separated by thousands of kilometers in Africa, with high levels of endemism described in the Cape region, the Drakensberg range and the high mountains of tropical east Africa . The floristic affinities between these centers of endemism have frequently been explored but the origin of many afrotemperate lineages remains enigmatic .
To identify the biogeographic history and drivers of biogeographic movements of the large afrotemperate genus Erica, the study of Pirie and colleagues  develops a robust hypothesis-testing approach relying on historical biogeographic models, phylogenetic and species occurrence data. Specifically, the authors test the directionality of migrations through Africa and address the general question on whether geographic proximity or climatic niche similarity constrained the colonization of the Afrotemperate by Erica. They found that the distribution of Erica species in Africa is the result of infrequent colonization events and that both geographic proximity and niche similarity limited geographic movements (with the model that incorporates both factors fitting the data better than null models). Unfortunately, the correlation between geographic and environmental distances found in this study limited the potential evaluation of their roles individually. They also found that species of Erica have dispersed from Europe to African regions, with the Drakensberg Mountains representing a colonization sink, rather than acting as a “stepping stone” between the Cape and Tropical African regions.
Advances in historical biogeography have been recently questioned by the difficulty to compare biogeographic models emphasizing long distance dispersal (DEC+J) versus vicariance (DEC) using statistical methods, such as AIC, as well as by questioning the own performance of DEC+J models . Behind Pirie et al. main conclusions prevails the assumption that patterns of concerted long distance dispersal are more realistic than vicariance scenarios, such that a widespread afrotemperate flora that receded with climatic changes never existed. Pirie et al. do not explicitly test for this scenario based on the idea that these habitats remained largely isolated over time and our current knowledge on African paleoclimates and vegetation, emphasizing the value of arguments based on empirical (biological, geographic) considerations in model comparisons. I, however, appreciate from this study that the results of the biogeographic models emphasizing long distance dispersal, vicariance, and the unconstrained models are congruent with each other and presented together.
Pirie and colleagues  bring a nice study on the importance of long distance dispersal and biome shift in structuring the regional floras of Africa. They evidence outstanding examples of radiations in Erica resulting from single dispersal events over long distances and between ecologically dissimilar areas, which highlight the importance of niche evolution and biome shifts in the assembly of diversity. Although we still face important limitations in data availability and model realism, the last decade has witnessed an improvement of our understanding of how historical and environmental triggers are intertwined on shaping biological diversity. I found Pirie et al.’s approach (and analytical framework) very stimulating and hope that will help movement in that direction, providing interesting perspectives for future investigations of other regions.
 Linder, H.P. 1990. On the relationship between the vegetation and floras of the Afromontane and the Cape regions of Africa. Mitteilungen aus dem Institut für Allgemeine Botanik Hamburg 23b:777–790.
 Galley, C., Bytebier, B., Bellstedt, D. U., & Peter Linder, H. (2006). The Cape element in the Afrotemperate flora: from Cape to Cairo?. Proceedings of the Royal Society B: Biological Sciences, 274(1609), 535-543. doi: 10.1098/rspb.2006.0046
 Pirie, M. D., Kandziora, M., Nuerk, N. M., Le Maitre, N. C., de Kuppler, A. L. M., Gehrke, B., Oliver, E. G. H., & Bellstedt, D. U. (2018). Leaps and bounds: geographical and ecological distance constrained the colonisation of the Afrotemperate by Erica. bioRxiv, 290791. ver. 5 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/290791
 Ree, R. H., & Sanmartín, I. (2018). Conceptual and statistical problems with the DEC+ J model of founder‐event speciation and its comparison with DEC via model selection. Journal of Biogeography, 45(4), 741-749. doi: 10.1111/jbi.13173
Andrea S. Meseguer (2019) The colonization history of largely isolated habitats. Peer Community in Evolutionary Biology, 100065. 10.24072/pci.evolbiol.100065
The recommender in charge of the evaluation of the article and the reviewers declared that they have no conflict of interest (as defined in the code of conduct of PCI) with the authors or with the content of the article. The authors declared that they comply with the PCI rule of having no financial conflicts of interest in relation to the content of the article.
Evaluation round #3
DOI or URL of the preprint: 10.1101/290791
Version of the preprint: 3
Author's Reply, 14 Dec 2018
Decision by Andrea S. Meseguer, posted 12 Dec 2018
I have decided not sending the paper again to reviewers in order to speed up the process, but a few important modifications are still necessary before the paper could be recommended.
Regarding the biogeographic models: I found satisfying that the results of the unconstrained model are presented together with the results in which jump dispersal was forced to occur between Europe and the Cape region. Although I am still sceptical with this assumption, I agree this approach could be valid if we assume that widespread ancestral reconstructions are biologically unlikely. I regret, however, the authors don’t provide a more detailed justification of this assumption; if they argue in the introduction that ancestral continuous (widespread) distributions fragmented by vicariance probably explain disjoint patterns of (arid-adapted) African plant groups (e.g., Sanmartín et al., 2010; Pokorny et al., 2015; Bellstedt et al., 2012), why in this particular case this biogeographic scenario (an ancestral widespread distribution) does not make biological sense? I imagine it has something to do with the temperate adaptations of the genus and the fact that temperate conditions were never continuous in Africa, but this needs to be clarified (maybe in Appendix 3 or in the main text?).
Reviewer 3 was concerned for the potential correlation of the studied variables (i.e. geographic distances and niche similarity). In this new version, the authors evaluated their correlation and found what is generally considered a moderate to strong value of correlation (Kendall’s R = -0.64), but was this result taken into account at all? It has strong implications, as one of the main questions of the study (i.e. the relative importance of niche vs. distance in dispersal patterns) cannot be answered. I am convinced this limitation does not affect the main conclusions of the study since the preferred model was the combined “niche/distance” model. In addition, this is an interesting result “per se”. However, in light of this, I have the impression that comparisons of the “geographic distance” and the “niche similarity” models do not make sense anymore because these variables are not independent. Only comparisons of the null and the combined “niche/distance” model might remain informative. I leave to the authors the decision on whether they want to exclude these models from the model comparison table or not, but this limitation needs to be taken into account and the results/discussion sections modified accordingly.
Again, I hope you will find these last comments helpful and look forward to read the final version of the manuscript!
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Evaluation round #2
DOI or URL of the preprint: https://doi.org/10.1101/290791
Version of the preprint: 2
Author's Reply, 04 Dec 2018
Decision by Andrea S. Meseguer, posted 25 Nov 2018
This paper has improved from the last version and the authors have taken into consideration and answered many of the concerns raised in the initial review. Reviewer 1 believes it is in good shape for recommendation after a few minor revisions. Reviewer 2 did not see the original, but only the revised version and agrees with Rev 1 that the paper is of general interest. However, Rev 2 has some substantive comments that need to be dealt with before the paper can be accepted for recommendation. The most critical comments centre on the niche modelling approach and how this affects your results. Rev 2 has a number of other critical but supportive and constructive comments that will make the paper more useful for the biogeographic community.
The authors’ response to my critique of their use of the DEC+J models is satisfying. I agree that this ms is not the place to go into the detail of this argumentation, although I appreciate they acknowledge the controversy and provide the DEC results. Just as a note of caution, the recent paper of Ree & Sanmartin (2018) shows that DEC and DEC+J models are not directly comparable using statistical methods such as AIC that assume probabilistic equivalency of events. Therefore, I recommend privileging arguments based on empirical (biological, geographic) considerations rather than AIC scores. AIC comparisons might otherwise work to compare DEC (and DEC+J) models among them.
I regret however, the authors have not fully taken into account my comments about the adjacency matrix. I apologize if this is because I was not clear enough. The “Cape to Cairo” hypothesis (dispersal from Europe to the Cape, followed by migrations to the Drakensberg; Figure 1), could not be properly tested if the adjacency matrix does not allow ancestral connections between Europe and the Cape regions (0 values on this connection). By setting 0 values you are specifying that these two areas were not connected in the past (an ancestral distribution in Europe and the Cape is disallowed). Hence, although in theory dispersal is still allowed, in practice this constraint forces species to follow another route to disperse between these areas or forces jump dispersal. In my opinion this is a too strong assumption when the “Cape to Cairo” is the hypothesis to test, specially given the possibility that before the Miocene aridification of northern Africa, Erica was distributed in regions where it does not occur today. This limitation seems to apply only to DEC+J and not to DEC analyses where the adjacency matrix was not implemented. I suggest testing again the hypotheses without this constriction, which will make the results more solid.
I also have a few minor points: - The biogeographic reconstructions on Appendix 13 don’t have any legend. You need to explain the symbols on the trees, the colours, the abbreviations or the analyses that have produced these figures. In addition, the size of the pie charts on the trees is way too big and needs to be reduced. - The unconstrained biogeographic DEC and DEC+J reconstructions need to be presented the Appendix. - Please, clarify if the “Cape to Cairo” model fits the data better than “Southerly stepping stone” model. Discussion lines 285-287 state: “Cape to Cairo” and “Drakensberg melting-pot” mostly fit the data better than “Southerly stepping stone”. Meanwhile, in the results: “Under DEC+J given the best tree, the Drakensberg melting pot, geographic distance, and southerly stepping stone models revealed the lowest AIC; under DEC the Drakensberg melting pot model alone scored best, but with higher AIC ”. Moreover, in Table 1, the CtoC model does not even appear among the best models when considering the best tree.
I hope that the authors will find these comments helpful to improve their work.
Andrea S. Meseguer
Reviewed by Florian Boucher, 05 Oct 2018
Reviewed by anonymous reviewer 2, 05 Oct 2018
Evaluation round #1
DOI or URL of the preprint: 10.1101/290791
Version of the preprint: 1
Author's Reply, 19 Sep 2018
Decision by Andrea S. Meseguer, posted 19 Sep 2018
All the reviewers now chimed in with their opinions and agreed on the interests of the manuscript. I commend the authors for all the work they have done, and I echo the reviewers. I think this study represents a nice piece of work investigating the factors and processes mediating dispersal of plant clades from Europe to Africa. I very much appreciated the thoroughness of the analyses and the clarity of the text.
I recommend the authors undertake a thorough revision based on the constructive comments of the reviewers, taking particular care to address the reviewerʼs methodological concerns. I found particularly interesting the criticism of one reviewer regarding the conceptual problem of proposing hypotheses that are not mutually exclusive (or framed at different levels), as well as all methodological suggestions proposed by the three reviewers.
I am, however, a bit more cautious than the reviewers regarding the results of this study. In agreement with one reviewer, I regret the choice of biogeographic models. The DEC+J model has been shown at best to not be directly comparable to the DEC model, and at worst to present some statistical problems (Ree & Sanmartin 2018). I would recommend excluding this model from the comparisons and if the authors still wanting to present it, to do it on supplementary material. I am also suspicious with the DEC+* model of Massana & al. (2015). This model has been published as a preprint with no reviewer assessment on their quality/performance. I thus suggest excluding this model from the comparisons as well.
In addition, I have concerns on the validity of the results. In addition to the different disperal matrices, you implemented an adjacent area matrix to constraint the maximum number of areas allowed as ancestral states. I agree on this procedure to decrease model uncertainty, for example as you did by using the “maximum number of areas” command. However, I think the constrictions on the adjacent matrix you implemented are problematic and could have affected the results: 1) my apologies if I’m wrong, but I think that by using this adjacency matrix you force stepping stone dispersal to occur, while this is one of the main hypotheses you want to test. For example, in the matrix on Appendix 3 you are impeding dispersal between Europe and the Cape region, the Drakensberg and Madagascar, while only allowing dispersal through tropical Africa. It is thus not surprising that you found support for the “Drakensberg melting pot” steeping stone scenario in comparison with other long distance dispersal models. 2) In addition, by implementing this matrix you automatically disallow disjoint distributions at ancestral nodes, decreasing the likelihood of extinction to occur.
An important part of the manuscript focuses on whether colonization was mediated by niche changes or occurred across similar habitats. On this regard one reviewer had concerns about the areas used for comparison. I agree with him that differences between study areas could dissapear when compared with other regions in Africa or Europe where Erica does not occur. I additionally regret you didn’t differentiate the Northern Hemisphere Mediterranean region from other Northern Hemisphere regions. My guess is that the low climatic similarity between southern African and Europe might most likely apply to the Eurosiberian region, but not to the Mediterranean one. I think this differentiation is important to test if long distance dispersals involved niche shifts.
Concerning model comparisons, in addition to AIC scores (e.g. on Appendix 8), I would like to see the differences in deltaAIC values, akaike weights or any other metric that allows to evaluate model improvements and perform model choice. Generally, it is the differences between the likelihoods or AICs that matter, not their absolute values. That is, the larger difference in AIC indicates stronger evidence for one model over the other (Burnham and Anderson, 2002). Delta (AIC differences) within 0-2 has a substantial support for a suboptimal model; delta within 4-7 considerably less support and delta greater than 10 essentially no support.
To conclude, apart from the nexus file I would suggest the author to include a figure with the most likely biogeographic reconstruction, maybe on SI.
I leave this, and the reviewer’s comments, for the authors to consider as they revise and improve the paper. I hope the authors will find that many of these will be helpful in improving the manuscript