This dispersal pattern has not been reported in earlier studies of birds in this region. The timing of the first colonization and the number of immigration events in each region were estimated using the ancestral states with the highest probability at each node inferred from the results of BioGeoBEARS (Matzke, 2014). Use the link below to share a full-text version of this article with your friends and colleagues. and extensibility, Metropolis coupled MCMC implemented by default to facilitate convergence. The results of the univariate regressions indicate that the regional species richness could be well explained by the first time of colonization (Figure 6a; r2 = .36; p < .05). Fumin Lei, Key Laboratory of the Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China. The speciation rate in each region was estimated using the average tip rates of all the species present estimated from BAMM (Rabosky, Grundler, et al., 2014). The timing of the first colonization is a strong predictor of the regional richness within these regions, while the explanatory power of immigrations and speciation rate are relatively weak. XDA19050202 to F.L. In contrast, the MS estimators (particularly using stem group ages), yielded stronger relationships between true and estimated diversification rates, by roughly twofold. Thus, we preferred models with parameter ‘j’ to account for ‘founder event’ or ‘jump dispersal’ in the historical biogeographical analyses (Matzke, 2014).

L. (Zamiaceae, Cycadales)

Under this scenario, it can be predicted that babblers first originated in the SHM and subsequently colonized other regions (Fjeldså, 2013). Tianlong Cai and Shimiao Shao have contributed equally. In contrast, richness was not significantly related to the number of immigration events (Figure 6b; r2 = .30; p = .06) or the speciation rate (Figure 6c; r2 = 0; p = .97). Near‐complete phylogeny and taxonomic revision of the world’s babblers (Aves: Passeriformes), Into the Andes: Multiple independent colonizations drive montane diversity in the Neotropical clearwing butterflies Godyridina, A comparative study in ancestral range reconstruction methods: Retracing the uncertain histories of insular lineages, Microevolution in island forms: The roles of drift and directional selection in morphological divergence of a passerine bird, The genome of the “great speciator” provides insights into bird diversification, Handbook of the birds of the world. At the same time, several articles have concluded that estimates of net diversification rates from the method‐of‐moments (MS) estimators are inaccurate. Results from the DEC model suggest that the highest PP for the ancestral area of babblers was the SHM (PP = 55%), but ancestral babblers may also have been widespread in the SHM and the Western Palaearctic (EH, PP = 35%).

Biological Journal of the Linnean Society. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors.

We ran the analysis for 50 million generations, sampling the Markov chain Monte Carlo (MCMC) chain every 1,000 generations. Temporal patterns of diversification in Brassicaceae demonstrate decoupling of rate shifts and mesopolyploidization events. Macroevolutionary dynamics of parasite diversification: A reality check. (2012) concluded, based on an analysis of all Himalayan songbirds, that competition for niche space limits species accumulation, and ecological competition for resources ultimately constrains speciation rates. Why is fruit colour so variable? Diversification rates, clade ages, and macroevolutionary methods. Using a comprehensive phylogeny of extant species (~90% sampled) and distributions of the world's babblers, we reconstructed their biogeographical history and analysed the diversification dynamics. The group first dispersed out of the SHM to the Western Palearctic in the early Miocene, with a subsequent split between the Sylviidae and Paradoxornithidae, and two independent dispersals to Africa within Sylviidae.

However, few studies (e.g., Cai et al., 2018; Chazot et al., 2016) have integrated all processes to explain diversity patterns on a large scale, in part due to the lack of comprehensive phylogenies available for widely distributed groups. Please check your email for instructions on resetting your password. A rate shift in the BAMM environment is a shift in the evolutionary dynamics of a system and can involve shifts to new time-varying or diversity-dependent evolutionary … Table 1 shows the regional species richness, the time of the first colonization, the number of immigration events and the average speciation rate in the 13 major geographical regions. First, accelerated allopatric speciation related to the formation of landscape barriers due to mountain building, as has been suggested to be the main driver of the high diversity in the SHM in plants (Wen, Zhang, Nie, Zhong, & Sun, 2014; Xing & Ree, 2017) and birds (Qu et al., 2014; Wu et al., 2014; Liu et al., 2016). Due to the ambiguity of the reconstructed states at the internal nodes when analysing the 13 regions, we reduced the total number of regions when analysed by merging different areas/regions as follows: (1) islands (A + C + K + L, and some archipelagos adjacent to Sundaland; Australia was merged into islands because Australia has only a single white‐eye species); (2) the lowlands of Indochina‐Sundaland (B + D); (3) the SHM (E); (4) the Indian subcontinent (F); (5) South China (G); (6) the Palearctic and North America (H + I + M) and (7) the mainland of sub‐Saharan Africa (J). (2019), based on 402 ingroup and 108 outgroup taxa (106 proposed closest relatives of the group), inferred from 12 genes. Rates of niche and phenotype evolution lag behind diversification in a temperate radiation. Recently, an approach called BAMM (Bayesian Analysis of Macro‐evolutionary Mixtures) has become widely used for estimating diversification rates and rate shifts. We used BAMM v.2.5.0 (Rabosky, Donnellan, Grundler, & Lovette, 2014) to model speciation and extinction rates through time and how these rates varied among lineages. Phylogenetic analyses reveal relationships between fruit‐colour evolution, biogeography and diversification. Sino‐Himalayan mountains act as cradles of diversity and immigration centres in the diversification of parrotbills (Paradoxornithidae). BAMM gives misleading rate estimates in simulated and empirical datasets.

The biogeographical reconstruction analyses based on six models implemented in BioGeoBEARS (Matzke, 2014) show very similar patterns (Figure 2, and Figures S1.3–S1.7 in Appendix S1). As social living canopy birds with high vagility, Zosteropidae could successfully colonize new areas by group dispersal from the mainland or nearby large islands, and establish populations (Mayr & Diamond, 2001). Any queries (other than missing content) should be directed to the corresponding author for the article.

Both analyses show that the immigration rates were significantly higher from the SHM to non‐SHM areas, than in the reverse direction. The spatio‐emporal colonization and diversification across the Indo‐Pacific by a 'great speciator' (Aves, Global gradients in vertebrate diversity predicted by historical area‐productivity dynamics and contemporary environment, The global diversity of birds in space and time, Build‐up of the Himalayan avifauna through immigration: A biogeographical analysis of the, Ecological limits on diversification of the Himalayan core Corvoidea. Hierarchies of evolutionary radiation in the world’s most species rich vertebrate group, the Neotropical

Estimated global sea level was from Miller et al.

Of course, we also need to consider the birth–death processes if the time‐for‐speciation effect is truly responsible for the high species richness in the SHM. Learn more. Initially, species accumulation in the islands increased at a constant rate, before a slight slowdown during the Pliocene and subsequently a rapid increase in the Pleistocene.

Yet, no studies have compared the ability of these two methods to accurately estimate clade diversification rates. Grid cells (0.5° × 0.5°) with red colours have a higher richness, whereas blue colours indicate lower richness. BAMM and associated methods have been described Nonetheless, repeated sea level changes during the Pleistocene probably led to intensive speciation in the dispersive and canopy‐dwelling genus Zosterops which is known as a ‘great speciator’ on the oceanic archipelagos. Walk, swim or fly?

Multiple origins of sexual dichromatism and aposematism within large carpenter bees. The model parameters and ancestral state probabilities at each node were estimated using BioGeoBEARS (Matzke, 2014). The important role of colonizing new geographical areas for subsequent diversification has been demonstrated in several recent studies (Johansson et al., 2007; Päckert et al., 2012; Liu et al., 2016; Cai et al., 2018; Chazot et al., 2016; but see Kennedy et al., 2017). If true, immigration rates would be higher from adjacent regions into the SHM than in the opposite direction. Pellorneidae underwent dispersal to Sundaland during the early Miocene, with multiple back‐colonizations of the Asian mainland, as well as a single dispersal to Africa, accompanied by subsequent diversification in these regions. Explaining global insect species richness: lessons from a decade of macroevolutionary entomology. We also estimated the regional richness in 13 geographical regions (A–M; Figure 1). Any queries (other than missing content) should be directed to the corresponding author for the article. The QTP was formed by the collision of the Indian and Eurasian plates 50–55 Ma and probably reached a height of 4,000 m by 40 Ma (Favre et al., 2015). According to this hypothesis, areas with high rates of immigration generally have available ecological opportunities and/or stable climates, providing more niches for diversification and refuges for escaping the negative consequences of climatic changes (Fjeldså et al., 2012; Price et al., 2014; Hoorn, Perrigo, & Antonelli, 2018).

Species were assigned to one or more of these geographical regions according to their breeding distributions. In addition to three primary models implemented in BioGeoBEARS (DEC, DIVA and BayArea), we included an additional parameter to each model (DEC+j, DIVA+j and BayArea+j), which allowed for ‘founder event’ speciation (Matzke, 2014). Time Explains Regional Richness Patterns within Clades More Often than Diversification Rates or Area.

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