Diversification rates and species richness across the Tree of Life

Scholl, Joshua P.; Wiens, John J.

doi:10.1098/rspb.2016.1334

Cited by 124 publications

(185 citation statements)

References 50 publications

(118 reference statements)

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“…These rates are directly related to the current diversity of birds and mammals (Belmaker and Jetz 2015), amphibians (Pyron and Wiens 2013), and squamate reptiles (Pyron 2014). The negative effect of DR on richness is contrary to findings from previous studies Wiens 2016, Scholl and and might be explained by the occurrence of young clades with high diversification rates but with low richness (Wiens 2011). The negative effect of DR on richness is contrary to findings from previous studies Wiens 2016, Scholl and and might be explained by the occurrence of young clades with high diversification rates but with low richness (Wiens 2011).…”

Section: Discussioncontrasting

confidence: 60%

Time and environment explain the current richness distribution of non‐marine turtles worldwide

et al. 2017

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Ecological, historical, and evolutionary hypotheses are important to explain geographical diversity gradients in many clades, but few studies have combined them into a single analysis allowing a comparison of their relative importance. This study aimed to evaluate the relative importance of ecological, historical, and evolutionary hypotheses in explaining the current global distribution of non-marine turtles, a group whose distribution patterns are still poorly explored. We used data from distribution range maps of 336 species of non-marine turtles, environmental layers, and phylogeny to obtain richness estimates of these animals in 2°  2° cells and predictors related to ecological, evolutionary and historical hypotheses driving richness patterns. Then we used a path analysis to evaluate direct and indirect effects of the predictors on turtle richness. Ancestral area reconstruction was also performed in order to evaluate the influence of time-for-speciation in the current diversity of the group. We found that environmental variables had the highest direct effects on non-marine turtle richness, whereas diversification rates and area available in the last 55 million yr minimally influenced turtle distributions. We found evidence for the time-for-speciation effect, since regions colonized early were generally richer than recently colonized regions. In addition, regions with a high number of colonization events had a higher number of turtle species. Our results suggested that ecological processes may influence non-marine turtle richness independent of diversification rates, but they are probably related to dispersal abilities. However, colonization time was also an important component that must be taken into account. Finally, our study provided additional support for the importance of ecological (climate and productivity) and historical (time-for-speciation and dispersal) processes in shaping current biodiversity patterns.

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Section: Discussioncontrasting

confidence: 60%

Time and environment explain the current richness distribution of non‐marine turtles worldwide

et al. 2017

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“…; Rabosky and Matute ; Gómez‐Rodríguez et al. ; Wiens ,b; Scholl and Wiens ; Cooney et al. ; Tedesco et al.…”

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confidence: 99%

“…Instead, they reported that simulations of net diversification rates often yielded significant, positive relationships between clade ages and their species richness, whereas observed relationships between clade age and richness were often nonsignificant or negative. It is unclear how these results were related to the accuracy of the MS estimators (as opposed to unrealistic simulation assumptions, see Kozak and Wiens ; Scholl and Wiens ). Similarly, these authors argued that the MS estimators should only be used when clade age and species richness are positively related (e.g., Rabosky and Matute ; Rabosky et al.…”

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confidence: 99%

Estimating diversification rates for higher taxa: BAMM can give problematic estimates of rates and rate shifts

Meyer

Wiens

2017

Evolution

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Here, we use simulations to compare their performance. We found that BAMM yielded relatively weak relationships between true and estimated diversification rates. This occurred because BAMM underestimated the number of rates shifts across each tree, and assigned high rates to small clades with low rates. Errors in both speciation and extinction rates contributed to these errors, showing that using BAMM to estimate only speciation rates is also problematic. In contrast, the MS estimators (particularly using stem group ages), yielded stronger relationships between true and estimated diversification rates, by roughly twofold. Furthermore, the MS approach remained relatively accurate when diversification rates were heterogeneous within clades, despite the widespread assumption that it requires constant rates within clades. Overall, we caution that BAMM may be problematic for estimating diversification rates and rate shifts.

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“…; Jezkova and Wiens ; Moen and Wiens ). Furthermore, diversification rates of higher taxa are generally strongly related to those of the clades within them (Scholl and Wiens ). (6)R2018 acknowledged that BAMM underestimates the number of rate shifts, but defended BAMM as being “conservative.” That is, it only assigns clades different rates if there is strong support for those differences.…”

Section: Bamm Versus the Ms Estimatorsmentioning

confidence: 99%

BAMM gives misleading rate estimates in simulated and empirical datasets

2018

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In a previous paper, we used simulations and empirical data to show that BAMM (Bayesian Analysis of Macroevolutionary Mixtures) can give misleading estimates of rates and rate shifts. In simulations, BAMM underestimated rate shifts across every tree analyzed, and assigned incorrect rates to most clades in most trees. In empirical analyses, BAMM behaved as expected from simulations, and assigned different rates to clades when clades were analyzed alone versus across the tree (i.e., with rate heterogeneity). Rabosky recently criticized our paper, focusing primarily on the idea that our comparison of BAMM to another approach (method-of-moments estimators of Magallón and Sanderson, or MS estimators) was unfair to BAMM. Here, we provide further evidence that BAMM gives misleading rate estimates in empirical studies. We then describe how Rabosky's rown method comparisons were either acknowledged as being problematic or were described inaccurately (to favor BAMM). Finally, we show that the MS estimators can perform well when rates vary over time, despite untested assertions that they require constant rates to be accurate. Many other methods are available for analyzing diversification rates: we argue that BAMM should be avoided for estimating both diversification rates and rate shifts.

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Diversification rates and species richness across the Tree of Life

Cited by 124 publications

References 50 publications

Time and environment explain the current richness distribution of non‐marine turtles worldwide

Time and environment explain the current richness distribution of non‐marine turtles worldwide

Estimating diversification rates for higher taxa: BAMM can give problematic estimates of rates and rate shifts

BAMM gives misleading rate estimates in simulated and empirical datasets

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