The temporal dynamics of species diversity are shaped by variations in the rates of speciation and extinction, and there is a long history of inferring these rates using first and last appearances of taxa in the fossil record. Understanding diversity dynamics critically depends on unbiased estimates of the unobserved times of speciation and extinction for all lineages, but the inference of these parameters is challenging due to the complex nature of the available data. Here, we present a new probabilistic framework to jointly estimate species-specific times of speciation and extinction and the rates of the underlying birth-death process based on the fossil record. The rates are allowed to vary through time independently of each other, and the probability of preservation and sampling is explicitly incorporated in the model to estimate the true lifespan of each lineage. We implement a Bayesian algorithm to assess the presence of rate shifts by exploring alternative diversification models. Tests on a range of simulated data sets reveal the accuracy and robustness of our approach against violations of the underlying assumptions and various degrees of data incompleteness. Finally, we demonstrate the application of our method with the diversification of the mammal family Rhinocerotidae and reveal a complex history of repeated and independent temporal shifts of both speciation and extinction rates, leading to the expansion and subsequent decline of the group. The estimated parameters of the birth-death process implemented here are directly comparable with those obtained from dated molecular phylogenies. Thus, our model represents a step towards integrating phylogenetic and fossil information to infer macroevolutionary processes.

Conservation of species and ecosystems is increasingly difficult because anthropogenic impacts are pervasive and accelerating. Under this rapid global change, maximizing conservation success requires a paradigm shift from maintaining ecosystems in idealized past states toward facilitating their adaptive and functional capacities, even as species ebb and flow individually. Developing effective strategies under this new paradigm will require deeper understanding of the long-term dynamics that govern ecosystem persistence and reconciliation of conflicts among approaches to conserving historical versus novel ecosystems. Integrating emerging information from conservation biology, paleobiology, and the Earth sciences is an important step forward on the path to success. Maintaining nature in all its aspects will also entail immediately addressing the overarching threats of growing human population, overconsumption, pollution, and climate change.

The Cape region of South Africa is one of the most remarkable hotspots of biodiversity with a flora comprising more than 9000 plant species, almost 70% of which are endemic, within an area of only ± 90,000 km2. Much of the diversity is due to an exceptionally large contribution of just a few clades that radiated substantially within this region, but little is known about the causes of these radiations. Here, we present a comprehensive analysis of plant diversification, using near complete species-level phylogenies of four major Cape clades (more than 470 species): the genus Protea, a tribe of legumes (Podalyrieae) and two speciose genera within the iris family (Babiana and Moraea), representing three of the seven largest plant families in this biodiversity hotspot. Combining these molecular phylogenetic data with ecological and biogeographical information, we tested key hypotheses that have been proposed to explain the radiation of the Cape flora. Our results show that the radiations started throughout the Oligocene and Miocene and that net diversification rates have remained constant through time at globally moderate rates. Furthermore, using sister-species comparisons to assess the impact of different factors on speciation, we identified soil type shifts as the most important cause of speciation in Babiana, Moraea, and Protea, whereas shifts in fire-survival strategy is the most important factor for Podalyrieae. Contrary to previous findings in other groups, such as orchids, pollination syndromes show a high degree of phylogenetic conservatism, including groups with a large number of specialized pollination syndromes like Moraea. We conclude that the combination of complex environmental conditions together with relative climatic stability promoted high speciation and/or low extinction rates as the most likely scenario leading to present-day patterns of hyperdiversity in the Cape.

The Cape region of South Africa is a hotspot of flowering plant biodiversity. However, the reasons why levels of diversity and endemism are so high remain obscure. Here, we reconstructed phylogenetic relationships among species in the genus Protea, which has its center of species richness and endemism in the Cape, but also extends through tropical Africa as far as Eritrea and Angola. Contrary to previous views, the Cape is identified as the ancestral area for the radiation of the extant lineages: most species in subtropical and tropical Africa are derived from a single invasion of that region. Moreover, diversification rates have been similar within and outside the Cape region. Migration out of the Cape has opened up vast areas, but those lineages have not diversified as extensively at fine spatial scales as lineages in the Cape. Therefore, higher net rates of diversification do not explain the high diversity and endemism of Protea in the Cape. Instead, understanding why the Cape is so diverse requires an explanation for how Cape species are able to diverge and persist at such small spatial scales.

Summary1. Despite the advancement of phylogenetic methods to estimate speciation and extinction rates, their power can be limited under variable rates, in particular for clades with high extinction rates and small number of extant species. Fossil data can provide a powerful alternative source of information to investigate diversification processes. 2. Here, we present PyRate, a computer program to estimate speciation and extinction rates and their temporal dynamics from fossil occurrence data. The rates are inferred in a Bayesian framework and are comparable to those estimated from phylogenetic trees. 3. We describe how PyRate can be used to explore different models of diversification. In addition to the diversification rates, it provides estimates of the parameters of the preservation process (fossilization and sampling) and the times of speciation and extinction of each species in the data set. Moreover, we develop a new birth-death model to correlate the variation of speciation/extinction rates with changes of a continuous trait.

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AimOur objective is to analyse global‐scale patterns of mountain biodiversity and the driving forces leading to the observed patterns. More specifically, we test the ‘mountain geobiodiversity hypothesis’ (MGH) which is based on the assumption that it is not mountain‐uplift alone which drives the evolution of mountain biodiversity, but rather the combination of geodiversity evolution and Neogene and Pleistocene climate changes. We address the following questions: (a) Do areas of high geodiversity and high biodiversity in mountains overlap, that is can mountain geodiversity predict mountain biodiversity? (b) What is the role of Pleistocene climate change in shaping mountain biodiversity? (c) Did diversification rate shifts occur predominantly with the onset of more pronounced climate fluctuations in the late Neogene and Pleistocene fostering a ‘species pump’ effect, as predicted by the MGH?LocationGlobal.TaxonVascular plants.MethodsWe used generalized linear models to test to what extent vascular plant species diversity in mountains is explained by net primary productivity (NPP), geodiversity and Pleistocene climate fluctuations (i.e. changes in temperature between the Last Glacial Maximum [LGM] and today). In addition, we compiled dates of diversification rate shifts from mountain systems and investigated whether these shifts occurred predominantly before or after the global major climatic fluctuations of the late Neogene and Pleistocene.ResultsBoth NPP and elevation range show a positive relationship, whereas Pleistocene climatic fluctuations show a negative impact on plant species diversity. The availability of climatic niche space during the LGM differs markedly among mountain systems. Shifts to higher diversification rates or starts of radiations showed the highest concentration from the late Miocene towards the Pleistocene, supporting the MGH. The most commonly inferred drivers of diversification were key innovations, geological processes (uplift) and climate.Main conclusionsOur analyses point towards an important role of historical factors on mountain plant species richness. Mountain systems characterized by small elevational ranges and strong modifications of temperature profiles appear to harbour fewer radiations, and fewer species. In contrast, mountain systems with the largest elevational ranges and stronger overlap between today´s and LGM temperature profiles are also those where most plant radiations and highest species numbers were identified.

BackgroundPatterns of species diversity are the result of speciation and extinction processes, and molecular phylogenetic data can provide valuable information to derive their variability through time and across clades. Bayesian Markov chain Monte Carlo methods offer a promising framework to incorporate phylogenetic uncertainty when estimating rates of diversification.ResultsWe introduce a new approach to estimate diversification rates in a Bayesian framework over a distribution of trees under various constant and variable rate birth-death and pure-birth models, and test it on simulated phylogenies. Furthermore, speciation and extinction rates and their posterior credibility intervals can be estimated while accounting for non-random taxon sampling. The framework is particularly suitable for hypothesis testing using Bayes factors, as we demonstrate analyzing dated phylogenies of Chondrostoma (Cyprinidae) and Lupinus (Fabaceae). In addition, we develop a model that extends the rate estimation to a meta-analysis framework in which different data sets are combined in a single analysis to detect general temporal and spatial trends in diversification.ConclusionsOur approach provides a flexible framework for the estimation of diversification parameters and hypothesis testing while simultaneously accounting for uncertainties in the divergence times and incomplete taxon sampling.