Synergistic Effect of UiO-66 Directly Grown on Kombucha-Derived Bacterial Cellulose for Dye Removal.

Metal-Organic Frameworks (MOFs) are particularly attractive sorbents with great potential for the removal of toxic dye pollutants from industrial wastewaters. The uniform dispersion of MOF particles on suitable substrates then represents a key condition to improve their processability and provide good accessibility to the active sites. In this work, we investigate the efficiency of a natural bacterial cellulose material derived from Kombucha (KBC) as an active functional support for growing and anchoring MOF particles with UiO-66 structures. An original hierarchical microstructure was obtained for the as-developed Kombucha cellulose/UiO-66 (KBC-UiO) composite material, with small MOF crystals (~100 nm) covering the cellulose fibers. Promising adsorption properties were demonstrated for anionic organic dyes such as fluorescein or bromophenol blue in water at pH 5 and pH 7 (more than 90% and 50% removal efficiency, respectively, after 10 min in static conditions). This performance was attributed to both the high accessibility and uniform dispersion of the MOF nanocrystals on the KBC fibers together with the synergistic effects involving the attractive adsorbing properties of UiO-66 and the surface chemistry of KBC. The results of this study provide a simple and generic approach for the design of bio-sourced adsorbents and filters for pollutants abatement and wastewater treatment.

Impact of interventions scenarios targeting three main vascular risk factors on the future burden of dementia in France.

The epidemiological and societal burden of dementia is expected to increase in the coming decades due to the world population aging. In this context, the evaluation of the potential impact of intervention scenarios aiming at reducing the prevalence of dementia risk factors is an active area of research. However, such studies must account for the associated changes in mortality and the dependence between the risk factors. Using micro-simulations, this study aims to estimate the changes in dementia burden in France in 2040 according to intervention scenarios targeting the prevention or treatment of hypertension, diabetes and physical inactivity. Accounting for their communality and their effects on mortality, the results show that the disappearance of hypertension, diabetes and physical inactivity in France in 2020 could decrease dementia prevalence by 33% among men and 26% among women in 2040 and increase the life expectancy without dementia at age 65 by 3.4 years (men) and 2.6 years (women). Among the three factors, the prevention of hypertension would be the most efficient. These projections rely on current estimates of the risk of dementia and death associated with risk factors. Thanks to the R package developed they could be refined for different countries or different interventions and updated with new estimates.

Analysis of time-to-event for observational studies: Guidance to the use of intensity models.

This paper provides guidance for researchers with some mathematical background on the conduct of time-to-event analysis in observational studies based on intensity (hazard) models. Discussions of basic concepts like time axis, event definition and censoring are given. Hazard models are introduced, with special emphasis on the Cox proportional hazards regression model. We provide check lists that may be useful both when fitting the model and assessing its goodness of fit and when interpreting the results. Special attention is paid to how to avoid problems with immortal time bias by introducing time-dependent covariates. We discuss prediction based on hazard models and difficulties when attempting to draw proper causal conclusions from such models. Finally, we present a series of examples where the methods and check lists are exemplified. Computational details and implementation using the freely available R software are documented in Supplementary Material. The paper was prepared as part of the STRATOS initiative.

Excess cumulative incidence estimation for matched cohort survival studies.

We suggest a regression approach to estimate the excess cumulative incidence function (CIF) when matched data are available. In a competing risk setting, we define the excess risk as the difference between the CIF in the exposed group and the background CIF observed in the unexposed group. We show that the excess risk can be estimated through an extended binomial regression model that actively uses the matched structure of the data, avoiding further estimation of both the exposed and the unexposed CIFs. The method naturally deals with two time scales, age and time since exposure and simplifies how to deal with the left truncation on the age time-scale. The model makes it easy to predict individual excess risk scenarios and allows for a direct interpretation of the covariate effects on the cumulative incidence scale. After introducing the model and some theory to justify the approach, we show via simulations that our model works well in practice. We conclude by applying the excess risk model to data from the ALiCCS study to investigate the excess risk of late events in childhood cancer survivors.

Drivers of amphibian population dynamics and asynchrony at local and regional scales.

Identifying the drivers of population fluctuations in spatially distinct populations remains a significant challenge for ecologists. Whereas regional climatic factors may generate population synchrony (i.e. the Moran effect), local factors including the level of density dependence may reduce the level of synchrony. Although divergences in the scaling of population synchrony and spatial environmental variation have been observed, the regulatory factors that underlie such mismatches are poorly understood. Few previous studies have investigated how density-dependent processes and population-specific responses to weather variation influence spatial synchrony at both local and regional scales. We addressed this issue in a pond-breeding amphibian, the great crested newt Triturus cristatus. We used capture-recapture data collected through long-term surveys in five T. cristatus populations in Western Europe. In all populations-and subpopulations within metapopulations-population size, annual survival and recruitment fluctuated over time. Likewise, there was considerable variation in these demographic rates between populations and within metapopulations. These fluctuations and variations appear to be context-dependent and more related to site-specific characteristics than local or regional climatic drivers. We found a low level of demographic synchrony at both local and regional levels. Weather has weak and spatially variable effects on survival, recruitment and population growth rate. In contrast, density dependence was a common phenomenon (at least for population growth) in almost all populations and subpopulations. Our findings support the idea that the Moran effect is low in species where the population dynamics more closely depends on local factors (e.g. population density and habitat characteristics) than on large-scale environmental fluctuation (e.g. regional climatic variation). Such responses may have far-reaching consequences for the long-term viability of spatially structured populations and their ability to respond to large-scale climatic anomalies.

Multiple density-dependent processes shape the dynamics of a spatially structured amphibian population.

Understanding the mechanisms that regulate the dynamics of spatially structured populations (SSP) is a critical challenge for ecologists and conservation managers. Internal population processes such as births and deaths occur at a local level, while external processes such as dispersal take place at an inter-population level. At both levels, density dependence is expected to play a critical role. At a patch scale, demographic traits (e.g., survival, breeding success) and the population growth rate can be influenced by density either negatively (e.g., competition effect) or positively (e.g., Allee effects). At the scale of an SSP, although positive density-dependent dispersal has been widely reported, an increasing number of studies have highlighted negative density-dependent dispersal. While many studies have investigated the effects of density on population growth or on dispersal, few have simultaneously examined density-dependent effects at the scale of both the local population and the entire SSP. In this study, we examine how density is related to demographic processes at both the pond level (survival and population growth) and the SSP level (between-pond dispersal) in a pond-breeding amphibian, the great crested newt (Triturus cristatus). The study was based on 20 years of individual capture-recapture (CR) data (from 1996 to 2015) gathered from an SSP made up of 12 experimental ponds ("patches"). We first used a CR multievent model to estimate both survival and dispersal rates in specific ponds as a function of distance between ponds. Then, using a second CR multievent model, we examined whether survival and recapture rates were influenced by population density in a pond. Lastly, we used state-space time series models to investigate whether density affected population growth in each pond. Our results found a positive density-dependent effect on survival and a negative density-dependent effect on departure. In addition, the findings indicate that population growth was negatively related to density in all 12 ponds. These results support the hypothesis that in SSPs, density may have multiple and contrasting effects on demographic parameters and growth rates within local populations as well as on dispersal. This study underlines the need to better understand how density dependence may influence potential trade-offs between life-history strategies and life-history stages.

Secular trends of mortality and dementia-free life expectancy over a 10-year period in France.

The aim of this paper was to investigate the evolution of mortality and life expectancy according to dementia in two French populations 10 years apart. Two different populations of subjects aged 65 or older included in PAQUID from 1988 to 1989 (n = 1342) and 3C from 1999 to 2000 (n = 1996) and initially not demented were followed over 10 years. Dementia was assessed using an algorithmic approach, and participants were considered to have dementia if they had an MMSE score < 24 AND a 4IADL score > 1. Illness-death models were used to compare mortality with and without dementia and to provide total life expectancy (LE), dementia-free life expectancy (DemFreeLE), life expectancy with dementia (DemLE), and survival with dementia. Mortality without dementia has decreased between the two populations among men [HR = 0.63 (0.49-0.81)] and women [HR = 0.67 (0.50-0.90)], whereas mortality with dementia has decreased for women only [HR = 0.59 (0.41-0.87)]. Total LE and DemFreeLE have increased between the 1990s and the 2000s populations (total LE: + 2.5 years; DemFreeLE: + 2.2 years); DemLE only slightly increased between the populations (DemLE: + 0.3 years). For survival with dementia, an increase in survival has been evidenced (mean survival: + 1.3 years) for women only. The improvement in DemFreeLE is promising. However, as the duration of life with dementia tends to increase for women, efforts to delay the onset of dementia should be reinforced.

Contribution of Maternal Antiretroviral Therapy and Breastfeeding to 24-Month Survival in Human Immunodeficiency Virus-Exposed Uninfected Children: An Individual Pooled Analysis of African and Asian Studies.

Background: Human immunodeficiency virus (HIV)-infected pregnant women increasingly receive antiretroviral therapy (ART) to prevent mother-to-child transmission (PMTCT). Studies suggest HIV-exposed uninfected (HEU) children face higher mortality than HIV-unexposed children, but most evidence relates to the pre-ART era, breastfeeding of limited duration, and considerable maternal mortality. Maternal ART and prolonged breastfeeding while on ART may improve survival, although this has not been reliably quantified. Methods: Individual data on 19 219 HEU children from 21 PMTCT trials/cohorts undertaken from 1995 to 2015 in Africa and Asia were pooled to estimate the association between 24-month mortality and maternal/infant factors, using random-effects Cox proportional hazards models. Adjusted attributable fractions of risks computed using the predict function in the R package "frailtypack" were used to estimate the relative contribution of risk factors to overall mortality. Results: Cumulative incidence of death was 5.5% (95% confidence interval, 5.1-5.9) by age 24 months. Low birth weight (LBW <2500 g, adjusted hazard ratio (aHR, 2.9), no breastfeeding (aHR, 2.5), and maternal death (aHR, 11.1) were significantly associated with increased mortality. Maternal ART (aHR, 0.5) was significantly associated with lower mortality. At the population level, LBW accounted for 16.2% of 24-month mortality, never breastfeeding for 10.8%, mother not receiving ART for 45.6%, and maternal death for 4.3%; combined, these factors explained 63.6% of deaths by age 24 months. Conclusions: Survival of HEU children could be substantially improved if public health practices provided all HIV-infected mothers with ART and supported optimal infant feeding and care for LBW neonates.

Estimating dispersal in spatiotemporally variable environments using multievent capture-recapture modeling.

Dispersal is a key process in ecological and evolutionary dynamics. Spatiotemporal variation in habitat availability and characteristics has been suggested to be one of the main cause involved in dispersal evolution and has a strong influence on metapopulation dynamics. In recent decades, the study of dispersal has led to the development of capture-recapture (CR) models that allow movement between sites to be quantified, while handling imperfect detection. For studies involving numerous recapture sites, Lagrange et al. () proposed a multievent CR model that allows dispersal to be estimated while omitting site identity by distinguishing between individuals that stay and individuals that move. More recently, Cayuela et al. () extended this model to allow survival and dispersal probabilities to differ for the different types of habitat represented by several sites within a study area. Yet in both of these modeling systems, the state of sites is assumed to be static over time, which is not a realistic assumption in dynamic landscapes. For that purpose, we generalized the multievent CR model proposed by Cayuela et al. () to allow the estimation of dispersal, survival and recapture probabilities when a site may appear or disappear over time (MODEL 1) or when the characteristics of a site fluctuate over space and time (MODEL 2). This paper first presents these two new modeling systems, and then provides an illustration of their efficacy and usefulness by applying them to simulated CR data and data collected on two metapopulations of amphibians. MODEL 1 was tested using CR data recorded on a metapopulation of yellow-bellied toads (Bombina variegata). In this first empirical case, we examined whether the drying-out dynamics of ponds and the past dispersal status of an individual might affect dispersal behavior. Our study revealed that the probability of facultative dispersal (i.e., from a pond group that remained available/flooded) fluctuated between years and was higher in individuals that had previously dispersed. MODEL 2 was tested using CR data collected on a metapopulation of great crested newts (Triturus cristatus). In this second empirical example, we investigated whether the density of alpine newts (Ichthyosaura alpestris), a potential competitor, might affect the dispersal and survival of the crested newt. Our study revealed that the departure rate was lower in ponds with a high density of heterospecifics than in ponds with a low density of heterospecifics at both inter-annual and intra-annual scales. Moreover, annual survival was slightly higher in ponds with a high density of heterospecifics. Overall, our findings indicate that these multievent CR models provide a highly flexible means of modeling dispersal in dynamic landscapes.

Projections of prevalence, lifetime risk, and life expectancy of Parkinson's disease (2010-2030) in France.

BACKGROUND: Previous studies on the number of Parkinson's disease (PD) patients in the future based on projections of population size underestimated PD burden because they did not take into account the improvement of life expectancy over time. OBJECTIVE: The objective of this study was to assess PD progression from 2010 to 2030 in France in terms of prevalent patient numbers, prevalence rates, lifetime risk, and life expectancy with PD, accounting for projections of overall mortality and increased risk of death of PD patients. METHODS: To provide projections of PD burden, we applied a multistate approach considering age and calendar time to incidence and prevalence rates of PD (France 2010) based on drug claims and national demographic data. RESULTS: The number of PD patients will increase by ∼65% between 2010 (n = 155,000) and 2030 (n ∼ 260,000), mainly for individuals older than 65 years; the prevalence rate of PD after age 45 will increase from 0.59% in 2010 to ∼0.80% in 2030. We project an extension of ∼3 years of the life expectancy of PD patients at 65 years between 2010 (women, 14.8 years; men, 13.0 years) and 2030 (women, 17.8 years; men, 16.1 years), and a relative increase of about 10% of the lifetime risk of PD at 45 years between 2010 (women, 5.5%; men, 6.0%) and 2030 (women, 6.3%; men, 7.4%). CONCLUSIONS: The number of PD patients is predicted to grow substantially in future years as a consequence of population aging and life expectancy improvement. The assessment of the future PD burden is an important step for planning resources needed for patient care in aging societies. © 2018 International Parkinson and Movement Disorder Society.

Projections of health indicators for chronic disease under a semi-Markov assumption.

Chronic diseases are a growing public health problem due to the population aging. Their economic, social and demographic burden will worsen in years to come. Up to now, the method used to provide projections and assess the future disease burden makes a non-homogeneous Markov assumption in an illness-death model. Both age and calendar year have been taken into account in all parameter estimations, but the time spent with the disease was not considered. This work develops the method with a semi-Markov assumption to model mortality among the diseased and considering the time spent with the disease. The method is applied to estimate several health indicators for dementia in France in 2030. We find that mortality among the individuals with dementia depends on age, calendar year and disease duration, and it is greater for men than for women at all ages. The projections for 2030 suggest a 27% increase of the number of dementia cases. The model proposed in this work has flexible assumptions that make it adaptable to provide projections for various diseases.

Context-dependent dispersal, public information, and heterospecific attraction in newts.

Dispersal is one of the main processes that determine community structure. Individuals make dispersal decisions according to environmental and/or social cues that reflect the fitness prospects in a given patch. The presence and abundance of heterospecifics within the same ecological guild, and/or their breeding success, may act as public information that influences movement decisions. To date, most studies investigating the role of heterospecific attraction have focused on habitat choice, using both experimental and correlational approaches. The present study is the first to examine how long-term variation in heterospecific density in breeding patches may affect dispersal patterns in spatially structured populations. We investigate how the dispersal decisions of the great crested newt (Triturus cristatus) are related to the variable density of two other newt species, the alpine newt (Ichthyosaura alpestris) and the palmate newt (Lissotriton helveticus). To examine this issue, we used capture-recapture data collected in an experimental pond network over a 20-year period. The results revealed that the great crested newt's dispersal is context dependent and is affected by variation in heterospecific density: individuals were less likely to emigrate from ponds with high heterospecific density and were more likely to immigrate to ponds with high heterospecific density. These findings suggest that individuals adjust their dispersal decisions at least partly based on public information provided by heterospecifics. This mechanism may play a critical role in the dynamics of spatially structured populations and community functioning.

Life history tactics shape amphibians' demographic responses to the North Atlantic Oscillation.

Over the last three decades, climate abnormalities have been reported to be involved in biodiversity decline by affecting population dynamics. A growing number of studies have shown that the North Atlantic Oscillation (NAO) influences the demographic parameters of a wide range of plant and animal taxa in different ways. Life history theory could help to understand these different demographic responses to the NAO. Indeed, theory states that the impact of weather variation on a species' demographic traits should depend on its position along the fast-slow continuum. In particular, it is expected that NAO would have a higher impact on recruitment than on adult survival in slow species, while the opposite pattern is expected occur in fast species. To test these predictions, we used long-term capture-recapture datasets (more than 15,000 individuals marked from 1965 to 2015) on different surveyed populations of three amphibian species in Western Europe: Triturus cristatus, Bombina variegata, and Salamandra salamandra. Despite substantial intraspecific variation, our study revealed that these three species differ in their position on a slow-fast gradient of pace of life. Our results also suggest that the differences in life history tactics influence amphibian responses to NAO fluctuations: Adult survival was most affected by the NAO in the species with the fastest pace of life (T. cristatus), whereas recruitment was most impacted in species with a slower pace of life (B. variegata and S. salamandra). In the context of climate change, our findings suggest that the capacity of organisms to deal with future changes in NAO values could be closely linked to their position on the fast-slow continuum.

Does habitat unpredictability promote the evolution of a colonizer syndrome in amphibian metapopulations?

Dispersal is a central component of life history evolution. An increasing number of studies suggest that spatiotemporally variable environments may promote the evolution of "dispersal syndromes," consisting of covariation patterns between dispersal and morphological, physiological, behavioral, and life history traits. At the interspecific scale, the "colonizer syndrome" appears to be one of the most frequently recorded associations between dispersal and life history traits, linking a high dispersal rate, high fecundity, and a short lifespan as systematically combined adaptations in spatiotemporally varying environments. However, few studies have highlighted the existence of a "colonizer syndrome" at the intraspecific scale, and none have investigated how different degrees of habitat stochasticity might shape covariation patterns between dispersal and life history traits. In this study, we examined this issue in free-ranging metapopulations of the yellow-bellied toad (Bombina variegata) using capture-recapture data. Combining the results of this study with another recent study, we found that a high dispersal rate, high fecundity, and a short lifespan are associated in metapopulations experiencing unpredictable environments. In contrast, a very low dispersal rate (close to zero), low fecundity and a long lifespan are associated in metapopulations occupying predictable environments. We discuss these results as well as their demographic and evolutionary consequences.

Contrasting patterns of environmental fluctuation contribute to divergent life histories among amphibian populations.

Because it modulates the fitness returns of possible options of energy expenditure at each ontogenetic stage, environmental stochasticity is usually considered a selective force in driving or constraining possible life histories. Divergent regimes of environmental fluctuation experienced by populations are expected to generate differences in the resource allocation schedule between survival and reproductive effort and outputs. To our knowledge, no study has previously examined how different regimes of stochastic variation in environmental conditions could result in changes in both the temporal variation and mean of demographic parameters, which could then lead to intraspecific variation along the slow-fast continuum of life history tactics. To investigate these issues, we used capture-recapture data collected on five populations of a long-lived amphibian (Bombina variegata) experiencing two distinct levels of stochastic environmental variation: (1) constant availability of breeding sites in space and time (predictable environment), and (2) variable spatio-temporal availability of breeding sites (unpredictable environment). We found that female breeding propensity varied more from year to year in unpredictable than in predictable environments. Although females in unpredictable environments produced on average more viable offspring per year, offspring production was more variable between years. Survival at each ontogenetic stage was slightly lower and varied significantly more from year to year in unpredictable environments. Taken together, these results confirm that increased environmental stochasticity can modify the resource allocation schedule between survival and reproductive effort and outputs and may lead to intraspecific variation along the slow-fast continuum of life history tactics.

Demographic responses to weather fluctuations are context dependent in a long-lived amphibian.

Weather fluctuations have been demonstrated to affect demographic traits in many species. In long-lived organisms, their impact on adult survival might be buffered by the evolution of traits that reduce variation in interannual adult survival. For example, skipping breeding is an effective behavioral mechanism that may limit yearly variation in adult survival when harsh weather conditions occur; however, this in turn would likely lead to strong variation in recruitment. Yet, only a few studies to date have examined the impact of weather variation on survival, recruitment and breeding probability simultaneously in different populations of the same species. To fill this gap, we studied the impact of spring temperatures and spring rainfall on survival, on reproductive skipping behavior and on recruitment in five populations of a long-lived amphibian, the yellow-bellied toad (Bombina variegata). Based on capture-recapture data, our findings demonstrate that survival depends on interactions between age, population and weather variation. Varying weather conditions in the spring result in strong variation in the survival of immature toads, whereas they have little effect on adult toads. Breeding probability depends on both the individual's previous reproductive status and on the weather conditions during the current breeding season, leading to high interannual variation in recruitment. Crucially, we found that the impact of weather variation on demographic traits is largely context dependent and may thus differ sharply between populations. Our results suggest that studies predicting the impact of climate change on population dynamics should be taken with caution when the relationship between climate and demographic traits is established using only one population or few populations. We therefore highly recommend further research that includes surveys replicated in a substantial number of populations to account for context-dependent variation in demographic processes.

Joint latent class model for longitudinal data and interval-censored semi-competing events: Application to dementia.

Joint models are used in ageing studies to investigate the association between longitudinal markers and a time-to-event, and have been extended to multiple markers and/or competing risks. The competing risk of death must be considered in the elderly because death and dementia have common risk factors. Moreover, in cohort studies, time-to-dementia is interval-censored since dementia is assessed intermittently. So subjects can develop dementia and die between two visits without being diagnosed. To study predementia cognitive decline, we propose a joint latent class model combining a (possibly multivariate) mixed model and an illness-death model handling both interval censoring (by accounting for a possible unobserved transition to dementia) and semi-competing risks. Parameters are estimated by maximum-likelihood handling interval censoring. The correlation between the marker and the times-to-events is captured by latent classes, homogeneous sub-groups with specific risks of death, dementia, and profiles of cognitive decline. We propose Markovian and semi-Markovian versions. Both approaches are compared to a joint latent-class model for competing risks through a simulation study, and applied in a prospective cohort study of cerebral and functional ageing to distinguish different profiles of cognitive decline associated with risks of dementia and death. The comparison highlights that among subjects with dementia, mortality depends more on age than on duration of dementia. This model distinguishes the so-called terminal predeath decline (among healthy subjects) from the predementia decline.

Trends in dementia incidence: Evolution over a 10-year period in France.

INTRODUCTION: Few recent studies have suggested declining trends in dementia frequency. French cohorts with long follow-up allowed us to explore incidence evolution trends. METHODS: Two different populations of subjects aged ≥65 years included in 1988-1989 (n = 1469) and 1999-2000 (n = 2104) were followed up over 10 years, with systematic assessment for cognition and dementia. Multistates illness-death models were used to compare dementia incidence using both clinical and algorithmic diagnoses. RESULTS: Using the algorithmic diagnosis, incidence declined significantly overall and for women (age-adjusted hazard ratio [HR] = 0.62; confidence interval (CI) = 0.48-0.80 for women between the two populations). Differences in education, vascular factors, and depression accounted only to some extent for this reduction (women full-adjusted HR = 0.73; CI = 0.57-0.95). No significant decreasing trends were found for men or when using the clinical diagnosis for either sex. DISCUSSION: Our study provides further support for a decrease in dementia incidence in women using algorithmic diagnosis. Changes in diagnostic boundaries mask this reduction.

ADL disability and death in dementia in a French population-based cohort: New insights with an illness-death model.

INTRODUCTION: Transition to bathing or dressing disability is a milestone in the evolution of dementia. We examined the transition to disability in these specific activities and considered death to be a competitive event and age and sex to be prognostic factors. METHODS: From a large cohort of 570 incident dementia cases screened in two prospective population-based cohorts, the Paquid study, and the Three-City study, we estimated the probabilities of remaining nondisabled, becoming disabled in bathing or dressing, or dying after the diagnosis using an illness-death model. RESULTS: On average, approximately half of the period (3 years) of living with dementia was free of disability. In women, a higher survival rate was associated with an average of 1 additional year with disability. DISCUSSION: The joint prediction of death and disability in dementia by an illness-death model gives original and useful parameters for the prognosis and management of dementia.

Genetic consequences of population expansions and contractions in the common hippopotamus (Hippopotamus amphibius) since the Late Pleistocene.

Over the past two decades, an increasing amount of phylogeographic work has substantially improved our understanding of African biogeography, in particular the role played by Pleistocene pluvial-drought cycles on terrestrial vertebrates. However, still little is known on the evolutionary history of semi-aquatic animals, which faced tremendous challenges imposed by unpredictable availability of water resources. In this study, we investigate the Late Pleistocene history of the common hippopotamus (Hippopotamus amphibius), using mitochondrial and nuclear DNA sequence variation and range-wide sampling. We documented a global demographic and spatial expansion approximately 0.1-0.3 Myr ago, most likely associated with an episode of massive drainage overflow. These events presumably enabled a historical continent-wide gene flow among hippopotamus populations, and hence, no clear continental-scale genetic structuring remains. Nevertheless, present-day hippopotamus populations are genetically disconnected, probably as a result of the mid-Holocene aridification and contemporary anthropogenic pressures. This unique pattern contrasts with the biogeographic paradigms established for savannah-adapted ungulate mammals and should be further investigated in other water-associated taxa. Our study has important consequences for the conservation of the hippo, an emblematic but threatened species that requires specific protection to curtail its long-term decline.