Parasite diversity declines with host evolutionary distinctiveness: a global analysis of carnivores

Evolutionarily distinctive host lineages might harbor fewer parasite species because they have fewer opportunities for parasite sharing than hosts having extant close relatives, or because diverse parasite assemblages promote host diversification. We evaluate these hypotheses using data from 930 species of parasites reported to infect free-living carnivores. We applied nonparametric richness estimators to estimate parasite diversity among well-sampled carnivore species and assessed how well host evolutionary distinctiveness, relative to other biological and environmental factors, explained variation in estimated parasite diversity. Species richness estimates indicate that the current published literature captures less than 50% of the true parasite diversity for most carnivores. Parasite species richness declined with evolutionary distinctiveness of carnivore hosts (i.e., length of terminal ranches of the phylogeny) and increased with host species body mass and geographic range area. We found no support for the hypothesis that hosts from more diverse lineages support a higher number of generalist parasites, but we did find evidence that parasite assemblages might have driven host lineage diversification through mechanisms linked to sexual selection. Collectively, this work provides strong support for host evolutionary history being an essential predictor of parasite diversity, and offers a simple model for predicting parasite diversity in understudied carnivore species.

Ebola cases and health system demand in Liberia

The authors develop a multi-type branching process model of the 2014 Liberian Ebola outbreak that incorporates the impacts of changes in behavior on potential transmission scenarios, thereby informing the path to containment of the epidemic.

In 2014, a major epidemic of human Ebola virus disease emerged in West Africa, where human-to-human transmission has now been sustained for greater than 12 months. In the summer of 2014, there was great uncertainty about the answers to several key policy questions concerning the path to containment. What is the relative importance of nosocomial transmission compared with community-acquired infection? How much must hospital capacity increase to provide care for the anticipated patient burden? To which interventions will Ebola transmission be most responsive? What must be done to achieve containment? In recent years, epidemic models have been used to guide public health interventions. But, model-based policy relies on high quality causal understanding of transmission, including the availability of appropriate dynamic transmission models and reliable reporting about the sequence of case incidence for model fitting, which were lacking for this epidemic. To investigate the range of potential transmission scenarios, we developed a multi-type branching process model that incorporates key heterogeneities and time-varying parameters to reflect changing human behavior and deliberate interventions in Liberia. Ensembles of this model were evaluated at a set of parameters that were both epidemiologically plausible and capable of reproducing the observed trajectory. Results of this model suggested that epidemic outcome would depend on both hospital capacity and individual behavior. Simulations suggested that if hospital capacity was not increased, then transmission might outpace the rate of isolation and the ability to provide care for the ill, infectious, and dying. Similarly, the model suggested that containment would require individuals to adopt behaviors that increase the rates of case identification and isolation and secure burial of the deceased. As of mid-October, it was unclear that this epidemic would be contained even by 99% hospitalization at the planned hospital capacity. A new version of the model, updated to reflect information collected during October and November 2014, predicts a significantly more constrained set of possible futures. This model suggests that epidemic outcome still depends very heavily on individual behavior. Particularly, if future patient hospitalization rates return to background levels (estimated to be around 70%), then transmission is predicted to remain just below the critical point around R_eff = 1. At the higher hospitalization rate of 85%, this model predicts near complete elimination in March to June, 2015.

There is considerable uncertainty regarding the steps needed to contain the ongoing Ebola crisis in West Africa, the timeline required to achieve control, and the projected burden of mortality. To address these issues, we develop a branching process model for Ebola transmission that focuses on offspring distributions (i.e., the numbers of new infections caused by each case). We use the model to assess the likely progression of Ebola in Liberia. The model assesses the feedback between new cases and hospital demand under a range of plausible intervention scenarios, particularly ramping-up of treatment facilities over time and increasing the number of individuals seeking hospital treatment through outreach and education. Transmission scenarios—to health care workers in hospitals, to caregivers in the community, to hospital visitors, and to individuals preparing bodies for funerals—are described by distinct offspring distributions based on available data. Results suggest that the outcome of the epidemic depends on both hospital capacity and individual behavior. Additionally, the model highlights the conditions under which transmission might have outpaced hospital capacity, and projects possible epidemic trajectories into 2015.

Adaptive evolution and environmental durability jointly structure phylodynamic patterns in avian influenza viruses

Avian influenza viruses (AIVs) have been pivotal to the origination of human pandemic strains. Despite their scientific and public health significance, however, there remains much to be understood about the ecology and evolution of AIVs in wild birds, where major pools of genetic diversity are generated and maintained. Here, we present comparative phylodynamic analyses of human and AIVs in North America, demonstrating (i) significantly higher standing genetic diversity and (ii) phylogenetic trees with a weaker signature of immune escape in AIVs than in human viruses. To explain these differences, we performed statistical analyses to quantify the relative contribution of several potential explanations. We found that HA genetic diversity in avian viruses is determined by a combination of factors, predominantly subtype-specific differences in host immune selective pressure and the ecology of transmission (in particular, the durability of subtypes in aquatic environments). Extending this analysis using a computational model demonstrated that virus durability may lead to long-term, indirect chains of transmission that, when coupled with a short host lifespan, can generate and maintain the observed high levels of genetic diversity. Further evidence in support of this novel finding was found by demonstrating an association between subtype-specific environmental durability and predicted phylogenetic signatures: genetic diversity, variation in phylogenetic tree branch lengths, and tree height. The conclusion that environmental transmission plays an important role in the evolutionary biology of avian influenza viruses-a manifestation of the "storage effect"-highlights the potentially unpredictable impact of wildlife reservoirs for future human pandemics and the need for improved understanding of the natural ecology of these viruses.

Tail probabilities of extinction time in a large number of experimental populations

Determining the distribution of population extinction times is a fundamental problem in theoretical population biology. In particular, the tail properties, patterns in the probability of long-term persistence, have not been studied. Further, until now there have been no experimental or observational data sets with which to empirically test the "rare event" predictions of the standard stochastic theory of extinction, which holds that extinction times should be exponentially distributed. I performed an experimental study of extinction in a large number of replicate (n = 1076) laboratory populations of the waterflea Daphnia pulicaria. Observed extinction time ranged from 1 to 1239 days. Statistical models supported the hypothesis of a power-law distribution over the exponential distribution and other alternatives. This pattern contradicts the notion that population extinction time has an exponential tail, questioning its ubiquitous use in theoretical ecology. It is also a rare instance of a data set that exhibits power-law scaling under appropriate statistical criteria.

On signals of phase transitions in salmon population dynamics

Critical slowing down (CSD) reflects the decline in resilience of equilibria near a bifurcation and may reveal early warning signals (EWS) of ecological phase transitions. We studied CSD in the recruitment dynamics of 120 stocks of three Pacific salmon (Oncorhynchus spp.) species in relation to critical transitions in fishery models. Pink salmon (Oncorhynchus gorbuscha) exhibited increased variability and autocorrelation in populations that had a growth parameter, r, close to zero, consistent with EWS of extinction. However, models and data for sockeye salmon (Oncorhynchus nerka) indicate that portfolio effects from heterogeneity in age-at-maturity may obscure EWS. Chum salmon (Oncorhynchus keta) show intermediate results. The data do not reveal EWS of Ricker-type bifurcations that cause oscillations and chaos at high r. These results not only provide empirical support for CSD in some ecological systems, but also indicate that portfolio effects of age structure may conceal EWS of some critical transitions.

Ecological niche and potential distribution of Anopheles arabiensis in Africa in 2050

Background

The future distribution of malaria in Africa is likely to be much more dependent on environmental conditions than the current distribution due to the effectiveness of indoor and therapeutic anti-malarial interventions, such as insecticide-treated nets (ITNs), indoor residual spraying for mosquitoes (IRS), artemisinin-combination therapy (ACT), and intermittent presumptive treatment (IPT). Future malaria epidemiology is therefore expected to be increasingly dominated by Anopheles arabiensis, which is the most abundant exophagic mosquito competent to transmit Plasmodium falciparum and exhibits a wide geographic range.

Methods

To map the potential distribution of An. arabiensis in Africa, ecological niche models were fit to 20th century collection records. Many common species distribution modelling techniques aim to discriminate species habitat from the background distribution of environments. Since these methods arguably result in unnecessarily large Type I and Type II errors, LOBAG-OC was used to identify the niche boundary using only data on An. arabiensis occurrences. The future distribution of An. arabiensis in Africa was forecasted by projecting the fit model onto maps of simulated climate change following three climate change scenarios.

Results

Ecological niche modelling revealed An. arabiensis to be a climate generalist in the sense that it can occur in most of Africa’s contemporary environmental range. Under three climate change scenarios, the future distribution of An. arabiensis is expected to be reduced by 48%-61%. Map differences between baseline and projected climate suggest that habitat reductions will be especially extensive in Western and Central Africa; portions of Botswana, Namibia, and Angola in Southern Africa; and portions of Sudan, South Sudan, Somalia, and Kenya in East Africa. The East African Rift Valley and Eastern Coast of Africa are expected to remain habitable. Some modest gains in habitat are predicted at the margins of the current range in South Sudan, South Africa, and Angola.

Conclusion

In summary, these results suggest that the future potential distribution of An. arabiensis in Africa is likely to be smaller than the contemporary distribution by approximately half as a result of climate change. Agreement among the three modelling scenarios suggests that this outcome is robust to a wide range of potential climate futures.

On signals of phase transitions in salmon population dynamics

Critical slowing down (CSD) reflects the decline in resilience of equilibria near a bifurcation and may reveal early warning signals (EWS) of ecological phase transitions. We studied CSD in the recruitment dynamics of 120 stocks of three Pacific salmon (Oncorhynchus spp.) species in relation to critical transitions in fishery models. Pink salmon (Oncorhynchus gorbuscha) exhibited increased variability and autocorrelation in populations that had a growth parameter, r, close to zero, consistent with EWS of extinction. However, models and data for sockeye salmon (Oncorhynchus nerka) indicate that portfolio effects from heterogeneity in age-at-maturity may obscure EWS. Chum salmon (Oncorhynchus keta) show intermediate results. The data do not reveal EWS of Ricker-type bifurcations that cause oscillations and chaos at high r. These results not only provide empirical support for CSD in some ecological systems, but also indicate that portfolio effects of age structure may conceal EWS of some critical transitions.

Neutrality, cross-immunity and subtype dominance in avian influenza viruses

Avian influenza viruses (AIVs) are considered a threat for their potential to seed human influenza pandemics. Despite their acknowledged importance, there are significant unknowns regarding AIV transmission dynamics in their natural hosts, wild birds. Of particular interest is the difference in subtype dynamics between human and bird populations-in human populations, typically only two or three subtypes cocirculate, while avian populations are capable of simultaneously hosting a multitude of subtypes. One species in particular-ruddy turnstones (Arenaria interpres)--has been found to harbour a very wide range of AIV subtypes, which could make them a key player in the spread of new subtypes in wild bird populations. Very little is known about the mechanisms that drive subtype dynamics in this species, and here we address this gap in our knowledge. Taking advantage of two independent sources of data collected from ruddy turnstones in Delaware Bay, USA, we examine patterns of subtype diversity and dominance at this site. We compare these patterns to those produced by a stochastic, multi-strain transmission model to investigate possible mechanisms that are parsimonious with the observed subtype dynamics. We find, in agreement with earlier experimental work, that subtype differences are unnecessary to replicate the observed dynamics, and that neutrality alone is sufficient. We also evaluate the role of subtype cross-immunity and find that it is not necessary to generate patterns consistent with observations. This work offers new insights into the mechanisms behind subtype diversity and dominance in a species that has the potential to be a key player in AIV dynamics in wild bird populations.

Subtype diversity and reassortment potential for co-circulating avian influenza viruses at a diversity hot spot

Biological diversity has long been used to measure ecological health. While evidence exists from many ecosystems that declines in host biodiversity may lead to greater risk of disease emergence, the role of pathogen diversity in the emergence process remains poorly understood. Particularly, because a more diverse pool of pathogen types provides more ways in which evolutionary innovations may arise, we suggest that host-pathogen systems with high pathogen diversity are more prone to disease emergence than systems with relatively homogeneous pathogen communities. We call this prediction the diversity-emergence hypothesis. To show how this hypothesis could be tested, we studied a system comprised of North American shorebirds and their associated low-pathogenicity avian influenza (LPAI) viruses. These viruses are important as a potential source of genetic innovations in influenza. A theoretical contribution of this study is an expression predicting the rate of viral subtype reassortment to be proportional to both prevalence and Simpson's Index, a formula that has been used traditionally to quantify biodiversity. We then estimated prevalence and subtype diversity in host species at Delaware Bay, a North American AIV hotspot, and used our model to extrapolate from these data. We estimated that 4 to 39 virus subtypes circulated at Delaware Bay each year between 2000 and 2008, and that surveillance coverage (percentage of co-circulating subtypes collected) at Delaware Bay is only about 63.0%. Simpson's Index in the same period varied more than fourfold from 0.22 to 0.93. These measurements together with the model provide an indirect, model-based estimate of the reassortment rate. A proper test of the diversity-emergence hypothesis would require these results to be joined to independent and reliable estimates of reassortment, perhaps obtained through molecular surveillance. These results suggest both that subtype diversity (and therefore reassortment) varies from year to year and that several subtypes contributing to reassortment are going undetected. The similarity between these results and more detailed studies of one host, ruddy turnstone (Arenaria interpres), further suggests that this species may be the primary host for influenza reassortment at Delaware Bay. Biological diversity has long been quantified using Simpson's Index. Our model links this formula to a mechanistic account of reassortment in multipathogen systems in the form of subtype diversity at Delaware Bay, USA. As a theory of how pathogen diversity may influence the evolution of novel pathogens, this work is a contribution to the larger project of understanding the connections between biodiversity and disease.

Nitrate enrichment alters a Daphnia-microparasite interaction through multiple pathways

Nutrient pollution has the potential to alter many ecological interactions, including host-parasite relationships. One of the largest sources of nutrient pollution comes from anthropogenic alteration of the nitrogen (N) cycle, specifically the increased rate of nitrate (NO3-N) deposition to aquatic environments, potentially altering host-parasite relationships. This study aimed to assess the mechanisms through which nitrate may impact host-pathogen relationships using a fungal pathogen (Metschnikowia bicuspidata) parasitic to crustacean zooplankton (Daphnia dentifera) as a tractable model system. First, the influence of nitrate on host population dynamics was assessed along a gradient of nitrate concentrations. Nitrate decreased host population size and increased infection prevalence. Second, the influence of nitrate on host reproduction, mortality, and infection intensity was assessed at the individual host level by examining the relationship between pathogen dose and infection prevalence at ambient (0.4 mg NO3-N*L(-1)) and intermediate (12 mg NO3-N*L(-1)) levels of nitrate. Host fecundity and infection intensity both decreased with increasing pathogen dose, but increased nitrate levels corresponded to greater infection intensities. Nitrate had no effect on host growth rate, suggesting that hosts do not alter feeding behavior in nitrate-treated media compared with ambient conditions. This study suggests that nutrient enrichment may enhance disease through increased transmission and infection intensity, but that high levels of nitrate may result in smaller epidemics through reduced transmission caused by smaller population sizes and increased pathogen mortality.

A statistical model of Rift Valley fever activity in Egypt

Rift Valley fever (RVF) is a viral disease of animals and humans and a global public health concern due to its ecological plasticity, adaptivity, and potential for spread to countries with a temperate climate. In many places, outbreaks are episodic and linked to climatic, hydrologic, and socioeconomic factors. Although outbreaks of RVF have occurred in Egypt since 1977, attempts to identify risk factors have been limited. Using a statistical learning approach (lasso-regularized generalized linear model), we tested the hypotheses that outbreaks in Egypt are linked to (1) River Nile conditions that create a mosquito vector habitat, (2) entomologic conditions favorable to transmission, (3) socio-economic factors (Islamic festival of Greater Bairam), and (4) recent history of transmission activity. Evidence was found for effects of rainfall and river discharge and recent history of transmission activity. There was no evidence for an effect of Greater Bairam. The model predicted RVF activity correctly in 351 of 358 months (98.0%). This is the first study to statistically identify risk factors for RVF outbreaks in a region of unstable transmission.

Bacterial colonization and extinction on marine aggregates: stochastic model of species presence and abundance

Organic aggregates provide a favorable habitat for aquatic microbes, are efficiently filtered by shellfish, and may play a major role in the dynamics of aquatic pathogens. Quantifying this role requires understanding how pathogen abundance in the water and aggregate size interact to determine the presence and abundance of pathogen cells on individual aggregates. We build upon current understanding of the dynamics of bacteria and bacterial grazers on aggregates to develop a model for the dynamics of a bacterial pathogen species. The model accounts for the importance of stochasticity and the balance between colonization and extinction. Simulation results suggest that while colonization increases linearly with background density and aggregate size, extinction rates are expected to be nonlinear on small aggregates in a low background density of the pathogen. Under these conditions, we predict lower probabilities of pathogen presence and reduced abundance on aggregates compared with predictions based solely on colonization. These results suggest that the importance of aggregates to the dynamics of aquatic bacterial pathogens may be dependent on the interaction between aggregate size and background pathogen density, and that these interactions are strongly influenced by ecological interactions and pathogen traits. The model provides testable predictions and can be a useful tool for exploring how species-specific differences in pathogen traits may alter the effect of aggregates on disease transmission.

Experimental demonstration of accelerated extinction in source-sink metapopulations

Population extinction is a fundamental ecological process which may be aggravated by the exchange of organisms between productive (source) and unproductive (sink) habitat patches. The extent to which such source-sink exchange affects extinction rates is unknown. We conducted an experiment in which metapopulation effects could be distinguished from source-sink effects in laboratory populations of Daphnia magna. Time-to-extinction in this experiment was maximized at intermediate levels of habitat fragmentation, which is consistent with a minority of theoretical models. These results provided a baseline for comparison with experimental treatments designed to detect effects of concentrating resources in source patches. These treatments showed that source-sink configurations increased population variability (the coefficient of variation in abundance) and extinction hazard compared with homogeneous environments. These results suggest that where environments are spatially heterogeneous, accurate assessments of extinction risk will require understanding the exchange of organisms among population sources and sinks. Such heterogeneity may be the norm rather than the exception because of both the intrinsic heterogeneity naturally exhibited by ecosystems and increasing habitat fragmentation by human activity.

Theory of early warning signals of disease emergenceand leading indicators of elimination

Anticipating infectious disease emergence and documenting progress in disease elimination are important applications for the theory of critical transitions. A key problem is the development of theory relating the dynamical processes of transmission to observable phenomena. In this paper, we consider compartmental susceptible-infectious-susceptible (SIS) and susceptible-infectious-recovered (SIR) models that are slowly forced through a critical transition. We derive expressions for the behavior of several candidate indicators, including the autocorrelation coefficient, variance, coefficient of variation, and power spectra of SIS and SIR epidemics during the approach to emergence or elimination. We validated these expressions using individual-based simulations. We further showed that moving-window estimates of these quantities may be used for anticipating critical transitions in infectious disease systems. Although leading indicators of elimination were highly predictive, we found the approach to emergence to be much more difficult to detect. It is hoped that these results, which show the anticipation of critical transitions in infectious disease systems to be theoretically possible, may be used to guide the construction of online algorithms for processing surveillance data.

Dissecting a wildlife disease hotspot: the impact of multiple host species, environmental transmission and seasonality in migration, breeding and mortality

Avian influenza viruses (AIVs) have been implicated in all human influenza pandemics in recent history. Despite this, surprisingly little is known about the mechanisms underlying the maintenance and spread of these viruses in their natural bird reservoirs. Surveillance has identified an AIV 'hotspot' in shorebirds at Delaware Bay, in which prevalence is estimated to exceed other monitored sites by an order of magnitude. To better understand the factors that create an AIV hotspot, we developed and parametrized a mechanistic transmission model to study the simultaneous epizootiological impacts of multi-species transmission, seasonal breeding, host migration and mixed transmission routes. We scrutinized our model to examine the potential for an AIV hotspot to serve as a 'gateway' for the spread of novel viruses into North America. Our findings identify the conditions under which a novel influenza virus, if introduced into the system, could successfully invade and proliferate.

Reversal of global CD4+ subset dysfunction is associated with spontaneous clinical resolution of pulmonary sarcoidosis

Sarcoidosis pathogenesis is characterized by peripheral anergy and an exaggerated, pulmonary CD4(+) Th1 response. In this study, we demonstrate that CD4(+) anergic responses to polyclonal TCR stimulation are present peripherally and within the lungs of sarcoid patients. Consistent with prior observations, spontaneous release of IL-2 was noted in sarcoidosis bronchoalveolar lavage CD4(+) T cells. However, in contrast to spontaneous hyperactive responses reported previously, the cells displayed anergic responses to polyclonal TCR stimulation. The anergic responses correlated with diminished expression of the Src kinase Lck, protein kinase C-θ, and NF-κB, key mediators of IL-2 transcription. Although T regulatory (Treg) cells were increased in sarcoid patients, Treg depletion from the CD4(+) T cell population of sarcoidosis patients did not rescue IL-2 and IFN-γ production, whereas restoration of the IL-2 signaling cascade, via protein kinase C-θ overexpression, did. Furthermore, sarcoidosis Treg cells displayed poor suppressive capacity indicating that T cell dysfunction was a global CD4(+) manifestation. Analyses of patients with spontaneous clinical resolution revealed that restoration of CD4(+) Th1 and Treg cell function was associated with resolution. Conversely, disease progression exhibited decreased Th1 cytokine secretion and proliferative capacity, and reduced Lck expression. These findings implicate normalized CD4(+) T cell function as a potential therapeutic target for sarcoidosis resolution.

Extinction hazards in experimental Daphnia magna populations: effects of genotype diversity and environmental variation

Extinction is ubiquitous in natural systems and the ultimate fate of all biological populations. However, the factors that contribute to population extinction are still poorly understood, particularly genetic diversity and composition. A laboratory experiment was conducted to examine the influences of environmental variation and genotype diversity on persistence in experimental Daphnia magna populations. Populations were initiated in two blocks with one, two, three, or six randomly selected and equally represented genotypes, fed and checked for extinction daily, and censused twice weekly over a period of 170 days. Our results show no evidence for an effect of the number of genotypes in a population on extinction hazard. Environmental variation had a strong effect on hazards in both experimental blocks, but the direction of the effect differed between blocks. In the first block, variable environments hastened extinction, while in the second block, hazards were reduced under variable food input. This occurred despite greater fluctuations in population size in variable environments in the second block of our experiment. Our results conflict with previous studies, where environmental variation consistently increased extinction risk. They are also at odds with previous studies in other systems that documented significant effects of genetic diversity on population persistence. We speculate that the lack of sexual reproduction, or the phenotypic similarity among our experimental lines, might underlie the lack of a significant effect of genotype diversity in our study.

Two sides of the same coin? Rare and pest plants native to the United States and Canada

Plant biodiversity is at risk, with as many as 10% of native species in the United States being threatened with extinction. Habitat loss has led a growing number of plant species to become rare or threatened, while the introduction or expansion of pest species has led some habitats to be dominated by relatively few, mostly nonindigenous, species. As humans continue to alter many landscapes and vegetation types, understanding how biological traits determine the location of species along a spectrum from vulnerability to pest status is critical to designing risk assessment protocols, setting conservation priorities, and developing monitoring programs. We used boosted regression trees to predict rarity (based on The Nature Conservancy global rankings) and pest status (defined as legal pest status) from data on traits for the native vascular flora of the United States and Canada including Hawaii, Puerto Rico, and the Virgin Islands (n approximately = 15,000). Categories were moderately to highly predictable (AUCpest = 0.87 on 25% holdout test set, AUCrarity = 0.80 on 25% holdout test set). Key predictors were chromosome number, ploidy, seed mass, and a suite of traits suggestive of specialist vs. generalist adaptations (e.g., facultative wetland habitat association and phenotypic variability in growth form and life history). Specifically, pests were associated with high chromosome numbers, polyploidy, and seed masses ranging from 0.1 to 100 mg, whereas rare species were associated with low chromosome numbers, low ploidy, and large (>1000 mg) seed masses. In addition, pest species were disproportionately likely to be facultatively associated with wetlands, and variable in growth form and life history, whereas rare species exhibited an opposite pattern. These results suggest that rare and pest species contrast along trait axes related to dispersal and performance in disturbed or novel habitats.