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Rift Valley fever (RVF), an emerging mosquito-borne zoonotic infectious viral disease caused by the RVF virus (RVFV) (Bunyaviridae: Phlebovirus), presents significant threats to global public health and agriculture in Africa and the Middle East. RVFV is listed as a select agent with significant potential for international spread and use in bioterrorism. RVFV has caused large, devastating periodic epizootics and epidemics in Africa over the past ∼60 years, with severe economic and nutritional impacts on humans from illness and livestock loss. In the past 15 years alone, RVFV caused tens of thousands of human cases, hundreds of human deaths, and more than 100,000 domestic animal deaths. Cattle, sheep, goats, and camels are particularly susceptible to RVF and serve as amplifying hosts for the virus. This review highlights recent research on RVF, focusing on vectors and their ecology, transmission dynamics, and use of environmental and climate data to predict disease outbreaks. Important directions for future research are also discussed.

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BackgroundRecent clusters of outbreaks of mosquito-borne diseases (Rift Valley fever and chikungunya) in Africa and parts of the Indian Ocean islands illustrate how interannual climate variability influences the changing risk patterns of disease outbreaks. Although Rift Valley fever outbreaks have been known to follow periods of above-normal rainfall, the timing of the outbreak events has largely been unknown. Similarly, there is inadequate knowledge on climate drivers of chikungunya outbreaks. We analyze a variety of climate and satellite-derived vegetation measurements to explain the coupling between patterns of climate variability and disease outbreaks of Rift Valley fever and chikungunya.Methods and FindingsWe derived a teleconnections map by correlating long-term monthly global precipitation data with the NINO3.4 sea surface temperature (SST) anomaly index. This map identifies regional hot-spots where rainfall variability may have an influence on the ecology of vector borne disease. Among the regions are Eastern and Southern Africa where outbreaks of chikungunya and Rift Valley fever occurred 2004–2009. Chikungunya and Rift Valley fever case locations were mapped to corresponding climate data anomalies to understand associations between specific anomaly patterns in ecological and climate variables and disease outbreak patterns through space and time. From these maps we explored associations among Rift Valley fever disease occurrence locations and cumulative rainfall and vegetation index anomalies. We illustrated the time lag between the driving climate conditions and the timing of the first case of Rift Valley fever. Results showed that reported outbreaks of Rift Valley fever occurred after ∼3–4 months of sustained above-normal rainfall and associated green-up in vegetation, conditions ideal for Rift Valley fever mosquito vectors. For chikungunya we explored associations among surface air temperature, precipitation anomalies, and chikungunya outbreak locations. We found that chikungunya outbreaks occurred under conditions of anomalously high temperatures and drought over Eastern Africa. However, in Southeast Asia, chikungunya outbreaks were negatively correlated (p<0.05) with drought conditions, but positively correlated with warmer-than-normal temperatures and rainfall.Conclusions/SignificanceExtremes in climate conditions forced by the El Niño/Southern Oscillation (ENSO) lead to severe droughts or floods, ideal ecological conditions for disease vectors to emerge, and may result in epizootics and epidemics of Rift Valley fever and chikungunya. However, the immune status of livestock (Rift Valley fever) and human (chikungunya) populations is a factor that is largely unknown but very likely plays a role in the spatial-temporal patterns of these disease outbreaks. As the frequency and severity of extremes in climate increase, the potential for globalization of vectors and disease is likely to accelerate. Understanding the underlying patterns of global and regional climate variability and their impacts on ecolo...

Long-term studies of hybrid zones can provide valuable insight into a number of questions that have long attracted the attention of evolutionists. These questions range from the stability and fate of hybrid zones to the relative fitness of hybrids. In this paper we report the results of a 14-year survey of the Allonemobius fasciatus-Allonemobius socius hybrid zone. Populations were collected intensively in 1986 and 1987 and then more sporadically through the end of the 1980s and throughout the 1990s. By documenting changes in the genetic composition of populations near and within the zone during this period of time we assessed: the strength of the reproductive isolation between the two species; the relative growth rates (which can be considered a surrogate of relative fitness) of genotype classes corresponding to hybrids and to pure species individuals; and, the power of single-year and multi-year measurements of relative growth rates to predict changes in the genetic composition of mixed populations through time. In brief, we found very large year-to-year variation in the relative growth rates of pure species and hybrid individuals. This variation may reflect the fact that both species are at the edge of their range and perhaps at the limits of their ability to deal with environmental perturbations. As a consequence of the variation, even multi-year estimates of relative growth rates often provided imprecise predictions regarding the future genotypic composition of mixed populations. Despite our limited ability to predict the dynamics of individual populations, some trends are apparent. A. socius, the southern species, has clearly increased in frequency along a transect through the Appalachian Mountains, indicating that the zone is moving north in this region. In contrast, the zone appeared to be more stable along the East Coast transect. Within mixed populations, character-index profiles are often bimodal and stable through time, indicating relatively strong reproductive isolation between the two species that is not being reinforced, nor is it breaking down.

Interannual climate variability patterns associated with the El Niño-Southern Oscillation phenomenon result in climate and environmental anomaly conditions in specific regions worldwide that directly favor outbreaks and/or amplification of variety of diseases of public health concern including chikungunya, hantavirus, Rift Valley fever, cholera, plague, and Zika. We analyzed patterns of some disease outbreaks during the strong 2015–2016 El Niño event in relation to climate anomalies derived from satellite measurements. Disease outbreaks in multiple El Niño-connected regions worldwide (including Southeast Asia, Tanzania, western US, and Brazil) followed shifts in rainfall, temperature, and vegetation in which both drought and flooding occurred in excess (14–81% precipitation departures from normal). These shifts favored ecological conditions appropriate for pathogens and their vectors to emerge and propagate clusters of diseases activity in these regions. Our analysis indicates that intensity of disease activity in some ENSO-teleconnected regions were approximately 2.5–28% higher during years with El Niño events than those without. Plague in Colorado and New Mexico as well as cholera in Tanzania were significantly associated with above normal rainfall (p < 0.05); while dengue in Brazil and southeast Asia were significantly associated with above normal land surface temperature (p < 0.05). Routine and ongoing global satellite monitoring of key climate variable anomalies calibrated to specific regions could identify regions at risk for emergence and propagation of disease vectors. Such information can provide sufficient lead-time for outbreak prevention and potentially reduce the burden and spread of ecologically coupled diseases.

Incipient species groups or young adaptive radiations such as crossbills (Aves: Loxia) present the opportunity to investigate directly the processes occurring during speciation. New World crossbills include white-winged crossbills (Loxia leucoptera), Hispaniolan crossbills (Loxia megaplaga), and red crossbills (Loxia curvirostra complex), the last of which is comprised of at least nine morphologically and vocally differentiated forms ('call types') where divergent natural selection for specialization on different conifer resources has been strongly implicated as driving diversification. Here we use amplified fragment length polymorphism (AFLP) markers to investigate patterns of genetic variation across populations, call types, and species of New World crossbills. Tree-based analyses using 440 AFLP loci reveal strongly supported clustering of the formally recognized species, but did not separate individuals from the eight call types in the red crossbill complex, consistent with recent divergence and ongoing gene flow. Analyses of genetic differentiation based on inferred allele frequency variation however, reveal subtle but significant levels of genetic differentiation among the different call types of the complex and indicate that between call-type differentiation is greater than that found among different geographic locations within call types. Interpreted in light of evidence of divergent natural selection and strong premating reproductive isolation, the observed genetic differentiation suggests restricted gene flow among sympatric call types consistent with the early stages of ecological speciation.

We document significant worldwide weather anomalies that affected agriculture and vector-borne disease outbreaks during the 2010–2012 period. We utilized 2000–2012 vegetation index and land surface temperature data from NASA's satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) to map the magnitude and extent of these anomalies for diverse regions including the continental United States, Russia, East Africa, Southern Africa, and Australia. We demonstrate that shifts in temperature and/or precipitation have significant impacts on vegetation patterns with attendant consequences for agriculture and public health. Weather extremes resulted in excessive rainfall and flooding as well as severe drought, which caused ∼10 to 80% variation in major agricultural commodity production (including wheat, corn, cotton, sorghum) and created exceptional conditions for extensive mosquito-borne disease outbreaks of dengue, Rift Valley fever, Murray Valley encephalitis, and West Nile virus disease. Analysis of MODIS data provided a standardized method for quantifying the extreme weather anomalies observed during this period. Assessments of land surface conditions from satellite-based systems such as MODIS can be a valuable tool in national, regional, and global weather impact determinations.