An important issue in population biology is the dynamic interaction between pathogens. Interest has focused mainly on the indirect interaction of pathogen strains, mediated by cross immunity. However, a mechanism has recently been proposed for 'ecological interference' between pathogens through the removal of individuals from the susceptible pool after an acute infection. To explore this possibility, we have analysed and modelled historical measles and whooping cough records. Here we show that ecological interference is particularly strong when fatal infections permanently remove susceptibles. Disease interference has substantial dynamical consequences, making multi-annual outbreaks of different infections characteristically out of phase. So, when disease prevalence is high and is associated with significant mortality, it might be impossible to understand epidemic patterns by studying pathogens in isolation. This new ecological null model has important consequences for understanding the multi-strain dynamics of pathogens such as dengue and echoviruses.
In recent centuries bird species have been deteriorating in status and becoming extinct at a rate that may be 2-3 orders of magnitude higher than in prehuman times. We examined extinction rates of bird species designated critically endangered in 1994 and the rate at which species have moved through the IUCN (World Conservation Union) Red List categories of extinction risk globally for the period 1988-2004 and regionally in Australia from 1750 to 2000. For Australia we drew on historical accounts of the extent and condition of species habitats, spread of invasive species, and changes in sighting frequencies. These data sets permitted comparison of observed rates of movement through the IUCN Red List categories with novel predictions based on the IUCN Red List criterion E, which relates to explicit extinction probabilities determined, for example, by population viability analysis. The comparison also tested whether species listed on the basis of other criteria face a similar probability of moving to a higher threat category as those listed under criterion E. For the rate at which species moved from vulnerable to endangered, there was a good match between observations and predictions, both worldwide and in Australia. Nevertheless, species have become extinct at a rate that, although historically high, is 2 (Australia) to 10 (globally) times lower than predicted. Although the extinction probability associated with the critically endangered category may be too high, the shortfall in realized extinctions can also be attributed to the beneficial impact of conservation intervention. These efforts may have reduced the number of global extinctions from 19 to 3 and substantially slowed the extinction trajectory of 33 additional critically endangered species. Our results suggest that current conservation action benefits species on the brink of extinction, but is less targeted at or has less effect on moderately threatened species.
Seasonal changes in the environment are known to be important drivers of population dynamics, giving rise to sustained population cycles. However, it is often difficult to measure the strength and shape of seasonal forces affecting populations. In recent years, statistical time-series methods have been applied to the incidence records of childhood infectious diseases in an attempt to estimate seasonal variation in transmission rates, as driven by the pattern of school terms. In turn, school-term forcing was used to show how susceptible influx rates affect the interepidemic period. In this paper, we document the response of measles dynamics to distinct shifts in the parameter regime using previously unexplored records of measles mortality from the early decades of the twentieth century. We describe temporal patterns of measles epidemics using spectral analysis techniques, and point out a marked decrease in birth rates over time. Changes in host demography alone do not, however, suffice to explain epidemiological transitions. By fitting the time-series susceptible-infected-recovered model to measles mortality data, we obtain estimates of seasonal transmission in different eras, and find that seasonality increased over time. This analysis supports theoretical work linking complex population dynamics and the balance between stochastic and deterministic forces as determined by the strength of seasonality.
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