The evolution of cooperation is a fundamental problem in biology, especially for non-relatives, where indirect fitness benefits cannot counter within-group inequalities. Multilevel selection models show how cooperation can evolve if it generates a group-level advantage, even when cooperators are disadvantaged within their group. This allows the possibility of group selection, but few examples have been described in nature. Here we show that group selection can explain the evolution of cooperative nest founding in the harvester ant Pogonomyrmex californicus. Through most of this species’ range, colonies are founded by single queens, but in some populations nests are instead founded by cooperative groups of unrelated queens. In mixed groups of cooperative and single-founding queens, we found that aggressive individuals had a survival advantage within their nest, but foundress groups with such non-cooperators died out more often than those with only cooperative members. An agent-based model shows that the between-group advantage of the cooperative phenotype drives it to fixation, despite its within-group disadvantage, but only when population density is high enough to make between-group competition intense. Field data show higher nest density in a population where cooperative founding is common, consistent with greater density driving the evolution of cooperative foundation through group selection.
Olfactory discrimination tasks can provide useful information about how olfaction may have evolved by demonstrating which types of compounds animals will detect and respond to. Ants discriminate between nestmates and non-nestmates by using olfaction to detect the cuticular hydrocarbons on other ants, and Camponotus floridanus have particularly clear and aggressive responses to non-nestmates. A new method of adding hydrocarbons to ants, the “Snow Globe” method was further optimized and tested on C. floridanus. It involves adding hydrocarbons and a solvent to a vial of water, vortexing it, suspending hydrocarbon droplets throughout the solution, and then dipping a narcotized ant in. It is hoped this method can evenly coat ants in hydrocarbon. Ants were treated with heptacosane (C27), nonacosane (C29), hentriacontane (C31), a mixture of C27/C29/C31, 2-methyltriacontane (2MeC30), S-3-methylhentriacontane (SMeC31), and R-3-methylhentriacontane (RMeC31). These were chosen to see how ants reacted in a nestmate recognition context to methyl-branched hydrocarbons, R and S enantiomers, and to multiple added alkanes. Behavior assays were performed on treated ants, as well as two untreated controls, a foreign ant and a nestmate ant. There were 15 replicates of each condition, using 15 different queenright colonies. The Snow Globe method successfully transfers hydrocarbons, as confirmed by solid phase microextraction (SPME) done on treated ants, and the behavior assay data shows the foreign control, SMeC31, and the mixture of C27/29/31 were all statistically significant in their differences from the native control. The multiple alkane mixture received a significant response while single alkanes did not, which supports the idea that larger variations in hydrocarbon profile are needed for an ant to be perceived as foreign. The response to SMeC31 shows C. floridanus can respond during nestmate recognition to hydrocarbons that are not naturally occurring, and it indicates the nestmate recognition process may simply be responding to any compounds not found in the colony profile and rather than detecting particular foreign compounds.
In the weeks following the first imported case of Ebola in the U. S. on September 29, 2014, coverage of the very limited outbreak dominated the news media, in a manner quite disproportionate to the actual threat to national public health; by the end of October, 2014, there were only four laboratory confirmed cases of Ebola in the entire nation. Public interest in these events was high, as reflected in the millions of Ebola-related Internet searches and tweets performed in the month following the first confirmed case. Use of trending Internet searches and tweets has been proposed in the past for real-time prediction of outbreaks (a field referred to as “digital epidemiology”), but accounting for the biases of public panic has been problematic. In the case of the limited U. S. Ebola outbreak, we know that the Ebola-related searches and tweets originating the U. S. during the outbreak were due only to public interest or panic, providing an unprecedented means to determine how these dynamics affect such data, and how news media may be driving these trends.
Methodology
We examine daily Ebola-related Internet search and Twitter data in the U. S. during the six week period ending Oct 31, 2014. TV news coverage data were obtained from the daily number of Ebola-related news videos appearing on two major news networks. We fit the parameters of a mathematical contagion model to the data to determine if the news coverage was a significant factor in the temporal patterns in Ebola-related Internet and Twitter data.
Conclusions
We find significant evidence of contagion, with each Ebola-related news video inspiring tens of thousands of Ebola-related tweets and Internet searches. Between 65% to 76% of the variance in all samples is described by the news media contagion model.
Seroepidemiological studies before and after the epidemic wave of H1N1-2009 are useful for estimating population attack rates with a potential to validate early estimates of the reproduction number, R, in modeling studies.
Methodology/Principal Findings
Since the final epidemic size, the proportion of individuals in a population who become infected during an epidemic, is not the result of a binomial sampling process because infection events are not independent of each other, we propose the use of an asymptotic distribution of the final size to compute approximate 95% confidence intervals of the observed final size. This allows the comparison of the observed final sizes against predictions based on the modeling study (R = 1.15, 1.40 and 1.90), which also yields simple formulae for determining sample sizes for future seroepidemiological studies. We examine a total of eleven published seroepidemiological studies of H1N1-2009 that took place after observing the peak incidence in a number of countries. Observed seropositive proportions in six studies appear to be smaller than that predicted from R = 1.40; four of the six studies sampled serum less than one month after the reported peak incidence. The comparison of the observed final sizes against R = 1.15 and 1.90 reveals that all eleven studies appear not to be significantly deviating from the prediction with R = 1.15, but final sizes in nine studies indicate overestimation if the value R = 1.90 is used.
Conclusions
Sample sizes of published seroepidemiological studies were too small to assess the validity of model predictions except when R = 1.90 was used. We recommend the use of the proposed approach in determining the sample size of post-epidemic seroepidemiological studies, calculating the 95% confidence interval of observed final size, and conducting relevant hypothesis testing instead of the use of methods that rely on a binomial proportion.