RESUMO

Individuals can experience accentuated disputes for resources when living with many conspecifics, even in situations in which cooperative behaviors assure benefits associated with an increase in the frequency of food acquisition and in diet breadth. Thus, intraspecific competition may exert a significant selective pressure on social animals. Theoretical models suggest that females of social species could improve their fitness by producing relatively large offspring, since body size can provide competitive advantages during foraging activities. As female reserves are limited, the production of large offspring would occur at the expense of their number. Using five Anelosimus (Araneae, Theridiidae) species, we assessed whether the social ones produce fewer and larger eggs than the subsocials. In addition, we tested the effect of female size on the adoption of each particular reproductive strategy. Small females could hypothetically invest in producing large offspring since they cannot produce as many offspring as large females. Our results suggested that, indeed, sociality influences reproductive strategies. Females of social species produced fewer and larger offspring than females of subsocial species. Subsociality, in turn, would benefit the production of many small spiderlings, possibly because a large number of siblings is important to maintain and expand new webs and to subdue prey during their initial instars. Our results also indicated that large females produce more eggs without necessarily reduce their sizes. We discussed how the costs and benefits of group living may influence reproductive strategies.

Assuntos

RESUMO

Adequate waste management is vital for the success of social life, because waste accumulation increases sanitary risks in dense societies. We explored why different leaf-cutting ants (LCA) species locate their waste in internal nest chambers or external piles, including ecological context and accounting for phylogenetic relations. We propose that waste location depends on whether the environmental conditions enhance or reduce the risk of infection. We obtained the geographical range, habitat and refuse location of LCA from published literature, and experimentally determined whether pathogens on ant waste survived to the high soil temperatures typical of xeric habitats. The habitat of the LCA determined waste location after phylogenetic correction: species with external waste piles mainly occur in xeric environments, whereas those with internal waste chambers mainly inhabit more humid habitats. The ancestral reconstruction suggests that dumping waste externally is less derived than digging waste nest chambers. Empirical results showed that high soil surface temperatures reduce pathogen prevalence from LCA waste. We proposed that LCA living in environments unfavourable for pathogens (i.e. xeric habitats) avoid digging costs by dumping the refuse above ground. Conversely, in environments suitable for pathogens, LCA species prevent the spread of diseases by storing waste underground, presumably, a behaviour that contributed to the colonization of humid habitats. These results highlight the adaptation of organisms to the hygienic challenges of social living, and illustrate how sanitary behaviours can result from a combination of evolutionary history and current environmental conditions.

Assuntos

RESUMO

Social network analysis provides a useful lens through which to view the structure of animal societies, and as a result its use is increasingly widespread. One challenge that many studies of animal social networks face is dealing with limited sample sizes, which introduces the potential for a high level of uncertainty in estimating the rates of association or interaction between individuals. We present a method based on Bayesian inference to incorporate uncertainty into network analyses. We test the reliability of this method at capturing both local and global properties of simulated networks, and compare it to a recently suggested method based on bootstrapping. Our results suggest that Bayesian inference can provide useful information about the underlying certainty in an observed network. When networks are well sampled, observed networks approach the real underlying social structure. However, when sampling is sparse, Bayesian inferred networks can provide realistic uncertainty estimates around edge weights. We also suggest a potential method for estimating the reliability of an observed network given the amount of sampling performed. This paper highlights how relatively simple procedures can be used to estimate uncertainty and reliability in studies using animal social network analysis.

RESUMO

Both social and ecological factors influence population process and structure, with resultant consequences for phenotypic selection on individuals. Understanding the scale and relative contribution of these two factors is thus a central aim in evolutionary ecology. In this study, we develop a framework using null models to identify the social and spatial patterns that contribute to phenotypic structure in a wild population of songbirds. We used automated technologies to track 1053 individuals that formed 73 737 groups from which we inferred a social network. Our framework identified that both social and spatial drivers contributed to assortment in the network. In particular, groups had a more even sex ratio than expected and exhibited a consistent age structure that suggested local association preferences, such as preferential attachment or avoidance. By contrast, recent immigrants were spatially partitioned from locally born individuals, suggesting differential dispersal strategies by phenotype. Our results highlight how different scales of social decision-making, ranging from post-natal dispersal settlement to fission-fusion dynamics, can interact to drive phenotypic structure in animal populations.