RESUMO
Understanding how the structure of biological systems impacts their resilience (broadly defined) is a recurring question across multiple levels of biological organization. In ecology, considerable effort has been devoted to understanding how the structure of interactions between species in ecological networks is linked to different broad resilience outcomes, especially local stability. Still, nearly all of that work has focused on interaction structure in presence-absence terms, and has not investigated quantitative structure, i.e., the arrangement of interaction strengths in ecological networks. We investigated how the interplay between binary and quantitative structure impacts stability in mutualistic interaction networks (those in which species interactions are mutually beneficial), using community matrix approaches. We additionally examined the effects of network complexity and within-guild competition for context. In terms of structure, we focused on understanding the stability impacts of nestedness, a structure in which more-specialized species interact with smaller subsets of the same species that more-generalized species interact with. Most mutualistic networks in nature display binary nestedness, which is puzzling because both binary and quantitative nestedness are known to be destabilizing on their own. We found that quantitative network structure has important consequences for local stability. In more-complex networks, binary-nested structures were the most stable configurations, depending on the quantitative structures; but which quantitative structure was stabilizing depended on network complexity and competitive context. As complexity increases, and in the absence of within-guild competition, the most stable configurations have a nested binary structure with a complementary (i.e., anti-nested) quantitative structure. In the presence of within-guild competition, however, the most stable networks are those with a nested binary structure and a nested quantitative structure. In other words, the impact of interaction-overlap on community persistence is dependent on the competitive context. These results help to explain the prevalence of binary nested structures in nature and underscore the need for future empirical work on quantitative structure.
RESUMO
Honey bee parasites remain a critical challenge to management and conservation. Because managed honey bees are maintained in colonies kept in apiaries across landscapes, the study of honey bee parasites allows the investigation of spatial principles in parasite ecology and evolution. We used a controlled field experiment to study the relationship between population growth rate and virulence (colony survival) of the parasite Varroa destructor (Anderson and Trueman). We used a nested design of 10 patches (apiaries) of 14 colonies to examine the spatial scale at which Varroa population growth matters for colony survival. We tracked Varroa population size and colony survival across a full year and found that Varroa populations that grow faster in their host colonies during the spring and summer led to larger Varroa populations across the whole apiary (patch) and higher rates of neighboring colony loss. Crucially, this increased colony loss risk manifested at the patch scale, with mortality risk being related to spatial adjacency to colonies with fast-growing Varroa strains rather than with Varroa growth rate in the colony itself. Thus, within-colony population growth predicts whole-apiary virulence, demonstrating the need to consider multiple scales when investigating parasite growth-virulence relationships.