The frequency and type of dyadic social interactions individuals partake in has important fitness consequences. Social network analysis is an effective tool to quantify the complexity and consequences of these behaviors on the individual level. Less work has used social networks to quantify the social structure—specific attributes of the pattern of all social interactions in a network—of animal social groups, and its fitness consequences for those individuals who comprise the group. We studied the association between social structure, quantified via five network measures, and annual reproductive success in wild, free-living female yellow-bellied marmots (Marmota flaviventer). We quantified reproductive success in two ways: (1) if an individual successfully weaned a litter and (2) how many pups were weaned. Networks were constructed from 38 968 interactions between 726 unique individuals in 137 social groups across 19 years. Using generalized linear mixed models, we found largely no relationship between either measure of reproductive success and social structure. We found a modest relationship that females residing in more fragmentable social groups (i.e., groups breakable into two or more separate groups of two or more individuals) weaned larger litters. Prior work showed that yellow-bellied marmots residing in more fragmentable groups gained body mass faster—another important fitness correlate. Interestingly, we found no strong relationships between other attributes of social group structure, suggesting that in this facultatively social mammal, the position of individuals within their group, the individual social phenotype, may be more important for fitness than the emergent group social phenotype.

Mass gain is an important fitness correlate for survival in highly seasonal species. Although many physiological, genetic, life history, and environmental factors can influence mass gain, more recent work suggests the specific nature of an individual’s own social relationships also influences mass gain. However, less is known about consequences of social structure for individuals. We studied the association between social structure, quantified via social network analysis, and annual mass gain in yellow-bellied marmots (Marmota flaviventer). Social networks were constructed from 31 738 social interactions between 671 individuals in 125 social groups from 2002 to 2018. Using a refined dataset of 1022 observations across 587 individuals in 81 social groups, we fitted linear mixed models to analyze the relationship between attributes of social structure and individual mass gain. We found that individuals residing in more connected and unbreakable social groups tended to gain proportionally less mass. However, these results were largely age-dependent. Adults, who form the core of marmot social groups, residing in more spread apart networks had greater mass gain than those in tighter networks. Yearlings, involved in a majority of social interactions, and those who resided in socially homogeneous and stable groups had greater mass gain. These results show how the structure of the social group an individual resides in may have consequences for a key fitness correlate. But, importantly, this relationship was age-dependent.

A small number of extraordinary “Major Evolutionary Transitions” (METs) have attracted attention among biologists. They comprise novel forms of individuality and information, and are defined in relation to organismal complexity, irrespective of broader ecosystem-level effects. This divorce between evolutionary and ecological consequences qualifies unicellular eukaryotes, for example, as a MET although they alone failed to significantly alter ecosystems. Additionally, this definition excludes revolutionary innovations not fitting into either MET type (e.g., photosynthesis). We recombine evolution with ecology to explore how and why entire ecosystems were newly created or radically altered – as Major System Transitions (MSTs). In doing so, we highlight important morphological adaptations that spread through populations because of their immediate, direct-fitness advantages for individuals. These are Major Competitive Transitions, or MCTs. We argue that often multiple METs and MCTs must be present to produce MSTs. For example, sexually-reproducing, multicellular eukaryotes (METs) with anisogamy and exoskeletons (MCTs) significantly altered ecosystems during the Cambrian. Therefore, we introduce the concepts of Facilitating Evolutionary Transitions (FETs) and Catalysts as key events or agents that are insufficient themselves to set a MST into motion, but are essential parts of synergies that do. We further elucidate the role of information in MSTs as transitions across five levels: (I) Encoded; (II) Epigenomic; (III) Learned; (IV) Inscribed; and (V) Dark Information. The latter is ‘authored’ by abiotic entities rather than biological organisms. Level IV has arguably allowed humans to produce a MST, and V perhaps makes us a FET for a future transition that melds biotic and abiotic life into one entity. Understanding the interactive processes involved in past major transitions will illuminate both current events and the surprising possibilities that abiotically-created information may produce.

For social animals, group social structure has important consequences for disease and information spread. While prior studies showed individual connectedness within a group has fitness consequences, less is known about the fitness consequences of group social structure for the individuals who comprise the group. Using a long-term dataset on a wild population of facultatively social yellow-bellied marmots ( Marmota flaviventer ), we showed social structure had largely no relationship with survival, suggesting consequences of individual social phenotypes may not scale to the group social phenotype. An observed relationship for winter survival suggests a potentially contrasting direction of selection between the group and previous research on the individual level; less social individuals, but individuals in more social groups experience greater winter survival. This work provides valuable insights into evolutionary implications across social phenotypic scales.

Field studies seeking to identify interactions between the environment and behaviors of wild songbirds are often restricted by time, labor, and accessibility of the site; hampering the collection of long‐term, high‐resolution data. Here, we describe the development, utilization, and initial results of a long‐term field study of wild songbird feeding patterns using data collected through an inexpensive microcomputer‐controlled automated feeder. Our studies indicate the “smart feeder” is capable of reliable and accurate data collection on feeding and behavioral metrics over long durations with relation to a wide range of environmental conditions. This enables detailed analysis of songbird's environment–behavior interactions. Our results have identified trends in environment–behavior interactions, microhabitat variations, species‐specific feeding profiles, and differences in the frequency and involvement of displacement events. Computerized feeders enabled us to address environment–behavior interactions, resulting in more detailed data than traditional observational methods. This reinforces conclusions from previous work regarding the potential for automated data collection to be adapted for a wide variety of research studies across the field of ethology.