Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different fields and has found substantial variability among results despite analysts having the same data and research question. Many of these studies have been in the social sciences, but one small “many analyst” study found similar variability in ecology. We expanded the scope of this prior work by implementing a large-scale empirical exploration of the variation in effect sizes and model predictions generated by the analytical decisions of different researchers in ecology and evolutionary biology. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment). The project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects (compatible with our meta-analyses and with all necessary information provided) for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future.

Holospora and related bacteria are a group of obligate Paramecium symbionts. Characteristic features are their infectivity, the presence of two distinct morphotypes, and usually a strict specialization for a single Paramecium species as host and for a nuclear compartment (either somatic or generative nucleus) for reproduction. Holospora caryophila steps out of line, naturally occurring in Paramecium biaurelia and Paramecium caudatum. This study addresses the phylogenetic relationship among H. caryophila and other Holospora species based on 16S rRNA gene sequence comparison analyzing the type strain and seven new macronuclear symbionts. Key aspects of Holospora physiology such as infectivity, symbiosis establishment and host range were determined by comprehensive infection assays. Detailed morphological investigations and sequence-based phylogeny confirmed a high similarity between the type strain of H. caryophila and the novel strains. Surprisingly, they are only distantly related to other Holospora species suggesting that they belong to a new genus within the family Holosporaceae, here described as Preeria caryophila comb. nov. Adding to this phylogenetic distance, we also observed a much broader host range, comprising at least eleven Paramecium species. As these potential host species exhibit substantial differences in frequency of sexual processes, P. caryophila demonstrates which adaptations are crucial for macronuclear symbionts facing regular destruction of their habitat.

Insulin signaling is pivotal in controlling animals’ lifespan and responses to environmental changes and, when altered, it may lead to pathogenic states. Despite its importance and relevance for biomedical research, insulin’s mechanism of action and the full range of its pathophysiological effects remain incompletely understood. Likewise, the evolutionary origin of insulin and its associated signaling components are unclear. Notwithstanding the common view that insulin signaling originated within metazoans, experimental evidence from non-metazoans suggest a more widespread distribution across eukaryotes. Here, we summarize this evidence. Furthermore, we put forward an evolutionary account that reconciles seemingly contradictory results in the literature.

Dietary changes can alter the human microbiome with potential detrimental consequences for health. Given that environment, health, and evolution are interconnected, we ask: Could diet‐driven microbiome perturbations have consequences that extend beyond their immediate impact on human health? We address this question in the context of the urgent health challenges posed by global climate change. Drawing on recent studies, we propose that not only can diet‐driven microbiome changes lead to dysbiosis, they can also shape life‐history traits and fuel human evolution. We posit that dietary shifts prompt mismatched microbiome‐host genetics configurations that modulate human longevity and reproductive success. These mismatches can also induce a heritable intra‐holobiont stress response, which encourages the holobiont to re‐establish equilibrium within the changed nutritional environment. Thus, while mismatches between climate change‐related genetic and epigenetic configurations within the holobiont increase the risk and severity of diseases, they may also affect life‐history traits and facilitate adaptive responses. These propositions form a framework that can help systematize and address climate‐related dietary challenges for policy and health interventions.

Can ecological changes impact somatic genome development? Efforts to resolve this question could reveal a direct link between environmental changes and somatic variability, potentially illuminating our understanding of how variation can surface from a single genotype under stress. Here, we tackle this question by leveraging the biological properties of ciliates. WhenParamecium tetraureliareproduces sexually, its polyploid somatic genome regenerates from the germline genome through a developmental process that involves the removal of thousands of ORF-interrupting sequences known as internal eliminated sequences (IESs). We show that exposure to nonstandard culture temperatures impacts the efficiency of this process of programmed DNA elimination, prompting the emergence of hundreds of incompletely excised IESs in the newly developed somatic genome. These alternative DNA isoforms display a patterned genomic topography, impact gene expression, and might be inherited transgenerationally. On this basis, we conclude that environmentally induced developmental thermoplasticity contributes to genotypic diversification inParamecium.