The effect of sociality on competitive interactions among birds.

Sociality can provide many benefits, including increased foraging success, reproductive opportunities and defence against predation. How does sociality influence the dominance hierarchies of ecological competitors? Here, we address this question using a large citizen science dataset of competitive interactions among birds foraging at backyard feeders, representing a network of over 55 000 interactions among 68 common species. We first show that species differ in average group size (the number of conspecifics observed together) as a fundamental measure of sociality. When analysing heterospecific competition, we find that sociality is inversely related to dominance. On average, a single individual from a solitary species is more likely to displace a size-matched opponent than a single individual from a social species. Yet, we find that social species gain an increase in their competitive advantage when in the presence of their conspecifics, which may occur as a result of dynamics within their groups. Finally, we show that more social species have relatively fewer dominance interactions with heterospecifics, and more with conspecifics. Overall, these results demonstrate that sociality can influence competition in ecological networks. More social species have decreased competitive ability as individuals, but they may gain competitive ability in groups.

No evidence that mandatory open data policies increase error correction.

Using a database of open data policies for 199 journals in ecology and evolution, we found no detectable link between data sharing requirements and article retractions or corrections. Despite the potential for open data to facilitate error detection, poorly archived datasets, the absence of open code and the stigma associated with correcting or retracting articles probably stymie error correction. Requiring code alongside data and destigmatizing error correction among authors and journal editors could increase the effectiveness of open data policies at helping science self-correct.

Slow improvement to the archiving quality of open datasets shared by researchers in ecology and evolution.

Many leading journals in ecology and evolution now mandate open data upon publication. Yet, there is very little oversight to ensure the completeness and reusability of archived datasets, and we currently have a poor understanding of the factors associated with high-quality data sharing. We assessed 362 open datasets linked to first- or senior-authored papers published by 100 principal investigators (PIs) in the fields of ecology and evolution over a period of 7 years to identify predictors of data completeness and reusability (data archiving quality). Datasets scored low on these metrics: 56.4% were complete and 45.9% were reusable. Data reusability, but not completeness, was slightly higher for more recently archived datasets and PIs with less seniority. Journal open data policy, PI gender and PI corresponding author status were unrelated to data archiving quality. However, PI identity explained a large proportion of the variance in data completeness (27.8%) and reusability (22.0%), indicating consistent inter-individual differences in data sharing practices by PIs across time and contexts. Several PIs consistently shared data of either high or low archiving quality, but most PIs were inconsistent in how well they shared. One explanation for the high intra-individual variation we observed is that PIs often conduct research through students and postdoctoral researchers, who may be responsible for the data collection, curation and archiving. Levels of data literacy vary among trainees and PIs may not regularly perform quality control over archived files. Our findings suggest that research data management training and culture within a PI's group are likely to be more important determinants of data archiving quality than other factors such as a journal's open data policy. Greater incentives and training for individual researchers at all career stages could improve data sharing practices and enhance data transparency and reusability.

Performance trade-offs in wild mice.

Various aspects of performance (e.g., speed, strength, endurance) are thought to be important determinants of the success of animals in natural activities such as foraging, mating, and escaping from predators. However, it is generally known that morphological properties enhancing one type of performance (e.g., strength) can lead to a reduction in another (e.g., speed). Such performance trade-offs have been quantified at the inter-specific level, but evidence at the individual level remains equivocal. To test for the presence of a performance trade-off, we repeatedly captured a total of 189 wild white-footed mice (Peromyscus leucopus) and measured their grip strength and sprint speed. Using the maximum performance score obtained for each individual across all their repeated tests, we obtained a counter-intuitive (and biased) positive and highly significant phenotypic correlation. Using a bivariate mixed model, we detected a significant negative among-individual correlation between grip strength and sprint speed. By contrast, the within-individual correlation was positive but non-significant, thus illustrating the importance of properly partitioning the correlations at the among- and within-individual levels when testing for the presence of a performance trade-off. This study is one of the first to detect a performance trade-off at the among-individual level in a wild animal population. Such a trade-off may be caused by individual differences in muscle physiology and scapular morphology resulting from genetic differences and/or plastic responses to differential use of the arboreal vs. terrestrial parts of the environment.