Biologists increasingly rely on computer code to collect and analyze their data, reinforcing the importance of published code for transparency, reproducibility, training, and a basis for further work. Here we conduct a literature review examining temporal trends in code sharing in ecology and evolution publications since 2010, and test for an influence of code sharing on citation rate. We find that there is wide room for improvement in sharing code, as scientists are overwhelmingly (95%) failing to publish their code and that there has been no significant improvement over time. We also determined that there is a significant incentive to share, as we additionally find that code sharing can considerably improve citations, particularly when combined with open-access publication.

Although how rare species persist in communities is a major ecological question, the critical phenotypic dimension of rarity is broadly overlooked. Recent work has shown that evaluating functional distinctiveness, the average trait distance of a species to other species in a community, offers essential insights into biodiversity dynamics, ecosystem functioning, and biological conservation. However, the ecological mechanisms underlying the persistence of functionally distinct species are poorly understood. Here we propose a heterogeneous fitness landscape framework, whereby functional dimensions encompass peaks representing trait combinations that yield positive intrinsic growth rates in a community. We identify four fundamental causes leading to the persistence of functionally distinct species in a community. First, environmental heterogeneity or alternative phenotypic designs can drive positive population growth of functionally distinct species. Second, sink populations with negative growth can deviate from local fitness peaks and be functionally distinct. Third, species found at the margin of the fitness landscape can persist but be functionally distinct. Fourth, biotic interactions (either positive or negative) can dynamically alter the fitness landscape. We offer examples of these four cases and some guidelines to distinguish among them. In addition to these deterministic processes, we also explore how stochastic dispersal limitation can yield functional distinctiveness.

Life history variation in trees is a ubiquitous feature of tropical forests that may facilitate the niche partitioning of light. However, many tests have failed to detect light partitioning by saplings in gaps, which may reflect the stochastic nature of understory light penetration and recruitment. We argue that tree size is a critical component of niche partitioning that is more tightly linked to light availability. To account for size, we use a scaling framework to assess patterns of growth, abundance, mortality, and richness across life histories from >114,000 trees in a primary, neotropical forest. Relative abundance, productivity, and richness shift ~1−2 orders of magnitude with tree size: from shade tolerant, slow trees dominating the understory to parity with rapidly growing fast and long-lived pioneer species in the canopy. Life history tradeoffs promote vertical niche partitioning in tropical forests.

While the impact of biodiversity, notably functional diversity, on ecosystem productivity has been extensively studied, little is known about the effect of individual species. Here, we identified species of high importance for productivity (key species) in over 28,000 diverse grassland communities in the European Alps, and compared their effects with those of community-level measures of functional composition (weighted means, variances, skewness, and kurtosis). After accounting for the environment, the five most important key species jointly explained more deviance than all statistics of functional composition. Key species were generally tall with high specific leaf areas. By dividing the observations according to distinct habitats, the explanatory power of all non-environmental predictors increased considerably, and the relationships between functional composition and productivity varied systematically, presumably because of changing interactions and trade-offs between traits. Our results advocate for a better consideration of species’ individual effects on ecosystem functioning in complement to community-level measures.

Estimating the distribution of phenotypes in populations and communities is central to many questions in ecology and evolutionary biology. These distributions can be characterized by their moments: the mean, variance, skewness, and kurtosis. Typically, these moments are calculated using a community-weighted approach (e.g. community-weighted mean) which ignores intraspecific variation. As an alternative, bootstrapping approaches can incorporate intraspecific variation to improve estimates, and also quantify uncertainty in the estimate. Here, we compare the performance of different approaches for estimating the moments of trait distributions across a variety of sampling scenarios, taxa, and datasets. We introduce the traitstrap R package to facilitate inferences of trait distributions via bootstrapping. Our results suggest that randomly sampling ~9 individuals per sampling unit and species, focusing on covering all species in the community, and analysing the data using nonparametric bootstrapping generally enables reliable inference on trait distributions, including the central moments, of communities.

The COVID-19 crisis has forced researchers in Ecology to change the way we work almost overnight. Nonetheless, the pandemic has provided us with several novel components for a new way of conducting international Science. In this perspective piece, we summarize eight central insights that are helping us, as early career researchers, navigate the uncertainties, fears and challenges of advancing Science during the COVID-19 pandemic. We highlight how innovative, collaborative and often Open Science-driven developments that have arisen from this crisis can form a blueprint for a community reinvention in academia. Our insights include personal approaches to managing our new reality, maintaining capacity to focus and resilience in our projects, and a variety of tools that facilitate remote collaboration. We also highlight how, at a community level, we can take advantage of online communication platforms for gaining accessibility to conferences and meetings, and for maintaining research networks and community engagement while promoting a more diverse and inclusive community. Overall, we are confident that these practices can support a more inclusive and kinder scientific culture for the longer term.