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Abstract Genomic methods are becoming increasingly valuable and established in ecological research, particularly in nonmodel species. Supporting their progress and adoption requires investment in resources that promote (i) reproducibility of genomic analyses, (ii) accessibility of learning tools and (iii) keeping pace with rapidly developing methods and principles.We introduce marineomics.io, an open‐source, living document to disseminate tutorials, reproducibility tools and best principles for ecological genomic research in marine and nonmodel systems.The website's existing content spans population and functional genomics, including current recommendations for whole‐genome sequencing, RAD‐seq, Pool‐seq and RNA‐seq. With the goal to facilitate the development of new, similar resources, we describe our process for aggregating and synthesizing methodological principles from the ecological genomics community to inform website content. We also detail steps for authorship and submission of new website content, as well as protocols for providing feedback and topic requests from the community.These web resources were constructed with guidance for doing rigorous, reproducible science. Collaboration and contributions to the website are encouraged from scientists of all skill sets and levels of expertise. 

Abstract Understanding the evolutionary consequences of anthropogenic change is imperative for estimating long‐term species resilience. While contemporary genomic data can provide us with important insights into recent demographic histories, investigating past change using present genomic data alone has limitations. In comparison, temporal genomics studies, defined herein as those that incorporate time series genomic data, utilize museum collections and repeated field sampling to directly examine evolutionary change. As temporal genomics is applied to more systems, species and questions, best practices can be helpful guides to make the most efficient use of limited resources. Here, we conduct a systematic literature review to synthesize the effects of temporal genomics methodology on our ability to detect evolutionary changes. We focus on studies investigating recent change within the past 200 years, highlighting evolutionary processes that have occurred during the past two centuries of accelerated anthropogenic pressure. We first identify the most frequently studied taxa, systems, questions and drivers, before highlighting overlooked areas where further temporal genomic studies may be particularly enlightening. Then, we provide guidelines for future study and sample designs while identifying key considerations that may influence statistical and analytical power. Our aim is to provide recommendations to a broad array of researchers interested in using temporal genomics in their work. 

Abstract Genetic diversity within species represents a fundamental yet underappreciated level of biodiversity. Because genetic diversity can indicate species resilience to changing climate, its measurement is relevant to many national and global conservation policy targets. Many studies produce large amounts of genome‐scale genetic diversity data for wild populations, but most (87%) do not include the associated spatial and temporal metadata necessary for them to be reused in monitoring programs or for acknowledging the sovereignty of nations or Indigenous peoples. We undertook a distributed datathon to quantify the availability of these missing metadata and to test the hypothesis that their availability decays with time. We also worked to remediate missing metadata by extracting them from associated published papers, online repositories, and direct communication with authors. Starting with 848 candidate genomic data sets (reduced representation and whole genome) from the International Nucleotide Sequence Database Collaboration, we determined that 561 contained mostly samples from wild populations. We successfully restored spatiotemporal metadata for 78% of these 561 data sets (n = 440 data sets with data on 45,105 individuals from 762 species in 17 phyla). Examining papers and online repositories was much more fruitful than contacting 351 authors, who replied to our email requests 45% of the time. Overall, 23% of our email queries to authors unearthed useful metadata. The probability of retrieving spatiotemporal metadata declined significantly as age of the data set increased. There was a 13.5% yearly decrease in metadata associated with published papers or online repositories and up to a 22% yearly decrease in metadata that were only available from authors. This rapid decay in metadata availability, mirrored in studies of other types of biological data, should motivate swift updates to data‐sharing policies and researcher practices to ensure that the valuable context provided by metadata is not lost to conservation science forever. 

Developing robust professional networks can help shape the trajectories of early career scientists. Yet, historical inequities in science, technology, engineering, and mathematics (STEM) fields make access to these networks highly variable across academic programmes, and senior academics often have little time for mentoring. Here, we illustrate the success of a virtual Laboratory Meeting Programme (LaMP). In this programme, we matched students (mentees) with a more experienced scientist (mentors) from a research group. The mentees then attended the mentors’ laboratory meetings during the academic year with two laboratory meetings specifically dedicated to the mentee’s professional development. Survey results indicate that mentees expanded their knowledge of the hidden curriculum as well as their professional network, while only requiring a few extra hours of their mentor’s time over eight months. In addition, host laboratories benefitted from mentees sharing new perspectives and knowledge in laboratory meetings. Diversity of the mentees was significantly higher than the mentors, suggesting that the programme increased the participation of traditionally under-represented groups. Finally, we found that providing a stipend was very important to many mentees. We conclude that virtual LaMPs can be an inclusive and cost-effective way to foster trainee development and increase diversity within STEM fields with little additional time commitment. 

Although the concept of connectivity is ubiquitous in ecology and evolution, its definition is often inconsistent, particularly in interdisciplinary research. In an ecological context, population connectivity refers to the movement of individuals or species across a landscape. It is measured by locating organisms and tracking their occurrence across space and time. In an evolutionary context, connectivity is typically used to describe levels of current and past gene flow, calculated from the degree of genetic similarity between populations. Both connectivity definitions are useful in their specific contexts, but rarely are these two perspectives combined. Different definitions of connectivity could result in misunderstandings across subdisciplines. Here, we unite ecological and evolutionary perspectives into a single unifying framework by advocating for connectivity to be conceptualized as a generational continuum. Within this framework, connectivity can be subdivided into three timescales: (1) within a generation (e.g., movement), (2) across one parent-offspring generation (e.g., dispersal), and (3) across two or more generations (e.g., gene flow), with each timescale determining the relevant context and dictating whether the connectivity has ecological or evolutionary consequences. Applying our framework to real-world connectivity questions can help to identify sampling limitations associated with a particular methodology, further develop research questions and hypotheses, and investigate eco-evolutionary feedback interactions that span the connectivity continuum. We hope this framework will serve as a foundation for conducting and communicating research across subdisciplines, resulting in a more holistic understanding of connectivity in natural systems. 

Complex life cycles, in which discrete life stages of the same organism differ in form or function and often occupy different ecological niches, are common in nature. Because stages share the same genome, selective effects on one stage may have cascading consequences through the entire life cycle. Theoretical and empirical studies have not yet generated clear predictions about how life cycle complexity will influence patterns of adaptation in response to rapidly changing environments or tested theoretical predictions for fitness trade-offs (or lack thereof) across life stages. We discuss complex life cycle evolution and outline three hypotheses—ontogenetic decoupling, antagonistic ontogenetic pleiotropy and synergistic ontogenetic pleiotropy—for how selection may operate on organisms with complex life cycles. We suggest a within-generation experimental design that promises significant insight into composite selection across life cycle stages. As part of this design, we conducted simulations to determine the power needed to detect selection across a life cycle using a population genetic framework. This analysis demonstrated that recently published studies reporting within-generation selection were underpowered to detect small allele frequency changes (approx. 0.1). The power analysis indicates challenging but attainable sampling requirements for many systems, though plants and marine invertebrates with high fecundity are excellent systems for exploring how organisms with complex life cycles may adapt to climate change.