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1. Researchers in ecology and evolutionary biology are increasingly dependent on computational code to conduct research. Hence, the use of efficient methods to share, reproduce, and collaborate on code as well as document research is fundamental. GitHub is an online, cloud-based service that can help researchers track, organize, discuss, share, and collaborate on software and other materials related to research production, including data, code for analyses, and protocols. Despite these benefits, the use of GitHub in ecology and evolution is not widespread. 2. To help researchers in ecology and evolution adopt useful features from GitHub to improve their research workflows, we review 12 practical ways to use the platform. 3. We outline features ranging from low to high technical difficulty, including storing code, managing projects, coding collaboratively, conducting peer review, writing a manuscript, and using automated and continuous integration to streamline analyses. Given that members of a research team may have different technical skills and responsibilities, we describe how the optimal use of GitHub features may vary among members of a research collaboration. 4. As more ecologists and evolutionary biologists establish their workflows using GitHub, the field can continue to push the boundaries of collaborative, transparent, and open research. collaboration, data management, ecoinformatics, GitHub, open science, project management, reproducible research, version control

Fraser River Pacific salmon have declined in recent decades, possibly from parasitism by sea lice (Caligus clemensi and Lepeophtheirus salmonis). We describe the abundance of both louse species infesting co-migrating juvenile pink (Oncorhynchus gorbuscha), chum (Oncorhynchus keta), and sockeye (Oncorhynchus nerka) salmon over 5 years in the Discovery Islands and Johnstone Strait, British Columbia. The generalist louse, C. clemensi, was 5, 7, and 39 times more abundant than the salmonid specialist, L. salmonis, on pink, chum, and sockeye salmon, respectively. Caligus clemensi abundance was higher on pink salmon (0.45, 95% CI: 0.38–0.55) and sockeye (0.39, 95% CI: 0.33–0.47) than on chum salmon. Lepeophtheirus salmonis abundance was highest on pink salmon (0.09, 95% CI = 0.06–0.15). Caligus clemensi had higher abundances in Johnstone Strait than in the Discovery Islands. These results suggest differences in host specialization and transmission dynamics between louse species. Because both lice infest farmed salmon, but only C. clemensi infests Pacific herring (Clupea pallasii), conservation science and management regarding lice and Fraser River salmon should further consider C. clemensi and transmission from farmed salmon and wild herring.

Trait-based approaches are increasingly recognized as a tool for understanding ecosystem re-assembly and function under intensifying global change. Here we synthesize trait-based research globally (n= 865 studies) to examine the contexts in which traits may be used for global change prediction. We find that exponential growth in the field over the last decade remains dominated by descriptive studies of terrestrial plant morphology, highlighting significant opportunities to expand trait-based thinking across systems and taxa. Very few studies (less than 3%) focus on predicting ecological effects of global change, mostly in the past 5 years and via singular traits that mediate abiotic limits on species distribution. Beyond organism size (the most examined trait), we identify over 2500 other morphological, physiological, behavioural and life-history traits known to mediate environmental filters of species' range and abundance as candidates for future predictive global change work. Though uncommon, spatially explicit process models—which mechanistically link traits to changes in organism distributions and abundance—are among the most promising frameworks for holistic global change prediction at scales relevant for conservation decision-making. Further progress towards trait-based forecasting requires addressing persistent barriers including (1) matching scales of multivariate trait and environment data to focal processes disrupted by global change, and (2) propagating variation in trait and environmental parameters throughout process model functions using simulation.

Anthropogenic debris, namely plastic, is a concern across aquatic ecosystems worldwide, with freshwater systems being understudied relative to marine systems. In this study, we quantified and characterized debris in the diet of double-crested cormorant chicks (Phalacrocorax auritus) from three sites in two of the Laurentian Great Lakes to (i) determine whether or not the diet of double-crested cormorants in the Laurentian Great Lakes includes anthropogenic debris, (ii) characterize the size, shape, and type of debris incorporated, and (iii) examine relationships between the amount of debris ingested and their proximity to industrial–urban centres. Overall, >86% of cormorants in our study had anthropogenic debris (mostly fibers) in their digestive tracts with no correlation between site and the amount of debris ingested. The ingested debris includes microplastics, natural fibres from textiles, and other anthropogenic materials (e.g., glass). To the best of our knowledge, this is one of the first studies to examine anthropogenic debris in a diving bird in the Laurentian Great Lakes and one of few studies investigating this in freshwater birds.

Predation from the invasive Indo-Pacific lionfish is likely to amplify declines in marine fishes observed in multiple ocean basins. As the invasion intensifies and expands, there is an urgent need to identify species that are most at risk for extirpation-and possible extinction-from this added threat. To address this gap and inform conservation plans, we develop and apply a quantitative framework for classifying the relative vulnerability of fishes based on morphological and behavioural traits known to influence susceptibility to lionfish predation (e.g. body shape, water column position and aggregation behaviour), habitat overlap with lionfish, and degree of geographic range restriction. Applying the framework to fishes across the invaded Caribbean Sea and ahead of the invasion front in the southwestern Atlantic revealed the identity of at least 77 fishes with relatively small ranges that are likely to be most affected by lionfish predation. Trait-based vulnerability scores significantly predict the probability of fishes appearing within the diets of lionfish across the invaded region. Spatial richness analyses reveal hotspots of vulnerable species in the Bahamas, Belize and Curacao. Crucially, our framework identifies 29 vulnerable fishes endemic to Brazil, which has not yet been colonized by lionfish. Of these, we suggest reefs around offshore island groups occupied by a dozen highly vulnerable and range-restricted species as priorities for intervention should lionfish spread to the region. Observations of the rate of lionfish spread across the invaded range suggest that an average of 5 years (with a median of nearly 2 years) elapses from first sighting to maximum observed densities. This lag may allow managers to mobilize plans to suppress lionfish ahead of an invasion front in priority locations. Our framework also provides a method for assessing the relative vulnerability of cryptobenthic and/or deep-reef fishes, for which population-monitoring data are limited.

As global change forces species’ ranges and abundances into novel configurations, traits-based approaches could allow predictions of community re-assembly. We present a quantitative review of traits-based research globally to (1) evaluate the extent to which this approach has been applied, and (2) evaluate moving from description and to prediction. We highlight the application of traits-based frameworks to describe ecological patterns; terrestrial plant morphology comprises >30% of the literature alone. But fewer than 3% of studies predict ecological effects of global change, mostly in the past five years. While organism size is the most common trait, we identified 2,430 other morphological, physiological, behavioural, and life history traits that mediate environmental filters of species’ ranges across ecosystems and taxonomy. Global change studies forecast range shifts from a few physiological or life history traits. Though uncommon, spatially-explicit models constructed from correlated multivariate trait assemblages (or ‘syndromes’) offer the best chance of predicting shifts under global change scenarios. Moving the field towards trait-based prediction requires (1) matching the scale of trait measurement to the ecological processes, (2) increasing the resolution of environmental gradients along which traits are measured, (3) moving from single to multivariate traits, and (4) accounting for intraspecific trait variation.