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The relationship between traditional metrics of research impact (e.g., number of citations) and alternative metrics (altmetrics) such as Twitter activity are of great interest, but remain imprecisely quantified. We used generalized linear mixed modeling to estimate the relative effects of Twitter activity, journal impact factor, and time since publication on Web of Science citation rates of 1,599 primary research articles from 20 ecology journals published from 2012-2014. We found a strong positive relationship between Twitter activity (i.e., the number of unique tweets about an article) and number of citations. Twitter activity was a more important predictor of citation rates than 5-year journal impact factor. Moreover, Twitter activity was not driven by journal impact factor; the 'highest-impact' journals were not necessarily the most discussed online. The effect of Twitter activity was only about a fifth as strong as time since publication; accounting for this confounding factor was critical for estimating the true effects of Twitter use. Articles in impactful journals can become heavily cited, but articles in journals with lower impact factors can generate considerable Twitter activity and also become heavily cited. Authors may benefit from establishing a strong social media presence, but should not expect research to become highly cited solely through social media promotion. Our research demonstrates that altmetrics and traditional metrics can be closely related, but not identical. We suggest that both altmetrics and traditional citation rates can be useful metrics of research impact.

Recreational angling in the United States (US) is largely a personal hobby that scales up to a multibillion-dollar economic activity. Given dramatic changes to personal decisions and behaviors resulting from the COVID-19 pandemic, we surveyed recreational anglers across the US to understand how the pandemic may have affected their fishing motivations and subsequent activities. Nearly a quarter million anglers from 10 US states were invited to participate in the survey, and almost 18,000 responded. Anglers reported numerous effects of the pandemic, including fishing access restrictions. Despite these barriers, we found that the amount of fishing in the spring of 2020 was significantly greater—by about 0.2 trips per angler—than in non-pandemic springs. Increased fishing is likely associated with our result that most respondents considered recreational angling to be a COVID-19 safe activity. Nearly a third of anglers reported changing their motivation for fishing during the pandemic, with stress relief being more popular during the pandemic than before. Driven partly by the perceived safety of s ocial fishtancing , recreational angling remained a popular activity for many US anglers during spring 2020.

Multiple comparisons tests (MCTs) include the statistical tests used to compare groups (treatments) often following a significant effect reported in one of many types of linear models. Due to a variety of data and statistical considerations, several dozen MCTs have been developed over the decades, with tests ranging from very similar to each other to very different from each other. Many scientific disciplines use MCTs, including >40,000 reports of their use in ecological journals in the last 60 years. Despite the ubiquity and utility of MCTs, several issues remain in terms of their correct use and reporting. In this study, we evaluated 17 different MCTs. We first reviewed the published literature for recommendations on their correct use. Second, we created a simulation that evaluated the performance of nine common MCTs. The tests examined in the simulation were those that often overlapped in usage, meaning the selection of the test based on fit to the data is not unique and that the simulations could inform the selection of one or more tests when a researcher has choices. Based on the literature review and recommendations: planned comparisons are overwhelmingly recommended over unplanned comparisons, for planned non-parametric comparisons the Mann-Whitney-Wilcoxon U test is recommended, Scheffé’s S test is recommended for any linear combination of (unplanned) means, Tukey’s HSD and the Bonferroni or the Dunn-Sidak tests are recommended for pairwise comparisons of groups, and that many other tests exist for particular types of data. All code and data used to generate this paper are available at: https://github.com/stevemidway/MultipleComparisons .

Recreational angling is a very popular outdoor activity that is weather-dependent, although investigations of this relationship are rare. This study used weekly fishing effort (2015–2021) estimates throughout coastal Louisiana to understand how effort changed in response to weather conditions. Although we found evidence for some effect of all the weather variables, temperature reported the greatest number of monthly effects, along with an overall declining effect throughout the year. We also examined how tropical storms and hurricanes reduce fishing effort, but that effort recovers rapidly after the storm. Finally, we examined fishing effort during the first year of the pandemic (2020) compared to previous years and found some monthly increases exceeding 100% of normal effort. Understanding angler motivations remains an important part of fishery management, and in a future with changes to weather, hurricanes, and global health crises, we can now know more about how environmental factors change angling effort.

Shark attacks are a global phenomenon that attracts widespread attention and publicity, often with negative outcomes for shark populations. Despite the widespread perceptions of shark attacks, trends in human water activities and shark populations are both dynamic, resulting in variable rates of shark attacks over space and time. Understanding variable trends in shark attacks may contribute to a better understanding of risk, and a more tempered response in the wake of an attack. We found that global shark attack rates are low, yet variable across global regions and over decades. Countries with low populations were found to have the highest rates of attack, while countries with high populations (U.S.A., Australia, South Africa) tended to have overall low attack rates, but also much more interannual variability. From the 1960s to the present, those countries with the highest populations also tended to be the places where attack rates have increased. Ultimately, shark attack risk is also driven by local conditions (e.g., time of day, species present); however, a global scale understanding of attack rates helps place risk into perspective and may contribute to a more scientifically-grounded discussion of sharks, and their management and conservation.

Growth models estimate life history parameters (e.g., growth rates and asymptotic size) that are used in the management of fisheries stocks. Traditionally in fisheries science, it was common to fit one growth model—the von Bertalanffy growth model—to size-at-age data. However, in recent years, fisheries science has seen an increase in the number of growth models available and the evaluation of multiple growth models for a given species or study. We reviewed n = 196 peer-reviewed age and growth studies and n = 50 NOAA (National Oceanic and Atmospheric Administration) regional stock assessments to examine trends in the use of growth models and model selection in fisheries over time. Our results indicate that the total number of age and growth studies increased annually since 1988 with a slight proportional increase in the use of multi-model frameworks. Information theoretic approaches are replacing goodness-of-fit and a priori model selection in fisheries studies; however, this trend is not reflected in NOAA stock assessments, which almost exclusively rely on the von Bertalanffy growth model. Covariates such as system (e.g., marine or fresh), location of study, diet, family, maximum age, and range of age data used in model fitting did not contribute to which model was ultimately the best fitting, suggesting that there are no large-scale patterns of specific growth models being applied to species with common life histories or other attributes. Given the importance and ubiquity of growth modeling to fisheries science, a historical and contemporary understanding of the practice is critical to evaluate improvements that have been made and future challenges.

Establishment of nonnative fishes and extirpations of native fishes have homogenized freshwater fish faunas, yet our understanding of the drivers of this process remain limited. We addressed this knowledge gap by testing three hypotheses about introductions and homogenization of fish communities is the eastern United States: First, whether nonnative fish introductions have caused fish faunas to become homogenized or differentiated; second, whether patterns of faunal change are related to native species richness, propagule pressure, and anthropogenic disturbance; third, whether invasion patterns are attributable to either biotic resistance or preadaptation. We compared taxonomic similarity among watersheds in historical and contemporary time steps, and modeled contributions of different drivers to faunal change within watersheds. Average similarity among watersheds nearly doubled in contemporary times, pointing to substantial fish faunal homogenization. No watersheds lost species; patterns of homogenization are attributable entirely to nonnative species invasion. Community change and nonnative richness were positively associated with agriculture-urban land use, recreational fishing demand, and elevation. Native richness negatively affected community change and nonnative richness. Nonnative species originated from watersheds with higher richness than the ones they invaded, suggesting a role for biotic resistance. Understanding how mechanisms operate across spatial scales will help guide future conservation efforts.

Aim: We sought to identify direct and indirect effects of factors contributing to establishment and spread of 272 stream fish species. Location: Two hundred and ninety-seven watersheds in the eastern United States. Methods: We modelled two variables: (1) whether a species had become established outside its native range (establishment) and (2) the number of watersheds in which species established outside their native range (spread). We estimated these variables by comparing historical distributions to a rich data set of contemporary sampling. We calculated metrics of human use (indexing propagule pressure), and gathered species trait data from an open-access database. We then used piecewise path analysis to estimate direct and indirect effects of human use, native range size and species traits on the two metrics of species introductions. Results: We identified a hierarchical causal structure in which native range size and fishing pressure were important direct determinants of introductions. Species traits had some direct effects, but played a more indirect role. Native range size was significantly affected by thermal tolerance and diet breadth. Likewise, fishing pressure was significantly affected by life history strategy: larger-bodied, longer-living and more fecund species were positively associated with fishing pressure. Main conclusions: Functional traits can confer an advantage to some species during the establishment phase, but human use is important for subsequent dispersal throughout the non-native range. However, human use is non-random, and is largely a function of species traits. Considering both direct and indirect effects of traits across stages of the invasion process can help to elucidate the full role of traits in species invasions.

This study examines the misuse of normality tests in linear regression within ecology and biology, focusing on common misconceptions. A bibliometric review found that over 70% of ecology papers and 90% of biology papers incorrectly applied normality tests to raw data instead of model residuals. To assess the impact of this error, we simulated datasets with normal, interval, and skewed distributions across various sample and effect sizes. We compared statistical power between two approaches: testing the whole dataset for normality (incorrect) versus testing model residuals (correct) to determine whether to use a parametric ( t -test) or nonparametric (Mann-Whitney U test) method. Our results showed minimal differences in statistical power between the approaches, even when normality was incorrectly tested on raw data. However, when residuals violated the normality assumption, using the Mann-Whitney U test increased statistical power by 3–4%. Overall, the study suggests that, while correctly testing residuals for normality enhances model performance, the impact of testing raw data is negligible in terms of power loss, especially with large sample sizes. The findings highlight the need for more awareness of proper statistical practices, especially in evaluating the assumptions of linear models.

The global COVID-19 pandemic resulted in many jurisdictions implementing orders restricting the movements of people to inhibit virus transmission, with recreational angling often either not permitted or access to fisheries and/or related infrastructure being prevented. Following the lifting of restrictions, initial angler surveys and licence sales suggested increased participation and effort, and altered angler demographics, but with evidence remaining limited. Here, we overcome this evidence gap by identifying temporal changes in angling interest, licence sales, and angling effort in world regions by comparing data in the ‘pre-pandemic’ (up to and including 2019); ‘acute pandemic’ (2020) and ‘COVID-acclimated’ (2021) periods. We then identified how changes can inform the development of more resilient and sustainable recreational fisheries. Interest in angling (measured here as angling-related internet search term volumes) increased substantially in all regions during 2020. Patterns in licence sales revealed marked increases in some countries during 2020 but not in others. Where licence sales increased, this was rarely sustained in 2021; where there were declines, these related to fewer tourist anglers due to movement restrictions. Data from most countries indicated a younger demographic of people who participated in angling in 2020, including in urban areas, but this was not sustained in 2021. These short-lived changes in recreational angling indicate efforts to retain younger anglers could increase overall participation levels, where efforts can target education in appropriate angling practices and create more urban angling opportunities. These efforts would then provide recreational fisheries with greater resilience to cope with future global crises, including facilitating the ability of people to access angling opportunities during periods of high societal stress.