Learned societies, as professional bodies for scientists, are an integral part of the scientific system. However, their membership fees have the potential to be prohibitive to the most vulnerable members of the scientific community. To shed light on how membership fees are structured, we conducted a survey of 182 international learned societies relevant to researchers in ecology and evolution. We found that 83% of these societies offered fee concessions to students, but only 26% to postdoctoral researchers. An average regular membership fee-US$67.8, student fee-US$27.4 (42.7% of the regular fee) and postdoctoral fee-US$42.7 (52.9%). Other types of individual concessions, such as for emeritus, family or unemployed, were rare (2-20%). Of the surveyed societies, 43% had discounts for members from developing countries (Global South). Such discounts were more common among societies located in high-income countries. Societies with a publicly visible commitment to equity, diversity and inclusion were more likely to offer different types of concessions. Currently, fees may prevent researchers from vulnerable and underprivileged groups from accessing multiple professional benefits offered by learned societies in ecology and evolution. This includes postdoctoral researchers, who should receive more support. We recommend tangible actions towards making learned societies more affordable and accessible.

Who conducts biological research, where they do it and how results are disseminated vary among geographies and identities. Identifying and documenting these forms of bias by research communities is a critical step towards addressing them. We documented perceived and observed biases in movement ecology, a rapidly expanding sub-discipline of biology, which is strongly underpinned by fieldwork and technology use. We surveyed attendees before an international conference to assess a baseline within-discipline perceived bias (uninformed perceived bias). We analysed geographic patterns in Movement Ecology articles, finding discrepancies between the country of the authors' affiliation and study site location, related to national economics. We analysed race-gender identities of USA biology researchers (the closest to our sub-discipline with data available), finding that they differed from national demographics. Finally, we discussed the quantitatively observed bias at the conference, to assess within-discipline perceived bias informed with observational data (informed perceived bias). Although the survey indicated most conference participants as bias-aware, conversations only covered a subset of biases. We discuss potential causes of bias (parachute-science, fieldwork accessibility), solutions and the need to evaluate mitigatory action effectiveness. Undertaking data-driven analysis of bias within sub-disciplines can help identify specific barriers and move towards the inclusion of a greater diversity of participants in the scientific process.

Chemical pollution is one of the fastest-growing agents of global change. Numerous pollutants are known to disrupt animal behavior, alter ecological interactions, and shift evolutionary trajectories. Crucially, both chemical pollutants and individual organisms are nonrandomly distributed throughout the environment. Despite this fact, the current evidence for chemical-induced impacts on wildlife largely stems from tests that restrict organism movement and force homogeneous exposures. While such approaches have provided pivotal ecotoxicological insights, they overlook the dynamic spatiotemporal interactions that shape wildlife-pollution relationships in nature. Indeed, the seemingly simple notion that pollutants and animals move nonrandomly in the environment creates a complex of dynamic interactions, many of which have never been theoretically modeled or experimentally tested. Here, we conceptualize dynamic interactions between spatiotemporal variation in pollutants and organisms and highlight their ecological and evolutionary implications. We propose a three-pronged approach-integrating in silico modeling, laboratory experiments that allow movement, and field-based tracking of free-ranging animals-to bridge the gap between controlled ecotoxicological studies and real-world wildlife exposures. Advances in telemetry, remote sensing, and computational models provide the necessary tools to quantify these interactions, paving the way for a new era of ecotoxicology that accounts for spatiotemporal complexity.

Publishing preprints is quickly becoming commonplace in ecology and evolutionary biology. Preprints can facilitate the rapid sharing of scientific knowledge establishing precedence and enabling feedback from the research community before peer review. Yet, significant barriers to preprint use exist, including language barriers, a lack of understanding about the benefits of preprints and a lack of diversity in the types of research outputs accepted (e.g. reports). Community-driven preprint initiatives can allow a research community to come together to break down these barriers to improve equity and coverage of global knowledge. Here, we explore the first preprints uploaded to EcoEvoRxiv (n = 1216), a community-driven preprint server for ecologists and evolutionary biologists, to characterize preprint use in ecology, evolution and conservation. Our perspective piece highlights some of the unique initiatives that EcoEvoRxiv has taken to break down barriers to scientific publishing by exploring the composition of articles, how gender and career stage influence preprint use, whether preprints are associated with greater open science practices (e.g. code and data sharing) and tracking preprint publication outcomes. Our analysis identifies areas that we still need to improve upon but highlights how community-driven initiatives, such as EcoEvoRxiv, can play a crucial role in shaping publishing practices in biology.

Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different fields and has found substantial variability among results despite analysts having the same data and research question. Many of these studies have been in the social sciences, but one small “many analyst” study found similar variability in ecology. We expanded the scope of this prior work by implementing a large-scale empirical exploration of the variation in effect sizes and model predictions generated by the analytical decisions of different researchers in ecology and evolutionary biology. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment). The project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects (compatible with our meta-analyses and with all necessary information provided) for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future.

Anthropogenic noise is a global pollutant but its potential impacts on early life-stages in fishes are largely unknown. Here, using controlled laboratory experiments, we tested for impacts of continuous or intermittent exposure to low-frequency broadband noise on early life-stages of the common goby (Pomatoschistus microps), a marine fish with exclusive paternal care. Neither continuous nor intermittent noise exposure had an effect on filial cannibalism, showing that males were capable and willing to care for their broods. However, broods reared in continuous noise covered a smaller area and contained fewer eggs than control broods. Moreover, although developmental rate was the same in all treatments, larvae reared by males in continuous noise had, on average, a smaller yolk sac at hatching than those reared in the intermittent noise and control treatments, while larvae body length did not differ. Thus, it appears that the increased consumption of the yolk sac reserve was not utilised for increased growth. This suggests that exposure to noise in early life-stages affects fitness-related traits of surviving offspring, given the crucial importance of the yolk sac reserve during the early life of pelagic larvae. More broadly, our findings highlight the wide-ranging impacts of anthropogenic noise on aquatic wildlife living in an increasingly noisy world.

Contamination of aquatic ecosystems by pharmaceuticals is a growing threat worldwide. The antidepressant fluoxetine is one such pharmaceutical that is frequently detected in aquatic ecosystems, and has been found to alter the behaviour and physiology of exposed wildlife. Few studies, however, have investigated potential combined effects on behaviour and metabolic rate. In addition, exposures are often short in duration and rarely conducted under ecologically relevant conditions. Here, we examined the impacts of long-term fluoxetine exposure on boldness (exploration, activity, and antipredator behaviour), metabolic rate, and morphology in male guppies (Poecilia reticulata). Specifically, fish were exposed for 8 months (corresponding to approximately two overlapping generations) in semi-natural mesocosms to one of three treatments: an unexposed control (0 ng L-1), or low or high fluoxetine (mean measured concentrations: 30 ng L-1 and 292 ng L-1, respectively). Following exposure, we quantified male exploratory behaviour and activity in a novel environment (maze arena) and antipredator behaviour in the presence or absence of a live predator (spangled perch, Leiopotherapon unicolor), as well as metabolic rate and morphology (mass, standard length, and scaled mass index). Fluoxetine exposure did not significantly alter boldness, metabolic rate, mass, or standard length. However, fluoxetine exposure did alter body condition, whereby fish in the high treatment had a higher scaled mass index than control fish. Our results, considered alongside previous work, underscore the importance of exposure duration in mediating the effects of fluoxetine on fitness-related traits. Continued research under extended exposure periods (i.e., spanning multiple generations) is essential if we are to accurately predict the ecological impacts of fluoxetine on exposed wildlife, and their underlying mechanism(s).

Despite great promise for understanding the impacts and extent of climate change and extreme weather events on aquatic animals, their species, and ecological communities, it is surprising that electronic tagging and tracking tools, like biotelemetry and biologging, have not been extensively used to understand climate change or develop and evaluate potential interventions that may help adapt to its impacts. In this review, we provide an overview of methodologies and study designs that leverage available electronic tracking tools to investigate aspects of climate change and extreme weather events in aquatic ecosystems. Key interventions to protect aquatic life from the impacts of climate change, including habitat restoration, protected areas, conservation translocations, mitigations against interactive effects of climate change, and simulation of future scenarios, can all be greatly facilitated by using electronic tagging and tracking. We anticipate that adopting animal tracking to identify phenotypes, species, or ecosystems that are vulnerable or resilient to climate change will help in applying management interventions such as fisheries management, habitat restoration, invasive species control, or enhancement measures that prevent extinction and strengthen the resilience of communities against the most damaging effects of climate change. Given the scalability and increasing accessibility of animal tracking tools for researchers, tracking individual organisms will hopefully also facilitate research into effective solutions and interventions against the most extreme and acute impacts on species, populations, and ecosystems.

Behavioural analysis has been attracting significant attention as a broad indicator of sub-lethal toxicity and has secured a place as an important subdiscipline in ecotoxicology. Among the most notable characteristics of behavioural research, compared to other established approaches in sub-lethal ecotoxicology (e.g. reproductive and developmental bioassays), are the wide range of study designs being used and the diversity of endpoints considered. At the same time, environmental hazard and risk assessment, which underpins regulatory decisions to protect the environment from potentially harmful chemicals, often recommends that ecotoxicological data be produced following accepted and validated test guidelines. These guidelines typically do not address behavioural changes, meaning that these, often sensitive, effects are not represented in hazard and risk assessments. Here, we propose a new tool, the EthoCRED evaluation method, for assessing the relevance and reliability of behavioural ecotoxicity data, which considers the unique requirements and challenges encountered in this field. This method and accompanying reporting recommendations are designed to serve as an extension of the "Criteria for Reporting and Evaluating Ecotoxicity Data (CRED)" project. As such, EthoCRED can both accommodate the wide array of experimental design approaches seen in behavioural ecotoxicology, and could be readily implemented into regulatory frameworks as deemed appropriate by policy makers of different jurisdictions to allow better integration of knowledge gained from behavioural testing into environmental protection. Furthermore, through our reporting recommendations, we aim to improve the reporting of behavioural studies in the peer-reviewed literature, and thereby increase their usefulness to inform chemical regulation.

Here, we explore the first preprints uploaded to EcoEvoRxiv to characterise preprint practices in ecology and evolution. We aim to understand: 1) in what countries authors who use EcoEvoRxiv are located; 2) the taxonomic diversity of study systems across preprints; 3) whether preprint server use depends on career stage and gender; 4) the extent to which authors make use of preprint servers for reports and community-driven peer review; 5) the extent to which data and code are shared in preprints; and 6) how many preprints remain unpublished, and for those that are published, how long it took for them to become published. In the process, we also provide a summary of what makes EcoEvoRxiv distinct from other preprint servers to help further clarify the benefits of using community-driven preprint servers to disseminate research findings.

Pharmaceutical pollution poses an increasing threat to global wildlife populations. Psychoactive pharmaceutical pollutants (e.g. antidepressants, anxiolytics) are a distinctive concern owing to their ability to act on neural pathways that mediate fitness-related behavioural traits. However, despite increasing research efforts, very little is known about how these drugs might influence the behaviour and survival of species in the wild. Here, we capitalize on the development of novel slow-release pharmaceutical implants and acoustic telemetry tracking tools to reveal that exposure to environmentally relevant concentrations of the benzodiazepine pollutant temazepam alters movement dynamics and decreases the migration success of brown trout (Salmo trutta) smolts in a natural lake system. This effect was potentially owing to temazepam-exposed fish suffering increased predation compared with unexposed conspecifics, particularly at the river-lake confluence. These findings underscore the ability of pharmaceutical pollution to alter key fitness-related behavioural traits under natural conditions, with likely negative impacts on the health and persistence of wildlife populations.

Biological rhythms have a crucial role in shaping the biology and ecology of organisms. Light pollution is known to disrupt these rhythms, and evidence is emerging that chemical pollutants can cause similar disruption. Conversely, biological rhythms can influence the effects and toxicity of chemicals. Thus, by drawing insights from the extensive study of biological rhythms in biomedical and light pollution research, we can greatly improve our understanding of chemical pollution. This Essay advocates for the integration of biological rhythmicity into chemical pollution research to gain a more comprehensive understanding of how chemical pollutants affect wildlife and ecosystems. Despite historical barriers, recent experimental and technological advancements now facilitate the integration of biological rhythms into ecotoxicology, offering unprecedented, high-resolution data across spatiotemporal scales. Recognizing the importance of biological rhythms will be essential for understanding, predicting, and mitigating the complex ecological repercussions of chemical pollution.

Bertram and colleagues introduce the One Health concept, an interdisciplinary framework that aims to sustainably advance and safeguard the health of humans, animals, and the environment.

The Science-Policy Panel (SPP) on Chemicals, Waste, and Pollution Prevention, now being established under a mandate of the United Nations Environment Assembly, will address chemical pollution, one element of the triple planetary crises along with climate change and biodiversity loss. The SPP should provide governments with consensual, authoritative, and holistic solution-oriented assessments, particularly relevant to low- and middle-income countries (LMICs) and, we suggest, to issues regarding the global commons. The assessments should be flexible in scope and breadth, and address existing issues retrospectively and prospectively to minimize the high costs to human and environment health that come from delayed, slow, and/or fragmented policy responses. Two examples of assessments are presented here. The retrospective example is pharmaceutical pollution, which is of increasing importance, especially in LMICs. The SPP's assessment could identify data gaps, develop regionally attuned policy options for mitigation, promote "benign-by-design" chemistry, explore educational and capacity-building activities, and investigate financial mechanisms for implementation. The prospective example is on risks posed by chemicals and waste release from critical technological infrastructure and waste sites vulnerable to sea level rise and extreme weather events. Multisectoral and multidisciplinary inputs are needed to map and develop "disaster-proofing" responses, along with financing mechanisms. The new SPP offers the ambition and mechanisms for enabling much-needed assessments explicitly framed as inputs to policy-making, to protect, and support the recovery of, local to global human and environmental health.

Jack Brand and colleagues introduce the salmonid fishes comprising over 200 species.

The pervasive contamination of ecosystems with active pharmaceutical ingredients poses a serious threat to biodiversity, ecosystem services and public health. Urgent action is needed to design greener drugs that maintain efficacy but also minimize environmental impact.

Background The current scientific discourse on environmental impacts of veterinary medicines mostly focuses on ectoparasiticides. Meanwhile, the environmental impacts of widely prescribed drugs for the treatment of human and animal parasitic vector-borne diseases (PVBD) remain largely unexplored. There is thus a need for evidence-based information to support guidelines and protocols for sustainable One Health PVBD drug development and use, while promoting greener research practices. Here, we reflect on the potential environmental impacts of PVBD drugs in current use, and the environmental impact of our research practices for developing new antiparasitics. Methods We conducted a survey of the membership of the “One Health drugs against parasitic vector borne diseases in Europe and beyond” Cooperation in Science and Technology (COST) Action 21111 (OneHealth drugs) to assess the current appreciation of sustainable drug design concepts and the extent to which One Health and sustainability principles are integrated into PVBD drug discovery and development. The survey also explored which human, technical, and funding resources are currently used in Europe and neighbouring countries in PVBD drugs research. Results The survey was conducted and analysed by OneHealth drugs and garnered 89 respondents, representing a response rate of 66% from 32 countries, predominantly European. 87% of participating collaborators worked in Academia; research groups were small (60% with 1–4 researchers) and mostly consist of few researchers, mostly at early career stages (63% <35 years old). Collaborations were mostly between academics, and 60% collaborated with non-European researchers, while funding was mostly from national governments. Motivation for greener research practices was high but there was as yet low implementation of green strategies or the incorporation of ecotoxicological test in drug development workflows, due to cost and unfamiliarity. Conclusions We highlight the need for early-ecotoxicological testing of new drug candidates and suggest best practices as we move towards standardized protocols in developing safe and efficacious PVBD drugs.

Parasitic vector-borne diseases (VBDs) represent nearly 20% of the global burden of infectious diseases. Moreover, the spread of VBDs is enhanced by global travel, urbanization, and climate change. Treatment of VBDs faces challenges due to limitations of existing drugs, as the potential for side effects in nontarget species raises significant environmental concerns. Consequently, considering environmental risks early in drug development processes is critically important. Here, we examine the environmental risk assessment process for veterinary medicinal products in the European Union and identify major gaps in the ecotoxicity data of these drugs. By highlighting the scarcity of ecotoxicological data for commonly used antiparasitic drugs, we stress the urgent need for considering the One Health concept. We advocate for employing predictive tools and nonanimal methodologies such as New Approach Methodologies at early stages of antiparasitic drug research and development. Furthermore, adopting progressive approaches to mitigate ecological risks requires the integration of nonstandard tests that account for real-world complexities and use environmentally relevant exposure scenarios. Such a strategy is vital for a sustainable drug development process as it adheres to the principles of One Health, ultimately contributing to a healthier and more sustainable world.