Leveraging AI to improve evidence synthesis in conservation.

Systematic evidence syntheses (systematic reviews and maps) summarize knowledge and are used to support decisions and policies in a variety of applied fields, from medicine and public health to biodiversity conservation. However, conducting these exercises in conservation is often expensive and slow, which can impede their use and hamper progress in addressing the current biodiversity crisis. With the explosive growth of large language models (LLMs) and other forms of artificial intelligence (AI), we discuss here the promise and perils associated with their use. We conclude that, when judiciously used, AI has the potential to speed up and hopefully improve the process of evidence synthesis, which can be particularly useful for underfunded applied fields, such as conservation science.

Maternal transfer of per- and polyfluoroalkyl substances (PFAS) in wild birds: A systematic review and meta-analysis.

Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals widely used in consumer products. PFAS can accumulate in animal tissues, resulting in biomagnification and adverse effects on wildlife, such as reproductive impairment. In bird species, PFAS are transferred from mothers to eggs along with essential nutrients and may affect embryo development. However, the extent of maternal PFAS transfer across different species and compounds remains poorly understood. Here, we conducted a systematic review and meta-analysis to quantify maternal PFAS transfer in wild birds and investigate potential sources of variation. We tested the moderating effects of compounds' physicochemical properties and biological traits of studied birds. The dataset included 505 measurements of PFAS concentration and 371 effect sizes derived from 13 studies on 16 bird species and 25 compounds. Overall, across all studies and species, we found a 41% higher concentration of PFAS in offspring than in mothers. Specifically, contaminants were concentrated in the yolk, longer and heavier compounds showed preferential transfer, larger clutch size was associated with decreased PFAS transfer and a higher transfer rate was shown in species with piscivorous and opportunistic/diverse diets. A validation assessment showed good robustness of the overall meta-analytic result. Given the crucial role of birds in maintaining ecological balance, this research article has relevant implications for modelling the impacts of PFAS on wildlife, ecosystems, and human health.

Realism and robustness require increased sample size when studying both sexes.

A recent article claimed that researchers need not increase the overall sample size for a study that includes both sexes. This Formal Comment points out that that study assumed two sexes to have the same variance, and explains why this is a unrealistic assumption.

Academic publishing requires linguistically inclusive policies.

Scientific knowledge is produced in multiple languages but is predominantly published in English. This practice creates a language barrier to generate and transfer scientific knowledge between communities with diverse linguistic backgrounds, hindering the ability of scholars and communities to address global challenges and achieve diversity and equity in science, technology, engineering and mathematics (STEM). To overcome those barriers, publishers and journals should provide a fair system that supports non-native English speakers and disseminates knowledge across the globe. We surveyed policies of 736 journals in biological sciences to assess their linguistic inclusivity, identify predictors of inclusivity, and propose actions to overcome language barriers in academic publishing. Our assessment revealed a grim landscape where most journals were making minimal efforts to overcome language barriers. The impact factor of journals was negatively associated with adopting a number of inclusive policies whereas ownership by a scientific society tended to have a positive association. Contrary to our expectations, the proportion of both open access articles and editors based in non-English speaking countries did not have a major positive association with the adoption of linguistically inclusive policies. We proposed a set of actions to overcome language barriers in academic publishing, including the renegotiation of power dynamics between publishers and editorial boards.

Systematic approaches to assessing high-temperature limits to fertility in animals.

Critical thermal limits (CTLs) gauge the physiological impact of temperature on survival or critical biological function, aiding predictions of species range shifts and climatic resilience. Two recent Drosophila species studies, using similar approaches to determine temperatures that induce sterility (thermal fertility limits [TFLs]), reveal that TFLs are often lower than CTLs and that TFLs better predict both current species distributions and extinction probability. Moreover, many studies show fertility is more sensitive at less extreme temperatures than survival (thermal sensitivity of fertility [TSF]). These results present a more pessimistic outlook on the consequences of climate change. However, unlike CTLs, TFL data are limited to Drosophila, and variability in TSF methods poses challenges in predicting species responses to increasing temperature. To address these data and methodological gaps, we propose 3 standardized approaches for assessing thermal impacts on fertility. We focus on adult obligate sexual terrestrial invertebrates but also provide modifications for other animal groups and life-history stages. We first outline a "gold-standard" protocol for determining TFLs, focussing on the effects of short-term heat shocks and simulating more frequent extreme heat events predicted by climate models. As this approach may be difficult to apply to some organisms, we then provide a standardized TSF protocol. Finally, we provide a framework to quantify fertility loss in response to extreme heat events in nature, given the limitations in laboratory approaches. Applying these standardized approaches across many taxa, similar to CTLs, will allow robust tests of the impact of fertility loss on species responses to increasing temperatures.

A systematic evidence map and bibliometric analysis of the behavioural impacts of pesticide exposure on zebrafish.

Pesticides are indispensable in agriculture and have become ubiquitous in aquatic environments. Pesticides in natural environments can cause many negative impacts on aquatic species, ranging from mortality to sub-lethal physiological and behavioural changes. The complex sub-lethal impacts of pesticides are routinely tested on model species, with zebrafish (Danio rerio) being regularly used as a behavioural model. Although behavioural ecotoxicology research using zebrafish is increasing rapidly, we lack quantitative evidence to support which pesticides have been tested and how study designs are carried out. This shortcoming not only limits the deliberate planning for future primary studies to fill the knowledge gaps but also hinders evidence synthesis. To provide quantitative evidence of what pesticides are currently studied and what study designs are used, we combined a systematic evidence map approach and bibliometric analysis. This novel method has been coined research weaving and allows us to elicit gaps and clusters in our evidence base, whilst showing connections between authors and institutions. The methodology can be summarised in five primary steps: literature searching, screening, extraction, data analysis and bibliometric analysis. We identified four areas where research on the sub-lethal effects of pesticide exposure on zebrafish is lacking. First, some widely used pesticides, such as neonicotinoids, are understudied. Second, most studies do not report important elements of the study design, namely the sex and the life-stage of the zebrafish. Third, some behaviours, such as impacts of pesticide exposure on zebrafish cognition, are underexplored. And last, we revealed through the bibliometric analysis that most of the research is conducted in developed countries and there is limited cross country co-authorships. Upon identifying these gaps, we offer solutions for each limitation, emphasizing the importance of diverse global research output and cross-country co-authorships. Our systematic evidence map and bibliometric analysis provide valuable insights for helping to guide future research, which can be used to help support evidence-based policy decisions.

The ABC of academic writing: non-native speakers' perspective.

Academic writing is difficult, especially for non-native English speakers. We share a perspective on writing with a set of heuristics called the Writing Alphabet, consisting of Accurate, Brief, Clear, Dynamic, Engaging, Flowing, Goal, Habit, and Investment. These points can help struggling writers identify issues and, importantly, internalise good writing practices.

Species sensitivities to artificial light at night: A phylogenetically controlled multilevel meta-analysis on melatonin suppression.

The rapid urbanization of our world has led to a surge in artificial lighting at night (ALAN), with profound effects on wildlife. Previous research on wildlife's melatonin, a crucial mechanistic indicator and mediator, has yielded inconclusive evidence due to a lack of comparative analysis. We compiled and analysed an evidence base including 127 experiments with 437 observations across 31 wild vertebrates using phylogenetically controlled multilevel meta-analytic models. The evidence comes mainly from the effects of white light on melatonin suppression in birds and mammals. We show a 36% average decrease in melatonin secretion in response to ALAN across a diverse range of species. This effect was observed for central and peripheral melatonin, diurnal and nocturnal species, and captive and free-living populations. We also reveal intensity-, wavelength-, and timing-dependent patterns of ALAN effects. Exposure to ALAN led to a 23% rise in inter-individual variability in melatonin suppression, with important implications for natural selection in wild vertebrates, as some individuals may display higher tolerance to ALAN. The cross-species evidence has strong implications for conservation of wild populations that are subject to natural selection of ALAN. We recommend measures to mitigate harmful impacts of ALAN, such as using 'smart' lighting systems to tune the spectra to less harmful compositions.

New horizons for comparative studies and meta-analyses.

Comparative analyses and meta-analyses are key tools to elucidate broad biological principles, yet the two approaches often appear different in purpose. We propose an integrated approach that can generate deeper insights into ecoevolutionary processes. Marrying comparative and meta-analytic approaches will allow for (i) a more accurate investigation of drivers of biological variation, (ii) a greater ability to account for sources of non-independence in experimental data, (iii) more effective control of publication bias, and (iv) improved transparency and reproducibility. Stronger integration of meta-analytic and comparative studies can also broaden the scope from species-centric investigations to community-level responses and function-valued traits (e.g., reaction norms). We illuminate commonalities, differences, and the transformative potential of combining these methodologies for advancing ecology and evolutionary biology.

Finding the right power balance: Better study design and collaboration can reduce dependence on statistical power.

Power analysis currently dominates sample size determination for experiments, particularly in grant and ethics applications. Yet, this focus could paradoxically result in suboptimal study design because publication biases towards studies with the largest effects can lead to the overestimation of effect sizes. In this Essay, we propose a paradigm shift towards better study designs that focus less on statistical power. We also advocate for (pre)registration and obligatory reporting of all results (regardless of statistical significance), better facilitation of team science and multi-institutional collaboration that incorporates heterogenization, and the use of prospective and living meta-analyses to generate generalizable results. Such changes could make science more effective and, potentially, more equitable, helping to cultivate better collaborations.

Intra-specific correlations between ejaculate traits and competitive fertilization success: a meta-analysis across species and fertilization modes.

Understanding of how selection can act on traits that improve competitiveness and subsequent paternity has advanced, including the idea that internal and external fertilization presents different environments that may select differentially on ejaculate traits. However, no studies have quantitatively synthesized the intra-specific relationships between these traits and paternity. Therefore, we conducted a meta-analysis across 52 papers to determine which ejaculate traits positively correlate with paternity share and how these correlations vary with fertilization mode. Overall, most ejaculate traits were positively associated with paternity, with the notable exception of sperm length. Sub-analyses on sperm number, sperm length, and sperm velocity revealed no statistical differences between fertilization modes in the relationship between traits and paternity when all effect sizes across species were combined. However, in a sub-analysis on fish species only, we found evidence that sperm velocity may be more important in external fertilizers. We also observed differences in the importance of phylogenetic relatedness and some species-specific differences. Our results suggest that while most ejaculate traits should be under positive directional selection in both internal and external fertilizers, sperm length may be subject to more nuanced selection pressures. Overall, we highlight important patterns of intra-specific relationships between ejaculate traits and competitive fertilization success.

Shining a light on duckweed: exploring the effects of artificial light at night (ALAN) on growth and pigmentation.

Background: Artificial light at night (ALAN) is a novel environmental stressor of global concern. Various sources of artificial light are now common in urbanized areas and have diverse negative effects on many species of animals and plants. However, ALAN has also been shown to have no effect or a positive effect on some organisms. This study investigates the impact of ALAN on the growth and leaf pigmentation of a common floating freshwater plant species. Methods: We exposed wild-derived dotted duckweed (Landoltia punctata) to either darkness during the night (Control group) or to artificial light at night (ALAN group) for 49 days. We set up two large boxes of eighty samples each with 2-3 leaves of duckweed in each sample at the start of the experiment. The ALAN box had an opaque lid with a small lamp that was turned on at night. The Control box was also covered at night with an opaque lid but without a lamp. During the day, plants in both boxes were exposed to natural light. We counted the number of leaves in each sample weekly. We took photos of the samples on day 28 to measure the total leaf surface area per sample. On day 49, we took photos of the underside of the leaves for analyses of the relative levels of dark pigmentation across all samples. Results: We found that ALAN-exposed plant samples had, on average, more leaves than control plants after a few weeks of exposure. They also had a more variable number of leaves per sample. The total leaf area per sample on day 28 was larger in the ALAN samples. The underside of the leaves on day 49 was, on average, darker in the ALAN plants than in the control plants. Conclusion: There is a significant growth-enhancing effect from exposure to artificial light at night on Landolita punctata. However, higher variability induced by ALAN exposure indicates that ALAN is also a stressful condition for these plants. This is in line with our finding of the presence of larger amounts of dark pigments in the leaves of ALAN-exposed plants. Dark pigmentation in duckweed species could be a defence mechanism protecting tissues from stress-induced oxidative damage. Overall, both positive and negative effects of ALAN can be observed simultaneously in different traits of the same organism. Increased individual variation can facilitate population-level adaptation to stressful conditions. As such, this work contributes to our knowledge of the effects of light pollution in urban environments on common plants.

The impact of rising temperatures on the prevalence of coral diseases and its predictability: A global meta-analysis.

Coral reefs are under threat from disease as climate change alters environmental conditions. Rising temperatures exacerbate coral disease, but this relationship is likely complex as other factors also influence coral disease prevalence. To better understand this relationship, we meta-analytically examined 108 studies for changes in global coral disease over time alongside temperature, expressed using average summer sea surface temperature (SST) and cumulative heat stress as weekly sea surface temperature anomalies (WSSTAs). We found that both rising average summer SST and WSSTA were associated with global increases in the mean and variability in coral disease prevalence. Global coral disease prevalence tripled, reaching 9.92% in the 25 years examined, and the effect of 'year' became more stable (i.e. prevalence has lower variance over time), contrasting the effects of the two temperature stressors. Regional patterns diverged over time and differed in response to average summer SST. Our model predicted that, under the same trajectory, 76.8% of corals would be diseased globally by 2100, even assuming moderate average summer SST and WSSTA. These results highlight the need for urgent action to mitigate coral disease. Mitigating the impact of rising ocean temperatures on coral disease is a complex challenge requiring global discussion and further study.

The influence of immune challenges on the mean and variance in reproductive investment: a meta-analysis of the terminal investment hypothesis.

Finding the optimal balance between survival and reproduction is a central puzzle in life-history theory. The terminal investment hypothesis predicts that when individuals encounter a survival threat that compromises future reproductive potential, they will increase immediate reproductive investment to maximise fitness. Despite decades of research on the terminal investment hypothesis, findings remain mixed. We examined the terminal investment hypothesis with a meta-analysis of studies that measured reproductive investment of multicellular iteroparous animals after a non-lethal immune challenge. We had two main aims. The first was to investigate whether individuals, on average, increase reproductive investment in response to an immune threat, as predicted by the terminal investment hypothesis. We also examined whether such responses vary adaptively on factors associated with the amount of reproductive opportunities left (residual reproductive value) in the individuals, as predicted by the terminal investment hypothesis. The second was to provide a quantitative test of a novel prediction based on the dynamic threshold model: that an immune threat increases between-individual variance in reproductive investment. Our results provided some support for our hypotheses. Older individuals, who are expected to have lower residual reproductive values, showed stronger mean terminal investment response than younger individuals. In terms of variance, individuals showed a divergence in responses, leading to an increase in variance. This increase in variance was especially amplified in longer-living species, which was consistent with our prediction that individuals in longer-living species should respond with greater individual variation due to increased phenotypic plasticity. We find little statistical evidence of publication bias. Together, our results highlight the need for a more nuanced view on the terminal investment hypothesis and a greater focus on the factors that drive individual responses.

Next steps after airing disagreement on a scientific issue with policy implications: a meta-analysis, multi-lab replication and adversarial collaboration.

Canadian policymakers are interested in determining whether farmed Atlantic salmon, frequently infected with Piscine orthoreovirus (PRV), may threaten wild salmon populations in the Pacific Northwest. A relevant work has been published in BMC Biology by Polinksi and colleagues, but their conclusion that PRV has a negligible impact on the energy expenditure and respiratory performance of sockeye salmon is disputed by Mordecai and colleagues, whose re-analysis is presented in a correspondence article. So, what is the true effect and what should follow this unresolved dispute? We suggest a 'registered multi-lab replication with adversaries'.

Little transparency and equity in scientific awards for early- and mid-career researchers in ecology and evolution.

Scientific awards can shape scientific careers, helping to secure jobs and grants, but can also contribute to the lack of diversity at senior levels and in the elite networks of scientists. To assess the status quo and historical trends, we evaluated 'best researcher' awards and 'best paper' early- and mid-career awards from broad-scope international journals and societies in ecology and evolution. Specifically, we collated information on eligibility rules, assessment criteria and potential gender bias. Our results reveal that, overall, few awards foster equitable access and assessment. Although many awards now explicitly allow extensions of the eligibility period for substantial career interruptions, there is a general lack of transparency in terms of assessment and consideration of other differences in access to opportunities and resources among junior researchers. Strikingly, open science practices were mentioned and valued in only one award. By highlighting instances of desirable award characteristics, we hope this work will nudge award committees to shift from simple but non-equitable award policies and practices towards strategies enhancing inclusivity and diversity. Such a shift would benefit not only those at the early- and mid-career stages but the whole research community. It is also an untapped opportunity to reward open science practices, promoting transparent and robust science.

Publication bias impacts on effect size, statistical power, and magnitude (Type M) and sign (Type S) errors in ecology and evolutionary biology.

Collaborative efforts to directly replicate empirical studies in the medical and social sciences have revealed alarmingly low rates of replicability, a phenomenon dubbed the 'replication crisis'. Poor replicability has spurred cultural changes targeted at improving reliability in these disciplines. Given the absence of equivalent replication projects in ecology and evolutionary biology, two inter-related indicators offer the opportunity to retrospectively assess replicability: publication bias and statistical power. This registered report assesses the prevalence and severity of small-study (i.e., smaller studies reporting larger effect sizes) and decline effects (i.e., effect sizes decreasing over time) across ecology and evolutionary biology using 87 meta-analyses comprising 4,250 primary studies and 17,638 effect sizes. Further, we estimate how publication bias might distort the estimation of effect sizes, statistical power, and errors in magnitude (Type M or exaggeration ratio) and sign (Type S). We show strong evidence for the pervasiveness of both small-study and decline effects in ecology and evolution. There was widespread prevalence of publication bias that resulted in meta-analytic means being over-estimated by (at least) 0.12 standard deviations. The prevalence of publication bias distorted confidence in meta-analytic results, with 66% of initially statistically significant meta-analytic means becoming non-significant after correcting for publication bias. Ecological and evolutionary studies consistently had low statistical power (15%) with a 4-fold exaggeration of effects on average (Type M error rates = 4.4). Notably, publication bias reduced power from 23% to 15% and increased type M error rates from 2.7 to 4.4 because it creates a non-random sample of effect size evidence. The sign errors of effect sizes (Type S error) increased from 5% to 8% because of publication bias. Our research provides clear evidence that many published ecological and evolutionary findings are inflated. Our results highlight the importance of designing high-power empirical studies (e.g., via collaborative team science), promoting and encouraging replication studies, testing and correcting for publication bias in meta-analyses, and adopting open and transparent research practices, such as (pre)registration, data- and code-sharing, and transparent reporting.