Decline effects are rare in ecology

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.

Assessment of temporal instability in the applied ecology and conservation evidence base

Outcomes of meta-analyses are increasingly used to inform evidence-based decision making in various research fields. However, a number of recent studies have reported rapid temporal changes in magnitude and significance of the reported effects which could make policy-relevant recommendations from meta-analyses to quickly go out of date. We assessed the extent and patterns of temporal trends in magnitude and statistical significance of the cumulative effects in meta-analyses in applied ecology and conservation published between 2004 and 2018. Of the 121 meta-analyses analysed, 93% showed a temporal trend in cumulative effect magnitude or significance with 27% of the datasets exhibiting temporal trends in both. The most common trend was the early study effect when at least one of the first 5 years effect size estimates exhibited more than 50% magnitude difference to the subsequent estimate. The observed temporal trends persisted in majority of datasets once moderators were accounted for. Only 5 datasets showed significant changes in sample size over time which could potentially explain the observed temporal change in the cumulative effects. Year of publication of meta-analysis had no significant effect on presence of temporal trends in cumulative effects. Our results show that temporal changes in magnitude and statistical significance in applied ecology are widespread and represent a serious potential threat to use of meta-analyses for decision-making in conservation and environmental management. We recommend use of cumulative meta-analyses and call for more studies exploring the causes of the temporal effects.

A framework for untangling the consequences of artificial light at night on species interactions

Although much evidence exists showing organismal consequences from artificial light at night (ALAN), large knowledge gaps remain regarding ALAN affecting species interactions. Species interactions occur via shared spatio-temporal niches among species, which may be determined by natural light levels. We review how ALAN is altering these spatio-temporal niches through expanding twilight or full Moon conditions and constricting nocturnal conditions as well as creating patches of bright and dark. We review literature from a database to determine if ALAN is affecting species interactions via spatio-temporal dynamics. The literature indicates a growing interest in ALAN and species interactions: 58% of the studies we analysed have been published since 2020. Seventy-five of 79 studies found ALAN altered species interactions. Enhancements and reductions of species interactions were equally documented. Many studies revealed ALAN affecting species interactions spatially, but few revealed temporal alterations. There are biases regarding species interactions and ALAN-most studies investigated predator-prey interactions with vertebrates as predators and invertebrates as prey. Following this literature review, we suggest avenues, such as remote sensing and animal tracking, that can guide future research on the consequences of ALAN on species interactions across spatial and temporal axes. This article is part of the theme issue 'Light pollution in complex ecological systems'.

A meta-evaluation of the quality of reporting and execution in ecological meta-analyses

Quantitatively summarizing results from a collection of primary studies with meta-analysis can help answer ecological questions and identify knowledge gaps. The accuracy of the answers depends on the quality of the meta-analysis. We reviewed the literature assessing the quality of ecological meta-analyses to evaluate current practices and highlight areas that need improvement. From each of the 18 review papers that evaluated the quality of meta-analyses, we calculated the percentage of meta-analyses that met criteria related to specific steps taken in the meta-analysis process (i.e., execution) and the clarity with which those steps were articulated (i.e., reporting). We also re-evaluated all the meta-analyses available from Pappalardo et al. [1] to extract new information on ten additional criteria and to assess how the meta-analyses recognized and addressed non-independence. In general, we observed better performance for criteria related to reporting than for criteria related to execution; however, there was a wide variation among criteria and meta-analyses. Meta-analyses had low compliance with regard to correcting for phylogenetic non-independence, exploring temporal trends in effect sizes, and conducting a multifactorial analysis of moderators (i.e., explanatory variables). In addition, although most meta-analyses included multiple effect sizes per study, only 66% acknowledged some type of non-independence. The types of non-independence reported were most often related to the design of the original experiment (e.g., the use of a shared control) than to other sources (e.g., phylogeny). We suggest that providing specific training and encouraging authors to follow the PRISMA EcoEvo checklist recently developed by O'Dea et al. [2] can improve the quality of ecological meta-analyses.

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.

Extreme original data yield extreme decline effects

Clements et al. respond to Munday's claim that his "reanalysis shows there is not an extreme decline effect in fish ocean acidification studies". They contend that extreme data reported in early studies authored by Dixson and Munday indeed result in an "extreme" decline effect in this field, and conclude that the decline effect is primarily driven by papers by particular authors.

Decline effects are rare in ecology

The scientific evidence base on any given topic changes over time as more studies are published. Currently, there is widespread concern about non-random, directional changes over time in the scientific evidence base associated with many topics. In particular, if studies finding large effects (e.g., large differences between treatment and control means) tend to get published quickly, while small effects tend to get published slowly, the net result will be a decrease over time in the estimated magnitude of the mean effect size, known as a "decline effect". If decline effects are common, then the published scientific literature will provide a biased and misleading guide to management decisions, and to the allocation of future research effort. We compiled data from 466 meta-analyses in ecology to look for evidence of decline effects. We found that decline effects are rare. Only ~5% of ecological meta-analyses truly exhibit a directional change in mean effect size over time arising for some reason other than random chance, usually but not always in the direction of decline. Most apparent directional changes in mean effect size over time are attributable to regression to the mean, consistent with primary studies being published in random order with respect to the effect sizes they report. Our results are good news: decline effects are the exception to the rule in ecology. Identifying and rectifying rare cases of true decline effects remains an important task, but ecologists should not overgeneralize from anecdotal reports of decline effects.