Reproduction, Embryonic Development, and Maternal Transfer of Contaminants in the Amphibian Gastrophryne carolinensis

Although many amphibian populations around the world are declining at alarming rates, the cause of most declines remains unknown. Environmental contamination is one of several factors implicated in declines and may have particularly important effects on sensitive developmental stages. Despite the severe effects of maternal transfer of contaminants on early development in other vertebrate lineages, no studies have examined the effects of maternal transfer of contaminants on reproduction or development in amphibians. We examined maternal transfer of contaminants in eastern narrow-mouth toads (Gastrophryne carolinensis) collected from a reference site and near a coal-burning power plant. Adult toads inhabiting the industrial area transferred significant quantities of selenium and strontium to their eggs, but Se concentrations were most notable (up to 100 μg/g dry mass). Compared with the reference site, hatching success was reduced by 11% in clutches from the contaminated site. In surviving larvae, the frequency of developmental abnormalities and abnormal swimming was 55–58% higher in the contaminated site relative to the reference site. Craniofacial abnormalities were nearly an order of magnitude more prevalent in hatchlings from the contaminated site. When all developmental criteria were considered collectively, offspring from the contaminated site experienced 19% lower viability. Although there was no statistical relationship between the concentration of Se or Sr transferred to eggs and any measure of offspring viability, our study demonstrates that maternal transfer may be an important route of contaminant exposure in amphibians that has been overlooked

Relationship between Se () and Sr () concentrations (μg/g dry mass) in female and their eggs

<p><b>Copyright information:</b></p><p>Taken from "Reproduction, Embryonic Development, and Maternal Transfer of Contaminants in the Amphibian "</p><p>Environmental Health Perspectives 2005;114(5):661-666.</p><p>Published online 8 Dec 2005</p><p>PMCID:PMC1459916.</p><p>This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original DOI.</p> Females were collected from both contaminated and reference sites but bred under controlled, uncontaminated conditions. Female concentrations were determined 48 hr after oviposition. () = 1.0255 − 0.0448, = 0.9415. () = 0.2634 − 0.0237, = 0.4026

Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed