| Literature DB >> 30973871 |
Kate A Field1,2, Paul C Paquet1,2, Kyle Artelle1,2, Gilbert Proulx3, Ryan K Brook4, Chris T Darimont1,2.
Abstract
Despite abundant focus on responsible care of laboratory animals, we argue that inattention to the maltreatment of wildlife constitutes an ethical blind spot in contemporary animal research. We begin by reviewing significant shortcomings in legal and institutional oversight, arguing for the relatively rapid and transformational potential of editorial oversight at journals in preventing harm to vertebrates studied in the field and outside the direct supervision of institutions. Straightforward changes to animal care policies in journals, which our analysis of 206 journals suggests are either absent (34%), weak, incoherent, or neglected by researchers, could provide a practical, effective, and rapidly imposed safeguard against unnecessary suffering. The Animals in Research: Reporting On Wildlife (ARROW) guidelines we propose here, coupled with strong enforcement, could result in significant changes to how animals involved in wildlife research are treated. The research process would also benefit. Sound science requires animal subjects to be physically, physiologically, and behaviorally unharmed. Accordingly, publication of methods that contravenes animal welfare principles risks perpetuating inhumane approaches and bad science.Entities:
Mesh:
Year: 2019 PMID: 30973871 PMCID: PMC6459470 DOI: 10.1371/journal.pbio.3000193
Source DB: PubMed Journal: PLoS Biol ISSN: 1544-9173 Impact factor: 8.029
Fig 1Presence and strength of compliance language in animal care policies across 206 journals that commonly publish wildlife research.
3R, replacement, reduction, refinement.
Fig 2Association between journal characteristics and presence of animal care policies across 206 journals that commonly publish wildlife research.
Coefficients shown are odds ratios from a logistic model, with thick and thin bars representing 50 and 95% confidence intervals, respectively. X scale unit is per 2 SDs of predictor.