Data-Driven Method to Estimate Nonlinear Chemical Equivalence

There is great need to express the impacts of chemicals found in the environment in terms of effects from alternative chemicals of interest. Methods currently employed in fields such as life-cycle assessment, risk assessment, mixtures toxicology, and pharmacology rely mostly on heuristic arguments to justify the use of linear relationships in the construction of “equivalency factors,” which aim to model these concentration-concentration correlations. However, the use of linear models, even at low concentrations, oversimplifies the nonlinear nature of the concentration-response curve, therefore introducing error into calculations involving these factors. We address this problem by reporting a method to determine a concentration-concentration relationship between two chemicals based on the full extent of experimentally derived concentration-response curves. Although this method can be easily generalized, we develop and illustrate it from the perspective of toxicology, in which we provide equations relating the sigmoid and non-monotone, or “biphasic,” responses typical of the field. The resulting concentration-concentration relationships are manifestly nonlinear for nearly any chemical level, even at the very low concentrations common to environmental measurements. We demonstrate the method using real-world examples of toxicological data which may exhibit sigmoid and biphasic mortality curves. Finally, we use our models to calculate equivalency factors, and show that traditional results are recovered only when the concentration-response curves are “parallel,” which has been noted before, but we make formal here by providing mathematical conditions on the validity of this approach.     

The Customer Isn't Always Right—Conservation and Animal Welfare Implications of the Increasing Demand for Wildlife Tourism

Tourism accounts for 9% of global GDP and comprises 1.1 billion tourist arrivals per annum. Visits to wildlife tourist attractions (WTAs) may account for 20–40% of global tourism, but no studies have audited the diversity of WTAs and their impacts on the conservation status and welfare of subject animals. We scored these impacts for 24 types of WTA, visited by 3.6–6 million tourists per year, and compared our scores to tourists’ feedback on TripAdvisor. Six WTA types (impacting 1,500–13,000 individual animals) had net positive conservation/welfare impacts, but 14 (120,000–340,000 individuals) had negative conservation impacts and 18 (230,000–550,000 individuals) had negative welfare impacts. Despite these figures only 7.8% of all tourist feedback on these WTAs was negative due to conservation/welfare concerns. We demonstrate that WTAs have substantial negative effects that are unrecognised by the majority of tourists, suggesting an urgent need for tourist education and regulation of WTAs worldwide.