Estimating population extinction thresholds with categorical classification trees for Louisiana black bears

Setting Statistical Thresholds Is Useful to Define Truly Effective Conservation Interventions

Effective interventions are needed to solve conflicts between humans and predators over livestock killing, nuisance behavior, and attacks on pets and humans. Progress in quantification of evidence-based effectiveness and selection of the best interventions raises new questions, such as the existence of thresholds to identify truly effective interventions. Current classification of more and less effective interventions is subjective and statistically unjustified. This study describes a novel method to differentiate true and untrue effectiveness on a basis of false positive risk (FPR). I have collected 152 cases of applications of damage-reducing interventions from 102 scientific publications, 26 countries, 22 predator species, and 6 categories of interventions. The analysis has shown that the 95% confidence interval of the relative risk of predator-caused damage was 0.10–0.25 for true effectiveness (FPR < 0.05) and 0.35–0.56 for untrue effectiveness (FPR ≥ 0.05). This means that damage was reduced by 75–90% for truly effective interventions and by 44–65% for interventions of untrue effectiveness. Based on this, it was specified that truly effective interventions have the relative risk ≤ 0.25 (damage reduction ≥ 75%) and the effectiveness of interventions with the relative risk > 0.25 (damage reduction < 75%) is untrue. This threshold is statistically well-justified, stable, easy to remember, and practical to use in anti-predator interventions. More research is essential to know how this threshold holds true for other conservation interventions aiming to reduce negative outcomes (e.g., poaching rates) or increase positive outcomes (e.g., species richness).