Are anthropogenic pressures on biodiversity valued differently than natural ones? A meta-analysis of the non-use valuation literature

Anthropogenic climate change is expected to be a major driver of worldwide biodiversity losses. Non-use values can play an important role in the evaluation of strategies to combat these losses or to reduce anthropogenic climate change. However, non-use values may not be transferrable across contexts with different pressures on biodiversity. Contrary to expectations in economic theory, they may be determined not only by outcomes, but also by what causes the outcomes. Given that no extant studies have specifically estimated the willingness to pay (WTP) for reducing the impact of climate change on biodiversity, we compare the WTP more generally for reducing anthropogenic and natural pressures on biodiversity. We conduct a meta-regression analysis informed by data obtained from stated preferences studies focusing on non-use values of biodiversity conservation. We assess whether non-use values for improving or avoiding losses of habitats and species are affected by policy responses addressing anthropogenic or natural pressures. We estimate meta-regression models in which we explain the variation in biodiversity non-use values by accounting for the observed heterogeneity in good, methodology, sample, and context characteristics. We estimate meta-regression models using 159 observations from 62 publications. The models suggest that non-use values for biodiversity conservation addressing anthropogenic pressures may be 95–131 percent larger than those facing natural pressures. We also find that non-use values are generally not sensitive to habitat types or the scope of species preservation. The evaluation of climate policy in terms of biodiversity non-use values should be based on valuations of the effect of anthropogenic pressures on biodiversity, instead of inferring these benefits from a wide variety of existing studies. Furthermore, there is a clear need for additional valuation research focusing on estimating non-use values, specifically for climate change-induced biodiversity losses.