What drives the designation of protected areas? Accounting for spatial dependence using a composite marginal likelihood approach

Previous research indicates that policymakers make biodiversity conservation decisions with the goal of mini-mizing opportunity costs, as opposed to balancing conservation benefits and opportunity costs. However, such research used coarse biodiversity data and did not consider spatial dependence in observed conservation de-cisions. The present study estimates conservation choice models for two European countries (Spain and Italy) that, for the first time, include fine-resolution indicators of biodiversity conservation benefits and opportunity costs, and that account for spatial dependence using a pairwise composite marginal likelihood approach. For the preferred model specifications, we find that a 1% increase in species richness levels is associated with increases in the probability of protection of 0.59% and 0.22% in Spain and Italy, respectively. We also find evidence of spatial correlation and that accounting for it substantially affects the elasticity effects implied by the logit regression models. Although our findings confirm that protected area designations are consistently negatively associated with the potential for productive land-uses, local biodiversity levels may have played a larger role in protected area location decisions than suggested previously.

Automated summary

Previous research shows that policymakers prioritize minimizing opportunity costs rather than balancing conservation benefits and opportunity costs in biodiversity conservation decisions. However, previous studies lacked fine-resolution indicators of biodiversity conservation benefits and opportunity costs, and failed to consider the spatial dependence in observed conservation decisions. This study fills these gaps by estimating conservation choice models for Spain and Italy, incorporating fine-resolution indicators and accounting for spatial dependence. The findings suggest that protected area designations are negatively associated with productive land-uses and that local biodiversity levels play a significant role in protected area location decisions.