those administrative divisions that are located within a 25 km radius of our protected areas (Figure S12a).

The average effect of AP management on asset wealth is 0.102 standard deviations, with a standard error of 0.034 (Figure 3, Row 5). However, we cannot interpret this increase in economic well-being as being solely attributable to AP management due to elevated levels of asset wealth immediately prior to transference (Figure S12b). This suggests that communities near protected areas destined for AP management are already becoming richer at a faster rate than communities near protected areas that never come under AP management. The post-transference stability of asset wealth could, therefore, be a continuation of this pre-existing upward trend rather than a consequence of AP’s actions.

# **2.4 Conflict**

Finally, we investigate whether AP’s activities affect conflict within and around the protected areas it manages. AP’s militarized law enforcement components might generate positive spillover effects, deterring crime and forms of political violence linked to the extraction of natural resources [64–66]. However, it is also possible that AP’s law enforcement exacerbates local insecurity. For example, if AP undermines an armed group’s revenue generation by blocking their access to protected areas with valuable natural resources, then that armed group may be more likely to target civilians as a form of revenue generation [67, 68]. Indeed, Section 1502 of the Dodd-Frank Act— a de-facto prohibition on US manufacturers’ sourcing of tin, tantalum, and tungsten from the Democratic Republic of the Congo—undercut local armed groups’ profits but increased the looting of civilians and violent clashes over mining territories [69, 70]. Alternatively, AP management may trigger protests if it both limits local communities’ access to the resources within protected areas and fails to provide local communities with alternative sources of economic opportunity, similar to the local effects of mining concessions [71].

Accordingly, we use the Armed Conflict Location and Event Database [72] to measure the presence of three forms of conflict in and around the protected areas in our sample: violence against civilians (“civilian targeting”), battles, and protests and riots. We define our spatial unit of observation as the area within a protected area’s boundaries plus a 25-kilometer buffer around the protected area’s boundaries. We include these buffer zones in our analysis to capture possible spillover in AP management’s effect on conflict. We use relatively small buffers—in comparison to research investigating the spillover effects of climatic shocks on conflict [73]—because we focus on local security conditions. Given the scale of the mechanisms described above, we hesitate to attribute distant changes in conflict to AP management. SI A.6.2 discusses this decision in greater detail and reports a robustness check where we recompile our results using smaller and larger buffers (Figure S18).

We find suggestive and concerning evidence that AP makes civilian targeting more likely in and around the protected areas it comes to manage (Figure 3, Row 6). The probability of any civilian targeting occurring in AP-managed protected areas increases by 7.7 percentage points post-transference. This estimate represents a 47.2% increase in the presence of civilian targeting relative to the control mean, and in the 10