Incentive-Based Invasive Species Control

Invasive species impose substantial economic and ecological costs globally, yet little is known about how to design efficient contracts for private removal efforts under conditions of moral hazard. We develop a spatially-explicit bioeconomic model that integrates optimal control theory with contract design to examine two-part compensation schemes that pay contractors for both time spent searching and species captured. Our theoretical framework demonstrates that when effort has both observable (time) and unobservable (search intensity) dimensions, pure piece-rate contracts may fail to incentivize adequate effort in low-productivity areas or when "cobra effect" constraints limit bounty payments. We test these predictions using comprehensive data from Florida’s Python Elimination Program, which employs novel two-part contracts to remove invasive Burmese pythons from the Everglades ecosystem. Exploiting within-parcel variation in hourly compensation rates over time, we find that a 10% increase in hourly payments generates approximately 20% more search effort, with effects operating primarily through the intensive margin (effort per hunter) rather than hunter participation. The responsiveness varies systematically with ecological productivity, consistent with our theoretical prediction that time-based payments become more important when piece-rate incentives are weak. Our results demonstrate that spatially-differentiated contract design can significantly improve cost-effectiveness compared to uniform compensation schemes, with important implications for invasive species management, conservation policy, and other environmental contexts where effort quality is difficult to observe.