Effects of uniform-allocation constraints in networked common-pool resource extraction games

Author:

Schauf AndrewORCID,Oh PoongORCID

Abstract

Abstract Communities that share common-pool resources (CPRs) often coordinate their actions to sustain resource quality more effectively than if they were regulated by some centralized authority. Networked models of CPR extraction suggest that the flexibility of individual agents to selectively allocate extraction effort among multiple resources plays an important role in maximizing their payoffs. However, empirical evidence suggests that real-world CPR appropriators may often de-emphasize issues of allocation, for example by responding to the degradation of a single resource by reducing extraction from multiple resources, rather than by reallocating extraction effort away from the degraded resource. Here, we study the population-level consequences that emerge when individuals are constrained to apply an equal amount of extraction effort to all CPRs that are available to them within an affiliation network linking agents to resources. In systems where all resources have the same capacity, this uniform-allocation constraint leads to reduced collective wealth compared to unconstrained best-response extraction, but it can produce more egalitarian wealth distributions. The differences are more pronounced in networks that have higher degree heterogeneity among resources. In the case that the capacity of each CPR is proportional to its number of appropriators, the uniform-allocation constraint can lead to more efficient collective extraction since it serves to distribute the burden of over-extraction more evenly among the network’s CPRs. Our results reinforce the importance of adaptive allocation in self-regulation for populations who share linearly degrading CPRs; although uniform-allocation extraction habits can help to sustain higher resource quality than does unconstrained extraction, in general this does not improve collective benefits for a population in the long term.

Funder

Nanyang Technological University

Publisher

IOP Publishing

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Information Systems

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