Emergence of social inequality in the spatial harvesting of renewable public goods

PLoS Comput Biol. 2020 Jan 8;16(1):e1007483. doi: 10.1371/journal.pcbi.1007483. eCollection 2020 Jan.

Abstract

Spatially extended ecological public goods, such as forests, grasslands, and fish stocks, are at risk of being overexploited by selfish consumers-a phenomenon widely recognized as the 'tragedy of the commons.' The interplay of spatial and ecological dimensions introduces new features absent in non-spatial ecological contexts, such as consumer mobility, local information availability, and strategy evolution through social learning in neighborhoods. It is unclear how these features interact to influence the harvesting and dispersal strategies of consumers. To answer these questions, we develop and analyze an individual-based, spatially structured, eco-evolutionary model with explicit resource dynamics. We report the following findings. (1) When harvesting efficiency is low, consumers evolve a sedentary consumption strategy, through which the resource is harvested sustainably, but with harvesting rates far below their maximum sustainable value. (2) As harvesting efficiency increases, consumers adopt a mobile 'consume-and-disperse' strategy, which is sustainable, equitable, and gives maximum sustainable yield. (3) A further increase in harvesting efficiency leads to large-scale overexploitation. (4) If costs of dispersal are significant, increased harvesting efficiency also leads to social inequality between frugal sedentary consumers and overexploitative mobile consumers. Whereas overexploitation can occur without social inequality, social inequality always leads to overexploitation. Thus, we identify four conditions that-while being characteristic of technological progress in modern societies-risk social inequality and overexploitation: high harvesting efficiency, moderately low costs of dispersal, high consumer density, and the tendency of consumers to adopt new strategies rapidly. We also show how access to global information-another feature widespread in modern societies-helps mitigate these risks.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biobehavioral Sciences*
  • Computational Biology
  • Consumer Behavior*
  • Ecology*
  • Humans
  • Socioeconomic Factors*

Grants and funding

Part of the research reported here has been developed during the Young Scientists Summer Program (YSSP) at the International Institute for Applied Systems Analysis (IIASA) in Laxenburg, Austria, for which JJ gratefully acknowledges travel support and a stipend from the Technology Information, Forecasting & Assessment Council (TIFAC), Government of India. ÅB gratefully acknowledges support from the Swedish Research Council (2015-3917). UD gratefully acknowledges support by the Austrian Science Fund (FWF) for the multinational research project "Mutualisms, Contracts, Space, and Dispersal (BIOCONTRACT)". The authors would like to thank Vishwesha Guttal for providing GPU computing facilities (via the DST-FIST and DBT-IISc Partnership Programme). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.