Incentives for landscape restoration: Lessons from Shinyanga, Tanzania

J Environ Manage. 2021 Feb 15;280:111831. doi: 10.1016/j.jenvman.2020.111831. Epub 2020 Dec 23.

Abstract

Owing to high rates of land and forest degradation, there is consensus that forest landscape restoration is a global priority with the Bonn Challenge and the New York Declaration on Forests committing to restore about 350 Million hectares by 2030, globally. However, there is a need for incentives that motivate these restoration efforts and disincentives aimed at restricting activities that result in further land degradation. We provide insights and understanding of the incentives and disincentives measures applied within the forest restoration systems through a case study in the Shinyanga region of Tanzania. Incentives that have promoted forest landscape restoration in Shinyanga include; conservation benefits, education and information, Reducing Emissions from Deforestation and forest Degradation (REDD+), well-defined property rights & increasing land prices and awards while disincentives include; penalties, quotas and permits. Intrinsic incentives that are derived from self-desire within an individual such as conservation benefits and education & information were more preferred within Shinyanga region compared to extrinsic incentives which relied more on external factors such as REDD+ and awards. Nonetheless, a combination of both incentives and disincentives has led to the success of restoration in Shinyanga; positive incentives worked better for privately owned lands while regulatory disincentives worked better for communally owned restoration lands. High levels of social equity and trust have enabled the functioning of these incentives while a robust governance structure at the local level has been instrumental in enforcing the disincentives. There is need for government and all stakeholders to maintain and enhance the gains from restoration, especially empowering communities further, for these incentives to work.

Keywords: Disincentives; Ecosystem services; Forest landscape restoration; Incentives; Local knowledge and institutions.

MeSH terms

  • Conservation of Natural Resources*
  • Ecosystem
  • Forests
  • Motivation*
  • New York
  • Tanzania