Restoring forest landscapes for biodiversity conservation and rural livelihoods: a spatial optimisation model

Restoring forest landscapes for biodiversity conservation and rural livelihoods: a spatial optimisation model

Background

Conserving nature in the presence of human settlements is especially challenging in areas where livelihoods are largely based on locally available natural resources. The restoration of forests in such contexts calls for the identification of sites and actions that improve biodiversity protection, and ensure the provision of and accessibility to other forest-related ecosystem services. This paper introduces an integer-linear programming (ILP) approach to identify reforestation priorities that achieve such goals.

Research goals & methods

The model is designed to identify reforestation sites to encourage timber harvesting from secondary instead of primary forest, given a number of constraints and prioritization factors. The model incorporates the reforestation budget; potential land use conversions; the travel time to reach harvestable forest; conservation of landscape diversity; timber demands; and erosion risk. As an input, suitability maps, generated through a combination of ecological criteria, are used to prioritize the selection of reforestation sites. A test application to a 430 km2 area in Central Chiapas, Mexico, resulted in compact patches and thus a manageable reforestation plan. Trade-offs were found between the amount of soil stabilization possible and the prioritization goals, although these were deemed acceptable.

Conclusions & takeaways

The method aims to demonstrate that restoration actions can be spatially designed to benefit both nature and people with minimal losses on both sides.

Reference: 

Orsi F, Church RL, Geneletti D. Restoring forest landscapes for biodiversity conservation and rural livelihoods: A spatial optimisation model. Environmental Modelling & Software. 2011;26:1622–1638. doi:10.1016/j.envsoft.2011.07.008.

Affiliation: 

  • Dept. of Civil and Env. Engineering, University of Trento, Trento, Italy
  • Dept. of Geography, University of California – Santa Barbara, Santa Barbara, CA, USA
  • Sustainability Science Program, Harvard University, Cambridge, MA, USA