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Adapting the optimal selective-logging of Scots pine (Pinus sylvestris L.) stands in NE Spain to increasing CO2 concentrations

Author

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  • Mur, Ruben Javier
  • Goetz, Renan-Ulrich
  • Xabadia, Angels
  • Córdoba, Francesc
  • Gracia, Carles

Abstract

Predicted increases in CO2 concentrations will affect forest ecosystems. In particular, they will impact tree growth, which in turn affects reproduction and mortality and consequently, forest planning. This study integrates different climate change scenarios of future biogeochemical processes and an economic model into a forest management model to determine the optimal selective-logging regime of Scots pine stands. It analyzes the economic implications of the management changes in comparison with the business as usual strategy. Adaption to new climatic conditions shows that it is optimal to increase the number of standing trees and to reduce the age of the logged trees. The results suggest that the failure to adapt the management regime has clear implications on the profitability of forests. Moreover, they show that higher mortality is likely to have a significant impact on the optimal forest management regime.

Suggested Citation

  • Mur, Ruben Javier & Goetz, Renan-Ulrich & Xabadia, Angels & Córdoba, Francesc & Gracia, Carles, 2014. "Adapting the optimal selective-logging of Scots pine (Pinus sylvestris L.) stands in NE Spain to increasing CO2 concentrations," Journal of Forest Economics, Elsevier, vol. 20(3), pages 286-304.
    • Handle: RePEc:eee:foreco:v:20:y:2014:i:3:p:286-304
    DOI: 10.1016/j.jfe.2014.09.001
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    References listed on IDEAS

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    Keywords

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    JEL classification:

    • Q23 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Forestry
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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