Annals of Forest Science

, Volume 71, Issue 2, pp 173–186

Uneven-aged management options to promote forest resilience for climate change adaptation: effects of group selection and harvesting intensity

  • Valentine Lafond
  • Guillaume Lagarrigues
  • Thomas Cordonnier
  • Benoît Courbaud
Original Paper

DOI: 10.1007/s13595-013-0291-y

Cite this article as:
Lafond, V., Lagarrigues, G., Cordonnier, T. et al. Annals of Forest Science (2014) 71: 173. doi:10.1007/s13595-013-0291-y

Abstract

Context

Climate change is expected to increase forest vulnerability through disturbances such as windstorms and droughts. Forest managers are therefore investigating strategies to increase forest resistance and resilience, especially by promoting uneven-aged and mixed forests through group selection, and by reducing stand stocking and large trees proportion. However, there is little information on the long-term impacts of these two practices.

Aims

The objectives of this study were (1) to develop an original silviculture algorithm designed for uneven-aged management and (2) to use it to assess the effects of the above-mentioned management methods in long-term simulations.

Methods

We simulated individual and group selection techniques in order to study the effects of group size, harvesting intensity and their interactions on wood production, stand heterogeneity, and regeneration in mountain spruce–fir forests. We used the spatially explicit individual-based forest model Samsara2 to simulate forest dynamics.

Results

Our simulation results confirmed the positive effect of group selection practices on structure diversity and regeneration but not on spruce maintenance. Increasing harvesting intensity enabled forest destocking but decreased structure diversity and led to non-sustained yields for the most intensive scenarios.

Conclusion

As adaptation measure, we thus recommend moderate group selection harvesting creating 500 m2 gaps.

Keywords

Forest resilience Climate change adaptation Uneven-aged selection forest Thinning and harvesting algorithm Forest dynamics modeling 

Supplementary material

13595_2013_291_MOESM1_ESM.pdf (339 kb)
ESM 1Details on the main operations of the Uneven-aged Management Algorithm (UMA). This document gives more detailed information about the structure and the functioning of the algorithm used in that study. In particular, the input parameters which were not used in the present simulation experiments are presented here, as well as their role in the algorithm process. A specific emphasis is done on probability weightings, with an explanation of the use of these parameters (Species proportion power and Local density power) and of the weighted random selection process. Finally, the determination of cutting quantities is more detailed and functioning diagrams of the harvesting and thinning operations are added. (PDF 339 kb)
13595_2013_291_MOESM2_ESM.pdf (171 kb)
ESM 2Summary tables of the simulation experiment results. This file contains one table per simulation experiment (Exp1, Exp2, and Exp3). Each table consists in nine lines: one for each output variable. For each line, the three sub-lines correspond to the three dates considered to analyze the results. The columns represent the different modalities used for each experiment (Aggregation area for Exp1, Harvesting proportion for Exp2 and Exp3). For each modality, the results are detailed within three sub-columns: mean, SD (mean value and associated standard deviation, computed on the five repetitions for each experiment modality), and Tukey (letters determined by Tukey’s tests). The Tukey’s tests were realized to compare the values obtained for the different modalities and give information on significant differences; they were therefore independently computed for each output variable and for each date. (PDF 171 kb)

Copyright information

© INRA and Springer-Verlag France 2013

Authors and Affiliations

  • Valentine Lafond
    • 1
  • Guillaume Lagarrigues
    • 1
  • Thomas Cordonnier
    • 1
  • Benoît Courbaud
    • 1
  1. 1.Irstea–EMGRSaint-Martin-d’Hères CedexFrance

Personalised recommendations