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Uneven-aged management options
to promote forest resilience:
effects of group selection and harvesting intensity
The 9th IUFRO International Conference on Uneven-aged Silviculture
17/06/2014
Presented by Guillaume LAGARRIGUESCo-authors : Valentine Lafond , Thomas Cordonnier , Benoît Courbaud
National Research Institute of Science and Technology for Environment and Agriculture (IRSTEA) – Center of Grenoble
With the collaboration of Andreas Zingg
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL)
Adaptation of forest management to climate change
Uncertainties about climate change consequences(Beniston et al. 2007)
Precautionary approach: promote forest resilience by enhancing species diversity and uneven-aged structure(Puettman 2011 ; Seidl et al. 2011)
Managements options to promote forest resilience
Create forest gaps by group selection
Intensify harvesting
Enhance natural regeneration
Regenerate shade-intolerant species
(Streit 2009)
(Diaci and
Firm 2011)
Uneven-aged silviculture framework(Cordonnier et al. 2008)
Simulation experiments
Forest dynamics simulation model
Silviculture algorithmInitial state
Design of simulation experiments (Lafond et al. 2014)
Stand area : 4ha ; Simulation period: 150 years, with cuts every 10 years
• 2nd : harvesting intensification with individual selection
• 4 modalities of harvesting intensity
• 3rd : harvesting intensification with group selection (500 m²)
• 4 modalities of harvesting intensity
ILLUSTRATION• 1st experiment : spatialization of
cuts• Standard harvesting intensity• 7 modalities of spatializationo Individual selectiono Small groups (20 – 1 000m²)o One large gap at a time
Initial state
Diameter class
Ab
un
dan
ce (
tree
s /
ha)
1905
Permanent plot located in the canton of Bern in Swiss, monitored by the WSL of Zürich
Samsara : an individual-based forest model
Model calibration for this study
Diameter class
Ab
un
dan
ce (
tree
s /
ha)
1905 – Initial state
Inverse modeling to calibrate the stand dynamics model so that model predictions fit to historical data (Lagarrigues et al., submitted)
Observed data in 2009
Samsara
Calibration of model
parameters
Predictions
Modeling natural regeneration
Number of recruits
% of full light
Limitation by low light conditions
Limitation by low density of seed
bearers and competition with pioneer species
Norway spruce
Silver fir
Management modeling by a silviculture algorithm (Lafond et al. 2013)
Øh = 27,5 cm
Ø (cm)
N (t/ha)Gh
G max
G standard
G min
G (m²/ha)
Results of the 1st experiment (spatial aggregation of cut trees)
Species mix(% of spruce basal area)
Aggregation area (m²) Aggregation area (m²)
Species balance
Size diversity(Gini index)
Uneven-aged
Even-aged
2nd experiment (harvesting intensity with individual selection)
Species mix(% of spruce basal area)
Proportion of potential harvesting (%)
Proportion of potential harvesting (%)
Size diversity(Gini index)
Species balanceUneven-aged
Even-aged
3rd experiment (harvesting intensity with group selection)
Species mix(% of spruce basal area)
Proportion of potential harvesting (%)
Proportion of potential harvesting (%)
Species balance
Size diversity(Gini index)
Uneven-aged
Even-aged
Management durability
1st experiment 2nd experiment 3rd experiment
Aggregation area (m²)Proportion of potential
harvesting (%)Proportion of potential
harvesting (%)
Bas
al a
rea
(m²/
ha)
Main conclusions and limitationsCreating gaps and increasing harvesting intensity are both key
management options to drive species mix and size diversity in spruce-fir stands
Small-sized gaps (around 500m²) are sufficient to enhance natural regeneration, but large openings (> 1 000m²) may be necessary to increase proportion of shade-intolerant species such as spruce
Harvesting intensity: trade-off between durability and spruce maintenance
Group selection amplify harvesting intensity effects : forest management coupling both options should be applied with care
Simulations are very sensitive to regeneration parameters (see Lafond et al. 2014; Courbaud et al., submitted)
• Regeneration response to light must be calibrated accurately• Conclusions only valid in forest conditions close to those used for model calibration
Research perspectives with this silviculture algorithm
• Distinguishing thinning from harvesting operations
• Driving species mix directly by choosing the trees to harvest according to their species
• Driving forest stand structure and composition for biodiversity conservation
• Preserving rare species• Sparing some very large trees• Leaving more dead wood in stands
=> See poster session : Studying the response of timber production and biodiversity conservation to uneven-aged silviculture in mountain forests (Lafond et al.)
Thinning potential
Harvesting potential
Harvesting diameter
Thinning diameter
Funding and acknowledgments• Guillaume Lagarrigues PhD
• The French Environment and Energy Management Agency (ADEME)• The French National Forest Office (ONF)• IRSTEA (Grenoble, France)
• Projects• French research program “Biodiversity, Forest Management and Public
Policy” (BGF)• European Research project “Advanced multifunctional forest management
in European mountain ranges” (ARANGE)
• Data for model calibration• Swiss Federal Institute for Forest, Snow and Landscape Research (Zürich)
Thank you for your attention !
References
Beniston, M., Stephenson, D. B., Christensen, O. B., Ferro, C. A. T., Frei, C., Goyette, S., Halsnaes, K., Holt, T., Jylha, K., Koffi, B., Palutikof, J., Schoell, R., Semmler, T. & Woth, K. (2007). Future extreme events in European climate: an exploration of regional climate model projections. Climatic Change 81: 71-95.
Cordonnier, T., Courbaud, B., Berger, F. & Franc, A. (2008). Permanence of resilience and protection efficiency in mountain Norway spruce forest stands: A simulation study. Forest Ecology and Management 256(3): 347-354.
Courbaud, B., de Coligny, F. & Cordonnier, T. (2003). Simulating radiation distribution in a heterogeneous Norway spruce forest on a slope. Agricultural and Forest Meteorology 116(1-2): 1-18.
Courbaud, B., Goreaud, F., Dreyfus, P. & Bonnet, F. R. (2001). Evaluating thinning strategies using a tree distance dependent growth model: some examples based on the CAPSIS software uneven-aged spruce forests module. Forest Ecology and Management 145(1-2): 15-28.
Courbaud, B., Lafond, V., Lagarrigues, G., Cordonnier, T., Vieilledent, G. & De Coligny, F. (submitted). Critical steps to build and evaluate a mechanistic ecological model: a worked example with the Samsara.2 forest dynamics model. Ecological Modelling.
Diaci, J. & Firm, D. (2011). Long-term dynamics of a mixed conifer stand in Slovenia managed with a farmer selection system. Forest Ecology and Management 262(6): 931-939.
Lafond, V., Lagarrigues, G., Cordonnier, T. & Courbaud, B. (2014). Uneven-aged management options to promote forest resilience for climate change adaptation: effects of group selection and harvesting intensity. Annals of Forest Science 71(2): 173-186.
Lagarrigues, G., Jabot, F., Lafond, V. & Courbaud, B. (Submitted). Approximate Bayesian Computation to recalibrate ecological models with large scale data: illustration with a forest simulation model. Ecological Modelling.
Puettmann, K. J. (2011). Silvicultural Challenges and Options in the Context of Global Change: "Simple" Fixes and Opportunities for New Management Approaches. Journal of Forestry 109(6): 321-331.
Seidl, R., Rammer, W. & Lexer, M. J. (2011). Adaptation options to reduce climate change vulnerability of sustainable forest management in the Austrian Alps. Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere 41(4): 694-706.
Uneven-aged silviculture give managers many options to harvest wood while preserving forest resilience. Among them, we chose group selection and is favorably considered as forest gaps can enhance natural regeneration, especially for shade-intolerant species. Intensify harvesting is another interesting option that can allow reduce the amount of very large trees, reducing thus the risk of tree senescence and diseases while enhancing also natural regeneration by providing more light to the ground. However, such fine details about uneven-aged management have been poorly studied until now, and many questions remains about the efficiency of these options and the scales at which they should preferably applied.