Annual Report: CIRAD 2007

Selective logging can have various impacts on the demography and genetic diversity of commercial timber species populations. These operations have major consequences by eliminating large reproductive trees, ie reducing the pollen and seed production potential, and increasing the mean distance between reproductive trees. Demography and gene flows may be negatively affected and genetic diversity within the concerned populations can be altered. In contrast, logging also opens the canopy, thus increasing the light availability for all forest strata, which can stimulate the survival and growth of young trees, and in turn offset the loss of the largest trees.

Sustainable timber production therefore depends on the balance between the two phenomena, and forest managers require decision-making guidelines to enable them to preserve timber species populations and their genetic diversity in the long term. CIRAD and partners have developed prediction models to simulate forest dynamics and gene flows for several biological model species to be used as tools for studying and quantifying the effects of logging in French Guiana and for drawing up decision-making guidelines.

Model for basralocus

The most comprehensive model currently available was designed for basralocus (Dicorynia guianensis), a major commercial species. It was designed on the basis of data concerning the life cycle of the species, from seed production to adult mortality, and gene flows, derived from genotyping most of the reproductive and juvenile trees in a plot at the Paracou field station. In the model, the spatiotemporal dynamics of a basralocus population interacts with the dynamics of populations of all other forest tree species, whose life cycle descriptions are not as detailed. All of these models were integrated under the name Selva in the CAPSIS* tree growth and forest dynamics simulation software platform.

Selva can simulate different logging scenarios, eg by adjusting the minimum diameter cutting limit or the length of the logging cycle, and assess changes in demographic and genetic characteristics of the basralocus population relative to its natural undisturbed evolution.

Enhancing prediction

These studies generated essential data on the basralocus life cycle, but all aspects have not yet been covered sufficiently, eg data to accurately describe the mortality at different development stages are still lacking. These imperfections could lead to model prediction uncertainties. A sensitivity analysis revealed that mortality in the juvenile phase is the process that has the greatest effect on the predictions. Recalibration of this component from a broader database could enhance the prediction reliability, which should be a priority for the coming years. The model could also be improved by explicitly describing the stimulation of basralocus juvenile survival and growth after opening of the canopy by logging or natural tree falls.

Forest dynamics, gene flows and logging

In the model, gene flows are associated with several forest dynamics processes: seed production, which increases with the size of the reproductive tree; spatial seed dispersal patterns; and the survival and growth of trees at different stages. Selective logging affects these relationships by eliminating the largest reproductive trees. Simulations performed to date indicate that logging leads especially to reductions in population sizes, whereas the impact on genetic diversity does not seem to be as serious. Decision-making guidelines that are poorly adapted to the basralocus demography features could thus affect the future of this species—more by reducing its regeneration potential than by depleting its genetic base.

* CAPSIS: Computer-Aided Projection of Strategies in Silviculture

Contact

Holger Wernsdörfer, E-mail ; Sylvie Gourlet-Fleury, Dynamics of Natural Forests (UPR)

Partenaires

• AgroParisTech (France)
• Bureau des ressources génétiques (BRG, France)
• Groupement d’intérêt public Ecosystèmes forestiers (GIP ECIFOR, France)
• Institut national de la recherche agronomique (INRA, France)
• Muséum national d'histoire naturelle (France)

For further information

• Dreyfus P. et al., 2005. Couplage de modèles de flux de gènes et de modèles de dynamique forestière. Les Actes du BRG, 5 : 231-250.
• Gourlet-Fleury S. et al. , 2005. Using models to predict recovery and assess tree species vulnerability in logged tropical forests: a case study from French Guiana. Forest Ecology and Management, 209 : 69-86.
• Gourlet-Fleury S. et al. (éd.), 2004. Ecology and management of a neotropical rainforest. Paris, Elsevier, 311 p.
• Wernsdörfer H. et al., 2008. Sensitivity of a complex forest dynamics model. Ecological Modelling (soumis).