Predicting Primary Forest Recovery in
a Fragmented Landscape: a Restoration Roadmap
Botany Department, North Carolina State University
North Carolina, USA
To develop a predictive model for primary forest species establishment following disturbance, I propose to conduct experiments to measure dispersal and recruitment of primary forest species in three different habitats: primary forest, secondary forest, and pasture, and determine the relationship between these variables and seed characters along the environmental gradients found in the three habitat types. This information will be used to construct a model that will generate establishment probabilities for species under specified environmental conditions. This model will be used to determine which primary forest species will require intensive management (seeding, planting, etc) under a variety of environmental conditions. An interesting study site I have identified is the Nam Ha National Preserve Area in northwestern Laos. According to satellite imagery, this 222,000 hectare preserve is a mosaic of primary forest, secondary forest, and recently abandoned pasture. Furthermore, the dominant primary forest trees in the lowland moist forest in Laos are wind-dispersed Dipterocarps, which may present the opportunity to study a novel relationship between dispersal traits and environmental conditions.