A new article in Forest Ecology and Management reports an indirect remote sensing method to map the distribution of banmara, a cryptic forest understorey invasive species of Nepal.

This study by Chudamani Joshi of ITC and others used an indirect remote sensing method to map the seed production of Banmara (Chromolaena odorata), one of the world's 100 worst invasive species. The study was executed in lowland Shorea robusta forest in Nepal where Chromolaena invaded the understorey of degraded forest.

A Landsat ETM+ image processed through a neural network predicted 89% and 81% of forest canopy density and light intensity reaching the understorey, respectively. These models were inverted to predict Chromolaena seed productivity. Light intensity determined 93% of the variation in log₁₀ seed production per plant. Chromolaena failed to produce seed below a light intensity of 6.5 mJ m⁻² day⁻¹. Further analysis revealed that Chromolaena was absent above this light intensity in case of a high biomass of other shrub and herb species, a situation occurring in the absence of grazing. Remote sensing has so far not been applied to map invaders species like Chromolaena which do not dominate the canopy.

The study suggest that other species control Chromolaena through competitive exclusion in the absence of grazing, whereas grazing breaks the dominance of these other species thus creating the conditions for Chromolaena to attain canopy dominance.

Predicted Chromolaena cover and seed production per plant were combined into a map displaying the total seed production per unit area. Such map displaying seed producing sites could be used to significantly reduce the costs of controlling Chromolaena infestation by providing information on the spatial segregation of source and sink populations, which will support efficient habitat ranking to restore invaded areas and protect non-invaded ecosystems. This may prove particularly valuable when implementing control measures under circumstances of limited capital and manpower.

Chudamani Joshi, Jan De Leeuw, Jelte van Andel, Andrew K. Skidmore, Hari Datt Lekhak, Iris C. van Duren and Nawang Norbu. Indirect remote sensing of a cryptic forest understorey invasive species. Forest Ecology and Management. Available online 13 February 2006.