Effect of Climatic Variables on Abundance and Dispersal of Lecanosticta acicola Spores and Their Impact on Defoliation on Eastern White Pine.

The disease complex white pine needle damage (WPND), first reported in 2006, has now escalated to an epidemic state across the northeastern United States. Although this complex is composed of several fungal species, Lecanosticta acicola is considered to be the primary causal agent. Knowledge regarding the epidemiology, specific climatic factors that affect the spread of L. acicola on eastern white pine (Pinus strobus) in natural forest settings, and potential risks repeated defoliation may have on tree health is limited. Therefore, this study examined how climatic variables affect the abundance and distance of spore dispersal of L. acicola and compared litterfall caused by defoliation versus natural needle abscission. Conidia were observed on spore traps from May through August, with a peak in abundance occurring in June, corresponding to the defoliation of second- and third-year foliage measured in litter traps. During peak spore production, relative humidity and the occurrence of rainfall was found to have the greatest influence on spore abundance. Our results will aid managers in determining how far from infected trees natural regeneration will likely be affected and predicting future disease severity based on climatic conditions.

Imaging spectrometry for Earth remote sensing.

Imaging spectrometry, a new technique for the remote sensing of the earth, is now technically feasible from aircraft and spacecraft. The initial results show that remote, direct identification of surface materials on a picture-element basis can be accomplished by proper sampling of absorption features in the reflectance spectrum. The airborne and spaceborne sensors are capable of acquiring images simultaneously in 100 to 200 contiguous spectral bands. The ability to acquire laboratory-like spectra remotely is a major advance in remote sensing capability. Concomitant advances in computer technology for the reduction and storage of such potentially massive data sets are at hand, and new analytic techniques are being developed to extract the full information content of the data. The emphasis on the deterministic approach to multispectral data analysis as opposed to the statistical approaches used in the past should stimulate the development of new digital image-processing methodologies.