PARENT SESSION
Poster Session #38: Vegetation Analysis.
Wednesday, August 7. Presentation from 5:00 PM to 6:30 PM. Exhibit Hall B & C, TCC

Estimating leaf area in pine stands using hemispherical photography and tree allometrics.

Innes, James^*,1, Ducey, Mark², ¹ USDA Forest Service, Durham, New Hampshire² University of New Hampshire, Durham, New Hampshire

ABSTRACT- Hemispherical photography (HP) and tree allometrics are commonly used to predict leaf area (L) in forest canopies. We examined the predictive abilities of HP and allometrics at estimating L in eleven forest stands dominated by eastern white pine (Pinus strobus). Direct estimates of L were obtained in each stand using litter traps. Analysis of covariance (ANCOVA), with direct L as a covariate, was used to test six factors of HP implementation and analysis known to affect indirect estimation of L: (i) averaging method (linear vs. logarithmic), (ii) model type (elliptical vs. inversion), (iii) number of rings averaged (all vs. mid-rings) (iv) photo exposure, (v) camera height, and (vi) sky conditions (e.g. sunrise, sunset, overcast). Allometric relationships were compared with direct estimates of L using regression analysis. Results indicate that exposure, averaging method and the number of rings averaged accounted for more variation in the ANCOVA model than did the covariate. Sky conditions had a small effect on the model. The three allometric equations tested consistently underestimated L. These results suggest that indirect estimates of L obtained with HP are strongly influenced by technique and not actual canopy structure and that allometrics may not be applicable across sites.

KEY WORDS: Hemispherical photography, Leaf area