Allometric relationships predicting foliar biomass and leaf area:sapwood area ratio from tree height in five Costa Rican rain forest species.

We developed allometric equations to predict whole-tree leaf area (A(l)), leaf biomass (M(l)) and leaf area to sapwood area ratio (A(l):A(s)) in five rain forest tree species of Costa Rica: Pentaclethra macroloba (Willd.) Kuntze (Fabaceae/Mim), Carapa guianensis Aubl. (Meliaceae), Vochysia ferru-gi-nea Mart. (Vochysiaceae), Virola koshnii Warb. (Myristicaceae) and Tetragastris panamensis (Engl.) Kuntze (Burseraceae). By destructive analyses (n = 11-14 trees per species), we observed strong nonlinear allometric relationships (r(2) > or = 0.9) for predicting A(l) or M(l) from stem diameters or A(s) measured at breast height. Linear relationships were less accurate. In general, A(l):A(s) at breast height increased linearly with tree height except for Penta-clethra, which showed a negative trend. All species, however, showed increased total A(l) with height. The observation that four of the five species increased in A(l):A(s) with height is consistent with hypotheses about trade--offs between morphological and anatomical adaptations that favor efficient water flow through variation in the amount of leaf area supported by sapwood and those imposed by the need to respond quickly to light gaps in the canopy.

Calibration and assessment of seasonal changes in leaf area index of a tropical dry forest in different stages of succession.

A simple measure of the amount of foliage present in a forest is leaf area index (LAI; the amount of foliage per unit ground surface area), which can be determined by optical estimation (gap fraction method) with an instrument such as the Li-Cor LAI-2000 Plant Canopy Analyzer. However, optical instruments such as the LAI-2000 cannot directly differentiate between foliage and woody components of the canopy. Studies investigating LAI and its calibration (extracting foliar LAI from optical estimates) in tropical forests are rare. We calibrated optical estimates of LAI from the LAI-2000 with leaf litter data for a tropical dry forest. We also developed a robust method for determining LAI from leaf litter data in a tropical dry forest environment. We found that, depending on the successional stage of the canopy and the season, the LAI-2000 may underestimate LAI by 17% to over 40%. In the dry season, the instrument overestimated LAI by the contribution of the woody area index. Examination of the seasonal variation in LAI for three successional stages in a tropical dry forest indicated differences in timing of leaf fall according to successional stage and functional group (i.e., lianas and trees). We conclude that when calculating LAI from optical estimates, it is necessary to account for the differences between values obtained from optical and semi-direct techniques. In addition, to calculate LAI from litter collected in traps, specific leaf area must be calculated for each species rather than from a mean value for multiple species.

Baseline assessment for environmental services payments from satellite imagery: a case study from Costa Rica and Mexico.

In this study we evaluate the accuracy of four global and regional forest cover assessments (MODIS, IGBP, GLC2000, PROARCA) as tools for baseline estimation. We conduct this research at the national scale for Costa Rica and for two tropical dry forest study sites in Costa Rica (Santa Rosa) and Mexico (Chamela-Cuixmala). We found that at the national level, the total forest cover accuracy of the four land cover maps was inflated due to an overestimation of forest in areas with an evergreen canopy. However, the four maps greatly underestimated the extent of the deciduous forest (dry forest); an ecosystem that faces high deforestation pressure and poses complications to the mapping of its extent from remotely sensed data. For the tropical dry forest sites, all maps have low forest cover accuracies (mean for Santa Rosa: 27%; mean for Chamela-Cuixmala: 56%). This has implications for policy implementation.