Soil water dynamics and litter production in eucalypt and native vegetation in southeastern Brazil

High productivity of eucalypt plantations is the result of advances in research that have led to gradual improvements in intensive silvicultural technology. High productivity notwithstanding, eucalypt plantations remain the focus of environmental concerns. Our study aimed to compare the soil water regime, litter fall and nutrients dynamics either in a fragment of native forest or in an adjacent stand of growing eucalypt. We took field measurements during the first three years of eucalypt plantation in a sandy soil in the southeastern region of Brazil. Soil moisture and internal drainage were higher during the early stages of growth of the eucalypt stand, as compared with native vegetation. However, one and a half years after planting, available soil water was similar in both vegetations. Higher water availability under the eucalypt stand during the first year occurs because of silvicultural operations (soil preparation and weed control) and the small size of eucalypt trees; these factors increase water infiltration and decrease transpiration. Total leaf fall, over the study period, was similar for both ecosystems; however, differences were observed in the winter and early spring of 2010. The transfer of nutrients to soil by leaf fall was similar except for N and S, which was higher in native vegetation. Nitrogen concentration in the soil solution was higher in native vegetation, but K was higher under the eucalypt stand, mainly to a depth of up to 0.2 m

Assessing biomass based on canopy height profiles using airborne laser scanning data in eucalypt plantations

This study aimed to map the stem biomass of an even-aged eucalyptus plantation in southeastern Brazil based on canopy height profile (CHPs) statistics using wall-to-wall discrete return airborne laser scanning (ALS), and compare the results with alternative maps generated by ordinary kriging interpolation from field-derived measurements. The assessment of stem biomass with ALS data was carried out using regression analysis methods. Initially, CHPs were determined to express the distribution of laser point heights in the ALS cloud for each sample plot. The probability density function (pdf) used was the Weibull distribution, with two parameters that in a secondary task, were used as explanatory variables to model stem biomass. ALS metrics such as height percentiles, dispersion of heights, and proportion of points were also investigated. A simple linear regression model of stem biomass as a function of the Weibull scale parameter showed high correlation (adj.R2 = 0.89). The alternative model considering the 30th percentile and the Weibull shape parameter slightly improved the quality of the estimation (adj.R2 = 0.93). Stem biomass maps based on the Weibull scale parameter doubled the accuracy of the ordinary kriging approach (relative root mean square error = 6 % and 13 %, respectively)