Wood and bark water content and monthly stem growth in Amazonian tree species

ABSTRACT The knowledge of how trees respond to microclimate variability is important in the face of climate changes. The objectives of this study were to examine the variation in wood water content (WWC) and bark water content (BWC) in Amazonian trees, as well as to assess the effect of microclimatic variability on monthly diameter growth rates (DGR). We extracted a core sample from each of 120 trees (28 species) and determined WWC and BWC on a fresh matter basis. DGR was measured monthly during the 12 months of 2007. The effect of microclimatic variability on DGR was analyzed by redundancy analysis. Average BWC and WWC were 53.4% and 34.7%, respectively, with a large variation in stem water content among species (BWC = 36.2−67.1%; WWC = 26.4−50.8%). There was no significant relationship between stem diameter and WWC or BWC, nor between DGR and wood density (p > 0.05). However, wood density was negatively correlated with WWC (r s = −0.69, p < 0.001). The high BWC emphasizes the importance of the bark tissue in Amazonian trees. Contrary to expectations, variability of monthly irradiance, rainfall and temperature had no effect on DGR (p > 0.20). The unresponsiveness of DGR to microclimatic variability, even in an above-average rainy year such as 2007, indicates that other parts of the tree may have greater priority than the stem for carbon allocation during the dry season.

Determination of hemicellulose, cellulose, holocellulose and lignin content using FTIR in Calycophyllum spruceanum (Benth.) K. Schum. and Guazuma crinita Lam.

Capirona (Calycophyllum spruceanum (Benth.) K. Schum.) and Bolaina (Guazuma crinita Lam.) are fast-growing Amazonian trees with increasing demand in timber industry. Therefore, it is necessary to determine the content of cellulose, hemicellulose, holocellulose and lignin in juvenile trees to accelerate forest breeding programs. The aim of this study was to identify chemical differences between apical and basal stem of Capirona and Bolaina to develop models for estimating the chemical composition using Fourier transform infrared (FTIR) spectra. FTIR-ATR spectra were obtained from 150 samples for each species that were 1.8 year-old. The results showed significant differences between the apical and basal stem for each species in terms of cellulose, hemicellulose, holocellulose and lignin content. This variability was useful to build partial least squares (PLS) models from the FTIR spectra and they were evaluated by root mean squared error of predictions (RMSEP) and ratio of performance to deviation (RPD). Lignin content was efficiently predicted in Capirona (RMSEP = 0.48, RPD > 2) and Bolaina (RMSEP = 0.81, RPD > 2). In Capirona, the predictive power of cellulose, hemicellulose and holocellulose models (0.68 < RMSEP < 2.06, 1.60 < RPD < 1.96) were high enough to predict wood chemical composition. In Bolaina, model for cellulose attained an excellent predictive power (RMSEP = 1.82, RPD = 6.14) while models for hemicellulose and holocellulose attained a good predictive power (RPD > 2.0). This study showed that FTIR-ATR together with PLS is a reliable method to determine the wood chemical composition in juvenile trees of Capirona and Bolaina.

Determination of hemicellulose, cellulose, holocellulose and lignin content using FTIR in Calycophyllum spruceanum (Benth.) K.Schum. and Guazuma crinita Lam.

Capirona (Calycophyllum spruceanum (Benth.) K. Schum.) and Bolaina (Guazuma crinita Lam.) are fast-growing Amazonian trees with increasing demand in timber industry. Therefore, it is necessary to determine the content of cellulose, hemicellulose, holocellulose and lignin in juvenile tress to accelerate forest breeding programs. The aim of this study was to identify chemical differences between apical and basal stem of Capirona and Bolaina to develop models for estimating the chemical composition using Fourier transform infrared (FTIR) spectra. FTIR-ATR spectra were obtained from 150 samples for each specie that were 1.8 year-old. The results showed significant differences between the apical and basal stem for each species in terms of cellulose, hemicellulose, holocellulose and lignin content. This variability was useful to build partial least squares (PLS) models from the FTIR spectra and they were evaluated by root mean squared error of predictions (RMSEP) and ratio of performance to deviation (RPD). Lignin content was efficiently predicted in Capirona (RMSEP = 0.48, RPD > 2) and Bolaina (RMSEP = 0.81, RPD > 2). In Capirona, the predictive power of cellulose, hemicellulose and holocellulose models (0.68 < RMSEP < 2.06, 1.60 < RPD < 1.96) were high enough to predict wood chemical composition. In Bolaina, model for cellulose attained an excellent predictive power (RMSEP = 1.82, RPD = 6.14) while models for hemicellulose and holocellulose attained a good predictive power (RPD > 2.0). This study showed that FTIR-ATR together with PLS is a reliable method to determine the wood chemical composition in juvenile trees of Capirona and Bolaina.

Soil Water Uptake by Amazonian Trees and Simulation of Impacts on Energy Fluxes and Soil Moisture Dynamics at the LBA Flux Towers

Observational and modeling studies show that a deeper soil water uptake by tree roots is required for evapotranspiration in the Amazon Basin. Therefore, this study performed three numerical modeling experiments with different depths of soil water uptake by Amazonian tree roots using the Eta/CPTEC regional climate model. In the “Control” and “Deep Soil Shallow Root” experiments the depth of soil water uptake by tree roots is set up with 2 m, while in the “Deep Soil Deep Root” experiment this depth is set up with 7.2 m, according to the observational studies. The energy balance at the LBA flux towers is better simulated in the “Deep Soil Deep Root” experiment than in other experiments. Moreover, with the “Deep Soil Deep Root” experiment the seasonality of evapotranspiration is reduced in the regions where there is strong seasonality of precipitation, while the seasonality of moisture is reduced in shallow soil layers and increases in the deeper soil layers. In addition, in the regions with strong seasonality of precipitation the deeper soil layers have an inter-annual hydrological memory, and in all regions the soil moisture memory is inversely related to the amount of precipitation, with different behaviors in each soil layer. In conclusion, the deeper soil water uptake by the Amazonian trees is important for the energy balance and soil moisture dynamics in the Amazon Basin.

Sensory characteristics of wood from naturally fallen Amazonian trees for manufacture of products in Extractive Reserves

In view of the national and international demand for wood for industrial use, solutions are being created to combat and reduce deforestation. One such solution is to use wood from naturally fallen trees. However, there has been limited evaluation of the technological potential of this material. This study therefore aimed to assess the general characteristics of wood from naturally fallen tree species in the Auatí-Paraná Extractive Reserve (RESEX), for potential use in product development. The characteristics analyzed were color, texture, grain, heartwood, sapwood and density. The species of naturally fallen trees were assessed using online databases, specialized literature and the xylotheque at the Wood Anatomy and Identification Laboratory of the National Institute of Amazonian Research (LAIM/INPA). This study and its results confirm the great quantity and quality of wood from naturally fallen trees with technological potential for the development of products, based on the classification of the sensory characteristics of the woods.