A method for measuring above- and below-ground C stocks in hillside landscapes

Abstract

. 2005. A method for measuring above-and below-ground C stocks in hillside landscapes. Can. J. Soil Sci. 85: 523-530. Information on C stocks in agriculture and forest ecosystems in hillside landscapes is limited. The objective of this study was to develop and test field methods to measure above-and below-ground C stocks in hillside landscapes. Above-ground biomass in agricultural system was determined by measuring weight of residues left after crop harvest. In degraded secondary forests, tree biomass was estimated using allometric equations developed from in situ measurements. Herbs + bushes and litter dry weight were measured in two 0.25-m 2 quadrats located within one 100-m 2 treed plots. Carbon stocks were determined after chemical analysis of plant tissue and soil samples by dry combustion. Geo-referenced cores were taken inside a 1-m-diameter soil sampling clock that allows for spatial and temporal monitoring of soil C changes. The clock was marked with 12 divisions to establish the exact location of present and future sampling points. The below-ground fraction of C (mineral soil and fine roots) amounted to nearly 95% of the total C stock in agricultural systems and between 57 and 82% in the case of forest systems. Soil C stocks in hillside agricultural soils were higher than those found in forested soils with 70% of the C stored below-ground residing in the 0-45 cm of soil. The field method detected differences in C stocks in pools associated with various vegetations and soils in hillside ecosystems. Les auteurs ont déterminé la biomasse aérienne des systèmes agricoles en pesant les débris végétaux après la récolte. Dans les forêts secondaires dégradées, la biomasse des arbres a été estimée au moyen d'équations allométriques élaborées à partir de relevés pris sur le terrain. On a mesuré le poids sec des herbacées et des broussailles ainsi que de la litière dans deux cadrats de 0,25 m 2 situés à l'intérieur d'une parcelle arborée de 100 m 2 . Les réserves de carbone ont été établies après analyse chimique des tissus végétaux et des échantillons de sol par combustion sèche. On a prélevé des carottes géoréférencées dans un cercle d'échantillonnage de un mètre permettant de suivre les variations spatiales et temporelles du C dans le sol. Le cercle a été divisé en 12 secteurs ce qui autorise la localisation exacte des points d'échantillonnage actuels et futurs. La fraction souterraine du C (sol minéral et radicelles) représente près de 95 % des stocks totaux de C des systèmes agricoles et 57 à 82 % des stocks des systèmes forestiers. Les systèmes agricoles en pente possèdent de plus grandes réserves de C que les sols forestiers, 70 % du C souterrain se retrouvant dans la couche de 0 à 45 cm. Cette méthode permet de déceler la fluctuation des réserves de C dans les puits associés aux divers types de végétation et de sol dans les écosystèmes en pente.

CONCENTRATION OF CARBON IN Pinus cembroides Zucc: MITIGATION POTENTIAL SOURCE OF GLOBAL WARMING

“…Lamlon and Savidge (2003) recommend grinding the samples to improve estimates of C, obtaining fractions under 10 μm, according to the methodology described by Yerena, Jiménez, Aguirre y Treviño (2011). The concentration of total C was obtained using the Solids Analyzer equipment (model 1020A of O·l·Analytical, USA), which analyzes solid sample (5 mg) by complete combustion at a temperature of 900 °C (Monreal et al, 2005). At least three replicates per sample were performed ensuring that the standard deviation did not exceed 0.6 % of the concentration of C (Lamlon & Savidge, 2003 mejorar las estimaciones de C, por lo que se obtuvieron fracciones menores de 10 μm, de acuerdo con la metodología descrita por Yerena, Jiménez, Aguirre y Treviño (2011).…”

“…At least three replicates per sample were performed ensuring that the standard deviation did not exceed 0.6 % of the concentration of C (Lamlon & Savidge, 2003 mejorar las estimaciones de C, por lo que se obtuvieron fracciones menores de 10 μm, de acuerdo con la metodología descrita por Yerena, Jiménez, Aguirre y Treviño (2011). La concentración de C total se obtuvo con un equipo Solids TOC Analyzer (modelo 1020A de O·l·Analytical, USA), que analiza muestras sólidas (5 mg) mediante combustión completa, a una temperatura de 900 °C (Monreal et al, 2005). Se hicieron al menos tres repeticiones por muestra procurando que la desviación estándar no rebasara el 0.6 % de la concentración de C (Lamlon & Savidge, 2003).…”

Simulación de los cambios de carbono orgánico del suelo en sistema de cultivo con higuerilla por el modelo RothC

“…La medición directa del COS se llevó a cabo con el método descrito por Monreal et al (2005). En el año 2011, en parcelas de aproximadamente 1.000 m Pesq.…”

Mass spectrometry of organic matter influenced by long-term pedogenesis and a short-term reclamation practice in an Oxisol of Brazil

“…The change in land use from natural grasslands to cropped land greatly affects the structural stability and decreases OM content in Oxisols of Brazil (Zinn et al 2005) and in Acrisols and Luvisols of Mexico and Mollisols of Canada (van Veen and Paul 1981;Monreal et al 2005). Intense conversion of forest to agricultural land has been a frequent land use change in areas of Brazil and other countries (Fearnside 1993).…”

“…In tropical areas, changes in land use shift the composition of vegetation, which in turn affects the amount and quality of SOM input and the diversity of soil macro-and microfauna and microbial communities (Lavelle and Pashanasi 1989;Johnson et al 2003). In general, agroforestry enhances nutrient storage after land conversion as compared with sole cropping systems in semitropical and tropical regions (Isaac et al 2005;Monreal et al 2005). Determining the impact of human activities on SOM in the tropics is of interest owing to sustainability risks to food security associated with increased agricultural, deforestation, and urbanization activities (Hernández and López 2002), and these activities can be examined using simulation models (Wendling et al 2014).…”