Biomass and carbon in subtropical forests: Overview of determinants, quantification methods and estimates

Milena Fermina Rosenfield, Alexandre F. Souza

Abstract


The study of biomass is an important tool to evaluate the amount of carbon stored in ecosystems. Biomass accumulation is determined by many factors that affect community structure and productivity but its quantification presents a challenge due to its high spatial variation. The main purposes of this paper are to describe the factors influencing tree biomass, indicate the main methods used in quantification and show the spatial distribution and lack of estimates in subtropical forests. In forest ecosystems, aboveground biomass is mostly comprised of trees. Its storage is dependent of many environmental and biotic factors, including temperature, rainfall, soil characteristics and species composition. The quantification is usually made by direct weighing in the field or estimated through allometric equations. Destructive methods require cutting and weighing the plant material, encompassing a large labor force and a long period of fieldwork. Indirect methods on the other side are based on estimates obtained through allometric mathematical models or remote sensing techniques that rely on data of tree parameters collected from the community. Aboveground biomass estimates vary considerably across regions and forest types. Tropical and temperate forests concentrate the majority of biomass studies and few of these have evaluated aboveground biomass in subtropical forests at broader scale. These forests have been shown to have high biodiversity and great potential for carbon accumulation. Studies that focus on evaluating the factors that affect biomass storage at different locations and that aim at developing and improving regional allometric equations are important for making reliable estimates of forest ecosystems. Finally establishing longterm study sites will provide relevant data for monitoring biomass accumulation and shifts through time.

Key words: environmental variables, allometric models, biomass estimates, spatial distribution.


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