DIGITALNA ARHIVA ŠUMARSKOG LISTA
prilagođeno pretraživanje po punom tekstu
| ŠUMARSKI LIST 7-8/2015 str. 68 <-- 68 --> PDF |
change, designed to reduce the gases emissions that cause the greenhouse effect. The amount of biomass held and carbon stored in forest ecosystems plays important roles in global carbon cycle. They are considered as one of the most significant carbon sinks to reduce global warming. Carbon sequestration by terrestrial ecosystems is important in the global carbon balance for limiting the concentration of CO2 in the atmosphere (Muukkonen, 2006). There are three main deposits of carbon in the world. These deposits are the atmosphere, terrestrial and oceanic ecosystems. Each year, forest ecosystems take 100 gigatons of CO2 from the atmosphere and give half of it back to the atmosphere. On the contrary, earth’s oceans receive 104 gigatons of CO2 from the atmosphere and give 100 gigatons back. These facts reveal the importance of forests and forest ecosystems in terms of carbon stock (OGM 2014). Forest trees have the maximum amount of leaves compared to other plant species; they produce more CO2 than pastures and agricultural plant communities (Asan, 1999). Total biomass includes both aboveground biomass (AGB; e.g. trees, shrubs, and vines) and belowground biomass (e.g. living roots, dead fine and coarse litter associated with the soil) (Lu et al. 2014). Forest ecosystem stores about 80% of all above-ground and 40% of all below-ground terrestrial organic carbon (IPCC, 2001). Forests are the largest terrestrial carbon deposits. This fact alone reveals the necessity of learning how much carbon forests store. Many biomass estimation studies conducted are focused on above-ground forest biomass (De Gier et al., 2012; Riegel et al., 2013; Langner et al., 2012; Gulsunar, 2011) because it accounts for the majority of the total accumulated biomass in the forest ecosystem. Usually, as in the other tree components, regional and national biomass and carbon stock values related to above-ground biomass are calculated with the help of allometric biomass expansion factor (BEF) that are developed with the help of forest inventory data that is based on sample fields (Brown, 2002; Goodale et al., 2002). In conventional techniques on basis of statistical assessment (i.e., tree species, vertical structure, stand height and stand density), the forest AGB information comes from expensive and time consuming field surveys due to the high sampling intensity. As alternative, multi-parameter remote sensing techniques have been applied, in which remotely sensed data are used as proxy for quantitative forest AGB at various scales. (Tian et al. 2012). The study conducted by Yang et al. (2008), deal with the carbon stock capacity and the changes in carbon stock capacity of Pearl River Delta in China, between 1989 and 2003. It was concluded that there was a 16.76% increase in regional carbon stock and that 80% of this increment was stored in the stands. Gough, et al. (2008) conducted a study about how multiyear observations of forest carbon fluxes provide critical insight into the constraints on annual carbon stock rates. They examined how climate, disturbance, and forest succession simultaneously influence annual forest carbon stock. They also described how foresters and land managers can use knowledge gained from long-term ecosystem-scale studies to better manage forests for carbon sequestration. In addition to biomass factors, allometric biomass equations have been developed for a large number of tree species in different regions both geographically and ecologically (Peichl and Arain 2007). Also, carbon stock equations developed for some types of trees can be used without biomass equalities and are preferred because this increases the accuracy of the stock capacity estimations and are quick to implement. Land Use, Land-Use Change and Forestry (LULUCF) guide is frequently used for determining the amount of carbon in forest ecosystems (Penman et al. 2003). In the LULUCF guide, the annual carbon stock changes in the carbon pools that belong to the biomass of forest ecosystems are determined by using various equations and factors. Carbon flux measurements, remote sensing and modeling methods are used to determine the aboveground plant biomass. Remote sensing provides a practical and economical instrument to study vegetation cover and has been applied to map vegetation cover from local to global scales over the last three decades (Malatesta et al. 2013). Remote sensing methods are based on the relationship between forest stand parameters and their spectral properties. In this method, ground measurements are also needed to verify the remote sensed data (Ravindranath and Ostwald 2008). Remote sensing and geostatistical approaches have been used to map above-ground biomass by calibrating statistical models with field information (Goetz et al. 2009). A common approach has been the use of regression analyses of reflectance channels, and spectral and textural indices based on information from sampling sites. (Galeana-Pizaña et al. 2014). In one of the study (Sulistyawati et al. 2006), the statistical relationship between the amount of carbon determined with field measurements and spectral characteristics is used to develop a model that predicts the amount of carbon stored in workspace. In the study conducted by Chung et al. (2009), two different forest biomass estimation methods were used; (1) k-Nearest Neighbor (k-NN) method and (2) Biomass from Cluster Labeling Using Structure and Type (BioCLUST) method. Both of the biomass estimation methods using NFI data and satellite data are useful to provide total forest biomass information at large-scale as well as at small-scale. Even though the BioCLUST gives a more precise estimate, the method requires additional forest attributes and a more complex process than k-NN method. The study conducted by Myeong et al. (2006), a change in carbon stock capacity of urban green spaces in 1985, 1992 and 1999 was recorded using the Landsat 7 satellite images. The study conducted by Tan et al. (2007), changes in carbon |