Biomass inventory

There have been numerous estimates made on the total biomass and biomass potential of our forests 3,1Q). The inventory procedure used is based on estimates and averages, and is fully described by Wahlgren and Ellis (U). Forest surveys based on biomass measurement techniques are needed to accurately determine the quantities and location of our wood resource. Many studies on measuring the weight of individual trees, and to a lesser extent forest stands, have been made. This work has been summarized by Keays (12). and Hitchcock and McDonnell (12)- As work in forest biomass measurement is refined, regional weight tables can be developed and accurate biomass inventories compiled. 

Wood, S.W, LayzeU, D.B., 2003. A Canadian Biomass Inventory Feedstocks for the Bio-based Economy. BIOCAP Canada Foundation, Kingston, ON. 

Large amounts of carbon are found in the terrestrial ecosystems and there is a rapid exchange of carbon between the atmosphere, terrestrial biota, and soils. The complexity of the terrestrial ecosystems makes any description of their role in the carbon cycle a crude simplification and we shall only review some of the most important aspects of organic carbon on land. Inventories of the total biomass of terrestrial ecosystems have been made by several researchers, a survey of these is given by Ajtay etal.(1979). 

Brown S, Gillespie A, Lugo A. Biomass estimation methods for tropical forests with applications to forest inventory data. Forest Science, 1989. 35(4) pp. 381-902. 

MOR hydrothermal component, but that the very low 5 Fe values inferred for Fe(II)aq from low 5 Fe magnetite reflect interstitial pore waters and/or bottom waters that were closely associated with DIR bacteria, and not those of the open oceans. A substantial biomass of DIR bacteria is still required to process the very large inventory of Fe that is sequestered in BIFs as Iow-5 Fe magnetite, although not so extensive as that which would be required to lower the 5 Fe values of the open oceans if the oceans were rich in Fe(II)aq. 

Lobert JM, Keene WC, Logan JA, Yevich R (1999) Global Chlorine Emissions from Biomass Burning Reactive Chlorine Emissions Inventory. J Geophys Res 104 8373... 

A U. S. national biogenic sulfur emissions inventory with county spatial and monthly temporal scales has been developed using temperature dependent emission algorithms and available biomass, land use and climatic data. Emissions of dimethyl sulfide (DMS), carbonyl sulfide (COS), hydrogen sulfide (H2S), carbon disulfide (CS2), and dimethyl disulfide (DMDS) were estimated for natural sources which include water and soil surfaces, deciduous and coniferous leaf biomass, and agricultural crops. The best estimate of 16100 MT of sulfur per year was predicted with emission algorithms developed from emission rate data reported by Lamb et al. (1) and is a factor of 22 lower than an upper bound estimate based on data reported by Adams et al. 

Vegetative emission source factors also depend on biomass factors to convert surface area estimates to biomass estimates. The leaf biomass factors used in this inventory (Table II) are those suggested by Zimmerman (31). A comparison of leaf biomass factors reported in the literature provides a simple illustration of the variability associated with the conversion factors used in this inventory. Monk et al. (321 reported a biomass factor of 8400 kg - ha 1 for trees with 14 cm diameter trunks in an oak hickory forest. Biomass factors of 5700 kg ha 1 (301 and 5800 kg - ha 1 (331 have been estimated for mixed deciduous forests. Amts et al. Q4) reported a range of biomass factors between 4400 kg ha 1 and 6340 kg ha 1 for a loblolly pine forest. The variability in these biomass estimates is less than 25%. 

Three areas of uncertainty in this present inventory of natural sulfur emissions which need further work include natural variability in complicated wetland regions, differences in emission rates in the corrected SURE data and those reported by Lamb et al. (1) and Goldan et al. (21) for inland soil sites, and biomass emissions for which only a very limited data base easts. The current difficulty in determining the sources of variability emphasizes the need to better understand natural sulfur release mechanisms. At present, it may be useful to consider the emission rates based on the corrected SURE data as an upper bound to natural emissions and use the emission rates based on data described by Lamb et al. (1) as a more conservative estimate of natural sulfur emissions. However, this still leaves a factor of 22 difference between the suggested upper bound and our best current estimate. 

Figure 7. DMSP inventory in S. altemiflora and above-ground biomass at four S. altemiflora sites in Great Marsh, Lewes, Delaware, in June, 1986. Most above ground DMSP is concentrated in live leaves although stems and dead leaves represent the majority of above-ground biomass at this time. Roots have less DMSP per unit biomass but may represent a larger pool on an aerial basis. Below-ground DMSP is less likely, however, to play a role in DMS emission as discussed by Dacey et al. (19).

Table 2.22 Amounts of elements (per m ) in biota, atmosphere and the oceans, representing the entire column of the biosphere, from upper troposphere through surface-covering waters (70% of entire Earth surface ) downward to life-inhabited upper soil and sediment layers. Three essential (P, Zn, Cu) and one highly toxic (Be) element are gathered in biota by 8.5 3% of the entire inventory while others except of C, Mn (1-2%) remain most outside of biomass.

In an international effort, the Reactive Chlorine Emissions Inventory (Keene et al., 1999, and references therein) was compiled which includes chlorine emissions from the following four source-type classes (i) oceanic and terrestrial biogenic emissions (ii) sea salt aerosol production and dechlorination (iii) biomass burning and (iv) exclusively anthropogenic sources like industry, fossil fuel combustion, and incineration. They provide numbers from atmospheric burdens and fluxes for the individual species and sources. 

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