biomass residue means the estimated biomass in an area following the deforestation of the area. biomass stock means the amount of biomass held in a native forest or part of a native forest. biomass survey means a field-based survey of biomass. carbon estimation area has the meaning by section 3.6. carbon stock means the amount of carbon held in a native forest or part of a native forest. CFI Mapping Guidelines means the guidelines of that name, as published from time to time, and available on the website of the department that administers the Act. clearing means the conversion, caused by people, of native forest to a land use other than native forest. clearing buffer has the meaning given by section 3.5. clearing consent means approval to commence clearing required by Commonwealth, State or Territory law, issued by the relevant Commonwealth, State, Territory or local regulatory authority responsible for giving the approval. CO2-e means carbon dioxide equivalent conservation covenant has the meaning it has in section 9951 of the Income Tax Assessment Act 1997. controlled burn means the controlled application of fire within a carbon estimation area. cropland means arable or tillable land that is used for producing annual or perennial crops. debris pool means the biomass from trees cleared. deforestation means the direct conversion of forest, on or after 1 January 1990, to deforestation plan has the meaning given by subsection 3.15(3). degradation a detectable reduction in the biomass of the native forest in the project area where, notwithstanding the reduction, the area remains, or has the potential to remain, a native forest, and includes a reduction caused by management activities. diameter at breast height means the diameter of the stem of a tree, including the bark, measured at 1.3 metres above ground level. disturbance means: (a) degradation; or disturbance. exclusion area means an area of land within the project area that is not used to estimate abatement. forest means land of a minimum area of 0.2 of a hectare on which trees: (a) have attained, or have the potential to attain, a crown cover of at least 20% across the area of land; and
all measurements associated with trees not analysed in accordance with this section must be discarded; destructive sampling for the equivalent number of sample trees discarded in accordance with paragraph (a) must be repeated in accordance with subsection 3.27(1); and analysis of the sample trees must be completed in accordance with this section. If the coefficient of variation calculated in accordance with subsection (3) is equal to or less than 15%, the dry weight of any sample trees not analysed in accordance with this section must be estimated by multiplying the tree wet weight by the average tree dry to wet weight ratio. Step 10—Data exploration and analysis The whole tree dry weight data obtained in section 3.28 must be compiled into a database or spreadsheet suitable for statistical analysis or importation into a statistical analysis software package. If an existing allometric equation is to be validated, Step 10.1 in this section must be skipped and Step 11 in section 3.30 must be completed. If a new allometric equation is to be validated, Step 10.1 in this section must be completed. Step 10.1—Allometric development An allometric equation being developed must take the form of a statistical model fitted using: simple linear regression; multiple regression; polynomial regression; or non-linear regression. Each allometric equation developed must satisfy the assumptions that: (a) the means of the response variables change in a systematic way with variation in the explanatory variable; and errors are: independent; and normally distributed. To satisfy the assumptions in subsection (5), data may be transformed. If data is transformed as permitted by subsection (6), power transformations may be used. If a logarithmic transformation is applied to the response variable, the proportional bias must be estimated and applied the ratio of the arithmetic sample mean to the mean of the back-transformed predicted variables. Each explanatory variable used in an allometric equation must be statistically significant. For the purposes of subsection (9), a variable is statistically significant if the outcome of an or a two-tailed t-test has a probability value of less than 5%.