This guide is intended for students, researchers and engineers who wish to acquire the methodology necessary to construct tree volume, biomass or nutrient content tables. The various models used for this purposes have been grouped together here as they all call upon the same principle: they estimate a variable that is difficult to measure in trees (e.g. volume) using simpler characteristics such as tree diameter at breast height (1.30 m), or tree height or age. This guide is based on a large number of reference papers, and although it does not claim to present all the possible cases, it does describe techniques that can be used to construct the equations required. The references given in the text are specified when possible as author, year and page such that the reader can easily pursue threads of particular interest. A concrete example (dubbed the “red line”) guides the reader and helps acquire knowledge through practical application. This guide does not require a great many prerequisites. The red lines use Microsoft Excel to prepare files and R (R Development Core Team, 2005) for model fitting. The R command lines used are given in each red line. Forest & Emissions Assessments, m. MRV, Other Publications, allometric equations, biomass, carbon, forest carbon, manual, MRV, tree volume The foundations of biomass estimations ; “Biology”: Eichhorn’s rule, site index, etc; Even-aged, monospecific stands ; Uneven-aged and/or multispecific stands ; Selecting a method ; Estimating the biomass of a biome ; Estimating the biomass of a forest or a set of forests ; Measuring the biomass of a tree ; Sampling and stratification ; Sampling for a simple linear regression ; Predicting the volume of a particular tree ; Predicting the volume of a stand ; Sampling to construct volume tables ; Number of trees ; Sorting trees ; Stratification ; Selecting trees ; Sampling for stand estimations ; Sampling unit ; Relation between coefficient of variation and plot size ; Selecting plot size ; In the field ; Weighing in the field ; In the field ; In the laboratory ; Calculations ; Direct weighing and volume measurements ; In the field: case of semi-destructive measurements ; In the laboratory ; Partial weighings in the field ; Trees less than 20 cm in diameter ; Trees more than 20 cm in diameter ; Measuring roots ; Recommended equipment ; Heavy machinery and vehicles ; General equipment ; Computer-entering field data ; Laboratory equipment ; Recommended field team composition ; Entering and formatting data ; Data entry ; Data entry errors ; Meta-information ; Nested levels ; Data cleansing ; Data formatting ; Graphical exploration of the data ; Exploring the mean relation ; When there is more than one effect variable ; Determining whether or not a relation is adequate ; Catalog of primitives ; Exploring variance ; Exploring doesn’t mean selecting ; Model fitting ; Fitting a linear model ; Simple linear regression ; Multiple regression ; Weighted regression ; Linear regression with variance model ; Transforming variables ; Fitting a non-linear model ; Exponent known ; Estimating the exponent ; Numerical optimization ; Selecting variables and models ; Selecting variables ; Selecting models ; Choosing a fitting method ; Stratification and aggregation factors ; Stratifying data ; Tree compartments ; Validating a model ; Validation criteria ; Cross validation ; Predicting the volume or biomass of a tree ; Prediction: linear model ; Prediction: case of a non-linear model ; Approximated confidence intervals ; Inverse variables transformation ; Predicting the volume or biomass of a stand ; Expanding and converting volume and biomass models ; Arbitrating between different models ; Comparing using validation criteria ; Choosing a model ; Bayesian model averaging
