PhytoIn (version 0.2.0)

stats: Representativeness and confidence statistics for a forest inventory

Description

Computes representativeness and confidence statistics for a forest inventory. Summarizes inventory coverage, estimates absolute stand parameters per hectare with uncertainty (density, volume, basal area), and extrapolates results to the total habitat area, including sample-size requirements for target permissible errors.

Usage

stats(obj, area.tot, prob = 0.95, shape.factor = 1, rm.dead = FALSE)

Value

A list with three components:

• inventory: data frame summarizing inventory coverage (fields Stat and Values).

• ha: data frame of per-hectare statistics for stand parameters (fields Stat, ADe, AVol, ABA).

• population: data frame of population-level statistics for the total area (area.tot), including required numbers of SUs for 10% and 20% permissible errors.

Arguments

obj

An object of class param created by phytoparam. Must contain the raw data (obj$data), variable mappings (obj$vars), and global inventory metadata (obj$global).

area.tot

Total habitat area (in hectares) to which estimates will be extrapolated (e.g., the whole forest fragment). Required.

prob

Confidence level used to compute t-based confidence limits (default 0.95).

shape.factor

Stem form correction factor used in the individual volume calculation (\(V_i = abi \times h \times shape.factor\)). Default 1 (cylindrical shape).

rm.dead

Logical. If TRUE, dead trees are excluded from all calculations (rows whose taxon label matches the “dead” code stored in obj$vars).

Author

Rodrigo Augusto Santinelo Pereira

Details

Extracts the sample-unit (SU) identifier, taxon label, height/length variable, and “dead” code from obj$vars, and the surveyed (inventoried) area from obj$global. If rm.dead = TRUE, individuals flagged as dead are removed before analysis.

Individual volume is computed as \(V_i = abi \times h \times shape.factor\), where abi and h are columns present in obj$data. Per-SU totals of volume and basal area are converted to per-hectare values using the SU area. The function then derives, for density (ADe), volume (AVol), and basal area (ABA):

• mean, variance, standard deviation, standard error;

• coefficient of variation (CV);

• absolute and relative sampling error (based on the t quantile with |SU| - 1 df);

• lower and upper confidence limits per hectare.

Inventory representativeness (total area, number/area of SUs, and percentage inventoried) is reported, and population totals (for area.tot) are produced with corresponding confidence limits. Required numbers of SUs to attain 10% and 20% permissible relative errors are computed from standard finite-population sampling formulae.

References

FAO (1981). Manual of Forest Inventory—With Special Reference to Mixed Tropical Forests. Food and Agriculture Organization of the United Nations, Rome.

Examples

## Creating the param object containing the phytosociological parameters
quadrat.param <- phytoparam(x = quadrat.df, measure.label = "CBH",
                            taxon = "Species", dead = "Morta", family = "Family",
                            circumference = TRUE, su = "Plot", height = TRUE,
                            su.size = 25, rm.dead = FALSE)

## Calculating the statistics
stats(obj = quadrat.param, area.tot = 4)