Estimating tree biomass and merchantable volume

Hunter Stanke, Jeffrey W. Doser

2021 (last updated February 7, 2025)

Introduction

Prior to rFIA v0.3.1, the biomass() function provided estimates of volume, biomass, and carbon stocks of standing trees. This is what is described in the introductory rFIA manuscript (Stanke et al. 2020.

rFIA v0.3.1 introduced breaking changes to the biomass() function and how rFIA handles volume, carbon, and biomass estimation. Specifically, the biomass() function was overhauled to focus solely on estimation of tree biomass, providing enhanced flexibility in the estimation of biomass components (e.g., bole, limbs, coarse roots, etc.). In addition, v0.3.1 gave rise to the volume() function, which supersedes and expands upon the previous merchantable volume estimators implemented in biomass(). Carbon estimation now lives entirely in the dedicated carbon() function, which estimates carbon stocks across the full suite of forest ecosystem carbon pools (e.g., live and dead trees, understory vegetation, down dead wood, litter, soil organic matter), not just standing trees; see ?carbon for details.

As of rFIA v1.1.0, the biomass() and volume() functions now leverage FIA’s new National Scale Volume and Biomass Estimators (NSVB), which provides a more consistent and accurate accounting of structural components of trees. As with previous versions of biomass(), estimates can be returned by tree component using the byComponent method, although we note the specific components available have changged given underlying changes in FIADB and the NSVB approach. The NSVB represents a substantial advancement in national scale volume and biomass equations. Below we provide some basic examples of biomass() and volume().

Estimating tree biomass components

Let’s see how the biomass() function can be used to estimate tree biomass components! As always, you can check out our documentation with ?biomass:

# Load data from the rFIA package
library(rFIA)
data(fiaRI)

# Total live tree aboveground biomass, excluding foliage (default)
biomass(fiaRI)

## # A tibble: 6 × 5
##    YEAR BIO_ACRE BIO_ACRE_SE nPlots_TREE nPlots_AREA
##   <dbl>    <dbl>       <dbl>       <int>       <int>
## 1  2013     71.5        3.97         120         123
## 2  2014     72.6        3.99         121         123
## 3  2015     74.0        3.96         122         124
## 4  2016     75.8        3.80         124         125
## 5  2017     76.2        3.86         124         125
## 6  2018     75.7        3.87         126         127

By default, biomass estimates total aboveground live tree biomass for all reporting years available in the FIA.Database (treeType = "live", component = "AG"). Here aboveground tree biomass is a simple summation of wood biomass in the total stem from ground line to the tree tip, stem bark biomass, and branch wood and bark.

But what if we’re interested in estimating biomass within different tree components separately, e.g., we want an individual estimate for bole, foliage, stump, and others? Simply set the new byComponent argument to TRUE:

biomass(db = clipFIA(fiaRI), byComponent = TRUE)

## # A tibble: 5 × 6
##    YEAR COMPONENT BIO_ACRE BIO_ACRE_SE nPlots_TREE nPlots_AREA
##   <dbl> <chr>        <dbl>       <dbl>       <int>       <int>
## 1  2018 BRANCH       19.0         4.42         126         127
## 2  2018 FOLIAGE       2.09        3.05         126         127
## 3  2018 ROOT         14.0         4.10         126         127
## 4  2018 STEM         48.9         3.90         126         127
## 5  2018 STEM_BARK     7.78        3.49         126         127

Note that the sum of the provided components is NOT equal to total tree biomass. In other words, the components are not mutually exclusive (e.g., BOLE biomass is part of STEM biomass). Aboveground tree biomass is equal to the sum of STEM, STEM_BARK, and BRANCH. The Estimation Details section of the help page for biomass() provides all this information and more.

Awesome, but what if we want to estimate biomass for some combination of these components, e.g., bole plus stump? The new component argument has our backs. Users can specify any combination of components seen in the output above. For example, say we want to estimate abovegound biomass ("AG") plus foliage ("FOLIAGE"):

biomass(db = clipFIA(fiaRI), component = c("AG", "FOLIAGE"))

## # A tibble: 1 × 5
##    YEAR BIO_ACRE BIO_ACRE_SE nPlots_TREE nPlots_AREA
##   <dbl>    <dbl>       <dbl>       <int>       <int>
## 1  2018     77.7        3.82         126         127

Estimating merchantable tree volume

Previously, biomass() included support for estimation of net merchantable volume and net sawlog volume in units of cubic feet. Since rFIA v0.3.1, the volume() function expands on this previous capacity in two key ways: (1) allowing use of alternative volume definitions used by the FIA program (i.e., net, sound, and gross volume), and (2) offering estimates of sawlog volume in units of cubic feet (CF) and thousand board feet (MBF; International 1/4 inch rule).

By default, volume() will estimate net volume of live trees (volType = "NET" and treeType = "live"):

volume(db = fiaRI)

## # A tibble: 6 × 9
##    YEAR BOLE_CF_ACRE SAW_CF_ACRE SAW_MBF_ACRE BOLE_CF_ACRE_SE SAW_CF_ACRE_SE
##   <dbl>        <dbl>       <dbl>        <dbl>           <dbl>          <dbl>
## 1  2013        2305.       1366.         7.02            5.11           8.49
## 2  2014        2356.       1402.         7.17            5.10           8.41
## 3  2015        2409.       1445.         7.38            5.00           8.32
## 4  2016        2475.       1493.         7.58            4.91           8.16
## 5  2017        2480.       1497.         7.63            4.97           8.26
## 6  2018        2470.       1493.         7.63            4.99           8.26
## # ℹ 3 more variables: SAW_MBF_ACRE_SE <dbl>, nPlots_TREE <int>,
## #   nPlots_AREA <int>

Here, BOLE_CF_ACRE gives us merchantable bole volume per acre, SAW_CF_ACRE gives us sawlog volume in cubic feet per acre, and SAW_MBF_ACRE gives us sawlog volume in thousand board feet per acre (International 1/4 inch rule).

We can change our volume definition using the volType argument. Let’s try gross volume instead:

volume(db = fiaRI, volType = 'gross')

## # A tibble: 6 × 9
##    YEAR BOLE_CF_ACRE SAW_CF_ACRE SAW_MBF_ACRE BOLE_CF_ACRE_SE SAW_CF_ACRE_SE
##   <dbl>        <dbl>       <dbl>        <dbl>           <dbl>          <dbl>
## 1  2013        2680.       1551.         7.95            4.97           8.41
## 2  2014        2741.       1592.         8.13            4.94           8.33
## 3  2015        2804.       1642.         8.38            4.84           8.26
## 4  2016        2885.       1695.         8.60            4.72           8.10
## 5  2017        2902.       1703.         8.67            4.76           8.19
## 6  2018        2888.       1700.         8.69            4.77           8.19
## # ℹ 3 more variables: SAW_MBF_ACRE_SE <dbl>, nPlots_TREE <int>,
## #   nPlots_AREA <int>

So what do these different definitions mean? FIA defines net volume (volType="NET") as: “The net volume of wood in the central stem of timber species (trees where diameter is measured at breast height $\geq$ 5.0 inches d.b.h., from a 1-foot stump to a minimum 4-inch top diameter, or to where the central stem breaks into limbs all of which are <4.0 inches in diameter…. Does not include rotten, missing, and form cull (volume loss due to rotten, missing, and form cull defect has been deducted).” In volum(), we could also choose from two alternative definitions: sound volume (volType = 'SOUND') or gross volume (volType = 'GROSS'). Sound volume is identical to net volume except that sound includes volume from portions of the stem that are be considered “form cull” under the net volume definition (e.g., sweep). In contrast, gross volume is identical to the net volume definition except that gross includes volume from portions of the stem that are rotten, missing, and considered form cull.