Tree Growth

Latest Score:


in 2021

Weight: 8%
score trend is flat over time

Trees grow to different sizes and at various rates depending on species, age, and site characteristics. This distinction allows for various tree layers to form over time, resulting in structural diversity. When trees photosynthesize at a rate greater than what is needed for general processes, they can store excess carbon as wood, increasing their total biomass. Here, forest growth is measured as annual change in net growth (expressed in cubic feet) for all live trees on Forest Inventory and Analysis Phase 2 plots1. A high score means that tree growth is remaining stable over time.

-- Expert interpretation for Tree Growth is not available--

The score is calculated using a target value and the historical range of the the entire long-term dataset. The higher the score, the closer this year's value is to the target.

Once the score is computed for each year, the trend in scores over time is calculated. If the trend is significantly positive or negative, the long-term trend is marked as increasing or decreasing respectively.

Component Description
Scored as

Distance between minimum and target (scaled between 1 and 5)

Target value

Long-term mean

Directionality of scores

No change from the long-term mean is better

Minimum value used in scoring

Data minimum - 10% of the range

Maximum value used in scoring

Data maximum + 10% of the range

Data on tree growth were extracted from the USFS Forest Inventory and Analysis Program EVALIDator1. We used an FIA-established query (“Average annual net growth of sound bole volume of trees (at least 5 inches d.b.h./d.r.c.), in cubic feet, on forest land”) for net growth of live trees ≥5 inch DBH on sampled P1 plots. The first usable panel is for the year 2008. We relied on FIA’s statistical models for computing this value over time. We set the target for this dataset as the long-term mean. The current year is scored for where it falls between the target and the upper scoring bounds (maximum value in the dataset plus 10% of the range) or the lower scoring bounds (minimum value in the dataset minus 10% of the range), scaled to be between 1 and 5.

1 USDA Forest Service. 2019. FIA EVALIDator. Version Available at: