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* Metric Name: Density – Large Trees  

* Tier: 2  

* Data Vintage: 06/2020  

* Unit Of Measure: Percent live trees per pixel  

* Metric Definition and Relevance: Large trees are important to forest managers as they have a greater likelihood of survival from fire, provide sources of seed stock, wildlife habitat, and contribute to other critical processes like carbon storage and nutrient cycling. Large trees are often the focus of management in order to protect existing ones and to foster future ones. In consultation with National Forests, “large trees” have been designated as greater than 30” dbh.  

* Creation Method: To determine the cutoff for large trees, we developed an allometric equation to predict tree diameter as a function of height. We selected data for plots located in the Central California region from the USDA Forest Inventory and Analysis program (FIA) for California (FIA DataMart 2023; California 2022 database; ver. 9.0.1).

We included trees that met the following criteria: alive; crown class code of
open-grown, dominant, or co-dominant; diameter at breast height (DBH, breast
height = 4.5 ft) at least 1 inch; and height (HT) at least 5 feet. To minimize
the impact of outliers, we trimmed the maximum tree height to the 0.995th
percentile. These selection criteria yielded 7,089 trees. We used an
information theoretic approach to select the best allometric model (Burnham
and Anderson 2002). We evaluated three alternative functions: : linear, power,
and saturating. The criteria for model selection were based on the Akaike
Information Criterion (AIC). For this set of 3 potential models, we calculated
the difference in AIC between every model and the model with the lowest AIC
(ΔAIC).

The best allometric model was a saturating function where:

DBH (in ) = 0.752*HT(ft)0.772

The root mean square error on the DBH prediction was 6.67 in and the pseudoR2
= 0.70. Predicted diameters from heights are summarized here:.

Block statistics were run on California Forest Observatory (CFO) canopy height
pixels greater than or equal to 119’ (36m) with 3x3 window to calculate the
sum for input cells within a 30m rectangular neighborhood. This assigned
number of pixels per 30m (900m2) cell. Resultant values of 1 through 9 were
converted to percent. All background values were calculated to equal 0,
meaning 0% large tree existence.

  

* Credits: California Forest Observatory (Salo Sciences), 2020