mapMOG: Assessing Mature and old growth forest using FIA data
Data files
Sep 05, 2025 version files 159.98 MB
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mapMOG.zip
159.98 MB
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README.md
6.22 KB
Abstract
Although many species display relationships – both positive and negative – with various forest successional stages, researchers often rely on datasets that describe forest presence rather than forest age (i.e., National Landcover Database). In 2023, the USDA Forest Service introduced standardized region-specific mature and old-growth (MOG) forest definitions for the United States, but these definitions have not been readily integrated to address questions in ecology and conservation. Here, we introduce ‘mapMOG’—an open-access R function that applies the recently adopted federal MOG definitions to Forest Inventory and Analysis (FIA) plots across the contiguous United States (US). Additionally, our novel function interpolates MOG status across US forested lands between FIA plots. To demonstrate the utility of these data for forest landscape ecological modeling, we compare the predictive power of the MOG covariate against binary forest/non-forest and percent canopy cover covariates to examine forest habitat associations across three taxa, geographies, and modelling frameworks: avian richness in Mid-Atlantic national parks; Seminole bat (Lasiurus seminolus) occupancy in the Southeastern Coastal Plain; and Cascade torrent salamander (Rhyacotriton cascadae) distribution associated with US National Forests in the Pacific Northwest. In all three cases, our MOG covariate produced by our function explained variation in the wildlife occurrence data better than the alternative forest metrics. Finally, we compared imputed results across multiple spatial scales and found notable but statistically insignificant differences in interpolated MOG scores.
Dataset DOI: 10.5061/dryad.gmsbcc31s
Description of the data and file structure
Assessing Mature and Old Growth Forest using FIA data
Mature and old growth forest support vast quantities of life, and are critical to the function of many ecosystems. While remotely sensed landcover datasets can indicate the spatial distribution of forests, they offer little insight to the age of forests. Fortunately, the United States Forest Service maintains an extensive forest inventory program across public and private lands called the Forest Inventory Analysis (FIA). This function uses R (specifically the RFIA package) to access FIA data from the Forest Service data repository, then assesses the data to determine if it meets the definitions for mature or old growth forest. Definitions vary by region and forest-type, offering substantial flexibility even across ecosystems. Finally, this function offers the option to interpolate the mature/old growth (MOG) status of unsampled forests based on neighboring sampled forests. The following tutorial explains how to use the function.
Files and variables
File: mapMOG.zip
mapMOG tutorial.pdf is the fully annotated tutorial of how to access and use the mapMOG function in full detail.
Subfolder: tutorial_Olympic
OlympicNF: a shapefile of a (contiguous) selection of Olympic National Forest
Subfolder: utility_canopy (this folder is intentionally empty, users should place the most recent NLCD canopy cover raster in this folder)
Subfolder: utility_ecoregions
USA_ecoregions: A shapefile (polygon) of Level 3 ecoregions of the United States of America
Subfolder: utility_MTcontDivide
utility_MTcontDivide: A shapefile (polygon) indicating the regions east of the continental divide in the state of Montana
Subfolder: utility_NWFPboundary
NWFPboundary: A shapefile (polygon) of the boundary of the areas managed under the Northwest Forest Plan, covering the western portions of Washington, Oregon, and California
Subfolder: utility_ORcounties
counties: A shapefile (polygon) of Hood River County and Wasco County, Oregon
Subfolder: utility_USA
tl_2020_us_state: A shapefile (polygon) of the contiguous United States
R code: FUNCTION_mapMOG: script containing the mapMOG function as well as the tutorial function
Spreadsheet: utility.v9-5_2024-10_Natl_MasterTreeSpeciesList: List of tree species and the species codes used by the United States Forest Service (columns listed below)
- FIA Code: Species-specific numeric code used in Forest Inventory Analysis
- Common Name: Common name for plant species in English
- Genus: Genus name for plant species
- Species: Species name for plant species
- Subspecies: If applicable, subspecies epithet for species
- PLANTS Code: Species-specific 4-6 character code using letters and numbers, recognized by the USDA plants database
- SCIENTIFIC_NAME: Complete species-specific name in binomial nomenclature
Raster: utility_R5_PAZ: A raster of plant association zones (i.e., vegetative community types) in region 5 (Pacific Southwest).
Identifying a study area
The mapMOG() function requires the user to identify a study area using a shapefile in sf format. The study area, called a locale, can be as large as a state, or as small as a forest. Please note, however, that the function cannot currently accommodate multi-state processing. If your study locale spans multiple states, the function must be run separately for each state contained in the locale. Additionally, small forests are not likely to contain enough FIA plots for adequate interpolation. Assessing data at the landscape-level (e.g., county, etc.) is likely to produce greater insights, even if you are only interested in a small portion of the landscape. In this tutorial we will use part of Olympic National Forest as a case study. A shapefile of Olympic National Forest is included in the function folder for your convenience.
Downloading and Accessing the function and data
Download the entire mapMOG folder from Dryad and unzip the folder if necessary. We recommend moving the folder from the Downloads folder of your computer to a more permanent location. Do not remove files from the mapMOG folder, as these files are necessary for proper functionality.
Code/software
File size limitations barred us from including all necessary files in the ‘mapMOG’ folder available for download. Prior to running the function, download the following files and add them to the mapMOG folder:
If you plan on interpolating MOG across unsampled landscapes
- Download the most recent canopy cover layer from the National Land cover Database: https://www.mrlc.gov/data
- Unzip the downloaded folder into the ‘utility_canopy’ subfolder of ‘mapMOG’ such that the file structure is ‘[YOUR FILE PATH]/mapMOG/utility_canopy/[CANOPY RASTER]’
- No need to rename the raster
Once you have added the canopy and PNV files to your mapMOG folder (if necessary), open R Studio and load the function by sourcing the script from the mapMOG folder. Note that the entire filepath must be specified for your computer to find the file.
Dynamic data exploration can be achieved using the mapview package: mapview(MOG.raster.transformed)
If you encounter issues with the mapMOG() function, please email Dan Herrera at herrerawildlife(at)gmail.com.
Access information
Other publicly accessible locations of the data:
Data was derived from the following sources:
