Data from: Patterns and drivers of recent land cover change on two trailing-edge forest landscapes
Cite this dataset
Rodman, Kyle et al. (2022). Data from: Patterns and drivers of recent land cover change on two trailing-edge forest landscapes [Dataset]. Dryad. https://doi.org/10.5061/dryad.zw3r2289v
Climate change is altering the distribution of woody plants by influencing demographic processes and modifying disturbance regimes. Trailing-edge forests may be particularly vulnerable to these effects because they exist at warm, dry margins of tree distributions. To better understand recent climate-driven changes in trailing-edge forests, we used Landsat time series and 1,558 field reference plots to develop annual land cover maps from 1985 to 2020 in two large, biodiverse landscapes in central Arizona, USA. We then combined annual land cover maps with tree ring records and spatial data describing interannual climate, terrain, bark beetle (Curculionidae: Scolytinae) activity, wildfire, and harvest to quantify drivers of forest change. Throughout the two landscapes, forest extent declined by 0.3% and 0.8% from 1985 to 2020. However, considerable variation occurred within the study period, with abrupt (ca. 1–2 years) declines in forest extent followed by gradual (ca. 10 years) recovery on each landscape. Pinyon-juniper (Pinus edulis, Pinus monophylla, and/or Juniperus spp.) cover increased from 1985 to ca. 2000 but declined after 2000, a period of extreme drought and regional tree die-off. In contrast, pine-oak (Pinus ponderosa and Quercus spp.) cover increased from 2000 to 2020, primarily due to declines in ponderosa pine and mixed conifer cover over the same period. Wildfire was a key driver of transitions from forest to non-forest cover in our study area, with the occurrence of multiple compounded drought years playing an important role in unburned areas. By driving transitions to alternative forest types or non-forest cover, disturbance and drought will increasingly shape forest dynamics and ecosystem transformations throughout the southwestern US.
See "README.md" for further information on data processing and descriptions of individual files.
We place no restrictions on the use of these data, but encourage those interested in working with them to contact Kyle Rodman at Kyle.Rodman@nau.edu
Spatial data (.shp, .tif, etc.) can be opened using standard GIS software (i.e., ArcGIS, QGIS), R software, and command-line interfaces (e.g., GDAL)
R scripts (.r) can be executed using R software and viewed in standard text editors. Java-based scripts (.txt) can be executed in the Google Earth Engine code editor (https://code.earthengine.google.com/) and viewed in standard text editors.
Tabular data (.csv, .xlsx) can be opened in MS Excel or open-source alternatives (libreoffice).
See "README.md" for specific information about each file.
US Forest Service, Award: 20-DG-11030000-02