To gain more insights into the process influencing forest dynamics in Southern California, we have established the 4ha San Jacinto Forest Dynamics Plot (SJFDP) on the west slope of Mt. San Jacinto in Southern California. This area is adjacent to the University of California James Reserve and is in the U.S. Forest Service (USFS) Hall Canyon research natural area. This dataset include three files. Census data is data on every free-standing woody stem (live or dead) greater than 1cm in diameter which has identified to species, mapped, measured, and tagged for long-term monitoring. Seedling data includes data from 256 1m² plots where every seedling woody stem less than 1m tall has been identified to species, mapped, measured, and tagged for long-term monitoring. Envrionmental data includes soil and topographic variables that were collected within each of 100 20x20m quadrats withint he SJFDP.

To quantify woody species adult composition across the SJFDP, we subdivided the SJFDP into 100 20x20 all free-standing stems of woody species greater than 1cm diameter at breast height (DBH) that have been tagged, identified, measured, and mapped following CTFS-ForestGEO protocols (Condit, 1998). To quantify woody species seedling composition across the SJFDP, we surveyed the central 64 20x20m quadrats (out of 100 total quadrats) in 2021, leaving a 20-meter buffer between seedling plots and the edge of the SJFDP. The purpose of the buffer was to ensure that adult composition is quantified for all of the 8 quadrats surrounding every quadrat in which seedling composition was quantified so that we can more accurately assess the influence of adult composition on seedling composition. To estimate seedling composition within each of the central 64 quadrats, we established four 1m² subplots (n=256 subplots). Each subplot was positioned 7m from the corner of each quadrat and aligned on a 45-degree angle relative to the x-y axes of the SJFDP grid (65º, 155º, 245º, 335º). Subplot locations were moved to the nearest suitable location if the initial subplot location was completely occupied by a log or rock. In each subplot, we identified all seedlings (defined as individuals under 1m tall following the CTFS-ForestGEO protocol (Condit, 1998)) to species, mapped their locations in a 100-cell grid, measured their height, and added an identification tag unique to each individual.

To quantify environmental variation among quadrats we measured 8 soil variables and 6 topographic variables. In the center of each 20x20m quadrat, we collected a sample of ~500g of soil (0- to 10-cm depth) excluding the top organic horizon and analyzed organic matter (OM, by loss on ignition), phosphorus (P; Weak Bray and Sodium Bicarbonate), potassium (K), magnesium (Mg), calcium (Ca), sodium (Na), and cation exchange capacity (CEC, cations and CEC by ammonium acetate method) and pH (analysis was done by A & L Western Laboratories, Modesto, CA., USA). For each 20x20 m quadrat, we additionally calculated 6 topographic variables: mean elevation, slope, convexity, aspect, topographic position index, topographic ruggedness index, and flow direction. Mean elevation above sea level was quantified as the mean elevation of the four corners of each quadrat. Slope was quantified using the slope tool in ArcGIS 10.1. To quantify the remaining terrain characteristics,  we used a 1-m digital elevation model (DEM) from the USGS 3D Elevation Program (3DEP) and the raster package in R (Hijmans et al., 2013). Because aspect is a circular variable, we used cosine(aspect) in our analyses (Legendre et al., 2009). South aspect was measured as cos(aspect)*sin(slope), where higher values correspond to south-facing slopes that are associated with warmer and/or drier site conditions (Ackerly et al., 2020). Finally, we calculated the topographic position index (TPI) as the difference between the elevation of a quadrat and the mean elevation of the eight surrounding quadrats; topographic ruggedness index (TRI) as the mean absolute difference between the elevation of a quadrat and the elevation of the eight surrounding quadrats; and flow direction (flowdir) as the direction of the greatest drop in elevation for a given quadrat.