DOI: 10.5061/dryad.931zcrjq4
title: Supporting data for: Topographic information improves simulated patterns of post-fire conifer regeneration in the Southwest U.S.

description: The western U.S. is projected to experience more frequent and severe
 wildfires in the future due to drier and hotter climate conditions,
 exacerbating destructive wildfire impacts on forest ecosystems such as
 tree mortality and unsuccessful post-fire regeneration. While empirical
 studies have revealed strong relationships between topographical
 information and plant regeneration, ecological processes in ecosystem
 models have either not fully addressed topography-mediated effects on the
 probability of plant regeneration, or the probability is only controlled
 by climate-related factors, e.g., water and light stresses. In this study,
 we incorporated seedling survival data based on a planting experiment in
 the footprint of the 2011 Las Conchas Fire into the PnET extension of the
 LANDIS-II model by adding topographic and an additional climatic variable
 to the probability of regeneration. The modified algorithm included
 topographic parameters such as heat load index (HLI) and ground slope and
 spring precipitation. We ran simulations on the Las Conchas Fire landscape
 for 2012–2099 using observed and projected climate data (i.e., RCP 4.5 and
 8.5). Our modification significantly reduced the number of regeneration
 events of three common southwestern conifer tree species (piñon, ponderosa
 pine and Douglas-fir), leading to decreases in aboveground biomass,
 regardless of climate scenario. The modified algorithm decreased
 regeneration at higher elevations and increased regeneration at lower
 elevations relative to the original algorithm. Regenerations of three
 species also decreased on eastern aspects. Our findings suggest that
 ecosystem models may overestimate post-fire regeneration events in the
 southwest U.S. To better represent regeneration processes following
 wildfire, ecosystem models need refinement to better account for the range
 of factors that influence tree seedling establishment. This will improve
 model utility for projecting the combined effects of climate and wildfire
 on tree species distributions.
description: These outputs are from a set of simulations using the LANDIS-II
 (v7.0) model with a modified PnET Succession extension (based on v.4.1)
 and the Dynamic Fuels and Fire System (v3.0) extension. Our simulated
 landscape is the footprint of the 2011 Las Conchas fire in the Jemez
 Mountains, New Mexico. Observed climate data (Daymet) and downscaled
 climate projection data (access1.0.1, canesm2.1, cesm1-bgc.1 and
 hadgem2-es.1) forced with two emission scenarios (RCP4.5 and 8.5) from the
 CMIP5 models were used. We used contemporary fire conditions for
 simulating fire events (Keyser et al., 2020; Krofcheck et al.,
 2019).  We ran 10 replicate simulations from 2012 to
 2099. We summarized the data to calculate cumulative post-fire
 regenerations and biomass distribution as well as the relationship of
 regeneration with topographical variables such as elevation and
 aspect. 
description: The archived file includes an R script for creating figures with
 a Rdata file.  The modified PnET extension scripts
 (C#), executable setup files for LANDIS-II (v7.0) with the modified PnET
 extension and Dynamic Fuels and Fire System (v3.0) extension setup files
 and one set of examples for HPC application (SLURM) are archived at Zenodo
 (https://doi.org/10.5281/zenodo.7535673). Docker images for the HPC application are available in the Docker Hub (Original algorithm: https://hub.docker.com/r/ecochang/landis_pnet_dffs_org_v2; Modified algorithm: https://hub.docker.com/r/ecochang/landis_pnet_dffs_mod_v2).