DOI: 10.5061/dryad.pnvx0k6z1
title: FATES projections of forest structure and composition (1830-2098) at a mixed conifer site in the southern Sierra Nevada

description: This data repository contains model source code, parameter sets, driver
 data, and model output for simulations run with the Functionally Assembled
 Terrestrial Ecosystem Simulator (FATES) in a mixed conifer forest ~35
 miles northeast of Fresno (37.0717, 119.2265) in California’s southern
 Sierra Nevada. The code and data provided here were used to 1) hindcast
 historical fire regimes, forest structure and function, including
 responses to logging and fire suppression and 2), project future changes
 in fire regimes and vegetation structure, including conifer and oak basal
 area and shrub cover, under future climate (2015-2098) and forest
 management scenarios. Model output for five validated parameterizations
 are provided. The code and data were designed to answer the following
 research questions: 1) how will projected future climate (2015-2098)
 affect forest structure, composition, and persistence of a representative
 mixed conifer forest in the Sierra Nevada; 2) how does management in the
 form of fuel reduction treatments and thinning influence these outcomes?
 The manuscript associated with this research is titled: "Will
 thinning and fuel reduction treatments save dry conifer forests from
 climate change?"
description: FATES was run with 5 different validated parameter files (M1-M5)
 available in “validated_parameterizations_070224.zip”. All simulations
 were<strong> </strong>forced with<strong>
 </strong>hourly meteorology from the midpoint of the elevation range
 of yellow pine and mixed conifer (YPMC) forests in the southern Sierra
 Nevada (1730 m; Safford & Stevens, 2017) at a point approximately
 35 miles northeast of Fresno (37.0717, -119.2265). Pre-1870 simulations
 were initialized from bare ground and forced with pre-industrial
 CO<sub>2</sub> (280 ppm) and dynamically downscaled (Rahimi et
 al., 2022) ERA5 reanalysis meteorology (Hersbach et al., 2020) for 700
 simulation years. Pre-industrial meteorology was represented by recycling
 1951-1980 meteorology because this time period had the same mean
 temperature in the southern Sierra Nevada as the pre-industrial period.
 The meteorological driver data are available in
 “met_driver_wrf_1950_2020.tar.gz”. To recreate
 present-day forest conditions we used our pre-industrial simulations to
 represent the year 1870 and then logged the forest in accordance with
 early logging operations (Knapp et al., 2013; Stephens, 2000) by removing
 95% of all large (&gt; 75 cm dbh) conifers and varying fractions of
 medium-sized (45-75 cm dbh) pines, cedars, and firs (73%, 13%, and 33%
 respectively). We then forced the model with 20th century transient
 climate and CO2 (1870-2015; (Hersbach et al., 2020; Meinshausen et al.,
 2017; Rahimi et al., 2022). Transient climate (1951 to 2015) is in the
 “met_driver_wrf_1950_2020.tar.gz” file. We represented fire suppression
 during this period by only allowing fires to spread if fire intensity
 exceeded the threshold required to escape suppression efforts (1700 kW
 m-1) where a “hand line cannot be relied on to hold a fire” (Andrews et
 al., 2011). We calibrated the ignition rate so that annual burned area in
 the early 21st century aligned with observations (Williams et al.,
 2023). To simulate future climate we forced FATES with
 dynamically downscaled (Rahimi et al., 2022) FGOALS-g3 climate model
 projections (Li et al., 2020) under the SSP3-7.0 emissions scenario
 (2015-2098). Future meteorological data are provided in
 “met_driver_wrf_ssp370.tar.gz”. We used three forest treatment scenarios:
 1) “no treatment” 2) a “single treatment” in 2015 and 3) “continuous
 treatment” where the forest was treated every 14 years. Based on
 recommended intensive thinning protocols (North et al., 2007, 2022), our
 treatments removed small trees (&lt; 50 cm dbh) until relative stand
 density index (rSDI) was below 25%. If rSDI was still above 25% after
 removing small trees we thinned larger trees (50-75 cm dbh). Trees larger
 than 75 cm dbh were not removed and pines larger than 50 cm were not
 removed. Based on prior analyses of the effects of prescribed fire on fuel
 loads (Knapp et al., 2017; Stephens and Moghaddas, 2005; Vaillant et al.,
 2009) we removed 64% of surface fuels in each treatment. All future
 scenarios assumed that wildfire suppression would continue in the future.
 All model output is available as a timeseries (1870-2098) in
 “processed_fates_output_timeseries_1830-2098.tar.gz”
 <strong>References</strong>
 Andrews, P., Heinsch, F., Schelvan, L., 2011. How to generate and
 interpret fire characteristics charts for surface and crown fire behavior.
 U.S. Department of Agriculture, Forest Service, Fort Collins,
 CO. Hersbach, H., Bell, B., Berrisford, P., Hirahara,
 S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R.,
 Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo,
 G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G.,
 Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes,
 R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R.J., Hólm,
 E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti,
 G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., Thépaut, J.-N.,
 2020. The ERA5 global reanalysis. Quarterly Journal of the Royal
 Meteorological Society 146, 1999–2049.
 https://doi.org/10.1002/qj.3803 Knapp, E.E., Lydersen,
 J.M., North, M.P., Collins, B.M., 2017. Efficacy of variable density
 thinning and prescribed fire for restoring forest heterogeneity to
 mixed-conifer forest in the central Sierra Nevada, CA. Forest Ecology and
 Management 406, 228–241.
 https://doi.org/10.1016/j.foreco.2017.08.028 Knapp,
 E.E., Skinner, C.N., North, M.P., Estes, B.L., 2013. Long-term overstory
 and understory change following logging and fire exclusion in a Sierra
 Nevada mixed-conifer forest. Forest Ecology and Management 310, 903–914.
 https://doi.org/10.1016/j.foreco.2013.09.041 Li, L.,
 Yu, Y., Tang, Y., Lin, P., Xie, J., Song, M., Dong, L., Zhou, T., Liu, L.,
 Wang, Lu, Pu, Y., Chen, X., Chen, L., Xie, Z., Liu, Hongbo, Zhang, L.,
 Huang, X., Feng, T., Zheng, W., Xia, K., Liu, Hailong, Liu, J., Wang, Y.,
 Wang, Longhuan, Jia, B., Xie, F., Wang, B., Zhao, S., Yu, Z., Zhao, B.,
 Wei, J., 2020. The Flexible Global Ocean-Atmosphere-Land System Model
 Grid-Point Version 3 (FGOALS-g3): Description and Evaluation. Journal of
 Advances in Modeling Earth Systems 12, e2019MS002012.
 https://doi.org/10.1029/2019MS002012 Meinshausen, M.,
 Vogel, E., Nauels, A., Lorbacher, K., Meinshausen, N., Etheridge, D.M.,
 Fraser, P.J., Montzka, S.A., Rayner, P.J., Trudinger, C.M., Krummel, P.B.,
 Beyerle, U., Canadell, J.G., Daniel, J.S., Enting, I.G., Law, R.M.,
 Lunder, C.R., O’Doherty, S., Prinn, R.G., Reimann, S., Rubino, M.,
 Velders, G.J.M., Vollmer, M.K., Wang, R.H.J., Weiss, R., 2017. Historical
 greenhouse gas concentrations for climate modelling (CMIP6). Geoscientific
 Model Development 10, 2057–2116.
 https://doi.org/10.5194/gmd-10-2057-2017 North, M.,
 Innes, J., Zald, H., 2007. Comparison of thinning and prescribed fire
 restoration treatments to Sierran mixed-conifer historic conditions. Can.
 J. For. Res. 37, 331–342. https://doi.org/10.1139/X06-236
 North, M.P., Tompkins, R.E., Bernal, A.A., Collins, B.M.,
 Stephens, S.L., York, R.A., 2022. Operational resilience in western US
 frequent-fire forests. Forest Ecology and Management 507, 120004.
 https://doi.org/10.1016/j.foreco.2021.120004 Rahimi,
 S., Krantz, W., Lin, Y.-H., Bass, B., Goldenson, N., Hall, A., Lebo, Z.J.,
 Norris, J., 2022. Evaluation of a Reanalysis-Driven Configuration of WRF4
 Over the Western United States From 1980 to 2020. Journal of Geophysical
 Research: Atmospheres 127, e2021JD035699.
 https://doi.org/10.1029/2021JD035699 Stephens, S.L.,
 2000. MIXED CONIFER AND RED FIR FOREST STRUCTURE AND USES IN 1899 FROM THE
 CENTRAL AND NORTHERN SIERRA NEVADA, CALIFORNIA. Madroño 47,
 43–52. Stephens, S.L., Moghaddas, J.J., 2005.
 Experimental fuel treatment impacts on forest structure, potential fire
 behavior, and predicted tree mortality in a California mixed conifer
 forest. Forest Ecology and Management 215, 21–36.
 https://doi.org/10.1016/j.foreco.2005.03.070 Vaillant,
 N.M., Fites-Kaufman, J.A., Stephens, S.L., 2009. Effectiveness of
 prescribed fire as a fuel treatment in Californian coniferous forests.
 Int. J. Wildland Fire 18, 165–175. Williams, J.N.,
 Safford, H.D., Enstice, N., Steel, Z.L., Paulson, A.K., 2023.
 High-severity burned area and proportion exceed historic conditions in
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 https://doi.org/10.1002/ecs2.4397
description: # FATES projections of forest structure and composition (1830-2098) at a
 mixed conifer site in the southern Sierra Nevada
 [https://doi.org/10.5061/dryad.pnvx0k6z1](https://doi.org/10.5061/dryad.pnvx0k6z1) ## Description of the data and file structure The code and data provided here were used to hindcast historical fire regimes, forest structure and function in a mixed conifer forest in California's Sierra Nevada mountains. This included hindcasting responses to logging and fire suppression. These data were also used to project future changes in fire regimes and vegetation structure, including conifer and oak basal area and shrub cover, under future climate (2015-2098) and forest management scenarios. ### Files #### **File: `met_driver_wrf_1950_2020.tar.gz`** This file contains the **hourly meteorological forcing data** used for both the pre-industrial and 20th-century (1870–2015) FATES simulations. Key features include: * Dynamically downscaled WRF meteorology (Rahimi et al., 2022) based on ERA5 reanalysis (Hersbach et al., 2020). * Covers the time period **1950 to 2020**, with 1951–1980 used as a repeating proxy for pre-industrial climate due to its matching mean pre-industrial temperature in the southern Sierra Nevada. * Coordinates: 37.0717, -119.2265 (approx. 1730 m elevation), representative of yellow pine and mixed conifer (YPMC) forests. * Used in both **pre-1870 initialization runs** (with pre-industrial CO₂ at 280 ppm) and the **historical transient simulations** through 2015. --- #### **File: `met_driver_wrf_ssp370.tar.gz`** This file contains the **future meteorological forcing data** for FATES simulations under the **SSP3-7.0 emissions scenario**: * Source: FGOALS-g3 climate model projections (Li et al., 2020), dynamically downscaled via Rahimi et al. (2022). * Time span: **2015 to 2098**. * Used to drive simulations under three forest management scenarios: 1. No treatment, 2. Single treatment in 2015, 3. Continuous treatments every 14 years. * All scenarios assume continued wildfire suppression, with fire spread modeled only above a 1700 kW m⁻¹ threshold (Andrews et al., 2011). --- #### **File: `validated_parameterizations_070224.zip`** This archive contains **five validated parameter files (M1–M5)** used to configure FATES simulations. * Parameter sets were pre-validated and are used to explore structural and functional variation in simulated forest dynamics. * All simulation ensembles (historical and future) use these parameterizations to capture a range of ecosystem responses. --- #### **File: `column_descriptions_for_fates_output.csv`** This CSV file provides **descriptive metadata** for the variables included in the processed FATES output timeseries: * Corresponds to the data in `processed_fates_output_timeseries_1830-2098.tar.gz`. * Each column includes variable name, units, and brief description to facilitate interpretation and downstream analysis. --- #### **File: `processed_fates_output_timeseries_1830-2098.tar.gz`** This archive contains **time series output data** from FATES simulations spanning **1830 to 2098**, representing the full temporal evolution of YPMC forest dynamics under historical and future climate and management scenarios. **Time Span** - **1830–1869**: Spin-up phase using recycled 1951–1980 meteorology to simulate pre-industrial climate conditions with CO₂ fixed at 280 ppm. - **1870–2015**: Historical simulations incorporating: - Forest logging in 1870 following early Euro-American operations (Knapp et al., 2013; Stephens, 2000). - Transient 20th century meteorology and CO₂ concentrations (Hersbach et al., 2020; Meinshausen et al., 2017). - Wildfire suppression mechanisms calibrated to match observed burn rates in the early 21st century (Williams et al., 2023). - **2015–2098**: Future projections under SSP3-7.0 using downscaled FGOALS-g3 climate data (Rahimi et al., 2022). **Simulation Scenarios** Each simulation uses one of **five validated parameterizations** (M1–M5) from `validated_parameterizations_070224.zip`. Three distinct **forest management treatments** are included: 1. **No Treatment** 2. **Single Treatment (2015)**: Forest thinned once using North et al. (2007, 2022) protocols. 3. **Continuous Treatment**: Repeated thinning every 14 years through 2098. **Data Structure** - The archive contains time series outputs organized by scenario and parameterization. - Key ecosystem variables include biomass pools, fluxes, stand structure, fire occurrence, and carbon cycling metrics. - Variable definitions and units are documented in `column_descriptions_for_fates_output.csv`. **Usage Notes** - The output data is suitable for long-term analysis of forest structure, fire dynamics, climate sensitivity, and management outcomes. - It supports comparative studies across treatments and parameter sets to evaluate forest resilience, carbon sequestration, and disturbance response. --- #### **Software: `fates-ca_ahb.zip`** **Description:** FATES source code used for all simulations. For technical information about the FATES model please see the [FATES wiki](https://github.com/NGEET/fates/wiki). This version of the FATES source code has three important modifications compared to the FATES main branch: 1) Inter-patch dispersal to capture conifer dispersal limitation into large burned areas 2) Plant functional type-specific resprouting to capture observed post-fire resprouting in YPMC oaks and shrubs 3) Fire-sensitive germination rates to capture observed behavior in Ceanothus spp. and Manzanita spp. ## Code/software for viewing files Any open source software capable of reading netCDF files can be used to view the data in the parameter files and meteorological driver data. Any open source software capable of reading text and csv files can be used to view the model source code and model output.