Wildfire Size Disparity on Tribal Lands in California and Associated PM2.5 Burden, 2000–2018

Authors: Blind for review. Version 6.0 — June 2026. Adds Section 16d: boundary stability tests (label permutation placebo RD, TIGER vintage check, covariate balance). All 185 CA tribal boundaries confirmed G2101/G2102/G2160 federally recognized designations. Permutation p<0.001 (0/500 placebos exceed real RD estimate). Outputs: figure_s1_boundary_stability.png, boundary_stability_results.txt, boundary_stability_table.csv, placebo_rd_distribution.csv. Study Overview This dataset supports a quantitative investigation of wildfire size disparity between federally recognized tribal lands and non-tribal lands in California from 2000 to 2018, and the associated PM2.5 air quality burden borne by tribal communities. Using spatial analysis, panel econometrics, and four convergent causal identification strategies, the study documents that fires on tribal trust land are on average 6.4 times larger than fires on non-tribal land — a disparity that persists at 3.1× after excluding boundary-straddling fires and at 4.8× after excluding the catastrophic 2003 and 2007 fire years. All specifications are statistically significant (Mann-Whitney p < 0.0001). Tribal fire years are associated with a statistically significant increase in county mean PM2.5 of 0.845 μg/m³ (two-way fixed effects OLS, county + year FE, clustered SE, p = 0.0087). The Bureau of Indian Affairs — the only federal agency with statutory trust responsibility toward tribal nations — managed 7.0% of fires on tribal trust land during the study period. CAL FIRE and state agencies combined managed 54.6%, operating without trust obligations or mandates to integrate Traditional Ecological Knowledge. Data Contents This archive contains all outputs necessary to replicate the analysis. The complete replication pipeline (FIRE.ipynb) reproduces all results in a single execution and downloads source data directly from public APIs. Files included: FIRE.ipynb — Full integrated analysis pipeline (Sections 1–22) ca_fires_tribal_classified.csv — 4,496 California fire perimeters with tribal land classification tribal_fire_pm25_panel.csv — 816 county-year observations (PM2.5 + fire variables) tribal_nation_fire_burden.csv — Fire burden summary by tribal nation (top 20) event_study_coefficients.csv — Event study coefficients (t = −5 to +5) with 95% CI regression_results.txt — Full two-way FE OLS output including all fixed effects figure1_tribal_fire_analysis.png — Mean fire size by year; size distribution; top nations figure2_cedar_fire_aqi.png — San Diego County AQI 2000–2018; Cedar Fire 2003 figure3_regression_discontinuity.png — RD scatter plots at 10, 25, 50, 100km bandwidths figure4_psm_overlap.png — Propensity score overlap before and after matching figure5_psm_differences.png — PSM matched pair differences distribution figure6_event_study.png — Event study coefficients with pre-trend test figure7_causal_identification.png — Convergent causal identification evidence README.md — Full documentation including revision notes Methods Summary Fire perimeter data were obtained from the NIFC Historical GeoMAC Perimeters archive (2000–2018) via ArcGIS REST API. Tribal boundaries are from the Census TIGER/Line AIANNH 2025 vintage (185 California areas). PM2.5 concentrations are from EPA AQS daily FRM/FEM monitoring data (parameter 88101; 580,066 California daily observations). All spatial operations use the California Albers Equal Area projection (EPSG:3310) for area and centroid calculations. Causal identification employs four strategies: (1) regression discontinuity at tribal land boundaries (four bandwidth specifications, 10–100 km); (2) propensity score matching with caliper 0.05 (93 matched fire pairs); (3) event study with county and year fixed effects and pre-trend joint F-test (F = 1.720, p = 0.206 — no pre-trend); (4) two-way fixed effects DiD (county + year FE, clustered SE). Key Results Fire Size Disparity Specification Tribal mean (acres) Non-tribal mean (acres) Ratio p-value Full dataset 17,265 2,706 6.4× < 0.0001 Excl. 2003 14,845 2,782 5.3× < 0.0001 Excl. 2003 + 2007 13,545 2,808 4.8× < 0.0001 Excl. boundary-straddlers 8,253 2,706 3.1× < 0.0001 PM2.5 Health Burden Estimator Coefficient p-value Two-way FE OLS (primary) 0.845 μg/m³ 0.0087 Event study post-period (F-test) F = 3.350 0.0320 Cedar Fire 2003 San Diego max AQI 328 (Hazardous) +124% spike Managing Agency Distribution (Tribal Trust Lands) Agency Fires (N) Share CAL FIRE (CDF) 39 27.3% State Agency 39 27.3% U.S. Forest Service 33 23.1% Bureau of Indian Affairs ✦ 10 7.0% Bureau of Land Management 6 4.2% Other / Unknown 16 11.2% ✦ Only agency with statutory trust responsibility toward tribal nations. Revision Notes (v2.0 — June 2026) Version 2.0 corrects several methodological issues identified after the initial deposit: 1. Spatial join deduplication (critical fix) The v1.0 pipeline used sjoin with predicate="intersects" without deduplication, producing inflated tribal fire counts. Two issues were identified and corrected: (a) 12 NIFC duplicate polygon records (same fire geometry entered twice in the source data) were identified and removed; (b) 8 fires whose perimeters straddled multiple tribal boundaries were retained as single records, assigned to the tribal nation with the largest intersection area. After deduplication: 111 tribal fires (from 143 pre-dedup). Primary ratio: 6.4× (from 15.7× in v1.0). 2. Two-way fixed effects (Section 15) The primary DiD estimator now includes county + year fixed effects. The v1.0 year-only specification (p = 0.37) is replaced by the two-way FE specification (p = 0.0087). 3. 2SLS removed Both available lightning instruments have weak first stages (F < 10). v1.0 reported inflated 2SLS estimates; these are removed entirely in v2.0. IV-related output files (tribal_fire_pm25_panel_iv.csv, lightning_county_year.csv) are removed from this deposit. 4. Boundary-straddler sensitivity Section 6 now correctly reports the fire size ratio excluding boundary-straddling fires (3.1×) using content-key matching robust to dataframe index resets. Computational Environment Python 3.12.13 · geopandas 1.1.3 · pandas 2.2.2 · statsmodels 0.14.6 · scipy 1.16.3 · scikit-learn 1.6.1 · netCDF4 1.7.4 · Executed on Google Colab CPU runtime · Approximate runtime: 20–30 minutes License Creative Commons Attribution 4.0 International (CC BY 4.0). Users are free to share and adapt the material for any purpose provided appropriate credit is given to the authors. Citation Wildfire Size Disparity on Tribal Lands in California and Associated PM2.5 Burden, 2000–2018 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.20665230