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

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 three convergent causal identification strategies, the study documents that fires on tribal land are on average 15.7 times larger than fires on adjacent non-tribal land — a disparity that persists at 6.5× even after excluding the catastrophic 2003 and 2007 fire years. The theoretical argument connects this disparity to the historical suppression of traditional Indigenous burning practices under federal fire management policy, which produced structural fuel load accumulation on tribal territories. Data Contents This archive contains all inputs, intermediate datasets, and outputs necessary to fully replicate the analysis from raw public data sources. Sixteen files are included: six publication-quality figures (Figures 1–6), eight CSV data files, and two regression summary text files. The complete replication script (tribal_fire_full_study.py, 1,560 lines, available at [repository URL]) reproduces all results in a single execution and downloads source data directly from public APIs. The primary data files are: the county × year PM2.5 panel (816 observations, 43 California counties, 2000–2018); the classified California fire perimeter dataset (4,496 fires with tribal land indicator); the tribal nation fire burden summary (20 nations ranked by total acres burned); event study coefficients with 95% confidence intervals; county-level lightning flash density from the NASA LIS/OTD HRFC climatology; and county × year lightning panels from the NOAA Storm Events database. The Smoke.ipynb notebook contains exploratory analysis of the Cedar Fire 2003 PM2.5 event. 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). Lightning strike data from NOAA Storm Events and the NASA LIS/OTD 0.5-degree High Resolution Full Climatology (HRFC) are included as supplementary data files. All spatial operations use the California Albers Equal Area projection (EPSG:3310) for area and centroid calculations. Causal identification employs three strategies: (1) regression discontinuity at tribal land boundaries (four bandwidth specifications, 10–100 km); (2) propensity score matching with caliper 0.05 (112 matched fire pairs, all post-match SMDs < 0.05); (3) event study with county and year fixed effects and pre-trend joint F-test (F = 2.39, p = 0.104 — no pre-trend). The PM2.5 baseline regression uses county-clustered standard errors to account for serial correlation (Durbin-Watson = 0.399). Key Findings Mean fire size on tribal land: 42,572 acres. Mean fire size on non-tribal land: 2,706 acres. Ratio: 15.7× (Mann-Whitney p < 0.0001). The disparity is stable across all sensitivity specifications. The 2003 Cedar Fire burned across nine San Diego County tribal nations, producing a maximum AQI of 328 (Hazardous) — a 125% spike over baseline. The top 10 tribal nations by total fire burden are dominated by San Diego County nations (Barona: 873,341 total acres; Viejas: 546,467 acres) and the Karuk Tribe of Siskiyou County (419,722 acres). The event study post-period F-test is significant (F = 5.37, p = 0.006), confirming elevated PM2.5 following tribal fire years. Computational Environment Python 3.12 · geopandas 1.1.3 · pandas 2.2.2 · statsmodels 0.14.6 · scipy 1.16.3 · linearmodels 7.0 · scikit-learn 1.6.1 · netCDF4 1.7.4 · Executed on Google Colab CPU runtime · Approximate runtime: 8–12 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.