LANDFIRE Related Articles

Picotte, J.J., Peterson, B., Meier, G., and Howard, S.M., 2016, 1984–2010 trends in fire burn severity and area for the conterminous US: International Journal of Wildland Fire, v. 25, no. 4, p. 413–420, at https://doi.org/10.1071/wf15039.

Padilla, C.J., Martin, J.T., Cain, J.W., III, and Gompper, M.E., 2024, Abiotic and demographic drivers of flea parasitism on deer mice in a recovering mixed-conifer forest a decade postfire: The Journal of Parasitology, v. 110, no. 4, p. 375–385, at https://doi.org/10.1645/23-45.

Lewis, W.B., Chandler, R.B., Delancey, C.D., Rushton, E., Wann, G.T., McConnell, M.D., and Martin, J.A., 2022, Abundance and distribution of ruffed grouse Bonasa umbellus at the southern periphery of the range: Wildlife Biology, v. 2022, no. 5, article e01017, at https://doi.org/10.1002/wlb3.01017.

Lombardo, S., Kinney, J., Blake, D., Chase, S., Stovall, A., Siddiqi, A., Arquilla, K., Israel, S., Wood, D., et al., 2023, Accessible satellite data decision support systems for Yurok Tribe forest management: Acta Astronautica, v. 213, p. 777–791, at https://doi.org/10.1016/j.actaastro.2023.09.040.

Fusco, E.J., Rau, B.M., Falkowski, M., Filippelli, S., and Bradley, B.A., 2019, Accounting for aboveground carbon storage in shrubland and woodland ecosystems in the Great Basin: Ecosphere, v. 10, no. 8, article e02821, at https://doi.org/10.1002/ecs2.2821.

Chandler, H.C., Jenkins, C.L., and Bauder, J.M., 2021, Accounting for geographic variation in species-habitat associations during habitat suitability modeling: Ecological Applications, v. 32, no. 2, article e2504, at https://doi.org/10.1002/eap.2504.

Hurteau, M.D., Hungate, B.A., and Koch, G.W., 2009, Accounting for risk in valuing forest carbon offsets: Carbon Balance and Management, v. 4, article 1, at https://doi.org/10.1186/1750-0680-4-1.

White, M.A., Shaw, J.D., and Ramsey, R.D., 2005, Accuracy assessment of the vegetation continuous field tree cover product using 3954 ground plots in the south-western USA: International Journal of Remote Sensing, v. 26, no. 12, p. 2699–2704, at https://doi.org/10.1080/01431160500080626.

D’Elia, J., Haig, S.M., Johnson, M., Marcot, B.G., and Young, R., 2015, Activity-specific ecological niche models for planning reintroductions of California condors (Gymnogyps californianus): Biological Conservation, v. 184, p. 90–99, at https://doi.org/10.1016/j.biocon.2015.01.002.

Moody, M.J., Stoll, R., and Bailey, B.N., 2023, Adaptation of QES-Fire, a dynamically coupled fast response wildfire model for heterogeneous environments: International Journal of Wildland Fire, v. 32, no. 5, p. 749–766, at https://doi.org/10.1071/wf22190.

Calzado-Martinez, C., Brunson, M.W., Koutzoukis, S., Baggio, J., and Veblen, K.E., 2023, Addressing barriers to proactive restoration of at-risk sagebrush communities—A causal layered analysis: Restoration Ecology, v. 31, no. 7, article e13897, at https://doi.org/10.1111/rec.13897.

Liu, H., Shu, L., Liu, X., Cheng, P., Wang, M., and Huang, Y., 2025, Advancements in artificial intelligence applications for forest fire prediction: Forests, v. 16, no. 4, article 704, at https://doi.org/10.3390/f16040704.

Thompson, M.P., Calkin, D.E., Gilbertson-Day, J.W., and Ager, A.A., 2011, Advancing effects analysis for integrated, large-scale wildfire risk assessment: Environmental Monitoring and Assessment, v. 179, no. 4, p. 217–39, at https://doi.org/10.1007/s10661-010-1731-x.

Aune, K.T., Zaitchik, B.F., Curriero, F.C., Davis, M.F., and Smith, G.S., 2023, Agreement in extreme precipitation exposure assessment is modified by race and social vulnerability: Frontiers in Epidemiology, v. 3, article 1128501, at https://doi.org/10.3389/fepid.2023.1128501.

Dorshow, W.B., and Wills, W.H., 2022, Agricultural suitability of the Chaco Canyon Region, New Mexico—Implications for settlement patterning during the great house period (ca. AD 850 to 1200): Journal of Archaeological Science - Reports, v. 46, article 103650, at https://doi.org/10.1016/j.jasrep.2022.103650.

Yu, H., Guenther, A., Gu, D., Warneke, C., Geron, C., Goldstein, A., Graus, M., Karl, T., Kaser, L., et al., 2017, Airborne measurements of isoprene and monoterpene emissions from southeastern U.S. forests: Science of the Total Environment, v. 595, p. 149–158, at https://doi.org/10.1016/j.scitotenv.2017.03.262.

Houtman, R.M., Montgomery, C.A., Gagnon, A.R., Calkin, D.E., Dietterich, T.G., McGregor, S., and Crowley, M., 2013, Allowing a wildfire to burn—Estimating the effect on future fire suppression costs: International Journal of Wildland Fire, v. 22, no. 7, p. 871–882, at https://doi.org/10.1071/WF12157.

Schafer, T.L.J., Breck, S.W., Baruch-Mordo, S., Lewis, D.L., Wilson, K.R., Mao, J.S., and Day, T.L., 2018, American black bear den-site selection and characteristics in an urban environment: Ursus, v. 29, no. 1, p. 25–31, at https://doi.org/10.2192/URSUS-D-17-00004.2.

Kochanski, A.K., Clough, K., Farguell, A., Mallia, D.V., Mandel, J., and Hilburn, K., 2023, Analysis of methods for assimilating fire perimeters into a coupled fire-atmosphere model: Frontiers in Forests and Global Change, v. 6, article 1203578, at https://doi.org/10.3389/ffgc.2023.1203578.

Page, W.G., Wagenbrenner, N.S., Butler, B.W., and Blunck, D.L., 2019, An analysis of spotting distances during the 2017 fire season in the Northern Rockies, USA: Canadian Journal of Forest Research, v. 49, no. 3, p. 317–325, at https://doi.org/10.1139/cjfr-2018-0094.

Ager, A.A., Barros, A.M.G., Day, M.A., Preisler, H.K., Spies, T.A., and Bolte, J., 2018, Analyzing fine-scale spatiotemporal drivers of wildfire in a forest landscape model: Ecological Modelling, v. 384, p. 87–102, at https://doi.org/10.1016/j.ecolmodel.2018.06.018.

Ager, A.A., Vaillant, N.M., Finney, M.A., and Preisler, H.K., 2012, Analyzing wildfire exposure and source-sink relationships on a fire prone forest landscape: Forest Ecology and Management, v. 267, p. 271–283, at https://doi.org/10.1016/j.foreco.2011.11.021.

Turco, M., Abatzoglou, J.T., Herrera, S., Zhuang, Y., Jerez, S., Lucas, D.D., AghaKouchak, A., and Cvijanovic, I., 2023, Anthropogenic climate change impacts exacerbate summer forest fires in California: Proceedings of the National Academy of Sciences of the United States of America, v. 120, no. 25, article e2213815120, at https://doi.org/10.1073/pnas.2213815120.

Squires, J.R., Olson, L.E., Ivan, J.S., McDonald, P.M., and Holbrook, J.D., 2025, Anthropogenically protected but naturally disturbed—A specialist carnivore at its southern range periphery: Biodiversity and Conservation, v. 34, p. 401–427, at https://doi.org/10.1007/s10531-024-02978-8.

Moll, R.J., Jackson, P.J., Wakeling, B.F., Lackey, C.W., Beckmann, J.P., Millspaugh, J.J., and Montgomery, R.A., 2021, An apex carnivore’s life history mediates a predator cascade: Oecologia, v. 196, no. 1, p. 223–234, at https://doi.org/10.1007/s00442-021-04927-6.

Rwanga, S.S., and Ndambuki, J.M., 2014, Application of geographical information systems and FARSITE in fire spread modelling: International Journal of Environment and Sustainable Development, v. 13, no. 2, p. 185–203, at https://doi.org/10.1504/IJESD.2014.060201.

Smith, J.E., Billmire, M., French, N.H.F., and Domke, G.M., 2024, Application of the wildland fire emissions inventory system to estimate fire emissions on forest lands of the United States: Carbon Balance and Management, v. 19, no. 1, article 26, at https://doi.org/10.1186/s13021-024-00274-0.

Williamson, C.R., Campa, H., III, Locher, A.B., Winterstein, S.R., and Beyer, D.E.J., 2021, Applications of integrating wildlife habitat suitability and habitat potential models: Wildlife Society Bulletin, v. 45, no. 1, p. 70–84, at https://doi.org/10.1002/wsb.1152.

Meunier, J., and Shea, M.E., 2020, Applying the usual rules to an unusual ecological situation—Fire rotation in Great Lakes Pine Forests: Forest Ecology and Management, v. 472, article 118246, at https://doi.org/10.1016/j.foreco.2020.118246.

Cameron, D.R., Cohen, B.S., and Morrison, S.A., 2012, An approach to enhance the conservation-compatibility of solar energy development: PLoS ONE, v. 7, no. 6, article e38437, at https://doi.org/10.1371/journal.pone.0038437.

Vaillant, N.M., and Ager, A.A., 2014, ArcFuels—An ArcMap toolbar for fuel treatment planning and wildfire risk assessment: Fire Management Today, v. 74, no. 2, p. 21–23, at https://www.frames.gov/documents/usfs/fmt/fmt_74-1.pdf.

Hu, F.S., Higuera, P.E., Duffy, P., Chipman, M.L., Rocha, A.V., Young, A.M., Kelly, R., and Dietze, M.C., 2015, Arctic tundra fires—Natural variability and responses to climate change: Frontiers in Ecology and the Environment, v. 13, no. 7, p. 369–377, at https://doi.org/10.1890/150063.

Polasky, S., Johnson, K., Keeler, B., Kovacs, K., Nelson, E., Pennington, D., Plantinga, A.J., and Withey, J., 2012, Are investments to promote biodiversity conservation and ecosystem services aligned?: Oxford Review of Economic Policy, v. 28, no. 1, p. 139–163, at https://doi.org/10.1093/oxrep/grs011.

Wion, A.P., Weisberg, P.J., Pearse, I.S., and Redmond, M.D., 2019, Aridity drives spatiotemporal patterns of masting across the latitudinal range of a dryland conifer: Ecography, v. 43, no. 4, p. 569–580, at https://doi.org/10.1111/ecog.04856.

Saeedimoghaddam, M., Nearing, G., Goodrich, D.C., Hernandez, M., Guertin, D.P., Metz, L.J., Wei, H., Ponce-Campos, G., Burns, S., et al., 2024, An artificial neural network to estimate the foliar and ground cover input variables of the Rangeland Hydrology and Erosion Model: Journal of Hydrology, v. 631, article 130835, at https://doi.org/10.1016/j.jhydrol.2024.130835.

Fremgen-Tarantino, M.R., Olsoy, P.J., Frye, G.G., Connelly, J.W., Krakauer, A.H., Patricelli, G.L., and Forbey, J.S., 2021, Assessing accuracy of GAP and LANDFIRE land cover datasets in winter habitats used by greater sage-grouse in Idaho and Wyoming, USA: Journal of Environmental Management, v. 280, article 111720, at https://doi.org/10.1016/j.jenvman.2020.111720.

Cardil, A., Monedero, S., Ramírez, J., and Silva, C.A., 2019, Assessing and reinitializing wildland fire simulations through satellite active fire data: Journal of Environmental Management, v. 231, p. 996–1003, at https://doi.org/10.1016/j.jenvman.2018.10.115.

Theobald, D.M., Crooks, K.R., and Norman, J.B., 2011, Assessing effects of land use on landscape connectivity—Loss and fragmentation of western U.S. forests: Ecological Applications, v. 21, no. 7, p. 2445–2458, at https://doi.org/10.1890/10-1701.1.

Wimberly, M.C., Cochrane, M.A., Baer, A.D., and Kari, P., 2009, Assessing fuel treatment effectiveness using satellite imagery and spatial statistics: Ecological Applications, v. 19, no. 6, p. 1377–1384, at https://doi.org/10.1890/08-1685.1.

Woodie, M.B., Tomcho, A., Barnhill, L.M., and McComb, B.C., 2023, Assessing golden-winged warbler dispersal habitat in a highly parcelized landscape: Wildlife Society Bulletin, v. 47, no. 3, article e1473, at https://doi.org/10.1002/wsb.1473.

Paveglio, T.B., Edgeley, C.M., and Stasiewicz, A.M., 2018, Assessing influences on social vulnerability to wildfire using surveys, spatial data and wildfire simulations: Journal of Environmental Management, v. 213, p. 425–439, at https://doi.org/10.1016/j.jenvman.2018.02.068.

Buchholtz, E.K., Kreitler, J., Shinneman, D.J., Crist, M., and Heinrichs, J., 2023, Assessing large landscape patterns of potential fire connectivity using circuit methods: Landscape Ecology, v. 38, p. 1663–1676, at https://doi.org/10.1007/s10980-022-01581-y.

Halofsky, J.E., Hemstrom, M.A., Conklin, D.R., Halofsky, J.S., Kerns, B.K., and Bachelet, D., 2013, Assessing potential climate change effects on vegetation using a linked model approach: Ecological Modelling, v. 266, p. 131–143, at https://doi.org/10.1016/j.ecolmodel.2013.07.003.

Li, M., Huang, C., Zhu, Z., Shi, H., Lu, H., and Peng, S., 2009, Assessing rates of forest change and fragmentation in Alabama, USA, using the vegetation change tracker model: Forest Ecology and Management, v. 257, no. 6, p. 1480–1488, at https://doi.org/10.1016/j.foreco.2008.12.023.

Ghimire, S.R., Schumacher, B., Swanson, S., Hall, R., Hall, E.S., Zambrana, J., and Johnston, J.M., 2025, Assessing riparian functioning condition for improved ecosystem services—A case study of the Back Creek watershed (Virginia, USA): Journal of Environmental Management, v. 375, article 124154, at https://doi.org/10.1016/j.jenvman.2025.124154.

Scott, V., Juran, L., Ling, E.J., Benham, B., and Spiller, A., 2020, Assessing strontium and vulnerability to strontium in private drinking water systems in Virginia: Water, v. 12, no. 4, article 1053, at https://doi.org/10.3390/w12041053.

Shams, S.B., Boehnert, J., and Wilhelmi, O., 2025, Assessing the impact of conservation practices on post-wildfire recovery of evergreen and conifer forests using remote sensing data: Fire, v. 8, no. 3, article 92, at https://doi.org/10.3390/fire8030092.

Viteri, M.C., Stegner, M.A., and Hadly, E.A., 2021, Assessing the reliability of raptor pellets in recording local small mammal diversity: Quaternary Research, v. 106, p. 1–10, at https://doi.org/10.1017/qua.2021.59.

Wilson, A.C., Nolin, A.W., and Bladon, K.D., 2021, Assessing the role of snow cover for post-wildfire revegetation across the Pacific Northwest: Journal of Geophysical Research—Biogeosciences, v. 126, no. 11, article e2021JG006465, at https://doi.org/10.1029/2021jg006465.

Ager, A.A., Palaiologou, P., Evers, C.R., Day, M.A., and Barros, A.M.G., 2018, Assessing transboundary wildfire exposure in the southwestern United States: Risk Analysis, v. 38, no. 10, p. 2105–2127, at https://doi.org/10.1111/risa.12999.

Monroe, A.P., Nauman, T.W., Aldridge, C.L., O’Donnell, M.S., Duniway, M.C., Cade, B.S., Manier, D.J., and Anderson, P.J., 2022, Assessing vegetation recovery from energy development using a dynamic reference approach: Ecology and Evolution, v. 12, no. 2, article e8508, at https://doi.org/10.1002/ece3.8508.

Malashin, I.P., Masich, I., Nelyub, V., Borodulin, A., Gantimurov, A., and Tynchenko, V., 2025, Assessing wildfire extents in Siberian forests using machine learning: Scientific Reports, v. 15, no. 1, article 32834, at https://doi.org/10.1038/s41598-025-17465-5.

Sparklin, B.D., Doherty, K.E., Rodhouse, T.J., Lonneker, J.J., Spaak, J., Cross, T.B., and Warren, J.M., 2024, An assessment of conservation opportunities within sagebrush ecosystems of US national parks and wildlife refuges: Rangeland Ecology & Management, v. 97, p. 94–106, at https://doi.org/10.1016/j.rama.2024.09.005.

Palomaki, R.T., Rittger, K., Lenard, S.J.P., Bair, E., Dozier, J., Skiles, S.M., and Painter, T.H., 2025, Assessment of methods for mapping snow albedo from MODIS: Remote Sensing of Environment, v. 326, article 114742, at https://doi.org/10.1016/j.rse.2025.114742.

Reeves, M.C., Hanberry, B.B., Wilmer, H., Kaplan, N.E., and Lauenroth, W.K., 2020, An assessment of production trends on the Great Plains from 1984 to 2017: Rangeland Ecology & Management, v. 78, p. 165–179, at https://doi.org/10.1016/j.rama.2020.01.011.

Rashidi, E., Medal, H., and Hoskins, A., 2018, An attacker-defender model for analyzing the vulnerability of initial attack in wildfire suppression: Naval Research Logistics, v. 65, no. 2, p. 120–134, at https://doi.org/10.1002/nav.21792.

Henderson, C.R., Mitchell, M.S., Myers, W.L., Lukacs, P.M., and Nelson, G.P., 2018, Attributes of seasonal home range influence choice of migratory strategy in white-tailed deer: Journal of Mammalogy, v. 99, no. 1, p. 89–96, at https://doi.org/10.1093/jmammal/gyx148.

Azim, M.R., Keskin, M., Do, N., and Gul, M., 2022, Automated classification of fuel types using roadside images via deep learning: International Journal of Wildland Fire, v. 31, no. 10, p. 982–987, at https://doi.org/10.1071/WF21136.

Julianus, E., Hollingsworth, T.N., McGuire, A.D., and Kielland, K., 2019, Availability and use of moose browse in response to post-fire succession on Kanuti National Wildlife Refuge, Alaska: Alces, v. 55, p. 67–89, at https://www.alcesjournal.org/index.php/alces/article/view/231.

Jorge, M.H., Conner, L.M., Garrison, E.P., and Cherry, M.J., 2022, Avian species richness in a frequently burned ecosystem—A link between pyrodiversity and biodiversity: Landscape Ecology, v. 37, no. 4, p. 983–996, at https://doi.org/10.1007/s10980-022-01399-8.

Hysen, L., Nayeri, D., Cushman, S., and Wan, H.Y., 2022, Background sampling for multi-scale ensemble habitat selection modeling—Does the number of points matter?: Ecological Informatics, v. 72, article 101914, at https://doi.org/10.1016/j.ecoinf.2022.101914.

Helmstetter, N.A., Conway, C.J., Stevens, B.S., and Goldberg, A.R., 2020, Balancing transferability and complexity of species distribution models for rare species conservation: Diversity and Distributions, v. 27, no. 1, p. 95–108, at https://doi.org/10.1111/ddi.13174.

Ren, J., Hanan, E.J., Hicke, J.A., Kolden, C.A., Abatzoglou, J.T., Tague, C.N.L., Bart, R.R., Kennedy, M.C., Liu, M., et al., 2023, Bark beetle effects on fire regimes depend on underlying fuel modifications in semiarid systems: Journal of Advances in Modeling Earth Systems, v. 15, no. 1, article e2022MS003073, at https://doi.org/10.1029/2022MS003073.

Carroll, R.W.H., Manning, A.H., Niswonger, R., Marchetti, D., and Williams, K.H., 2020, Baseflow age distributions and depth of active groundwater flow in a snow-dominated mountain headwater basin: Water Resources Research, v. 56, no. 12, article e2020WR028161, at https://doi.org/10.1029/2020WR028161.

Yoo, M., and Wikle, C.K., 2024, A Bayesian spatio-temporal level set dynamic model and application to fire front propagation: Annals of Applied Statistics, v. 18, no. 1, p. 404–423, at https://doi.org/10.1214/23-AOAS1794.

Wells, A.G., Yackulic, C.B., Kostelnik, J., Bock, A., Zuellig, R.E., Carlisle, D.M., Roberts, J.J., Rogers, K.B., and Munson, S.M., 2024, Before the fire—Predicting burn severity and potential post-fire debris-flow hazards to conservation populations of the Colorado River cutthroat trout (Oncorhynchus clarkii pleuriticus): International Journal of Wildland Fire, v. 33, no. 11, article WF23199, at https://doi.org/10.1071/Wf23199.

Gray, S.M., Humphreys, J.M., Montgomery, R.A., Etter, D.R., VerCauteren, K.C., Kramer, D.B., and Roloff, G.J., 2022, Behavioral states in space and time—Understanding landscape use by an invasive mammal: The Journal of Wildlife Management, v. 86, no. 4, article e22211, at https://doi.org/10.1002/jwmg.22211.

Picardi, S., Coates, P., Kolar, J., O'Neil, S., Mathews, S., and Dahlgren, D., 2021, Behavioural state-dependent habitat selection and implications for animal translocations: Journal of Applied Ecology, v. 59, no. 2, p. 624–635, at https://doi.org/10.1111/1365-2664.14080.

Donnelly, J.P., Jensco, K., Kimball, J.S., Moore, J.N., Ketchum, D., Collins, D.P., and Naugle, D.E., 2024, Beneficial ‘inefficiencies’ of western ranching—Flood-irrigated hay production sustains wetland systems by mimicking historic hydrologic processes: Agriculture, Ecosystems and Environment, v. 370, article 109051, at https://doi.org/10.1016/j.agee.2024.109051.

Swaty, R., 2016, The best way to spend an hour—Reviewing LANDFIRE ecosystem descriptions and models: The Bulletin of the Ecological Society of America, v. 97, no. 2, p. 180–182, at https://doi.org/10.1002/bes2.1234.

Barnett, K., Parks, S.A., Miller, C., and Naughton, H.T., 2016, Beyond fuel treatment effectiveness—Characterizing interactions between fire and treatments in the US: Forests, v. 7, no. 10, article 237, at https://doi.org/10.3390/f7100237.

Hudson, T.D., Reeves, M.C., Hall, S.A., Yorgey, G.G., and Neibergs, J.S., 2020, Big landscapes meet big data—Informing grazing management in a variable and changing world: Rangelands, v. 43, no. 1, p. 17–28, at https://doi.org/10.1016/j.rala.2020.10.006.

Keane, R.E., Holsinger, L.M., and Loehman, R., 2020, Bioclimatic modeling of potential vegetation types as an alternative to species distribution models for projecting plant species shifts under changing climates: Forest Ecology and Management, v. 477, article 118498, at https://doi.org/10.1016/j.foreco.2020.118498.

Costanza, J.K., Abt, R.C., McKerrow, A.J., and Collazo, J.A., 2017, Bioenergy production and forest landscape change in the southeastern United States: GCB Bioenergy, v. 9, no. 5, p. 924–939, at https://doi.org/10.1111/gcbb.12386.

Stevens, J.T., Kling, M.M., Schwilk, D.W., Varner, J.M., and Kane, J.M., 2020, Biogeography of fire regimes in western U.S. conifer forests—A trait-based approach: Global Ecology and Biogeography, v. 29, no. 5, p. 944–955, at https://doi.org/10.1111/geb.13079.

Riggs, R.A., Keane, R.E., Cimon, N., Cook, R., Holsinger, L., Cook, J., DelCurto, T., Baggett, L., Justice, D., et al., 2015, Biomass and fire dynamics in a temperate forest-grassland mosaic—Integrating multi-species herbivory, climate, and fire with the FireBGCv2/GrazeBGC system: Ecological Modelling, v. 296, p. 57–78, at https://doi.org/10.1016/j.ecolmodel.2014.10.013.

Smith, T.C., Bishop, T.B.B., Duniway, M.C., Villarreal, M.L., Knight, A.C., Munson, S.M., Waller, E.K., Jensen, R., and Gill, R.A., 2023, Biophysical factors control invasive annual grass hot spots in the Mojave Desert: Biological Invasions, v. 25, p. 3839–3858, at https://doi.org/10.1007/s10530-023-03142-z.

Stephens, J.L., Dinger, E.C., Alexander, J.D., Mohren, S.R., Ralph, C.J., and Sarr, D.A., 2016, Bird communities and environmental correlates in southern Oregon and northern California, USA: PLoS ONE, v. 11, no. 10, article e0163906, at https://doi.org/10.1371/journal.pone.0163906.

Greenler, S.M., Lake, F.K., Tripp, W., McCovey, K., Tripp, A., Hillman, L.G., Dunn, C.J., Prichard, S.J., Hessburg, P.F., et al., 2024, Blending indigenous and western science—Quantifying cultural burning impacts in Karuk Aboriginal Territory: Ecological Applications, v. 34, no. 4, article e2973, at https://doi.org/10.1002/eap.2973.

Kasprak, A., Hough-Snee, N., Beechie, T., Bouwes, N., Brierley, G., Camp, R., Fryirs, K., Imaki, H., Jensen, M., et al., 2016, The blurred line between form and process—A comparison of stream channel classification frameworks: PLoS ONE, v. 11, no. 3, p. 1–31, at https://doi.org/10.1371/journal.pone.0150293.

Sauder, J.D., and Rachlow, J.L., 2014, Both forest composition and configuration influence landscape-scale habitat selection by fishers (Pekania pennanti) in mixed coniferous forests of the Northern Rocky Mountains: Forest Ecology and Management, v. 314, p. 75–84, at https://doi.org/10.1016/j.foreco.2013.11.029.

Beauregard, N.D., Theimer, T.C., Drost, C.A., and Sferra, S.J., 2024, Breeding by western Yellow-billed Cuckoos in xeroriparian habitat in southeastern Arizona: Journal of Field Ornithology, v. 95, no. 4, article 1, at https://doi.org/10.5751/JFO-00539-950401.

Davison, J.E., Coe, S., Finch, D., Rowland, E., Friggens, M., and Graumlich, L.J., 2012, Bringing indices of species vulnerability to climate change into geographic space—An assessment across the Coronado National Forest: Biodiversity and Conservation, v. 21, no. 1, p. 189–204, at https://doi.org/10.1007/s10531-011-0175-0.

Pierce, A.D., and Pickett, E., 2014, Building a spatial database of fire occurrence in Hawaii: Fire Management Today, v. 74, no. 1, p. 37–42, at https://www.fs.usda.gov/sites/default/files/legacy_files/fire-management-today/74-1.pdf#page=37.

Zlonis, E.J., Walton, N.G., Sturtevant, B.R., Wolter, P.T., and Niemi, G.J., 2019, Burn severity and heterogeneity mediate avian response to wildfire in a hemiboreal forest: Forest Ecology and Management, v. 439, p. 70–80, at https://doi.org/10.1016/j.foreco.2019.02.043.

Han, Y., Zheng, C., Liu, X., Tian, Y., and Dong, Z., 2024, Burned area and burn severity mapping with a transformer-based change detection model: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, v. 17, p. 13866–13880, at https://doi.org/10.1109/jstars.2024.3435857.

Freundlich, A.E., and Holt, E.A., 2020, Business as usual—Macrolichen community response to the resilience of spruce–fir forests to beetle disturbance in northwestern Colorado: Canadian Journal of Forest Research, v. 50, no. 11, p. 1172–1183, at https://doi.org/10.1139/cjfr-2020-0159.

Thorne, J.H., and Le, T.N.g., 2016, California's historic legacy for landscape change, the Wieslander vegetation type maps: Madroño, v. 63, no. 4, p. 293–328, at https://doi.org/10.3120/0024-9637-63.4.293.

Loehman, R., Flatley, W., Holsinger, L., and Thode, A., 2018, Can land management buffer impacts of climate changes and altered fire regimes on ecosystems of the southwestern United States?: Forests, v. 9, no. 4, article 192, at https://doi.org/10.3390/f9040192.

Barnard, D.M., Germino, M.J., Pilliod, D.S., Arkle, R.S., Applestein, C., Davidson, B.E., and Fisk, M.R., 2019, Cannot see the random forest for the decision trees—Selecting predictive models for restoration ecology: Restoration Ecology, v. 27, no. 5, p. 1053–1063, at https://doi.org/10.1111/rec.12938.

Moisseeva, N., and Businger, S., 2025, Capturing variable fire and smoke behavior in the presence of a turbulent hydraulic jump during the Lahaina Wildfire: Journal of Geophysical Research—Atmospheres, v. 130, no. 17, article e2025JD044728, at https://doi.org/10.1029/2025JD044728.

Vegh, T., Huang, C.H., and Finkral, A., 2013, Carbon credit possibilities and economic implications of fuel reduction treatments: Western Journal of Applied Forestry, v. 28, no. 2, p. 57–65, at https://doi.org/10.5849/wjaf.12-006.

Volkova, L., and Weston, C.J., 2015, Carbon loss from planned fires in southeastern Australian dry eucalyptus forests: Forest Ecology and Management, v. 336, p. 91–98, at https://doi.org/10.1016/j.foreco.2014.10.018.

Failey, E.L., and Dilling, L., 2010, Carbon stewardship—Land management decisions and the potential for carbon sequestration in Colorado, USA: Environmental Research Letters, v. 5, no. 2, article 024005, at https://doi.org/10.1088/1748-9326/5/2/024005.

Hickey, C., Jenkins, S., and Allen, M., 2025, Carbon storage portfolios for the transition to net zero: Joule, v. 9, no. 11, article 102164, at https://doi.org/10.1016/j.joule.2025.102164.

Gardner, C.B., Wichterich, C., Calero, A.E., Welch, S.A., Widom, E., Smith, D.F., Carey, A.E., and Lyons, W.B., 2022, Carbonate weathering, phosphate fertilizer, and hydrologic controls on dissolved uranium in rivers in the US Corn Belt—Disentangling seasonal geogenic- and fertilizer-derived sources: Science of the Total Environment, v. 861, article 160455, at https://doi.org/10.1016/j.scitotenv.2022.160455.

Hyde, J., Strand, E.K., Hudak, A.T., and Hamilton, D., 2015, A case study comparison of LANDFIRE fuel loading and emissions generation on a mixed conifer forest in northern Idaho, USA: Fire Ecology, v. 11, no. 3, p. 108–127, at https://doi.org/10.4996/fireecology.1103108.

Nematshahi, S., Sohrabi, B., Arabnya, A., Khodaei, A., and Belval, E., 2025, A catastrophe bond design for the financial resilience of electric utilities against wildfires: IEEE Transactions on Energy Markets, Policy and Regulation, v. 3, no. 1, p. 133–143, at https://doi.org/10.1109/tempr.2024.3501012.

Roever, C.L., DelCurto, T., Rowland, M., Vavra, M., and Wisdom, M., 2015, Cattle grazing in semiarid forestlands—Habitat selection during periods of drought: Journal of Animal Science, v. 93, no. 6, p. 3212–3225, at https://doi.org/10.2527/jas2014-8794.

Ratcliff, F., Rao, D., Barry, S., Dewees, S., Macaulay, L., Larsen, R., Shapero, M., Peterson, R., Moritz, M., et al., 2022, Cattle grazing reduces fuel and leads to more manageable fire behavior: California Agriculture, v. 76, no. 3, p. 60–69, at https://doi.org/10.3733/ca.2022a0011.

Collins, B.M., Stephens, S.L., Moghaddas, J.J., and Battles, J., 2010, Challenges and approaches in planning fuel treatments across fire-excluded forested landscapes: Journal of Forestry, v. 108, no. 1, p. 24–31, at https://doi.org/10.1093/jof/108.1.24.

Fargione, J., Haase, D.L., Burney, O.T., Kildisheva, O.A., Edge, G., Cook-Patton, S.C., Chapman, T., Rempel, A., Hurteau, M.D., et al., 2021, Challenges to the reforestation pipeline in the United States: Frontiers in Forests and Global Change, v. 4, article 629198, at https://doi.org/10.3389/ffgc.2021.629198.

Airey-Lauvaux, C., Pierce, A.D., Skinner, C.N., and Taylor, A.H., 2022, Changes in fire behavior caused by fire exclusion and fuel build-up vary with topography in California montane forests, USA: Journal of Environmental Management, v. 304, article 114255, at https://doi.org/10.1016/j.jenvman.2021.114255.

Crimmins, M.A., Geli, H.M.E., Greene, C., Meko, M., and Prihodko, L., 2025, Changing climate, changing fire—Understanding ecosystem-specific fire-climate dynamics in Arizona and New Mexico: Earth Interactions, v. 29, no. 1, article e250001, at https://doi.org/10.1175/ei-d-25-0001.1.

Cullen, A.C., Goldgeier, B.R., Belval, E., and Abatzoglou, J.T., 2024, Characterising ignition precursors associated with high levels of deployment of wildland fire personnel: International Journal of Wildland Fire, v. 33, no. 8, article Wf23182, at https://doi.org/10.1071/WF23182.

O’Grady, M.C., Wells, A.G., Just, M.G., and Wall, W.A., 2025, Characterizing fire history on military land using machine learning and Landsat imagery: International Journal of Wildland Fire, v. 34, no. 8, article Wf24214, at https://doi.org/10.1071/WF24214.

Martinez, A.J., Meddens, A.J.H., Kolden, C.A., Strand, E.K., and Hudak, A.T., 2019, Characterizing persistent unburned islands within the Inland Northwest USA: Fire Ecology, v. 15, no. 1, article 20, at https://doi.org/10.1186/s42408-019-0036-x.

Flint, A.L., Flint, L.E., Stern, M.A., Ackerly, D.D., Boynton, R., and Thorne, J.H., 2024, Characterizing soil and bedrock water use of native California vegetation: Hydrology, v. 11, no. 12, article 211, at https://doi.org/10.3390/hydrology11120211.

Boyte, S.P., Wylie, B.K., and Major, D.J., 2016, Cheatgrass percent cover change—Comparing recent estimates to climate change-driven predictions in the northern Great Basin: Rangeland Ecology & Management, v. 69, no. 4, p. 265–279, at https://doi.org/10.1016/j.rama.2016.03.002.

Edmunds, D.R., Albeke, S.E., Grogan, R.G., Lindzey, F.G., Legg, D.E., Cook, W.E., Schumaker, B.A., Kreeger, T.J., and Cornish, T.E., 2018, Chronic wasting disease influences activity and behavior in white-tailed deer: The Journal of Wildlife Management, v. 82, no. 1, p. 138–154, at https://doi.org/10.1002/jwmg.21341.

Page, W.G., Freeborn, P.H., Butler, B.W., and Jolly, W.M., 2019, A classification of US wildland firefighter entrapments based on coincident fuels, weather, and topography: Fire, v. 2, no. 4, article 52, at https://doi.org/10.3390/fire2040052.

Barnett, K., Aplet, G.H., and Belote, R.T., 2023, Classifying, inventorying, and mapping mature and old-growth forests in the United States: Frontiers in Forests and Global Change, v. 5, article 1070372, at https://doi.org/10.3389/ffgc.2022.1070372.

Buechling, A., Martin, P.H., and Canham, C.D., 2017, Climate and competition effects on tree growth in Rocky Mountain forests: Journal of Ecology, v. 105, no. 6, p. 1636–1647, at https://doi.org/10.1111/1365-2745.12782.

Creutzburg, M.K., Henderson, E.B., and Conklin, D.R., 2015, Climate change and land management impact rangeland condition and sage-grouse habitat in southeastern Oregon: AIMS Environmental Science, v. 2, no. 2, p. 203–236, at https://doi.org/10.3934/environsci.2015.2.203.

Falke, J.A., Flitcroft, R.L., Dunham, J.B., McNyset, K.M., Hessburg, P.F., Reeves, G.H., and Marshall, C.T., 2015, Climate change and vulnerability of bull trout (Salvelinus confluentus) in a fire-prone landscape: Canadian Journal of Fisheries and Aquatic Sciences, v. 72, no. 2, p. 304–318, at https://doi.org/10.1139/cjfas-2014-0098.

Inglis, N.C., and Vukomanovic, J., 2020, Climate change disproportionately affects visual quality of cultural ecosystem services in a mountain region: Ecosystem Services, v. 45, article 101190, at https://doi.org/10.1016/j.ecoser.2020.101190.

McCollum, D.W., Tanaka, J.A., Morgan, J.A., Mitchell, J.E., Fox, W.E., Maczko, K.A., Hidinger, L., Duke, C.S., and Kreuter, U.P., 2017, Climate change effects on rangelands and rangeland management—Affirming the need for monitoring: Ecosystem Health and Sustainability, v. 3, no. 3, article e01264, at https://doi.org/10.1002/ehs2.1264.

Holsinger, L., Parks, S.A., Parisien, M.A., Miller, C., Batllori, E., and Moritz, M.A., 2019, Climate change likely to reshape vegetation in North America's largest protected areas: Conservation Science and Practice, v. 1, no. 7, article e50, at https://doi.org/10.1111/csp2.50.

Hawkins, G.A., Vivoni, E.R., Robles-Morua, A., Mascaro, G., Rivera, E., and Dominguez, F., 2015, A climate change projection for summer hydrologic conditions in a semiarid watershed of central Arizona: Journal of Arid Environments, v. 118, p. 9–20, at https://doi.org/10.1016/j.jaridenv.2015.02.022.

McHugh, T.A., Compson, Z., Gestel, N., Hayer, M., Ballard, L., Haverty, M., Hines, J., Irvine, N., Krassner, D., et al., 2017, Climate controls prokaryotic community composition in desert soils of the southwestern United States: FEMS Microbiology Ecology, v. 93, no. 10, article fix116, at https://doi.org/10.1093/femsec/fix116.

Brown, P.M., Heyerdahl, E.K., Kitchen, S.G., and Weber, M.H., 2008, Climate effects on historical fires (1630–1900) in Utah: International Journal of Wildland Fire, v. 17, no. 1, p. 28–39, at https://doi.org/10.1071/WF07023.

Williams, C.A., Gu, H., and Jiao, T., 2021, Climate impacts of U.S. forest loss span net warming to net cooling: Science Advances, v. 7, no. 7, article eaax8859, at https://doi.org/10.1126/sciadv.aax8859.

Crockett, J.L., and Hurteau, M.D., 2024, Climate limits vegetation green-up more than slope, soil erodibility, and immediate precipitation following high-severity wildfire: Fire Ecology, v. 20, no. 1, article 41, at https://doi.org/10.1186/s42408-024-00264-0.

Schrag, A., Konrad, S., Miller, S., Walker, B., and Forrest, S., 2011, Climate-change impacts on sagebrush habitat and West Nile virus transmission risk and conservation implications for greater sage-grouse: GeoJournal, v. 76, no. 5, p. 561–575, at https://doi.org/10.1007/s10708-010-9369-3.

Cotton, J.M., Cerling, T.E., Hoppe, K.A., Mosier, T.M., and Still, C.J., 2016, Climate, CO2, and the history of North American grasses since the Last Glacial Maximum: Science Advances, v. 2, no. 3, article e1501346, at https://doi.org/10.1126/sciadv.1501346.

Cansler, C.A., and McKenzie, D., 2014, Climate, fire size, and biophysical setting control fire severity and spatial pattern in the northern Cascade Range, USA: Ecological Applications, v. 24, no. 5, p. 1037–1056, at https://doi.org/10.1890/13-1077.1.

Liu, Z., and Wimberly, M.C., 2015, Climatic and landscape influences on fire regimes from 1984 to 2010 in the western United States: PLoS ONE, v. 10, no. 10, article e0140839, at https://doi.org/10.1371/journal.pone.0140839.

Foga, S., Scaramuzza, P.L., Guo, S., Zhu, Z., Dilley, R.D., Jr., Beckmann, T., Schmidt, G.L., Dwyer, J.L., Hughes, M.J., et al., 2017, Cloud detection algorithm comparison and validation for operational Landsat data products: Remote Sensing of Environment, v. 194, p. 379–390, at https://doi.org/10.1016/j.rse.2017.03.026.

Smith, D.M., and Friggens, M.M., 2024, Co‐production of a vulnerability assessment for aquatic and riparian ecosystems in the southwestern United States: Journal of the American Water Resources Association, v. 60, no. 6, p. 1293–1312, at https://doi.org/10.1111/1752-1688.13240.

Gardner, C.L., Lawler, J.P., ver Hoef, J.M., Magoun, A.J., and Kellie, K.A., 2010, Coarse-scale distribution surveys and occurrence probability modeling for wolverine in interior Alaska: The Journal of Wildlife Management, v. 74, no. 8, p. 1894–1903, at https://doi.org/10.2193/2009-386.

Pacheco, A.P., Claro, J., Fernandes, P.M., de Neufville, R., Oliveira, T.M., Borges, J.G., and Rodrigues, J.C., 2015, Cohesive fire management within an uncertain environment—A review of risk handling and decision support systems: Forest Ecology and Management, v. 347, p. 1–17, at https://doi.org/10.1016/j.foreco.2015.02.033.

Zhou, T., Ding, L., Ji, J., Yu, L., and Wang, Z., 2020, Combined estimation of fire perimeters and fuel adjustment factors in FARSITE for forecasting wildland fire propagation: Fire Safety Journal, v. 116, article 103167, at https://doi.org/10.1016/j.firesaf.2020.103167.

Urbanski, S.P., 2013, Combustion efficiency and emission factors for wildfire-season fires in mixed conifer forests of the Northern Rocky Mountains, US: Atmospheric Chemistry and Physics, v. 13, no. 14, p. 7241–7262, at https://doi.org/10.5194/acp-13-7241-2013.

Atkinson, J.L., Coates, P.S., Brussee, B.E., Dwight, I.A., Ricca, M.A., and Jackson, P.J., 2021, Common ravens disrupt greater sage-grouse lekking behavior in the Great Basin, USA: Human-Wildlife Interactions, v. 15, no. 3, p. 374–390, at https://doi.org/10.26077/add8-50a4.

Zhou, J., Jiang, W., Wang, F., Qiao, Y., and Meng, Q., 2024, Comparing accuracy of wildfire spread prediction models under different data deficiency conditions: Fire, v. 7, no. 4, article 141, at https://doi.org/10.3390/fire7040141.

Zhao, F., Keane, R., Zhu, Z., and Huang, C., 2015, Comparing historical and current wildfire regimes in the Northern Rocky Mountains using a landscape succession model: Forest Ecology and Management, v. 343, p. 9–21, at https://doi.org/10.1016/j.foreco.2015.01.020.

Whitenack, L.E., Snell Taylor, S.J., Tomcho, A., and Hurlbert, A.H., 2023, Comparing multiscale, presence-only habitat suitability models created with structured survey data and community science data for a rare warbler species at the southern range margin: PLoS ONE, v. 18, article e0275556, at https://doi.org/10.1371/journal.pone.0275556.

Thompson, M.P., Vogler, K.C., Scott, J.H., and Miller, C., 2022, Comparing risk-based fuel treatment prioritization with alternative strategies for enhancing protection and resource management objectives: Fire Ecology, v. 18, no. 1, article 26, at https://doi.org/10.1186/s42408-022-00149-0.

Fagua, J.C., and Ramsey, R.D., 2019, Comparing the accuracy of MODIS data products for vegetation detection between two environmentally dissimilar ecoregions—The Chocó-Darien of South America and the Great Basin of North America: GIScience & Remote Sensing, v. 56, no. 7, p. 1–19, at https://doi.org/10.1080/15481603.2019.1611024.

Baron-Hyppolite, C., Lashley, C.H., Garzon, J., Miesse, T., Ferreira, C., and Bricker, J.D., 2019, Comparison of implicit and explicit vegetation representations in SWAN hindcasting wave dissipation by coastal wetlands in Chesapeake Bay: Geosciences, v. 9, no. 1, article 8, at https://doi.org/10.3390/geosciences9010008.

McCarley, T.R., Hudak, A.T., Restaino, J.C., Billmire, M., French, N.H.F., Ottmar, R.D., Hass, B., Zarzana, K., Goulden, T., et al., 2022, A comparison of multitemporal airborne laser scanning data and the fuel characteristics classification system for estimating fuel load and consumption: Journal of Geophysical Research—Biogeosciences, v. 127, no. 5, article e2021JG006733, at https://doi.org/10.1029/2021jg006733.

Forthofer, J.M., Butler, B.W., McHugh, C.W., Finney, M.A., Bradshaw, L.S., Stratton, R.D., Shannon, K.S., and Wagenbrenner, N.S., 2014, A comparison of three approaches for simulating fine-scale surface winds in support of wildland fire management. Part II. An exploratory study of the effect of simulated winds on fire growth simulations: International Journal of Wildland Fire, v. 23, no. 7, p. 982–994, at https://doi.org/10.1071/WF12090.

Greene, D.F., Lindley, S.T., and Kane, J.M., 2024, Competition between resprouting chaparral and the recruits of a serotinous conifer following stand-replacing fire: Trees, Forests and People, v. 17, article 100651, at https://doi.org/10.1016/j.tfp.2024.100651.

Chesshire, P.R., Fischer, E.E., Dowdy, N.J., Griswold, T.L., Hughes, A.C., Orr, M.C., Ascher, J.S., Guzman, L.M., Hung, K.L.J., et al., 2023, Completeness analysis for over 3000 United States bee species identifies persistent data gap: Ecography, v. 2023, no. 5, article e06584, at https://doi.org/10.1111/ecog.06584.

Garman, S.L., Yu, C.L., and Li, Y., 2024, Composite estimation to combine spatially overlapping environmental monitoring surveys: PLoS One, v. 19, no. 3, article e0299306, at https://doi.org/10.1371/journal.pone.0299306.

Tasnia, A., Lara, G., Foster, D., and Sengupta, D., 2025, Comprehensive fuel and emissions measurements highlight uncertainties in smoke production using predictive modeling tools: ACS ES&T Air, v. 2, no. 6, p. 982–997, at https://doi.org/10.1021/acsestair.4c00142.

Decastro, A.L., Juliano, T.W., Kosović, B., Ebrahimian, H., and Balch, J.K., 2022, A computationally efficient method for updating fuel inputs for wildfire behavior models using Sentinel imagery and random forest classification: Remote Sensing, v. 14, no. 6, article 1447, at https://doi.org/10.3390/rs14061447.

Kane, J.M., Kerhoulas, L.P., and Goff, G.S., 2023, Conifer encroachment increases foliar moisture content in a northwestern California oak woodland: International Journal of Wildland Fire, v. 32, no. 5, p. 728–737, at https://doi.org/10.1071/WF22184.

Fraser, D.L., Ironside, K., Wayne, R.K., and Boydston, E.E., 2019, Connectivity of mule deer (Odocoileus hemionus) populations in a highly fragmented urban landscape: Landscape Ecology, v. 34, no. 5, p. 1097–1115, at https://doi.org/10.1007/s10980-019-00824-9.

Stevens-Rumann, C.S., Prichard, S., Whitman, E., Parisien, M.-A., and Meddens, A.J.H., 2022, Considering regeneration failure in the context of changing climate and disturbance regimes in western North America: Canadian Journal of Forest Research, v. 52, no. 10, p. 1281–1302, at https://doi.org/10.1139/cjfr-2022-0054.

Buonanduci, M.S., Donato, D.C., Halofsky, J.S., Kennedy, M.C., and Harvey, B.J., 2023, Consistent spatial scaling of high-severity wildfire can inform expected future patterns of burn severity: Ecology Letters, v. 26, no. 10, p. 1687–1699, at https://doi.org/10.1111/ele.14282.

Vanderhoof, M.K., Hawbaker, T.J., Teske, C., Noble, J., and Smith, J., 2022, Contemporary (1984-2020) fire history metrics for the conterminous United States and ecoregional differences by land ownership: International Journal of Wildland Fire, v. 31, no. 12, p. 1167–1183, at https://doi.org/10.1071/WF22044.

Parks, S.A., Holsinger, L.M., Blankenship, K., Dillon, G.K., Goeking, S.A., and Swaty, R., 2023, Contemporary wildfires are more severe compared to the historical reference period in western US dry conifer forests: Forest Ecology and Management, v. 544, article 121232, at https://doi.org/10.1016/j.foreco.2023.121232.

Homer, C., Dewitz, J., Jin, S., Xian, G., Costello, C., Danielson, P., Gass, L., Funk, M., Wickham, J., et al., 2020, Conterminous United States land cover change patterns 2001–2016 from the 2016 National Land Cover Database: ISPRS Journal of Photogrammetry and Remote Sensing, v. 162, p. 184–199, at https://doi.org/10.1016/j.isprsjprs.2020.02.019.

Comer, P.J., Hak, J.C., Kindscher, K., Muldavin, E., and Singhurst, J., 2018, Continent-scale landscape conservation design for temperate grasslands of the Great Plains and Chihuahuan Desert: Natural Areas Journal, v. 38, no. 2, p. 196–211, at https://doi.org/10.3375/043.038.0209.

Meunier, J., 2022, Contradictions and continuities—A historical context to Euro-American settlement era fires of the Lake States, USA: Fire Ecology, v. 18, no. 1, article 3, at https://doi.org/10.1186/s42408-022-00127-6.

Alcasena, F., Ager, A.A., Belavenutti, P., Krawchuk, M., and Day, M.A., 2022, Contrasting the efficiency of landscape versus community protection fuel treatment strategies to reduce wildfire exposure and risk: Journal of Environmental Management, v. 309, article 114650, at https://doi.org/10.1016/j.jenvman.2022.114650.

Bremer, L.L., Wada, C.A., Medoff, S., Page, J., Falinski, K., and Burnett, K.M., 2019, Contributions of native forest protection to local water supplies in East Maui: Science of the Total Environment, v. 688, p. 1422–1432, at https://doi.org/10.1016/j.scitotenv.2019.06.220.

Collar, N.M., Saxe, S., Rust, A.J., and Hogue, T.S., 2021, A CONUS-scale study of wildfire and evapotranspiration—Spatial and temporal response and controlling factors: Journal of Hydrology, v. 603, article 127162, at https://doi.org/10.1016/j.jhydrol.2021.127162.

Donato, D.C., Halofsky, J.S., and Reilly, M.J., 2019, Corralling a black swan—Natural range of variation in a forest landscape driven by rare, extreme events: Ecological Applications, v. 30, no. 1, article e02013, at https://doi.org/10.1002/eap.2013.

Miller, J.D., and Safford, H.D., 2017, Corroborating evidence of a pre-euro-American low-to moderate-severity fire regime in yellow pine–mixed conifer forests of the Sierra Nevada, California, USA: Fire Ecology, v. 13, no. 1, p. 58–90, at https://doi.org/10.4996/fireecology.1301058.

Kreitler, J., Thompson, M.P., Vaillant, N.M., and Hawbaker, T.J., 2019, Cost-effective fuel treatment planning—A theoretical justification and case study: International Journal of Wildland Fire, v. 29, no. 1, article 42, at https://doi.org/10.1071/WF18187.

Elder, M., Phillips, C.A., Potter, S., Frumhoff, P.C., and Rogers, B.M., 2022, The costs and benefits of fire management for carbon mitigation in Alaska through 2100: Environmental Research Letters, v. 17, no. 10, article 105001, at https://doi.org/10.1088/1748-9326/ac8e85.

Huang, W., Swatantran, A., Duncanson, L., Johnson, K., Watkinson, D., Dolan, K., O'Neil-Dunne, J., Hurtt, G., and Dubayah, R., 2017, County-scale biomass map comparison—A case study for Sonoma, California: Carbon Management, v. 8, no. 5-6, p. 1–18, at https://doi.org/10.1080/17583004.2017.1396840.

Simeone, C., Maneta, M.P., Holden, Z.A., Sapes, G., Sala, A., and Dobrowski, S.Z., 2018, Coupled ecohydrology and plant hydraulics modeling predicts ponderosa pine seedling mortality and lower treeline in the US Northern Rocky Mountains: New Phytologist, v. 221, no. 4, p. 1814–1830, at https://doi.org/10.1111/nph.15499.

Sidman, G., Guertin, D.P., Goodrich, D.C., Thoma, D., Falk, D., and Burns, I.S., 2016, A coupled modelling approach to assess the effect of fuel treatments on post-wildfire runoff and erosion: International Journal of Wildland Fire, v. 25, no. 3, p. 351–362, at https://doi.org/10.1071/WF14058.

Jarnevich, C.S., Cullinane Thomas, C., Young, N.E., Grissom, P., Backer, D., and Frid, L., 2022, Coupling process-based and empirical models to assess management options to meet conservation goals: Biological Conservation, v. 265, article 109379, at https://doi.org/10.1016/j.biocon.2021.109379.

Liu, J.X., Sleeter, B.M., Zhu, Z.L., Loveland, T.R., Sohl, T., Howard, S.M., Key, C.H., Hawbaker, T., Liu, S.G., et al., 2020, Critical land change information enhances the understanding of carbon balance in the United States: Global Change Biology, v. 26, no. 7, p. 3920–3929, at https://doi.org/10.1111/gcb.15079.

Chen, X., Vogelmann, J.E., Chander, G., Ji, L., Tolk, B., Huang, C., and Rollins, M., 2013, Cross-sensor comparisons between Landsat 5 TM and IRS-P6 AWiFS and disturbance detection using integrated Landsat and AWiFS time-series images: International Journal of Remote Sensing, v. 34, no. 7, p. 2432–2453, at https://doi.org/10.1080/01431161.2012.743690.

Jelinski, N.A., Sousa, M.J., Williams, A., GreyBear, E., Finnesand, K., Mulligan, D., Cole, C., Stillinger, M.D., and Feinberg, J.M., 2019, Cryoturbation and carbon stocks in gelisols under late-successional black spruce forests of the Copper River Basin, Alaska: Soil Science Society of America Journal, v. 83, no. 6, p. 1760–1778, at https://doi.org/10.2136/sssaj2019.07.0212.

Veraverbeke, S., Rogers, B.M., and Randerson, J.T., 2015, Daily burned area and carbon emissions from boreal fires in Alaska: Biogeosciences, v. 12, no. 11, p. 3579–3601, at https://doi.org/10.5194/bg-12-3579-2015.

Lebeau, C.W., Nielson, R.M., Hallingstad, E.C., and Young, D.P., Jr., 2015, Daytime habitat selection by resident golden eagles (Aquila chrysaetos) in southern Idaho, U.S.A: Journal of Raptor Research, v. 49, no. 1, p. 29–42, at https://doi.org/10.3356/JRR-13-00052.1.

Familusi, I., Gebremedhin, M., Gyawali, B., and Chiluwal, A., 2025, A deciduous forest's CO2 exchange within the mixed-humid climate of Kentucky, USA: Forests, v. 14, no. 4, article 562, at https://doi.org/10.3390/f16040562.

Skinner, H.K., Prichard, S.J., and Cullen, A.C., 2024, Decision support for landscapes with high fire hazard and competing values at risk—The Upper Wenatchee Pilot Project: Fire, v. 7, no. 3, article 77, at https://doi.org/10.3390/fire7030077.

Bruggeman, J.E., Kennedy, P.L., Andersen, D.E., Deisch, S., and Stukel, E.D., 2023, Declining American Goshawk (Accipiter atricapillus) nest site habitat suitability in a timber production landscape—Effects of abiotic, biotic, and forest management factors: Journal of Raptor Research, v. 57, no. 4, p. 595–616, at https://doi.org/10.3356/JRR-22-116.

Coen, J.L., Stavros, E.N., and Fites-Kaufman, J.A., 2018, Deconstructing the King megafire: Ecological Applications, v. 28, no. 6, p. 1565–1580, at https://doi.org/10.1002/eap.1752.

Thomas, K.A., Stauffer, B.A., and Jarchow, C.J., 2023, Decoupling of species and plant communities of the U.S. southwest—A CCSM4 climate scenario example: Ecosphere, v. 14, no. 2, article e4414, at https://doi.org/10.1002/ecs2.4414.

Ghali, R., and Akhloufi, M.A., 2023, Deep learning approaches for wildland fires using satellite remote sensing data—Detection, mapping, and prediction: Fire, v. 6, no. 5, article 192, at https://doi.org/10.3390/fire6050192.

Kumar, A.V., Tack, J.D., Doherty, K.E., Smith, J.T., Ross, B.E., and Bedrosian, G., 2024, Defend and grow the core for birds—How a sagebrush conservation strategy benefits rangeland birds: Rangeland Ecology & Management, v. 97, p. 160–168, at https://doi.org/10.1016/j.rama.2024.08.018.

Morrison, R.R., Simonson, K., McManamay, R.A., and Carver, D., 2023, Degradation of floodplain integrity within the contiguous United States: Communications Earth & Environment, v. 4, no. 1, article 215, at https://doi.org/10.1038/s43247-023-00877-4.

Frisvold, G.B., Zhang, N., Crimmins, M.A., Ferguson, D., and Maxwell, C., 2024, Demand for information for wildland fire management: Atmosphere, v. 15, no. 11, article 1364, at https://doi.org/10.3390/atmos15111364.

Gould, M.J., Cain, J.W., III, Roemer, G.W., Gould, W.R., and Liley, S.G., 2018, Density of American black bears in New Mexico: The Journal of Wildlife Management, v. 82, no. 4, p. 775–788, at https://doi.org/10.1002/jwmg.21432.

Schultz, E.L., Filippelli, S.K., Vogeler, J.C., and Shriver, R.K., 2023, Density-dependent dynamics help explain the simultaneous expansion and decline of woodlands in the western US: Forest Ecology and Management, v. 546, article 121359, at https://doi.org/10.1016/j.foreco.2023.121359.

Keane, R.E., 2013, Describing wildland surface fuel loading for fire management—A review of approaches, methods and systems: International Journal of Wildland Fire, v. 22, no. 1, p. 51–62, at https://doi.org/10.1071/WF11139.

Belavenutti, P., Ager, A.A., Day, M.A., and Chung, W., 2022, Designing forest restoration projects to optimize the application of broadcast burning: Ecological Economics, v. 201, article 107558, at https://doi.org/10.1016/j.ecolecon.2022.107558.

Gu, Y., and Wylie, B.K., 2010, Detecting ecosystem performance anomalies for land management in the Upper Colorado River Basin using satellite observations, climate data, and ecosystem models: Remote Sensing, v. 2, no. 8, p. 1880–1891, at https://doi.org/10.3390/rs2081880.

Meddens, A.J.H., Kolden, C.A., and Lutz, J.A., 2016, Detecting unburned areas within wildfire perimeters using Landsat and ancillary data across the northwestern United States: Remote Sensing of Environment, v. 186, p. 275–285, at https://doi.org/10.1016/j.rse.2016.08.023.

Fusco, E.J., Finn, J.T., Abatzoglou, J.T., Balch, J.K., Dadashi, S., and Bradley, B.A., 2019, Detection rates and biases of fire observations from MODIS and agency reports in the conterminous United States: Remote Sensing of Environment, v. 220, p. 30–40, at https://doi.org/10.1016/j.rse.2018.10.028.

Karau, E.C., and Keane, R.E., 2007, Determining landscape extent for succession and disturbance simulation modeling: Landscape Ecology, v. 22, no. 7, p. 993–1006, at https://doi.org/10.1007/s10980-007-9081-y.

Nepal, S., Spetich, M.A., and Fan, Z., 2024, Determining spatial units for modeling regional nonnative invasive plant species spread in the southern US forestlands—Using the state of Alabama as an example: Forestry Research, v. 4, article e013, at https://doi.org/10.48130/forres-0024-0010.

Mehaffey, M., Van Remortel, R., Smith, E., and Bruins, R., 2011, Developing a dataset to assess ecosystem services in the midwest United States: International Journal of Geographical Information Science, v. 25, no. 4, p. 681–695, at https://doi.org/10.1080/13658816.2010.497148.

Jarnevich, C.S., Cullinane Thomas, C., Young, N.E., Backer, D., Cline, S., Frid, L., and Grissom, P., 2019, Developing an expert elicited simulation model to evaluate invasive species and fire management alternatives: Ecosphere, v. 10, no. 5, article e02730, at https://doi.org/10.1002/ecs2.2730.

Murray, A.T., Baik, J., Figueroa, V.E., Rini, D., Moritz, M.A., Roberts, D.A., Sweeney, S.H., Carvalho, L.M.V., and Jones, C., 2023, Developing effective wildfire risk mitigation plans for the wildland urban interface: International Journal of Applied Earth Observation and Geoinformation, v. 124, article 103531, at https://doi.org/10.1016/j.jag.2023.103531.

Provencher, L., Byer, S., Badik, K.J., and Clifford, M.J., 2024, Developing spatially explicit and stochastic measures of ecological departure: International Journal of Wildland Fire, v. 33, no. 4, article Wf23038, at https://doi.org/10.1071/wf23038.

Zhao, B., and Wong, S.D., 2021, Developing transportation response strategies for wildfire evacuations via an empirically supported traffic simulation of Berkeley, California: Transportation Research Record, v. 2675, no. 12, p. 557–582, at https://doi.org/10.1177/03611981211030271.

Spyratos, V., Bourgeron, P.S., and Ghil, M., 2007, Development at the wildland-urban interface and the mitigation of forest-fire risk: Proceedings of the National Academy of Sciences of the United States of America, v. 104, no. 36, p. 14272–14276, at https://doi.org/10.1073/pnas.0704488104.

Walston, L.J., and Hartmann, H.M., 2018, Development of a landscape integrity model framework to support regional conservation planning: PLoS ONE, v. 13, no. 4, article e0195115, at https://doi.org/10.1371/journal.pone.0195115.

Li, C., Xian, G., Wellington, D., Smith, K., Horton, J., and Zhou, Q., 2022, Development of the LCMAP annual land cover product across Hawai?i: International Journal of Applied Earth Observation and Geoinformation, v. 113, article 103015, at https://doi.org/10.1016/j.jag.2022.103015.

Kohl, M.T., Stahler, D.R., Metz, M.C., Forester, J.D., Kauffman, M.J., Varley, N., White, P.J., Smith, D.W., and MacNulty, D.R., 2018, Diel predator activity drives a dynamic landscape of fear: Ecological Monographs, v. 88, no. 4, p. 638–652, at https://doi.org/10.1002/ecm.1313.

Miller, J.D., Collins, B.M., Lutz, J.A., Stephens, S.L., van Wagtendonk, J.W., and Yasuda, D.A., 2012, Differences in wildfires among ecoregions and land management agencies in the Sierra Nevada region, California, USA: Ecosphere, v. 3, no. 9, p. 1–20, at https://doi.org/10.1890/ES12-00158.1.

Evans, B.E., Brehm, A.M., Dri, G.F., Bolinjkar, A., Archambault, G., and Mortelliti, A., 2024, Differential habitat use between demographic states of black bears in managed timber forests: The Journal of Wildlife Management, v. 88, no. 1, article e22501, at https://doi.org/10.1002/jwmg.22501.

Wilson, S.G., and Prentice, S., 2024, Digital soil mapping of soil burn severity: Soil Science Society of America Journal, v. 88, no. 4, p. 1045–1067, at https://doi.org/10.1002/saj2.20702.

Hough-Snee, N., Kasprak, A., Roper, B.B., and Meredith, C.S., 2014, Direct and indirect drivers of instream wood in the interior Pacific Northwest, USA—Decoupling climate, vegetation, disturbance, and geomorphic setting: Riparian Ecology and Conservation, v. 2, no. 1, p. 14–34, at https://doi.org/10.2478/remc-2014-0002.

Wagler, B.L., Stewart, C., Turnbull, Z., Malmberg, J.L., and Monteith, K.L., 2025, Disease and migratory tactic mediate the nutritional benefits of irrigated agriculture to mule deer: The Journal of Wildlife Management, v. 89, no. 2, article e22705, at https://doi.org/10.1002/jwmg.22705.

Tourville, J.C., Murray, G.L.D., and Nelson, S.J., 2024, Distinct latitudinal patterns of shifting spring phenology across the Appalachian Trail Corridor: Ecology, v. 105, no. 10, article e4403, at https://doi.org/10.1002/ecy.4403.

Bendix, J., and Commons, M.G., 2017, Distribution and frequency of wildfire in California riparian ecosystems: Environmental Research Letters, v. 12, no. 7, article 075008, at https://doi.org/10.1088/1748-9326/aa7087.

de la Cruz, J.L., Ford, W.M., Jones, S., Johnson, J.B., and Silvis, A., 2023, Distribution of northern long-eared bat summer habitat on the Monongahela National Forest, West Virginia: Journal of the Southeastern Association of Fish and Wildlife Agencies, v. 10, p. 114–124, at https://hdl.handle.net/10919/114593.

O'Connor, C.D., Falk, D.A., Lynch, A.M., Swetnam, T.W., and Wilcox, C.P., 2017, Disturbance and productivity interactions mediate stability of forest composition and structure: Ecological Applications, v. 27, no. 3, p. 900–915, at https://doi.org/10.1002/eap.1492.

Rodman, K.C., Andrus, R.A., Veblen, T.T., and Hart, S.J., 2021, Disturbance detection in Landsat time series is influenced by tree mortality agent and severity, not by prior disturbance: Remote Sensing of Environment, v. 254, article 112244, at https://doi.org/10.1016/j.rse.2020.112244.

Palmquist, K.A., Schlaepfer, D.R., Renne, R.R., Torbit, S.C., Doherty, K.E., Remington, T.E., Watson, G., Bradford, J.B., and Lauenroth, W.K., 2021, Divergent climate change effects on widespread dryland plant communities driven by climatic and ecohydrological gradients: Global Change Biology, v. 27, no. 20, p. 5169–5185, at https://doi.org/10.1111/gcb.15776.

Elias, E., Reyes, J., Steele, C., and Rango, A., 2018, Diverse landscapes, diverse risks—Synthesis of the special issue on climate change and adaptive capacity in a hotter, drier southwestern United States: Climatic Change, v. 148, no. 3, p. 339–353, at https://doi.org/10.1007/s10584-018-2219-x.

Kohl, M.T., Ruth, T.K., Metz, M.C., Stahler, D.R., Smith, D.W., White, P.J., and MacNulty, D.R., 2019, Do prey select for vacant hunting domains to minimize a multi-predator threat?: Ecology Letters, v. 22, no. 11, p. 1724–1733, at https://doi.org/10.1111/ele.13319.

Bucklin, D.M., Shedden, J.M., Quinn, N.M., SCummings, R., and Stapp, P., 2023, Do trap-neuter-return (TNR) practices contribute to human–coyote conflicts in southern California?: Human-Wildlife Interactions, v. 17, no. 1, article 7, at https://doi.org/10.26077/b86e-600f.

Benefield, A., and Chen, J., 2023, Does human accessibility affect lightning-caused wildfires? A case study of the Southern Rocky Mountains: Fire Technology, v. 59, p. 2355–2374, at https://doi.org/10.1007/s10694-023-01400-z.

Donato, D.C., Halofsky, J.S., Churchill, D.J., Haugo, R.D., Cansler, C.A., Smith, A., and Harvey, B.J., 2023, Does large area burned mean a bad fire year? Comparing contemporary wildfire years to historical fire regimes informs the restoration task in fire-dependent forests: Forest Ecology and Management, v. 546, article 121372, at https://doi.org/10.1016/j.foreco.2023.121372.

Milligan, M.C., and McNew, L.B., 2021, Does researcher activity impact nest survival of sharp-tailed grouse?: Wildlife Biology, v. 2021, no. 3, article wlb.00690, at https://doi.org/10.2981/wlb.00690.

Smith, K.T., Beck, J.L., and Pratt, A.C., 2016, Does Wyoming's core area policy protect winter habitats for greater sage-grouse?: Environmental Management, v. 58, no. 4, p. 585–596, at https://doi.org/10.1007/s00267-016-0745-8.

Beckmann, J.J., Sherriff, R.L., Kerhoulas, L.P., and Kane, J.M., 2021, Douglas-fir encroachment reduces drought resistance in Oregon white oak of northern California: Forest Ecology and Management, v. 498, article 119543, at https://doi.org/10.1016/j.foreco.2021.119543.

Robichaud, P.J.L., and Padowski, J.C., 2024, Drinking water under fire—Water utilities' vulnerability to wildfires in the Pacific Northwest: Journal of the American Water Resources Association, v. 60, no. 2, p. 590–602, at https://doi.org/10.1111/1752-1688.13174.

Harvey, B.J., Donato, D.C., and Turner, M.G., 2016, Drivers and trends in landscape patterns of stand-replacing fire in forests of the US Northern Rocky Mountains (1984–2010): Landscape Ecology, v. 31, no. 10, p. 2367–2383, at https://doi.org/10.1007/s10980-016-0408-4.

Taylor, A.H., Harris, L.B., and Drury, S.A., 2021, Drivers of fire severity shift as landscapes transition to an active fire regime, Klamath Mountains, USA: Ecosphere, v. 12, no. 9, article e03734, at https://doi.org/10.1002/ecs2.3734.

Quinlan, B.A., Rosenberger, J.P., Kalb, D.M., Abernathy, H.N., Thorne, E.D., Ford, W.M., and Cherry, M.J., 2022, Drivers of habitat quality for a reintroduced elk herd: Scientific Reports, v. 12, no. 1, article 20960, at https://doi.org/10.1038/s41598-022-25058-9.

Parren, M.K., Furnas, B.J., Barton, D.C., Nelson, M.D., and Clucas, B., 2022, Drought and coyotes mediate mesopredator response to human disturbance: Ecosphere, v. 13, no. 10, article e4258, at https://doi.org/10.1002/ecs2.4258.

Goldstein, B.R., Furnas, B.J., Calhoun, K.L., Larsen, A.E., Karp, D.S., and de Valpine, P., 2024, Drought influences habitat associations and abundances of birds in California's Central Valley: Diversity and Distributions, v. 30, no. 5, article e13827, at https://doi.org/10.1111/ddi.13827.

Meigs, G.W., Case, M.J., Churchill, D.J., Hersey, C.M., Jeronimo, S.M.A., Smith, L.A.C., and Thom, D., 2023, Drought, wildfire and forest transformation—Characterizing trailing edge forests in the eastern Cascade Range, Washington, USA: Forestry - An International Journal of Forest Research, v. 96, no. 3, p. 340–354, at https://doi.org/10.1093/forestry/cpac046.

Harvey, B.J., Andrus, R.A., Battaglia, M.A., Negrón, J.F., Orrego, A., and Veblen, T.T., 2021, Droughty times in mesic places—Factors associated with forest mortality vary by scale in a temperate subalpine region: Ecosphere, v. 12, no. 1, article e03318, at https://doi.org/10.1002/ecs2.3318.

Kelly, B.T., and Bruckerhoff, L.A., 2024, Dry, drier, driest—Differentiating flow patterns across a gradient of intermittency: River Research and Applications, v. 40, no. 7, p. 1273–1285, at https://doi.org/10.1002/rra.4289.

Cheung, K.K.W., Sharples, J., Del Favero, D., and Tirado Cortes, C., 2025, Dynamic fire-atmosphere interaction in the 2020 Montana Bridger Foothills Wildfire as revealed by WRF-SFIRE simulations: npj Natural Hazards, v. 2, no. 1, article 75, at https://doi.org/10.1038/s44304-025-00132-0.

Green, A.W., Pavlacky, D.C., Jr., and George, T.L., 2019, A dynamic multi-scale occupancy model to estimate temporal dynamics and hierarchical habitat use for nomadic species: Ecology and Evolution, v. 9, no. 2, p. 793–803, at https://doi.org/10.1002/ece3.4822.

Hellesto, R.A., Shipley, L.A., Huggler, K., DeVivo, M., and Bennett, P.E., 2025, Early fawn-rearing habitat of mule deer in an agricultural landscape: Ecosphere, v. 16, no. 9, article e70403, at https://doi.org/10.1002/ecs2.70403.

Santos, F., Bailey, J.K., and Schweitzer, J.A., 2023, The eco-evolutionary role of fire in shaping terrestrial ecosystems: Functional Ecology, v. 37, no. 8, p. 2090–2095, at https://doi.org/10.1111/1365-2435.14387.

Lichwa-Schneringer, E.M., Cain, J.W., Wan, H.Y., Fuller, G., Millberry, C., and Gunther, M.S., 2025, Ecological and social drivers of Mexican Wolf home range size across spatiotemporal scales: Journal of Mammalogy, v. 106, no. 1, p. 105–117, at https://doi.org/10.1093/jmammal/gyae110.

Rabon, J.C., Nuñez, C.M.V., Coates, P.S., Ricca, M.A., and Johnson, T.N., 2021, Ecological correlates of fecal corticosterone metabolites in female greater sage-grouse (Centrocercus urophasianus): Canadian Journal of Zoology, v. 99, no. 9, p. 812–822, at https://doi.org/10.1139/cjz-2020-0258.

Sherriff, R.L., and Veblen, T.T., 2006, Ecological effects of changes in fire regimes in Pinus ponderosa ecosystems in the Colorado Front Range: Journal of Vegetation Science, v. 17, no. 6, p. 705–718, at https://doi.org/10.1658/1100-9233(2006)17[705:EEOCIF]2.0.CO;2.

Wibbenmeyer, M., Sloggy, M.R., and Sánchez, J.J., 2023, Economic analysis of wildfire impacts to water quality—A Review: Journal of Forestry, v. 121, no. 4, p. 374–382, at https://doi.org/10.1093/jofore/fvad012.

Ager, A.A., Vogler, K.C., Day, M.A., and Bailey, J.D., 2017, Economic opportunities and trade-offs in collaborative forest landscape restoration: Ecological Economics, v. 136, p. 226–239, at https://doi.org/10.1016/j.ecolecon.2017.01.001.

Maher, A.T., Ashwell, N.E.Q., MacZko, K.A., Taylor, D.T., Tanaka, J.A., and Reeves, M.C., 2021, An economic valuation of federal and private grazing land ecosystem services supported by beef cattle ranching in the United States: Translational Animal Science, v. 5, no. 3, article txab054, at https://doi.org/10.1093/tas/txab054.

Bayham, J., Yoder, J.K., Champ, P.A., and Calkin, D.E., 2022, The economics of wildfire in the United States: Annual Review of Resource Economics, v. 14, p. 379–401, at https://doi.org/10.1146/annurev-resource-111920-014804.

Gaines, W.L., Lyons, A.L., Suring, L.H., and Hughes, C.S., 2023, Ecosystem conditions that influence the viability of an old-forest species with limited vagility—The Red Tree Vole: Animals, v. 13, no. 7, article 1166, at https://doi.org/10.3390/ani13071166.

Faber-Langendoen, D., Baldwin, K., Peet, R.K., Meidinger, D., Muldavin, E., Keeler-Wolf, T., and Josse, C., 2018, The EcoVeg approach in the Americas—U.S., Canadian and international vegetation classifications: Phytocoenologia, v. 48, no. 2, p. 215–237, at https://doi.org/10.1127/phyto/2017/0165.

Koltunov, A., Ramirez, C.M., Ustin, S.L., Slaton, M., and Haunreiter, E., 2019, eDaRT—The Ecosystem Disturbance and Recovery Tracker system for monitoring landscape disturbances and their cumulative effects: Remote Sensing of Environment, v. 238, article 111482, at https://doi.org/10.1016/j.rse.2019.111482.

Bose, S., Forrester, T.D., Casady, D.S., and Wittmer, H.U., 2018, Effect of activity states on habitat selection by black-tailed deer: The Journal of Wildlife Management, v. 82, no. 8, p. 1711–1724, at https://doi.org/10.1002/jwmg.21529.

Wan, H.Y., Cushman, S.A., and Ganey, J.L., 2020, The effect of scale in quantifying fire impacts on species habitats: Fire Ecology, v. 16, no. 1, article 9, at https://doi.org/10.1186/s42408-020-0068-2.

Balaji, K., and Rabiei, M., 2020, Effect of terrain, environment and infrastructure on potential CO2 pipeline corridors—A case study from north-central USA: Energy, Ecology and Environment, v. 6, no. 4, p. 378–393, at https://doi.org/10.1007/s40974-020-00194-y.

Hanberry, B.B., 2023, Effectiveness of land use and disturbance measures, compared to climate, soil, and topography, for modeling relative abundances of tree species in the eastern United States: Ecological Informatics, v. 75, article 102110, at https://doi.org/10.1016/j.ecoinf.2023.102110.

Sleeter, B.M., Marvin, D.C., Cameron, D.R., Selmants, P.C., Westerling, A.L., Kreitler, J., Daniel, C.J., Liu, J., and Wilson, T.S., 2019, Effects of 21st-century climate, land use, and disturbances on ecosystem carbon balance in California: Global Change Biology, v. 25, no. 10, p. 3334–3353, at https://doi.org/10.1111/gcb.14677.

Roper, B.B., 2022, Effects of beaver dams on stream and riparian conditions on public lands in the United States' inland northwest: Western North American Naturalist, v. 82, no. 4, p. 638–659, at https://doi.org/10.3398/064.082.0402.

Litschert, S.E., Theobald, D.M., and Brown, T.C., 2014, Effects of climate change and wildfire on soil loss in the Southern Rockies ecoregion: Catena, v. 118, p. 206–219, at https://doi.org/10.1016/j.catena.2014.01.007.

Kohl, M.T., Messmer, T.A., Crabb, B.A., Guttery, M.R., Dahlgren, D.K., Larsen, R.T., Frey, S.N., Liguori, S., and Baxter, R.J., 2019, The effects of electric power lines on the breeding ecology of greater sage-grouse: PLoS ONE, v. 14, no. 1, article e0209968, at https://doi.org/10.1371/journal.pone.0209968.

Evans, B.E., and Mortelliti, A., 2022, Effects of forest disturbance, snow depth, and intraguild dynamics on American marten and fisher occupancy in Maine, USA: Ecosphere, v. 13, no. 4, article e4027, at https://doi.org/10.1002/ecs2.4027.

Bar Massada, A., Syphard, A.D., Hawbaker, T.J., Stewart, S.I., and Radeloff, V.C., 2011, Effects of ignition location models on the burn patterns of simulated wildfires: Environmental Modelling & Software, v. 26, no. 5, p. 583–592, at https://doi.org/10.1016/j.envsoft.2010.11.016.

Sun, J., Twine, E.T., Hill, J., Noe, R., Shi, J., and Li, M., 2017, Effects of land use change for crops on water and carbon budgets in the midwest USA: Sustainability, v. 9, no. 2, article 225, at https://doi.org/10.3390/su9020225.

Bremer, L.L., Elshall, A.S., Wada, C.A., Brewington, L., Delevaux, J.M.S., El-Kadi, A.I., Voss, C.I., and Burnett, K.M., 2021, Effects of land-cover and watershed protection futures on sustainable groundwater management in a heavily utilized aquifer in Hawai‘i (USA): Hydrogeology Journal, v. 29, no. 5, p. 1749–1765, at https://doi.org/10.1007/s10040-021-02310-6.

Bestelmeyer, B.T., Burkett, L.M., and Lister, L., 2021, Effects of managed fire on a swale grassland in the Chihuahuan Desert: Rangelands, v. 43, no. 5, p. 181–184, at https://doi.org/10.1016/j.rala.2021.05.001.

Bilodeau‐Hussey, N.M., Huggler, K.S., Cassirer, E.F., Miyasaki, H., Hurley, M.A., Shipley, L.A., and Long, R.A., 2025, Effects of maternal condition, disease status, and behavior on survival of juvenile bighorn sheep: The Journal of Wildlife Management, v. 89, no. 3, article e22721, at https://doi.org/10.1002/jwmg.22721.

Janousek, W.M., Hicke, J.A., Meddens, A.J.H., and Dreitz, V.J., 2019, The effects of mountain pine beetle outbreaks on avian communities in lodgepole pine forests across the greater Rocky Mountain region: Forest Ecology and Management, v. 444, p. 374–381, at https://doi.org/10.1016/j.foreco.2019.04.047.

Pittman, H.T., and Krementz, D.G., 2022, Effects of prescribed fire on prenesting movements of wild turkeys in Arkansas: Wildlife Society Bulletin, v. 46, no. 2, article e1264, at https://doi.org/10.1002/wsb.1264.

Mahan, L.B., Bassett, L.G., Duarte, A., Forstner, M.R.J., and Mali, I., 2022, Effects of salinization on the occurrence of a long-lived vertebrate in a desert river: Scientific Reports, v. 12, no. 1, article 15907, at https://doi.org/10.1038/s41598-022-20199-3.

Leirfallom, S.B., Keane, R.E., Tomback, D.F., and Dobrowski, S.Z., 2015, The effects of seed source health on whitebark pine (Pinus albicaulis) regeneration density after wildfire: Canadian Journal of Forest Research, v. 45, no. 11, p. 1597–1606, at https://doi.org/10.1139/cjfr-2015-0043.

Hyde, K.D., Wilcox, A.C., Jencso, K., and Woods, S., 2014, Effects of vegetation disturbance by fire on channel initiation thresholds: Geomorphology, v. 214, p. 84–96, at https://doi.org/10.1016/j.geomorph.2014.03.013.

Aragón, A., Gaither, C.J., Madden, M., and Goodrick, S.L., 2019, The "efficiency concern"—Exploring wildfire risk on heirs' property in Macon‑Bibb County, Georgia, United States of America: Human Ecology Review, v. 25, no. 2, p. 51–68, at https://www.jstor.org/stable/26964354.

Carroll, R.W.H., Gochis, D., and Williams, K.H., 2020, Efficiency of the summer monsoon in generating streamflow within a snow-dominated headwater basin of the Colorado River: Geophysical Research Letters, v. 47, no. 23, article e2020GL090856, at https://doi.org/10.1029/2020GL090856.

Huang, H., Qian, Y., Hao, D., McDowell, N., Li, L., Rogers, B.M., Shi, M., Rittger, K., Song, Y., et al., 2025, Elevated forest canopy loss after wildfires in moist and cool forests in the Pacific Northwest: Earth's Future, v. 13, no. 7, article e2025EF006373, at https://doi.org/10.1029/2025ef006373.

DeVoe, J.D., Proffitt, K.M., Mitchell, M.S., Jourdonnais, C.S., and Barker, K.J., 2019, Elk forage and risk tradeoffs during the fall archery season: The Journal of Wildlife Management, v. 83, no. 4, p. 801–816, at https://doi.org/10.1002/jwmg.21638.

Liang, Y., Stamatis, C., Fortner, E.C., Wernis, R.A., Van Rooy, P., Majluf, F., Yacovitch, T.I., Daube, C., Herndon, S.C., et al., 2022, Emissions of organic compounds from western US wildfires and their near-fire transformations: Atmospheric Chemistry and Physics, v. 22, no. 15, p. 9877–9893, at https://doi.org/10.5194/acp-22-9877-2022.

Irvine, K.M., Miller, S.W., Al-Chokhachy, R.K., Archer, E.K., Roper, B.B., and Kershner, J.L., 2015, Empirical evaluation of the conceptual model underpinning a regional aquatic long-term monitoring program using causal modelling: Ecological Indicators, v. 50, p. 8–23, at https://doi.org/10.1016/j.ecolind.2014.10.011.

Connor, C.D.O., Calkin, D.E., and Thompson, M.P., 2017, An empirical machine learning method for predicting potential fire control locations for pre-fire planning and operational fire management: International Journal of Wildland Fire, v. 26, no. 7, article 587, at https://doi.org/10.1071/wf16135.

Gudex-Cross, D., Pontius, J., and Adams, A., 2017, Enhanced forest cover mapping using spectral unmixing and object-based classification of multi-temporal Landsat imagery: Remote Sensing of Environment, v. 196, p. 193–204, at https://doi.org/10.1016/j.rse.2017.05.006.

Clough, K., Farguell, A., Mandel, J., Hilburn, K., and Kochanski, A., 2025, Enhancing wildfire and smoke forecasting by integrating fire observations—A comparative analysis of methods for integrating infrared and satellite data into a coupled fire‐atmosphere model: Journal of Geophysical Research—Atmospheres, v. 130, no. 12, article e2024JD042561, at https://doi.org/10.1029/2024jd042561.

Yue, X., Mickley, L.J., Logan, J.A., and Kaplan, J.O., 2013, Ensemble projections of wildfire activity and carbonaceous aerosol concentrations over the western United States in the mid-21st century: Atmospheric Environment, v. 77, p. 767–780, at https://doi.org/10.1016/j.atmosenv.2013.06.003.

Zhou, T., Ding, L., Ji, J., Li, L., and Huang, W., 2019, Ensemble transform Kalman filter (ETKF) for large-scale wildland fire spread simulation using FARSITE tool and state estimation method: Fire Safety Journal, v. 105, p. 95–106, at https://doi.org/10.1016/j.firesaf.2019.02.009.

Parisien, M.A., and Moritz, M.A., 2009, Environmental controls on the distribution of wildfire at multiple spatial scales: Ecological Monographs, v. 79, no. 1, p. 127–154, at https://doi.org/10.1890/07-1289.1.

Poessel, S.A., Gese, E.M., and Young, J.K., 2017, Environmental factors influencing the occurrence of coyotes and conflicts in urban areas: Landscape and Urban Planning, v. 157, p. 259–269, at https://doi.org/10.1016/j.landurbplan.2016.05.022.

Phillips, C.A., Rogers, B.M., Elder, M., Cooperdock, S., Moubarak, M., Randerson, J.T., and Frumhoff, P.C., 2022, Escalating carbon emissions from North American boreal forest wildfires and the climate mitigation potential of fire management: Science Advances, v. 8, no. 17, article eabl7161, at https://doi.org/10.1126/sciadv.abl7161.

Sheng, J., Li, X., Wang, X., Wang, Y., Li, S., Li, D., Sun, S., and Zhao, L., 2024, An escape route planning model based on wildfire prediction information and travel rate of firefighters: International Journal of Wildland Fire, v. 33, no. 3, article Wf23166, at https://doi.org/10.1071/WF23166.

Fernandez-Guisuraga, J.M., Calvo, L., Fernandes, P.M., Hulet, A., Perryman, B., Schultz, B., Jensen, K.S., Enterkine, J., Boyd, C.S., et al., 2023, Estimates of fine fuel litter biomass in the northern Great Basin reveal increases during short fire-free intervals associated with invasive annual grasses: Science of the Total Environment, v. 860, article 160634, at https://doi.org/10.1016/j.scitotenv.2022.160634.

Ruhl, C.Q., Cain, J.W., Abadi, F., and Hennig, J.D., 2025, Estimating abundance of desert bighorn sheep with double‐observer sightability modeling with residual heterogeneity: The Journal of Wildlife Management, v. 89, no. 6, article e70050, at https://doi.org/10.1002/jwmg.70050.

Engelstad, P.S., Falkowski, M., Wolter, P., Poznanovic, A., and Johnson, P., 2019, Estimating canopy fuel attributes from low-density LiDAR: Fire, v. 2, no. 3, article 38, at https://doi.org/10.3390/fire2030038.

Wada, C.A., Bremer, L.L., Burnett, K., Trauernicht, C., Giambelluca, T., Mandle, L., Parsons, E., Weil, C., Kurashima, N., et al., 2017, Estimating cost-effectiveness of Hawaiian dry forest restoration using spatial changes in water yield and landscape flammability under climate change: Pacific Science, v. 71, no. 4, p. 401–424, at https://doi.org/10.2984/71.4.2.

Hogland, J., Affleck, D.L.R., Anderson, N., Seielstad, C., Dobrowski, S., Graham, J., and Smith, R., 2020, Estimating forest characteristics for longleaf pine restoration using normalized remotely sensed imagery in Florida USA: Forests, v. 11, no. 4, article 426, at https://doi.org/10.3390/F11040426.

Keeley, A.T.H., Beier, P., and Gagnon, J.W., 2016, Estimating landscape resistance from habitat suitability—Effects of data source and nonlinearities: Landscape Ecology, v. 31, no. 9, p. 2151–2162, at https://doi.org/10.1007/s10980-016-0387-5.

Staley, D.M., Tillery, A.C., Kean, J.W., McGuire, L.A., Pauling, H.E., Rengers, F.K., and Smith, J.B., 2018, Estimating post-fire debris-flow hazards prior to wildfire using a statistical analysis of historical distributions of fire severity from remote sensing data: International Journal of Wildland Fire, v. 27, no. 9, p. 595–608, at https://doi.org/10.1071/WF17122.

Hampton, H.M., Sesnie, S.E., Bailey, J.D., and Snider, G.B., 2011, Estimating regional wood supply based on stakeholder consensus for forest restoration in northern Arizona: Journal of Forestry, v. 109, no. 1, p. 15–26, at https://doi.org/10.1093/jof/109.1.15.

Scamardo, J.E., Marshall, S., and Wohl, E., 2022, Estimating widespread beaver dam loss—Habitat decline and surface storage loss at a regional scale: Ecosphere, v. 13, no. 3, article e3962, at https://doi.org/10.1002/ecs2.3962.

Connor, T., Dheer, A., Dorcy‐Ponce, J., Steinbeiser, C., Landers, R.H., Klip, M., and Furnas, B.J., 2025, Estimating wildlife populations and their dynamics using multiple data sources and a hierarchical integrated model—The case of California's black bears: Ecological Solutions and Evidence, v. 6, no. 3, article e70076, at https://doi.org/10.1002/2688-8319.70076.

Cochrane, M.A., Moran, C.J., Wimberly, M.C., Baer, A.D., Finney, M.A., Beckendorf, K.L., Eidenshink, J., and Zhu, Z., 2012, Estimation of wildfire size and risk changes due to fuels treatments: International Journal of Wildland Fire, v. 21, no. 4, p. 357–367, at https://doi.org/10.1071/WF11079.

Carlson, A.R., Hawbaker, T.J., Bair, L.S., Hoffman, C.M., Meldrum, J.R., Scott Baggett, L.S., and Steblein, P.F., 2025, Evaluating a simulation-based wildfire burn probability map for the conterminous US: International Journal of Wildland Fire, v. 34, no. 1, article Wf23196, at https://doi.org/10.1071/WF23196.

Povak, N.A., Furniss, T.J., Hessburg, P.F., Salter, R.B., Wigmosta, M., Duan, Z., and LeFevre, M., 2022, Evaluating basin-scale forest adaptation scenarios—Wildfire, streamflow, biomass, and economic recovery synergies and trade-offs: Frontiers in Forests and Global Change, v. 5, article 805179, at https://doi.org/10.3389/ffgc.2022.805179.

Carroll, S.L., Schmidt, G.M., Waller, J.S., and Graves, T.A., 2024, Evaluating density-weighted connectivity of black bears (Ursus americanus) in Glacier National Park with spatial capture-recapture models: Movement Ecology, v. 12, no. 1, article 8, at https://doi.org/10.1186/s40462-023-00445-7.

Seeley, M.M., Vaughn, N.R., and Asner, G.A., 2024, Evaluating individual tree species classification performance across diverse environments: Environmental Research—Ecology, v. 3, no. 1, article 011001, at https://doi.org/10.1088/2752-664X/ad1f49.

Robichaud, P.R., Lewis, S.A., Brown, R.E., Bone, E.D., and Brooks, E.S., 2020, Evaluating post-wildfire logging-slash cover treatment to reduce hillslope erosion after salvage logging using ground measurements and remote sensing: Hydrological Processes, v. 34, no. 23, p. 4431–4445, at https://doi.org/10.1002/hyp.13882.

Waring, K.M., Hansen, K.J., and Flatley, W., 2016, Evaluating prescribed fire effectiveness using permanent monitoring plot data—A case study: Fire Ecology, v. 12, no. 3, p. 1–25, at https://doi.org/10.4996/fireecology.1203002.

Marsha, A.L., and Larkin, N.K., 2022, Evaluating satellite fire detection products and an ensemble approach for estimating burned area in the United States: Fire, v. 5, no. 5, article 147, at https://doi.org/10.3390/fire5050147.

Veraverbeke, S., and Hook, S.J., 2013, Evaluating spectral indices and spectral mixture analysis for assessing fire severity, combustion completeness and carbon emissions: International Journal of Wildland Fire, v. 22, no. 5, p. 707–720, at https://doi.org/10.1071/WF12168.

Keane, R.E., and Karau, E., 2010, Evaluating the ecological benefits of wildfire by integrating fire and ecosystem simulation models: Ecological Modelling, v. 221, no. 8, p. 1162–1172, at https://doi.org/10.1016/j.ecolmodel.2010.01.008.

Bridges-Lyman, T.A., Brown, J.L., Chambers, J.C., Ellsworth, L.M., Reeves, M.C., Short, K.C., Strand, E.K., and Taylor, M.H., 2024, Evaluating the economic efficiency of fuel reduction treatments in sagebrush ecosystems that vary in ecological resilience and invasion resistance: Land, v. 13, no. 12, article 2131, at https://doi.org/10.3390/land13122131.

Kluever, B.M., and Gese, E.M., 2017, Evaluating the influence of water developments on the demography and spatial ecology of a rare, desert-adapted carnivore—The kit fox (Vulpes macrotis): Journal of Mammalogy, v. 98, no. 3, p. 815–826, at https://doi.org/10.1093/jmammal/gyx038.

Campbell, M.J., Eastburn, J.F., Dennison, P.E., Vogeler, J.C., and Stovall, A.E.L., 2024, Evaluating the performance of airborne and spaceborne lidar for mapping biomass in the United States' largest dry woodland ecosystem: Remote Sensing of Environment, v. 308, article 114196, at https://doi.org/10.1016/j.rse.2024.114196.

Sayarshad, H.R., and Ghorbanloo, R., 2023, Evaluating the resilience of electrical power line outages caused by wildfires: Reliability Engineering and System Safety, v. 240, article 109588, at https://doi.org/10.1016/j.ress.2023.109588.

Al-Chokhachy, R., Roper, B.B., and Archer, E.K., 2010, Evaluating the status and trends of physical stream habitat in headwater streams within the interior Columbia River and upper Missouri River basins using an index approach: Transactions of the American Fisheries Society, v. 139, no. 4, p. 1041–1059, at https://doi.org/10.1577/T08-221.1.

Shin, P., Sankey, T., Moore, M.M., and Thode, A.E., 2018, Evaluating unmanned aerial vehicle images for estimating forest canopy fuels in a ponderosa pine stand: Remote Sensing, v. 10, no. 8, article 1266, at https://doi.org/10.3390/rs10081266.

Hessburg, P.F., Reynolds, K.M., Keane, R.E., James, K.M., and Salter, R.B., 2007, Evaluating wildland fire danger and prioritizing vegetation and fuels treatments: Forest Ecology and Management, v. 247, no. 1–3, p. 1–17, at https://doi.org/10.1016/j.foreco.2007.03.068.

Page, W.G., Wagenbrenner, N.S., Butler, B.W., Forthofer, J.M., and Gibson, C., 2017, An evaluation of NDFD weather forecasts for wildland fire behavior prediction: Weather and Forecasting, v. 33, no. 1, p. 301–315, at https://doi.org/10.1175/WAF-D-17-0121.1.

Vaillant, N.M., and Reinhardt, E.D., 2017, An evaluation of the Forest Service hazardous fuels treatment program-are we treating enough to promote resiliency or reduce hazard?: Journal of Forestry, v. 115, no. 4, p. 300–308, at https://doi.org/10.5849/jof.16-067.

Hagmann, R.K., Hessburg, P.F., Prichard, S.J., Povak, N.A., Brown, P.M., Fule, P.Z., Keane, R.E., Knapp, E.E., Lydersen, J.M., et al., 2021, Evidence for widespread changes in the structure, composition, and fire regimes of western North American forests: Ecological Applications, v. 31, no. 8, article e02431, at https://doi.org/10.1002/eap.2431.

Urza, A.K., Weisberg, P.J., and Dilts, T., 2020, Evidence of widespread topoclimatic limitation for lower treelines of the Intermountain West, United States: Ecological Applications, v. 30, no. 7, article e02158, at https://doi.org/10.1002/eap.2158.

Ausband, D.E., Thompson, S.J., Oates, B.A., Roberts, S.B., Hurley, M.A., and Mumma, M.A., 2023, Examining dynamic occupancy of gray wolves in Idaho after a decade of managed harvest: The Journal of Wildlife Management, v. 87, no. 6, article e22453, at https://doi.org/10.1002/jwmg.22453.

Kumar, M., Li, S., Nguyen, P., and Banerjee, T., 2022, Examining the existing definitions of wildland-urban interface for California: Ecosphere, v. 13, no. 12, article e4306, at https://doi.org/10.1002/ecs2.4306.

Benefield, A., and Chen, J., 2021, Examining the influence of outdoor recreation on anthropogenic wildfire regime of the Southern Rocky Mountains: Natural Hazards, v. 111, no. 1, p. 523–545, at https://doi.org/10.1007/s11069-021-05065-1.

Demeo, T., Haugo, R., Ringo, C., Kertis, J., Acker, S., Simpson, M., and Stern, M., 2018, Expanding our understanding of forest structural restoration needs in the Pacific Northwest: Northwest Science, v. 92, no. 1, p. 18–35, at https://doi.org/10.3955/046.092.0104.

Mekonnen, Z.A., Riley, W.J., Randerson, J.T., Grant, R.F., and Rogers, B.M., 2019, Expansion of high-latitude deciduous forests driven by interactions between climate warming and fire: Nature Plants, v. 5, no. 9, p. 952–958, at https://doi.org/10.1038/s41477-019-0495-8.

Shouse, M.L., and Blandford, B.L., 2015, Expert systems model for Kentucky arrow darter habitat in the Upper Kentucky River Basin: Papers in Applied Geography, v. 1, no. 4, p. 383–390, at https://doi.org/10.1080/23754931.2015.1095789.

Scott, J.H., Thompson, M.P., and Gilbertson-Day, J.W., 2015, Exploring how alternative mapping approaches influence fireshed assessment and human community exposure to wildfire: GeoJournal, v. 82, no. 1, p. 201–215, at https://doi.org/10.1007/s10708-015-9679-6.

Peeler, J.L., and Smithwick, E.A.H., 2018, Exploring invasibility with species distribution modeling—How does fire promote cheatgrass (Bromus tectorum) invasion within lower montane forests?: Diversity and Distributions, v. 24, no. 9, p. 1308–1320, at https://doi.org/10.1111/ddi.12765.

Donnelly, J.P., Tack, J.D., Doherty, K.E., Naugle, D.E., Allred, B.W., and Dreitz, V.J., 2017, Extending conifer removal and landscape protection strategies from sage-grouse to songbirds, a range-wide assessment: Rangeland Ecology & Management, v. 70, no. 1, p. 95–105, at https://doi.org/10.1016/j.rama.2016.10.009.

Reeves, M.C., and Mitchell, J.E., 2011, Extent of coterminous US rangelands—Quantifying implications of differing agency perspectives: Rangeland Ecology & Management, v. 64, no. 6, p. 585–597, at https://doi.org/10.2111/REM-D-11-00035.1.

Thaler, E.A., Larsen, I.J., and Yu, Q., 2021, The extent of soil loss across the US Corn Belt: Proceedings of the National Academy of Sciences of the United States of America, v. 118, no. 8, article e1922375118, at https://doi.org/10.1073/pnas.1922375118.

McFarland, J.R., Coop, J.D., Balik, J.A., Rodman, K.C., Parks, S.A., and Stevens-Rumann, C.S., 2025, Extreme fire spread events burn more severely and homogenize postfire landscapes in the southwestern United States: Global Change Biology, v. 31, no. 2, article e70106, at https://doi.org/10.1111/gcb.70106.

Evers, C., Holz, A., Busby, S., and Nielsen-Pincus, M., 2022, Extreme winds alter influence of fuels and topography on megafire burn severity in seasonal temperate rainforests under record fuel aridity: Fire, v. 5, no. 2, article 41, at https://doi.org/10.3390/fire5020041.

Smith, M.M., and Goldberg, C.S., 2022, Facilitative interaction promotes occupancy of a desert amphibian across a climate gradient: Oecologia, v. 198, no. 3, p. 815–823, at https://doi.org/10.1007/s00442-022-05127-6.

Scholer, M.N., Leu, M., and Belthoff, J.R., 2014, Factors associated with flammulated owl and northern saw-whet owl occupancy in southern Idaho: Journal of Raptor Research, v. 48, no. 2, p. 128–141, at https://doi.org/10.3356/JRR-13-00049.1.

Carroll, R.W.H., Bearup, L.A., Brown, W., Dong, W., Bill, M., and Willlams, K.H., 2018, Factors controlling seasonal groundwater and solute flux from snow-dominated basins: Hydrological Processes, v. 32, no. 14, p. 2187–2202, at https://doi.org/10.1002/hyp.13151.

DeVoe, J.D., Proffitt, K.M., and Millspaugh, J.J., 2025, Factors influencing pronghorn migration behavior and plasticity: Ecosphere, v. 16, no. 9, article e70411, at https://doi.org/10.1002/ecs2.70411.

Rhodes, T.K., Aguilar, F.X., Jose, S., and Gold, M., 2016, Factors influencing the adoption of riparian forest buffers in the Tuttle Creek Reservoir watershed of Kansas, USA: Agroforestry Systems, v. 92, no. 3, p. 739–757, at https://doi.org/10.1007/s10457-016-0045-6.

Alexandre, P.M., Stewart, S.I., Keuler, N.S., Clayton, M.K., Mockrin, M.H., Bar-Massada, A., Syphard, A.D., and Radeloff, V.C., 2016, Factors related to building loss due to wildfires in the conterminous United States: Ecological Applications, v. 26, no. 7, p. 2323–2338, at https://doi.org/10.1002/eap.1376.

Yang, P., Cai, X., and Khanna, M., 2021, Farmers' heterogeneous perceptions of marginal land for biofuel crops in US midwestern states considering biophysical and socioeconomic factors: GCB Bioenergy, v. 13, no. 5, p. 849–861, at https://doi.org/10.1111/gcbb.12821.

Marcozzi, A., Wells, L., Parsons, R., Mueller, E., Linn, R., and Hiers, J.K., 2025, FastFuels—Advancing wildland fire modeling with high-resolution 3D fuel data and data assimilation: Environmental Modelling & Software, v. 183, article 106214, at https://doi.org/10.1016/j.envsoft.2024.106214.

Soulard, C.E., Walker, J.J., Smith, B.W., and Kreitler, J., 2024, The feasibility of using national-scale datasets for classifying wetlands in Arizona with machine learning: Earth Surface Processes and Landforms, v. 49, no. 14, p. 4632–4649, at https://doi.org/10.1002/esp.5985.

Loggers, E.A., Litt, A.R., Haroldson, M.A., Gunther, K.A., and van Manen, F.T., 2025, Female and male grizzly bears differ in their responses to low-intensity recreation in a protected area: The Journal of Wildlife Management, v. 89, no. 7, article e70068, at https://doi.org/10.1002/jwmg.70068.

Ramirez, S., Bedrosian, B., Woolwine, D., and Pejchar, L., 2025, Ferruginous hawk nest site selection, success, and productivity—Implications for mitigating the effects of natural gas development: Biological Conservation, v. 310, article 111314, at https://doi.org/10.1016/j.biocon.2025.111314.

West, A.M., Kumar, S., Brown, C.S., Stohlgren, T.J., and Bromberg, J., 2016, Field validation of an invasive species Maxent model: Ecological Informatics, v. 36, p. 126–134, at https://doi.org/10.1016/j.ecoinf.2016.11.001.

Stonesifer, C.S., Calkin, D.E., Thompson, M.P., and Stockmann, K.D., 2016, Fighting fire in the heat of the day—An analysis of operational and environmental conditions of use for large airtankers in United States fire suppression: International Journal of Wildland Fire, v. 25, no. 5, p. 520–533, at https://doi.org/10.1071/WF15149.

Palaiologou, P., Ager, A.A., Evers, C.R., Nielsen-Pincus, M., Day, M.A., and Preisler, H.K., 2019, Fine-scale assessment of cross-boundary wildfire events in the western United States: Natural Hazards and Earth System Sciences, v. 19, no. 8, p. 1755–1777, at https://doi.org/10.5194/nhess-19-1755-2019.

Stroh, E.D., Struckhoff, M.A., Stambaugh, M.C., and Guyette, R.P., 2018, Fire and climate suitability for woody vegetation communities in the south central United States: Fire Ecology, v. 14, no. 1, p. 106–124, at https://doi.org/10.4996/fireecology.140110612.

Cansler, C.A., Hood, S.M., Varner, J.M., van Mantgem, P.J., Agne, M.C., Andrus, R.A., Ayres, M.P., Ayres, B.D., Bakker, J.D., et al., 2020, The Fire and Tree Mortality Database, for empirical modeling of individual tree mortality after fire: Scientific Data, v. 7, no. 1, article 194, at https://doi.org/10.1038/s41597-020-0522-7.

Smith, J.K., 2010, Fire effects information system—New engine, remodeled interior, added options: Fire Management Today, v. 70, no. 1, p. 44–47, at https://nrfirescience.org/sites/default/files/2023-08/rmrs_2010_smith_j001_0.pdf.

Miesel, J.R., Goebel, P.C., Corace, R.G., III, Hix, D.M., Kolka, R., Palik, B., and Mladenoff, D., 2012, Fire effects on soils in Lake States forests—A compilation of published research to facilitate long-term investigations: Forests, v. 3, no. 4, p. 1034–1070, at https://doi.org/10.3390/f3041034.

Airey, C.T., and Taylor, A.H., 2024, Fire exclusion and megadrought accelerate whitebark pine mortality and succession in a trailing edge subalpine forest: Forest Ecology and Management, v. 568, article 122104, at https://doi.org/10.1016/j.foreco.2024.122104.

Steel, Z.L., Safford, H.D., and Viers, J.H., 2015, The fire frequency-severity relationship and the legacy of fire suppression in California forests: Ecosphere, v. 6, no. 1, article 8, at https://doi.org/10.1890/ES14-00224.1.

Schoennagel, T., Sherriff, R.L., and Veblen, T.T., 2011, Fire history and tree recruitment in the Colorado Front Range upper montane zone—Implications for forest restoration: Ecological Applications, v. 21, no. 6, p. 2210–2222, at https://doi.org/10.1890/10-1222.1.

Sparks, A.M., Kolden, C.A., Smith, A.M.S., Boschetti, L., Johnson, D.M., and Cochrane, M.A., 2018, Fire intensity impacts on post-fire temperate coniferous forest net primary productivity: Biogeosciences, v. 15, no. 4, p. 1173–1183, at https://doi.org/10.5194/bg-15-1173-2018.

Kemp, K.B., Higuera, P.E., and Morgan, P., 2016, Fire legacies impact conifer regeneration across environmental gradients in the U.S. Northern Rockies: Landscape Ecology, v. 31, no. 3, p. 619–636, at https://doi.org/10.1007/s10980-015-0268-3.

Meunier, J., Holoubek, N.S., and Sebasky, M., 2019, Fire regime characteristics in relation to physiography at local and landscape scales in Lake States pine forests: Forest Ecology and Management, v. 454, article 117651, at https://doi.org/10.1016/j.foreco.2019.117651.

Krawchuk, M.A., and Moritz, M.A., 2009, Fire regimes of China—Inference from statistical comparison with the United States: Global Ecology and Biogeography, v. 18, no. 5, p. 626–639, at https://doi.org/10.1111/j.1466-8238.2009.00472.x.

Fulé, P.Z., Barrett, M.P., Cocke, A.E., Crouse, J.E., Roccaforte, J.P., Normandin, D.P., Covington, W.W., Moore, M.M., Heinlein, T.A., et al., 2023, Fire regimes over a 1070-m elevational gradient, San Francisco Peaks/Dook’o’oos?ííd, Arizona, USA: Fire Ecology, v. 19, no. 1, article 41, at https://doi.org/10.1186/s42408-023-00204-4.

Odion, D.C., and Hanson, C.T., 2006, Fire severity in conifer forests of the Sierra Nevada, California: Ecosystems, v. 9, no. 7, p. 1177–1189, at https://doi.org/10.1007/s10021-003-0134-z.

Holden, S.R., Rogers, B.M., Treseder, K.K., and Randerson, J.T., 2016, Fire severity influences the response of soil microbes to a boreal forest fire: Environmental Research Letters, v. 11, no. 3, article 035004, at https://doi.org/10.1088/1748-9326/11/3/035004.

Kim, M., Pais, C., and Gonzalez, M.C., 2025, Fire spread simulations using Cell2Fire on synthetic and real landscapes: Scientific Reports, v. 15, no. 1, article 25173, at https://doi.org/10.1038/s41598-025-05706-6.

Frost, S.M., Alexander, M.E., Derose, R.J., and Jenkins, M.J., 2020, Fire-environment analysis—An example of Army Garrison Camp Williams, Utah: Fire, v. 3, no. 1, article 6, at https://doi.org/10.3390/fire3010006.

Adams, K.V., Dixon, J.L., Wilcox, A.C., and McWethy, D., 2023, Fire-produced coarse woody debris and its role in sediment storage on hillslopes: Earth Surface Processes and Landforms, v. 48, no. 9, p. 1665–1678, at https://doi.org/10.1002/esp.5573.

Sheehan, T., Bachelet, D., and Ferschweiler, K., 2019, Fire, CO2 , and climate effects on modeled vegetation and carbon dynamics in western Oregon and Washington: PLoS ONE, v. 14, no. 1, article e0210989, at https://doi.org/10.1371/journal.pone.0210989.

Yang, X., Melachrinoudis, E., Kubat, P., and Smith, J.M., 2022, Fireline path optimisation in a heterogeneous forest landscape: International Journal of Wildland Fire, v. 31, no. 11, p. 1068–1079, at https://doi.org/10.1071/WF22037.

Chen, J., Anderson, K., Pavlovic, R., Moran, M.D., Englefield, P., Thompson, D.K., Munoz-Alpizar, R., and Landry, H., 2019, The FireWork v2.0 air quality forecast system with biomass burning emissions from the Canadian Forest Fire Emissions Prediction System v2.03: Geoscientific Model Development, v. 12, no. 7, p. 3283–3310, at https://doi.org/10.5194/gmd-12-3283-2019.

Reinhardt, E.D., and Dickinson, M.B., 2010, First-order fire effects models for land management—Overview and issues: Fire Ecology, v. 6, no. 1, p. 131–142, at https://doi.org/10.4996/fireecology.0601131.

Olson, L.E., Sauder, J.D., Fekety, P.A., Golding, J.D., Lewis, C.W., Sadak, R.B., and Schwartz, M.K., 2024, Fishers (Pekania pennanti) are forest structure specialists when resting and generalists when moving—Behavior influences resource selection in a northern Rocky Mountain fisher population: Movement Ecology, v. 12, no. 1, article 49, at https://doi.org/10.1186/s40462-024-00487-5.

Miller, R.A., Wallace, Z.P., Skorkowsky, R.C., Blakesley, J.A., Mika, M., Buchanan, J.B., Carlisle, J.D., and Green, M., 2024, Flammulated owl distribution and habitat associations during the breeding season in the western United States: Forest Ecology and Management, v. 558, article 121798, at https://doi.org/10.1016/j.foreco.2024.121798.

Cao, Q., Gershunov, A., Shulgina, T., Ralph, F.M., Sun, N., and Lettenmaier, D.P., 2020, Floods due to atmospheric rivers along the U.S. west coast—The role of antecedent soil moisture in a warming climate: Journal of Hydrometeorology, v. 21, no. 8, p. 1827–1845, at https://doi.org/10.1175/JHM-D-19-0242.1.

Gustafson, E.J., Sturtevant, B.R., de Bruijn, A.M.G., Lichti, N., Jacobs, D.F., Kashian, D.M., Miranda, B.R., and Townsend, P.A., 2018, Forecasting effects of tree species reintroduction strategies on carbon stocks in a future without historical analog: Global Change Biology, v. 24, no. 11, p. 5500–5517, at https://doi.org/10.1111/gcb.14397.

Kean, J.W., and Staley, D.M., 2021, Forecasting the frequency and magnitude of postfire debris flows across southern California: Earth's Future, v. 9, no. 3, article e2020EF001735, at https://doi.org/10.1029/2020ef001735.

Rittenhouse, C.D., and Rissman, A.R., 2012, Forest cover, carbon sequestration, and wildlife habitat—Policy review and modeling of tradeoffs among land-use change scenarios: Environmental Science & Policy, v. 21, p. 94–105, at https://doi.org/10.1016/j.envsci.2012.04.006.

Liang, L., Hawbaker, T.J., Zhu, Z., Li, X., and Gong, P., 2016, Forest disturbance interactions and successional pathways in the Southern Rocky Mountains: Forest Ecology and Management, v. 375, p. 35–45, at https://doi.org/10.1016/j.foreco.2016.05.010.

Hanberry, B.B., 2021, Forest disturbance types and current analogs for historical disturbance-independent forests: Land, v. 10, no. 2, article 136, at https://doi.org/10.3390/land10020136.

Zheng, Z., Huang, W., Li, S., and Zeng, Y., 2017, Forest fire spread simulating model using cellular automaton with extreme learning machine: Ecological Modelling, v. 348, p. 33–43, at https://doi.org/10.1016/j.ecolmodel.2016.12.022.

McCabe, L.M., Chesshire, P., and Cobb, N.S., 2023, Forest habitats and plant communities strongly predicts Megachilidae bee biodiversity: PeerJ, v. 11, article e16145, at https://doi.org/10.7717/peerj.16145.

Soulard, C.E., Walker, J.J., and Griffith, G.E., 2017, Forest harvest patterns on private lands in the Cascade Mountains, Washington, USA: Forests, v. 8, no. 10, article 383, at https://doi.org/10.3390/f8100383.

Bond, M.L., Chi, T.Y., Bradley, C.M., and DellaSala, D.A., 2022, Forest management, barred owls, and wildfire in northern spotted owl territories: Forests, v. 13, no. 10, article 1730, at https://doi.org/10.3390/f13101730.

Hart, P.J., Ibanez, T., Uehana, S., and Pang-Ching, J., 2020, Forest regeneration following ungulate removal in a montane Hawaiian wet forest: Restoration Ecology, v. 28, no. 4, p. 757–765, at https://doi.org/10.1111/rec.13116.

Thompson, M.P., Gannon, B.M., and Caggiano, M.D., 2021, Forest roads and operational wildfire response planning: Forests, v. 12, no. 2, p. 1–11, at https://doi.org/10.3390/f12020110.

McQuillan, K.A., Tulbure, M.G., and Martin, K.L., 2022, Forest water use is increasingly decoupled from water availability even during severe drought: Landscape Ecology, v. 37, no. 7, p. 1801–1817, at https://doi.org/10.1007/s10980-022-01425-9.

Li, X., Tian, H., Lu, C., and Pan, S., 2023, Four-century history of land transformation by humans in the United States (1630-2020)—Annual and 1gkm grid data for the HIStory of LAND changes (HISLAND-US): Earth System Science Data, v. 15, no. 2, p. 1005–1035, at https://doi.org/10.5194/essd-15-1005-2023.

Carroll, K.A., Inman, R.M., Hansen, A.J., Lawrence, R.L., and Barnett, K., 2021, A framework for collaborative wolverine connectivity conservation: iScience, v. 24, no. 8, article 102840, at https://doi.org/10.1016/j.isci.2021.102840.

Kiesecker, J.M., Copeland, H., Pocewicz, A., Nibbelink, N., McKenney, B., Dahlke, J., Holloran, M., and Stroud, D., 2009, A Framework for implementing Biodiversity offsets—Selecting sites and determining scale: BioScience, v. 59, no. 1, p. 77–84, at https://doi.org/10.1525/bio.2009.59.1.11.

Tidwell, V.C., Lowry, T.S., Binning, D., Graves, J., Peplinski, W.J., and Mitchell, R., 2019, Framework for shared drinking water risk assessment: International Journal of Critical Infrastructure Protection, v. 24, p. 37–47, at https://doi.org/10.1016/j.ijcip.2018.10.007.

Coe, S.T., Elmore, J.A., Elizondo, E.C., and Loss, S.R., 2021, Free-ranging domestic cat abundance and sterilization percentage following five years of a trap-neuter-return program: Wildlife Biology, v. 2021, no. 1, article wlb.00799, at https://doi.org/10.2981/wlb.00799.

Page, W.G., and Butler, B.W., 2018, Fuel and topographic influences on wildland firefighter burnover fatalities in southern California: International Journal of Wildland Fire, v. 27, no. 3, p. 141–154, at https://doi.org/10.1071/WF17147.

Prichard, S.J., Povak, N.A., Kennedy, M.C., and Peterson, D.W., 2020, Fuel treatment effectiveness in the context of landform, vegetation, and large, wind-driven wildfires: Ecological Applications, v. 30, no. 5, article e02104, at https://doi.org/10.1002/eap.2104.

Prichard, S.J., and Kennedy, M.C., 2014, Fuel treatments and landform modify landscape patterns of burn severity in an extreme fire event: Ecological Applications, v. 24, no. 3, p. 571–590, at https://doi.org/10.1890/13-0343.1.

Shaik, R.U., Alipour, M., Rowell, E., Balaji, B., Watts, A., and Taciroglu, E., 2025, FUELVISION—A multimodal data fusion and multimodel ensemble algorithm for wildfire fuels mapping: International Journal of Applied Earth Observation and Geoinformation, v. 138, article 104436, at https://doi.org/10.1016/j.jag.2025.104436.

Kohl, M.T., Sandford, C.P., Rogers, P.C., Chi, R., Messmer, T.A., and Dahlgren, D.K., 2024, Function over form—The benefits of aspen as surrogate brood‐rearing habitat for greater sage‐grouse: Ecosphere, v. 15, no. 12, article e70060, at https://doi.org/10.1002/ecs2.70060.

Shinneman, D.J., Strand, E.K., Pellant, M., Abatzoglou, J.T., Brunson, M.W., Glenn, N.F., Heinrichs, J.A., Sadegh, M., and Vaillant, N.M., 2023, Future direction of fuels management in sagebrush rangelands: Rangeland Ecology & Management, v. 86, p. 50–63, at https://doi.org/10.1016/j.rama.2022.10.009.

Hessilt, T.D., Abatzoglou, J.T., Chen, Y., Randerson, J.T., Scholten, R.C., van der Werf, G., and Veraverbeke, S., 2022, Future increases in lightning ignition efficiency and wildfire occurrence expected from drier fuels in boreal forest ecosystems of western North America: Environmental Research Letters, v. 17, no. 5, article 54008, at https://doi.org/10.1088/1748-9326/ac6311.

Mullin, C.A., Kirchhoff, C.J., Wang, G., and Vlahos, P., 2020, Future projections of water temperature and thermal stratification in Connecticut reservoirs and possible implications for cyanobacteria: Water Resources Research, v. 56, no. 11, article e2020WR027185, at https://doi.org/10.1029/2020WR027185.

Kodero, J.M., Felzer, B.S., and Shi, Y., 2024, Future transition from forests to shrublands and grasslands in the western United States is expected to reduce carbon storage: Communications Earth & Environment, v. 5, no. 1, article 78, at https://doi.org/10.1038/s43247-024-01253-6.

Bennett, K.E., Miller, G., Talsma, C., Jonko, A., Bruggeman, A., Atchley, A., Lavadie-Bulnes, A., Kwicklis, E., and Middleton, R., 2020, Future water resource shifts in the high desert southwest of northern New Mexico, USA: Journal of Hydrology - Regional Studies, v. 28, article 100678, at https://doi.org/10.1016/j.ejrh.2020.100678.

Silva, L.C.R., Wood, M.C., Johnson, B.R., Coughlan, M.R., Brinton, H., McGuire, K., and Bridgham, S.D., 2022, A generalizable framework for enhanced natural climate solutions: Plant and Soil, v. 479, p. 3–24, at https://doi.org/10.1007/s11104-022-05472-8.

Coen, J.L., Schroeder, W., and Quayle, B., 2018, The generation and forecast of extreme winds during the origin and progression of the 2017 Tubbs Fire: Atmosphere, v. 9, no. 12, article 462, at https://doi.org/10.3390/atmos9120462.

Pettinari, M.L., and Chuvieco, E., 2016, Generation of a global fuel data set using the Fuel Characteristic Classification System: Biogeosciences, v. 13, no. 7, p. 2061–2076, at https://doi.org/10.5194/bg-13-2061-2016.

Parchman, T.L., Buerkle, C.A., Soria-Carrasco, V., and Benkman, C.W., 2016, Genome divergence and diversification within a geographic mosaic of coevolution: Molecular Ecology, v. 25, no. 22, p. 5705–5718, at https://doi.org/10.1111/mec.13825.

Flanagan, D.C., Frankenberger, J.R., Cochrane, T.A., Renschler, C.S., and Elliot, W.J., 2013, Geospatial application of the Water Erosion Prediction Project (WEPP) model: Transactions of the ASABE, v. 56, no. 2, p. 591–601, at https://doi.org/10.13031/2013.42681.

Chivhenge, E., Weiskittel, A.R., Woodall, C.W., D'Amato, A.W., and Daigneault, A., 2025, Geospatial estimation of forest relative density for carbon stewardship decision support across the continental US: Scientific Data, v. 12, no. 1, article 1728, at https://doi.org/10.1038/s41597-025-06012-6.

Johnson, A., Leigh, J., Morin, P., and Van Keken, P., 2006, GeoWall—Stereoscopic visualization for geoscience research and education: IEEE Computer Graphics and Applications, v. 26, no. 6, p. 10–14, at https://doi.org/10.1109/MCG.2006.127.

Ma, Z., Dong, C., Lin, K., Yan, Y., Luo, J., Jiang, D., and Chen, X., 2022, A global 250-m downscaled NDVI product from 1982 to 2018: Remote Sensing, v. 14, no. 15, article 3639, at https://doi.org/10.3390/rs14153639.

Beers, A.T., and Frey, S.N., 2022, Greater sage-grouse habitat selection varies across the marginal habitat of its lagging range margin: Ecosphere, v. 13, no. 7, article e4146, at https://doi.org/10.1002/ecs2.4146.

Poessel, S.A., Barnard, D.M., Applestein, C., Germino, M.J., Ellsworth, E.A., Major, D., Moser, A., and Katzner, T.E., 2022, Greater sage-grouse respond positively to intensive post-fire restoration treatments: Ecology and Evolution, v. 12, no. 3, article e8671, at https://doi.org/10.1002/ece3.8671.

Cook, A.A., Messmer, T.A., and Guttery, M.R., 2017, Greater sage-grouse use of mechanical conifer reduction treatments in northwest Utah: Wildlife Society Bulletin, v. 41, no. 1, p. 27–33, at https://doi.org/10.1002/wsb.742.

Wells, S.L., McNew, L.B., Tyers, D.B., Van Manen, F.T., and Thompson, D.J., 2018, Grizzly bear depredation on grazing allotments in the Yellowstone Ecosystem: The Journal of Wildlife Management, v. 83, no. 3, p. 556–566, at https://doi.org/10.1002/jwmg.21618.