Megafires in Oregon: Riparian vegetation layers differ three years after mixed severity fire

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Six, Jake Verschuyl, Ashley A. Coble This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6205148/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Oct, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Riparian ecosystems are highly diverse and dynamic, but effects of fire on riparian vegetation are poorly understood. In 2020, widespread fires impacted forests across the western Oregon Cascades, including riparian areas. To investigate riparian plant community recovery, we quantified riparian vegetation responses to wildfire and forest management. We determined that vegetation response to burn severity varied by structural layer and was dynamic across the first three years post-fire. Overstory mortality after fire varied by species. In the understory, forb cover recovered rapidly; shrub cover and richness showed some recovery within three years. Indicator species highlighted compositional differences between sites that burned and those that did not. Although riparian zones are thought to be resilient to fire, our results demonstrate megafires can significantly alter them, resulting in extensive initial and delayed mortality, and dynamic regrowth. Globally, riparian zones are increasingly exposed to fire, and understanding factors influencing their recovery is critical. Biological sciences/Ecology/Fire ecology Biological sciences/Ecology/Forest ecology Biological sciences/Ecology/Riparian ecology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION Riparian areas are often characterized by high plant diversity and structural complexity but can be affected by forest management 1 . Although the width of forested buffers and specific operating restrictions differ in managed forests across the globe 2 , 3 , the broader goal is often to insulate aquatic ecosystems from upslope disturbance. The efficacy of riparian buffers in protecting aquatic ecosystems from disturbance likely differs between anthropogenic and natural disturbances, and unique responses may occur when multiple disturbances occur in sequence. Natural disturbance (e.g., wind, fire, flood) can disrupt the regulating efficacy of riparian vegetation. However, riparian vegetation can also help regulate fire intensity or extent due to higher fuel moisture content and relative humidity 4 . While ecosystem response after fire has been examined, the response of riparian areas to fire, specifically that of understory riparian vegetation, has not been well-studied. Understory vegetation in riparian areas may be less affected by fire than adjacent uplands, even with similar overstory fire severity 5 . Fire may also be less frequent in riparian areas than in nearby upland forest, yet little is known about return intervals in riparian areas 6 , 7 . In the western US, greater water availability in riparian areas often supports deciduous trees and shrubs with greater levels of stem and foliar moisture content, particularly in dry periods 8 , although larger streams tend to have more hardwoods than smaller streams that support more conifers 5 . Therefore, riparian areas may act as refugia for fire-sensitive species typically found in upland forests 4 . If most of the riparian buffer is wet with a deep soil organic layer, understory community composition may be minimally affected by fire compared to unburned stands 9 . Even if affected by fire, riparian plant species may be uniquely resilient to disturbances given their adaptations to seasonal flooding, seasonal drought, and fire 1 , 10 . The speed and nature of riparian vegetation regrowth following disturbance are important because they affect recovery of stream ecosystem characteristics, such as stream temperature, bank stability, and sediment delivery. Without an intact overstory, riparian understory vegetation may serve a critical function in the post-fire recovery of the aquatic ecosystem by providing shade to the stream, intercepting precipitation and limiting overland runoff, and stabilizing banks with root development. In Mediterranean ecosystems, riparian zones can achieve rapid re-growth, particularly when riparian zones may have greater moisture content and nutrient availability 11 , or when disturbance-adapted species, with traits such as rapid sprouting or suckering, can quickly re-colonize 7 , 12 , 13 . In September 2020, widespread forest fires affected a mosaic of federal and private managed forests in the western Oregon Cascades, USA. Five mega-fires burned approximately 3440 km 2 , with more than 80 percent of that area burning in the first 48 hours of the wind-driven event 14 . These fires burned at relatively high severity, affecting numerous forested riparian areas along headwaters streams 4 . To better understand how these fires affected aquatic ecosystem processes, we applied an established, large-scale replicated study design, used to quantify environmental responses to variation in watershed forest composition, to examine site and vegetation characteristics following mixed severity fire within riparian management zones adjacent to small perennial streams. Our objectives were to determine whether riparian vegetation recovery after severe wildfires varied with burn severity, years since fire, pre-fire watershed age, or riparian stand structure. We explored these questions for each layer of riparian vegetation including 1) overstory 2) shrub and 3) forb layers using mortality, cover, and species richness as response variables. We hypothesized that burn severity would affect mortality and cover for all vegetation layers with delayed overstory mortality contributing to reduced canopy cover with time since fire, and rapid re-growth and establishment for shrub and forb layers contributing to increasing understory cover and species richness with time since fire. METHODS Our study was designed to compare stream and riparian responses to wildfires in the western Oregon Cascades, USA 15 , 16 . This area has a maritime climate regime, with mild wet winters and warm, dry summers, resulting in highly productive tree species, like Pseudotsuga menziesii , and a long history of timber production by various forest industry landowners 17 . Soils in the area are moderately deep, well drained loams and supports vegetation within the Tsuga heterophylla forest zone 17 . For our study, we used a stratified random sampling design with mean watershed pre-fire stand age (based on 2017 data) and watershed fire extent for 25, 4th order watersheds within 6 km of the Beachie Creek, Riverside, and Holiday Farm fire boundaries (Fig. 1 ). We considered watershed fire extent as one of four categories: unburned (0%), minority ( 50% and 99%) watershed burned. Mean watershed pre-fire stand age was split into 85y, based on the distribution of mean watershed stand age from all 4th order watersheds within 6 km of these fires. From the available 4th -order watersheds, we randomly selected three streams for each of the eight categories. For the vegetation sampling, we sampled an additional five streams located further up in the stream network, including two 3rd order and three 2nd order streams, to capture more severely burned riparian areas and monitor their recovery over time. This was done because riparian responses were expected to differ with watershed size and geomorphology of hydrologic features that also control riparian species composition 7 . To estimate the length of stream and associated riparian areas burned in these three fires, we clipped the National Hydrography Dataset plus version 2 (NHDPlus V2) stream layer to the fire boundaries for Beachie Creek, Riverside, and Holiday Farm and summed total length of stream. We obtained soil burn severity (SBS) from Burned Area Emergency Response (BAER) database, and evaluated riparian areas as within 30.48 m of stream. We collected data on overstory, shrub, and forb layer during summers 2021–2023 (after 2020 wildfires) at 30 different subbasin watersheds stratified across gradients of fire severity and prior forest management intensity. Each study site was comprised of a 100 m stream reach located at the downstream end of a 4th order stream basin. We placed four transects at 20 m intervals on alternating sides of each stream, extending 50 m perpendicular to each stream. We collected data on overstory condition and species composition in 10 × 20 m (200 m 2 plots), placed at 5–25 m along each transect. Using a line-intercept method along each transect, we recorded cover of each shrub species. For forb layer species, we placed 1 m 2 quadrats every 5 m along each transect and recorded cover class of each species: 1 = 0–1%, 2 = 1–5%, 3 = 5–25%, 4 = 25–50%, 5 = 50–75%, 6 = 75–95%, or 7 = > 95% cover. We sampled canopy density at each quadrat using a spherical densiometer by calculating an average of 4 readings at each quadrat. As a measure of burn severity, we used a qualitative scale (0–3) to quantify evidence of fire/burn at each quadrat (e.g., 0 = no evidence of fire, 3 = most of plot is covered by charred organic matter or other signs of fire) during the first sample year. We calculated mean burn severity for each site by averaging the plot-level numeric assessments of burn severity. To include a measure of riparian stand structure in our statistical models, we defined dominant canopy trees as those representing the largest 50 percent of total plot basal area (m 2 /ha), and calculated the mean diameter at breast height (DBH (cm)) of those dominant trees for each site. We averaged canopy cover measurements for each quadrat and then summarized these to the site level for each sample year. We calculated overstory mortality annually as the proportional mortality (number of dead trees divided by number of both live and dead trees) by tree plot, and then calculated mean mortality across the four tree plots at each site. We summarized shrub cover as the total distance (m) along each transect covered by each unique species. We then calculated shrub richness as the count of unique species recorded per transect each sample year, and then calculated a mean across the four transects for each site. We summarized forb cover and richness by species each sample year at the quadrat level and then calculated means to the site level. Statistical Analyses To assess whether burn severity influenced mortality and cover for all vegetation layers, we developed generalized linear mixed models with plot-level burn severity, year sampled, watershed average stand age, average DBH of dominant riparian trees, and selected interactions as fixed effects (burn severity × year, burn severity × age, burn severity × DBH, and age × DBH), and Site or Transect within a Site as random effect(s). We specified a binomial or quasibinomial distribution for canopy cover, overstory mortality, shrub cover and forb cover. For shrub richness, we specified a Poisson distribution, and forb richness, we specified a Gamma distribution. For each model, we assessed model fit by examining the standardized residuals against the fitted values. We evaluated the significance of terms using an Analysis of Deviance and estimated least squared means using a significance level of 0.1. To examine the association between species patterns and fire severity in the shrub and forb layers, we performed an indicator species analysis using the multipatt function in R, specifying the IndVal index and 999 permutations 18 . We subset the data by mean watershed stand age (Old or Young) and grouped by mean plot-level fire severity (None (0-0.05), Mid (0.5-1), or High (1-1.5). We calculated an Indicator Value (IV) for each significant species (ISA A × ISA B × 100) and considered any species with an IV > 25 to be an important indicator of a group, sensu Dufrêne and Legendre 19 . RESULTS Vast stream networks and their riparian zones burned in the three fires included in our study (Riverside, Beachie Creek, and Holiday Farm), where 2,044 km 2 area burned. This included 4,020 km of stream length and their associated riparian areas; over 50% of which resulted in moderate soil burn severity and < 5% at high soil burn severity. Riparian overstory cover was influenced by fire severity and exhibited some delay in overstory mortality. Canopy cover was negatively related to year since fire ( p < 0.001) and burn severity × year since fire ( p < 0.01), with canopy cover decreasing with increasing burn severity and decreasing each year since fire (Fig. 2 A). At no/low and high fire severity, canopy cover was consistently very high or very low each year, but at mid-level burn severity, canopy cover greatly varied by year. Conversely, overstory mortality increased with increasing burn severity ( p < 0.001), year since fire ( p < 0.001), and by burn severity × year since fire ( p = 0.01); mortality increased 2–3 years after fire compared to the first year, especially at sites with mid-level burn severity (Fig. 2 B). Burn severity and years since fire had heterogenous effects on overstory mortality across tree species: e.g., Thuja plicata had higher mortality immediately after fire, even in stands with lower burn severity, while Tsuga heterophylla and especially Alnus rubra showed higher survival the first year after fire but had high mortality two- and three-years post-fire (Fig. 3 ). Fire effects were more variable on understory than overstory vegetation. Shrub cover was affected by burn severity ( p = 0.001) and the interaction of burn severity × year sampled ( p < 0.001). In general, shrub cover decreased with increasing burn severity but showed some increases in cover by year three (Fig. 4 A). Shrub species richness also decreased with increasing burn severity ( p < 0.001) and burn severity × year since fire ( p < 0.001) with similar increases in species richness three years after fire (Fig. 4 B). Forb cover and species richness also varied by burn severity × year since fire ( p < 0.001 for both). There appears to be some recovery in forb cover two and three years after fire (Fig. 5 A), but the effect of year since fire for forb species richness is less clear (Fig. 5 B). For both shrub and forb species, indicators of fire were pioneer or early seral species, while species indicative of no fire tended to be mid- to late seral species (Table 1 ). In addition, most significant indicator species were native; the only significant exotic indicator species was a forb species indicative of high severity fire at older sites ( Lactuca serriola). Table 1 Indicator Species Analysis results for shrub and forb species across watershed ages and plot-level burn severity groupings. Age = watershed age, Old (> 85 year) or Young, ( 1); ISA A = relative abundance; ISA B = relative frequency; IV (Indicator Value) = ISA A × ISA B × 100. Nativity and Duration classifications are from USDA PLANTS Database 44 . Seral stage was determined from multiple sources 45 – 48 . All important indicator species (IV > 25) are listed below, sensu Dufrêne and Legendre 19 . Graminoid species comprised multiple species of grasses, sedges, and rushes; since the nativity, duration, and seral stage could not be narrowed down to one type, they were left blank. Age Fire Severity Species ISA A ISA B p -value IV Growth Form Nativity Duration Seral Stage Shrub Species Old High Rubus leucodermis 0.72 0.33 0.00 23.87 woody native perennial pioneer Old Mid + None Rubus spectabilis 1.00 0.28 0.01 27.43 woody native perennial early Old None Acer circinatum 0.74 0.78 0.00 58.00 woody native perennial mid Old None Tsuga heterophylla 0.97 0.55 0.00 53.09 woody native perennial late Old None Thuja plicata 0.92 0.48 0.00 44.32 woody native perennial late Old None Rhododendron macrophyllum 1.00 0.42 0.00 41.67 woody native perennial early Old None Vaccinium ovatum 1.00 0.37 0.00 36.67 woody native perennial late Old None Vaccinium parvifolium 0.98 0.33 0.00 32.55 woody native perennial late Young High + None Rubus spectabilis 0.91 0.29 0.01 26.80 woody native perennial early Young None Acer circinatum 0.59 0.80 0.00 47.17 woody native perennial mid Young None Oemleria cerasiformis 0.70 0.57 0.00 40.27 woody native perennial mid Young None Vaccinium parvifolium 0.98 0.38 0.00 36.72 woody native perennial late Young None Corylus cornuta 0.47 0.57 0.01 26.91 woody native perennial mid Young None Tsuga heterophylla 1.00 0.27 0.00 26.79 woody native perennial late Forb Species Old High Lactuca serriola 0.91 0.44 0.00 39.77 forb exotic annual early Old High + Mid Claytonia sibirica 0.80 0.33 0.00 26.79 forb native perennial early Old High + Mid Epilobium angistifolium 1.00 0.26 0.00 25.87 forb native perennial pioneer Old High + Mid Graminoid species 0.80 0.32 0.00 25.49 forb Young High Epilobium angistifolium 0.85 0.50 0.00 42.16 forb native perennial pioneer Young High + Mid Epilobium ciliatum 0.98 0.28 0.00 26.90 forb native perennial pioneer Young None Oxalis oregana 0.71 0.59 0.00 41.82 forb native perennial late Young None Polystichum munitum 0.73 0.49 0.00 35.85 fern native perennial late DISCUSSION Changes in riparian cover across vegetation layers Globally, megafires (> 40,500 ha) have been increasing, creating greater exposure for riparian ecosystems. These three megafires resulted in a range of fire severities at a patch scale that contributed significant initial overstory mortality throughout entire watersheds, including riparian forests where canopy cover continued to decrease each year for the first three years after fire. While soil burn severity in adjacent riparian areas were generally less severely burned than much of the corresponding upland, we found riparian overstory mortality was extensive – exceeding 73% within three years post-fire in mostly burned and completely burned watersheds. Although initial overstory mortality in riparian areas in our study was lower for Alnus rubra than Thuja plicata 15 , our analyses revealed overstory mortality was dynamic in the first three years post-fire, with evidence of both delayed mortality and rapid re-sprouting. Mortality of deciduous species was particularly dynamic with Alnus rubra experiencing delayed mortality a nd Acer macrophyllum , which can resprout after fire, initially showing delayed mortality from year one to two and then reviving again by year three. Species that re-sprout after apparent top kill can survive even high severity fire 20 and, in our study, Acer macrophyllum apparent mortality reversed by over half in moderately burned sites between years two and three post-fire. Both Tsuga heterophylla and Alnus rubra experienced delayed mortality two and three years after fire, with the greatest change in delayed mortality observed in more moderately burned sites for both species, although Alnus rubra also experienced substantial delayed mortality in the most severely burned sites. Alnus rubra mortality increased from 66% in year one to 100% in years two and three in the most severely burned sites. At moderately burned sites, Alnus rubra mortality more than tripled from 23% in year one to 82% in year two and 89% in year three. In the most severely burned sites, Tsuga heterophylla already experienced high mortality (95%) in year one, which increased to 100% in years two and three. In moderately burned sites, Tsuga heterophylla mortality increased 30% from 56% in year one to 88% in years two and three. The magnitude of delayed mortality observed with these riparian species exceeded estimated delayed mortality in the literature, likely because much of that literature focuses on conifer mortality and reflects a lack of information in riparian areas where initial survival may be greater for some riparian species. Using a remote sensing analysis across the western U.S., Busby, et al. 21 estimated delayed mortality of conifers reached 5–25% at the scale of a fire perimeter five years after fire. This is similar to the 30% increase in mortality in moderately burned sites of the only conifer (Tsuga heterophylla) that experienced delayed mortality in our study. Others found that most mortality occurred within two years of fire, although only conifers were considered in their study 22 . Other studies of riparian areas found that 94% of Alnus rubra and Salix spp. (willow) trees were killed within three years by a wildfire in a Chapparral landscape in southern California, USA 23 and canopy cover was reduced from 48–63% post-fire compared to pre-fire 24 . Pre-fire drought can increase tree mortality susceptibility to fire 25 , 26 and post-fire drought may compound impacts 20 , 27 . Water years 2019–2021 (Oct 1 to Sep 30) were drought years for northwest Oregon (includes Riverside and Beachie Creek fires) and 2018, 2020, and 2021 in southwest Oregon (includes Holiday Farm fire) based on the PRISM Standardized Precipitation Index 28 . Thus, drought conditions before, during, and after these wildfires may have contributed to initial and delayed fire-induced mortality. Fire-induced injuries that lead to cambium necrosis and limit hydraulic conductivity of the xylem contribute to delayed mortality 20 , 29 , likely limiting ability to survive future stressful conditions in addition to fire, such as flooding, winds, ice storms, and forest pests. Forest structure, including tree density, may influence mortality after fire, particularly as it affects fuels, moisture content of vegetation, and interacts with fire behavior 20 . Pre-fire watershed stand age also encompasses differences in forest ownership and management practices that lead to a divergence in forest stand structure across our study sites. However, we did not find overstory mortality response to differ by pre-fire stand age; rather, only fire severity explained mortality, indicating riparian tree mortality in these fires was similar regardless of pre-fire stand conditions. Riparian vegetation response to fire was dynamic across vegetation layers with forb cover recovering most rapidly by the second year after fire across all burn severities, and forb richness temporarily increased in two years and but did not remain elevated three years after fire. Shrub recovery was delayed to the third-year post-fire when both shrub cover and richness increased three years after fire across all burn severities, with substantial increases in richness in more severely burned sites. Simultaneous with forb recovery was the delayed mortality of Alnus rubra and Tsuga heterophylla [primarily two years after wildfire], and continued reductions in canopy cover each year, which may have contributed to the timing and success of forb and shrub recovery by opening the canopy. We observed a greater decline in canopy cover through time for moderately burned sites (44%) than in severely burned sites (25%). Moderately burned sites also exhibited greater magnitude shrub cover increase (3X) relative to most severely burned sites. In contrast, the most severely burned sites had the greatest magnitude of increases in forb cover. Severity of fire, and time since fire, are important factors that drive complex responses in various layers of riparian vegetation. Therefore, continued monitoring of recovery after wildfire in these riparian areas is critical not only to understand terrestrial ecosystems, but also for aquatic ecosystems that rely on vegetation for shade, organic matter and nutrient inputs, and bank stability. Simultaneous monitoring of canopy cover from measurements taken in these streams revealed similar declines in overstory canopy cover each year since the fire, with high overstory mortality contributing to higher stream temperature maxima 15 , 16 . In-stream monitoring indicated that understory re-growth, while extensive, did not effectively shade or limit thermal increases in the first three years post-fire. Despite these elevated summer stream temperatures, fish biomass and densities were elevated in exposed and severely burned watersheds, presumably due to greater basal resource availability, while amphibian biomass and densities were unaffected 16 . Dead standing trees, their root structures, and roots of understory shrubs and forbs, may provide important functions for stream and riparian ecosystems such as bank stability and microhabitats 23 . Fallen overstory trees can also contribute to riparian function as coarse wood on forest floor or as large wood in streams 15 , 30 . Indicator species Studies from other land uses have revealed anthropogenically disturbed riparian zones may represent novel ecosystems, hosting different species and combinations of species than less disturbed systems 31 . Although we are unaware of prior documentation of this effect in forests, we expected forest management-related disturbances either pre-fire or post-fire (including a greater proportion of recently harvested stands, salvage, higher road density and stream crossings) to have been of greater magnitude or frequency in the watersheds with younger pre-fire stand age. In our study, older mean watershed stand ages generally indicated less anthropogenic disturbance and often included a component of old-growth. Importantly, legacy effects of prior historical harvest activities likely affected most/all sites (i.e., splash dams and log drives were once prevalent throughout much of western Oregon streams) 32 . Novel riparian zones may be more likely to have invasive plant species in their seed banks 33 , 34 or their unique combinations of species may make them more flammable 11 . Examining differences in the vegetation community composition after fire allows us to explore whether novel species combinations occur in riparian systems that had more frequent or greater magnitude anthropogenic disturbance before also being confronted with fire. We found distinct indicator species in watersheds draining older stands versus younger stands, which have experienced more recent anthropogenic disturbance. We expected to find exotic indicator species in younger sites, but only documented Lactuca serriola , an exotic forb species characteristic of fire in older sites. Anthropogenic disturbance gradients in forested riparian areas did not contribute to novel riparian communities (i.e., there were no invasives in more disturbed sites), but did have unique native species indicators. We found unique combinations of species in younger forested watersheds as four unique indicator species were characteristic of younger mean watershed stand ages, with only two indicator species shared by both young and old unburned riparian areas ( Acer circinatum and Tsuga heterophylla ). We also found four unique indicator species that were characteristic of sites draining older mean watershed stand ages. In burned sites, Rubus spectabilis was an indicator of both young and old sites, and no other indicator species were found in young sites. This indicates that while a unique combination of mid- to late-seral species present in younger unburned sites can be used to identify riparian areas draining younger stands, in our study, only presence of Rubus leucodermis may differentiate an older burned site from younger burned sites. Only two species of shrubs were indicators of fire: Rubus leucodermis in younger mean watershed stand ages, and Rubus spectabilis in both younger and older stand age watersheds. In a prior study of clearcut followed by broadcast burning in northern Idaho, USA, Rubus leucodermis occurred more frequently in less severely burned sites than high burn severity sites and also varied by time since fire, maintaining cover in the first five years and then reduced 15 years post-fire 35 . Both of these native shrub species are rhizomatous, and may have established quickly post-fire via dormant seeds 36 or sprouted from belowground perennating roots. Implications & Conclusions Our findings indicate understory vegetation initiated recovery within three years after fire. Although individual species may re-establish quickly after fire, recovery of vegetation structure and composition takes more time 37 . In the absence of overstory canopy, understory vegetation layers provided little shade to streams even after three years post-fire, but this will likely change in coming years. Early seral or pioneer species were indicative of fire effects which align with previous research showing disturbance-associated species to be more common or abundant after fire 38 . Other studies have shown fire in riparian areas reduced both total and native species richness 39 , but our data do not reflect that pattern during the first three years post-fire. Longer term study is essential to fully understand recovery of vegetation in these riparian forest stands. Our results demonstrate that megafires can significantly alter riparian zones, even in relatively large 4th order streams. While the three fires included in our study were extensive, these three fires represent only a fraction of area burned in Oregon’s 2020 wildfires, which encompassed 4,900 km 2 across the state 40 , 41 . Furthermore, the three megafires in our study burned > 2000X the stream length of what had burned over a 30-year period (1984–2014) in this region. 42 Similarly, megafires in Australia burned 126,000 km 2 , in a brief 7 month period in 2019–2020, affecting 81,304 km of rivers and their riparian areas, and 29% of that river’s riparian network burned at extreme or high burn severity 31 . Although riparian areas comprise a small proportion of an area burned, the extent of riparian vegetation burned, and therefore the fire return intervals of the riparian areas themselves, are extremely varied between different ecoregions 43 . Globally riparian zones are increasingly exposed to fire across broad scales, and understanding their recovery is important for water quality, nutrient cycling, and providing habitat structure for in-stream and riparian associated wildlife 42 . Declarations Author Contribution All authors (L.S., J.V., and A.C.) contributed to writing the manuscript, while L.S. completed the analyses and most figures/tables, except for Figure 1, which A.C. contributed. All authors reviewed the manuscript. Acknowledgement We thank M. Barnett, R. Boucher, A. Clements, E. Cruz, A. Hammond, A Lamet, B. Hobscheid, G. Demorest, A. Owens, M. Thomas, and especially G. Broyles and L. Koerner for assisting with field data collection. Bureau of Land Management, Campbell Global, LLC, Fruit Growers Supply, Giustina Resources, Port Blakely, Rayonier, State of Oregon, United States Forest Service, and Weyerhaeuser kindly allowed land access and provided assistance. Statistical support was provided by J. 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Fire, floods and woody debris: Interactions between biotic and geomorphic processes. Geomorphology 116 , 297-304 (2010). Rehn, A. C. The effects of wildfire on benthic macroinvertebrates in southern California. (San Diego, CA, 2010). van Mantgem, P. J. et al. Climatic stress increases forest fire severity across the western U nited S tates. Ecol. Lett. 16 , 1151-1156 (2013). Van Mantgem, P. J., Falk, D. A., Williams, E. C., Das, A. J. & Stephenson, N. L. Pre‐fire drought and competition mediate post‐fire conifer mortality in western US National Parks. Ecol. Appl. 28 , 1730-1739 (2018). Furniss, T. J., Das, A. J., van Mantgem, P. J., Stephenson, N. L. & Lutz, J. A. Crowding, climate, and the case for social distancing among trees. Ecol. Appl. 32 , e2507 (2022). O'Neill, L. W., Koszuta, M., Siler, N. & Fleishman, E. Historical and Projected Future Drought in Oregon . (Oregon State University, 2023). Bär, A., Michaletz, S. T. & Mayr, S. Fire effects on tree physiology. New Phytol. 223 , 1728-1741 (2019). Pettit, N. E. & Naiman, R. J. Fire in the riparian zone: characteristics and ecological consequences. Ecosystems 10 , 673-687 (2007). Fryirs, K., Zhang, N., Duxbury, E. & Ralph, T. Rivers up in smoke: impacts of Australia’s 2019–2020 megafires on riparian systems. Int. J. Wildland Fire 31 , 720-727 (2022). Steel, Z. L., Safford, H. D. & Viers, J. H. The fire frequency‐severity relationship and the legacy of fire suppression in California forests. Ecosphere 6 , 1-23 (2015). Moffatt, S. F. & Mclachlan, S. M. Effects of land use disturbance on seed banks of riparian forests in southern Manitoba. Ecoscience 10 , 361-369 (2003). O'Donnell, J., Fryirs, K. A. & Leishman, M. R. Seed banks as a source of vegetation regeneration to support the recovery of degraded rivers: a comparison of river reaches of varying condition. Sci. Total Environ. 542 , 591-602 (2016). Morgan, P. & Neuenschwander, L. F. Shrub response to high and low severity burns following clearcutting in northern Idaho. Western Journal of Applied Forestry 3 , 5-9 (1988). Morgan, P. & Neuenschwander, L. Seed-bank contributions to regeneration of shrub species after clear-cutting and burning. Canadian Journal of Botany 66 , 169-172 (1988). DeBano, L. F. & Neary, D. G. Effects of fire on riparian systems. UNITED STATES DEPARTMENT OF AGRICULTURE FOREST SERVICE GENERAL TECHNICAL REPORT RM , 69-76 (1996). Donato, D. C., Fontaine, J. B., Robinson, W. D., Kauffman, J. B. & Law, B. E. Vegetation response to a short interval between high-severity wildfires in a mixed-evergreen forest. J. Ecol. 97 , 142-154 (2009). Hankins, D. L. The effects of indigenous prescribed fire on riparian vegetation in central California. Ecological Processes 2 , 1-9 (2013). Mass, C. F., Ovens, D., Conrick, R. & Saltenberger, J. The september 2020 wildfires over the Pacific Northwest. Weather and Forecasting 36 , 1843-1865 (2021). Council, O. W. E. R. Recovering & Rebuilding from Oregon’s 2020 Wildfires. Governor, O., Ed , 32 (2021). Ball, G., Regier, P., González-Pinzón, R., Reale, J. & Van Horn, D. Wildfires increasingly impact western US fluvial networks. Nature Communications 12 , 2484, doi:10.1038/s41467-021-22747-3 (2021). Bendix, J. & Commons, M. G. Distribution and frequency of wildfire in California riparian ecosystems. Environmental Research Letters 12 , 075008 (2017). USDA, N. The PLANTS Database ( http://plants.usda.gov) , 2017). Halpern, C. B. Early successional patterns of forest species: interactions of life history traits and disturbance. Ecology 70 , 704-720, doi:https://doi.org/10.2307/1940221 (1989). Cook, J. E. & Halpern, C. B. Vegetation changes in blown-down and scorched forests 10–26 years after the eruption of Mount St. Helens, Washington, USA. Plant Ecol. 219 , 957-972 (2018). Priebe, J. E. Silvicultural treatment impacts on understory trees and 20-year understory vegetation dynamics in mature Douglas-fir forests. (2016). Hitchcock, C. L., Cronquist, A., Ownbey, M. & Thompson, J. Vascular plants of the Pacific Northwest . (University of Washington Press, 1969). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 16 Oct, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 14 Jul, 2025 Reviews received at journal 11 Jul, 2025 Reviewers agreed at journal 02 Jul, 2025 Reviews received at journal 20 Jun, 2025 Reviewers agreed at journal 06 Jun, 2025 Reviewers invited by journal 30 Mar, 2025 Editor assigned by journal 29 Mar, 2025 Editor invited by journal 19 Mar, 2025 Submission checks completed at journal 18 Mar, 2025 First submitted to journal 11 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Six","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEUlEQVRIiWNgGAWjYBACPijNw8DeAGYkENTCBtfCc4BELQwMEgnEamE/Y/bhB0OdjMHNN4aPeSru5fG39xh/+LiHQZ5f7AB2LTw5xjN7GA7zSM7OMTbmOVNcLHHmjJnkjGcMhjNnY7eRjSHHGOiRAzz80rnbpHnbEhIbbuSYMQM9lmBwG4cW/jfGjH8Y6njYJM9u/837LyFx/v03xp//4NMikWPMzMPAzMMvwbuNmbchIXHDDR4DaQa8Wp4VM8sYAP3Sk/9Zcs6xhMSNZ9LKJHsOSOD0Cz9/8mbGNxV19gbHjyV+eFOTkDjv+OHNH34csJHnl8auBQIMIBQTD0JIAo9yJMD4gzh1o2AUjIJRMMIAAIjiVunbuN/IAAAAAElFTkSuQmCC","orcid":"","institution":"Weyerhaeuser","correspondingAuthor":true,"prefix":"","firstName":"Laura","middleName":"J.","lastName":"Six","suffix":""},{"id":437480740,"identity":"db804bbb-ecec-4335-bb87-69780dc1ee6f","order_by":1,"name":"Jake Verschuyl","email":"","orcid":"","institution":"National Council for Air and Stream Improvement, Inc.","correspondingAuthor":false,"prefix":"","firstName":"Jake","middleName":"","lastName":"Verschuyl","suffix":""},{"id":437480741,"identity":"0eca6379-e184-48ff-ae31-ad661e30e95e","order_by":2,"name":"Ashley A. Coble","email":"","orcid":"","institution":"National Council for Air and Stream Improvement","correspondingAuthor":false,"prefix":"","firstName":"Ashley","middleName":"A.","lastName":"Coble","suffix":""}],"badges":[],"createdAt":"2025-03-11 16:38:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6205148/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6205148/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-20242-z","type":"published","date":"2025-10-16T15:58:20+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80883783,"identity":"4369a40e-8cac-4bf6-a658-057b8d4e9514","added_by":"auto","created_at":"2025-04-18 08:22:04","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":561093,"visible":true,"origin":"","legend":"\u003cp\u003eStudy sites (watersheds denoted in black polygons) across western Oregon, USA Cascade Mountains, within and near the Riverside, Beachie Creek, and Holiday Farm fires of 2020.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6205148/v1/769b4f4db90ebbd901f1a8a6.jpeg"},{"id":80883779,"identity":"a885b939-95c7-41a7-bc7b-c311b6900ab8","added_by":"auto","created_at":"2025-04-18 08:22:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":16486,"visible":true,"origin":"","legend":"\u003cp\u003eCanopy cover (A) and overstory mortality (B) by plot-level burn severity and year sampled. Lines were calculated from least squared means at fire severity intervals of 0.005, with shading denoting 90% confidence intervals.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6205148/v1/8f192aca34c7a34feee8a289.png"},{"id":80883782,"identity":"4593e756-3454-4b75-8088-87fc0c7c45ac","added_by":"auto","created_at":"2025-04-18 08:22:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":15490,"visible":true,"origin":"","legend":"\u003cp\u003eOverstory mortality by plot-level burn severity and year. Lines were calculated from least squared means of proportional mortality (number of dead trees / total number of trees) at fire severity intervals of 0.005, with shading denoting 90% confidence intervals.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6205148/v1/7c82456d37fcbb28394d32e8.png"},{"id":80883787,"identity":"c2889854-5d76-47e4-ad07-cf529b99fa8f","added_by":"auto","created_at":"2025-04-18 08:22:04","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":16836,"visible":true,"origin":"","legend":"\u003cp\u003eShrub cover (A) and richness (B) by plot-level burn severity and year sampled. Lines were calculated from least squared means at fire severity intervals of 0.005, with shading denoting 90% confidence intervals.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6205148/v1/d03ed4e55dcac35273878419.png"},{"id":80883794,"identity":"1de2460b-579e-4ec6-b648-5adaa944e7fa","added_by":"auto","created_at":"2025-04-18 08:22:07","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":13661,"visible":true,"origin":"","legend":"\u003cp\u003eForb cover (A) and richness (B) by plot-level burn severity and year sampled. Lines were calculated from least squared means at fire severity intervals of 0.005, with shading denoting 90% confidence intervals. Forb cover could exceed 100% because of multiple layers of vegetation in the forb layer.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6205148/v1/a347644934053339fd543226.png"},{"id":93956038,"identity":"61204350-0d3a-4c1c-b93f-e4cdcfe4a2b1","added_by":"auto","created_at":"2025-10-20 16:09:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1433452,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6205148/v1/a8fd65ed-6bc7-449b-9a2f-f731c17fbd28.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Megafires in Oregon: Riparian vegetation layers differ three years after mixed severity fire","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eRiparian areas are often characterized by high plant diversity and structural complexity but can be affected by forest management\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Although the width of forested buffers and specific operating restrictions differ in managed forests across the globe\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, the broader goal is often to insulate aquatic ecosystems from upslope disturbance. The efficacy of riparian buffers in protecting aquatic ecosystems from disturbance likely differs between anthropogenic and natural disturbances, and unique responses may occur when multiple disturbances occur in sequence. Natural disturbance (e.g., wind, fire, flood) can disrupt the regulating efficacy of riparian vegetation. However, riparian vegetation can also help regulate fire intensity or extent due to higher fuel moisture content and relative humidity\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWhile ecosystem response after fire has been examined, the response of riparian areas to fire, specifically that of understory riparian vegetation, has not been well-studied. Understory vegetation in riparian areas may be less affected by fire than adjacent uplands, even with similar overstory fire severity\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Fire may also be less frequent in riparian areas than in nearby upland forest, yet little is known about return intervals in riparian areas\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. In the western US, greater water availability in riparian areas often supports deciduous trees and shrubs with greater levels of stem and foliar moisture content, particularly in dry periods\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, although larger streams tend to have more hardwoods than smaller streams that support more conifers\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Therefore, riparian areas may act as refugia for fire-sensitive species typically found in upland forests\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. If most of the riparian buffer is wet with a deep soil organic layer, understory community composition may be minimally affected by fire compared to unburned stands\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Even if affected by fire, riparian plant species may be uniquely resilient to disturbances given their adaptations to seasonal flooding, seasonal drought, and fire \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe speed and nature of riparian vegetation regrowth following disturbance are important because they affect recovery of stream ecosystem characteristics, such as stream temperature, bank stability, and sediment delivery. Without an intact overstory, riparian understory vegetation may serve a critical function in the post-fire recovery of the aquatic ecosystem by providing shade to the stream, intercepting precipitation and limiting overland runoff, and stabilizing banks with root development. In Mediterranean ecosystems, riparian zones can achieve rapid re-growth, particularly when riparian zones may have greater moisture content and nutrient availability\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, or when disturbance-adapted species, with traits such as rapid sprouting or suckering, can quickly re-colonize\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn September 2020, widespread forest fires affected a mosaic of federal and private managed forests in the western Oregon Cascades, USA. Five mega-fires burned approximately 3440 km\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, with more than 80 percent of that area burning in the first 48 hours of the wind-driven event\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. These fires burned at relatively high severity, affecting numerous forested riparian areas along headwaters streams\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. To better understand how these fires affected aquatic ecosystem processes, we applied an established, large-scale replicated study design, used to quantify environmental responses to variation in watershed forest composition, to examine site and vegetation characteristics following mixed severity fire within riparian management zones adjacent to small perennial streams. Our objectives were to determine whether riparian vegetation recovery after severe wildfires varied with burn severity, years since fire, pre-fire watershed age, or riparian stand structure. We explored these questions for each layer of riparian vegetation including 1) overstory 2) shrub and 3) forb layers using mortality, cover, and species richness as response variables. We hypothesized that burn severity would affect mortality and cover for all vegetation layers with delayed overstory mortality contributing to reduced canopy cover with time since fire, and rapid re-growth and establishment for shrub and forb layers contributing to increasing understory cover and species richness with time since fire.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eOur study was designed to compare stream and riparian responses to wildfires in the western Oregon Cascades, USA\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. This area has a maritime climate regime, with mild wet winters and warm, dry summers, resulting in highly productive tree species, like \u003cem\u003ePseudotsuga menziesii\u003c/em\u003e, and a long history of timber production by various forest industry landowners\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Soils in the area are moderately deep, well drained loams and supports vegetation within the \u003cem\u003eTsuga heterophylla\u003c/em\u003e forest zone\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. For our study, we used a stratified random sampling design with mean watershed pre-fire stand age (based on 2017 data) and watershed fire extent for 25, 4th order watersheds within 6 km of the Beachie Creek, Riverside, and Holiday Farm fire boundaries (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe considered watershed fire extent as one of four categories: unburned (0%), minority (\u0026lt;\u0026thinsp;50%) of watershed burned, majority (\u0026gt;\u0026thinsp;50% and \u0026lt;\u0026thinsp;99%) of watershed burned, and complete (\u0026gt;\u0026thinsp;99%) watershed burned. Mean watershed pre-fire stand age was split into \u0026lt;\u0026thinsp;85y or \u0026gt;\u0026thinsp;85y, based on the distribution of mean watershed stand age from all 4th order watersheds within 6 km of these fires. From the available 4th -order watersheds, we randomly selected three streams for each of the eight categories. For the vegetation sampling, we sampled an additional five streams located further up in the stream network, including two 3rd order and three 2nd order streams, to capture more severely burned riparian areas and monitor their recovery over time. This was done because riparian responses were expected to differ with watershed size and geomorphology of hydrologic features that also control riparian species composition\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. To estimate the length of stream and associated riparian areas burned in these three fires, we clipped the National Hydrography Dataset plus version 2 (NHDPlus V2) stream layer to the fire boundaries for Beachie Creek, Riverside, and Holiday Farm and summed total length of stream. We obtained soil burn severity (SBS) from Burned Area Emergency Response (BAER) database, and evaluated riparian areas as within 30.48 m of stream.\u003c/p\u003e \u003cp\u003eWe collected data on overstory, shrub, and forb layer during summers 2021\u0026ndash;2023 (after 2020 wildfires) at 30 different subbasin watersheds stratified across gradients of fire severity and prior forest management intensity. Each study site was comprised of a 100 m stream reach located at the downstream end of a 4th order stream basin. We placed four transects at 20 m intervals on alternating sides of each stream, extending 50 m perpendicular to each stream. We collected data on overstory condition and species composition in 10 \u0026times; 20 m (200 m\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e plots), placed at 5\u0026ndash;25 m along each transect. Using a line-intercept method along each transect, we recorded cover of each shrub species. For forb layer species, we placed 1 m\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e quadrats every 5 m along each transect and recorded cover class of each species: 1\u0026thinsp;=\u0026thinsp;0\u0026ndash;1%, 2\u0026thinsp;=\u0026thinsp;1\u0026ndash;5%, 3\u0026thinsp;=\u0026thinsp;5\u0026ndash;25%, 4\u0026thinsp;=\u0026thinsp;25\u0026ndash;50%, 5\u0026thinsp;=\u0026thinsp;50\u0026ndash;75%, 6\u0026thinsp;=\u0026thinsp;75\u0026ndash;95%, or 7\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;95% cover. We sampled canopy density at each quadrat using a spherical densiometer by calculating an average of 4 readings at each quadrat.\u003c/p\u003e \u003cp\u003eAs a measure of burn severity, we used a qualitative scale (0\u0026ndash;3) to quantify evidence of fire/burn at each quadrat (e.g., 0\u0026thinsp;=\u0026thinsp;no evidence of fire, 3\u0026thinsp;=\u0026thinsp;most of plot is covered by charred organic matter or other signs of fire) during the first sample year. We calculated mean burn severity for each site by averaging the plot-level numeric assessments of burn severity.\u003c/p\u003e \u003cp\u003eTo include a measure of riparian stand structure in our statistical models, we defined dominant canopy trees as those representing the largest 50 percent of total plot basal area (m\u003csup\u003e2\u003c/sup\u003e/ha), and calculated the mean diameter at breast height (DBH (cm)) of those dominant trees for each site.\u003c/p\u003e \u003cp\u003eWe averaged canopy cover measurements for each quadrat and then summarized these to the site level for each sample year. We calculated overstory mortality annually as the proportional mortality (number of dead trees divided by number of both live and dead trees) by tree plot, and then calculated mean mortality across the four tree plots at each site. We summarized shrub cover as the total distance (m) along each transect covered by each unique species. We then calculated shrub richness as the count of unique species recorded per transect each sample year, and then calculated a mean across the four transects for each site. We summarized forb cover and richness by species each sample year at the quadrat level and then calculated means to the site level.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analyses\u003c/h2\u003e \u003cp\u003eTo assess whether burn severity influenced mortality and cover for all vegetation layers, we developed generalized linear mixed models with plot-level burn severity, year sampled, watershed average stand age, average DBH of dominant riparian trees, and selected interactions as fixed effects (burn severity \u0026times; year, burn severity \u0026times; age, burn severity \u0026times; DBH, and age \u0026times; DBH), and Site or Transect within a Site as random effect(s). We specified a binomial or quasibinomial distribution for canopy cover, overstory mortality, shrub cover and forb cover. For shrub richness, we specified a Poisson distribution, and forb richness, we specified a Gamma distribution. For each model, we assessed model fit by examining the standardized residuals against the fitted values. We evaluated the significance of terms using an Analysis of Deviance and estimated least squared means using a significance level of 0.1.\u003c/p\u003e \u003cp\u003eTo examine the association between species patterns and fire severity in the shrub and forb layers, we performed an indicator species analysis using the multipatt function in R, specifying the IndVal index and 999 permutations\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. We subset the data by mean watershed stand age (Old or Young) and grouped by mean plot-level fire severity (None (0-0.05), Mid (0.5-1), or High (1-1.5). We calculated an Indicator Value (IV) for each significant species (ISA A \u0026times; ISA B \u0026times; 100) and considered any species with an IV\u0026thinsp;\u0026gt;\u0026thinsp;25 to be an important indicator of a group, \u003cem\u003esensu\u003c/em\u003e Dufr\u0026ecirc;ne and Legendre \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eVast stream networks and their riparian zones burned in the three fires included in our study (Riverside, Beachie Creek, and Holiday Farm), where 2,044 km\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e area burned. This included 4,020 km of stream length and their associated riparian areas; over 50% of which resulted in moderate soil burn severity and \u0026lt;\u0026thinsp;5% at high soil burn severity.\u003c/p\u003e \u003cp\u003eRiparian overstory cover was influenced by fire severity and exhibited some delay in overstory mortality. Canopy cover was negatively related to year since fire (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.001) and burn severity \u0026times; year since fire (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.01), with canopy cover decreasing with increasing burn severity and decreasing each year since fire (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). At no/low and high fire severity, canopy cover was consistently very high or very low each year, but at mid-level burn severity, canopy cover greatly varied by year. Conversely, overstory mortality increased with increasing burn severity (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), year since fire (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.001), and by burn severity \u0026times; year since fire (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01); mortality increased 2\u0026ndash;3 years after fire compared to the first year, especially at sites with mid-level burn severity (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Burn severity and years since fire had heterogenous effects on overstory mortality across tree species: e.g., \u003cem\u003eThuja plicata\u003c/em\u003e had higher mortality immediately after fire, even in stands with lower burn severity, while \u003cem\u003eTsuga heterophylla\u003c/em\u003e and especially \u003cem\u003eAlnus rubra\u003c/em\u003e showed higher survival the first year after fire but had high mortality two- and three-years post-fire (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFire effects were more variable on understory than overstory vegetation. Shrub cover was affected by burn severity (\u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.001) and the interaction of burn severity \u0026times; year sampled (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In general, shrub cover decreased with increasing burn severity but showed some increases in cover by year three (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Shrub species richness also decreased with increasing burn severity (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and burn severity \u0026times; year since fire (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) with similar increases in species richness three years after fire (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Forb cover and species richness also varied by burn severity \u0026times; year since fire (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for both). There appears to be some recovery in forb cover two and three years after fire (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA), but the effect of year since fire for forb species richness is less clear (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor both shrub and forb species, indicators of fire were pioneer or early seral species, while species indicative of no fire tended to be mid- to late seral species (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In addition, most significant indicator species were native; the only significant exotic indicator species was a forb species indicative of high severity fire at older sites (\u003cem\u003eLactuca serriola).\u003c/em\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIndicator Species Analysis results for shrub and forb species across watershed ages and plot-level burn severity groupings. Age\u0026thinsp;=\u0026thinsp;watershed age, Old (\u0026gt;\u0026thinsp;85\u0026nbsp;year) or Young, (\u0026lt;\u0026thinsp;85\u0026nbsp;year); Fire Severity\u0026thinsp;=\u0026thinsp;none (0.-0.5), mid (1-1.5), or high (\u0026gt;\u0026thinsp;1); ISA A\u0026thinsp;=\u0026thinsp;relative abundance; ISA B\u0026thinsp;=\u0026thinsp;relative frequency; IV (Indicator Value)\u0026thinsp;=\u0026thinsp;ISA A \u0026times; ISA B \u0026times; 100. Nativity and Duration classifications are from USDA PLANTS Database \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. Seral stage was determined from multiple sources \u003csup\u003e\u003cspan additionalcitationids=\"CR46 CR47\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. All important indicator species (IV\u0026thinsp;\u0026gt;\u0026thinsp;25) are listed below, sensu Dufr\u0026ecirc;ne and Legendre \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Graminoid species comprised multiple species of grasses, sedges, and rushes; since the nativity, duration, and seral stage could not be narrowed down to one type, they were left blank.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFire Severity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eISA A\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eISA B\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eGrowth Form\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNativity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eDuration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eSeral Stage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003eShrub Species\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOld\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eRubus leucodermis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ewoody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eperennial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003epioneer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOld\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMid\u0026thinsp;+\u0026thinsp;None\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eRubus spectabilis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e27.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ewoody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eperennial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eearly\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOld\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eAcer circinatum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e58.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ewoody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eperennial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003emid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOld\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eTsuga heterophylla\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e53.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ewoody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eperennial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003elate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOld\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eThuja plicata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e44.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ewoody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eperennial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003elate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOld\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eRhododendron macrophyllum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ewoody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eperennial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eearly\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOld\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eVaccinium ovatum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e36.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ewoody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eperennial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003elate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOld\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eVaccinium parvifolium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ewoody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eperennial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003elate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYoung\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u0026thinsp;+\u0026thinsp;None\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eRubus spectabilis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ewoody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eperennial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eearly\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYoung\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eAcer circinatum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e47.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ewoody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eperennial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003emid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYoung\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eOemleria cerasiformis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ewoody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eperennial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003emid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYoung\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eVaccinium parvifolium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e36.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ewoody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eperennial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003elate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYoung\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCorylus cornuta\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ewoody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eperennial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003emid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYoung\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eTsuga heterophylla\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ewoody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eperennial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003elate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eForb Species\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOld\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eLactuca serriola\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e39.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eforb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eexotic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eannual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eearly\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOld\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u0026thinsp;+\u0026thinsp;Mid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eClaytonia sibirica\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eforb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eperennial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eearly\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOld\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u0026thinsp;+\u0026thinsp;Mid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eEpilobium angistifolium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eforb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eperennial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003epioneer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOld\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u0026thinsp;+\u0026thinsp;Mid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eGraminoid species\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eforb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYoung\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eEpilobium angistifolium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e42.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eforb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eperennial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003epioneer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYoung\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u0026thinsp;+\u0026thinsp;Mid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eEpilobium ciliatum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eforb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eperennial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003epioneer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYoung\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eOxalis oregana\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eforb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eperennial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003elate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYoung\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ePolystichum munitum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003efern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eperennial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003elate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eChanges in riparian cover across vegetation layers\u003c/h2\u003e \u003cp\u003eGlobally, megafires (\u0026gt;\u0026thinsp;40,500 ha) have been increasing, creating greater exposure for riparian ecosystems. These three megafires resulted in a range of fire severities at a patch scale that contributed significant initial overstory mortality throughout entire watersheds, including riparian forests where canopy cover continued to decrease each year for the first three years after fire. While soil burn severity in adjacent riparian areas were generally less severely burned than much of the corresponding upland, we found riparian overstory mortality was extensive \u0026ndash; exceeding 73% within three years post-fire in mostly burned and completely burned watersheds.\u003c/p\u003e \u003cp\u003eAlthough initial overstory mortality in riparian areas in our study was lower for \u003cem\u003eAlnus rubra\u003c/em\u003e than \u003cem\u003eThuja plicata\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, our analyses revealed overstory mortality was dynamic in the first three years post-fire, with evidence of both delayed mortality and rapid re-sprouting. Mortality of deciduous species was particularly dynamic with \u003cem\u003eAlnus rubra\u003c/em\u003e experiencing delayed mortality \u003cem\u003ea\u003c/em\u003end \u003cem\u003eAcer macrophyllum\u003c/em\u003e, which can resprout after fire, initially showing delayed mortality from year one to two and then reviving again by year three. Species that re-sprout after apparent top kill can survive even high severity fire\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e and, in our study, \u003cem\u003eAcer macrophyllum\u003c/em\u003e apparent mortality reversed by over half in moderately burned sites between years two and three post-fire. Both \u003cem\u003eTsuga heterophylla\u003c/em\u003e and \u003cem\u003eAlnus rubra\u003c/em\u003e experienced delayed mortality two and three years after fire, with the greatest change in delayed mortality observed in more moderately burned sites for both species, although \u003cem\u003eAlnus rubra\u003c/em\u003e also experienced substantial delayed mortality in the most severely burned sites. \u003cem\u003eAlnus rubra\u003c/em\u003e mortality increased from 66% in year one to 100% in years two and three in the most severely burned sites. At moderately burned sites, \u003cem\u003eAlnus rubra\u003c/em\u003e mortality more than tripled from 23% in year one to 82% in year two and 89% in year three. In the most severely burned sites, \u003cem\u003eTsuga heterophylla\u003c/em\u003e already experienced high mortality (95%) in year one, which increased to 100% in years two and three. In moderately burned sites, \u003cem\u003eTsuga heterophylla\u003c/em\u003e mortality increased 30% from 56% in year one to 88% in years two and three.\u003c/p\u003e \u003cp\u003eThe magnitude of delayed mortality observed with these riparian species exceeded estimated delayed mortality in the literature, likely because much of that literature focuses on conifer mortality and reflects a lack of information in riparian areas where initial survival may be greater for some riparian species. Using a remote sensing analysis across the western U.S., Busby, et al. \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e estimated delayed mortality of conifers reached 5\u0026ndash;25% at the scale of a fire perimeter five years after fire. This is similar to the 30% increase in mortality in moderately burned sites of the only conifer \u003cem\u003e(Tsuga heterophylla)\u003c/em\u003e that experienced delayed mortality in our study. Others found that most mortality occurred within two years of fire, although only conifers were considered in their study\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Other studies of riparian areas found that 94% of \u003cem\u003eAlnus rubra\u003c/em\u003e and \u003cem\u003eSalix spp.\u003c/em\u003e (willow) trees were killed within three years by a wildfire in a Chapparral landscape in southern California, USA\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e and canopy cover was reduced from 48\u0026ndash;63% post-fire compared to pre-fire\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePre-fire drought can increase tree mortality susceptibility to fire\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e and post-fire drought may compound impacts\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Water years 2019\u0026ndash;2021 (Oct 1 to Sep 30) were drought years for northwest Oregon (includes Riverside and Beachie Creek fires) and 2018, 2020, and 2021 in southwest Oregon (includes Holiday Farm fire) based on the PRISM Standardized Precipitation Index\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Thus, drought conditions before, during, and after these wildfires may have contributed to initial and delayed fire-induced mortality. Fire-induced injuries that lead to cambium necrosis and limit hydraulic conductivity of the xylem contribute to delayed mortality\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, likely limiting ability to survive future stressful conditions in addition to fire, such as flooding, winds, ice storms, and forest pests. Forest structure, including tree density, may influence mortality after fire, particularly as it affects fuels, moisture content of vegetation, and interacts with fire behavior\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Pre-fire watershed stand age also encompasses differences in forest ownership and management practices that lead to a divergence in forest stand structure across our study sites. However, we did not find overstory mortality response to differ by pre-fire stand age; rather, only fire severity explained mortality, indicating riparian tree mortality in these fires was similar regardless of pre-fire stand conditions.\u003c/p\u003e \u003cp\u003eRiparian vegetation response to fire was dynamic across vegetation layers with forb cover recovering most rapidly by the second year after fire across all burn severities, and forb richness temporarily increased in two years and but did not remain elevated three years after fire. Shrub recovery was delayed to the third-year post-fire when both shrub cover and richness increased three years after fire across all burn severities, with substantial increases in richness in more severely burned sites. Simultaneous with forb recovery was the delayed mortality of \u003cem\u003eAlnus rubra\u003c/em\u003e and \u003cem\u003eTsuga heterophylla\u003c/em\u003e [primarily two years after wildfire], and continued reductions in canopy cover each year, which may have contributed to the timing and success of forb and shrub recovery by opening the canopy. We observed a greater decline in canopy cover through time for moderately burned sites (44%) than in severely burned sites (25%). Moderately burned sites also exhibited greater magnitude shrub cover increase (3X) relative to most severely burned sites. In contrast, the most severely burned sites had the greatest magnitude of increases in forb cover.\u003c/p\u003e \u003cp\u003eSeverity of fire, and time since fire, are important factors that drive complex responses in various layers of riparian vegetation. Therefore, continued monitoring of recovery after wildfire in these riparian areas is critical not only to understand terrestrial ecosystems, but also for aquatic ecosystems that rely on vegetation for shade, organic matter and nutrient inputs, and bank stability. Simultaneous monitoring of canopy cover from measurements taken in these streams revealed similar declines in overstory canopy cover each year since the fire, with high overstory mortality contributing to higher stream temperature maxima\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. In-stream monitoring indicated that understory re-growth, while extensive, did not effectively shade or limit thermal increases in the first three years post-fire. Despite these elevated summer stream temperatures, fish biomass and densities were elevated in exposed and severely burned watersheds, presumably due to greater basal resource availability, while amphibian biomass and densities were unaffected\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Dead standing trees, their root structures, and roots of understory shrubs and forbs, may provide important functions for stream and riparian ecosystems such as bank stability and microhabitats\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Fallen overstory trees can also contribute to riparian function as coarse wood on forest floor or as large wood in streams\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eIndicator species\u003c/h3\u003e\n\u003cp\u003eStudies from other land uses have revealed anthropogenically disturbed riparian zones may represent novel ecosystems, hosting different species and combinations of species than less disturbed systems\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Although we are unaware of prior documentation of this effect in forests, we expected forest management-related disturbances either pre-fire or post-fire (including a greater proportion of recently harvested stands, salvage, higher road density and stream crossings) to have been of greater magnitude or frequency in the watersheds with younger pre-fire stand age. In our study, older mean watershed stand ages generally indicated less anthropogenic disturbance and often included a component of old-growth. Importantly, legacy effects of prior historical harvest activities likely affected most/all sites (i.e., splash dams and log drives were once prevalent throughout much of western Oregon streams)\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Novel riparian zones may be more likely to have invasive plant species in their seed banks\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e or their unique combinations of species may make them more flammable\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Examining differences in the vegetation community composition after fire allows us to explore whether novel species combinations occur in riparian systems that had more frequent or greater magnitude anthropogenic disturbance before also being confronted with fire. We found distinct indicator species in watersheds draining older stands versus younger stands, which have experienced more recent anthropogenic disturbance.\u003c/p\u003e \u003cp\u003eWe expected to find exotic indicator species in younger sites, but only documented \u003cem\u003eLactuca serriola\u003c/em\u003e, an exotic forb species characteristic of fire in older sites. Anthropogenic disturbance gradients in forested riparian areas did not contribute to novel riparian communities (i.e., there were no invasives in more disturbed sites), but did have unique native species indicators. We found unique combinations of species in younger forested watersheds as four unique indicator species were characteristic of younger mean watershed stand ages, with only two indicator species shared by both young and old unburned riparian areas (\u003cem\u003eAcer circinatum\u003c/em\u003e and \u003cem\u003eTsuga heterophylla\u003c/em\u003e). We also found four unique indicator species that were characteristic of sites draining older mean watershed stand ages. In burned sites, \u003cem\u003eRubus spectabilis\u003c/em\u003e was an indicator of both young and old sites, and no other indicator species were found in young sites. This indicates that while a unique combination of mid- to late-seral species present in younger unburned sites can be used to identify riparian areas draining younger stands, in our study, only presence of \u003cem\u003eRubus leucodermis\u003c/em\u003e may differentiate an older burned site from younger burned sites.\u003c/p\u003e \u003cp\u003eOnly two species of shrubs were indicators of fire: \u003cem\u003eRubus leucodermis\u003c/em\u003e in younger mean watershed stand ages, and \u003cem\u003eRubus spectabilis\u003c/em\u003e in both younger and older stand age watersheds. In a prior study of clearcut followed by broadcast burning in northern Idaho, USA, \u003cem\u003eRubus leucodermis\u003c/em\u003e occurred more frequently in less severely burned sites than high burn severity sites and also varied by time since fire, maintaining cover in the first five years and then reduced 15 years post-fire\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Both of these native shrub species are rhizomatous, and may have established quickly post-fire via dormant seeds\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e or sprouted from belowground perennating roots.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eImplications \u0026amp; Conclusions\u003c/h2\u003e \u003cp\u003eOur findings indicate understory vegetation initiated recovery within three years after fire. Although individual species may re-establish quickly after fire, recovery of vegetation structure and composition takes more time\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. In the absence of overstory canopy, understory vegetation layers provided little shade to streams even after three years post-fire, but this will likely change in coming years. Early seral or pioneer species were indicative of fire effects which align with previous research showing disturbance-associated species to be more common or abundant after fire\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Other studies have shown fire in riparian areas reduced both total and native species richness\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e, but our data do not reflect that pattern during the first three years post-fire. Longer term study is essential to fully understand recovery of vegetation in these riparian forest stands.\u003c/p\u003e \u003cp\u003eOur results demonstrate that megafires can significantly alter riparian zones, even in relatively large 4th order streams. While the three fires included in our study were extensive, these three fires represent only a fraction of area burned in Oregon\u0026rsquo;s 2020 wildfires, which encompassed 4,900 km\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e across the state\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Furthermore, the three megafires in our study burned\u0026thinsp;\u0026gt;\u0026thinsp;2000X the stream length of what had burned over a 30-year period (1984\u0026ndash;2014) in this region.\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e Similarly, megafires in Australia burned 126,000 km\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, in a brief 7 month period in 2019\u0026ndash;2020, affecting 81,304 km of rivers and their riparian areas, and 29% of that river\u0026rsquo;s riparian network burned at extreme or high burn severity\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Although riparian areas comprise a small proportion of an area burned, the extent of riparian vegetation burned, and therefore the fire return intervals of the riparian areas themselves, are extremely varied between different ecoregions\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Globally riparian zones are increasingly exposed to fire across broad scales, and understanding their recovery is important for water quality, nutrient cycling, and providing habitat structure for in-stream and riparian associated wildlife\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors (L.S., J.V., and A.C.) contributed to writing the manuscript, while L.S. completed the analyses and most figures/tables, except for Figure 1, which A.C. contributed. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank M. Barnett, R. Boucher, A. Clements, E. Cruz, A. Hammond, A Lamet, B. Hobscheid, G. Demorest, A. Owens, M. Thomas, and especially G. Broyles and L. Koerner for assisting with field data collection. Bureau of Land Management, Campbell Global, LLC, Fruit Growers Supply, Giustina Resources, Port Blakely, Rayonier, State of Oregon, United States Forest Service, and Weyerhaeuser kindly allowed land access and provided assistance. Statistical support was provided by J. Thornton-Frost, J. Jones, and M. Fix. J. Homyack and D. Miller provided revisions to an earlier version of this manuscript. This research was funded by the National Council for Air and Stream Improvement, Inc., and Weyerhaeuser.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eStella, J. C., Rodr\u0026iacute;guez-Gonz\u0026aacute;lez, P. M., Dufour, S. \u0026amp; Bendix, J. 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Vegetation changes in blown-down and scorched forests 10\u0026ndash;26 years after the eruption of Mount St. Helens, Washington, USA. \u003cem\u003ePlant Ecol.\u003c/em\u003e \u003cstrong\u003e219\u003c/strong\u003e, 957-972 (2018).\u003c/li\u003e\n\u003cli\u003ePriebe, J. E. Silvicultural treatment impacts on understory trees and 20-year understory vegetation dynamics in mature Douglas-fir forests. (2016).\u003c/li\u003e\n\u003cli\u003eHitchcock, C. L., Cronquist, A., Ownbey, M. \u0026amp; Thompson, J. \u003cem\u003eVascular plants of the Pacific Northwest\u003c/em\u003e. (University of Washington Press, 1969).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6205148/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6205148/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRiparian ecosystems are highly diverse and dynamic, but effects of fire on riparian vegetation are poorly understood. In 2020, widespread fires impacted forests across the western Oregon Cascades, including riparian areas. To investigate riparian plant community recovery, we quantified riparian vegetation responses to wildfire and forest management. We determined that vegetation response to burn severity varied by structural layer and was dynamic across the first three years post-fire. Overstory mortality after fire varied by species. In the understory, forb cover recovered rapidly; shrub cover and richness showed some recovery within three years. Indicator species highlighted compositional differences between sites that burned and those that did not. Although riparian zones are thought to be resilient to fire, our results demonstrate megafires can significantly alter them, resulting in extensive initial and delayed mortality, and dynamic regrowth. Globally, riparian zones are increasingly exposed to fire, and understanding factors influencing their recovery is critical.\u003c/p\u003e","manuscriptTitle":"Megafires in Oregon: Riparian vegetation layers differ three years after mixed severity fire","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-18 08:21:59","doi":"10.21203/rs.3.rs-6205148/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-14T07:36:20+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-11T23:00:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"184371058833704192079894869550467978803","date":"2025-07-02T14:12:57+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-20T23:58:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"95635844761327731057058531228919640193","date":"2025-06-07T00:28:42+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-30T09:48:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-30T02:49:28+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-03-20T03:59:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-18T17:48:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-03-11T16:29:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4867db1f-d83f-47ed-a3fe-64994723c303","owner":[],"postedDate":"April 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":46583310,"name":"Biological sciences/Ecology/Fire ecology"},{"id":46583311,"name":"Biological sciences/Ecology/Forest ecology"},{"id":46583312,"name":"Biological sciences/Ecology/Riparian ecology"}],"tags":[],"updatedAt":"2025-10-20T16:03:53+00:00","versionOfRecord":{"articleIdentity":"rs-6205148","link":"https://doi.org/10.1038/s41598-025-20242-z","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-10-16 15:58:20","publishedOnDateReadable":"October 16th, 2025"},"versionCreatedAt":"2025-04-18 08:21:59","video":"","vorDoi":"10.1038/s41598-025-20242-z","vorDoiUrl":"https://doi.org/10.1038/s41598-025-20242-z","workflowStages":[]},"version":"v1","identity":"rs-6205148","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6205148","identity":"rs-6205148","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}