23 research outputs found

    Fuel Dynamics After Reintroduced Fire in an Old-Growth Sierra Nevada Mixed-Conifer Forest

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    Background: Surface fuel loadings are some of the most important factors contributing to fire intensity and fire spread. In old-growth forests where fire has been long excluded, surface fuel loadings can be high and can include woody debris ≥100 cm in diameter. We assessed surface fuel loadings in a long-unburned old-growth mixed-conifer forest in Yosemite National Park, California, USA, and assessed fuel consumption from a management-ignited fire set to control the progression of the 2013 Rim Fire. Specifically, we characterized the distribution and heterogeneity of pre-fire fuel loadings, both along transects and contained in duff mounds around large trees. We compared surface fuel consumption to that predicted by the standard First Order Fire Effects Model (FOFEM) based on pre-fire fuel loadings and fuel moistures. We also assessed the relationship between tree basal area—calculated for two different spatial neighborhood scales—and pre-fire fuel loadings. Results: Pre-fire total surface fuel loading averaged 192 Mg ha−1 and was reduced by 79% by the fire to 41 Mg ha−1 immediately after fire. Most fuel components were reduced by 87% to 90% by the fire, with the exception of coarse woody debris (CWD), which was reduced by 60%. Litter depth in duff mounds were within 1 SD of plot means, but duff biomass for the largest trees (\u3e150 cm diameter at breast height [DBH]) exceeded plot background levels. Overstory basal area generally had significant positive relationships with pre-fire fuel loadings of litter, duff, 1-hour, and 10-hour fuels, but the strength of the relationships differed between overstory components (live, dead, all [live and dead], species), and negative relationships were observed between live Pinus lambertiana Douglas basal area and CWD. FOFEM over-predicted rotten CWD consumption and under-predicted duff consumption. Conclusions: Surface fuel loadings were characterized by heterogeneity and the presence of large pieces. This heterogeneity likely contributed to differential fire behavior at small scales and heterogeneity in the post-fire environment. The reductions in fuel loadings at our research site were in line with ecological restoration objectives; thus, ecologically restorative burning during fire suppression is possible

    Latent Resilience in Ponderosa Pine Forest: Effects of Resumed Frequent Fire

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    Ecological systems often exhibit resilient states that are maintained through negative feedbacks. In ponderosa pine forests, fire historically represented the negative feedback mechanism that maintained ecosystem resilience; fire exclusion reduced that resilience, predisposing the transition to an alternative ecosystem state upon reintroduction of fire. We evaluated the effects of reintroduced frequent wildfire in unlogged, fire-excluded, ponderosa pine forest in the Bob Marshall Wilderness, Montana, USA. Initial reintroduction of fire in 2003 reduced tree density and consumed surface fuels, but also stimulated establishment of a dense cohort of lodgepole pine, maintaining a trajectory toward an alternative state. Resumption of a frequent fire regime by a second fire in 2011 restored a low-density forest dominated by large-diameter ponderosa pine by eliminating many regenerating lodgepole pines and by continuing to remove surface fuels and small-diameter lodgepole pine and Douglas-fir that established during the fire suppression era. Our data demonstrate that some unlogged, fire-excluded, ponderosa pine forests possess latent resilience to reintroduced fire. A passive model of simply allowing lightning-ignited fires to burn appears to be a viable approach to restoration of such forests

    Shrub Communities, Spatial Patterns, and Shrub-Mediated Tree Mortality following Reintroduced Fire in Yosemite National Park, California, USA

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    Shrubs contribute to the forest fuel load; their distribution is important to tree mortality and regeneration, and vertebrate occupancy. We used a method new to fire ecology—extensive continuous mapping of trees and shrub patches within a single large (25.6 ha) study site—to identify changes in shrub area, biomass, and spatial pattern due to fire reintroduction by a backfire following a century of fire exclusion in lower montane forests of the Sierra Nevada, California, USA. We examined whether trees in close proximity to shrubs prior to fire experienced higher mortality rates than trees in areas without shrubs. We calculated shrub biomass using demography subplots and existing allometric equations, and we developed new equations for beaked hazel (Corylus cornuta ssp. californica [A. de Candolle] E. Murray) from full dissection of 50 stems. Fire decreased shrub patch area from 15.1 % to 0.9 %, reduced live shrub biomass from 3.49 Mg ha−1 to 0.27 Mg ha−1, and consumed 4.41 Mg ha−1 of living and dead shrubs. Distinct (non-overlapping) shrub patches decreased from 47 ha−1 to 6 ha−1. The mean distance between shrub patches increased 135 %. Distances between montane chaparral patches increased 285 %, compared to a 54 % increase in distances between riparian shrub patches and an increase of 267 % between generalist shrub patches. Fire-related tree mortality within shrub patches was marginally lower (67.6 % versus 71.8 %), showing a contrasting effect of shrubs on tree mortality between this forest ecosystem and chaparral-dominated ecosystems in which most trees are killed by fire

    Large-Diameter Trees Dominate Snag and Surface Biomass Following Reintroduced Fire

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    The reintroduction of fire to landscapes where it was once common is considered a priority to restore historical forest dynamics, including reducing tree density and decreasing levels of woody biomass on the forest floor. However, reintroducing fire causes tree mortality that can have unintended ecological outcomes related to woody biomass, with potential impacts to fuel accumulation, carbon sequestration, subsequent fire severity, and forest management. In this study, we examine the interplay between fire and carbon dynamics by asking how reintroduced fire impacts fuel accumulation, carbon sequestration, and subsequent fire severity potential. Beginning pre-fire, and continuing 6 years post-fire, we tracked all live, dead, and fallen trees ≥ 1 cm in diameter and mapped all pieces of deadwood (downed woody debris) originating from tree boles ≥ 10 cm diameter and ≥ 1 m in length in 25.6 ha of an Abies concolor/Pinus lambertiana forest in the central Sierra Nevada, California, USA. We also tracked surface fuels along 2240 m of planar transects pre-fire, immediately post-fire, and 6 years post-fire. Six years after moderate-severity fire, deadwood ≥ 10 cm diameter was 73 Mg ha−1, comprised of 32 Mg ha−1 that persisted through fire and 41 Mg ha−1 of newly fallen wood (compared to 72 Mg ha−1 pre-fire). Woody surface fuel loading was spatially heterogeneous, with mass varying almost four orders of magnitude at the scale of 20 m × 20 m quadrats (minimum, 0.1 Mg ha−1; mean, 73 Mg ha−1; maximum, 497 Mg ha−1). Wood from large-diameter trees (≥ 60 cm diameter) comprised 57% of surface fuel in 2019, but was 75% of snag biomass, indicating high contributions to current and future fuel loading. Reintroduction of fire does not consume all large-diameter fuel and generates high levels of surface fuels ≥ 10 cm diameter within 6 years. Repeated fires are needed to reduce surface fuel loading

    The Fire and Tree Mortality Database, for Empirical Modeling of Individual Tree Mortality After Fire

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    Wildland fires have a multitude of ecological effects in forests, woodlands, and savannas across the globe. A major focus of past research has been on tree mortality from fire, as trees provide a vast range of biological services. We assembled a database of individual-tree records from prescribed fires and wildfires in the United States. The Fire and Tree Mortality (FTM) database includes records from 164,293 individual trees with records of fire injury (crown scorch, bole char, etc.), tree diameter, and either mortality or top-kill up to ten years post-fire. Data span 142 species and 62 genera, from 409 fires occurring from 1981-2016. Additional variables such as insect attack are included when available. The FTM database can be used to evaluate individual fire-caused mortality models for pre-fire planning and post-fire decision support, to develop improved models, and to explore general patterns of individual fire-induced tree death. The database can also be used to identify knowledge gaps that could be addressed in future research

    Reduced fire severity offers near-term buffer to climate-driven declines in conifer resilience across the western United States

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    Increasing fire severity and warmer, drier postfire conditions are making forests in the western United States (West) vulnerable to ecological transformation. Yet, the relative importance of and interactions between these drivers of forest change remain unresolved, particularly over upcoming decades. Here, we assess how the interactive impacts of changing climate and wildfire activity influenced conifer regeneration after 334 wildfires, using a dataset of postfire conifer regeneration from 10,230 field plots. Our findings highlight declining regeneration capacity across the West over the past four decades for the eight dominant conifer species studied. Postfire regeneration is sensitive to high-severity fire, which limits seed availability, and postfire climate, which influences seedling establishment. In the near-term, projected differences in recruitment probability between low- and high-severity fire scenarios were larger than projected climate change impacts for most species, suggesting that reductions in fire severity, and resultant impacts on seed availability, could partially offset expected climate-driven declines in postfire regeneration. Across 40 to 42% of the study area, we project postfire conifer regeneration to be likely following low-severity but not high-severity fire under future climate scenarios (2031 to 2050). However, increasingly warm, dry climate conditions are projected to eventually outweigh the influence of fire severity and seed availability. The percent of the study area considered unlikely to experience conifer regeneration, regardless of fire severity, increased from 5% in 1981 to 2000 to 26 to 31% by mid-century, highlighting a limited time window over which management actions that reduce fire severity may effectively support postfire conifer regeneration. © 2023 the Author(s)

    Global importance of large-diameter trees

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    Aim: To examine the contribution of large‐diameter trees to biomass, stand structure, and species richness across forest biomes. Location: Global. Time period: Early 21st century. Major taxa studied: Woody plants. Methods: We examined the contribution of large trees to forest density, richness and biomass using a global network of 48 large (from 2 to 60 ha) forest plots representing 5,601,473 stems across 9,298 species and 210 plant families. This contribution was assessed using three metrics: the largest 1% of trees ≥ 1 cm diameter at breast height (DBH), all trees ≥ 60 cm DBH, and those rank‐ordered largest trees that cumulatively comprise 50% of forest biomass. Results: Averaged across these 48 forest plots, the largest 1% of trees ≥ 1 cm DBH comprised 50% of aboveground live biomass, with hectare‐scale standard deviation of 26%. Trees ≥ 60 cm DBH comprised 41% of aboveground live tree biomass. The size of the largest trees correlated with total forest biomass (r2 = .62, p < .001). Large‐diameter trees in high biomass forests represented far fewer species relative to overall forest richness (r2 = .45, p < .001). Forests with more diverse large‐diameter tree communities were comprised of smaller trees (r2 = .33, p < .001). Lower large‐diameter richness was associated with large‐diameter trees being individuals of more common species (r2 = .17, p = .002). The concentration of biomass in the largest 1% of trees declined with increasing absolute latitude (r2 = .46, p < .001), as did forest density (r2 = .31, p < .001). Forest structural complexity increased with increasing absolute latitude (r2 = .26, p < .001). Main conclusions: Because large‐diameter trees constitute roughly half of the mature forest biomass worldwide, their dynamics and sensitivities to environmental change represent potentially large controls on global forest carbon cycling. We recommend managing forests for conservation of existing large‐diameter trees or those that can soon reach large diameters as a simple way to conserve and potentially enhance ecosystem services

    Drivers of burn severity in the northern Cascade Range, Washington, USA

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    MS ThesisI examined the influence of annual climate and topographical complexity on the occurrence, size, severity, and within-fire severity pattern of fires in the northern Cascade Range of Washington, USA. Landsat Thematic Mapper (LTM) data were used to quantify fire severity for all fires greater than 10 ha (n = 125) that occurred during a 25-year period (1984-2008). Categorical burn-severity images were developed from an index of burn severity (Relative differenced Normalized Burn Ratio) derived from LTM data and parameterized with data from 639 field plots. My results show that the fire regime of the northern Cascade Range responds to annual climatic variation. Spring snowpack and summer temperature were negatively and positively correlated, respectively, with fire occurrence, and summer temperature was positively correlated with annual area burned, the proportion of landscape burned at high severity, and spatial aggregation of the high-severity class. Nevertheless, the within-fire severity mosaic reflects the underlying topographic complexity. Fires in areas with greater topographical complexity had increased spatial complexity of burn severity. Several recent studies in the western United States have documented a positive relationship between warm and dry climate and annual area burned. The relationship between climate drivers and fire-regime attributes identified in this study—a positive relationship between warm and dry conditions and the proportion of area burned at high severity and spatial aggregation of high severity patches—adds nuance to the climate-area burned relationship documented in previous studies

    How Robust Are Burn Severity Indices When Applied in a New Region? Evaluation of Alternate Field-Based and Remote-Sensing Methods

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    Remotely sensed indices of burn severity are now commonly used by researchers and land managers to assess fire effects, but their relationship to field-based assessments of burn severity has been evaluated only in a few ecosystems. This analysis illustrates two cases in which methodological refinements to field-based and remotely sensed indices of burn severity developed in one location did not show the same improvement when used in a new location. We evaluated three methods of assessing burn severity in the field: the Composite Burn Index (CBI)—a standardized method of assessing burn severity that combines ecologically significant variables related to burn severity into one numeric site index—and two modifications of the CBI that weight the plot CBI score by the percentage cover of each stratum. Unexpectedly, models using the CBI had higher R2 and better classification accuracy than models using the weighted versions of the CBI. We suggest that the weighted versions of the CBI have lower accuracies because weighting by percentage cover decreases the influence of the dominant tree stratum, which should have the strongest relationship to optically sensed reflectance, and increases the influence of the substrates strata, which should have the weakest relationship with optically sensed reflectance in forested ecosystems. Using a large data set of CBI plots (n = 251) from four fires and CBI scores derived from additional field-based assessments of burn severity (n = 388), we predicted two metrics of image-based burn severity, the Relative differenced Normalized Burn Ratio (RdNBR) and the differenced Normalized Burn Ratio (dNBR). Predictive models for RdNBR showed slightly better classification accuracy than for dNBR (overall accuracy = 62%, Kappa = 0.40, and overall accuracy = 59%, Kappa= 0.36, respectively), whereas dNBR had slightly better explanatory power, but strong differences were not apparent. RdNBR may provide little or no improvement over dNBR in systems where pre-fire reflectance is not highly variable, but may be more appropriate for comparing burn severity among regions
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