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Research about Sierra Nevada Mountains

Source-linked reports with geographic coverage including Sierra Nevada Mountains.

13 recordsLinked to original sources
USGS2026

The state of the giant sequoias: Losses, risks, and opportunities

Background Giant sequoias, an iconic tree found only in a narrow band along the western slope of the Sierra Nevada of California, are facing unprecedented threats. Despite being adapted to fire and resistant to both drought and insect attack, the species has exhibited signs of vulnerability to these stressors in recent years, with the most substantial impacts coming from wildfire. Recently, several unprecedentedly large and severe fires have resulted in the deaths of many large trees and, in some cases, limited postfire regeneration. These impacts have led to heightened efforts by managers to implement treatments to protect those places that are still vulnerable. Here, we provide a comprehensive, range-wide assessment of the condition of the species, including an evaluation of the trends in wildfire and its effects on large giant sequoia mortality and the potential for local extirpation, treatment patterns, and vulnerability to future fire. Results From 2015 to 2024, 82% of giant sequoia grove area burned in wildfire, compared to 24% between 1910 and 2014. We conservatively estimate that 17.6% of all large giant sequoias have been killed by wildfire since 1984, with most dying in 2020 and 2021. Due to very severe wildfire, roughly 13% of the range is at some risk of local extirpation due to the loss of mature trees and limited predicted regeneration. Treatment activity has increased since 1995, with treatment type and amount varying by jurisdiction. The combination of treatment and wildfire has created a mosaic of resistance to severe fire, with 26% of grove area at high resistance, 38% at moderate resistance, 2% at low resistance, and 16% having no resistance. The remaining 18% are areas where mature giant sequoia forest was lost due to high severity fire. Conclusions Giant sequoias have experienced substantial losses due to recent wildfire, with large areas at risk of grove loss. However, most burned area had lower severity effects, creating opportunities to leverage wildfire as a treatment. When combined with areas of active management, these opportunities can promote giant sequoia conservation in a time of rapid change.

California↗
USGS2025

Mapping bedrock outcrops in the Sierra Nevada Mountains (California, USA) using machine learning

Accurate, high-resolution maps of bedrock outcrops can be valuable for applications such as models of land–atmosphere interactions, mineral assessments, ecosystem mapping, and hazard mapping. The increasing availability of high-resolution imagery can be coupled with machine learning techniques to improve regional bedrock outcrop maps. In the United States, the existing 30 m U.S. Geological Survey (USGS) National Land Cover Database (NLCD) tends to misestimate extents of barren land, which includes bedrock outcrops. This impacts many calculations beyond bedrock mapping, including soil carbon storage, hydrologic modeling, and erosion susceptibility. Here, we tested if a machine learning (ML) model could more accurately map exposed bedrock than NLCD across the entire Sierra Nevada Mountains (California, USA). The ML model was trained to identify pixels that are likely bedrock from 0.6 m imagery from the National Agriculture Imagery Program (NAIP). First, we labeled exposed bedrock at twenty sites covering more than 83 km 2 (0.13%) of the Sierra Nevada region. These labels were then used to train and test the model, which gave 83% precision and 78% recall, with a 90% overall accuracy of correctly predicting bedrock. We used the trained model to map bedrock outcrops across the entire Sierra Nevada region and compared the ML map with the NLCD map. At the twenty labeled sites, we found the NLCD barren land class, even though it includes more than just bedrock outcrops, accounted for only 41% and 40% of mapped bedrock from our labels and ML predictions, respectively. This substantial difference illustrates that ML bedrock models can have a role in improving land-cover maps, like NLCD, for a range of science applications.

California↗
USGS2020

Coming to terms with the new normal: Forest health in the Sierra Nevada

The vast conifer forests of California’s Sierra Nevada range inspire awe and create lasting memories. The size and longevity of these trees make them seem both otherworldly and everlasting. Indeed, their grandeur is such that visitors may not appreciate how these forests are connected to the larger landscape, and so there is little understanding that something as common as a drought could lead to the death of so many trees and trigger massive and irreversible changes in the nature of these forests (Box 1: Reflections on the California Drought). Although tree death is a natural and essential process, human activity is increasing the mortality rate to such an extent that it threatens the persistence of the "big tree" forests we have come to associate with the Sierra Nevada. Here, we briefly explain how forests change, with a focus on the role of tree mortality. We then describe the contemporary risks and outline a way toward restoring the resilience of Sierran forests.

California↗
USGS2015

An integrated approach to modeling changes in land use, land cover, and disturbance and their impact on ecosystem carbon dynamics: a case study in the Sierra Nevada Mountains of California

Increased land-use intensity (e.g. clearing of forests for cultivation, urbanization), often results in the loss of ecosystem carbon storage, while changes in productivity resulting from climate change may either help offset or exacerbate losses. However, there are large uncertainties in how land and climate systems will evolve and interact to shape future ecosystem carbon dynamics. To address this we developed the Land Use and Carbon Scenario Simulator (LUCAS) to track changes in land use, land cover, land management, and disturbance, and their impact on ecosystem carbon storage and flux within a scenario-based framework. We have combined a state-and-transition simulation model (STSM) of land change with a stock and flow model of carbon dynamics. Land-change projections downscaled from the Intergovernmental Panel on Climate Change’s (IPCC) Special Report on Emission Scenarios (SRES) were used to drive changes within the STSM, while the Integrated Biosphere Simulator (IBIS) ecosystem model was used to derive input parameters for the carbon stock and flow model. The model was applied to the Sierra Nevada Mountains ecoregion in California, USA, a region prone to large wildfires and a forestry sector projected to intensify over the next century. Three scenario simulations were conducted, including a calibration scenario, a climate-change scenario, and an integrated climate- and land-change scenario. Based on results from the calibration scenario, the LUCAS age-structured carbon accounting model was able to accurately reproduce results obtained from the process-based biogeochemical model. Under the climate-only scenario, the ecoregion was projected to be a reliable net sink of carbon, however, when land use and disturbance were introduced, the ecoregion switched to become a net source. This research demonstrates how an integrated approach to carbon accounting can be used to evaluate various drivers of ecosystem carbon change in a robust, yet transparent modeling environment.

California↗
USGS2012

Displacement fields from point cloud data: Application of particle imaging velocimetry to landslide geodesy

Acquiring spatially continuous ground-surface displacement fields from Terrestrial Laser Scanners (TLS) will allow better understanding of the physical processes governing landslide motion at detailed spatial and temporal scales. Problems arise, however, when estimating continuous displacement fields from TLS point-clouds because reflecting points from sequential scans of moving ground are not defined uniquely, thus repeat TLS surveys typically do not track individual reflectors. Here, we implemented the cross-correlation-based Particle Image Velocimetry (PIV) method to derive a surface deformation field using TLS point-cloud data. We estimated associated errors using the shape of the cross-correlation function and tested the method's performance with synthetic displacements applied to a TLS point cloud. We applied the method to the toe of the episodically active Cleveland Corral Landslide in northern California using TLS data acquired in June 2005–January 2007 and January–May 2010. Estimated displacements ranged from decimeters to several meters and they agreed well with independent measurements at better than 9% root mean squared (RMS) error. For each of the time periods, the method provided a smooth, nearly continuous displacement field that coincides with independently mapped boundaries of the slide and permits further kinematic and mechanical inference. For the 2010 data set, for instance, the PIV-derived displacement field identified a diffuse zone of displacement that preceded by over a month the development of a new lateral shear zone. Additionally, the upslope and downslope displacement gradients delineated by the dense PIV field elucidated the non-rigid behavior of the slide.

California↗
USGS2008

A Miocene to Pleistocene climate and elevation record of the Sierra Nevada (California)

Orographic precipitation of Pacific-sourced moisture creates a rain shadow across the central part of the Sierra Nevada (California) that contrasts with the southern part of the range, where seasonal monsoonal precipitation sourced to the south obscures this rain shadow effect. Orographic rainout systematically lowers the hydrogen isotope composition of precipitation (δ D ppt ) and therefore δ D ppt reflects a measure of the magnitude of the rain shadow. Hydrogen isotope compositions of volcanic glass (δ D glass ) hydrated at the earth's surface provide a unique opportunity to track the elevation and precipitation history of the Sierra Nevada and adjacent Basin and Range Province. Analysis of 67 well dated volcanic glass samples from widespread volcanic ash-fall deposits located from the Pacific coast to the Basin and Range Province demonstrates that between 0.6 and 12.1 Ma the hydrogen isotope compositions of meteoric water displayed a large (>40‰) decrease from the windward to the leeward side of the central Sierra Nevada, consistent with the existence of a rain shadow of modern magnitude over that time. Evidence for a Miocene-to-recent rain shadow of constant magnitude and systematic changes in the longitudinal climate and precipitation patterns strongly suggest that the modern first-order topographic elements of the Sierra Nevada characterized the landscape over at least the last 12 million years.

California, Nevada↗
USGS2006

Heterogeneity in fire severity within early season and late season prescribed burns in a mixed-conifer forest

Structural heterogeneity in forests of the Sierra Nevada was historically produced through variation in fire regimes and local environmental factors. The amount of heterogeneity that prescription burning can achieve might now be more limited owing to high fuel loads and increased fuel continuity. Topography, woody fuel loading, and vegetative composition were quantified in plots within replicated early and late season burn units. Two indices of fire severity were evaluated in the same plots after the burns. Scorch height ranged from 2.8 to 25.4 m in early season plots and 3.1 to 38.5 m in late season plots, whereas percentage of ground surface burned ranged from 24 to 96% in early season plots and from 47 to 100% in late season plots. Scorch height was greatest in areas with steeper slopes, higher basal area of live trees, high percentage of basal area composed of pine, and more small woody fuel. Percentage of area burned was greatest in areas with less bare ground and rock cover (more fuel continuity), steeper slopes, and units burned in the fall (lower fuel moisture). Thus topographic and biotic factors still contribute to the abundant heterogeneity in fire severity with prescribed burning, even under the current high fuel loading conditions. Burning areas with high fuel loads in early season when fuels are moister may lead to patterns of heterogeneity in fire effects that more closely approximate the expected patchiness of historical fires.

California, Nevada↗
USGS1996

An overview of fire in the Sierra Nevada

Fire, ignited by lightning and Native Americans, was common in the Sierra Nevada prior to 20th century suppression efforts. Presettlement fire return intervals were generally less than 20 years throughout a broad zone extending from the foothills through the mixed conifer forests. In the 20th century, the areal extent of fire was greatly reduced. This reduction in fire activity, coupled with the selective harvest of many large pines, produced forests which today are denser, with generally smaller trees, and have higher proportions of white fir and incense cedar than were present historically. These changes have almost certainly increased the levels of fuel, both on the forest floor and “ladder fuels”—small trees and brush which carry the fire into the forest canopy. Increases in fuel, coupled with efficient suppression of low and moderate intensity fires, has led to an increase in general fire severity. We suggest extensive modification of forest structure will be necessary to minimize severe fires in the future. In high-risk areas, landscapes should be modified both to reduce fire severity and to increase suppression effectiveness. We recommend thinning and underburning to reduce fire-related tree mortality coupled with strategically placed defensible fuel profile zones (DFPZs). DFPZs are areas in which forest structure and fuels have been modified to reduce flame length and “spotting”, allowing effective suppression. This chapter is an overview of work by the fire-subgroup of the Sierra Nevada Ecosystem Project. Details concerning these findings are found in Skinner and Chang 1996; Chang 1996; Husari and McKelvey 1996; McKelvey and Busse 1996; Erman and Jones 1996; van Wagtendonk 1996; and Weatherspoon 1996.

California↗
USGS1960

Foothills fault system, western Sierra Nevada, California

A large fault system , here named the Foothills fault system , is the dominant structural feature of the western Sierra Nevada . The steeply dipping to vertical component faults trend northwestward through an area about 200 miles long and 30 miles wide north of 37°30' north latitude. The faulted Paleozoic and Mesozoic rocks are overlapped by unfaulted younger rocks, and the total extent of the fault system is not known. It is probably not limited to the western Sierra Nevada . Faults are marked by belts as much as 4 miles wide of cataclastically deformed and recrystallized rocks and by truncated folds. Along one fault , Upper Jurassic rocks are juxtaposed against Paleozoic rocks for at least 100 miles. The direction of fault movement has not been determined. Net displacement on some of the component faults exceeds 3000 feet and may be measurable in miles. Major faults cut beds of Late Jurassic age and are in turn cut by plutonic rocks of probable Late Jurassic and Middle Cretaceous age. Faults that controlled deposition of quartz veins and gold ore bodies of the Mother Lode belt are apparently younger and structurally less important features superimposed on one of the fault zones of the large system .

California, Nevada↗