Rapid Loss of the Sierra Nevada's Largest Trees Driven by Fire

📅 2026-09-15
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🤖 AI Summary
研究使用深度学习模型U-Net-ID和高分辨率航空影像，量化了内华达山脉大型树木的分布与健康状况，并通过Sentinel-2时间序列分析揭示火灾是导致这些树木死亡的主要原因。
📝 Abstract
Large trees disproportionately contribute to biomass storage, habitat structure, and ecosystem functioning. However, their distribution and health dynamics remain poorly quantified at a regional scale. Here, a deep learning model (U-Net-ID) and canopy height models derived from sub-meter aerial imagery from 2020 were used to delineate all individual trees with crown area $\geq$ 100 m$^2$ across the Sierra Nevada Floristic Province. The model was trained using more than 3.3 million synthetic tree crowns and achieved a median Intersection over Union (IoU) of 0.602 when validated against an independent dataset of 20,273 crowns. A total of 6,515,705 large trees were mapped, occurring across approximately 78.7% of the Sierra Nevada Floristic Province. The spatial distribution of large trees showed associations with elevation, temperature, and precipitation. Using Sentinel-2 time series from 2020 to 2025, tree health dynamics were characterized by extracting spectral trajectories for each crown and applying BFAST breakpoint detection algorithm combined with a disturbance classification framework to identify mortality, disturbance, and recovery trajectories of individual trees. Wildfires, estimated from CAL FIRE fire perimeters, were identified as the dominant driver of large-tree mortality, killing 10% of all large trees in the Sierra Nevada, with mortality strongly concentrated during the extreme 2020-2021 fire seasons.
Problem

Research questions and friction points this paper is trying to address.

Large Trees
Rapid Loss
Ecosystem Functioning
Health Dynamics
Innovation

Methods, ideas, or system contributions that make the work stand out.

deep learning model
U-Net-ID
canopy height models
Sentinel-2 time series
BFAST breakpoint detection algorithm
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Affiliations4
California Institute of Technology
University of California, Los Angeles
University of Maryland, Baltimore County
University of São Paulo
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Fabien H. Wagner
CTrees, Pasadena, CA, 91105, USA.
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Dan J. Dixon
Department of Land, Air and Water Resources, University of California, Davis, Davis, CA, 95616, USA.
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Christopher W. Woodall
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Mayumi C. M. Hirye
CTrees, Pasadena, CA, 91105, USA.; Institute of Environment and Sustainability, University of California, Los Angeles, Los Angeles, CA, USA.; Quapá Lab, Faculty of Architecture and Urbanism, University of São Paulo, 05508080, São Paulo, SP, Brazil.
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Felipe Saad
Department of Geography and Environmental Systems, University of Maryland Baltimore County, USA.
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Griffin Carter
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Ricardo Dalagnol
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Lorena Alves
CTrees, Pasadena, CA, 91105, USA.; Institute of Environment and Sustainability, University of California, Los Angeles, Los Angeles, CA, USA.
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Cynthia Creze
CTrees, Pasadena, CA, 91105, USA.; Institute of Environment and Sustainability, University of California, Los Angeles, Los Angeles, CA, USA.
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Stephen C. Hagen
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Bryan Shaddy
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