4.4 Article

DOES FUELS MANAGEMENT ACCOMPLISH RESTORATION IN SOUTHWEST OREGON, USA, CHAPARRAL? INSIGHTS FROM AGE STRUCTURE

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FIRE ECOLOGY
卷 6, 期 2, 页码 76-96

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SPRINGER
DOI: 10.4996/fireecology.0602076

关键词

age structure; Arctostaphylos viscida; Ceanothus cuneatus; chaparral; fuels management; grazing; Klamath region; obligate-seeder; southwest Oregon

资金

  1. Joint Fire Science Program [06-3-1-35]

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Fuels management is often intended to both reduce fire hazard and restore ecosystems thought to be impacted by fire suppression. Objectives to reduce fire hazard, however, are not compatible with restoration in many vegetation types. Application of ecologically incompatible treatments to poorly understood ecosystems can drain management resources and contribute to ecosystem degradation. Extensive areas of chaparral on Bureau of Land Management lands in southwest Oregon, USA, are annually targeted for fuels treatment. However, the fire ecology of this ecosystem is not well understood and the assumptions guiding treatment need and design are based on extrapolations from other ecosystems. We studied patterns in age structure of two obligate-seeding chaparral shrubs, sticky whiteleaf manzanita (Arctostaphylos viscida Parry) and buckbrush (Ceanothus cuneatus [Hook.] Nutt.) and assessed relationships with environment, fire, and potential livestock disturbance. Results indicate that chaparral of obligate seeding species encompasses a wide range of structures and responses to environment and fire throughout its range. While Mediterranean climate obligate-seeding shrub populations are typically even-aged, most stands unburned >30 yr were uneven-aged due to both recruitment in the absence of fire and to persistence of shrubs that predated the last fire. Fire suppression does not seem to have altered chaparral structure or fire severity, and current fuels treatments appear unlikely to reproduce stand structures observed in mature chaparral or in post-wildfire stands. Results underscore that effective fuels management should be both sensitive to regional variability and founded on ecosystem-specific data.

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