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Evaluating immaturity risk in young stands of the serotinous knobcone pine (Pinus attenuata)

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posted on 2025-08-19, 02:57 authored by Katherine Marlin, David Greene, Jeffrey Kane, Matthew Reilly, Buddhika Maderapperuma
<p>As wildfire becomes increasingly frequent, many plant populations risk local extirpation if fire recurs too soon, a problem dubbed “immaturity risk”. We studied the regeneration of a serotinous conifer species, knobcone pine (<em>Pinus attenuata</em>), as a function of the time between high-severity fires (6-79 years). We evaluated age, cone production, and regeneration at two burned sites in northern California, the Ranch Fire (2018) in Mendocino National Forest, and the Carr Fire (2018) in Whiskeytown National Recreation Area. We found an average of 30.5 filled seeds in closed, brown cones (42% viability of filled seeds). The bulk of the older (gray) cones were partially or fully open, and thus available seed in them at the time of fire was approximately halved. Adjusting for survivorship, the estimated minimum age for knobcone pine to produce one recruit per tree (self-replacement) was 8.2 years. Characterizing the probability of burning as a negative exponential model and using an 81-year return time, we found the likelihood of reburn before 8.2 years was 0.09. Our study demonstrated the importance of understanding the size and time to reproductive maturity in serotinous tree species to adequately quantify immaturity risk. Based on our results and current estimates of return time, we suggested that immaturity risk is very low for knobcone pine. Our approach could be broadly applied to better quantify immaturity risk in other conifer species.</p>

History

Data contact name

Marlin, Katherine

Data contact email

marlinkatie070@gmail.com

Publisher

Dryad

Theme

  • Not specified

ISO Topic Category

  • biota

National Agricultural Library Thesaurus terms

species; California; sexual maturity; survival rate; wildfires; risk; viability; recreation; Pinus attenuata; trees; conifers; Mendocino National Forest; probability; models

Pending citation

  • No

Public Access Level

  • Public

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