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Project ID: 17-2-01-23

Year: 2017

Date Started: 06/01/2017

Ending Date:  05/01/2019

Title: Predicting forest recovery following high-severity fire

Project Proposal Abstract: The combination of climatic change and other human influences has altered fire regimes. Predicting successional patterns in such altered regimes is difficult, particularly for long-living, slow-growing organisms. In Sierra Nevada mixed-conifer forests, high-severity fire (with total or near-total tree mortality) is burning in unprecedented patch sizes. Native tree species are adapted to regenerate in mixed-severity, mosaicked forests but lack reproductive traits suited for reoccupation of large high-severity fire patches. Recent evidence shows variable long-term tree recovery across patches, suggesting that tree recruitment may be governed by site-specific and temporally variable factors such as mast seeding and weather in the first few postfire years. Our study will further this research by modeling shifts in tree dominance under variable initial conditions. Using a combination of data synthesis, field measurements, and forest growth simulations, we will identify the demographic process(es) that most limit tree recruitment in these patches.

Principal Investigator: Scott L. Stephens

Agency/Organization: University of California-Berkeley

Branch or Dept: Department of Environmental Sciences-Policy & Management


Other Project Collaborators

Type

Name

Agency/Organization

Branch or Dept

Agreements Contact

Noam Pines

University of California-Berkeley

Sponsored Projects Office

Budget Contact

Noam Pines

University of California-Berkeley

Sponsored Projects Office

Student Investigator

Carmen L. Tubbesing

University of California-Berkeley

Department of Environmental Sciences-Policy & Management


Project Locations

Fire Science Exchange Network

California


Level

State

Agency

Unit

STATE

CA

FS

Eldorado National Forest

STATE

CA

FS

Tahoe National Forest


Project Deliverables

There is no final report available for this project.
There are no deliverables available for this project.

Supporting Documents

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