# Presentation: 497289

## A Conceptual Approach to Prioritizing Landscapes for Fuels Treatments in Northern Spotted Owl Habitats

**A Conceptual Approach to Prioritizing Landscapes ****for Fuels Treatments in ****Northern Spotted Owl Habitats**

## AcknowledgementsScott CenterCindy DoneganLynn Gemlo

**Acknowledgements****Scott Center****Cindy Donegan****Lynn Gemlo**

## The paradox facing land managers today is the need to treat northern spotted owl habitat in order to save it (Agee 1992).To achieve this, we need to identify priority areas for reducing the risk of stand replacement wildfires in areas with high habitat values.

**Problem Statement**

## Conceptual Model

- One to many

- Composite
- Risk Map

- Composite
- Values Map

**Landscape Prioritization Map**

**Risk**
**Factors**

- One to many

**Resource**
**Values**

## Northern Spotted Owl                                                                                      and the

**Northern Spotted Owl                                                                                      and the**
**Northwest Forest Plan**

-  **18.1 million acres of habitat**
**  ****capable Federal land**
** ****9.3 million acres of habitat**
** ****Declining populations**
** ****Habitat at risk**

## Lightning Ignited Wildfire

**Lightning Ignited Wildfire**
**during the**
**First Decade**
**(1994-2003)**

**50% were caused by lightning**
**75% of the total area burned**
**was the result of lightning  **

**Around 13,200 wildfires were recorded on Federal lands, burning about 1.7 million acres**

## Wildfire

**High Density**

**Low Density**

**Wildfire**
**Density Map**
**( ****# Fires / 100 mi****2**** ****)**

**Moderate Density**

## Largest Wildfires

**B&B Complex**

**Largest Wildfires**
**( ****first decade ****)**

**Tiller Complex**

**Biscuit Fire**

***>15,000 acres in WA***

***>10,000 acres in OR***

***>5,000 acres in CA***

## Resulting in

**Resulting in**
**Loss of Habitat**
**( ****first decade ****)**

**230,000 acres of habitat**
**were lost range wide to**
**wildfire in the 1****st**** decade.**
**About a 1.3% decrease**
**across the range.**
**About 5x as much than**
**was lost from clearcut**
**timber harvesting.**

**7% Habitat Loss**
**( Klamath )**

**1% Habitat Loss**
**( East Cascades )**

**1% Habitat Loss**
**( West Cascades)**

## Spotted Owl

**NSO Demography Areas**

**Spotted Owl**
**Population Trends**
**( Anthony et al. 2005 )**

## Southwestern Oregon

_**Southwestern Oregon**_
**Stationary populations**
**Active wildfire history**

**Conceptual **
**Landscape**
**Analysis Area**

## Analysis Area

**Analysis Area**
**Location Map**

**Medford**

**Ashland**

**Grants Pass**

**Roseburg**

**Coos Bay**

**8.2 million total acres**
**41% Federal land**

**Southern Oregon**
**Coastal Basin **
**( HUC 3 )**

## Analysis Area

**Analysis Area**
**Location Map**

**Medford**

**Ashland**

**Grants Pass**

**Roseburg**

**Coos Bay**

**USFS = 2,039,431 ac**
**BLM = 1,292,492 ac**
**NPS = 36,639 ac**

## Conceptual Model

**Spotted Owl Elements**

- Crown Fire
- Potential

- Wildfire
- Density

- Condition
- Class

- Reserved
- Allocations

- Habitat
- Connectivity

- Owl
- Presence

- Critical
- Habitat

- Composite
- Risk Map

- Composite
- Values Map

**Landscape Prioritization Map**

**Conceptual Model**

## WILDFIRE

**WILDFIRE**
**ELEMENTS**

## Crown Fire Modeling

**Crown Fire Modeling**
**( FlamMap 3.0 )**

## Fire “Validation”

**Fire “Validation”**

**Crown Fire Modeling**
**( FlamMap 3.0 )**

## Crown Fire Potential

**Crown Fire Potential**
**( binary map - 0 or 1 )**

## Lightning Ignitions

**Lightning Ignitions**
**( 1970-2002 )**

## Lightning Ignition Density

**High density**

**Lightning Ignition Density**
**( 1970-2002 )**

## Wildfire Density

**Wildfire Density**
**( binary map - 0 or 1 )**

## Fire Regime – Condition Class

**Fire Regime – Condition Class**
**( Landfire Rapid Assessment )**

**Condition**
**Class 2**

**Condition**
**Class 3**

**Condition**
**Class 1**

## SPOTTED OWL

**SPOTTED OWL**
**ELEMENTS**

## NSO Critical Habitat Units

**NSO Critical Habitat Units**
**( binary map – 0 or 1 )**

- USFWS 1992

## NWFP Reserved Allocations

**NWFP Reserved Allocations**
**( binary map – 0 or 1 )**

- FEMAT 1994

## NSO Habitat Connectivity

- Lint et al. 2005

**NSO Habitat Connectivity**
**( binary map – 0 or 1 )**

## NSO Owl Pair Territories

- Lint et al. 2005

**NSO Owl Pair Territories**
**( binary map – 0 or 1 )**

## Putting It Together

## Fire Risk

- Crown Fire
- Potential

- Wildfire
- Density

- Condition
- Class

**Fire Risk**
**Composite Map**

## Habitat Value

- Critical
- Habitat

- Reserved
- Habitat

- Habitat
- Connectivity

- Owl
- Presence

**Habitat Value**
**Composite Map**

## Combined Composite Map

**Combined Composite Map**

**High Fire Risk & **
**High Habitat Value**

**Lower Fire Risk & **
**Low Habitat Value**

**Moderate Fire Risk & **
**Medium Habitat Value**

- High
- Priority
- Protection

- Lower
- Priority
- Protection

## Amount of Prioritized Treatment Acres

**Within Analysis Area**

## Application

- Cow Creek Project

## Slide 34

## 29,000 acres

- Tiller Ranger District
- Umpqua National Forest

## Fortune Branch

**Fortune Branch**

## USFS

**USFS**

**BLM**

## Slide 38

## Slide 39

## Slide 40

## Slide 41

## Critical

**Critical**
**habitat**
**unit**

**Critical**
**habitat**
**unit**

## Slide 43

## Slide 44

## High Priority Area

## Slide 46

## Recent fires

- (1974-2002)

## Historic fires

- (1936 forest map)

## Fire modeling

- (terrain)

## Fire modeling

- (current situation)

## Landscape Rx

- (proposed)

## Landscape Rx

- (proposed)

## Fuel breaks

- (planned)

## Fuel breaks

- (planned)

## High Priority Area

## Slide 56

## ?

## Take home messages

- Large-scale landscape analysis can focus land managers to key locations, given limited resources and staffing
- Possible mechanism for regulatory agency guidance and interagency collaboration
- Provides a purpose and need for the action agencies and aids in project planning

## Caveats

- This was only a conceptual example
- But...we did use real data and models...

## Thank you!