Assessing the Impact of Blister Rust Infected

Whitebark Pine in the Alpine Treelines of Glacier

National Park and the Beartooth Plateau, U.S.A.

Emily K. Smith-McKenna*

PhD Student, GEA program

Dr. Lynn M. Resler

Associate Professor

Department of Geography

Virginia Tech, U.S.A.

Topics Discussed

Background: Whitebark Pine, Blister Rust,

and Treeline

Data Collection and Analysis

Preliminary Findings

Continuing Research

Importance of Whitebark Pine (Pinus albicaulis)

A high elevation five-needled white pine that serves multiple

roles as a foundation and keystone species (Keane and Arno, 1993; Kendall, 1994; Resler and Tomback, 2008)

Provides many ecosystem services:

Provides food for wildlife (Grizzly Bears, Red Squirrels, Clark’s Nutcracker)

Facilitates other tree species

Stabilizes soil, rock, preserves snowpack

Don Piggott USGS,1999

Decline of Whitebark Pine

Whitebark Pine is distributed throughout Western North American Mountain Ranges

Found in high elevation forests Subalpine, as erect trees

Alpine, dwarfed, krummholz form

One reason for decline (in addition to

mountain pine beetle, fire suppression)

is White Pine Blister Rust

(Cronartium ribicola) which has

devastated populations of

subalpine whitebark pine. (Keane and Arno, 1993)

Highest infection rate in subalpine

Northern Rockies Infection levels 70-90% (Kendall and Keane, 2001) (Kendall, 1995)

Blister Rust Incidence

Blister Rust canker

with aecial sacs on

Whitebark pine

Exotic, invasive, fungal disease (Cronartium ribicola)

Two host species needed to complete life cycle

White pine (host species)

Ribes species (alternate host species)

Black Currants, Gooseberries

Other potential alternate hosts are: Scarlet

Indian Paintbrush, and Sickletop Lousewort (McDonald et al., 2006)

Ribes spp.

Five cycles of spore production

Transfer between alternate host plant and

White pine

Returns to white pine to complete life cycle (Hoff and Hagle, 1990)

Ramifications to Alpine Treeline

Vegetation response to changing climate

(Hall and Fagre, 2003)

Blister rust was originally thought to be more prevalent in milder, moist climates (Van Arsdel et al.,1956)

Researchers have discovered that it can spread to dryer, colder regions of WBP ecosystems (Resler and Tomback, 2008)

How does disease effect treeline dynamics?

Declining WBP populations

Decline in tree islands?

Change in treeline dynamics

Treeline response to climate?

Research Objectives

1) To investigate and quantify blister rust incidence and

intensity in the alpine treeline ecotone

Across a N-S latitudinal range east of Continental Divide

Sample whitebark pine, enumerate cankers

Treeline study areas in Glacier National Park, Beartooth Plateau

2) To determine what environmental variables correlate

strongly to the intensity of blister rust incident areas.

Characterize the terrain and derive topographic factors with a

GPS-created DEM

GPS Whitebark Pine and other conifers in plot

Derive variables in a GIS

Distance to water

Topographic variables

Sampling Blister Rust Incidence

Quadrat Sampling

Sample WBP/BR incidence at alpine treeline ecotone

15m x 15m Quads

15m

15m

• # Whitebark Pine

• # Cankers, if any

• Intensity of Blister Rust

• Measure environmental

conditions

Background Weather Data

Monitoring weather during growing season:

July-September

Wind direction/speed/gusts

Temp/Relative Humidity

Soil Moisture

PAR (photosynthetically

active radiation)

Modeling Terrain: Creating a High

Resolution Digital Elevation Model (DEM)

Create DEM for

each Quad in GNP

Generate Elevation

Surfaces

Geostatistical Analysis

= Finalize DEMs

GPS-derived DEM

Pilot Study

•Compare w/ LiDAR

•Develop field technique

(MS. in progress, Smith et al.)

Data Analysis: Derive Variables in GIS

• Slope

• Aspect

• Curvature

• Flow Accumulation

• Potential Solar Radiation

• Distance to Perennial Stream

• Distance to Lakes

• Distance to Wetlands

Derive Variables in GIS

Data Analysis: Compare to Field Observations

• Slope

• Aspect

• Curvature

• Flow Accumulation

• Potential Solar Radiation

• Distance to Perennial Stream

• Distance to Lakes

• Distance to Wetlands

Derive Variables in GIS

• Density of Blister Rust:

Total Cankers per Whitebark

Compare Variables to

Blister Rust Intensity

Treeline Research: 2008

2008 Research Study, Glacier National Park (M.S. Thesis work)

30 sampling plots

Among 6 treelines

N = 333 WBP

46% BR infection

Largest WBP

population at

White Calf/Divide

Mountain

Treeline Research: 2010

2010 Research in Glacier National Park and Beartooth Plateau

(NSF Grant awarded to Lynn Resler, Diana Tomback, George Malanson)

30 sampling

plots Glacier NP

N = 581 WBP

24% BR infection

30 sampling

plots Beartooth

N = 326 WBP

20% BR infection

Treeline Implications

WBP growing in lee of rock

Dead WBP, former Initiator of tree island

Dead WBP, most due to Blister Rust

Treeline Implications

Size of patch seems to influence infection

A significant correlation (rs = 0.36, p < 0.001) existed between length of

the tree island and incidence of active and inactive blister rust cankers.

Length of the longest dimension of the tree islands ranged from 0.02 to

35 m. (Resler and Tomback, 2008).

Whitebark pine associated with tree islands had higher blister rust

intensity than solitary trees. (Smith, 2009)

Whitebark pine in tree islands: N=219, 56% infected, 581 total cankers (2.65 cankers per tree)

Solitary whitebark pine: N=114, 29% infected, 97 total cankers (0.85 cankers per tree)

Treeline Implications

How does Blister Rust affect treeline dynamics?

How will the absence of WBP affect

patch dynamics?

Research continues…

Expand latitudinal range of study Conduct WBP and Blister

Rust sampling in Jasper and Banff Park, Alberta Canada

Tree island metrics

Model surface terrain

Examine spatial relationships between environmental variables and blister rust incidence

Model Treeline Dynamics NetLogo

Consider environmental factors

Integrate field observations in a simulated, learning environment

Acknowledgements

Financial Support:

NSF, funded project awarded to Lynn Resler, Diana

Tomback, and George Malanson

Graduate Research Development Program, Virginia

Tech

Department of Geography, Virginia Tech

Field Assistance:

2010: Lauren Franklin, Kathryn Prociv, Diana

Tomback, Jill Pyatt, Sarah Blakeslee

2008: Lynn Resler, Amos Desjardins,

Allisyn Hudson-Dunn, Cindy Smith, Matt Foley

Questions?

References Cited

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