Using a Geoprocessing Script to Aid in the Exploration of Linkages between Southern Pine

Beetle Outbreaks and Forest Density

Dahl Winters

December 6, 2006

Introduction

Southern pine beetle (Dendroctonus frontalis) is the most destructive insect to pine trees.

Vast numbers of individuals can become infested and die, with large ecological and economic consequences.

Images from http://www.na.fs.fed.us/spfo/pubs/fidls/so_pine_beetle/so_pine.htm andhttp://www.srs.fs.usda.gov/econ/data/spb/

Questions

How might SPB infestations correlate withthe density of various forest types?

Questions that might be answered by answering the above:

• Are SPB infestations more severe in pine plantations?

• How might smaller, more mixed stands of pine-hardwood trees contribute to outbreak severity?

Data and Outline of Approach

1. Land Cover Data: This data will be taken from the 2001 National Land Cover Dataset (NLCD 2001) – free download from the USGS Seamless Data Server.

2. SPB Infestation Data by County from 1960-2004

-Goal is to explore the environmental correlates (i.e. different quantities and patterns of forest cover) of SPB outbreaks.

-Will focus attention on one region in one year

-1) identify and isolate SPB habitat and non-habitat from the NLCD 2001 raster dataset

-2) Identify and isolate SPB infestation data for all counties in NC and SC in 2001

Methods

NLCD 2001 Land Cover

1960-2004 SPB Infestation

Data

Reclassified LULC data into 3 classes

Extract by Mask to get LULC for just NC and SC

Mosaic to join the two LULC rasters

Wrote Python code to extract LULC rasters

for each county

Copy pixel counts for the 3 classes into an Excel spreadsheet

Spatial Join to Infested Counties layer using

FIPS code to get desired graphs later

Select by Attributes to get just NC and SC

data for 2001

Normalization: use Editor to calculate

values for pixel counts (one pixel = 30 sq m)

Graph infestation severity vs. percent

cover types

Fit linear regressions to

graphs to quantify trends

Generate choropleth maps of each cover

type to show distribution

NLCD 2001 Reclassification

1. Definitely Habitat for SPB:

Evergreen Forest (42)

2. Potential Habitat for SPB:

Developed, Low Intensity (22) – SPB often attack stressed and injured trees in older-aged dense stands – some neighborhoods might have these

Deciduous Forest (41) – might be small isolated populations of pine trees here that serve as stepping stones for SPB dispersal

Mixed Forest (43) – likely to have more pine stands than deciduous forest

3. Non-Habitat for SPB:Open Water (11)Developed, Open Space (21)Developed, Medium Intensity (23)Developed, High Intensity (24)Barren Land (Rock/Sand/Clay) (31)Shrub/Scrub (52) – since SPB attacks

only mature trees, and the trees in this category would be young, early successional ones

Grassland/Herbaceous (71)Pasture/Hay (81)Cultivated Crops (82)Woody Wetlands (90)Emergent Herbaceous Wetlands (95)

Land Cover and Counties

Python Geoprocessing Script

Virtual memory problems…

Maps and Graphs

Calculated the following 4 percentages:

• percent pine forest = pine pixels/total pixels * 100• percent potential habitat = potential pixels/ total pixels * 100• percent forested = pine+potential habitat/total pixels * 100 • percent non-habitat = non-habitat pixels/total pixels * 100 (just the

inverse of percent forested)

Generated several maps using each of these percentages to visually estimate if there might be any correlations between infestation severity and the amount of different habitat types.

Percent Pine Forest

Percent Potential Habitat

Percent Forested (Pine + Potential)

Results - Percent Forest Coverage

Percent Pine Forest vs. Infestation Severity y = -0.2822x + 8.6383

R2 = 0.0418

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Percent Pine Forest

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Percent Potential Habitat vs. Infestation Severity y = 0.2433x - 3.5999

R2 = 0.1616

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Percent Potential Habitat

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The values on the X-axis have been normalized to represent (area of forest type / total forest area) * 100.

• As the percent of pine forest increases, interestingly the infestation severity decreases. This is opposite of what was expected.

• However, as the percent of smaller and more mixed pine-hardwood stands increases, infestation severity increases – 0.24 more infestations per 1000 acres for every % increase in potential habitat.

Results - Percent Forest Coverage

Percent Forest vs. Infestation Severity y = 0.2619x - 8.5805

R2 = 0.1353

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Percent Forest

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• As the percent of both pine forest and smaller, mixed pine-hardwood forest increases, infestation severity increases more strongly from 0.24 to 0.26 infestations/1000 acres/% increase of forest area.

• Another way to look at this: the more non-habitat, the lower the infestation severity, which is expected since there are fewer places for SPB to exist.

Conclusion

• Prevention of SPB outbreaks should not focus on just pine plantations.

• Smaller, more mixed stands of pine in both natural and residential areas are important to SPB outbreaks—there are more of them and are more widely spread

• The connectivity of these smaller mixed stands is likely more important than we think it is, and merits further research into how it might affect SPB spread

• Further research directions: use more of the 1960-2004 infestation data to see how land cover correlates with SPB outbreaks over time