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Pinning Down the Change:
A Community-Level Study of Timberland Ownership Change
Photo credit: W.T. Smith Lumber Company: A chronicle
Anne Cumbie Randle, Becky Barlow, Andrew Gunnoe, John Gilbert, Auburn University
Introduction
Millions of Acres, Billions of Trees: Social and
Economic Impacts of Timberland Sales by the
Forest Products Industry in Alabama
โ€ข To document and analyze the social and economic impacts of
ownership and land use change affecting the single most
important manufacturing sector in Alabama
โ€ข To understand what timberland ownership change might mean
on a local level
The Study Area:
Baldwin, Clarke, Conecuh,
Escambia and Monroe
counties
Research objectives The Study Area Literature Review
Mapping Timberland
Ownership Change
Using GIS Analysis to
Explain Ownership
Change
Discussion and
Conclusion
Future Studies
The Study Area:
Evidence of forest
products industry
restructuring, 2012
Research objectives The Study Area Literature Review
Mapping Timberland
Ownership Change
Using GIS Analysis to
Explain Ownership
Change
Discussion and
Conclusion
Future Studies
Literature Review
โ€ข Ownership change in U.S. timberland
(Clutter et al. 2005, Gunnoe and Gellert 2010)
Forest Products Industry
10
million
acres
Corporate owners
(TIMOs and REITs)
Public and NGO
Non-Industrial
Private Forest owners
(NIPF)
Research objectives The Study Area Literature Review
Mapping Timberland
Ownership Change
Using GIS Analysis to
Explain Ownership
Change
Discussion and
Conclusion
Future Studies
Literature Review
โ€ข Who owns the forest (Butler and Wear 2011)
โ€“ Provides a basis for understanding how the forest
will be managed
โ€ข Using GIS to study land ownership change
(Scott and Janikas 2010)
Research objectives The Study Area Literature Review
Mapping Timberland
Ownership Change
Using GIS Analysis to
Explain Ownership
Change
Discussion and
Conclusion
Future Studies
Mapping Timberland Ownership Change:
Objectives
Research objectives The Study Area Literature Review
Mapping Timberland
Ownership Change
Using GIS Analysis to
Explain Ownership
Change
Discussion and
Conclusion
Future Studies
Objective 1: Map industrial
timberland ownership
circa 1990 in Escambia,
Baldwin, Clarke, Monroe,
and Conecuh counties
Objective 2: Identify
changes in industrial
timberland ownership as
of 2012
โ€ข Map industry ownership prior to land sales
โ€“ County plat books (1983 โ€“ 1991) were
georeferenced and digitized
โ€“ Industry owners were identified and timberland
was mapped
Mapping Timberland Ownership Change:
Methods
Research objectives The Study Area Literature Review
Mapping Timberland
Ownership Change
Using GIS Analysis to
Explain Ownership
Change
Discussion and
Conclusion
Future Studies
โ€ข Map industry ownership prior to land sales
โ€ข Overlay map of industry land with 2012
ownership maps
โ€“ 2012 ownership data was obtained
โ€“ New owners were identified and assembled into a
database
Mapping Timberland Ownership Change:
Methods
Research objectives The Study Area Literature Review
Mapping Timberland
Ownership Change
Using GIS Analysis to
Explain Ownership
Change
Discussion and
Conclusion
Future Studies
โ€ข Map industry ownership prior to land sales
โ€ข Overlay map of industry land with 2012
ownership maps
โ€ข New owners were categorized according to
ownership type and location, use change
identified
โ€“ Alabama Government Records Inquiry System,
2012 Current Use Tax Roll, USDA Orthoimagery
โ€“ Tax roll mailing address
Mapping Timberland Ownership Change:
Methods
Research objectives The Study Area Literature Review
Mapping Timberland
Ownership Change
Using GIS Analysis to
Explain Ownership
Change
Discussion and
Conclusion
Future Studies
Mapping
Timberland
Ownership
Change:
Results
Industry owned
land 1983 - 1991:
total of 925,211
acres
Research objectives The Study Area Literature Review
Mapping Timberland
Ownership Change
Using GIS Analysis to
Explain Ownership
Change
Discussion and
Conclusion
Future Studies
1983-1991
18 owners
Mapping Timberland Ownership Change: Results
Research objectives The Study Area Literature Review
Mapping Timberland
Ownership Change
Using GIS Analysis to
Explain Ownership
Change
Discussion and
Conclusion
Future Studies
1983-1991 2012
18 owners 1,822 owners
Mapping Timberland Ownership Change: Results
Research objectives The Study Area Literature Review
Mapping Timberland
Ownership Change
Using GIS Analysis to
Explain Ownership
Change
Discussion and
Conclusion
Future Studies
84%
16%
1983 - 1991
Top 5 Owners Everybody Else
53%47%
2012
Ownership Concentration
Mapping Timberland Ownership Change: Results
Research objectives The Study Area Literature Review
Mapping Timberland
Ownership Change
Using GIS Analysis to
Explain Ownership
Change
Discussion and
Conclusion
Future Studies
New owners of former industry land, 2012
Counties Industry % Corporate % NIPF % Gov. %
Use
Change
%
Total: 172,074 18% 575,263 63% 91,218 10% 56,729 6% 15,483 1.7%
Mapping Timberland Ownership Change:
Results
Research objectives The Study Area Literature Review
Mapping Timberland
Ownership Change
Using GIS Analysis to
Explain Ownership
Change
Discussion and
Conclusion
Future Studies
Industry
Corporate
NIPF
Government
Use Change
New owners of
former industry
land by class, 2012
Mapping
Timberland
Ownership Change:
Results
Research objectives The Study Area Literature Review
Mapping Timberland
Ownership Change
Using GIS Analysis to
Explain Ownership
Change
Discussion and
Conclusion
Future Studies
Mapping Timberland Ownership Change: Results
Research objectives The Study Area Literature Review
Mapping Timberland
Ownership Change
Using GIS Analysis to
Explain Ownership
Change
Discussion and
Conclusion
Future Studies
โ€ขAbsentee owned industry land in 1983
โ€“ 1991: 771,593 acres
โ€ขAbsentee owned former industry land
2012: 744,966 (increase of 10,569)
โ€ขTwo-sample t-test shows significant
increase in local ownership (P = .016, T
= -40.16, N=1)
โ€ขStill, absentee ownership accounted
for 83% of this land
Mapping
Timberland
Ownership Change:
Results
Research objectives The Study Area Literature Review
Mapping Timberland
Ownership Change
Using GIS Analysis to
Explain Ownership
Change
Discussion and
Conclusion
Future Studies
Using GIS Analysis to Explain Ownership Change:
Objectives
Research objectives The Study Area Literature Review
Mapping Timberland
Ownership Change
Using GIS Analysis to
Explain Ownership
Change
Discussion and
Conclusion
Future Studies
Objective 1: Map industrial
timberland ownership circa
1990 in Escambia, Baldwin,
Clarke, Monroe, and
Conecuh counties
Objective 2: Identify
changes in industrial
timberland ownership as of
2012
Objective 3: Explain what
influenced new timberland
owners and where that
change is concentrated
Explanatory Variables Relationship
Adjusted R2
(OLS)
GWR Sigma GWR R2 GWR R2
Adjusted
Government
Percent Poverty + 0.63
1.3 0.78 0.71
Percent Population with Bachelorโ€™s
Degree
- 0.39
Distance to Roads + 0.05
Distance to Place + 0.04
Distance to Water - 0.04
Corporate
Distance to Place + 0.05
3.18 0.44 0.37
Percent Unemployment + 0.02
Median House Value - 0.01
Median Household Income - 0.01
Percent Population with Bachelorโ€™s
Degree
- 0.00
NIPF
Distance to Place - 0.04
8.27 0.41 0.39
Percent Population with Bachelorโ€™s
Degree
- 0.04
Median Household Income - 0.03
Percent Unemployment + 0.00
Median House Value - 0.00
Change in Use
Percent Population with Bachelorโ€™s
Degree
+ 0.94
2.82 0.61 0.51
Percent Poverty - 0.71
Distance to Roads - 0.20
Distance to Place - 0.13
Distance to Water - 0.04
Using GIS Analysis to Explain Ownership Change:
Geographically Weighted Regression Analysis
Research objectives The Study Area Literature Review
Mapping Timberland
Ownership Change
Using GIS Analysis to
Explain Ownership
Change
Discussion and
Conclusion
Future Studies
Using GIS Analysis to
Explain Ownership
Change:
Hot Spot Analysis
Clusters of NIPF landowners may
lead to increased disturbance rates
in these areas
Research objectives The Study Area Literature Review
Mapping Timberland
Ownership Change
Using GIS Analysis to
Explain Ownership
Change
Discussion and
Conclusion
Future Studies
โ€ข Industry has sold almost all the land owned in the study area
โ€ข New owners are primarily corporate, followed by NIPF and
government
โ€ข 1.7% of land changed in use
โ€ข Local ownership has significantly increased, but absentee ownership
still accounts for 83% of the land
โ€ข New government land was negatively influenced by higher quality of
life variables and positively influenced by distance to roads and place.
Use change was almost exactly the opposite.
โ€ข NIPF and Corporate timberland owners were negatively influenced by
quality of life variables.
Discussion and Conclusion
Research objectives The Study Area Literature Review
Mapping Timberland
Ownership Change
Using GIS Analysis to
Explain Ownership
Change
Discussion and
Conclusion
Future Studies
โ€ขInterview NIPF and Corporate owners to find what variables
influenced them to purchase land in this area
โ€ขReplicate this study in different areas of the state
โ€ขContinue mapping these parcels in the future, or from an
earlier point in time, to show how they change over time
โ€ขDetermine if the potential outcomes do occur in the future
in this area
Research objectives The Study Area Literature Review
Mapping Timberland
Ownership Change
Using GIS Analysis to
Explain Ownership
Change
Discussion and
Conclusion
Future Studies
Future Studies
Acknowledgements
Dr. Larry Teeter, Dr. Conner Bailey, Dr. John Kush
Pinning Down the Change:
A Community-Level Study of Timberland Ownership Change
Variables Used in Exploratory
Regression
Significant Variables Not Significant or Redundant
Variables
Percent Poverty Percent Poverty Percentage of Population with
a High School Degree
Percent Unemployment Percent Unemployment Distance to Shoreline
Median Housing Value Median Housing Value Distance to Conservation
Easements
Percentage of Population with
a High School Degree
Percentage of Population with
a Bachelorโ€™s Degree
Population
Percentage of Population with
a Bachelorโ€™s Degree
Median Income
Median Income Distance to Bodies of Water
Population Distance to Roads
Distance to Bodies of Water Distance to Place
Distance to Roads
Distance to Shoreline
Distance to Conservation
Easements
Distance to Place
Corporate Timberland Owners
Real Estate Investment
Trusts (REITs)
โ€ข Invest the capital of
many investors to
garner returns for
investors
โ€ข May or may not be
publicly traded
โ€ข Institutional as well as
individual investors,
most shares are owned
by mutual funds
Timber Investment
Management
Organizations (TIMOs)
โ€ข Management
companies that work on
behalf of investors to
buy, sell, and manage
timberland
โ€ข Most are not publicly
traded
โ€ข Pension funds,
endowments,
foundations, insurance
firms

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Pinning Down the Change: A Community-Level Study of Timberland Ownership Change

  • 1. Pinning Down the Change: A Community-Level Study of Timberland Ownership Change Photo credit: W.T. Smith Lumber Company: A chronicle Anne Cumbie Randle, Becky Barlow, Andrew Gunnoe, John Gilbert, Auburn University
  • 2. Introduction Millions of Acres, Billions of Trees: Social and Economic Impacts of Timberland Sales by the Forest Products Industry in Alabama โ€ข To document and analyze the social and economic impacts of ownership and land use change affecting the single most important manufacturing sector in Alabama โ€ข To understand what timberland ownership change might mean on a local level
  • 3. The Study Area: Baldwin, Clarke, Conecuh, Escambia and Monroe counties Research objectives The Study Area Literature Review Mapping Timberland Ownership Change Using GIS Analysis to Explain Ownership Change Discussion and Conclusion Future Studies
  • 4. The Study Area: Evidence of forest products industry restructuring, 2012 Research objectives The Study Area Literature Review Mapping Timberland Ownership Change Using GIS Analysis to Explain Ownership Change Discussion and Conclusion Future Studies
  • 5. Literature Review โ€ข Ownership change in U.S. timberland (Clutter et al. 2005, Gunnoe and Gellert 2010) Forest Products Industry 10 million acres Corporate owners (TIMOs and REITs) Public and NGO Non-Industrial Private Forest owners (NIPF) Research objectives The Study Area Literature Review Mapping Timberland Ownership Change Using GIS Analysis to Explain Ownership Change Discussion and Conclusion Future Studies
  • 6. Literature Review โ€ข Who owns the forest (Butler and Wear 2011) โ€“ Provides a basis for understanding how the forest will be managed โ€ข Using GIS to study land ownership change (Scott and Janikas 2010) Research objectives The Study Area Literature Review Mapping Timberland Ownership Change Using GIS Analysis to Explain Ownership Change Discussion and Conclusion Future Studies
  • 7. Mapping Timberland Ownership Change: Objectives Research objectives The Study Area Literature Review Mapping Timberland Ownership Change Using GIS Analysis to Explain Ownership Change Discussion and Conclusion Future Studies Objective 1: Map industrial timberland ownership circa 1990 in Escambia, Baldwin, Clarke, Monroe, and Conecuh counties Objective 2: Identify changes in industrial timberland ownership as of 2012
  • 8. โ€ข Map industry ownership prior to land sales โ€“ County plat books (1983 โ€“ 1991) were georeferenced and digitized โ€“ Industry owners were identified and timberland was mapped Mapping Timberland Ownership Change: Methods Research objectives The Study Area Literature Review Mapping Timberland Ownership Change Using GIS Analysis to Explain Ownership Change Discussion and Conclusion Future Studies
  • 9. โ€ข Map industry ownership prior to land sales โ€ข Overlay map of industry land with 2012 ownership maps โ€“ 2012 ownership data was obtained โ€“ New owners were identified and assembled into a database Mapping Timberland Ownership Change: Methods Research objectives The Study Area Literature Review Mapping Timberland Ownership Change Using GIS Analysis to Explain Ownership Change Discussion and Conclusion Future Studies
  • 10. โ€ข Map industry ownership prior to land sales โ€ข Overlay map of industry land with 2012 ownership maps โ€ข New owners were categorized according to ownership type and location, use change identified โ€“ Alabama Government Records Inquiry System, 2012 Current Use Tax Roll, USDA Orthoimagery โ€“ Tax roll mailing address Mapping Timberland Ownership Change: Methods Research objectives The Study Area Literature Review Mapping Timberland Ownership Change Using GIS Analysis to Explain Ownership Change Discussion and Conclusion Future Studies
  • 11. Mapping Timberland Ownership Change: Results Industry owned land 1983 - 1991: total of 925,211 acres Research objectives The Study Area Literature Review Mapping Timberland Ownership Change Using GIS Analysis to Explain Ownership Change Discussion and Conclusion Future Studies
  • 12. 1983-1991 18 owners Mapping Timberland Ownership Change: Results Research objectives The Study Area Literature Review Mapping Timberland Ownership Change Using GIS Analysis to Explain Ownership Change Discussion and Conclusion Future Studies
  • 13. 1983-1991 2012 18 owners 1,822 owners Mapping Timberland Ownership Change: Results Research objectives The Study Area Literature Review Mapping Timberland Ownership Change Using GIS Analysis to Explain Ownership Change Discussion and Conclusion Future Studies
  • 14. 84% 16% 1983 - 1991 Top 5 Owners Everybody Else 53%47% 2012 Ownership Concentration Mapping Timberland Ownership Change: Results Research objectives The Study Area Literature Review Mapping Timberland Ownership Change Using GIS Analysis to Explain Ownership Change Discussion and Conclusion Future Studies
  • 15. New owners of former industry land, 2012 Counties Industry % Corporate % NIPF % Gov. % Use Change % Total: 172,074 18% 575,263 63% 91,218 10% 56,729 6% 15,483 1.7% Mapping Timberland Ownership Change: Results Research objectives The Study Area Literature Review Mapping Timberland Ownership Change Using GIS Analysis to Explain Ownership Change Discussion and Conclusion Future Studies Industry Corporate NIPF Government Use Change
  • 16. New owners of former industry land by class, 2012 Mapping Timberland Ownership Change: Results Research objectives The Study Area Literature Review Mapping Timberland Ownership Change Using GIS Analysis to Explain Ownership Change Discussion and Conclusion Future Studies
  • 17. Mapping Timberland Ownership Change: Results Research objectives The Study Area Literature Review Mapping Timberland Ownership Change Using GIS Analysis to Explain Ownership Change Discussion and Conclusion Future Studies
  • 18. โ€ขAbsentee owned industry land in 1983 โ€“ 1991: 771,593 acres โ€ขAbsentee owned former industry land 2012: 744,966 (increase of 10,569) โ€ขTwo-sample t-test shows significant increase in local ownership (P = .016, T = -40.16, N=1) โ€ขStill, absentee ownership accounted for 83% of this land Mapping Timberland Ownership Change: Results Research objectives The Study Area Literature Review Mapping Timberland Ownership Change Using GIS Analysis to Explain Ownership Change Discussion and Conclusion Future Studies
  • 19. Using GIS Analysis to Explain Ownership Change: Objectives Research objectives The Study Area Literature Review Mapping Timberland Ownership Change Using GIS Analysis to Explain Ownership Change Discussion and Conclusion Future Studies Objective 1: Map industrial timberland ownership circa 1990 in Escambia, Baldwin, Clarke, Monroe, and Conecuh counties Objective 2: Identify changes in industrial timberland ownership as of 2012 Objective 3: Explain what influenced new timberland owners and where that change is concentrated
  • 20. Explanatory Variables Relationship Adjusted R2 (OLS) GWR Sigma GWR R2 GWR R2 Adjusted Government Percent Poverty + 0.63 1.3 0.78 0.71 Percent Population with Bachelorโ€™s Degree - 0.39 Distance to Roads + 0.05 Distance to Place + 0.04 Distance to Water - 0.04 Corporate Distance to Place + 0.05 3.18 0.44 0.37 Percent Unemployment + 0.02 Median House Value - 0.01 Median Household Income - 0.01 Percent Population with Bachelorโ€™s Degree - 0.00 NIPF Distance to Place - 0.04 8.27 0.41 0.39 Percent Population with Bachelorโ€™s Degree - 0.04 Median Household Income - 0.03 Percent Unemployment + 0.00 Median House Value - 0.00 Change in Use Percent Population with Bachelorโ€™s Degree + 0.94 2.82 0.61 0.51 Percent Poverty - 0.71 Distance to Roads - 0.20 Distance to Place - 0.13 Distance to Water - 0.04 Using GIS Analysis to Explain Ownership Change: Geographically Weighted Regression Analysis Research objectives The Study Area Literature Review Mapping Timberland Ownership Change Using GIS Analysis to Explain Ownership Change Discussion and Conclusion Future Studies
  • 21. Using GIS Analysis to Explain Ownership Change: Hot Spot Analysis Clusters of NIPF landowners may lead to increased disturbance rates in these areas Research objectives The Study Area Literature Review Mapping Timberland Ownership Change Using GIS Analysis to Explain Ownership Change Discussion and Conclusion Future Studies
  • 22. โ€ข Industry has sold almost all the land owned in the study area โ€ข New owners are primarily corporate, followed by NIPF and government โ€ข 1.7% of land changed in use โ€ข Local ownership has significantly increased, but absentee ownership still accounts for 83% of the land โ€ข New government land was negatively influenced by higher quality of life variables and positively influenced by distance to roads and place. Use change was almost exactly the opposite. โ€ข NIPF and Corporate timberland owners were negatively influenced by quality of life variables. Discussion and Conclusion Research objectives The Study Area Literature Review Mapping Timberland Ownership Change Using GIS Analysis to Explain Ownership Change Discussion and Conclusion Future Studies
  • 23. โ€ขInterview NIPF and Corporate owners to find what variables influenced them to purchase land in this area โ€ขReplicate this study in different areas of the state โ€ขContinue mapping these parcels in the future, or from an earlier point in time, to show how they change over time โ€ขDetermine if the potential outcomes do occur in the future in this area Research objectives The Study Area Literature Review Mapping Timberland Ownership Change Using GIS Analysis to Explain Ownership Change Discussion and Conclusion Future Studies Future Studies
  • 24. Acknowledgements Dr. Larry Teeter, Dr. Conner Bailey, Dr. John Kush Pinning Down the Change: A Community-Level Study of Timberland Ownership Change
  • 25.
  • 26. Variables Used in Exploratory Regression Significant Variables Not Significant or Redundant Variables Percent Poverty Percent Poverty Percentage of Population with a High School Degree Percent Unemployment Percent Unemployment Distance to Shoreline Median Housing Value Median Housing Value Distance to Conservation Easements Percentage of Population with a High School Degree Percentage of Population with a Bachelorโ€™s Degree Population Percentage of Population with a Bachelorโ€™s Degree Median Income Median Income Distance to Bodies of Water Population Distance to Roads Distance to Bodies of Water Distance to Place Distance to Roads Distance to Shoreline Distance to Conservation Easements Distance to Place
  • 27. Corporate Timberland Owners Real Estate Investment Trusts (REITs) โ€ข Invest the capital of many investors to garner returns for investors โ€ข May or may not be publicly traded โ€ข Institutional as well as individual investors, most shares are owned by mutual funds Timber Investment Management Organizations (TIMOs) โ€ข Management companies that work on behalf of investors to buy, sell, and manage timberland โ€ข Most are not publicly traded โ€ข Pension funds, endowments, foundations, insurance firms

Editor's Notes

  1. Forest Inventory Data Online (FIDO). 2012. USDA Forest Service
  2. USDA Forest Service. 2005, 1999
  3. Top ownership class is now corporate (63%), then industry (18%) Industry land is primarily owned by Cedar Creek/T.R. Miller, but includes new industrial companies that have formed
  4. The Mobile-Tensaw Delta and Perdido River-Longleaf Hills tracts
  5. Many NIPF owners, most owned less than 2,000 acres and were located near the land they owned Corporate owners owned larger tracts and were located further away Spread of orange dots indicates many absentee investors
  6. Sigma = the estimated standard deviation for the residuals A higher Sigma value (SD) indicates that the variables were not consistent across the study area Also tested for high school degrees, population, distance to conservation easements, distance to shoreline (were not significant in any models)
  7. Getis-Ord Gi* , 99% confidence level