United States

Department of

Agriculture

Forest Service

Southern 

Research Station

General Technical 

Report SRS–139

Black Belt Landowners Respond to

State-Sponsored Wildland Fire 

Mitigation Policies and Programs

Cassandra Johnson-Gaither, Jianbang Gan, Adam Jarrett, 

Miriam S. Wyman, Sparkle Malone, Keenan J. Adams,

J.M. Bowker, and Taylor V. Stein 
The Authors: 

Cassandra Johnson-Gaither is a Research Social Scientist, USDA Forest 

Service, Southern Research Station, Forestry Sciences Laboratory, Athens, GA 

30602-2044; Jianbang Gan is a Professor and Associate Department Head for 

Graduate Programs, Texas A&M University, Department of Ecosystem Science and 

Management, College Station, TX 77843-2138; Adam Jarrett is a Superintendent, 

Parrie Haynes Ranch State Park, Texas Parks and Wildlife Department, Killen, TX 

76549; Miriam S. Wyman is an Adjunct Assistant Professor, Utah State University, 

College of Natural Resources, Department of Environment and Society, Logan, 

UT 84322-5200; Sparkle Malone is a Graduate Student, University of Alabama, 

Department of Biological Sciences, Tuscaloosa, AL 35487-0118; Keenan J. Adams

is a Deputy Refuge Manager, U.S. Fish and Wildlife Service, Vero Beach, FL 

32960-3559; J.M. Bowker is a Research Social Scientist, USDA Forest Service, 

Southern Research Station, Forestry Sciences Laboratory, Athens, GA 30605; and 

Taylor V. Stein is an Associate Professor, University of Florida, School of Forest 

Resources and Conservation, Gainesville, FL 32611-0411.

Cover: Fire running uphill. (Image by Philip Juras)

August 2011 

Southern Research Station 

200 W.T. Weaver Blvd. 

Asheville, NC 28804
Black Belt Landowners Respond to 

State-Sponsored Wildland Fire Mitigation 

Policies and Programs

Cassandra Johnson-Gaither, Jianbang Gan, Adam Jarrett, Miriam S. Wyman, 

Sparkle Malone, Keenan J. Adams, J.M. Bowker, and Taylor V. Stein 

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Southern Wildfire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Wildland-Urban Interface and Fire in the South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Citizen Knowledge and Awareness of State-Sponsored Wildland Fire Mitigation Programs . . . . . . . . . . . . . . . . . . . 4

Hypotheses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Data Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Statistical Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Logistic Regression Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Bivariate Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Logistic Regression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Discussion and Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Page

Contents

iii

Abstract

This investigation focused on nonindustrial private forest (NIPF) 

landowners in selected counties across five States in the Southeastern 

United States (Alabama, Florida, Georgia, Mississippi, and South 

Carolina). These counties are located in the Southern Black Belt region, 

which has higher than average percentages of African-American 

residents and higher poverty rates than the United States as a whole. 

We assessed African-American and White private landowner awareness 

and responsiveness to State-sponsored wildland fire mitigation policies 

and programs. Other indicators of environmental awareness and 

engagement suggest that African-Americans rank lower than Whites on 

these measures in the South. We extend this research with a focus on 

awareness and responsiveness to wildland fire mitigation programming.

African-American landowners were more likely to be aware than White 

landowners of wildland fire mitigation programs, but less likely than 

Whites to use such information and less likely to engage in various 

other actions to reduce wildland fire threats to their property. In terms 

of constraints, African Americans who did not request mitigation 

information were more likely than Whites to say they did not do so 

because they did not know the information was available. However, 

African Americans were less likely to say lack of trust prevented them 

from requesting information. Overall, findings did not suggest that 

Black Belt African-American landowners were disadvantaged with 

respect to either information awareness or acquisition; but results 

should be taken with caution given that nonrandom sampling was used 

for some data collection with the African-American sample.

Keywords: African-American landowners, Black Belt, poverty, 

wildfire mitigation, wildland-urban interface. 

Introduction

The Southern Black Belt1 spans a geographical region 

descending from Virginia through the Carolinas and into 

Louisiana and east Texas (Rankin and Falk 1991, Wimberley 

and Morris 1997) (fig. 1). Booker T. Washington coined the 

descriptor at the turn of the 20th century, in reference to the 

region’s fertile black soil. Since then, the term has come 

to define counties with African-American2 populations at 

least equal to the national average (Allen-Smith and others 

2000).3 In addition to demography, Webster and Bowman 

(2008) include other non-physiographic features such as 

economic, social, and political characteristics.

During the civil rights era, social and economic conditions 

in the South were highlighted by both grassroots and 

governmental efforts to end Jim Crow segregation. Forty 

years later, many would argue that the South as a whole is 

a different place, both economically and socially. However, 

conditions in persistently poor, rural Black Belt counties 

have not improved appreciatively. A study of Black Belt 

poverty commissioned by former Senator Zell Miller of 

Georgia found that in 2000, 13.6 million poor people lived in 

the South. This number represented 40 percent of total U.S. 

poverty, and this percentage is concentrated in the Black 

Belt (Carl Vinson Institute of Government 2002). During 

the 1990s, significantly fewer jobs were created in the Black 

Belt relative to other places in the South, and unemployment 

rates exceeded national averages (Gibbs 2003). Womack 

(2007) writes of the region: “By most definitions, the Black 

Belt is America’s Third World....The relationship between 

this region and poverty is unmistakable, with 280 of the 444 

persistent poverty counties being located there.”

This investigation addresses Task 2 of the 2005 Joint Fire 

Science Program (JFSP) involving citizen knowledge and 

awareness of State-sponsored wildland fire mitigation 

programs. The JFSP was established in 1998 as an 

interagency project designed to fund research, development, 

and applications related to fire science. The JFSP is managed 

cooperatively between the U.S. Department of the Interior 

and the U.S. Department of Agriculture.

Our objective centers on African-American and White 

nonindustrial private forest (NIPF) landowners in selected 

counties across five States (Alabama, Florida, Georgia, 

Mississippi, and South Carolina) in the rural Black Belt. 

Black Belt Landowners Respond to State-Sponsored 

Wildland Fire Mitigation Policies and Programs 

Cassandra Johnson-Gaither, Jianbang Gan, Adam Jarrett, Miriam S. Wyman,

Sparkle Malone, Keenan J. Adams, J.M. Bowker, and Taylor V. Stein

1

The Black Belt comprises 623 counties contained in 11 States of the former 

Confederacy: Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, 

North Carolina, South Carolina, Tennessee, Texas, and Virginia. The region 

holds 18 percent of the Nation’s population (Allen-Smith and others 2000). 

These counties are mostly adjacent, although they span several States 

(Wimberley and Morris 1997).

2

African American and Black are used interchangeably.

3

Rankin and Falk (1991) offer a more conservative definition, specifying 

the Black Belt as those counties with a black population of 33 percent 

or more. 
To address the objective, we compared African-American 

and White landowner awareness and responsiveness to 

State-level wildland fire mitigation policies and programs in 

rural Black Belt counties. The audience for this publication 

is researchers, State and Federal fire managers, and 

policymakers.

Just over 71 percent of total forest land in the United States 

is in the South (Smith and others 2001). NIPF landowners 

hold 79 percent of all private timberland in the South 

(Wicker 2002). This figure represents about 140 million 

acres. The largest group of rural, minority landowners 

in the region is African-American (Wicker 2002). Table 

1 shows that in 2003 roughly 1.7 million acres of NIPF, 

family-owned forests in the South were held by 121,000 

African Americans. This represents a very small amount 

when compared to private land ownership by Whites. In 

terms of acreage, the ratio of African-American, familyowned forests to White, family-owned forests in the South is 

roughly 1 to 64.

Racial comparisons of mitigation policy and program 

awareness in the rural Black Belt command attention 

because of continuing social well-being gaps between 

African Americans and Whites in the region (Dyer and 

Bailey 2008, Dyer and others 2009, Zabawa 1991). 

According to Gibbs (2003), the poverty rate for Black Belt 

African Americans is three times the rate of White Black 

Belt dwellers; also, White poverty is lower in the Black Belt 

compared to other rural areas of the country. Moreover, 

research shows that predominantly African-American 

communities tend to have fewer environmental goods and 

services than White communities, and African Americans 

are more likely than Whites to cite lack of information about 

environmental resources as a reason for not engaging with 

these resources (Taylor 2000, Taylor and others 2007).

Southern Wildfire

Wildland fire behavior in the South varies depending on 

forest ecosystems (Monroe and others 2002). In marshes, 

swamplands, and bottomland hardwood stands fire is rare. 

Figure 1—The Black Belt: percentage of Black population in the U.S.

Percent by county

0.0 – 12.0

12.1 – 24.9

25.0 – 39.9

40.0 – 100.0 U. S. Census Bureau, 2007 estimated data.

The Black Belt: Percentage of Black population in U.S. counties

2
Fire occurs more often in pine and oak forests. Importantly, 

the South accounts for the largest number of wildland 

fires by region (National Interagency Fire Center, n.d.). In 

2007, 50 percent of all wildland fires reported in the nation 

occurred in the South; in 2006, more than one-half of all 

reported wildland fires in the Nation were in the South, and 

42 percent of all large wildland fires reported were in this 

region (Andreu and Hermansen-Báez 2008).

Historically, fire was central to the formation of southern 

forest ecosystems. Native Americans used prescribed fire 

regimes to manage wildland fires before the arrival of 

nonindigenous people. Early European settlers adopted 

these practices to help manage the landscape. The advent 

of plantation agriculture, turpentine/naval stores operations, 

logging, and railroad encroachment shifted the focus of 

southern landscapes from pine forests to agricultural lands 

(Monroe 2002). Since the 1930s, when agricultural products 

ceased to be the region’s primary economic output, fire 

suppression efforts have been put in place to aid forest 

recovery. As a result, fuel buildup in southern forests has 

produced the opposite effect. The 1998 Florida wildland 

fires demonstrated that southern forests and adjacent 

communities are not immune to wildland fire devastation 

(Macie and Hermansen 2002).

Wildland-Urban Interface and

Fire in the South

The climatic and biophysical features conducive to wildland 

fire in the South demand even greater attention when one 

considers the expanding wildland-urban interface (WUI) 

across the region. The WUI represents areas where human 

settlement intersects with wildlands. The South is still 

predominantly rural and contains 40 percent of the Nation’s 

farms, but the southern landscape is rapidly changing. The 

South contained 8 of the 10 fastest growing counties in the 

Nation, in terms of percentage population increase from 

2006 to 2007 (U.S. Census Bureau 2009). Population growth 

increases demand for housing and other development, 

much of which is occurring on lands directly adjacent to 

wildlands. Population growth in the WUI increases the 

likelihood of wildland fire ignition caused by humans 

(Macie and Hermansen 2002). People contribute to 93 

percent of all wildland fires in the South (Southern Group of 

State Foresters 2005). 

Less densely populated rural areas of the Black Belt are 

also important to consider in wildland fire mitigation 

and containment. These areas may not coincide with 

the expanding WUI4

 but have the added disadvantage 

of high poverty rates. In the West, non-WUI rural areas 

often contain communities with high poverty rates but less 

capacity for wildland fire mitigation compared to more 

densely populated WUI areas (Lynn and Gerlitz 2006). 

WUI expansion, typically lead by affluent migrants seeking 

aesthetic woodlands, has been criticized as an action that 

creates inequalities among lower and upper income groups 

(Collins 2008). WUI expansion can increase wildland fire 

risk for both those groups moving into the WUI and also 

for traditional settlements of lower income groups that 

may live either in the WUI or in adjacent non-WUI areas 

Table 1—Number of family-owned forests in the South and in the United States (excluding Alaska 

and Hawaii) 

Description 

Area Ownership

South United States South United States

(thousand acres) (thousand) 

Race

White 111,874 230,688 3,924 9,345

Black or African American 1,754 1,945 121 144

American Indian/Alaska Native 732 965 41 51

Asian 196 463 8 36

Native Hawaiian/Pacific Islander 225 307 24 58

Other 244 1,042 16 47

Two or more races 2,652 5,675 146 356

No answer 9,883 20,554 304 656

Ethnicity

Hispanic or Latino 513 1,718 38 143

Non-Hispanic/Latino 110,948 228,767 4,056 9,467

No answer 16,097 31,154 489 1,073

Source: National Woodland Owner Survey 2002-2003. http://www.ncrs.fs.fed.us/4801/national-programs/woodland-owners. 

 4Black Belt counties coterminous with WUI counties are located in coastal 

South Carolina, southeastern North Carolina, and southern Mississippi 

(Stewart and others 2003).

3
(Collins 2008). Importantly, inequalities can arise in cases 

where middle and upper income groups are able to insulate 

themselves from potential wildfire losses by purchasing 

insurance or demanding fire services. These buffers are less 

likely to exist for lower income groups.

Fire-prone conditions in the South, when coupled with 

historical patterns of social inequity and poverty in the 

Black Belt, raise questions about residents’ vulnerability to 

wildland fire and about resident engagement with wildland 

fire mitigation programs and policies. The following 

sections discuss project objectives with reference to the 

literature on heir property and cultural responses to wildland 

fire perception and mitigation. We then state research 

hypotheses, describe the methodology used to address our 

hypotheses, present analyses, and discuss findings.

Citizen Knowledge and Awareness

of State-Sponsored Wildland Fire

Mitigation Programs

The Forest Service’s Interim Strategic Public Outreach Plan 

(2000) indicated that African American forest landowners 

(most of whom reside in the South) see themselves 

as underserved or underrepresented landowners. This 

perception relates, in part, to historical discrimination 

patterns practiced by governmental agencies. Federal 

agencies are now attempting to better serve minority 

populations. Little information exists, however, regarding 

minority groups’ understanding about or participation 

in wildland fire mitigation programs, or about how they 

may differ from other minority or majority landowners in 

the region (Gan and others 2003). In a study of AfricanAmerican forest landowners in two Alabama Black Belt 

counties, Gan and Kolison (1999) found that fire prevention 

and protection were the most needed kinds of technical 

assistance for this group.

Another situation that complicates land stewardship for 

southern African Americans is the predominance of heir 

property or tenancy in common (Dyer and others 2009, 

Mitchell 2001). When freed slaves purchased or were 

deeded land after slavery, they commonly treated the land as 

communal property within the family. In many cases, land 

was passed to subsequent generations without having been 

probated. This has occurred over successive generations. 

Mitchell (2001) reports that 41 percent of AfricanAmerican-owned land in the Southeastern United States 

is heir property, although Dyer and others (2009) caution 

that accurate estimates of heir property have likely not been 

determined. This type of dispersed ownership makes it more 

difficult for residing landowners to follow best management 

practices for fire resistance or other purposes because of 

conflicts between residing and absentee landowners.

With respect to racial, ethnic, and cultural variation in 

attitudes about wildland fire, a limited number of studies 

suggest minorities have less knowledge than Whites about 

mitigation techniques or information sources for wildland 

fire protection. In a national study, Bowker and others 

(2005) found African Americans to be less knowledgeable 

than Whites about basic wildland fire information, to 

have less supportive attitudes about the usefulness of 

wildland fire for ecological maintenance, and to indicate 

less trust in governmental agencies for managing wildland 

fire. More recently, Bowker and others (2008) found that 

African Americans indicated less trust than Whites in land 

management agencies charged with reducing wildland fire 

threats.

Hypotheses

Based on the foregoing discussion, we propose the following 

research hypotheses:

H1

: Black Belt African Americans are less likely than 

Black Belt Whites to be aware of wildland fire 

mitigation policies and programs.

H2

: Black Belt African Americans are less likely than 

Black Belt Whites to request wildland fire mitigation 

information.

H3

: Black Belt African Americans are less likely than 

Black Belt Whites to receive wildland fire mitigation 

information.

H4: Black Belt African Americans are less likely than 

Black Belt Whites to use wildland fire mitigation 

information.

H5: Black Belt African Americans are less likely than 

Black Belt Whites to take “other” actions to reduce 

wildland fire threats to their property.

H6

: Black Belt African Americans are more likely than 

Black Belt Whites to cite barriers to requesting 

wildland fire information.

Methodology

To evaluate the study hypotheses, we obtained data from 

several sources. We first contacted State forestry agencies 

in Alabama, Florida, Georgia, Mississippi, and South 

Carolina to ascertain what type of wildland fire mitigation 

and education program the agency sponsored. Information 

about various Federal, State, and interagency fire education 

programs was also obtained online at the respective 

State forestry agency Web sites and collectively at www.

forestencyclopedia.com. We used information from these 

databases in addition to directly contacting State forestry 

agency personnel.

The survey contained questions relating to: (1) awareness 

of State-level wildland fire hazard mitigation programs and 

4
policy; (2) experience with and perception of wildland fire 

occurrence and other natural disturbances; (3) receipt and 

use of information about wildland fire mitigation policies 

and procedures; (4) requests for mitigation information 

and reasons for lack of requests; (5) landowner sources 

of information about mitigation; (6) preferred sources 

of information; (7) landowner actions taken to reduce 

wildland fire hazards; (8) preferences for State remediation 

of wildland fire threat; and (9) landowner interest in and 

awareness of biomass.

Data on land ownership characteristics were also solicited. 

These included amount of acreage owned, management 

objectives, whether land was classified as heir property, 

percentage of annual household income generated from 

land, whether respondents had a management plan for 

their land, and whether respondents lived on or personally 

managed their land.

Demographic data on land owner age, race, gender, 

education, and income level were also collected. The 

survey questions were developed in consultation with State 

foresters in each of the five States.

Data Collection

We collected data with two mail surveys, a telephone survey, 

and two face-to-face surveys. The sample was restricted to 

landowners with 10 acres or more of privately held land. 

Because of difficulties in obtaining responses from African 

Americans, we employed both random and nonrandom 

sampling techniques for this population. The nonrandom, 

face-to-face survey was used to obtain African-American 

responses because of extremely low African-American 

responses to a mail survey.

The first mail survey was administered by Texas A&M 

University from June 2007 to September 2007. The 

questionnaire was distributed to a randomly selected group 

of NIPF landowners in the selected counties (table A.1) 

in the five study States. The sampling frame for Florida, 

Georgia, and South Carolina landowners was county tax 

assessor rolls. We selected a random sample of 1,500 

potential respondents from these listings (500 per State). 

A random sample of landowners from the Mississippi and 

Alabama counties was supplied by project collaborators 

who had previously administered surveys to landowners in 

the counties of interest in these States. Counties within the 

five study States were selected based on the percentage of 

the population that was African-American (≥ 25 percent), 

percentage of forest land area in the county (≥ 33 percent), 

and the amount of “State” acreage burned by wildland fire 

over the period 1999-20035

 (table A.1). 

The Texas A&M survey was administered according to 

Dillman’s (1978) Total Design Method, with three mailings 

that included an initial mailing of the survey followed by a 

postcard reminder and a second mailing to those who had 

not responded. The obtained sample size was 583 (24.7 

percent response rate). This sample contained responses 

from only 44 African-American landowners (7.5 percent). 

Yet, the percentage of African-Americans in the counties 

we targeted ranged from 38.3 percent to 86.5 percent. We 

anticipated the need to augment the African-American 

sample with nonrandom sampling using either telephone or 

face-to-face methods. Past studies with African-American 

landowners have demonstrated the difficulty of obtaining 

adequate sample sizes from this population (Gan and 

Kolison 1999, Gan and others 2003).

A second data collection effort involved face-to-face 

interviews with African-American respondents. Two female, 

African-American interviewers were hired to administer 

surveys via a convenience sampling of attendees at three 

landowner conferences targeted to small landowners in the 

South: (1) the Federation of Southern Cooperatives Farmer’s 

Conference (Albany, GA, February 2008); (2) Alcorn 

University/Mississippi Association of Cooperatives Small 

Farmers Conference (Natchez, MS, March-April 2008); 

and (3) the Federation of Southern Cooperatives/Land 

Assistance Fund Conference (Epps, AL, August 2008). The 

sample size was 98, with 76 African-American, two White, 

one Native American, and one Asian-American respondent. 

Eighteen respondents indicated no race. We used only those 

respondents identified as African-American in the analyses. 

Two limitations were associated with these data. First, 

they were obtained by nonrandom sampling. Second, the 

respondents could have resided in counties other than those 

with ≥ 25 percent African-American representation or ≥ 33 

percent forest land cover.

A third effort to increase the number of Blacks in the sample 

was undertaken by the University of Florida (UF). This 

effort combined telephone and face-to-face interviews of 

landowners in four Florida counties (Gadsden, Hamilton, 

Jefferson, and Madison). These counties had been identified 

a priori as survey counties in Florida. Each met the criteria 

for inclusion in the study, in terms of percentage African 

American, amount of forest land area, and amount of 

State acreage burned by wildland fire. UF researchers 

worked through county extension agents in each county to 

obtain African-American landowner names and addresses. 

Interviewers then secured telephone numbers from the 

telephone directory in each county and contacted potential 

study participants either by phone or in person.

Because there were African-American landowners in the 

Florida counties who were unknown to the extension offices, 

UF researchers used cluster sampling to conduct face-toface interviews at the respondents’ residence. Researchers 

5

Fire cause and acreage calculated by year, State, and agency. Unpublished 

data. On file with the Southern Area Coordination Center, 1200 Ashwood 

Parkway, Suite 230, Atlanta, GA 30338. “State” incorporates all nonFederal acreage, including privately held land.

5
identified random streets covering diverse sections of each 

county on county maps, and then every third house with an 

African-American landowner was selected for interviewing. 

The address was checked against the extension list to ensure 

that landowner had not already been contacted by phone. 

Household relationships were also confirmed to ensure no 

two households interviewed belonged to the same extended 

family. Of 92 African-American households contacted in 

all four counties (either by phone list or random house 

selection), 77 respondents participated in the study for an 

83.6 percent response rate. 

Finally, we supplemented the African-American sample with 

57 observations from South Carolina. This data collection 

was conducted by Clemson University. The data were 

obtained in two ways. First, a mail survey was sent to a 

random sample of 250 potential respondents in Allendale, 

Bamberg, and Hampton Counties. These counties had also 

been identified as sampling areas at the beginning of the 

project, and each had the aforementioned qualities. The 

response rate was 42 percent, with eight African-American 

respondents. Again, a mail survey was not effective in 

providing an adequate African-American response rate. 

A second effort in South Carolina involved distributing 

200 questionnaires through county extension agents to 

African-American landowners in Charleston, Lee, Sumter, 

Anderson, and Williamsburg Counties. These counties also 

had substantial rural populations with high concentrations 

of African Americans. The questionnaires were distributed 

nonrandomly and involved face-to-face interviews. We 

obtained a 24.5 percent response rate with 49 completed 

interviews.

Because of differences in sampling among the four datasets, 

we compared the African-American sample in the Texas 

A&M mail survey and the three supplementary AfricanAmerican datasets in terms of gender, age, education, and 

income. The percent male for the Texas A&M mail survey 

was 67 percent, 63 percent for the face-to-face conference 

surveys, 57 percent for the UF survey, and 87 percent for 

the Clemson survey. The modal category of educational 

attainment was higher than a 4-year college degree for the 

Texas A&M mail survey; college for the conference surveys; 

and high school for the UF and Clemson samples. The 

modal income category was < $30,000 for all samples. Mean 

age was 60 (Texas A&M), 58 (conference), 58 (UF), and 58 

(Clemson).

These results indicated commonalities for income and 

age but larger variation for gender and education. We 

also recognized the potential bias, in terms of landowner 

awareness of wildland fire mitigation programs and 

policies, associated with a sample taken from attendees 

at conferences where the focus was landowner advocacy. 

Indeed, responses on a key indicator, awareness of wildland 

fire mitigation programs, indicated that a substantially 

higher percentage of respondents in the face-to-face survey 

administered at landowner conferences was aware of at least 

one wildland fire mitigation program (75 percent). This 

compared to only 45 percent of African Americans in the 

mail sample, 56 percent for the UF sample, and 52 percent 

for the Clemson survey.

We acknowledge the potential biases in combining these 

datasets; however, we believe the commonalities contained 

in the data and the potential for learning about AfricanAmerican landowners in the Black Belt outweigh any 

systematic differences that might be present. Furthermore, 

the difficulties of securing rural, African-American 

responses justify the inclusion of nonrandom data.

Statistical Analyses

We compiled descriptive statistics for gender, age, education, 

and income for the entire sample and for each racial group. 

We also examined bivariate associations between race and 

each of the following types of variables: (1) awareness of 

mitigation programs and policy; (2) experience with and 

perception of wildland fire occurrence and other natural 

disturbances; (3) receipt and use of information about 

wildland fire mitigation policies and procedures; (4) requests 

for mitigation information and reasons for lack of requests; 

(5) landowner sources of information about mitigation; (6) 

preferred sources of information; (7) landowner actions 

taken to reduce wildland fire hazards; (8) preferences for 

State remediation of wildland fire threat; and (9) landowner 

interest in and awareness of biomass.

The variable used to measure the dependent variable 

awareness (AWARE1) was derived by first composing an 

awareness index. The index consisted of the proportion of 

mitigation programs of which the average respondent was 

aware. The number and types of wildland fire mitigation 

programs varied by State although there may have been 

some overlap for certain programs.6 For instance, there 

were six programs in Georgia. If the respondent were aware 

of two of them, the respondent’s awareness score would 

be 0.333. The second awareness variable (AWARE2) then 

dichotomized those scores into a binary variable. All nonzero scores were recoded as one for AWARE2; zero scores 

were kept at zero. AWARE2, which we used in the logistic 

regression analysis, was the proportion of respondents 

indicating awareness of wildland mitigation programs in 

each State (table A.2). 

Other dependent variables (i.e., use of wildland fire 

mitigation information, receipt and request of wildland fire 

6

Because of variation in the number of mitigation programs across the 

five study States, “awareness” may not be comparable in different States 

(e.g., Georgia has only 6 mitigation programs while Florida has 13). An 

alternative would have been to analyze awareness for the individual States, 

but doing so would have resulted in unacceptably small sample sizes for the 

regression models.

6
mitigation information, and various other mitigation action) 

were coded as one if respondents had requested, received, or 

used information, or engaged in other mitigation practices. 

These variables were coded as zero if respondents had no 

engagement or interest.

A test of the null hypothesis that no significant differences 

existed between the African-American and White samples 

was performed with chi-square analysis, including Fisher’s 

Exact Test for nominally coded variables with only two 

response categories (2 x 2 table). Independent sample t-tests 

were conducted for the continuous variables of age and 

percentage of income derived from rural land. Regretfully, 

the number of rural acres owned was omitted from the 

larger Texas A&M mail survey. Results for number of acres 

owned are presented only for respondents to the face-to-face 

conference survey, the UF survey, and the Clemson survey.

Logistic Regression Models

Logistic regression models were used to test for racial 

differences in wildland fire mitigation awareness, 

information use and request, receipt of wildland fire 

mitigation information, actions taken to reduce wildland fire 

threat, and barriers to information requests (Gujarati 1988). 

Logistic regression accounts for nominally coded response 

variables that take the form Y = 1 or 0. The logistic equation 

gives the logit of the probability of an outcome, for example, 

the logit pertaining to awareness of wildland fire mitigation 

programs. The logit derives from the equation:

Z = b1 + b2x2 + ... + bixi,

where 

 b1 = the intercept

 b2

 ... bx1= model parameters

 x = explanatory variables 

The probability for a positive response is given by:

P = 1/1 + e-Z

where

 e = the natural log

The probability of a respondent providing a positive 

response, or scoring 1 on the dependent variables was 

modeled as a function of eight independent variables. The 

dependent variables were: (1) awareness of wildland fire 

mitigation programs; (2) request of wildland fire mitigation 

information; (3) receipt of wildland fire mitigation 

information; (4) use of wildland fire mitigation information; 

(5) actions to reduce wildland fire threat; and (6) barriers to 

information request (e.g., not aware information available, 

no contact information, lack of trust in agencies providing 

information). Independent variables were coded as follows: 

race (1=African-American, 0=White); gender (1=female, 

0=male); education (less than high school=1, high school 

graduate or equivalent=2, college or technical school 

graduate=3, higher than 4-year college=4); whether one had 

experienced property loss resulting from wildfire (1=yes, 

0=no); whether one believed property could be damaged 

by wildfire (1=yes, 0=no); whether one managed property 

(1=yes, 0=no); whether one lived on land (1=yes, 0=no); 

and whether one had a management plan for his or her land 

(1=yes, 0=no).

Results

The total number of rural, NIPF landowners was 903. Of 

these, 849 respondents provided racial/ethnic data. White 

respondents totaled 589; African American, 246; Native 

American, 8; and Hispanic, Asian American, and Other each 

contributed two respondents.7 Respondents not identifying 

as either African American or White were omitted from the 

analysis. The final sample size was 835, with 71.5 percent 

White and 29.5 percent African American. 

Bivariate Analyses

Demographics—Table 2 shows that the overall sample was 

predominantly male, roughly 70 percent overall. Slightly 

< 70 percent of African-American landowners were male, 

and about 75 percent of White landowners were male. The 

sample was also composed of mostly older respondents 

(table 3). Mean age for the total sample and for Whites was 

61; it was slightly lower for African Americans at about 59.

In terms of educational attainment, the most pronounced 

racial differences appeared in the highest and lowest 

education categories. About 13 percent of African Americans 

did not have a high school diploma compared to only 2 

percent of Whites, and 18 percent of African Americans had 

post-baccalaureate education compared to Whites with 28 

percent (table 4). Percentages for high school completion 

and college or technical school completion were more 

comparable. 

Table 2—Gender of survey respondents by race 

Gender

AfricanAmerican White Total

N

 percent 

Female 77

(31.7)

152

(25.9)

229

(27.6)

Male 166

(68.3) 

436

(74.5) 

602

(72.4) 

 Total 243

(29.2) 

588

(70.8) 

831

(100.0) 

x2 =2.93; (df=1) p=.089.

7

The percentage of non-Black minority groups in these States owning 

substantial acreage would likely be too small for analysis.

7
We found extreme differences in terms of income for 

African Americans and Whites (table 5). Close to one-half 

of African Americans reported annual household income of 

< $30,000, but only about 11 percent of Whites did so; and 

roughly 30 percent of Whites claimed income at $120,000 or 

more compared to only 4 percent of African Americans. The 

two groups were more similar in the middle income category 

of $50,000 to $69,000, but African-American income 

decreased sharply after this category. White income was 

distributed more evenly over the upper income categories. 

African-American and White responses were statistically 

different for three of the four demographic variables, 

although age differences were minimal in substantive terms.

Land management—Table 6 contains results for general 

land management strategies. Overall, 78 percent of 

landowners said they personally managed their land. 

Significantly more African Americans than Whites indicated 

this was the case (89 percent compared to 73 percent). About 

55 percent of landowners said they had no management 

plan. Only about one-third of African Americans had a 

plan, compared to about one-half of Whites. Also, about 

60 percent of landowners said they lived on their land. Close 

to 80 percent of African Americans lived on their land, 

but only about one-half of Whites. No significant racial 

differences were found in terms of whether the respondent’s 

land was heir property. However, these results should be 

taken with some caution as the survey did not define 

heir property. 

Table 7 shows that, on average, about 13 percent of 

respondents’ household income derived from their rural 

land. African Americans received 12 percent of household 

income from their land on average, and Whites received 

about 13 percent. However, the median percentage of 

income from land was only 1 percent overall, zero for 

African Americans, and 2 percent for Whites. The frequency 

distribution for this variable showed that no household 

income came from the land for roughly 46 percent 

of respondents.

Land use—Table 8 contains results for land use categories. 

The most common use was growing timber (52 percent), 

followed by farming and recreation (43 percent and 42 

percent, respectively), and other (34 percent). Significantly 

more African Americans than Whites indicated farming 

as a land use; growing timber, recreation, and other uses 

were mentioned significantly more by Whites. About twice 

as many Whites as African Americans used their land for 

growing timber and recreation.

The demographic, land management, and land use 

analyses show that proportionately more White males 

than African-American males responded to the survey, but 

proportionately more African-American females than White 

females participated. On average, Whites were older than 

Table 3—Mean age percentage of survey 

respondents by race 

AfricanAmerican White Total

M=58.6

(s.d.=14.1) 

N=198

M=61.6

(s.d.=12.3) 

N=466

M=60.7

(s.d.=12.9) 

N=664

M=mean; s.d.=standard deviation; t =2.6; (df=331) p=.009. 

Table 4—Education of survey respondents by race

Education

AfricanAmerican White Total

N

percent 

Less than high school 32

(13.4) 

11

(1.9) 

43

(5.3) 

High school graduate or equivalent 82

(35.0) 

176

(30.6) 

258

(31.9) 

College or technical school 77

(32.9) 

229

(39.8) 

306

(37.8) 

Higher than 4 year college 43

(18.3) 

160

(27.8) 

203

(25.1) 

 Total 234

(28.9) 

576

(71.1) 

810

(100.0) 

x

2 =52.4; (df=3) p<0.0001.

8
African Americans. African Americans had lower education 

levels than Whites, and there were substantial differences in 

household income levels. African Americans indicated more 

personal involvement in land management, as they were 

more likely to manage their land directly and to live on their 

land. Whites appeared to have more formal land management 

arrangements, as indicated by the greater likelihood in this 

group for land management plans.

The following sections present bivariate analyses related 

to race and wildfire mitigation perception, information 

preferences, and actions. Dependent variables included: 

(1) landowner experience and perception of wildland fire 

occurrence and other natural disturbances; (2) landowner 

preventive actions and preferences for State remediation of 

wildland fire threat; (3) landowner sources of information 

about mitigation and source preferences; (4) landowner 

interest in and awareness of biomass; and (5) incentives to 

encourage mitigation participation. 

Wildland fire and other natural disturbances—Table 9 

shows that just under 30 percent of respondents said that 

wildland fire had burned on their land. The percent of 

landowners indicating they had experienced a wildland fire 

occurrence was approximately 31 percent for Whites but 

only 20 percent for African Americans. About 20 percent of 

African Americans and 30 percent of Whites reported that 

either they or someone they knew had experienced property 

loss resulting from wildland fire in the past 10 years 

(table 9). Significant differences between Whites and 

African Americans were found for both these questions. 

Roughly equal percentages of Whites and African Americans 

believed their land could be damaged by wildland fire 

(table 9). About three-quarters of Whites said their land had 

been struck by a hurricane (table 9), about 46 percent had 

beetle infestations, and 34 percent said their land had been 

damaged by some other natural disaster. Significantly lower 

percentages of African Americans indicated experience with 

these three types of disturbance.

Landowner actions taken to prevent wildland fire and 

preferences for State mitigation—Table 10 shows that 

Whites were more likely to say they had done “nothing” 

to reduce wildland fire threats on their land but were more 

likely to say they had implemented “other” actions than 

those listed in the survey. In terms of the State providing 

mitigation action (table 11), higher percentages of African 

Americans than Whites indicated the State should control 

excess vegetation (57 percent versus 38 percent), provide 

fire risk education for property owners (66 percent versus 

53 percent), or provide low cost insurance (55 percent 

versus 37 percent). About 30 percent of White landowners, 

compared to 14 percent of African Americans, indicated the 

State should do something “other” than one of the actions 

listed in table 11. 

Table 5—Annual household income of survey respondents by race 

Income

AfricanAmerican White Total sample

N

percent 

< $30,000 96 

(44.7)

58 

(11.3)

154 

(21.2)

$30,000-$49,000 46 

(21.4) 

89 

(17.4) 

135 

(18.5) 

$50,000-$69,000 38 

(17.7) 

80 

(15.6) 

118 

(16.2) 

$70,000-$89,000 17 

(7.9) 

72 

(14.0) 

89 

(12.2) 

$90,000-$111,999 10 

(4.7)

68 

(13.3)

78 

(10.7)

$120,000 or more 8 

(3.7)

146 

(28.5)

154 

(21.2)

 Total 215 

(29.5)

513 

(70.5)

728 

(100.0)

x2 =140.3; (df=5) p<.0001.

9
Table 6—Land management responses from survey respondents by race 

Land management Response 

AfricanAmerican White Total 

N

- - - - - - percent - - - - - -

Do you personally manage your rural land? 

x

2 =23.7; (df=1) p<0.0001 

Yes 

No 

210 

(88.6) 

27 

(11.4) 

423 

(72.9) 

157 

(27.1) 

633 

(77.5) 

184 

(22.5) 

Total 237

(29.0) 

580

(71.0) 

817

(100.0) 

Do you have a management plan for your rural land? 

x

2 =11.9; (df=1) p<0.001 

Yes 

No 

86 

(36.0) 

153 

(64.2) 

270 

(49.3) 

278 

(50.7) 

356 

(45.2) 

431 

(54.8) 

Total 239

(30.4) 

548

(69.6) 

787

(100.0) 

Do you live on this land? 

x

2 =49.8; (df=1) p<0.0001 

Yes 

No 

190 

(79.2) 

50 

(20.8) 

305 

(52.7) 

274 

(47.3) 

495 

(60.4) 

324 

(39.6) 

Total 240

(29.3) 

579

(70.7) 

819

(100.0) 

Is this heir’s property? 

x

2 =0.9; (df=1) p<0.3503 

Yes 

No 

117 

(48.8) 

123 

(51.3) 

242 

(44.9) 

297 

(55.1) 

359 

(46.1) 

420 

(53.9) 

Total 240

(30.8) 

539

(69.2) 

779

(100.0) 

Table 7—Mean precentage of income from land

for survey respondents by race

AfricanAmerican White Total sample

M=12.0

(s.d.=22.8)

Median

0.0

N-214

M=13.1

(s.d.=24.3)

Median

2.0

N=512

M=12.7;

(s.d.=23.9)

Median

1.0

N=726

M = mena; standard deviation; t-.59; p>0.56.

10
Mitigation information sources and preferences—

Table 12 presents sources for wildland fire mitigation 

information. Overall, State forestry agencies (37 percent), 

State or county extension agents (35 percent), and family or 

friends (33 percent) were the sources most frequently cited 

for this kind of information. Results also suggested White 

landowners were more reliant than African Americans on 

informal channels for obtaining mitigation information. 

Significantly higher percentages of Whites relied on family/

friends (37 percent versus 22 percent), developed their own 

fire protection methods (32 percent versus 11 percent), 

asked neighbors/community members for help (31 percent 

versus 14 percent), or used the Internet (26 percent versus 

9 percent). A higher percentage of African Americans than 

Whites referenced State or county extension agents (42 

percent compared to 33 percent). The greater tendency of 

White landowners to seek informal information sources 

is consistent with our results showing relatively lower 

trust levels Whites have in State agencies providing this 

information. 

White landowners were significantly more likely than 

African Americans to prefer the Internet or “other” 

information sources, and African Americans were somewhat 

more likely to prefer workshops hosted by professionals 

(table 13).

Biomass awareness and interest—A short paragraph 

explaining biomass and its potential uses for energy was 

included in the survey. After reading the explanation, 

respondents were asked whether they were aware of 

land assistance or incentive programs in their State that 

encouraged biomass removal. About one-fifth of landowners 

said they were aware of State biomass removal programs 

(table 14). Significantly more Whites were aware (23 

percent) than African Americans (13 percent). Overall, close 

to 60 percent of respondents said they would be interested 

in obtaining more information about such programs (table 

14). Seventeen percent were uncertain. Seventy-one percent 

of African Americans indicated interest in these programs, 

while just over 50 percent of Whites were interested. 

Table 8—Land use responses from survey respondents by racea

Land Use Response

AfricanAmerican White Total

N

- - - - - - - - percent - - - - - - - - 

Timber

x

2 =49.1 (df=1) p<0.0001 

Yes

 

No 

Total 

79

(32.9) 

161 

(67.1) 

240 

(29.1)

349

(59.8) 

235 

(40.2) 

584 

(70.9)

428

(51.9) 

396 

(48.1) 

824 

(100.0)

Farming

x

2 =27.2 (df=1) p<0.0001 

Yes

No 

Total 

137

(56.6) 

105 

(43.4) 

242 

(29.3) 

215

(36.9) 

368 

(63.1) 

583 

(70.7) 

352

(42.7) 

473 

(57.3) 

825 

(100.0) 

Recreation

x

2 =50.1 (df=1) p<0.0001 

Yes

No 

Total 

55

(23.0) 

184 

(77.0) 

239 

(29.0) 

291

(49.8) 

293 

(50.2) 

584 

(71.0) 

346

(42.0) 

477 

(58.0) 

823 

(100.0) 

Other

x

2 =6.3 (df=1) p<0.013 

Yes

No 

Total 

68

(27.8) 

177 

(72.2) 

245 

(30.0) 

215

(36.8) 

369 

(63.2) 

584 

(70.5) 

283

(34.1) 

546 

(65.9) 

829 

(100.0) 

a What do you use this land for? 

11
Table 9—Natural disturbance responses from survey respondents by race 

Disturbance Response

AfricanAmerican White Total

 N

- - - - - - - - percent - - - - - - - -

Has wildfire ever burned on your rural land?

x

2 =11.1; (df=2) p=0.004 

Yes

No 

Don’t know 

49

(20.2) 

177 

(72.8) 

17 

(7.0) 

182

(31.1) 

358 

(61.2) 

45 

(7.7) 

231

(27.9) 

535 

(64.4) 

62 

(7.5) 

Total 243

(29.4) 

585

(70.7) 

828

(100.0) 

Have you or anyone you know lost property 

as a results of wildfire in the past 10 years?

x

2 =7.3; (df=2) p=0.026

Yes

No 

Don’t know 

51

(20.9) 

182 

(74.6) 

11 

(4.5) 

175

(30.0) 

382 

(65.4) 

27 

(4.6) 

226

(27.3) 

564 

(68.1) 

38 

(4.6) 

Total 244

(29.5) 

584

(70.5) 

828

(100.0) 

Do you believe your rural land could be 

damaged by wildfire?

x

2 =4.35; (df=2) p<0.114

Yes

No 

Don’t know 

183

(75.6) 

44 

(18.2) 

15 

(6.2) 

412

(72.7) 

133 

(23.5) 

22 

(3.9) 

595

(73.6) 

177 

(21.9) 

37 

(4.6) 

Total 242

(29.9) 

567

(70.1) 

809

(100.0) 

Has your rural land been hit by hurricane?

x

2 =59.2; (df=2) p<0.0001

Yes

No 

91

(37.1) 

153 

(62.7) 

380

(74.5) 

130 

(25.5) 

449

(63.9) 

254 

(36.1) 

Total 244

(29.5) 

584

(70.5) 

828

(100.0) 

Has your rural land been hit by beetles?

x

2 =78.6; (df=2) p<0.0001

Yes

No 

28

(11.4) 

216 

(88.2) 

233

(45.7) 

277 

(54.3) 

258

(36.7) 

445 

(63.3) 

Total 244

(29.5) 

584

(70.5) 

828

(100.0) 

Has your rural land been hit by some other 

natural disaster?

x

2 =50.5; (df=1) p<0.0001

Yes

No 

25

(10.2) 

220 

(89.8) 

200

(34.3) 

384 

(65.8) 

225

(27.1) 

604 

(72.9) 

Total 245

(29.6) 

584

(70.5) 

829

(100.0) 

12
Table 10—Landowner actions to reduce wildland fire threat by racea

Mitigation action Response

AfricanAmerican White Total

N

- - - - - - - - percent - - - - - - - -

Construct fire line

x

2 =2.4; (df=1) p<0.139 

Yes

No 

Total 

87

(35.4) 

159 

(64.6) 

246 

(29.4) 

242

(41.1) 

347 

(58.9) 

589 

(70.6) 

329

(39.4) 

506 

(60.6) 

835 

(100.0) 

Purchase fire insurance

x

2 =0.03; (df=1) p=0.873 

Yes

No 

Total 

69

(28.1) 

177 

(71.9) 

246 

(29.5) 

162

(27.5) 

427 

(72.5) 

589 

(70.5) 

231

(72.3) 

604 

(72.3) 

835 

(100) 

Remove unwanted trees and shrubs

x

2 =0.25; (df=1) p<0.643 

Yes

No 

Total 

104

(42.3) 

142 

(57.7) 

246 

(29.5) 

238

(40.4) 

351 

(59.6) 

589 

(70.5) 

342

(41.0) 

493 

(59.0) 

835 

(100.0) 

Nothing

x

2 =39.3; (df=1) p<0.0001 

Yes

No 

Total 

39

(20.1) 

155 

(79.9) 

194 

(27.4) 

236

(45.8) 

279 

(54.2) 

515 

(72.6) 

275

(38.8) 

434 

(61.2) 

709 

(100.0) 

Other

x

2 =30.4; (df=1) p<0.0001 

Yes

No 

Total 

14

(8.2) 

156 

(91.8) 

170 

(22.5) 

169

(28.8) 

418 

(71.2) 

587 

(77.5) 

183

(24.2) 

574 

(75.8) 

757 

(100.0) 

a What things have you done to prevent wildfire on your rural land?

13
Table 11—State actions to reduce wildland fire threat to private homes by racea

Roles Response

AfricanAmerican White Total

N

- - - - - - - percent - - - - - - -

Remove, burn, or otherwise control excess

growth of trees, shrubs, vines 

x

2 =24.1; (df=1) p<0.0001 

Yes

No 

Total 

139

(56.5) 

107 

(43.5) 

246 

(29.5) 

224

(38.0) 

365 

(62.0) 

589 

(70.5) 

363

(43.5) 

472 

(56.5) 

835 

(100.0) 

Provide fire risk education for home and 

business owners 

x

2 =12.3; (df=1) p<0.0001 

Yes

No 

Total 

162

(65.9) 

84 

(34.2) 

246 

(29.5) 

310

(52.6) 

279 

(47.4) 

589 

(70.5) 

472

(56.5) 

363 

(43.5) 

835 

(100) 

Provide low cost insurance

x

2 =22.6; (df=1) p<0.0001 

Yes

No 

Total 

134

(54.7) 

111 

(45.3) 

245 

(29.4) 

217

(36.8) 

372 

(63.2) 

589 

(70.6) 

351

(42.1) 

483 

(57.9) 

834 

(100.0) 

Other

x

2 =22.9; (df=1) p<0.0001 

Yes

No 

Total 

35

(14.2) 

211 

(85.8) 

246 

(29.5) 

177

(30.1) 

412 

(69.9) 

589 

(70.5) 

212

(25.4) 

623 

(74.6) 

835 

(100.0) 

a What roles do you think your State should play in reducing wildfire threats to your home?

14
Table 12—Information sources for wildland fire mitigation by racea

Information source Response

AfricanAmerican White Total

N

- - - - - - - - percent - - - - - - - -

Family or friends

x

2 =18.2; (df=1) p<0.0001 

Yes

No 

Total 

52

(21.6) 

189 

(78.4) 

241 

(29.1) 

217

(36.9) 

371 

(63.1) 

588 

(36.9) 

269

(32.5) 

560 

(67.6) 

829 

(100.0) 

State or county extension agent

x

2 =6.0; (df=1) p<0.016 

Yes

No 

Total 

101

(41.7) 

141 

(58.3) 

589 

(70.9) 

193

(32.8) 

396 

(67.2) 

242 

(29.1) 

242

(35.4) 

537 

(64.6) 

831 

(100.0) 

Federal forestry agency

x

2 =1.86; (df=1) p<0.185 

Yes

No 

Total 

52

(21.5) 

190 

(78.5) 

242 

(29.1) 

153

(26.0) 

436 

(74.0) 

589 

(70.9) 

205

(24.7) 

626 

(75.3) 

831 

(100.0) 

Develop own fire protection methods

x

2 =39.1; (df=1) p<0.0001 

Yes

No 

Total 

27

(11.2) 

215 

(88.8) 

242 

(29.1) 

189

(32.1) 

400 

(67.9) 

589 

(70.9) 

216

(26.0) 

615 

(74.0) 

831 

(100.0) 

Neighbors or other community members

x

2 =26.7; (df=1) p<0.0001 

Yes

No 

Total 

33

(13.6) 

209 

(86.4) 

242 

(29.1) 

182

(30.9) 

407 

(69.1) 

589 

(70.9) 

215

(25.9) 

616 

(74.1) 

831 

(100.0) 

State forestry agencies

x

2 =0.6; (df=1) p<0.478 

Yes

No 

Total 

85

(35.1) 

157 

(64.9) 

242 

(29.1) 

224

(38.0) 

365 

(62.0) 

589 

(70.9) 

309

(37.2) 

522 

(62.8) 

831 

(100.0) 

Internet

x

2 =30.4; (df=1) p<0.0001 

Yes

No 

Total 

22

(9.1) 

220 

(90.9) 

242 

(29.1) 

155

(26.3) 

434 

(73.7) 

589 

(70.9) 

177

(21.3) 

654 

(78.7) 

831 

(100.0) 

a Where do you typically get information about wildland fire protection?

15
Table 13—Landowner preferences for wildland fire mitigation information by racea

Information source Response

AfricanAmerican White Total

N

- - - - - - - percent - - - - - - -

Conversation with professionals

x

2 =0.9; (df=1) p<0.363 

Yes

No 

Total 

128

(52.2) 

117 

(47.8) 

245 

(29.4) 

287

(48.7) 

302 

(51.3) 

589 

(70.6) 

415

(50.2) 

419 

(49.8) 

834 

(100.0) 

Internet

x

2 =14.2; (df=1) p<0.0002 

Yes

No 

Total 

42

(17.1) 

203 

(82.9) 

245 

(29.4) 

175

(29.7) 

414 

(70.3) 

589 

(70.6) 

217

(26.0) 

617 

(74.0) 

834 

(100) 

Workshop hosted by professionals

x

2 =3.9; (df=1) p<0.054 

Yes

No 

Total 

97

(39.6) 

148 

(60.4) 

245 

(29.4) 

191

(32.4) 

398 

(67.6) 

589 

(70.6) 

288

(34.5) 

546 

(65.5) 

834 

(100.0) 

Information pamphlet

x

2 =0.2; (df=1) p<0.699 

Yes

No 

Total 

97

(39.6) 

148 

(60.4) 

245 

(29.4) 

243

(41.2) 

346 

(58.7) 

589 

(70.6) 

340

(40.8) 

494 

(59.2) 

834 

(100.0) 

Other information source

X2 =34.2; (df=1) p<0.0001 

Yes

No 

Total 

13

(5.3) 

232 

(94.7) 

245 

(29.4) 

130

(22.1) 

459 

(77.9) 

589 

(70.6) 

143

(17.2) 

691 

(82.9) 

834 

(100.0) 

a If you contact forestry professionals about managing your land, what kind of information is best for you?

16
Twenty-seven percent of Whites had no interest, compared 

to 18 percent of African Americans, and about 20 percent of 

Whites were uncertain compared to 11 percent of African 

Americans. The data suggested Whites approached this issue 

with more caution than African Americans.

Incentives to encourage household-level wildland fire 

mitigation—We asked those who said they did nothing to 

protect their land from wildland fire risk what incentives 

might encourage them to do so. Table 15 shows that more 

African-American landowners would be encouraged by 

technical assistance for fire protection and State or Federal 

cost-sharing measures and the ability to sell biomass. 

African Americans were also more likely to say some 

“other” incentive would encourage them to begin fire 

prevention practices.

Logistic Regression

Awareness—Table 16 shows roughly equal proportions of 

respondents who were either aware or not aware of wildland 

fire mitigation programs, about 52 percent compared to 48 

percent (See row titled percent of “yes” responses). African 

Americans were significantly more likely than Whites to be 

aware of at least one wildland fire mitigation program. This 

result was similar to the finding of Jarrett and others (2009), 

who found greater awareness among African American 

landowners compared to Whites. The principal difference 

between Jarrett and others (2009) and the present study is 

the inclusion of more African-American responses and the 

explicit objective of examining the association between 

wildfire risk and race.

Respondents who had experienced a property loss were 

more likely than those who had not had such a loss to be 

aware of these programs. Interestingly, those who believed 

their property could be damaged by wildland fire were less 

likely to be aware. Also, those who managed their own land 

were less likely to be aware, but those with a management 

plan were more likely to be aware. The odds of a AfricanAmerican respondent being aware of a mitigation program 

was about 3.3 times that of a White respondent.8

Information requests—About 22 percent of respondents 

had requested information about wildland fire mitigation 

(table 16). Similar to the awareness model, those with 

knowledge of property losses from wildland fire and those 

with a management plan were more likely to request 

information. Also, respondents who believed their property 

could burn and those who managed their own land were less 

likely to request information.

Receipt of wildland fire mitigation information—About 

one-third of respondents had received information about 

wildland fire mitigation programs (table 16). Those with 

a property loss were more likely than others to get this 

information, the odds being roughly 1.9 to 1 that those with 

property losses would receive this information. Those who 

managed their land were less likely to get information, while 

those who lived on their land and those with a management 

plan were more likely to receive information.

Table 14—Biomass awareness and interest by race 

Biomass awareness and interest Response

AfricanAmerican White Total

N

- - - - - - - - percent - - - - - - - -

Are you aware of any landowner 

assistance and incentive programs in your 

state that encourage biomass removal? 

x

2 =9.9; (df=1) p<0.002 

Yes

No 

32

(13.1) 

212 

(86.9) 

132

(22.7) 

449 

(77.3) 

164

(19.9) 

661 

(80.1) 

Total 244

(29.6) 

581

(70.4) 

825

(100.0) 

Would you be interested in learning more 

about forest biomass and bioenergy 

production? 

x

2 =21.5; (df=2) p<0.0001 

Yes

No 

Don’t know 

173

(70.9) 

44 

(18.0) 

27 

(11.1) 

310

(53.6) 

154 

(26.6) 

114 

(19.7) 

483

(58.8) 

198 

(24.1) 

141 

(17.2) 

Total 244

(29.7) 

578

(70.3) 

822

(100.0) 

8

The odds ratio is the probability of a positive response for the dependent 

variable divided by the probability of a negative response.

17
Information use—The sample size was reduced to 136 for 

those who said they had received mitigation information 

(table 16). Of these, just over 80 percent actually put it to 

some use. African Americans were less likely than Whites 

to use wildland fire mitigation information. Also, those who 

managed their land were more likely than others to use this 

information.

Other action to reduce wildland fire risk—Although 

the chi-square analyses showed no significant racial 

differences for specified actions for reducing wildland fire 

risk (e.g., constructing a fire line, purchasing insurance, or 

removing unwanted vegetation), there were differences for 

a generalized “other” category. Accordingly, we modeled 

“other action” as the dependent variable. Again, African 

Americans were less likely to say they did anything besides 

the specified actions to reduce wildland fire risk. Also, those 

who believed their property could be hit by wildland fire and 

those who managed their land were less likely to employ 

other actions. Landowners with property loss from wildfire 

and those with a management plan were more likely to do 

other things to prevent wildfire.

A second group of logistic models examined potential 

constraints faced by respondents when requesting wildland 

fire mitigation information (table 17). These included having 

no awareness of programs, not knowing whom to contact 

about information, and lack of trust in agencies providing 

this information. The models included only respondents 

who said they had not requested wildland fire mitigation 

information. 

Information availability—African Americans who had 

not requested wildland fire information were more likely 

Table 15—Incentives to encourage household-level wildland fire mitigation by racea

Actions to encourage mitigation Response

AfricanAmerican White Total

N

- - - - - - - - percent - - - - - - - - 

Technical assistance for fire protection

x

2 =10.8; (df=1) p<0.001 

Yes

No 

Total 

27

(71.1) 

11 

(28.9) 

38 

(13.9) 

100

(42.4) 

136 

(57.6) 

236 

(86.1) 

127

(46.4) 

147 

(53.7) 

274 

(100.0) 

State or federal cost-sharing for taking

preventive measures 

x

2 =3.93; (df=1) p<0.05 

Yes

No 

Total 

23

(59.0) 

16 

(41.0) 

39 

(14.2) 

99

(42.0) 

137 

(58.1) 

236 

(85.8) 

122

(44.4) 

153 

(55.6) 

275 

(100.0) 

Ability to sell removed biomass from land

x

2 =0.978; (df=1) p<0.385 

Yes

No 

Total 

20

(51.3) 

19 

(48.7) 

39 

(14.2) 

101

(42.8) 

135 

(57.2) 

236 

(85.8) 

121

(44.0) 

154 

(56.0) 

275 

(100.0) 

Other

x

2 =18.2; (df=1) p<0.0001 

Yes

No 

Total 

35

(89.7) 

4 

(10.3) 

39 

(14.2) 

126

(53.4) 

110 

(46.6) 

236 

(85.8) 

161

(58.6) 

114 

(41.5) 

275 

(100.0) 

a

 If you have not taken any measure to prevent fire on your land, which of the following would encourage you to begin fire 

prevention practices? 

18
than Whites who had not requested such information to say 

they did not ask for information because they did not know 

it existed (table 17). Those with property loss were also 

more likely to name this constraint. Females and those who 

managed land were less likely to cite this constraint. 

Contact information—A related constraint to information 

requests is lack of knowledge about appropriate persons or 

agencies to contact. No significant racial differences were 

found here (table 17). Those who had experienced property 

loss were more likely to say they were constrained by this 

factor, and those with a management plan were less likely to 

say they were constrained.

Lack of trust—African Americans were less likely than 

Whites to indicate lack of trust in agencies as a barrier 

to information requests (table 17). Also, those with a 

management plan were less likely to indicate trust. 

Discussion and Conclusion

Recalling our research hypotheses, we can use the regression 

analyses to address each one:

H1: Black Belt African Americans are less likely than 

Black Belt Whites to be aware of wildland fire 

mitigation policies and programs.

H2

: Black Belt African Americans are less likely than 

Black Belt Whites to request wildland fire mitigation 

information.

H3: Black Belt African Americans are less likely than 

Black Belt Whites to receive wildland fire mitigation 

information.

H4: Black Belt African Americans are less likely than 

Black Belt Whites to use wildland fire mitigation 

information.

H5

: Black Belt African Americans are less likely than 

Black Belt Whites to take other actions to reduce 

wildland fire threats to their property.

H6

: Black Belt African Americans are more likely than 

Black Belt Whites to cite barriers requesting wildland 

fire information.

Results did not support hypotheses one, two, and three 

but did support hypotheses four and five. We found mixed 

support for hypothesis six. This hypothesis was assessed with 

the three constraints to information request (i.e., not knowing 

about information availability, not knowing whom to contact, 

and not trusting public agencies providing information). 

Again, African Americans were more likely than Whites 

to say they did not request information because they did 

not know it was available. However, there were no racial 

differences for the contact constraint, and African Americans 

indicated more trust than Whites.

Table 16—Logistic regression estimates: Wildfire mitigation awareness, information request, receipt, use, and other mitigation action 

Information Information Use requested Other actions

Awareness request receipt information to reduce threats

Percent of “yes” responses 51.8 21.8 32.8 83.0 22.8

Parameter MLE Odds MLE Odds MLE Odds MLE Odds MLE Odds

coeff. ratio coeff. ratio coeff. ratio coeff. ratio coeff. ratio

Intercept 0.39 -0.92a -1.28b 1.61 0.10

Black 1.20b 3.32 -0.18 0.84 0.34 1.41 -1.59b 0.20 -1.26b 0.28

Female -0.12 0.89 0.17 1.18 0.12 1.13 -0.34 0.71 -0.35 0.71

Education 0.15 1.16 0.16 1.17 0.04 1.04 -0.11 0.89 0.14 1.15

Property loss 0.49b 1.64 0.90b 2.47 0.65b 1.91 -0.30 0.74 1.04b 2.84

Believe burn -1.18b 0.31 -1.49b 0.23 -0.29 0.75 -0.56 0.57 -1.82b 0.16

Manage land -0.94b 0.39 -1.12b 0.33 -0.81b 0.45 1.26a 3.53 -1.16b 0.32

Live on land 0.18 1.20 0.31 1.36 0.45a 1.57 0.22 1.25 -0.20 0.82

Management plan 0.79b 2.20 0.93b 2.54 1.29b 3.62 0.87 2.39 0.59a 1.81

N = 728 634 585 136 658

Model chi-square 142.48 150.45 79.54 16.44 221.63

Significance level <0.0001 <0.0001 <0.0001 <0.037 <0.0001

Percent correct predictions 74.7 80.0 71.2 74.4 84.6

MLE = Maximum likelihood coefficient. 

a p < 0.05. 

b p < 0.01. 

19
In terms of the trust variable, our results contrasted with the 

nationwide analyses of Bowker and others (2008). These 

authors showed that African Americans had less trust than 

Whites in the effectiveness of governmental agencies in 

managing wildland fire. The difference in results may have 

to do with sample differences. Bowker and others (2008) 

sampled the general U.S. population, whereas our data were 

specific to southern landowners. Still, we might expect 

southern rural African-American landowners to demonstrate 

a distancing from governmental agencies given recent 

controversies about discrimination by the U.S. Department 

of Agriculture (USDA) against African-American farmers 

in the South. African Americans have lost land over the 

past century due to various factors including northward 

migration, lack of understanding of the law, and also through 

various forms of discrimination. The 1997 class action 

law suit (Pigford versus Glickman) initiated by AfricanAmerican farmers alleging systematic discrimination on the 

part of the U.S. Department of Agriculture exemplifies this 

latter problem. 

Our sample included both non-farm landowners as well 

as farmers. Supplementary data obtained from two focus 

groups conducted with African-American landowners in 

Sumter and Dorchester Counties, SC, revealed an important 

distinction between rural landowners who primarily farmed 

and those who held land for other purposes.9

 In the farmer 

focus group, the discussion around land meanings and 

values focused almost singularly on issues of race and 

racism embedded in local branches of resource management 

and extension agencies. In stark contrast, discussion in the 

general landowner focus group centered more on landowners 

attempting to acquire more information about their land. 

Institutional racism was not raised by this group.

The overriding aim of this JFSP project was to examine 

awareness and engagement by historically marginalized 

groups in the Black Belt South with State-level wildland fire 

mitigation policies and programs. African Americans were 

actually more aware than Whites of State-level programs, 

and we found no differences for information request or 

receipt. The only variable suggesting African-American 

marginalization relates to information use; African 

Table 17—Logistic regression estimates: Variables constraining information request 

Information No contact Lack of

availability information trust

Percent of “yes” responses 19.7 23.9 38.7

Parameter MLE Odds MLE Odds MLE. Odds

coeff. ratio coeff. ratio coeff. ratio

Intercept -0.78 -0.41 0.30

Black 0.84 2.32 0.23 1.26 -2.27 0.10

Female -0.78 0.46 -0.39 0.68 0.40 1.50

Education 0.02 1.02 0.04 1.04 0.19 1.21

Property loss 0.39 1.48 0.41 1.51 0.11 1.12

Believe burn -0.22 0.80 -0.46 0.63 -0.45 0.64

Manage land -0.89 0.41 -0.33 0.72 0.01 1.01

Live on land 0.14 1.15 0.02 1.02 -0.36 0.70

Management plan -0.05 0.95 -0.73 0.48 -0.90 0.41

N = 493 493 493

Model chi-square 31.05 25.80 94.45

Significance level <0.0001 <0.0011 <0.0001

Percent correct predictions 67.5 63.1 73.9

MMLE = aximum likelihood coefficient.

a p < 0.05. 

b p < 0.01. 

b

b

b

b

a

b

b

b

9

Keenan Adams conducted two focus groups in Mayesville, SC, and 

Ridgeville, SC, on January 30, 2009 and February 6, 2009. The first session 

lasted 1 hour and 14 minutes and the second, 47 minutes. Open-ended data 

were solicited with phenomenological questioning (Moerer-Urdahl and 

Creswell 2004).

20
Americans who requested information were less likely than 

Whites to use it. Also, for the subsample that did not request 

information, more African Americans said lack of awareness 

of mitigation information was a barrier to requesting such 

information.

Overall, our findings do not suggest that Black Belt AfricanAmerican landowners are disadvantaged with respect to 

either information awareness or acquisition. Our results 

should be taken with some caution because portions of 

the African-American sample were selected from small 

landowner advocacy conferences. Although the focus was 

not wildland fire mitigation, the fact that these landowners 

attended a land ownership conference suggested they may 

also be engaged with various kinds of land management and 

protection programs and policies.

As discussed, our study was limited by our ability to obtain 

an unobjectionable random sample from African-American 

landowners, although the African-American sample obtained 

may be defended. A related sampling limitation arises from 

the mixing of telephone and mail surveys for the AfricanAmerican sample. In order for land management agencies 

to make the most use of the kinds of information solicited 

in this study, it would be helpful to provide comparisons 

for specific parts of a State or for communities within given 

counties. As the data are, they provide very general racial 

comparisons that may operate differently across the five 

States.

Acknowledgments

We would like to acknowledge the JFSP and its assistance 

in funding this research. We would also like to recognize the 

assistance of Raye Williams and Carol Harvey for their data 

collection efforts at landowner conferences.

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22
Table A.1—Percentage of African-American population and forest

 land area for sampled counties 

Sample size for each State = 100.

a U.S. Bureau of the Census. 2002. State and county quick facts. Washington, DC: 

Available online at http://quickfacts. census.gov/qfd/states/01000.html.

 [Date accessed: November 2004].

b Forest statistics for the five States were consulted in the computation of these

percentages. Forest statistics for Southern States are published through the

 Southern Forest Experiment Station in Asheville, NC and are also available 

online. See first principal investigator for exact reference.

Location Forest land b

- - - - - - percent - - - - - - 

Alabama

Greene 80.3 69 

Hale 59.0 64 

Marengo 51.7 72

Perry 68.4 78 

Sumter 73.2 74

Florida

Gadsden 57.1 77 

Hamilton 37.7 74 

Jefferson 38.3 75 

Madison 40.3 74 

Georgia

Greene 44.4 80 

Hancock 77.8 91

Taliaferro 60.3 87 

Warren 59.5 84

Wilkes 43.1 76 

Mississippi

Adams 52.8 71 

Claiborne 84.1 81 

Copiah 51.0 77 

Jefferson 86.5 79 

Wilkinson 68.2 80 

South Carolina

Allendale 71.0 64 

Bamberg 62.5 66 

Hampton 55.7 71 

African-Americana

Appendix

23
1

Table A.2—State-level wildland fire mitigation programs and policies 

State Agency Program/Policy

Alabama Alabama Forestry 

Commission

Prescribed Burning or Fire Break Services:

Fire prevention advice with burn permit 

Firewise communities 

Publication: 

“Firewise landscaping for woodland homes” 

“Living with fire” 

“Safety guidelines for woodland homes” 

Internet: 

Fire prevention publications on Alabama Forestry 

Commission Web site (www.forestry.state.al.us)

Alabama Wildland Urban Interface councils

Alabama Wildfire Mitigation Program

Alabama Rural 

Community Fire 

Protection Institute and 

Alabama Fire College

Publication:

“Learn not to burn” 

Alabama Cooperative 

Extension Service 

Course: 

Prescribed burning certification course 

Internet: 

Private Forest Management Team Web site

Florida Florida Department of 

Community Affairs

Handbook:

“Best development practices for wildfire mitigation 

in Florida”

Florida Division of 

Forestry 

Prevention: 

Wildfire prevention clowns 

Smokey Bear 

Firewise communities 

Prescribed burning or fire break services 

Fire prevention advice with burn permit 

Internet: 

Florida Risk Assessment System 

Smoke screening tool 

Forestry fire management 

Other: 

Fire in Florida’s ecosystem (for teachers) 

Living on the edge in Florida (CD) 

Wildfire Risk Assessment Guide 

Florida Cooperative 

Extension Service

Internet:

Landscaping with Florida in mind

Georgia Georgia Forestry 

Commission

Firewise Program:

Firewise mobile exhibit 

Firewise Risk Assessment 

Prescribed Burning or Fire Break Services 

Fire prevention advice with burn permit 

Internet: 

Internet video: “Working Together for Safer 

Communities” 

Other: 

Georgia National Fire Plan Mitigation Projects

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Appendix

continued

24
1

Table A.2—State-level wildland fire mitigation programs and policies 

State Agency Program/Policy

Alabama Alabama Forestry 

Commission

Prescribed Burning or Fire Break Services:

Fire prevention advice with burn permit 

Firewise communities 

Publication: 

“Firewise landscaping for woodland homes” 

“Living with fire” 

“Safety guidelines for woodland homes” 

Internet: 

Fire prevention publications on Alabama Forestry 

Commission Web site (www.forestry.state.al.us)

Alabama Wildland Urban Interface councils

Alabama Wildfire Mitigation Program

Alabama Rural 

Community Fire 

Protection Institute and 

Alabama Fire College

Publication:

“Learn not to burn” 

Alabama Cooperative 

Extension Service 

Course: 

Prescribed burning certification course 

Internet: 

Private Forest Management Team Web site

Florida Florida Department of 

Community Affairs

Handbook:

“Best development practices for wildfire mitigation 

in Florida”

Florida Division of 

Forestry 

Prevention: 

Wildfire prevention clowns 

Smokey Bear 

Firewise communities 

Prescribed burning or fire break services 

Fire prevention advice with burn permit 

Internet: 

Florida Risk Assessment System 

Smoke screening tool 

Forestry fire management 

Other: 

Fire in Florida’s ecosystem (for teachers) 

Living on the edge in Florida (CD) 

Wildfire Risk Assessment Guide 

Florida Cooperative 

Extension Service

Internet:

Landscaping with Florida in mind

Georgia Georgia Forestry 

Commission

Firewise Program:

Firewise mobile exhibit 

Firewise Risk Assessment 

Prescribed Burning or Fire Break Services 

Fire prevention advice with burn permit 

Internet: 

Internet video: “Working Together for Safer 

Communities” 

Other: 

Georgia National Fire Plan Mitigation Projects

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

State Agency Program/Policy

Mississippi Mississippi Forestry 

Commission 

Internet:

“The role of prescribed burning in managing your 

southern pine forest” 

Prescribed burning or fire break services 

Fire prevention advice with burn permit 

Firewise Program: 

Teacher’s Wildfire Prevention Workshops 

Firewise Community Workshop 

Firewise Radio and TV public service 

announcements

South 

Carolina 

South Carolina Forestry 

Commission 

“Living on the edge in South Carolina” community 

workshop 

Internet Fact Sheets: 

“Fire and burning” information 

“Firewise” information 

“Protecting your home from wildfire” 

“Your home in the line of fire” 

Prescribed burning or fire break services 

Fire prevention advice with burn permit 

 “How to have a firewise home” 

“Think before you burn”

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Appendix

(continued)

25



Johnson-Gaither, Cassandra; Gan, Jianbang; Jarrett, Adam [and others]. 2011. Black belt 

landowners respond to State-sponsored wildland fire mitigation policies and programs. Gen. 

Tech. Rep. SRS–139. Asheville, NC: U.S. Department of Agriculture Forest Service, 

 Southern Research Station. 25 p.

This investigation focused on nonindustrial private forest (NIPF) landowners in selected 

counties across five States in the Southeastern United States (Alabama, Florida, Georgia, 

Mississippi, and South Carolina). These counties are located in the Southern Black Belt 

region, which has higher than average percentages of African-American residents and higher 

poverty rates than the United States as a whole. We assessed African-American and White 

private landowner awareness and responsiveness to State-sponsored wildland fire mitigation 

policies and programs. Other indicators of environmental awareness and engagement suggest 

that African-Americans rank lower than Whites on these measures in the South. We extend 

this research with a focus on awareness and responsiveness to wildland fire mitigation 

programming.

African-American landowners were more likely to be aware than White landowners of 

wildland fire mitigation programs, but less likely than Whites to use such information and 

less likely to engage in various other actions to reduce wildland fire threats to their property. 

In terms of constraints, African Americans who did not request mitigation information were 

more likely than Whites to say they did not do so because they did not know the information 

was available. However, African Americans were less likely to say lack of trust prevented 

them from requesting information. Overall, findings did not suggest that Black Belt AfricanAmerican landowners were disadvantaged with respect to either information awareness or 

acquisition; but results should be taken with caution given that nonrandom sampling was used 

for some data collection with the African-American sample.

Keywords: African-American landowners, Black Belt, poverty, wildfire mitigation, 

wildland-urban interface. 
The Forest Service, United States Department 

of Agriculture (USDA), is dedicated to the 

principle of multiple use management of the 

 Nation’s forest resources for sustained yields of wood, water, 

forage, wildlife, and recreation. Through forestry research, 

cooperation with the States and private forest owners, and 

management of the National Forests and National Grasslands, 

it strives—as directed by Congress—to provide increasingly 

greater service to a growing Nation.

The USDA prohibits discrimination in all its programs and 

activities on the basis of race, color, national origin, age, 

disability, and where applicable, sex, marital status, familial 

status, parental status, religion, sexual orientation, genetic 

information, political beliefs, reprisal, or because all or part 

of an individual’s income is derived from any public assistance 

program. (Not all prohibited bases apply to all programs.) 

Persons with disabilities who require alternative means for 

communication of program information (Braille, large print, 

audiotape, etc.) should contact USDA’s TARGET Center at 

(202) 720-2600 (voice and TDD).

To file a complaint of discrimination, write to USDA, 

Director, Office of Civil Rights, 1400 Independence Avenue, 

SW, Washington, D.C. 20250-9410, or call (800) 795-3272 

(voice) or (202) 720-6382 ( TDD). USDA is an equal 

opportunity provider and employer.

 The Forest Service, United States Department 

 of Agriculture (USDA), is dedicated to the 

 principle of multiple use management of the 

Nation’s forest resources for sustained yields of wood, water, 

forage, wildlife, and recreation. Through forestry research, 

cooperation with the States and private forest owners, and 

management of the National Forests and National Grasslands, 

it strives—as directed by Congress—to provide increasingly 

greater service to a growing Nation.

The USDA prohibits discrimination in all its programs and 

activities on the basis of race, color, national origin, age, 

disability, and where applicable, sex, marital status, familial 

status, parental status, religion, sexual orientation, genetic 

information, political beliefs, reprisal, or because all or part 

of an individual’s income is derived from any public assistance 

program. (Not all prohibited bases apply to all programs.) 

Persons with disabilities who require alternative means for 

communication of program information (Braille, large print, 

audiotape, etc.) should contact USDA’s TARGET Center at 

(202) 720-2600 (voice and TDD).

To file a complaint of discrimination, write to USDA, 

Director, Office of Civil Rights, 1400 Independence Avenue, 

SW, Washington, D.C. 20250-9410, or call (800) 795-3272 

(voice) or (202) 720-6382 ( TDD). USDA is an equal 

opportunity provider and employer.