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Author s personal copy, C J Gaither et al Forest Policy and Economics 13 2011 24 36 25. lived in the South representing 40 of total U S poverty Carl Vinson The greatest number of wildland res by region occurs in the. Institute of Government 2002 Along with high poverty concentra South National Interagency Fire Center Wildland Fire Statistics n d. tions however the South also contains areas of af uence in urban In 2007 one half of all reported wildland res in the nation occurred. metropolises such as Atlanta Georgia and wealth pockets in amenity in the thirteen states comprising the U S Forest Service s Southern. rich wildland areas The South contained six of the fastest growing Region in 2006 more than one half of all reported wildland res in. counties in the nation in terms of percentage change in population the nation were in the South and 42 of all large wildland res. from 1 April 2000 to 1 July 2009 U S Census Bureau 2009a reported were in this region Andreu and Hermansen B ez 2008. Population growth increases demand for housing and other In pre industrial times Native Americans and early European. development much of which contributes to the expanding Wildland settlers used re to reduce fuel loads The advent of agricultural and. Urban Interface or the WUI the area where structures and other industrial development during the nineteenth century resulted in. human development meet or intermingle with undeveloped wild wide spread loss of forest cover throughout the South To aid forest. land http silvis forest wisc edu projects WUI Main asp WUI regeneration in the early twentieth century re suppression. growth in turn increases the likelihood of wildland re ignition programs were implemented across the region However decades. caused by humans given the closer proximity of human dwellings of re suppression have resulted in substantial fuel buildup in. and activities to woodlands Macie and Hermansen 2002 Research Southern woodlands which contribute to an increased likelihood of. indicates that WUI expansion is driven largely by af uent migration to wildland re Fowler and Konopik 2007 Monroe 2002. peri urban areas Rodrigue 1993 Collins 2008a b In many In addition severe drought conditions over the past several years. instances then WUI settlement implies higher income strata have made some areas in the region especially susceptible to wildland. populating woodland and wildland areas 3 re In Florida for instance state re of cials reported 1847 wildland. Federal mandates for wildland re mitigation efforts prioritize res on state and private lands from January to April 2009 This. WUI communities Lynn and Gerlitz 2006 Western Governor s number represents an increase of 88 over 2008 gures for the same. Association 2002 This is justi able given the combination of period Florida Division of Forestry 2009. physical and social factors increasing population and housing The Southern Group of State Foresters 2005 report Fire in the. density contributing to higher wildland re risk in the WUI South identi es a number of factors contributing to the problem of. However less densely populated rural areas outside the WUI wildland re in the region These include the fact that there is. containing abundant vegetation may be at a comparable risk of relatively little federally owned land in the South which makes states. wildland re responsible for wildland re protection on greater than 94 of the. Importantly non WUI settlements have been found to contain region s land area Again the wildland urban interface WUI. higher percentages of lower income populations in contrast to the exacerbates wildland re threat in many areas and local re. WUI In Oregon and Washington Lynn and Gerlitz 2006 found a departments must contribute heavily to re suppression Also. higher percentage of poor people in a class of wildlands they term changing demographics in heavily forested areas makes the task of. Inhabited Wildlands as compared with the WUI As well analysis of prescribed burning harder to implement resulting in increased fuel. county level WUI data4 for the six states included in this study shows loadings in some communities. that non WUI acreage in nonmetropolitan counties5 varies positively. with percentage of population below the poverty threshold 3 Social vulnerability and wildland re risk. r 0 363 p b 0 0001 correlation between a county s WUI acreage. and percentage of population below poverty is r 0 439 p b 0 0001 Haque and Etkin 2007 write that an after the fact response to. Radeloff et al 2005 Hence those places where development is disaster emphasizing cleanup and recovery efforts has for the most. expanding into rural wildlands are less likely to be in high poverty part been replaced with a vulnerability resilience paradigm This. counties in Alabama Arkansas Florida Georgia Mississippi and perspective places as much emphasis on the social dimensions of. South Carolina disaster that is on suspected societal conditions and inequities which. Again however our interest in wildland re across these may cause some groups to be less prepared for and less able to recover. southeastern states concentrates on those socially vulnerable popula from hazard events as physical causes. tions that locate in nonmetropolitan areas outside the WUI Thus our In a review of the literature on poverty and disasters in the U S. analysis includes not just the WUI but also less densely settled high Fothergill and Peek 2004 describe disasters as a social phenome. vegetation places outside the WUI that contain long established non and cite a number of studies showing that poorer people are. socially vulnerable groups These populations are prevalent in Black more likely than other income groups to perceive greater risks from. Belt counties such as Jefferson County Mississippi and Perry County natural disasters but are less likely to respond to disaster warnings. Alabama where 37 5 and 31 7 respectively of the population is Poor people also suffer disproportionately from the physical and. classi ed as impoverished U S Census Bureau 2009b psychological impacts of disasters experience higher mortality rates. and nd it more dif cult to recover after disasters The authors. 2 Wildland re risk in the South conclude that these ndings illustrate a systematic pattern of. strati cation within the United States and that disasters often. Physiographic features contribute signi cantly to wildland re risk highlight a priori disparities in social well being Fothergill and. in the South Stanturf et al 2002 Monroe 2002 Critical factors are Peek 2004 p 103. long growing seasons with frequent rainfall and wind which Cannon in Haque and Etkin 1994 makes explicit social variables. contribute to abundant vegetation This growth along with a high that contribute to social vulnerability social economic and political. frequency of lightning strikes and lack of a persistent snow layer factors These factors can either enhance or detract from a commu. increase the likelihood of wildland re nity s ability to mitigate disaster Along similar lines Cutter et al. 2000 argue that socially vulnerable groups such as the elderly lower. Collins 2005 stresses that poor communities may coexist with af uent income racial minorities and women are more likely to be exposed to. populations in the WUI a larger number of hazards and or be less able to recover from. Data source Forest and Wildlife Ecology University of Wisconsin at Madison disasters e g chemical spills hurricanes wild re than wealthier. Wildland Interface Maps Statistics and GIS Download http silvis forest wisc edu. projects WUI Main asp, more able bodied individuals and communities Morrow 1999 and. As measured by the USDA s Rural Urban Continuum Codes http www ers usda Lynn and Gerlitz 2006 also posit that poor communities are less able. gov brie ng Rurality RuralUrbCon to absorb the effects of natural disasters. Author s personal copy, 26 C J Gaither et al Forest Policy and Economics 13 2011 24 36. Similar to Cutter et al 2000 Ojerio 2008 examined both analyses the CBG provides the most detailed spatial resolution. biophysical and social data to assess the vulnerability of census block publicly available. groups in Arizona to wildland re risks Results consistently showed. that census block groups comprised largely of poor non Whites. Navajo and Apache were less likely than majority white census 5 1 Wildland re susceptibility index. block groups to participate in either state sponsored grants aimed at. wildland re mitigation community wild re protection programs or We selected the Wildland Fire Susceptibility Index WFSI as our. the Firewise Community program indicator of wildland re risk The index is one of several indices. Importantly Collins 2008a critiques assumptions of risk expo produced by the Southern Wild re Risk Assessment SWRA The. sure in the First World which assume that higher income households SWRA is the rst comprehensive wildland re risk assessment of its. willingly expose themselves to risk by locating in aesthetically kind in the nation It is supported by the thirteen state forestry. pleasing yet ecologically fragile environments Marginalized groups agencies that comprise the USDA Forest Service s Southern Region in. he argues are rendered invisible in these settings Collins 2008a partnership with the USDA Forest Service USDI Fish and Wildlife. offers instead a political ecology view of risk exposure in developed Service USDI National Park Service Bureau of Indian Affairs and the. nations which makes marginalization relative He stresses that Department of Defense The WFSI measures on a scale of zero to one. socially vulnerable populations exist alongside the well heeled in the probability6 of an acre burning based on surface fuels and forest. places with high environmental risk in developed nations However conditions weather historical re sizes and historical suppression. state and market institutions local re protection and re risk effectiveness Buckley et al 2006a b. insurance act to insulate the rich from devastating loss in the event of The index includes three key components 1 probability of re. disaster by the provision of such services Marginal communities occurrence 2 re behavior and 3 re suppression effectiveness The. conversely absorb the risk avoided by the wealthy because of their rst component probability of re occurrence is comprised princi. relative inability to access these safeguards pally of Fire Occurrence Areas FOA and Weather In uence Zones. Collins 2008a focus is the contribution of institutions to the WIZ Buckley et al 2006a p 41 52 FOAs are determined by. facilitation of more af uent communities A more comprehensive look historical data pinpointing re ignition Quantitatively FOA is the. at the advantages accruing to the rich or disadvantages of the poor historical mean of ignitions calculated as the number of res per year. necessitates an examination of agency that is not just the larger per thousand acres Periods of re occurrence were not speci ed but. society shielding some sectors from harm but also the activities rather referred to generally as re history reports which we assume. initiated by the well off to insulate their properties from wild re loss were supplied by state and federal land management agencies Fire. Not only do the more af uent have better access to structural services ignition data were collected between 1997 and 2002. to mitigate re but residents act at the individual and community Weather also in uences probability of re occurrence To. level to prevent loss by engaging with mitigation programs in the incorporate this variable WIZs or weather zones were designated. communities where they live Such participation distinguishes upper for the thirteen southern states and daily weather observations for. income areas from poor and working class communities each WIZ were recorded from 1 January 1994 to 31 December 2003. Buckley et al 2006a Weather conditions were categorized into. percentiles that indicated conditions which were more or less. 4 Research hypothesis conducive to re ignition low moderate high and extremely high. percentiles Various land management agencies and the National. We expect that the type of association between social vulnerability Oceanic and Atmospheric Administration supplied weather data. and wildland re risk will vary geographically cluster with hot spot The second signi cant component of WFSI is Fire Behavior rate of. clusters high social vulnerability high wildland re risk prevalent in spread ROS crown re potential and ame length ROS is simulated. less densely populated rural areas We do not suppose that a using FB3 DLL Windows software commercial software licensed by. particular type of association for instance hot spots or cold Fire Program Solutions LLC Fire Behavior attributes in turn are. spots would characterize an entire state because again socially calculated based on surface fuels canopy closure canopy character. vulnerable populations also locate in urban areas with very low istics 7 and topography aspect slope elevation Surface and canopy. wildland re risk and more af uent populations concentrate in or fuels data were obtained from crosswalks of existing datasets Fire. near high wildland re risk rural areas However we expect fewer behavior is estimated in 30 30 m cells with speci c weather. wildland re mitigation programs to exist near hot spot clusters conditions ROS is calculated for the four weather categories low. compared to low social vulnerability high wildland re risk clusters moderate high and extreme. Lastly WFSI includes Fire Suppression Effectiveness which is a. H1 Communities with high wildland re risk and high social function of Final Fire Size FFS and ROS Fire suppression effective. vulnerability hot spots are less likely than communities with high ness is the comparison of actual re sizes to a theoretical size which. wildland re risk and low social vulnerability to be engaged with assumes re spreads under stable conditions with homogenous. wildland re mitigation programs weather and fuel conditions with no suppression activity Data used. for these calculations are from states and federal agencies for the time. 5 Methods period 1997 2002 The nal WFSI gure for a 30 30 m cell in a given. WIZ is the summation of the respective WFSI calculations for the four. To examine the association between wildland re risk and social weather percentile areas WFSI is available in a raster format. vulnerability in the six state region we rst identi ed indicators of To facilitate analysis at the CBG level basic statistics maximum. wildland re risk and social vulnerability at the Census Block Group mean minimum and standard deviation were calculated for all 30 m. CBG level We chose the CBG as the unit of analysis because this pixels within each CBG using the summarize zones function in the. geography approximates community groupings The U S Census ESRI s Environmental Systems Research Institute Spatial Analyst. Bureau de nes a CBG as an aggregation of blocks with blocks being. analogous to city blocks demarcated by streets in rural areas CBGs Although due to some necessary assumptions such as fuel homogeneity it is not. the true probability, can contain an extensive number of square miles and do not have 7. Data on canopy characteristics were limited by the lack of extant data and funding. street boundaries Also the CBG level approximates the spatiality at to collect primary canopy fuels data canopy ceiling height canopy base height and. which most wild res occur and for the variables included in our canopy bulk density Buckley et al 2006a p 49. Author s personal copy, C J Gaither et al Forest Policy and Economics 13 2011 24 36 27.
extension for ArcVIEW Values ranged from 0 to 0 86 mean 0 04 Census Bureau Summary File 3 sample data tables Data were. standard deviation 0 086 and median 0 005 obtained for each CBG in the six state region We downloaded total. population total African American population total population. 5 2 Social vulnerability index 25 years and older both male and female population 25 and older. with varying degrees of educational attainment total population for. Concurrently we constructed an index to measure social vulnera whom poverty was determined population with income below. bility SOVUL We de ne vulnerability as marginalization character poverty total housing units total mobile home units total occupied. ized by the lack of ability to assertively navigate social systems or to housing units and total renter occupied housing units. move progressively towards higher living standards in terms of material From these frequencies percent African American percent over 25. wealth and in uence As indicated a number of researchers have found without high school diploma percent below poverty percent mobile. a range of social indicators associated with an individual household or home dweller and percent renter were calculated Percentages for. community s ability to mitigate and or recover from disasters Cutter et each indicator e g percent below poverty black etc were summed. al 2000 identi ed eleven county level factors that in uence social to produce the SOVUL value for a given census block group Values. vulnerability These have to do with personal wealth housing stock and were not standardized and all variables are assumed to carry equal. tenancy percent mobile homes in county and race ethnicity Morrow weight. 1999 includes similar factors physically and mentally disabled SOVUL values ranged from 0 to 3 64 with a mean of 1 10 standard. elderly female headed households and the homeless Cutter et al deviation 0 64 and median 1 03 Values larger than the mean indicate. 2003 developed a Social Vulnerability Index SoVi8 which examines high social vulnerability Zero values would be observed in the case of. how socio demographic characteristics in uence climate related CBGs with no population. hazards drought oods hurricane force winds and sea level rise in. the southeast Oxfam 2009 Wildland re hazard is not included 6 Exploratory spatial data analysis. among the environmental risks this group examines, Our SOVUL index includes percent of population below poverty 6 1 Bivariate clusters of wildland re risk and social vulnerability. percent of population 25 or older without a high school diploma. percent African American percent of housing structures that are We use the LISA statistic localized indicator of spatial association. mobile homes and percent of renter occupied housing units Each of to test the strength of association between WFSI and SOVUL and also. these variables can have a direct bearing on social vulnerability for to map these associations at the CBG level Anselin 1995 The. both individuals and communities As discussed persons or house correlation statistic indicates how observations of a variable in a given. holds below poverty and those with lower education levels typically CBG say i are associated with observations of a different variable in. have less ef cacy in obtaining services or information about adjacent CBGs or the neighborhood of the ith CBG In our case this. environmental protection Also race often gures into issues involving involves correlations between WFSI in an areal unit i and SOVUL in. services and information access White middle class neighborhoods the cluster of CBGs surrounding and including the ith CBG. and communities typically have a greater number of facilities and Neighboring CBGs or the neighborhood of the ith CBG was de ned. services compared to poorer minority areas Taylor et al 2007 based on a rst order contiguity weight matrix CBGs adjacent to the. Taylor 2000 Wolch et al 2002 ith CBG sharing a common border length or at least a vertex were. Racial status tends to correlate positively with other socio considered to be in the neighborhood The mean neighborhood value. demographic and economic indicators such as those included in our for SOVUL and WFSI includes the value for the variable in the ith CBG. index particularly poverty and education However we also believe as well as the values for all CBGs adjacent to it This was achieved by. that the descriptor African American or Black carries an additional manually editing the weight matrix les. weight beyond that of income or education This relates to both overt Bivariate LISA statistics were used in GeoDa 0 9 5 I to map four. and more subtle forms of discrimination from the larger society and different types of spatial clusters for WFSI and SOVUL at the CBG level. also to self imposed racial segregation which continues de facto racial For WFSI for example clusters include 1 High High CBGs with high. separation Mobile homes are less able to withstand natural disasters wildland re risk surrounded by CBGs with high social vulnerability. such as hurricanes because the building material is generally of lower 2 Low Low CBGs with low wildland re risk surrounded by CBGs. quality than constructed dwellings This may also be the case with re with low social vulnerability 3 Low High CBGs with low wildland. resistance as mobile structures are less likely than constructed homes re risk surrounded by CBGs with high social vulnerability 4 High. to be made of re resistant durable materials Finally renters have Low CBGs with high wildland re risk surrounded by CBGs with low. less control over building materials landscaping re insurance or social vulnerability. other safeguards against wildland re which could result in greater Again the high and low level of a given variable is de ned in. vulnerability for this group reference to its mean value for the neighborhood We de ned High. Because of overlaps between race and the other variables included High and Low Low clusters as hot spots and cold spots. in SOVUL we examined the degree of multicollinearity for the respectively where the association between two phenomena is. variables comprising the index by examining a regression model positive For the other clusters Low High and High Low the. where WFSI was the dependent variable and percent black percent associations are negative and are described as spatial outliers. below poverty percent low education percent renter and mobile Anselin 2005 LISA scores signi cant at p 0 05 or less were used. home were predictors Here we wanted to detect in ated standard to map statistically signi cant clusters Pseudo p values were. errors by looking at the variance in ation factor VIF as multi generated for LISA statistics utilizing 999 permutation criteria. collinearity is indicated by uctuating standard errors Generally VIF available in GeoDa 0 9 5 I www geodacenter asu edu. values greater than ten may indicate multicollinearity among The following equation Sunderlin et al 2008 provides the. variables VIF values for each of our predictors were below three computation of bivariate LISA based on Anselin 1995. which suggests low or moderate multicollinearity Frequencies for N. variables comprising SOVUL were downloaded from the 2000 U S Il zxi wij zyj 1. SoVi includes eight variables which explain 75 of the variance in social. vulnerability The variables are wealth age race ethnicity rural residence special where Il is the local Moran s I LISA x and y are two variables of. needs populations gender and employment Oxfam 2009 interest measured for CBG i and neighborhood j respectively. Author s personal copy, 28 C J Gaither et al Forest Policy and Economics 13 2011 24 36. Similarly zx and zy represent the standardized z scores for variables x To make the interpretation easier and more meaningful cluster. and y respectively The term wij is the weight matrix that de nes the maps for each state are overlaid with interstate highway and federal. structure of the neighborhood LISA and weight matrices were created land areas Geo visualization of clusters with such recognizable. in GeoDa 0 9 5 I This analysis uses a rst order queen contiguity gures provides reference for illustrating the spatial location of. matrix where wij 1 if the adjacent CBG j shares a common border clusters For example in the analysis for Alabama Fig 1 red clusters. length or common vertex with the ith CBG If a common border is not or hot spots are located in the southern part of the state mostly south. shared the value is zero of Interstate 85 and US 80 Interestingly this portion of the state. contains relatively less federal land area compared to areas north of. those highways South Alabama also contains large areas of light blue. 6 2 Results clusters which again indicated high social vulnerability CBGs in the. neighborhood of low wildland re risk CBGs, 6 2 1 ESDA at the state level The overall pattern of high social vulnerability red and light blue. Figs 1 6 show bivariate LISA analyses for each state In each gure patches follows the spatiality of Alabama s impoverished Black Belt The. the red color indicates clusters of high wildland re risk CBGs located more socially vulnerable clusters are located almost exclusively in the. in neighborhoods or clusters with high social vulnerability High southern part of the state The present analyses demonstrate how low. High dark blue clusters denote low wildland re risk CBGs in socio economic status or socially vulnerable communities intersect with. clusters with low social vulnerability Low Low low wildland re wildland re risk In some areas of the state s Black Belt there is an inverse. risk high social vulnerability clusters are shown in light blue Low association between social well being and this type of environmental risk. High and high wildland re risk low social vulnerability clusters are light blue whereas in others the association is positive red. colored mango High Low White areas within the study area North Alabama stands out as a near antonym to the southern part. represent CBGs where the spatial association between WFSI and of the state in terms of social well being From Birmingham and. SOVUL is not statistically signi cant Tuscaloosa northward the state contains remarkably more low. Federal Lands,High Wildfire Risk High Socia l Vulnerability. Low Wildfire Risk Low Social Vulnerability,Low Wildfire Risk High Socia l Vulnerability.
High Wildfire Risk Low Socia l Vulnerability, Note The clusters are based on bivariate LISA Statistic significant al p 0 05. lJI tIite areas represent census block groups where the association is insignificant. Fig 1 Bivariate LISA based spatial clusters showing the local association between wildland re risk and social vulnerability in Alabama. Author s personal copy, C J Gaither et al Forest Policy and Economics 13 2011 24 36 29. CIfoIPP Community,Firewise Commun y,W Federal lands. High VVildfire Risk Hfgh Social Vulnerabil y,l ow Wildfire Risk l ow Social Vulnerability. l ow Wildfire Risk High Social Vulnerability, Note The clusters are based on Bivariate U SA Statistic sign ificant at p 0 05 High VVildfire Risk low Social Vulnerabilily.
Vv11i1e areas represent the Census Block Groups where th e association is insignificant. Fig 2 Bivariate LISA based spatial clusters showing the local association between wild re risk and social vulnerability in Arkansas. socially vulnerable clusters The dark blue Low Low clusters predom area The only exception to this pattern is the light blue High Low. inate in the north but high re risk areas also intersect with more area of central city Birmingham The cluster here is similar to that in. well off communities in north Alabama in the Huntsville Florence the rural Black Belt south of Interstate 20 This is not surprising given. Firewise Community,CWPP Community,Federal Lands,Hig h Wildfire Risk High Social Vulnerability. Low Wildfire Risk Low Social Vulnerability,Low Wildfire Risk High Social Vulnerability. Hig h Wildfire Risk Low Social Vulnerability, Note The clusters are based on bivariate U SA Statistic significant at p 0 05. Vv11ite areas represent census block grou ps where the association is insignificant. Fig 3 Bivariate LISA based spatial clusters showing the local association between wildland re risk and social vulnerability in Florida. Author s personal copy, 30 C J Gaither et al Forest Policy and Economics 13 2011 24 36. CWPP MS CountLcentroid Merg,L CWPP Community,Firewise Community.
W Federal Lands,High Wildfire Risk High Social Vulnerability. Low Wildfire Risk Low Social Vulnerability,Low Wildfire Risk High Social Vulnerability. High Wildfire Risk Low Social Vulnerability, Note The clusters are based on bivariate LISA Statistic significant at p 0 05. lMlite areas represent census block groups where the association is insignificant. The CWPP sign at the Japer City represents 7 CWPP Communities. Fig 4 Bivariate LISA based spatial clusters showing the local association between wildland re risk and social susceptibility in Georgia. that roughly 73 of Birmingham s city population is African American In Florida Fig 3 more af uent communities are located along the. U S Census Bureau 2000 A similar phenomenon occurs around coast from the Jacksonville area on the Atlantic coast down to. other major cities in the region Titusville and West Palm Beach Low socially vulnerable clusters. A moderate clustering northeast of Montgomery and in the state s extend inland to the Everglades on Florida s southern tip and up the. panhandle region is also characterized by high re risk low social Gulf coast from the Naples and Fort Myers area along the coastline of. vulnerability Near Mobile there is a small light blue cluster Sarasota up to the Tampa St Petersburg region As well higher re. approximating the location of central city Mobile 56 African risk is associated with higher income communities on both the. American that is low wildland re risk high social vulnerability Atlantic and south Gulf coasts and in the upper Everglades region Hot. Fig 2 also shows rough demarcations along socio economic lines spots are clustered in extreme north central and south central Florida. in Arkansas The eastern portion of the state south of Interstate 30 40 Similar to Alabama and Arkansas social vulnerability in Georgia also. contains more socially vulnerable CBGs however there are only two varies geographically with south Georgia containing noticeably more. distinct hot spot clusters in southeast Arkansas A light blue area is socially vulnerable clusters compared to suburban Atlanta area and. again evident near the state s capital city Little Rock but areas to the points north Fig 4 shows segments of the southern Black Belt. north and west of Little Rock are either dark blue or mango which denoted by light blue clusters and a spattering of hot spot red clusters. indicate low social vulnerability In this state too high wildland re mainly south of Atlanta running along a line from southwest Georgia. risk areas do not overlap with federal lands northeast to the South Carolina boarder In contrast dark blue clusters. Author s personal copy, C J Gaither et al Forest Policy and Economics 13 2011 24 36 31. l CWPP Community,Firewise Community,W Federal Land s.
High Wi ldfire Risk High Social Vulnerability,Low Wi ldfire Risk Low Social Vulnerability. Low Wi ldfire Risk High Social Vu lnerability,High Wi ldfire Risk Low Social Vu lnerability. Note The clusters are based on bivariate LISA Statistic significant at p 0 05. VV11ite areas represent census block groups where the association is insignificant. Fig 5 Bivariate LISA based spatial clusters showing the local association between wildland re risk and social susceptibility in Mississippi. are located mainly in the periphery of metropolitan Atlanta and in southwest Mississippi but Jackson is similar to other larger cities in. northeast Georgia around the Chattahoochee National Forest terms of low re risk and high social vulnerability With the exception. The Chattahoochee portion of the Chattahoochee Oconee National of an area to the immediate east of Interstate 55 and extreme east. Forest is located in a high re risk area along Georgia s northern border central Mississippi more areas in the western part of the state are. with North Carolina however the Oconee preserve in the Piedmont characterized by low social vulnerability In the north low social. between Interstates 20 and 16 is not The light blue coloring vulnerability intersects more with low wildland re risk whereas in. distinguishes central city Atlanta from its more af uent suburbs North the south low social vulnerability crosses with higher re risk. of Atlanta there are also mango colored areas which suggests higher re Finally Fig 6 shows a large portion of east South Carolina in hot. risk in concert with higher socio economic status As well there are spot clusters Hot spots overlap with the Francis Marion National. smaller clusters of mango in southeast Georgia near Savannah Forest along the Atlantic coast and also with the Sumpter National. Mississippi northwest of Interstate 55 contains the low lying Forest on the Georgia border There are smaller dark blue areas along. Mississippi Delta or alluvial plain which historically has been the state s east coast but these clusters are located more in the. associated with high poverty rates and is indicated in Fig 5 by light upstate region around Greenville Spartanburg and Columbia A. blue color In this region there is little overlap between social spattering of mango is also along the coast and in the extreme upstate. vulnerability and wildland re risk given the higher moisture content region near Greenville. of this terrain Wildland re risk is positively associated with social As expected our analyses identi ed socially vulnerable clusters. vulnerability in a central Mississippi cluster north of Jackson and also which coincide with the rural Black Belt across the region Again. Author s personal copy, 32 C J Gaither et al Forest Policy and Economics 13 2011 24 36. Firewise Community,1 CWPP Community,W Federal Lands. High Wi ldfire Risk High Social Vulnerability,Low Wildfire Risk Low Social Vulnerability.
Low Wildfire Risk High Social Vulnerability,High Wildfire Risk Low Social Vul nerability. Note The clusters are based on bivariate LISA Statistic significant at p 0 05. VVhite areas represent census block groups where the association is insignificant. Fig 6 Bivariate LISA based spatial clusters showing the local association between wildland re risk and social vulnerability in South Carolina. however elevated wild re risk did not overlap with social vulnera theoretical size which assumes the re is spreading under steady. bility in some areas of south Alabama southwest Georgia and the conditions with no suppression activity Built infrastructure such as. Georgia Piedmont This lack of association may be explained in part roads and re ghting services contribute to re suppression ef cacy. by the three components of WFSI i e weather conditions contrib Poor road networks in some parts of west Alabama may contribute to. uting to re occurrence re behavior and suppression low re suppression scores and hence higher WFSI scores in these. Naturally occurring res are caused by lightning Peak lightning CBGs Road quality can change abruptly depending upon county. concentrations occur along the coast where sea breeze forced resources Poor roads as well as mountainous landscape are also. thunderstorms are common Higher WFSI clusters are clearly seen factors that would contribute to low re suppression effectiveness. in the Gulf areas of Alabama and Mississippi and along Florida s raising the re risk in northern Georgia Contrast the higher re risk. coastline The coastal plain is also characterized by a higher for the Chattahoochee National Forest in north Georgia with the lower. percentage of plant communities that burn with greater intensities risk for the Oconee preserve in the Georgia Piedmont southeast of. on average than upland areas In contrast to the coast and coastal Atlanta Most federal lands however have dedicated re suppression. plain south Alabama southwest Georgia and the Georgia Piedmont resources which lowers re risk in their vicinity. are not characterized by these physical conditions. Those areas of southwest Alabama and other states with adjacent 6 2 2 Spatial associations by type. Low High and High High clusters seem contradictory but may be Distribution of CBGs by cluster type was tabulated for each state. explained by the re suppression component of WFSI To recount re and is presented in Table 1 In all of the states about one quarter of. suppression effectiveness is the comparison of actual re sizes to a total CBGs were found to have negative associations between. Distribution of CBGs for Alabama Arkansas Florida Georgia Mississippi and South Carolina according to types of local spatial association between WFSI and SOVUL. Types of association Alabama Arkansas Florida Georgia Mississippi South Carolina Total. CBG N CBG CBG N CBG CBG N CBG CBG N CBG CBG N CBG CBG N CBG CBG N CBG. High wildland re risk high 85 2 55 6 0 28 405 4 46 58 1 21 44 2 05 248 8 68 846 3 48. social vulnerability, Low wildland re risk low 543 16 31 268 12 95 1425 15 68 887 18 53 301 14 02 549 19 21 3973 16 36. social vulnerability, Low wildland re risk high 589 17 69 344 16 62 1269 13 96 899 18 78 356 16 58 327 11 44 3784 15 58. social vulnerability, High wildland re risk low 142 4 27 144 6 95 890 9 79 266 5 56 144 6 71 91 3 18 1677 6 91. social vulnerability, Insigni cant 1970 59 18 1307 63 17 5099 56 11 2678 55 93 1302 60 64 1643 57 49 13 999 57 66.
Total 3329 100 2069 100 9088 100 4788 100 2147 100 2858 100 24 279 100. Author s personal copy, C J Gaither et al Forest Policy and Economics 13 2011 24 36 33. wildland re risk and social vulnerability i e either had high Firewise Community locations from a national Firewise manager for. wildland re risk and were located in higher status neighborhoods each of our states A total of 145 active Firewise Communities were. or had low wildland re risk and located in more socially vulnerable reported Alabama 1 Arkansas 91 Florida 38 Georgia 10. neighborhoods South Carolina had the highest percentage of CBGs Mississippi 1 and South Carolina 4 It was more dif cult to secure. classed as hot spots 8 68 and Arkansas had the lowest 0 28 CWPP locations The NFP website lists 730 Communities at Risk for. South Carolina also had the highest percentage of cold spots 19 21 wildland re in the South covered by a CWPP in 2008 http www. and again Arkansas had the lowest cold spot percentage 12 95 forestsandrangelands gov reports documents healthyforests 2008. Florida had the highest percentage of High Low clusters 9 79 and healthy forests report fy2008 pdf however the location of these. South Carolina the lowest 3 18 CWPPs is not mapped by NFP managers. The row totals show that roughly 3 5 of CBGs in the region were We contacted the individual state forestry agencies to obtain. hot spots About 16 of CBGs were in either cold spot areas or Low CWPP locations For some states CWPP data had not been assembled. High clusters and roughly 7 were in High Low social vulnerability at the state level In the case of Florida for instance individual re. areas About 58 of the CBGs in the region exhibited no signi cant districts forwarded latitudinal and longitudinal coordinates to us and. association between wildland re risk and social vulnerability we mapped CWPP locations at the CBG Mississippi establishes. county wide CWPPs so the CWPPs listed for that state represent a. 6 2 3 Distribution of wildland re mitigation programs across the central point in the respective counties We obtained the most. Southeast complete listing of CWPP sites for each state that was available. Our primary objective is to examine the spatial relationship although these listings may not be exhaustive Alabama 1 Florida. between 1 hot spots and wildland re mitigation programs and 2 10 Georgia 10 Mississippi 34 and South Carolina 2 but we. High Low areas and wildland re mitigation programs We would did have a complete listing for Arkansas 109. assume that those areas across the region identi ed as being highly Despite their limitations these mappings represent the rst efforts. susceptible to wildland re occurrence would have a greater number of which we are aware that attempt to locate CWPP locations in the. of mitigation programs compared to low re risk communities Our South Both CWPP and Firewise programs locations are typically. aim is to determine how such programs may be distributed in areas associated with residential or a community association address rather. that are also socially vulnerable than a centralized address removed from communities thus the. There are a number of federal state and local level mitigation coordinates for mitigation programs directly re ect community. programs across the country Three key programs are Community involvement. Wild re Protection Plans CWPPs Firewise Communities and To test the hypothesis that hot spots are less likely than High Low. hazardous fuels reduction programs on federal lands The latter are areas to be engaged with wildland re mitigation programs we. funded by the USDA Forest Service and USDI Department of Interior computed the mean distance in kilometers between hot spots and. through the Healthy Forest Initiative and the National Fire Plan NFP High Low clusters respectively to the nearest CWPP location and. http www forestsandrangelands gov reports documents healthy Firewise program Distances were computed in ArcGIS using the. forests 2008 healthy forests report fy2008 pdf Fuels reduction simple distance feature to determine the straight line distance from. programs in the form of prescribed burns or mechanical thinning hot spot and High Low clusters for Firewise and CWPPs respectively. might occur on any federal lands with fuel loads suf cient to warrant CWPP and Firewise location data were also combined into a single. reductions in loadings Communities adjacent to those lands would generic layer representing the location of both types of community. accrue bene ts of such treatments mitigation programs and the distances from hot spots and High Low. We are interested in mitigation efforts involving signi cantly more CBGs to the nearest programs were estimated. community initiative and input CWPPs or Community Wild re Table 2 contains means standard deviations and t tests generated. Protection Plans are also funded by the NFP but are founded principally from the analyses Results show that the average distance from hotspots to. by communities rather than public agencies Communities at risk for CWPPs was signi cantly longer than from High Low clusters to CWPPs in. wildland re collaborate with public agencies local re departments Arkansas Georgia Mississippi and South Carolina The distance was. and municipalities to prioritize private landholdings needing hazard signi cantly shorter in Alabama but not signi cant in Florida For Firewise. ous fuel reduction and recommend appropriate treatments to reduce the mean distance between hot spots and these programs was longer for. future wildland re threats http hazardmitigation calema ca gov Florida Georgia and South Carolina but shorter for Alabama and. hazards natural re Typically state forestry agencies provide infor Mississippi and not signi cant for Arkansas For the combined programs. mation to at risk communities about CWPPs but individual commu mean hot spot distance was longer for all states except Alabama. nity groups or municipalities must take ownership of the plan by It should be noted that the mean distances between a cluster type. becoming active partners with sponsoring agencies and program locations in some cases are the same or very similar This. Similarly the national Firewise Communities program involves has to do with the way hotspots and programs are spatially arranged. signi cant community input These programs are intended to on the ground For instance if most of the hotspots in a state are. reach beyond the re service by involving homeowners community located close to a particular CWPP program their mean distance to. leaders planners developers and others in the effort to protect CWPPs and mean distance to CWPP and Firewise combined would be. people property and natural resources from the risk of wildland the same if there are no Firewise programs in the area Similar. re before a re starts http www rewise org Because of the observations were observed between distances to CWPP and. commitment and involvement required for successful implementa distances to Firewise if a state had only a few programs that are. tion and running of both CWPPs and Firewise programs we believe located close to each other. that communities with higher social and human capital assuming Of the 18 comparisons made 12 or 66 indicated a longer average. high wildland re risk would be more likely than lower capital distance between hot spot clusters and High Low clusters Because. communities or those communities rating high in social vulnerability there was only one CWPP and Firewise in Alabama one Firewise. to establish these programs location in Mississippi and two CWPPs in South Carolina these. We selected CWPPs and Firewise Communities as indicators of comparisons should be taken with some caution If these comparisons. mitigation programs on the ground We realize there are other and the combined category for Alabama are excluded from the. programs at the local and state level that could also be included but analyses eleven of the remaining thirteen means show longer. the dif culty of obtaining data on such programs across the study area distances for hot spots 84 6 Overall results support the research. prohibits their inclusion We obtained complete and current listings of hypothesis and suggest that communities with both higher re risk. Author s personal copy, 34 C J Gaither et al Forest Policy and Economics 13 2011 24 36. Table 2 While we acknowledge that individual landowner preferences for. Mean distance of CWPP Firewise and combined CWPP Firewise programs to high mitigation may vary we also submit that speci c socio cultural practices. Wfsi SOVUL hotspot and high WFSI low SOVUL clusters in Alabama Arkansas. Florida Georgia Mississippi and South Carolina, regarding landownership rights inhibit more socially vulnerable groups. from engaging in mitigation Speci cally the practice or system of heir. State Types of CBG CWPP mean Firewise CWPP and property ownership among lower income southern landowners may. association N km stand mean km Firewise mean, work to constrain involvement in land improvement initiatives Building. dev stand dev km stand dev, on Collins 2008a thesis that the environmental values of distinct socio.
Alabama High 85 173 30 172 40 172 40, cultural groups in uence community exposure to wildland re risk we. WFSI high 85 01 86 58 86 58, SOVUL posit that differences in hot spot and High Low community engagement. High 142 227 19 249 09 227 19 with mitigation may be explained in part by cultural norms reifying. WFSI low 15 74 168 93 157 41 communal ownership of land in the South. SOVUL t 13 50 t 16 07 t 14 35 Heir property or tenancy in common is inherited land which is. Arkansas High 6 27 42 25 10 24 75, passed on intestate without clear title typically to family members. WFSI high 13 27 13 01 12 79, SOVUL Although such owners have legal claims to land there are no. High 144 18 90 25 87 16 89 demarcations of the land specifying what amount is held by a single. WFSI low 17 22 19 87 16 53 individual Dyer et al 2009 Dyer and Bailey 2008 With each. SOVUL t 2 14 t 0 21 t 2 05, succeeding generation individual ownership interests shrink because.
Florida High 405 75 45 34 28 33 56, WFSI high 44 13 23 53 23 83 of the growing number of heirs. SOVUL Mitchell 2001 estimates that 41 of African American owned land in. High 890 77 41 28 03 26 57 the southeastern U S is heir property and Craig Taylor 2000 in Dyer. WFSI low 45 06 22 77 23 00 and Bailey 2008 states that heir property represents the most wide. SOVUL t 2 87 t 15 38 t 16 92, spread form of property ownership in the African American Community. Georgia High 58 145 52 92 61 92 41, WFSI high 54 52 37 68 37 69 But Dyer et al 2009 caution against overestimates arguing that few. SOVUL systematic investigations of heir property prevalence have been con. High 266 74 65 55 49 55 37 ducted because of the meticulous methodology required to classify such. WFSI low 46 29 32 29 32 37, properties Although much of the scholarship on heir property concen. SOVUL t 16 40 t 12 51 t 12 50,Mississippi High 44 26 74 304 47 26 74.
trates on southern blacks this type of ownership is also prevalent among. WFSI high 19 88 113 72 19 88 Appalachian whites Deaton et al 2009. SOVUL There are a number of problems associated with heir property and. High 144 14 68 377 01 14 68 land management Principle among these is that the lack of clear title. WFSI low 12 43 126 89 12 43, prohibits participation in any government sponsored home improvement. SOVUL t 6 15 t 11 04 t 6 15, South High 248 276 33 150 33 150 33 programs Also property owners cannot use heir property as collateral for. Carolina WFSI high 39 26 64 11 64 11 a mortgage and selling timber from such land is virtually impossible. SOVUL because a buyer would have to secure the consent of all heirs for a sale and. High 91 234 18 124 44 124 44, most buyers are unwilling to do so Besides this the lack of clear title acts. WFSI low 106 95 68 77 68 78,SOVUL t 4 83 t 8 25 t 8 25. as a disincentive to the improvement of real property attached to land If a. Total 2523 structure were remodeled the increase in value would not accrue to the. individual who paid for the upgrade but again must be disbursed among. signi cant at 0 05 or less, all heirs regardless of where they live Dyer et al 2009 Dyer and Bailey.
2008 In many cases heirs may not even live in the same state as the. and higher levels of social vulnerability are less involved with these property location Drawing from economics Deaton et al 2009 argue. particular wildland re mitigation programs that such impediments result in ef ciency problems which occur when. the existing uses of the property result in lower net bene ts to the. 7 Discussion and conclusion cotenants than might otherwise be achieved Viewed from the lens of. pro t maximization land use in such scenarios is underutilized. Reasons why socially vulnerable communities are less engaged We submit that heir property holders would also be less motivated. with Firewise Communities or CWPPs may have to do with a range of to participate in wildland re mitigation because of the communal. factors emanating from lack of interest to again a dearth of social and nature of their land interest Again any fees land clearing structure. human capital in these communities A state forester in Florida preparation or other time commitments to CWPP or Firewise would be. stressed that information about CWPPs Firewise and other mitiga likely be borne by the residing heir or others living closer to the. tion programs is readily available from the Florida Division of Forestry property While all heirs would not have to consent to mitigation. but individual homeowners and communities express varying levels planning the disproportionate involvement by one or a few heirs might. of interest in adopting the programs 9 Also unpublished data from our deter participation because of costs necessary to insulate structures or. recent analysis of southern landowner knowledge and understanding clear land either on or off one s property Deaton et al s 2009 case. of wildland re mitigation programs indicated that overall roughly study from Kentucky illustrates how cotenants unwillingness to cut. 40 of landowners reported that they had done nothing to prevent timber from their land had the unintentional consequence of increasing. wild re on their rural land and nearly 46 of African Americans said undergrowth resulting in increased fuel loading. they had taken no action to mitigate wild re although blacks were Deaton et al 2009 describe heir property management as a. more likely than whites to say they aware of mitigation information It tragedy of the anti commons in that heirs of jointly held land can. may be that awareness or knowledge possession among African prevent any single heir from certain land uses some of which would. Americans does not translate easily into action either in the form of yield pro ts or potentially lessen hazards In contrast to the overuse. mitigation efforts on one s own land or for the formation of tragedy of the commons problem with heir property the con ict. community efforts like Firewise or CWPPs involves under or nonuse. Also a key factor in mitigation success for CWPPs is collaboration. with and federal agencies U S Forest Service U S Bureau of Land. Personal communication 2010 Gerry Lacavera Florida Division of Forestry Management Communities are expected to draw on the expertise of. Author s personal copy, C J Gaither et al Forest Policy and Economics 13 2011 24 36 35. these agencies for plan preparation and develop a trust in agency the Centers for Urban and Interface Forestry Available online at www south. ernwild rerisk com reports FireInTheSouth2 pdf Date accessed 11 January 2009. responsiveness This type of involvement might deter southern rural Anselin L 1995 Local indicators of spatial association LISA Geographical Analysis 27. African Americans in general whether heir property owners or not 2 93 115. from participating in re mitigation planning Anselin L 2005 Exploring spatial data with GeoDaTM a workbook Spatial Analysis. Laboratory Department of Geography University of Illinois at Urbana Champaign. African Americans have lost land due to multiple factors including Urbana Illinois U S A. lack of understanding of estate planning and taxation and also from Blaikie P Cannon T Davis I Wisner B 1994 At Risk Natural Hazards Peoples. various forms of discrimination perpetuated through federal agencies Vulnerability and Disasters Routledge New York. Buckley D Berry J K Spencer T 2006a Quantifying wildland re risk in the south Sanborn. The 1997 class action law suit Pigford versus Glickman initiated by Total Geospatial Solutions Available online at http www southernwild rerisk com. black farmers alleging systematic discrimination on the part of the downloads reports Sanborn 20 20Quantifying Wildland Fire Risk in South pdf. USDA exempli es this latter problem and also highlights the some Date accessed 11 June 2009. Buckley D Carlton D Krieter D Sabourin K 2006b Southern wild re risk assessment. times antagonistic relationship between Southern black landowners. project nal report Available online at http www southernwild rerisk com reports. and governmental agencies Despite a settlement in the Pigford case projectreports html Date accessed 6 April 2010. that favored black farmers there remains an atmosphere of mistrust Cannon T 1994 Vulnerability analysis and the explanation of natural disasters In. and apprehension on the part of some black Southern landowners Varley A Ed Disasters Development and Environment John Wiley and Sons. New York pp 13 30, towards the federal government and other public agencies Carl Vinson Institute of Government 2002 Dismantling Persistent Poverty in the. Dyer and Bailey 2008 and Deaton et al 2009 write that the Southeastern United States Carl Vinson Institute of Government University of. drawbacks of heir property are countered by a socio cultural Georgia Athens. Collins T W 2005 Households forests and re hazard vulnerability in the American. understanding of extended family and its relationship to home This west a case study of a California community Environmental Hazards 6 23 37. landownership form fosters a collective identity which has been a Collins T W 2008a The political ecology of hazard vulnerability marginalization. cornerstone of rural culture especially among southern African facilitation and the production of differential risk to urban wild res in Arizona s. White Mountains Journal of Political Ecology 15 21 43. Americans Heir property arrangements allow cotenants to maintain Collins T 2008b What in uences hazard mitigation Household decision making. strong bonds and a connection to the land the land not individually about wild re risks in Arizona s White Mountains The Professional Geographer 60. owned but shared by those counted as family Indeed with heir 508 526. Craig Taylor P 2000 Through a colored looking glass a view of judicial partition. property family members can more easily establish residences by family land loss and rule setting Washington University Law Quarterly 78. simply putting mobile homes on the land The more rigorous process of 737 788. home building is avoided The rural countryside of the South is dotted Cutter S L Mitchell J T Scott M S 2000 Revealing the vulnerability of people and. places a case study of Georgetown South Carolina Annals of the Association of. with such small communities of kin characterized by clusters of mobile. American Geographers 90 4 713 737, homes and simple houses Again however mobile homes are a key factor Cutter S L Boruff B J Shirley W L 2003 Social vulnerability to environmental. which increases social vulnerability thus exacerbating wildland re risk hazards Social Science Quarterly 84 242 261. Our objective in highlighting heir property should not be interpreted Deaton B J Baxter J Bratt C S 2009 Examining the consequences and character of. heir property Ecological Economics 68 2344 2353, as a fatalistic culture of poverty explanation for poor people s lack of Dyer J F Bailey C 2008 A place to call home cultural understanding of heir property. participation in wild re mitigation programs but rather to point out a among rural African Americans Rural Sociology 73 3 317 338. distinct socio cultural landownership arrangement that many help to Dyer J F Bailey C Van Tran N 2009 Ownership characteristics of heir property in a Black. Belt County a quantitative approach Southern Rural Sociology 24 2 192 217. explain land management ef cacy Evans A DeBonis M Krasilovsky E Melton M 2007 Measuring Community. This was an exploratory investigation into the relationship between Capacity for Protection from Wild re Forest Guild Research Paper. social status and wildland re risk as such study limitations were Florida Division of Forestry 2009 Daily reports on wildland re activity Available. online at http www dof com wild re stats daily reports html Date accessed. identi ed These relate to our measurement of social vulnerability We 9 June 2009. argued that community capacity or involvement with mitigation Fothergill A Peek L A 2004 Poverty and disasters in the United States a review of. programs is a key factor distinguishing communities however the recent sociological ndings Natural Hazards 32 1 89 110. Fowler C Konopik E 2007 The history of re in the southern United States Human. components of SOVUL percent black below poverty are primarily Ecology Review 14 165 176. individual level variables While individual characteristics are important Haque C E Etkin D 2007 People and community as constituent parts of hazards the. vulnerability markers community level variables indicating natural signi cance of societal dimensions in hazards analysis Natural Hazards 41 271 282. Lynn K Gerlitz W 2006 Mapping the relationship between wild re and poverty In. amenities e g proportion of seasonal recreation homes or number of. Andrews P L Butler B W Eds Fuels Management How to Measure Success. new housing permits or other types of mitigation services offered by Conference Proceeding USDA Forest Service Proceedings Rocky Mountain Research. municipalities would help to sharpen a social vulnerability index speci c Station Fort Collins 2005 pp 401 415 Available online at http www fs fed us rm. to wildland re For instance we would expect to nd positive correlations pubs rmrs p041 rmrs p041 401 415 pdf Date accessed 8 June 2009. Macie E A Hermansen L A 2002 Human In uences on Forest Ecosystems The. between structural safety nets identi ed by Collins 2008a re ghting Southern Wild land Urban Interface Assessment U S Department of Agriculture. services insurance and community involvement in mitigation programs Forest Service Southern Research Station Asheville GTR SRS 55. Subsequent investigations should explore the utility of community McCaffrey S 2004 Thinking of wild re as a natural hazard Society and Natural. Resources 17 509 516, level variables to SOVUL Also given the overall greater distances Mercer D E Prestemon J P 2005 Comparing production function models for wild re risk.
between hot spot clusters and these two mitigation forms CWPPs and analysis in the wildland urban interface Forest Policy and Economics 7 782 795. Firewise programs we would recommend expanding this inquiry to Mitchell T W 2001 From reconstruction to deconstruction undermining black. landownership political independence and community through partition sales of. include other community based mitigation programming in the South tenancies in common Northwestern University Law Review 95 505 580. and the inclusion of more southern states to determine whether these Monroe M C 2002 Fire In Macie E A Hermansen L A Eds Human In uences on. relationships hold across the larger region We believe the current work Forest Ecosystems The Southern Wild land Urban Interface Assessment GTR SRS. 55 USDA Forest Service Southern Research Station Asheville pp 133 150. provides a novel point of departure for wildland re studies in the South. Morrow B H 1999 Identifying and mapping community vulnerability Disasters 23 1 18. and gives practical information to regional re managers contending National Interagency Fire Center n d Wildland re statistics Available online at http. with both natural and social risk factors www nifc gov re info re stats htm Date accessed 4 May 2009. Ojerio R S 2008 Equity in wild re risk management does socioeconomic status predict. involvement in federal programs to mitigate wild re Unpublished thesis pp 1 72. Ojerio R Lynn K Evans A DeBonis M Gerlitz W 2008 Engaging socially. References vulnerable people in community wild re protection plans Resource Innovations. University of Oregon Forest Guild New Mexico Watershed Research and Training. Allen Smith J E Wimberley R C Morris L V 2000 America s forgotten people and Center California pp 1 24 Available online at http ri uoregon edu documents. places ending the legacy of poverty in the rural south Journal of Agricultural and 20and 20pdfs socvul Guide 9 8 08 web pdf Date accessed 8 June 2009. Applied Economics 32 2 319 329 Oxfam 2009 Exposed Social Vulnerability and Climate Change in the US Southeast. Andreu A Hermansen B ez A 2008 Fire in the South 2 the Southern Wild re Risk Available online at http adapt oxfamamerica org resources Exposed Report pdf. Assessment A Report by the Southern Group of State Foresters InterfaceSouth of Date accessed 8 December 2009. Author s personal copy, 36 C J Gaither et al Forest Policy and Economics 13 2011 24 36. Radeloff V C Hammer R B Stewart S I Fried J S Holcomb S S McKeefry J F 2005 interactions among wild res re related programs and poverty in the western states. The wildland urban interface in the United States Ecological Applications 15 Available online at http www upa pdx edu CWCH Date accessed unknown. 799 805 U S Census Bureau 2000 Summary File 3 Detailed Tables for Alabama Universe Total. Rodrigue C M 1993 Home with a view Chaparral re hazard and the social Population P6 Data Set Census 2000 Summary File 3 SF 3 Sample Data Available. geographies of risk and vulnerability The California Geographer 33 29 42 online at http fact nder census gov Date accessed 7 December 2009. Southern Group of State Foresters 2005 Fire in the South Available online at http U S Census Bureau 2009a County Population Estimates 100 Fastest Growing Counties. www dof virginia gov re resources pub SGSF Fire In The South pdf Date Resident Population Estimates for the 100 Fastest Growing U S Counties with. accessed 5 May 2009 10 000 or More Population in 2009 Available online at http www census gov. Stanturf J A Wade D D Waldrop T A Kennard D K Achtemeier G L 2002 popest counties CO EST2009 08 html Date accessed 13 September 2010. Background paper re in southern forest landscapes In Wear D N Greis J G U S Census Bureau 2009b Small Area Income and Poverty Estimates Available online. Eds Southern Forest Resource Assessment USDA Forest Service Southern at http www census gov did www saipe data statecounty data 2008 html. Research Station Asheville Southern Research Station Asheville pp 607 630 Date accessed 14 July 2010. Sunderlin W D Dewi S Puntodewo A Muller D Angelsen A Epprecht M 2008 Western Governor s Association 2002 A collaborative approach for reducing wildland. Why forests are important for global poverty alleviation a spatial explanation re risks to communities and the environment Conference Report for the Fiscal. Ecology and Society 13 2 24 Year 2001 Interior and Related Agencies Appropriations Act. Taylor D 2000 The rise of the environmental justice paradigm injustice framing and Wimberley R C Morris L V 1997 The Southern Blackbelt A National Perspective. the social construction of environmental discourses The American Behavioral Southern Rural Development Center Starkville. Scientist 43 4 508 580 Wolch J Wilson J Fehrenbach J 2002 Parks and park funding in Los Angeles An. Taylor W Floyd M F Whitt Glover M Brooks J 2007 Environmental justice a equity mapping analysis Sustainable Cities Program GIS Research Laboratory. framework for collaboration between the public health and recreation and parks University of Southern California Retrieved July 7 2008 from http college usc. elds to study disparities and physical activity Journal of Physical Activity Health edu geography ESPE documents publications parks pdf. The Center for Watershed and Community Health 2001 Mark O Hat eld School of. Government Portland State University Wild re and poverty an overview of the.

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