Limits...
Pigs in Space: Determining the Environmental Justice Landscape of Swine Concentrated Animal Feeding Operations (CAFOs) in Iowa

View Article: PubMed Central - PubMed

ABSTRACT

Given the primacy of Iowa in pork production for the U.S. and global markets, we sought to understand if the same relationship with traditional environmental justice (EJ) variables such as low income and minority populations observed in other concentrated animal feeding operation (CAFO) studies exists in the relationship with swine CAFO densities in Iowa. We examined the potential for spatial clustering of swine CAFOs in certain parts of the state and used spatial regression techniques to determine the relationships of high swine concentrations to these EJ variables. We found that while swine CAFOs do cluster in certain regions and watersheds of Iowa, these high densities of swine are not associated with traditional EJ populations of low income and minority race/ethnicity. Instead, the potential for environmental injustice in the negative impacts of intensive swine production require a more complex appraisal. The clustering of swine production in watersheds, the presence of antibiotics used in swine production in public waterways, the clustering of manure spills, and other findings suggest that a more literal and figurative “downstream” approach is necessary. We document the presence and location of antibiotics used in animal production in the public waterways of the state. At the same time, we suggest a more “upstream” understanding of the structural, political and economic factors that create an environmentally unjust landscape of swine production in Iowa and the Upper Midwest is also crucial. Finally, we highlight the important role of publicly accessible and high quality data in the analysis of these upstream and downstream EJ questions.

No MeSH data available.


Spatial distribution of EJ covariates percent non-white residence (A); percent residents living in poverty (B); percent no college degree (C); and population density (D) in Iowa CBGs. Urban areas are outlined in red.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC5036682&req=5

ijerph-13-00849-f006: Spatial distribution of EJ covariates percent non-white residence (A); percent residents living in poverty (B); percent no college degree (C); and population density (D) in Iowa CBGs. Urban areas are outlined in red.

Mentions: Descriptive statistics for Census EJ variables and swine AU densities indicate a highly varied human and swine geography in Iowa (Table 1). Swine densities in CBGs vary from zero (in urban areas) to over 2000 swine/square mile in some parts of the state. While the overall mean percentage of non-white and poor populations in Iowa CBGs are low (7.85 and 9.06, respectively, some CBGs in Iowa have no non-white or poor residents, while others have nearly all non-white and poor residents. The range for the percentage of population with less than a college education is similarly wide (9.2–100) and some parts of the state are very densely populated and some CBGs have very low population density. The spatial distributions of these variables are shown in Figure 6. Swine densities in CBGs and HUC-8 watersheds are also highly variable, as has been previously explored in hotspot analysis.


Pigs in Space: Determining the Environmental Justice Landscape of Swine Concentrated Animal Feeding Operations (CAFOs) in Iowa
Spatial distribution of EJ covariates percent non-white residence (A); percent residents living in poverty (B); percent no college degree (C); and population density (D) in Iowa CBGs. Urban areas are outlined in red.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5036682&req=5

ijerph-13-00849-f006: Spatial distribution of EJ covariates percent non-white residence (A); percent residents living in poverty (B); percent no college degree (C); and population density (D) in Iowa CBGs. Urban areas are outlined in red.
Mentions: Descriptive statistics for Census EJ variables and swine AU densities indicate a highly varied human and swine geography in Iowa (Table 1). Swine densities in CBGs vary from zero (in urban areas) to over 2000 swine/square mile in some parts of the state. While the overall mean percentage of non-white and poor populations in Iowa CBGs are low (7.85 and 9.06, respectively, some CBGs in Iowa have no non-white or poor residents, while others have nearly all non-white and poor residents. The range for the percentage of population with less than a college education is similarly wide (9.2–100) and some parts of the state are very densely populated and some CBGs have very low population density. The spatial distributions of these variables are shown in Figure 6. Swine densities in CBGs and HUC-8 watersheds are also highly variable, as has been previously explored in hotspot analysis.

View Article: PubMed Central - PubMed

ABSTRACT

Given the primacy of Iowa in pork production for the U.S. and global markets, we sought to understand if the same relationship with traditional environmental justice (EJ) variables such as low income and minority populations observed in other concentrated animal feeding operation (CAFO) studies exists in the relationship with swine CAFO densities in Iowa. We examined the potential for spatial clustering of swine CAFOs in certain parts of the state and used spatial regression techniques to determine the relationships of high swine concentrations to these EJ variables. We found that while swine CAFOs do cluster in certain regions and watersheds of Iowa, these high densities of swine are not associated with traditional EJ populations of low income and minority race/ethnicity. Instead, the potential for environmental injustice in the negative impacts of intensive swine production require a more complex appraisal. The clustering of swine production in watersheds, the presence of antibiotics used in swine production in public waterways, the clustering of manure spills, and other findings suggest that a more literal and figurative “downstream” approach is necessary. We document the presence and location of antibiotics used in animal production in the public waterways of the state. At the same time, we suggest a more “upstream” understanding of the structural, political and economic factors that create an environmentally unjust landscape of swine production in Iowa and the Upper Midwest is also crucial. Finally, we highlight the important role of publicly accessible and high quality data in the analysis of these upstream and downstream EJ questions.

No MeSH data available.