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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.


Parallel coordinate plot showing the relationship between Census block group observations of swine AU density and traditional EJ variables, as well as population density. Each line is a CBG. Red and orange lines highlight the characteristics of CBGs with the highest standard deviations of swine densities.
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ijerph-13-00849-f007: Parallel coordinate plot showing the relationship between Census block group observations of swine AU density and traditional EJ variables, as well as population density. Each line is a CBG. Red and orange lines highlight the characteristics of CBGs with the highest standard deviations of swine densities.

Mentions: Parallel coordinate plotting was used to visualize the relationship between the raw data on swine AU densities in CBGs and the traditional EJ variables (non-white populations, poverty and low education) and population density in those CBGs in Iowa (Figure 7). Parallel coordinate plots are useful for visualizing patterns in data across multiple variables, in this case simultaneously visualizing for every CBG in Iowa the value of swine AU densities in an individual CBG (each line is a CBG) versus the EJ variable values for that CBG. The overall pattern in the chart suggests that those Iowa CBGs within the highest two standard deviations of the distribution of swine AU density are also CBGs where low percentages of people living in poverty or who are not white reside but where the population has a high percentage of residents with less than a college education. At the same time, the highest standard deviations of swine density are observed in CBGs with low population density.


Pigs in Space: Determining the Environmental Justice Landscape of Swine Concentrated Animal Feeding Operations (CAFOs) in Iowa
Parallel coordinate plot showing the relationship between Census block group observations of swine AU density and traditional EJ variables, as well as population density. Each line is a CBG. Red and orange lines highlight the characteristics of CBGs with the highest standard deviations of swine densities.
© Copyright Policy
Related In: Results  -  Collection

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

ijerph-13-00849-f007: Parallel coordinate plot showing the relationship between Census block group observations of swine AU density and traditional EJ variables, as well as population density. Each line is a CBG. Red and orange lines highlight the characteristics of CBGs with the highest standard deviations of swine densities.
Mentions: Parallel coordinate plotting was used to visualize the relationship between the raw data on swine AU densities in CBGs and the traditional EJ variables (non-white populations, poverty and low education) and population density in those CBGs in Iowa (Figure 7). Parallel coordinate plots are useful for visualizing patterns in data across multiple variables, in this case simultaneously visualizing for every CBG in Iowa the value of swine AU densities in an individual CBG (each line is a CBG) versus the EJ variable values for that CBG. The overall pattern in the chart suggests that those Iowa CBGs within the highest two standard deviations of the distribution of swine AU density are also CBGs where low percentages of people living in poverty or who are not white reside but where the population has a high percentage of residents with less than a college education. At the same time, the highest standard deviations of swine density are observed in CBGs with low population density.

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.