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

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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.


Related in: MedlinePlus

Hotspots of high swine animal unit density in Census block groups (A) and watersheds (B).
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ijerph-13-00849-f004: Hotspots of high swine animal unit density in Census block groups (A) and watersheds (B).

Mentions: Significant global spatial autocorrelation exists for swine AU densities in both CBGs and watersheds in Iowa (CBG z-score = 46.8, p < 0.001; watershed z-score = 4.3, p < 0.001). Hotspot analysis shows many CBGs with high densities of swine AUs that are neighbored by other CBGs with high swine AU density (Figure 4A). These are located primarily in the northern portions of the state with a grouping of high swine density CBGs in the southeast. Approximately 11% of the CBGs in Iowa are located in a high swine AU density hotspot. Significant hotspots of high swine AU density are also observed in north-central watersheds (Figure 4B). Because the determination of a hotspot includes the densities in neighboring units, some CBGs and watersheds that themselves contain high swine AU densities but are surrounded by areas with relatively lower AU densities are not significant hotspots. Southeastern Iowa, for instance, has high swine AU densities in some watersheds but not in neighboring watersheds that constitute a hotspot.


Pigs in Space: Determining the Environmental Justice Landscape of Swine Concentrated Animal Feeding Operations (CAFOs) in Iowa
Hotspots of high swine animal unit density in Census block groups (A) and watersheds (B).
© Copyright Policy
Related In: Results  -  Collection

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

ijerph-13-00849-f004: Hotspots of high swine animal unit density in Census block groups (A) and watersheds (B).
Mentions: Significant global spatial autocorrelation exists for swine AU densities in both CBGs and watersheds in Iowa (CBG z-score = 46.8, p < 0.001; watershed z-score = 4.3, p < 0.001). Hotspot analysis shows many CBGs with high densities of swine AUs that are neighbored by other CBGs with high swine AU density (Figure 4A). These are located primarily in the northern portions of the state with a grouping of high swine density CBGs in the southeast. Approximately 11% of the CBGs in Iowa are located in a high swine AU density hotspot. Significant hotspots of high swine AU density are also observed in north-central watersheds (Figure 4B). Because the determination of a hotspot includes the densities in neighboring units, some CBGs and watersheds that themselves contain high swine AU densities but are surrounded by areas with relatively lower AU densities are not significant hotspots. Southeastern Iowa, for instance, has high swine AU densities in some watersheds but not in neighboring watersheds that constitute a hotspot.

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 &ldquo;downstream&rdquo; 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 &ldquo;upstream&rdquo; 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.


Related in: MedlinePlus