Comparative Analysis of the Bureau of Land Managements Wild Horse/Burro and Grazing Programs

There is a large amount of controversy online and in the media about the plight of wild horse on Federal lands and their care as prescribed to the Bureau of Land Management under the 1971 Wild Horse and Burro Protection Act.

The Program sets forth the requirement that wild horses and burros on BLM land are protected insofar as their presence does not cause undue environmental damage. The data analyzed in this project utilizes information about the Acceptable Management Level (AML) statistic from the BLM itself and is compared to datasets related to Grazing by private citiens on Grazing Allotment Areas which are leased to livestock owners and have a requirement of management by the lease holders.

I was unable to find the standard by which the High and Low AML fiqgures were arrived at in any capacity or particularly to the specfic Horse Management Areas (HMA) referenced. Nor was I able to find specific data as to the particular or general standards for Acceptable Management Levels (AML) for grazing allotments or even estimates of livestock populations allowed or actual on those allotments.

Boxplot of Square Mileage: Grazing Program

blm_graze_df %>%
  filter(!admin_st == "" & !admin_st == " ") %>%
  ggplot(aes(gis_miles, fill = admin_st)) +
  geom_boxplot() +
  theme_bw()

Boxplot of Square Mileage: HMA Program

blm_hb_df %>%
  ggplot(aes(total_miles, fill = admin_st)) +
  geom_boxplot() +
  theme_bw()

Boxplot of HMA Horse Populations by state

blm_hb_df %>%
  ggplot(aes(est_horse_pop, fill =  admin_st)) +
  geom_boxplot() +
  labs(title = "Total estimated Horse Distribution Summary by State",
       x = "Estimated Horse Population",
       y  = "State") +
  theme_bw()

Total # of HMAs per state

hb_df  <- blm_hb_df %>%
  group_by(admin_st) %>%
  summarise(Num_HMAs = n(),
            all_hb_miles = sum(total_miles))


  
hb_df %>%
  filter(!admin_st == "" & !admin_st == " ") %>%
  ggplot(aes(admin_st, Num_HMAs, fill = admin_st)) +
  geom_col() +
  theme_bw() +
  labs(title = "Number of HMAs per State", x = "State", y = " # of HMAs")

Total Horse Population by State

blm_hb_df %>%
  group_by(admin_st) %>%
  summarise(total_pop = sum(est_horse_pop)) %>%
  ggplot(aes(admin_st, total_pop, fill = admin_st)) +
  geom_col() +
  labs(title = "Total Horses per by State", x = "State", y = "Total Estimated Horse Population")

Mean Horse Population per Square Mile by State

blm_hb_df %>%
  group_by(admin_st) %>%
  summarise(mean_pop_mile = mean(est_horse_pop/total_miles)) %>%
  ggplot(aes(admin_st, mean_pop_mile, fill = admin_st)) +
  geom_col() +
  labs(title = "Mean Horses per Square Mile by State", x = "State", y = "Mean Horse Population")