Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.
Loading in …3
×
1 of 27

Wildlife crime in Uganda: who, how many and why?

1

Share

Download to read offline

This is a presentation by Dr Henry Travers from Oxford University, a project partner of the International Institute for Environment and Development (IIED).

It presents the research findings of who undertakes wildlife crime in Uganda, why they do so and how much wildlife crime is undertaken. This research was undertaken as part of the three-year project ‘Building capacity for pro-poor responses to wildlife crime in Uganda’.

Travers gave this presentation during the project’s research workshop, which was held in Kampala, Uganda, on 25 May 2016.

More information: http://www.iied.org/building-capacity-for-pro-poor-responses-wildlife-crime-uganda

More Related Content

You Might Also Like

Related Books

Free with a 30 day trial from Scribd

See all

Related Audiobooks

Free with a 30 day trial from Scribd

See all

Wildlife crime in Uganda: who, how many and why?

  1. 1. Wildlife crime in Uganda: who, how many and why?
  2. 2. Evidence review Evidence review Investigation of drivers Investigation of drivers Intervention evaluation Intervention evaluation Recommendations for UWA Recommendations for UWA
  3. 3. “any harm to (or intent to harm or subsequent trade of) non-domesticated wild animals, plants and fungi, in contravention of national and international laws and conventions” “any harm to (or intent to harm or subsequent trade of) non-domesticated wild animals, plants and fungi, in contravention of national and international laws and conventions”
  4. 4. Murchison Falls Protected Area (incl. Bugungu and Karuma WRs) • 5,056 km2 • approx. 23,000 households living within 3km of PA boundary in 2002 Queen Elizabeth Protected Area (incl. Kigezi and Kyambura WRs) • 2,475 km2 • approx. 44,000 households living within 3km of PA boundary in 2002 Murchison Falls Protected Area (incl. Bugungu and Karuma WRs) • 5,056 km2 • approx. 23,000 households living within 3km of PA boundary in 2002 Queen Elizabeth Protected Area (incl. Kigezi and Kyambura WRs) • 2,475 km2 • approx. 44,000 households living within 3km of PA boundary in 2002
  5. 5. 0 500 1000 1500 2000 2500 3000 3500 4000 2004200520062007200820092010201120122013 Snares(total) 0 50 100 150 200 250 300 350 400 450 2004200520062007200820092010201120122013 Arrests(total) 0 50 100 150 200 250 300 350 400 450 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Arrests(total) 0 500 1000 1500 2000 2500 3000 3500 4000 2004200520062007200820092010201120122013 Snares(total) MFMF QEQE
  6. 6. We conducted a large scale household survey • 1955 respondents • 125 villages selected from within 3km of PA boundaries • villages sampled proportionally to length of boundary within each district Key informant interviews were conducted with UWA staff, current or former offenders, bushmeat sellers and village leaders We conducted a large scale household survey • 1955 respondents • 125 villages selected from within 3km of PA boundaries • villages sampled proportionally to length of boundary within each district Key informant interviews were conducted with UWA staff, current or former offenders, bushmeat sellers and village leaders
  7. 7. We considered five activities within PA boundaries: • fishing • grazing livestock • collecting firewood • hunting for consumption • hunting for selling We considered five activities within PA boundaries: • fishing • grazing livestock • collecting firewood • hunting for consumption • hunting for selling
  8. 8. We used a combination of direct and indirect approaches • unmatched count technique • key informant interviews We used a combination of direct and indirect approaches • unmatched count technique • key informant interviews
  9. 9. firewood subsistence hunting fish commercial hunting grazing
  10. 10. We used two types of poverty measure: • basic necessity survey • Uganda multidimensional poverty index (UMPI) Both scores include access to key services in addition to indicators of asset wealth More reliable estimate of poverty status when household income comes from illegal activities We used two types of poverty measure: • basic necessity survey • Uganda multidimensional poverty index (UMPI) Both scores include access to key services in addition to indicators of asset wealth More reliable estimate of poverty status when household income comes from illegal activities
  11. 11. 53% : 47% 53% : 47%
  12. 12. The probability of a household hunting (for subsistence or commercial purposes) increases: • if they are better off • they report suffering from livestock predation • they do not feel they have benefited from revenue sharing No effect for households reporting losses from crop raiding The probability of a household hunting (for subsistence or commercial purposes) increases: • if they are better off • they report suffering from livestock predation • they do not feel they have benefited from revenue sharing No effect for households reporting losses from crop raiding
  13. 13. subsistence hunterssubsistence hunters occasional huntersoccasional hunters professional huntersprofessional hunters senior hunterssenior hunters middlemenmiddlemen bushmeat tradersbushmeat traders restaurants and consumersrestaurants and consumers
  14. 14. On average hunters reported earning: • 100,000 sh per successful trip (50% success rate) • 450,000 sh per month during peak hunting season The average reported daily wage was 20-30,000 sh On average hunters reported earning: • 100,000 sh per successful trip (50% success rate) • 450,000 sh per month during peak hunting season The average reported daily wage was 20-30,000 sh “if you worked for that money, you couldn’t get it easily” “if you worked for that money, you couldn’t get it easily” “I cannot stop hunting without another way of earning money” “I cannot stop hunting without another way of earning money”
  15. 15. Little deterrence effect found from law enforcement • Average encounter rate with rangers found to be 5% • Arrest rate only 0.14% • Average sentence 3 months and 400,000 sh fine Little deterrence effect found from law enforcement • Average encounter rate with rangers found to be 5% • Arrest rate only 0.14% • Average sentence 3 months and 400,000 sh fine “I am not afraid – I am too fast for the rangers to catch me” “I am not afraid – I am too fast for the rangers to catch me” “you go with fear but you have to be alert” “you go with fear but you have to be alert” “even though there is fear, problems will force you to do what you are not supposed to do” “even though there is fear, problems will force you to do what you are not supposed to do”
  16. 16. Subsistence: • 35% of households hunt for meat for home consumption BUT this is often a byproduct of hunting for money • Poorer households less likely to hunt but more likely to be affected by law enforcement Subsistence: • 35% of households hunt for meat for home consumption BUT this is often a byproduct of hunting for money • Poorer households less likely to hunt but more likely to be affected by law enforcement
  17. 17. Commercial: • 42% of households hunt to sell • Better off households are more likely to hunt • Some households have significant income from hunting (> million sh) • Senior and professional hunters hunt to order • Species of international concern (e.g. elephant and pangolin) caught as ‘bycatch’ Commercial: • 42% of households hunt to sell • Better off households are more likely to hunt • Some households have significant income from hunting (> million sh) • Senior and professional hunters hunt to order • Species of international concern (e.g. elephant and pangolin) caught as ‘bycatch’
  18. 18. Perceived injustice: • Households who suffer from livestock predation more likely to hunt • Households that feel they haven’t benefited from revenue sharing more likely to hunt • Revenge for crop raiding cited as a common reason people hunt Perceived injustice: • Households who suffer from livestock predation more likely to hunt • Households that feel they haven’t benefited from revenue sharing more likely to hunt • Revenge for crop raiding cited as a common reason people hunt
  19. 19. Traditional cultural practices • Many wildlife products used in traditional rituals and medicine • Sharp increase in hunting around religious festivals • Limited evidence that cultural heritage drives hunting Traditional cultural practices • Many wildlife products used in traditional rituals and medicine • Sharp increase in hunting around religious festivals • Limited evidence that cultural heritage drives hunting
  20. 20. Enforcement: • Limited effectiveness in deterring hunting • Significant success in control of firearms • More likely to impact poorer households • Collusion an issue for professional and senior hunters Enforcement: • Limited effectiveness in deterring hunting • Significant success in control of firearms • More likely to impact poorer households • Collusion an issue for professional and senior hunters Community conservation: • Perceptions of parks largely unfavourable • Key informants feel let down by failure to deliver on promises • Anger at perceived lack of response to crop raiding and livestock predation Community conservation: • Perceptions of parks largely unfavourable • Key informants feel let down by failure to deliver on promises • Anger at perceived lack of response to crop raiding and livestock predation But there are solutions!But there are solutions!
  21. 21. Thank you for listeningThank you for listening
  22. 22. 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 Elephant Buffalo Uganda kob Waterbuck Warthog
  23. 23. 0 5000 10000 15000 20000 25000 30000 35000 40000 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 Elephant Buffalo Uganda kob Waterbuck Warthog

×