Wildlife Crime and Prosecution Effectiveness in the State of Uttarakhand
DOI:
https://doi.org/10.36808/if/2025/v151i7/170837Keywords:
Wildlife Crime, Illegal wildlife trades, Poaching, Wildlife (Protection) Act, UttarakhandAbstract
The authors present the analysis of wildlife offense records for the state of Uttarakhand with especial reference to the frequent victim species and prosecution success. Based on data collected from different forest divisions and police departments they observed variable duration of investigations. Of the 563 wildlife offence cases, 471 were reported by forest department and 92 by Police department of Uttarakhand. Among 333(54%) cases were of Schedule-I, 12(2%) were of Schedule-II, 161 (26%) were of Schedules-III and 11(2%) were of Schedule-IV species under the Wild Life (Protection) Act, 1972. It was also observed that 66 (11%) wildlife samples were inconclusive, 14(2%) unscheduled and 8(1%) were found to be fake and remaining 8(1%) cases are still pending with wildlife forensics lab, WII, Dehradun in Uttarakhand, conviction rate in respect of arrested offenders was 50%. In Rajaji Tiger Reserve, only 10 offenders were convicted out of 80 got arrested. In cases of police department only 4 offenders got convicted out of 86 being arrested in wildlife seizure cases. The Kumaon zone has demonstrated a stronger performance in wildlife prosecution, where 66 out of 79 cases have resulted in convictions. The wildlife zone demonstrated robust conviction record, where 60 out of the 162 registered wildlife cases have been decided by trial courts with favourable outcomes for the prosecution in 52 cases. The presented data will be useful in understanding the gaps in law enforcement and streamlining the follow-up mechanism in the logical conclusion of the associated cases.
References
Gorr W. and Harries R. (2003). Introduction to crime forecasting, 19 : 551–555. DOI: https://doi.org/10.1016/S0169-2070(03)00089-X
Gorr W., Olligschlaeger A. and Thompson Y. (2003). Short-term forecasting of crime, International Journal of Forecasting, 19: 579–594. DOI: https://doi.org/10.1016/S0169-2070(03)00092-X
Groff E.R. and La Vigne N.G. (2002). Forecasting the Future of Predictive Crime Mapping, Crime Prevention Studies, 3: 29–57.
Gupta S.K., Thangaraj K. and Singh L. (2011a). Identification of the source of ivory idol by DNA analysis. Journal of Forensic Science, 56: 1343-1345. DOI: https://doi.org/10.1111/j.1556-4029.2011.01750.x
Gupta S.K., Verma S.K. and Singh L. (2005). Molecular insight into a wildlife crime: the case of a peafowl slaughter. Forensic Science International, 154: 214-217. DOI: https://doi.org/10.1016/j.forsciint.2004.12.010
International Consortium on Combating Wildlife Crime (2012). Wildlife and Forest Crime Analytic Toolkit IInd ed. UNITED NATIONS, New York, 2012
Odgen R., Dawnay N. and McEwing R. (2009). Wildlife DNA Forensics- bridging the gap between conservation Genetics and Law enforcement. Endangered Species Research, 9: 179-195. DOI: https://doi.org/10.3354/esr00144
Vellani K.H. (2010). Crime Analysis: for Problem Solving Security Professionals in 25 Small Steps, Facilities 1– 56.
Verma S.K. and Singh L. (2003). Novel universal primers establish identity of enormous number of animal species for forensic application. Molecular Ecology Notes, 3:28-31. DOI: https://doi.org/10.1046/j.1471-8286.2003.00340.x
Vipin, Sharma V. and Gupta S.K. (2018). Molecular identification of victim species and its sex from the ash: a case of burning alive leopard (Panthera pardus). International Journal of Legal Medicine. 132: 1075-1078. DOI: 10.1007/s00414-017-1619-1 DOI: https://doi.org/10.1007/s00414-017-1619-1
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