@article{10.11648/j.ijepp.20130102.12,
  author = {Shadrack Mumo Ngene and Andrew Skidmore and Hein van Gils and Francis Kamau Muthoni and Wycliffe Mutero and Patrick Omondi},
  title = {Zero Tolerance: Evolving Wildlife Management in Kenya},
  journal = {International Journal of Environmental Protection and Policy},
  volume = {1},
  number = {2},
  pages = {24-31},
  doi = {10.11648/j.ijepp.20130102.12},
  url = {https://doi.org/10.11648/j.ijepp.20130102.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepp.20130102.12},
  abstract = {This study investigates the impact of contrasting wildlife management regimes on the probability of elephant presence in the Tsavo ecosystem base on the New York “zero tolerance policing”. Point data for the location of elephant, elephant carcasses, cattle, buffalo, giraffe, occupied bomas, charcoal kilns, settlements and farms, and water points were collected through aerial survey from 7-12 February 2011. Secondary data layers included main rivers, 30m resolution digital elevation model, and moderate resolution imaging spectro-radiometer (MODIS) 250m spatial resolution normalized difference vegetation index (NDVI) data for January 2011. Information on the three management regimes (none, passive, and active) adopted by protected areas and ranches in Tsavo ecosystem was identified through interviews. The Maxent algorithm was used for modeling the probability of elephant presence in the ecosystem. Multicollinearity of the fourteen explanatory variables was tested using Eigen values and Condition Index (CI). We used Maxent with elephant location points as the presence only data and the twelve explanatory variables as environmental variables. Bootstrapping of ten replications was included in the model. The accuracy of the model was determined using the area under the curve (AUC) of the Receiver Operating Characteristic (ROC) function. The results indicated that elephants were significantly more likely to be found in the protected areas than the non-protected areas. The northern sector of Tsavo West and the Voi sector of Tsavo East were the most likely areas to record elephants. Sectors with protected areas and ranches that practiced active management were more likely to show elephant than those with passive or no management. The areas with high probability of elephant occurrence coincided with actual high elephant density. Elephant carcasses, buffalo, giraffe, and settlements were the main variables that predicted the probability of elephant presence. Elephants are more likely to be in protected areas and ranches that were managed actively than those passively or not managed. In order to capitalize on the notion of protection and active management, we propose a wildlife management model based on the New York ‘zero tolerance’ policing. Any misdemeanor is not tolerated, especially illegal charcoal burning and livestock grazing in the ranches.},
 year = {2013}
}

Copy | Download

TY  - JOUR
T1  - Zero Tolerance: Evolving Wildlife Management in Kenya
AU  - Shadrack Mumo Ngene
AU  - Andrew Skidmore
AU  - Hein van Gils
AU  - Francis Kamau Muthoni
AU  - Wycliffe Mutero
AU  - Patrick Omondi
Y1  - 2013/07/20
PY  - 2013
N1  - https://doi.org/10.11648/j.ijepp.20130102.12
DO  - 10.11648/j.ijepp.20130102.12
T2  - International Journal of Environmental Protection and Policy
JF  - International Journal of Environmental Protection and Policy
JO  - International Journal of Environmental Protection and Policy
SP  - 24
EP  - 31
PB  - Science Publishing Group
SN  - 2330-7536
UR  - https://doi.org/10.11648/j.ijepp.20130102.12
AB  - This study investigates the impact of contrasting wildlife management regimes on the probability of elephant presence in the Tsavo ecosystem base on the New York “zero tolerance policing”. Point data for the location of elephant, elephant carcasses, cattle, buffalo, giraffe, occupied bomas, charcoal kilns, settlements and farms, and water points were collected through aerial survey from 7-12 February 2011. Secondary data layers included main rivers, 30m resolution digital elevation model, and moderate resolution imaging spectro-radiometer (MODIS) 250m spatial resolution normalized difference vegetation index (NDVI) data for January 2011. Information on the three management regimes (none, passive, and active) adopted by protected areas and ranches in Tsavo ecosystem was identified through interviews. The Maxent algorithm was used for modeling the probability of elephant presence in the ecosystem. Multicollinearity of the fourteen explanatory variables was tested using Eigen values and Condition Index (CI). We used Maxent with elephant location points as the presence only data and the twelve explanatory variables as environmental variables. Bootstrapping of ten replications was included in the model. The accuracy of the model was determined using the area under the curve (AUC) of the Receiver Operating Characteristic (ROC) function. The results indicated that elephants were significantly more likely to be found in the protected areas than the non-protected areas. The northern sector of Tsavo West and the Voi sector of Tsavo East were the most likely areas to record elephants. Sectors with protected areas and ranches that practiced active management were more likely to show elephant than those with passive or no management. The areas with high probability of elephant occurrence coincided with actual high elephant density. Elephant carcasses, buffalo, giraffe, and settlements were the main variables that predicted the probability of elephant presence. Elephants are more likely to be in protected areas and ranches that were managed actively than those passively or not managed. In order to capitalize on the notion of protection and active management, we propose a wildlife management model based on the New York ‘zero tolerance’ policing. Any misdemeanor is not tolerated, especially illegal charcoal burning and livestock grazing in the ranches.
VL  - 1
IS  - 2
ER  - 

Copy | Download