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Modeling the Spatial Distribution and the Risk of Hunting Pressure of Three Co-occurring African Pangolins in Ghana

Atta-Kusi, Eric (2013) Modeling the Spatial Distribution and the Risk of Hunting Pressure of Three Co-occurring African Pangolins in Ghana.

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Abstract:Knowledge on spatial distribution of species and hunting pressure is vital to conservation planning and management of threatened wildlife species. Species distribution models can be applied to map potentially suitable and priority areas, making them essential tools in conservation studies. These models are also used as a guide to the selection of areas for systematic ecological studies and wildlife management purposes. Not much is known about the current distribution pattern and hunting pressure on pangolin in Ghana and West Africa as a whole. To understand this, the study employed the MaxEnt model to map the probable distribution of three threatened African pangolins in Ghana. The study as well mapped the distribution of risk of hunting pressure using six important anthropogenic factors known to influence game hunting in West Africa. The MaxEnt model was run using presence only data of the three known pangolin species in Ghana. Eleven environmental variables suspected to influence pangolin distribution were used for the MaxEnt modelling of the three species at 1 by 1km resolution. The three models were evaluated using the area under the ROC curve (AUC) whilst the jackknife test was used in determining the importance of the variables used in the models. At probability threshold of 0.6 for distribution maps of all three species, model for the Giant pangolin (Manis gigantea) yielded the widest potential distribution with extent of 22,060km² (representing 9% of the study area) followed by the Tree pangolin (Phataginus tricuspis) 18,500 km² (7.5%). The Long-tailed pangolin (Manis tetradactyle) had the least distribution with total extent of 5,200 km² (2.1 %). South western part of Ghana dominated by semi-deciduous and high rain forest showed high probability of occurrence for all 3 pangolin species than other parts of the study area. The three models performed better than random with mean AUC (> 0.8). The most important predictor variable for both Long-tailed pangolin and Tree pangolin is dry-season NDVI. Maximum Temperature was the most important variable for predicting the distribution of the Giant pangolin (Manis gigantea). Aspect and mean annual temperature were of least importance to predicting distribution of Manis tetradactyle and Manis gigantea. To evaluate the level of threat on pangolins in Ghana with regards to hunting, risk of hunting pressure map was modelled using selected anthropogenic factors such as ; road density, distance to bushmeat markets, human population density, distance to game reserves, distance towns and ecological factors like cover type and species preference. The resultant risk map revealed that all three pangolin species in Ghana are potentially prone to high risk of hunting pressure. However, areas in and around game reserves showed low to moderate hunting pressure mainly due to lack of road accessibility and low human population density. Even though there are challenges to the applicability of species distribution models, comparing potential and known distributions can enhance the reliability of model outputs as well as offer resource managers with much confidence in strategizing for conservation programs. Lastly, the move towards identifying areas of potential risk of hunting pressures can be applied to effective planning of anti-poaching operations and evaluation of law enforcement programs to realize optimum results.
Item Type:Essay (Master)
Faculty:ITC: Faculty of Geo-information Science and Earth Observation
Programme:Geoinformation Science and Earth Observation MSc (75014)
Link to this item:https://purl.utwente.nl/essays/93986
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