Habitat Suitability Modeling of Endangered Primates in Nigeria: Integrating Satellite Remote Sensing and Spatial Modeling Techniques

This paper investigates the impacts of forest cover and spatial structure changes on the forest landscape across Afi-Mbe-Okwangwo protected area of Cross River State, Nigeria and its corresponding implication on two endangered primates (Cross River Gorilla and Nigeria-Cameroon Chimpanzee) habitat using satellite remote sensing and modeling techniques. Using remote sensing change detection analysis, the spatial extent and annual rate of deforestation for the study area was determined as 34,620 hectares and 1.5% respectively (from 2000 to 2014). The protected areas with highest annual deforestation rates were Afi Mountain Wildlife Sanctuary (2.6%) and Mbe Mountains (2.2%), both prominent for gorilla and chimpanzee sightings and nests. Further investigations on changes to the forest landscape structure revealed high levels of forest fragmentation across the study area for the 14-year period investigated. As a means of further understanding effects of forest landscapes changes across the study area, a 14-year forward simulation was performed using the Markov model as to determine the spatial extent of futuristic forest cover changes. The results showed that if this current trend of forest cover change continued, 28,121 hectares of forests would be lost to deforestation in 2028 (approximately 16% of the total landmass of the entire study area). Using Maxent modeling, suitable primate habitats were predicted and the total coverage determined as 30,940 hectares (54.4% situated in CRNP—Okwangwo division, 29.4% in AMWS, 14.3% in Mbe Mountains and 1.9% in ARFR). Further analysis revealed 6468 hectares of predicted primate habitat were affected by deforestation in 2014 (21% of the predicted primate habitats). These results indicate that suitable primate habitats (particularly for gorillas and chimpanzees) are under immense pressure from deforestation and forest fragmentation. This paper presents a cost effective and time saving approach for determining suitable primate habitats and understanding the effects of forest transition on primate habitat suitability.

Dynamics of Forest Landscape Transition across Protected Areas in the Niger Delta from 1986 to 2014

The overall aim of this study was to conduct a spatially explicit study of forest cover changes across 13 selected protected areas (PAs) across the study area using a combination of satellite remote sensing and ground data. The objectives of the study included: determine the spatial extent of forest landscape for selected PAs using three epochs of satellite imagery (1986, 2000 and 2014);determine the spatial extent and rates of forest transition over two 14-year periods (1986 to 2000 and 2000 to 2014);and provide a comprehensive summary of current forest landscape status in the study area. The results indicated that the spatial extent of forest landscape for the 13 FRs was 522,164, 481,870 and 457,651 hectares in 1986, 2000 and 2014 respectively. The forest cover transition for the two 14-year periods investigation showed a larger percentage of forest landscape across the 13 FRs were more affected by deforestation in comparison to afforestation. The overall annual deforestation rates for the PAs were 0.82% and 0.68% for 1986 to 2000 and 2000 to 2014 time periods. The annual afforestation rates for both 14-year periods were 0.38% and 0.39% respectively. Based on the results being obtained there was an urgent need to review the ways forest reserves and national parks in Cross River state were managed. The promotion of forest conservation was vital to the preservation of existing forest landscapes and endangered wildlife, such as the Cross River Gorilla gorilla and Nigeria-Cameroon chimpanzees. The role of community participation with the assistance of government and conservation organizations would prove effective in forest monitoring activities across the state. In conclusion, results of this study showed the potential of incorporating satellite remote sensing and ground truth data for better understanding the spatial dynamics of forest cover in PAs across the Niger Delta region.