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.
The negative impacts of forest loss and hunting activities across the world’s tropical forests are sources of concern, as it affects the continued existence of endangered primates [
The combined use of satellite remote sensing and ground truth data has shown to be an effective method of understanding changes in forest landscapes across the world [
An important component of this study was to perform a forward simulation of forest landscape transition in the study area as a means to create futuristic scenarios based on existing trends of forest cover dynamics. This would provide a direct representation as to the spatial and structural changes of forest landscape in the future, provided the current trend of forest transition continues. With such outputs, it would be particularly useful for wildlife conservation and decision makers involving in the day to day running and management of protected areas across the country. To this end, the Markovian process which had capabilities to model future state of landscapes using the immediate preceding state as a basis for forward prediction [
Having a good understanding of wildlife species distribution and identifying factors that influence habitat selection would greatly assist wildlife conservation and management. Within Afi-Mbe-Okwangwo protected area landscape, delineating the current and potential distribution of endangered species, such as the Cross River Gorillas and Chimpanzees primates are critical to conservation management and planning. Part of this study shall investigate the use of presence-only data and other environmental variables for mapping suitable habitats for endangered primates in the study area. The Maximum Entropy modeling (Maxent), allows for suitable habitat distribution through combined use of presence data and environmental variables [
Taking into consideration the afore-mentioned, this study aimed to investigate impacts of forest cover and spatial structure changes on the forest landscape of Afi-Mbe-Okwangwo protected area in Cross River State, Nigeria particularly its corresponding implication on two endangered primates (Cross River Gorilla and Nigeria-Cameroon Chimpanzee) habitat using satellite remote sensing and modeling techniques. The key objectives of the study were: 1) to examine the changes in forest cover and spatial structure across the study area using satellite remote sensing and ground data; 2) to perform predicted forward simulation of forest cover changes across the study area as a means of projecting possible impacts of deforestation on existing forest landscapes; 3) to model habitat suitability of endangered primates using a combination of species presence data and other key environmental variables; and 4) to estimate the spatial extent and effects of deforestation on predicted primate habitats.
The study area, Afi-Mbe-Okwangwo forest landscape, is composed of four protected areas namely Afi Mountain Wildlife Sanctuary (AMWS), Afi River Forest Reserve (ARFR), Mbe Mountains and Cross River National Park (CRNP) (Okwangwo division) all situated in the northern part of Cross River State (
The AMWS is the westernmost protected area that serves as home to estimated 25 - 30 Cross River Gorilla sightings. The sanctuary created in 2000 was established to protect wildlife in approximately 100 km2 of lowland and hill forests in the north-western corner of the 380 km2 Afi River Forest Reserve (ARFR) [
To the east of the Afi Mountains and adjourning the ARFR is the Mbe Mountains protected area, a forest dominated hilly landscape with sightings of gorillas since 1983 was established a wildlife sanctuary in 2000 [
ties, poaching, bush burning and fragmentation of existing forest landscapes are key issues of concern in the protected area. [
Further to the east of Mbe Mountains, divided by the Okon River is CRNP Okwangwo Division. The CRNP located in south eastern Nigeria consists of two divisions, the Oban division to the south of Cross River state and the Okwangwo division to the north as shown in
The field data on endangered primates (gorillas and chimpanzees) presence across the study area was collected using cyber-tracking technology employed by patrol officers of WCS and CRSFC [
The change in the forest landscape across the study area was performed using satellite remote sensing data for two epochs (2000 and 2014). For this study Landsat 7 Enhanced Thematic Mapper (ETM+) with World Reference System path 187, row 056 (10 December 2010) and UK-DMC satellite data (7 January 2014) were used. The Landsat data was downloaded from the United States Geological Survey GLOVIS web-page (http://glovis.usgs.gov/) while the UK-DMC satellite data was supplied by Nigeria Space Agency, NASRA (National Space Research and Development Agency), based on sharing agreement with UK partners (Disaster Monitoring Constellation Company, DMCii). The Landsat image was processed to Level 1 Terrain-corrected, implying it was already ortho-rectified making it a suitable product for direct image-to-image comparison in change detection analysis. Similarly the UK-DMC satellite image was radiometrically and geometrically corrected. Since the images were already radiometrically and geometrically corrected on delivery, the Landsat and UK-DMC images were atmospherically corrected [
For this study, the supervised maximum likelihood classifier (MLC) was applied to each satellite image. A total of six broad classes were used in the study, based on the Intergovernmental Panel on Climate Change land use classification scheme [
In this study, the IDRISI Selva Land Cover Modeler was used to analyses forest cover change over the study area. Using results of the forest cover maps for 2000 and 2014, forest cover change maps across the protected areas were determined for 2000 to 2014. The forest cover change maps for both time intervals showed deforested, unchanged forest and afforested landscapes classes. In order to calculate, the annual deforestation and forest changes for the two time periods were used.
The open source software, FRASTATS (version 4.3.1.603), [
An important component of this study, with particular emphasis on the management of protected areas and eventual benefits to endangered primate habitats, was predicting the future status forest landscapes across the study area using current trends of forest cover transition. To this end, the Markov Chain Analysis and Cellular Automata Analysis (CA_MARKOV) module in IDRISI Selva was used to model forest cover scenario over a 14-year future projection (i.e. from 2014 to 2028). The Markovian process models the future state of any chosen landscape using the immediate preceding state as the basis for forward prediction [
The Maximum Entropy Distribution (Maxent) [
The modeling of environmental suitability for endangered primates using the presence data of gorilla and chimpanzee sightings and nests and three key environmental variables namely, DEM (for terrain information), Slope map (derived from the DEM) and forest cover map of the study area. The recommended default values for maximum iteration numbers (50), convergence threshold (100,000) and regularization values (10,000) were used. The random test percentage of value used was 30 (meaning that 30% of the presence data was used for validation while 70% for training of the model). For analysis a threshold was specified to help perform binary predictions of habitat suitability conditions with suitable habitats predicted above such threshold and unsuitable indicated as below. In this study a convergence threshold of 0.00001 was used with maximum iterations of 500. The ASCII raster outputs of predicted primate habitats were further analyzed using ESRI ArcGIS software version 10.2 [
The overall land cover classification accuracy results were approximately 89 percent (2000) and 91 percent (2014) respectively.
The classification result shows that total forest cover for the entire study area was 152,509 hectares in 2000 and 129,339 hectares in 2014 (
Land Use | 2000 (ETM+) | 2014 (UK-DMC) | ||
---|---|---|---|---|
UA (%) | PA (%) | UA (%) | PA (%) | |
Forest | 87.1 | 95.7 | 91.8 | 88.2 |
Farmland | 88.6 | 87.8 | 90.9 | 86.2 |
Grassland | 93.6 | 96.7 | 91.7 | 94.3 |
Wetland | 86.4 | 88.4 | 90 | 87.8 |
Settlement | 100 | 54.6 | 93.3 | 96.6 |
Other land | 100 | 100 | 86.7 | 100 |
OA (%) | 89.4 | 90.8 |
cover of forest landscape for the 14-year period investigated (
The forest cover transition results indicated that overall deforestation for the study area from 2000 to 2014 was 34,620 hectares (
Using spatial metrics measures (NP, PD and MPA) over time, the changes in spatial structure over the 14-year period was investigated for the study area The NPs for the entire study area increased from 1255 in 2000 to 2843 in 2014. Similarly, the PD of the entire study area increased from 0.48 in 2000 to 1.12 in 2014 while MPA decreased from 122 hectares (in 2000) to 46 hectares (in 2014) (
Zone | Forest Cover (ha) | Number of Patches | Patch Density (no. per 100 ha.) | Mean Patch Area (ha) | ||||
---|---|---|---|---|---|---|---|---|
2000 | 2014 | 2000 | 2014 | 2000 | 2014 | 2000 | 2014 | |
Project area | 152,509 | 129,339 | 1255 | 2843 | 0.48 | 1.12 | 121.52 | 45.49 |
AMWS | 9715 | 7418 | 76 | 474 | 0.35 | 2.18 | 127.83 | 15.65 |
ARFR | 27,033 | 22,315 | 113 | 338 | 0.13 | 0.39 | 239.23 | 66.02 |
Mbe Mountains | 8944 | 6728 | 2 | 141 | 0.01 | 0.67 | 4475.24 | 47.72 |
CRNP (Okwangwo) | 61,828 | 53,614 | 80 | 496 | 0.06 | 0.37 | 772.85 | 108.09 |
Zone | Deforested (ha) | Unchanged forest (ha) | Afforested (ha) | Deforested (%) | Unchanged forest (%) | Afforested (%) | Annual deforestation rate (%) | Annual rate of change in forest cover (%) |
---|---|---|---|---|---|---|---|---|
Project area | 34,620 | 117,730 | 11,574 | 13.26 | 45.09 | 4.46 | 1.48 | 0.51 |
AMWS | 3229 | 6486 | 933 | 14.84 | 29.80 | 4.29 | 2.61 | 0.84 |
ARFR | 5559 | 21,474 | 830 | 6.43 | 24.85 | 0.96 | 1.48 | 0.59 |
Mbe Mountains | 2311 | 6634 | 94 | 10.92 | 31.35 | 0.45 | 2.19 | 0.88 |
CRNP (Okwangwo) | 9623 | 52,196 | 1388 | 7.17 | 38.89 | 1.03 | 1.06 | 0.44 |
forestation across existing protected areas.
To this end, the Nigerian Government is actively involved in the United Nations REDD+ (Reducing Emissions from Deforestation and Forest Degradation) programme aimed at preserving existing forest landscape across the country, particularly forest dependent communities [
The results of forest cover change analysis for the entire study area based on the 2014 and 2028 predicted forest maps showed that 28,121 hectares of forest cover would be deforested. The spatial extent of unchanged forest and afforested landscape between 2014 and 2028 would be 101,183 and 9988 hectares respectively. These
predicted results are based on the current trend of forest cover change driven by current forest management practices and pressures from human activities (such as farming encroachment, bush burning and illegal logging).
The omission and predicted area plots of the endangered primates (
The AUC and standard deviation for the modeled prediction of gorillas and chimpanzees habitats were 0.921 (standard deviation 0.006) and 0.921 (standard deviation 0.007) respectively. The gorilla suitability habitat modeling was performed using 359 presence records for training and 153 for testing. For the chimpanzee habitat suitability modeling 217 presence records was used for training and 93 for testing. The environmental variables used in the model included the study area DEM, classified forest map and slope map datasets.
During the training phase of species prediction modeling Maxent software keeps track of environmental variables that contribute to fitting the model. Consistent with ecological knowledge the model predicted that Cross River Gorilla and chimpanzees are found mostly in forested areas (particularly tropical high and montane forests) in mountainous locations across the site.
The raster datasets showing predicted primate habitats generated using Maxent model were imported into ArcGIS software for further analysis and visualization. The raster outputs were reclassified to binary images showing only predicted primate habitats with possible probability of occurrence (i.e. 0.4 - 1.0) (
AMWS, ARFR, Mbe Mountains and CRNP (Okwangwo division) were approximately 9094 hectares, 573 hectares, 4428 hectares and 16,846 hectares respectively. These results would prove vital in the effective management and development of conservation plans for endangered primate habitats across the study area required by wildlife conservation organizations and the State government.
Following the modeling of suitable gorilla and chimpanzee habitats, the authors investigated the effects of deforestation trends (2000-2014) on the spatial coverage of predicted primate habitats across the study area. Using spatial analysis techniques in ArcGIS, the forest transition map (
The high levels of forest fragmentation across the four protected areas investigated in this study are largely dependent on the current prevailing agricultural practices across the region. The presence of intensified pressure from agricultural encroachment by surrounding villages and communities are key catalysts to the disturbance of existing gorilla and chimpanzee habitats. Over the years the combined effects of forest fragmentation and deforestation has resulted in extensive restriction of primates to isolated and highly fragmented forest patches. This pattern of forest transition combined with uncontrolled hunting in protected areas such as the CRNP (Okwangwo division) has resulted in rapid loss of endangered primates (particularly gorillas and chimpanzees) and in drastic cases extinction of some wildlife species such as the grey-cheeked mangabey (Lophocebus albigena) and crowned guenon (Cercopithecus pogonias) [
In the Mbe Mountains, a key catalyst asides from the above mentioned factors, is the presence of the Ikom―Obudu highway which traverses across Ago Ogbagante, Kayang-1, Kayang-2, Wula-1 and Wula-2 communities. Results of past studies [
The devastating impact of deforestation and other human related activities on remaining forest landscape and wildlife (in particular endangered primates) justifies the need for Cross River State (CRS) Government (in collaboration with the National Government) to put in place mitigative measures and policies/laws that would protect all wildlife and forests. In this regard, the CRS government on February 2014 established a mobile court under the CRSFC charged with the responsibility of prosecuting any individual found guilty of killing or hunting any animal (or endangered species) as listed in the CRS Forestry Commission Law No. 3 of 2010 [
The study has demonstrated the use of remote sensing data and techniques combined with various modeling approaches to understand effects of forest cover transitions on the spatial structure and prediction of suitable primate habitats. The results show that suitable habitats for gorillas and chimpanzees are under immense pressure from deforestation and high levels of forest fragmentation. Forest change analysis results showed that the overall extent of deforestation across the study area (2000 to 2014) was 34,620 hectares with annual deforestation rate of 1.5%. The protected area with the highest annual deforestation rates were AMWS (2.6%) and Mbe Mountains (2.2%), both prominent for gorilla and chimpanzee sightings and nests. The key drivers of deforestation across the study area were identified as illegal logging, over exploitation of non-timber forest products, hunting, farm encroachment, and forest fires. Further investigations as to changes in forest landscape structure revealed presence of high forest fragmentation levels, factors that had adverse negative effects on endangered primate and other wildlife habitat. As a means of further understanding the effects of the current forest cover transition trends, a forward simulation of forest landscape was performed for a 14-year forward prediction. The results showed that if the current trend of forest cover changes continued, a total of 28,121 hectares of forest cover would be deforested in the 2028 (approximately 16% of the total landmass of the entire study area). Using Maxent, suitable primate habitats were modeled and the total coverage of predicted habitat was estimated to be 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 as to the extent of deforestation in the predicted primates habitat revealed that 6468 hectares of forest cover had been deforested in 2014 (an estimated 21% of the predicted primate habitats). These results show that suitable primate habitats (particularly for gorillas and chimpanzees) are under immense pressure from deforestation and forest fragmentation.
This study has demonstrated that using remote sensing analysis combined with predictive modeling tools (such as Markovian and Maxent models) provides better understanding of forest transition and corresponding effects on primate habitats across parts of Africa. The approach presented in this study is a cost effective and time saving method of accurately predicting endangered primate habitats and understanding the dynamics of forest change and structure in the area. The information derived using this approach would assist conservation organizations, wildlife managers and the Government of Nigeria in making decisions and implementing policies that would help protect the forests and conserve endangered primates and other wildlife that are forest dependent for their existence.
In conclusion, the continued conservation of forests across African countries is paramount, as gorillas and chimpanzees alike depend on forest for survival. Hence, the only way to ensure their survival is to fight for the conservation of remaining forests. Such efforts will require support from government of African nations, Conservation Organizations, World Donor Agencies and most important the assistance of communities where such forests and endangered primates are found. The place of financial independence of forest protected areas can be promoted through ecotourism and infrastructure development [
The authors would like to appreciate Wildlife Conservation Society (Cross River) for providing the relevant field data on endangered primates across the study area and National Space Research and Development Agency (NASRDA) for making available the UK-DMC satellite image of Cross River State for image analysis.
Alex O.Onojeghuo,Alan G.Blackburn,FrancisOkeke,Ajoke R.Onojeghuo, (2015) Habitat Suitability Modeling of Endangered Primates in Nigeria: Integrating Satellite Remote Sensing and Spatial Modeling Techniques. Journal of Geoscience and Environment Protection,03,23-38. doi: 10.4236/gep.2015.38003