Threat of land-cover change in Cameroon 885


different land-cover type. At the category level, the largest patch index (LPI) is computed as:


LPI = maxn


j=1(aij) A


where aij is the area of patch ij, subscript i indicates the score for an individual patch within a particular group j, A is the area of the landscape and n is time. Thirdly, wemanually digitized line and polygon features


that corresponded to major roads, access roads, logging roads, logging tracks, cleared land and oil palm plantations between 2009 and 2017, using the historical view of the Google Earth image interface (Supplementary Fig. 1). Land-cover maps and relevant land-use layers were inte- grated. This approach is similar to the concept of data fusion, used to combine multi-source data (Pohl & Van Genderen, 1998).


Results Discussion


Land-use and land-cover mapping and accuracy analysis We identified significant land-cover changes between 1975 and 2017 in the Littoral Region (Fig. 2). The confidence of our error-adjusted estimate fell within 95%, although it was slightly different from that of the mapped areas using the crude land-cover classification maps of 1975 and 2017 (Table 1, Supplementary Table 1). The accuracy of our land- cover maps based on the error-adjusted matrix was 90% for the 1975 data and 96% for the 2017 data, the producer’s accuracy was 89–100%and theuser’saccuracywas 71–100% (Supplementary Table 2).


Spatio-temporal change in fragmentation and landscape


There was a significant (57%) increase in the fragmentation of natural forest in the study area (Supplementary Fig. 2a). The largest patch index value for natural forest decreased in mean forest patch size, from.74%in 1975 to c. 62%in 2017. The values for disturbed vegetation increased from 7.2%in 1975 to 39.3%in 2017. Similarly, the largest patch index value for cleared land increased from 0.5%in 1975 to 5.6%in 2017, and for urban area from 1.28%in 1975 to 7.85%in 2017 (Supplementary Fig. 2b). Wefound considerable net change in the gains or losses of the individual land-use/land-cover change types (Fig. 3) between 1975 and 2017, as determined by our spatio-temporal change detection analysis. Therewas a significant loss of c. 420,000 ha of high-value natural forest cover in the study area from 1975 to 2017, and an increase of c. 400,000 ha of disturbed vegetation (Fig. 3). Similarly, urban areas, cleared land, and water all increased in area, by 78,631, 26,809 and 3,880 ha, respectively (Fig. 3).


Drivers of land-cover change The unregulated expansion of human land use and land- cover change in the Littoral Region of Central Africa poses irreversible threats to biodiversity and natural forest ecosystems. Our results show that land-cover change since 1975 has substantially modified the forest landscapes of the Littoral Region, including one of the remaining intact forest landscapes, north of Sanga River (Figs 2, 4&Supplementary Fig. 4). We found significant and expanding land-cover change within 10 km of the periphery of Ebo Forest and Mount Nlonako, two important conservation areas in the region (Fig. 4). Our findings are supported by earlier studies (Fa et al., 2006; Potapov et al., 2017), which used coarser da- tasets but also reported significant tree cover loss, deforesta- tion and biodiversity degradation in the region. Using the fine-scale data in this study, deforestation was found to be driven by multiple human land uses, namely oil palm plan- tation, logging and land clearing, all of which were facili- tated by expansion of the road network that enabled access to the forest. These findings are similar to elsewhere in the tropics where anthropogenic deforestation has been identified as an initial driver of forest degradation leading to progressive land-use changes and ultimately widespread land-cover conversion (Marsik et al., 2011; Renó et al., 2011). The expansion of oil palm plantations appears to be the


major factor driving deforestation in the studied landscapes of the southern Littoral Region. There is evidence that, in general, logging preceded deforestation and is amajor facili- tator of deforestation (Fig. 4, Supplementary Fig. 5) and the initial step in forest degradation. Logging clears the way for the land to be used for oil palm plantations or cleared


Oryx, 2020, 54(6), 882–891 © 2019 Fauna & Flora International doi:10.1017/S0030605318000881


Drivers of anthropogenic environmental change at the landscape level


We identified four major factors driving land-cover change in the Littoral Region: the expansion of paved and unpaved major and access roads and rail infrastructure, which facili- tated access to remote forest areas; logging; land clearing; and agricultural expansion, especially for palm oil produc- tion (Fig. 4). According to our interpretation and digiti- zation of fine-scale land-use maps, the area of oil palm plantation in the study area is .26,892 ha and the area of cleared land is at least 34,838 ha (Fig. 4, Supplementary Fig. 3a). The identified unpaved access roads were .3,012 km in length, logging roads and deforestation tracks spanned .443 km, and the total length of paved major roads was c. 205 km (Supplementary Fig. 3b). Panels A and B of Fig. 4 are enlarged in Supplementary Fig. 4, showing recently logged area, logging roads, cleared land, and oil palm plantations.


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60  |  Page 61  |  Page 62  |  Page 63  |  Page 64  |  Page 65  |  Page 66  |  Page 67  |  Page 68  |  Page 69  |  Page 70  |  Page 71  |  Page 72  |  Page 73  |  Page 74  |  Page 75  |  Page 76  |  Page 77  |  Page 78  |  Page 79  |  Page 80  |  Page 81  |  Page 82  |  Page 83  |  Page 84  |  Page 85  |  Page 86  |  Page 87  |  Page 88  |  Page 89  |  Page 90  |  Page 91  |  Page 92  |  Page 93  |  Page 94  |  Page 95  |  Page 96  |  Page 97  |  Page 98  |  Page 99  |  Page 100  |  Page 101  |  Page 102  |  Page 103  |  Page 104  |  Page 105  |  Page 106  |  Page 107  |  Page 108  |  Page 109  |  Page 110  |  Page 111  |  Page 112  |  Page 113  |  Page 114  |  Page 115  |  Page 116  |  Page 117  |  Page 118  |  Page 119  |  Page 120  |  Page 121  |  Page 122  |  Page 123  |  Page 124  |  Page 125  |  Page 126  |  Page 127  |  Page 128  |  Page 129  |  Page 130  |  Page 131  |  Page 132  |  Page 133  |  Page 134  |  Page 135  |  Page 136  |  Page 137  |  Page 138  |  Page 139  |  Page 140  |  Page 141  |  Page 142  |  Page 143  |  Page 144  |  Page 145  |  Page 146  |  Page 147  |  Page 148  |  Page 149  |  Page 150  |  Page 151  |  Page 152  |  Page 153  |  Page 154  |  Page 155  |  Page 156  |  Page 157  |  Page 158  |  Page 159  |  Page 160  |  Page 161  |  Page 162  |  Page 163  |  Page 164