Deforestation poses a major threat to the tropical montane forest ecosystems of East Africa. Montane forests provide key and unique ecological and socio-economic benefits to the local communities and host diverse flora and fauna. There is evidence of ongoing deforestation and forest clearance in these montane forests although estimates diverge among different sources suggesting rates of 0.4%–3% yr−1. Quantifying deforestation rates and forest disturbance is critical to design conservation and sustainable management policies for forest management. This study quantified the rate of deforestation and forest recovery over the last three decades for the Mau Forest Complex and Mount Elgon forests in Kenya and Uganda using Landsat time-series satellite imagery. With the analysis, classification accuracies of 86.2% and 90.5% (kappa 0.81 and 0.88) were achieved for the Mau Forest Complex and the Mt Elgon forests, respectively. 21.9% (88,493 ha) of the 404,660 ha of Mau forest was lost at an annual rate of −0.82% yr−1 over the period between 1986 and 2017. More positively, 18.6% (75,438 ha) of the forest cover that was disturbed during the same period and is currently undergoing recovery. In Mt Elgon forest, 12.5% (27,201 ha) of 217,268 ha of the forest cover was lost to deforestation at an annual rate of −1.03% yr−1 for the period between 1984–2017 and 27.2% (59,047 ha) of the forest cover disturbed is undergoing recovery. The analysis further demonstrated agriculture (both smallholder and commercial) was the main driver of forest cover loss in Mau forest, accounting for 81.5% (70,612 ha) of the deforestation, of which 13.2% was due to large scale and 68.3% was related to the smallholders. For the Mt Elgon forest, agriculture was also the main driver accounting for 63.2% (24,077 ha) of deforestation followed by the expansion of human settlements that contributed to 14.7% (5,597 ha) of forest loss. This study provides accurate and novel estimates of the rate of deforestation for the Mau forest complex and Mt Elgon forest ecosystems. These rates are higher than previously estimated and recent deforestation has been identified, which provides a quantitative basis for forest restoration programs and to design conservation policies.
DOI:
https://doi.org/10.3389/fenvs.2023.1084764Skor altmetrik:
Jumlah Kutipan Dimensi:
Tahun publikasi
2023
Penulis
Ojoatre, S.; Zhang, C.; Yesuf, G.; Rufino, M.C.
Bahasa
English
Kata kunci
deforestation, tropical forests, land use change, forest rehabilitation
Geografis
Kenya, Uganda
