Aim Climate change is pressing extra strain on the already degraded forest ecosystem in Tanzania. However, it is mostly unknown how climate change will affect the distribution of forests in the future. We aimed to model the impacts of climate change on natural forests to help inform national‐level conservation and mitigation strategies. Location Tanzania. Methods We conducted maximum entropy (MaxEnt) modelling to simulate forest habitat suitability using the Tanzanian national forest inventory survey (1,307 occurrences) and environmental data. Changes in forest habitats were simulated under two Representative Concentration Pathways (RCPs) emission scenarios RCP 4.5 and RCP 8.5 for 2055 and 2085. Results The results indicate that climate change will threaten forest communities, especially fragmented strips of montane forests. Even under optimistic emission scenario, the extent of montane forest is projected to almost halve by 2085, intersecting many biodiversity hotspots across the Eastern Arc Mountains. Similarly, climate change is predicted to threaten microhabitat forests (i.e. thickets), with losses exceeding 70% by 2085 (RCP8.5). Other forest habitats are predicted to decrease (lowland forest and woodland) representing essential ecological networks, whereas suitable habitats for carbon‐rich mangroves are predicted to expand by more than 40% at both scenarios. Conclusions Climate change will impact forests by accelerating habitat loss, and fragmentation and the remaining land suitable for forests will also be subject to pressures associated with rising demand for food and biofuels. These changes are likely to increase the probability of adverse impacts to the country's indigenous flora and fauna. Our findings, therefore, call for a shift in conservation efforts, focusing on (i) the enhanced management of existing protected areas that can absorb the impacts of future climate change, and (ii) expanding conservation efforts into newly suitable regions through effective land use planning and land reclamation, helping to preserve and enhance forest connectivity between fragmented patches.
Tropical forests provide essential ecosystem services related to human livelihoods. However, the distribution and condition of tropical forests are under significant pressure, causing shrinkage and risking biodiversity loss across the tropics. Tanzania is currently undergoing significant forest cover changes, but monitoring is limited, in part due to a lack of remote sensing knowledge, tools and methods. This study has demonstrated a comprehensive approach to creating a national-scale forest monitoring system using Earth Observation data to inform decision making, policy formulation, and combat biodiversity loss. A systematically wall-to-wall forest baseline was created for 2018 through the application of Landsat 8 imagery. The classification was developed using the extreme gradient boosting (XGBoost) machine-learning algorithm, and achieved an accuracy of 89% and identified 45.76% of the country’s area to be covered with forest. Of those forested areas, 45% was found within nationally protected areas. Utilising an innovative methodology based on a forest habitat suitability analysis, the forest baseline was classified into forest types, with an overall accuracy of 85%. Woodlands (open and closed) were found to make up 79% of Tanzania’s forests. To map changes in forest extent, an automated system for downloading and processing of the Landsat imagery was used along with the XGBoost classifiers trained to define the national forest extent, where Landsat 8 scenes were individually downloaded and processed and the identified changes summarised on an annual basis. Forest loss identified for 2019 was found to be 157,204 hectares, with an overall accuracy of 82%. These forest losses within Tanzania have already triggered ecological problems and alterations in ecosystem types and species loss. Therefore, a forest monitoring system, such as the one presented in this study, will enhance conservation programmes and support efforts to save the last remnants of Tanzania’s pristine forests.
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