Predicting suitable habitats of the African cherry (Prunus africana) under climate change in Tanzania

Prunus africana is a fast-growing, evergreen canopy tree with several medicinal, household, and agroforestry uses, as well as ecological value for over 22 countries in sub-Saharan Africa. This species is under immense pressure from human activity, compounding its vulnerability to the effects of climate change. Predicting suitable habitats for P. africana under changing climate is essential for conservation monitoring and planning. This study intends to predict the impact of climate change on the suitable habitats for the vulnerable P. africana in Tanzania. We used maximum entropy modeling to predict future habitat distribution based on the representative concentration pathways scenario 4.5 and 8.5 for the mid-century 2050 and late-century 2070. Species occurrence records and environmental variables were used as a dependent variable and predictor variables respectively. The model performance was excellent with the area under curve (AUC) and true skill statistics (TSS) values of 0.96 and 0.85 respectively. The mean annual temperature (51.7%) and terrain ruggedness. index (31.6%) are the most important variables in predicting the current and future habitat distribution for P. africana. Our results show a decrease in suitable habitats for P. africana under all future representative concentration pathways scenario when compared with current distributions. These results have policy implications for over 22 countries of sub-Saharan Africa that are facing problems associated with the sustainability of this species. Institutional, policy, and conservation management approaches are proposed to support sustainable practices in favor of P. africana

Changing climate patterns risk the spread of Varroa destructor infestation of African honey bees in Tanzania

Background Climate change creates opportune conditions that favour the spread of pests and diseases outside their known active range. Modelling climate change scenarios is oftentimes useful tool to assess the climate analogues to unveil the potential risk of spreading suitability conditions for pests and diseases and hence allows development of appropriate responses to address the impending challenge. In the current study, we modelled the impact of climate change on the distribution of Varroa destructor, a parasitic mite that attacks all life forms of honey bees and remains a significant threat to their survival and productivity of bee products in Tanzania and elsewhere. Methods The data about the presence of V. destructor were collected in eight regions of Tanzania selected in consideration of several factors including potentials for beekeeping activities, elevation (highlands vs. lowlands) and differences in climatic conditions. A total of 19 bioclimatic datasets covering the entire country were used for developing climate scenarios of mid-century 2055 and late-century 2085 for both rcp4.5 and rcp8.5. We thereafter modelled the current and future risk distribution of V. destructor using MaxEnt. Results The results indicated a model performance of AUC = 0.85, with mean diurnal range in temperature (Bio2, 43.9%), mean temperature (Bio1, 20.6%) and mean annual rainfall (Bio12, 11.7%) as the important variables. Future risk projections indicated mixed responses of the potential risk of spreads of V. destructor, exhibiting both decrease and increases in the mid-century 2055 and late-century 2085 on different sites. Overall, there is a general decline of highly suitable areas of V. destructor in mid- and late-century across all scenarios (rcp4.5 and rcp8.5). The moderately suitable areas indicated a mixed response in mid-century with decline (under rcp4.5) and increase (under rcp8.5) and consistent increase in late century. The marginally suitable areas show a decline in mid-century and increase in late-century. Our results suggest that the climate change will continue to significantly affect the distribution and risks spread of V. destructor in Tanzania. The suitability range of V. destructor will shift where highly suitable areas will be diminishing to the advantage of the honey bees’ populations, but increase of moderately suitable sites indicates an expansion to new areas. The late century projections show the increased risks due to surge in the moderate and marginal suitability which means expansion in the areas where V. destructor will operate. Conclusion The current and predicted areas of habitat suitability for V. destructor’s host provides information useful for beekeeping stakeholders in Tanzania to consider the impending risks and allow adequate interventions to address challenges facing honey bees and the beekeeping industry. We recommend further studies on understanding the severity of V. destructor in health and stability of the honey bees in Tanzania. This will provide a better picture on how the country will need to monitor and reduce the risks associated with the increase of V. destructor activities as triggered by climate change. The loss of honey bees’ colonies and its subsequent impact in bees’ products production and pollination effect have both ecological and economic implications that need to have prioritization by the stakeholders in the country to address the challenge of spreading V. destructor

Attributes of 10 corridors mapped between PAs in south-western Tanzania.

Corridors are sorted by decreasing centrality scores to demonstrate their importance in keeping the protected areas network connected.</p

Map of habitat suitability, indicating spatial and temporal distribution of potential habitat for elephant within protected areas network of south-western Tanzania.

The polygon with the blue colour in (a) 2000 indicates area annexed by the RNP in 2006.</p

Analysis of Land Cover Changes in Afromontane Vegetation of Image Forest Reserve, Southern Highlands of Tanzania

An analysis of land cover changes (LCCs) was done in Image Forest Reserve (IFR) from August to October 2019. Free satellite images for 1990, 2004, and 2018 were downloaded from Landsat 5 (TM) and Landsat 8 (OLI) available through the USGS portal. Ground surveys were conducted using systematically set plots of 20 m × 40 m to identify the existing land cover types and human illegal activities. Geographical coordinates for each of these plots were recorded using handheld GPS. We witnessed the changes of land cover types in the three decades. Forest had contracted, while shrubland and grassland and woodland had expanded within IFR. Between 1990 and 2004, woodland, bareland and rocky outcrops, shrubland, and grassland had consistently decreased though at a different rate of change, while forest has increased between the same assessment periods. The period of 2004–2018 has shown a consistent increase at different rates in woodland, bareland and rocky outcrops, shrubland, and grassland at a different rate of change, while forest has decreased between the same assessment periods. Further study is needed, bylaws and laws should be implemented, participatory forest management should be encouraged, beekeeping and ecotourism should be introduced, provision of regular education to the community by the Tanzania Forest Service (TFS) should be encouraged, and awareness creation should be made

Relative contribution of predictor variables for predicting the potential habitat distribution of elephants in south-western Tanzania.

Relative contribution of predictor variables for predicting the potential habitat distribution of elephants in south-western Tanzania.</p

Cross-tabulation error matrix for 2000, 2010 and 2019 land cover classification in south-western Tanzania.

Cross-tabulation error matrix for 2000, 2010 and 2019 land cover classification in south-western Tanzania.</p

Map of the study region, showing the estimated distribution of cropland in (a) 2000, (b) 2010, and (c) 2019.

The polygon with the blue colour in (a) 2000 indicates area annexed by the RNP in 2006.</p

Extent and rate of land cover changes between 2000 and 2019 in south-western Tanzania (Area covered = 187,308 km²).

Extent and rate of land cover changes between 2000 and 2019 in south-western Tanzania (Area covered = 187,308 km2).</p

Map of the study region, showing the cropland distribution within and around the modelled corridors in (a) 2000, (b) 2010, and (c) 2019.

The polygon with the blue colour in (a) 2000 indicates area annexed by the RNP in 2006. (DOCX)</p