Variations in urban land surface temperature intensity over four cities in different ecological zones.

This study aims at assessing variations and changes in the intensity of urban land surface temperature (LST) over four major cities in different ecological zone. The study intends to examine the contributions of different land cover types and variation in ecological locations on the intensity of urban LST. Remote Sensing and GIS techniques were used to measure the extent of the LST intensity over different cities and implications of land use/land cover (LULC) changes, using the Landsat TM/ ETM from 1984 to 2012, and Landsat OLI/TIRS from 2015 to 2019. The contributions of different landscape types to urban LST intensity were examined, using contribution index (CI) and Landscape index (LI) methods while the relationship between urban LST, and changes in LULC was examined using zonal statistics. The results revealed that the spatial and temporal changes in the LULC have greatly influenced the LST in the cities, though this varies from identified LULC. Changes in estimated LST vary from 0.12 to 1 °C yearly, while the changes are much intensified in the core section of the cities. The contribution of each landscapes varies, - 0.25 < CI > - 1.17 for sink landscape and 0.24 < CI > 1.05 for source landscape. The results further reveal that as LI ≥ 1, the contribution of source landscape to intensity of LST is lesser than that of sink landscape, but LI ≤ 1 shows that source landscapes contribute more to intensity of LST than sink landscapes. This might be as a result of changes in the vegetation cover between 1984 and 2019 as revealed in LULC change. Loss in the vegetal cover is anthropogenically induced leading to an increase in built-up and impervious surfaces resulted in mean monthly and yearly temperature changes. It is observed that the core and densities areas of cities witnessed higher LST compared with the rural area. The study concludes that different types of land cover within an urban area can affect the spatial pattern of urban LST, though this varies from one ecological zone to another and distribution of LST intensity in the urban area depends on its changes LULC. Thus, as cities' population is expected to keep expanding there is a need to establish more viable linkages between the ever-growing population and land use patterns. The major findings from this study are useful in informing policymakers of the need to promote more sustainable urban development in the cities.

Potential distribution of dominant malaria vector species in tropical region under climate change scenarios.

Risk assessment regarding the distribution of malaria vectors and environmental variables underpinning their distribution under changing climates is crucial towards malaria control and eradication. On this basis, we used Maximum Entropy (MaxEnt) Model to estimate the potential future distribution of major transmitters of malaria in Nigeria-Anopheles gambiae sensu lato and its siblings: Anopheles gambiae sensu stricto, and Anopheles arabiensis under low and high emissions scenarios. In the model, we used mosquito occurrence data sampled from 1900 to 2010 alongside land use and terrain variables, and bioclimatic variables for baseline climate 1960-1990 and future climates of 2050s (2041-2060) and 2070s (2061-2080) that follow RCP2.6 and RCP8.5 scenarios. The Anopheles gambiae species are projected to experience large shift in potential range and population with increased distribution density, higher under high emissions scenario (RCP8.5) and 2070s than low emission scenario (RCP2.6) and 2050s. Anopheles gambiae sensu stricto and Anopheles arabiensis are projected to have highest invasion with 47-70% and 10-14% percentage increase, respectively in Sahel and Sudan savannas within northern states in 2041-2080 under RCP8.5. Highest prevalence is predicted for Humid forest and Derived savanna in southern and North Central states in 2041-2080; 91-96% and 97-99% for Anopheles gambiae sensu stricto, and 67-71% and 72-75% for Anopheles arabiensis under RCP2.6 and RCP8.5, respectively. The higher magnitude of change in species prevalence predicted for the later part of the 21st century under high emission scenario, driven mainly by increasing and fluctuating temperature, alongside longer seasonal tropical rainfall accompanied by drier phases and inherent influence of rapid land use change, may lead to more significant increase in malaria burden when compared with other periods and scenarios during the century; especially in Humid forest, Derived savanna, Sahel and Sudan savannas.

Dominant malaria vector species in Nigeria: Modelling potential distribution of Anopheles gambiae sensu lato and its siblings with MaxEnt.

Malaria is a major infectious disease that still affects nearly half of the world's population. Information on spatial distribution of malaria vector species is needed to improve malaria control efforts. In this study we used Maximum Entropy Model (MaxEnt) to estimate the potential distribution of Anopheles gambiae sensu lato and its siblings: Anopheles gambiae sensu stricto, and Anopheles arabiensis in Nigeria. Species occurrence data collected during the period 1900-2010 was used together with 19 bioclimatic, landuse and terrain variables. Results show that these species are currently widespread across all ecological zones. Temperature fluctuation from mean diurnal temperature range, extreme temperature and precipitation conditions, high humidity in dry season from precipitation during warm months, and land use and land cover dynamics have the greatest influence on the current seasonal distribution of the Anopheles species. MaxEnt performed statistically significantly better than random with AUC approximately 0.7 for estimation of the Anopheles species environmental suitability, distribution and variable importance. This model result can contribute to surveillance efforts and control strategies for malaria eradication.