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Habitat condition is a vital ecological attribute in wildlife conservation and management in protected areas, including the Burunge wildlife management areas in Tanzania. Traditional techniques, including satellite remote sensing and ground-based techniques used to assess habitat condition, have limitations in terms of costs and low resolution of satellite platforms. The Normalized Difference Vegetation Index (NDVI) and Green NDVI (GNDVI) have potential for assessing habitat condition, e.g., forage quantity and quality, vegetation cover and degradation, soil erosion and salinization, fire, and pollution of vegetation cover. We, therefore, examined how the recently emerged Unmanned Aerial Vehicle (UAV) platform and the traditional Sentinel-2 differs in indications of habitat condition using NDVI and GNDVI. We assigned 13 survey plots to random locations in the major land cover types: three survey plots in grasslands, shrublands, and woodlands, and two in riverine and mosaics cover types. We used a UAV-mounted, multi-spectral sensor and obtained Sentinel-2 imagery between February and March 2020. We categorized NDVI and GNDVI values into habitat condition classes (very good, good, poor, and very poor). We analyzed data using descriptive statistics and linear regression model in R-software. The results revealed higher sensitivity and ability of UAV to provide the necessary preliminary diagnostic indications of habitat condition. The UAV-based NDVI and GNDVI maps showed more details of all classes of habitat conditions than the Sentinel-2 maps. The linear regressions results showed strong positive correlations between the two platforms (p < 0.001). The differences were attributed primarily to spatial resolution and minor atmospheric effects. We recommend further studies to test other vegetation indices. [ABSTRACT FROM AUTHOR]

Globally, traffic associated with roads that pass through protected areas are the cause of many negative impacts on wildlife, such as wildlife roadkill, which has occurred within the Serengeti ecosystem. A 200 km stretch of gravel road networks that passes through the Serengeti ecosystem was surveyed in 2015 for five consecutive days during each study period during the wet and dry seasons, between March and August 2015, to document the magnitude, patterns and composition of wildlife roadkill. We found a total of 51 wildlife roadkills that consisted of 26 species of wild animals and included 18 bird and 8 mammal species. Bird species (60.8%) were more frequently killed than mammal species (39.2%). Moreover, a higher incidence of wildlife roadkill was recorded in the morning (56.9%) than in the afternoon (43.1%) and more mammals (51.7%) than birds (48.3%) were recorded in the morning. Greater numbers of wildlife roadkill were recorded along road segments with good road conditions (69.4%) that were wider (>8 m) and with higher traffic volumes than along roads with poor conditions (30.6%). Overall, the Cape hare (Lepus capensis) was the most frequently killed species (17.6%) among the mammals, whereas the helmeted guineafowl (Numida meleagris) (13.7%) was most frequently killed among the avifauna. To reduce the number of roadkill incidents, we recommend changing driver speeding behaviours by installing wildlife-warning signage that consists of picture-based signs, because they have been proved to be more effective than word-based signs to reduce speeds and hence, reduce collisions. Additionally, the responsible management authorities should provide education to drivers on safe driving and enforcement of laws and regulations. Further, policy briefings that focus on wildlife roadkill should be made available to assist decision-makers and engineers to improve road design in protected areas. [ABSTRACT FROM AUTHOR]