Understanding habitat quality and its dynamics is imperative for maintaining healthy wildlife populations and ecosystems. We mapped and evaluated changes in habitat quality (1975–2015) in the Greater Serengeti Ecosystem of northern Tanzania using the Integrated Valuation of Environmental Services and Tradeoffs (InVEST) model. This is the first habitat quality assessment of its kind for this ecosystem. We characterized changes in habitat quality in the ecosystem and in a 30 kilometer buffer area. Four habitat quality classes (poor, low, medium and high) were identified and their coverage quantified. Overall (1975–2015), habitat quality declined over time but at rates that were higher for habitats with lower protection level or lower initial quality. As a result, habitat quality deteriorated the most in the unprotected and human-dominated buffer area surrounding the ecosystem, at intermediate rates in the less heavily protected Wildlife Management Areas, Game Controlled Areas, Game Reserves and the Ngorongoro Conservation Area and the least in the most heavily protected Serengeti National Park. The deterioration in habitat quality over time was attributed primarily to anthropogenic activities and major land use policy changes. Effective implementation of land use plans, robust and far-sighted institutional arrangements, adaptive legal and policy instruments are essential to sustaining high habitat quality in contexts of rapid human population growth.
Even though over many years the IUCN has considered the African buffalo and waterbuck and abundant species in Africa with no conservation concern, the situation is rapidly changing. Using aerial counts in wet and dry season in 2010 and 2013, this study assessed the trend, population status and distribution of the African buffalo and common waterbuck in the Northern Tanzania and Southern Kenya borderland. Both species were rare in the borderland, with the Amboseli region had the highest number of buffalo (241.5 ± 29.9), followed by Magadi/Namanga (58.0 ± 22.0), West Kilimanjaro (38.8 ± 34.9), and lastly Lake Natron (14.5 ± 9.0) areas. In terms of density, Amboseli also led with 0.03 ± 0.00 (buffalo per km 2), but rest had similar densities of 0.01 ± 0.00 buffalo per km 2. In terms of percent changes in buffalo, Amboseli area had a positive increase (+10.59 ± 27.71), but with a negative growth of −17.12 in the dry season. All other changes in all locations had negative (decline) buffalo numbers over time. For waterbuck numbers, Amboseli area also led with 12.3 ± 3.9 waterbuck), followed by Magadi/Namanga (10.3 ± 3.7.0), Lake Natron (3.8 ± 3.4), and lastly West Kilimanjaro (0.5 ± 0.5) areas. In terms of waterbuck density, they were low and less than 0.00 ± 0.00 per km 2. For percent changes in waterbuck numbers, Magadi/Namanga had higher positive change (+458.33 ± 291.67), but all other locations had negative (decline) changes with the worst being West Kilimanjaro and Lake Natron areas. Further, buffalo number was dependent (p = 0.008) on the season, with numbers being higher in the wet season than dry season.
Accurate detection of individual animals and estimation of ungulate population density might be a function of vegetation cover, animal size, observation radius or season. We assessed the effect of these factors on estimates of detection probability and density using five ungulate species in Western Serengeti National Park, Tanzania. Estimates were derived from information collected using ground surveys involving line transects targeting three resident species (impala, topi and buffalo) and two migrants (wildebeest and zebra) and analysed using DISTANCE, MANOVA, t-test and Pearson correlation. Results showed that ground surveys that take observation radii of 100 m would appreciably estimate at least 80% of the available ungulates. Beyond 100 m radii, surveys would leave approximately 43% of individuals undetected, the reason being a substantial influence of animal size, vegetation cover and observation radius on the detection. Animal size and observation radius have interactive effects. On their own seasonal differences, they do not have any effect but in interaction with animal size have significant effects especially on the migrant species. As reliable estimates of detection and density are required for making reasonable inferences, we urge that surveys using DISTANCE approach should consider incorporating both ground and aerial survey methods and ensure adequate sample replication.
Management of invasive species, whether prevention, population reduction, or eradication, requires assessment of the invasive species' population status and an assessment of the probability of success of management options. Perceptions of a species' permanence in an environment or lack thereof frequently drives how limited time, financial, and personnel resources are allocated to such efforts. Language we use to describe a non-native species' status largely defines these perceptions and sets boundaries, real or perceived, to potential management actions. Here we discuss the use of a particular term-"established"when confronting management decisions for invasive species. Our objective is to contribute to bridging the gap between the realms of conceptual development and management with respect to use of the term "established". We find that although there are benefits of polysemy and synonymy to conceptual development they present an additional challenge to managers who must weigh the costs, benefits, and potential for success of particular management actions. We also examine how existing conceptual frameworks might be augmented to bridge the theoretical-practical gap, such as more precisely defining potential management actions and explicitly including assessment of risk.
Context Differences in body size and mouth morphologies influence dietary resource separation among savanna ungulates, and this influences their distribution across landscape. Aim The aim was to understand the influence of body size and mouth morphology differences on both diet and patch selection by ungulate species in western Serengeti. Two hypotheses were tested: (1) for ungulate species, the relative body sizes and muzzle widths (mean muzzle width range: 3.1- 9.85) relate directly to food biomass, and to quality of diets selected in the wet season when food is abundant; (2) in the wet season, if food is not limiting, similar-sized species should exhibit greater dietary niche overlap than ungulate species that differ greatly in body size and muzzle width; moreover, similar-sized species exhibit less dietary niche overlap than ungulate species that differ greatly in body size. Methods In the western Serengeti ecosystem, road transects and direct observation were used to obtain data on the distribution and diet of five ungulate species namely buffalo, zebra, wildebeest, topi and impala; which have of varying sizes (range: 70–630kg) feeding in three different vegetation types. Grassland biomass, structure, nutrient content and ungulate use were measured at sites along transects. Key Results Results indicated that large-bodied ungulates utilised patches of greater food abundance compared with those of smaller ungulates. Body mass was also negatively correlated with diet quality, so that smaller animals ate higher protein and lower-fibre foods, as predicted. Diet niche overlap (niche similarity) showed a strong positive relationship with body mass differences among ungulate species, in support of the second of the two predictions from this hypothesis, namely that dissimilarly sized species could eat the same food. Conclusion Overall, the results suggest that in this savanna system, variation in ungulate body size influences resource separation even in the food-abundant wet season, and that this helps multiple species to co-exist. Implications Implementing more focused conservation strategies will improve wildlife habitat quality by integrating fire as a forage management tool with grazing preferences to promote forage heterogeneity in protected areas.
Conservation management is strongly shaped by the interpretation of population trends. In the Serengeti ecosystem, Tanzania, aerial total counts indicate a striking increase in elephant abundance compared to all previous censuses. We developed a simple age-structured population model to guide interpretation of this reported increase, focusing on three possible causes: (1) in situ population growth, (2) immigration from Kenya, and (3) differences in counting methodologies over time. No single cause, nor the combination of two causes, adequately explained the observed population growth. Under the assumptions of maximum in situ growth and detection bias of 12.7% in previous censuses, conservative estimates of immigration from Kenya were between 250 and 1,450 individuals. Our results highlight the value of considering demography when drawing conclusions about the causes of population trends. The issues we illustrate apply to other species that have undergone dramatic changes in abundance, as well as many elephant populations.
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