Biology subjects

Ogutu, J. O.

Publications and source records attributed to Ogutu, J. O..

4 recordsLinked to original sources

bioRxiv2019

Spatial and temporal variation in small mammal abundance and diversity under protection, pastoralism and agriculture in the Serengeti Ecosystem, Tanzania

Land use is an important factor influencing animal abundance, species richness and diversity in both protected and human-dominated landscapes. Increase in human population and activities intensify changes in habitat structure and hence abundance, species richness and diversity. We investigated the influences of land use and seasonality on small mammal abundance, species richness and diversity in 10 habitat types distributed over protected, agricultural and pastoral landscapes in the Serengeti ecosystem in Tanzania. We used live traps (n = 141) and capture-recapture methods in each of 10 fixed plots distributed across three landscapes for a total of 28,200 trap nights of effort. Trapping was carried out in the wet and dry seasons for two consecutive years (April 2017 to October 2018). Small mammal abundance was higher in the pastoral than in the protected and in the agricultural landscape. Abundance was higher in the dry than the wet season across all the three landscapes. Species richness and diversity were higher in the protected, middling in the agricultural and lowest in the pastoral landscape. The high abundance in the pastoral landscape was due to the numerical dominance of two species, namely A. niloticus in the shrubland and M. natalensis in the cropland habitat, resulting in low species richness and diversity. Abundance was more evenly distributed across all habitats in the protected area due to less disturbance. The low abundance in the agricultural landscape, likely reflects disturbance from cultivation. High species richness and diversity in the protected area indicate high habitat heterogeneity while high species diversity in the agricultural landscape was likely due to high food availability during and soon after harvests. These findings emphasize the importance of protection in maintaining habitat heterogeneity for wildlife. They also reaffirm the need for buffer zones around protected areas to cushion them from intensifying human activities.

ecology↗

bioRxiv2019

Robust estimation of heritability and predictive accuracy in plant breeding: evaluation using simulation and empirical data

BackgroundGenomic prediction (GP) is used in animal and plant breeding to help identify the best genotypes for selection. One of the most important measures of the effectiveness and reliability of GP in plant breeding is predictive accuracy. An accurate estimate of this measure is thus central to GP. Moreover, regression models are the models of choice for analyzing field trial data in plant breeding. However, models that use the classical likelihood typically perform poorly, often resulting in biased parameter estimates, when their underlying assumptions are violated. This typically happens when data are contaminated with outliers. These biases often translate into inaccurate estimates of heritability and predictive accuracy, compromising the performance of GP. Since phenotypic data are susceptible to contamination, improving the methods for estimating heritability and predictive accuracy can enhance the performance of GP. Robust statistical methods provide an intuitively appealing and a theoretically well justified framework for overcoming some of the drawbacks of classical regression, most notably the departure from the normality assumption. We compare the performance of robust and classical approaches to two recently published methods for estimating heritability and predictive accuracy of GP using simulation of several plausible scenarios of random and block data contamination with outliers and commercial maize and rye breeding datasets.\n\nResultsThe robust approach generally performed as good as or better than the classical approach in phenotypic data analysis and in estimating the predictive accuracy of heritability and genomic prediction under both the random and block contamination scenarios. Notably, it consistently outperformed the classical approach under the random contamination scenario. Analyses of the empirical maize and rye datasets further reinforce the stability and reliability of the robust approach in the presence of outliers or missing data.\n\nConclusionsThe proposed robust approach enhances the predictive accuracy of heritability and genomic prediction while alleviating the need for performing outlier detection for a broad range of simulation scenarios and empirical breeding datasets. Accordingly, plant breeders should seriously consider regularly using the robust alongside the classical approach and increasing the number of replicates to three or more, to further enhance the accuracy of the robust approach.

genomics↗

bioRxiv2019

Wildebeest migration in East Africa: Status, threats and conservation measures

Migration of ungulates is under pressure worldwide from range contraction, habitat loss and degradation, anthropogenic barriers and poaching. Here, we synthesize and compare the extent of historical migrations of the white-bearded wildebeest (Connochaetes taurinus) to their contemporary status, in five premier East African ecosystems, namely the Serengeti-Mara, Masai Mara, Athi-Kaputiei, Amboseli and Tarangire-Manyara. The current status, threats to migration, migratory ranges and routes for wildebeest were characterized using colonial-era maps, literature reviews, GIS and aerial survey databases, GPS collared animals and interviews with long-term researchers. Interference with wildebeest migratory routes and dispersal ranges has stopped or severely threatens continuation of the historical migration patterns in all but the Serengeti-Mara ecosystem where the threat level is relatively lower. Wildebeest migration has collapsed in Athi-Kaputiei ecosystem and is facing enormous pressures from land subdivision, settlements and fences in Amboseli and Mara ecosystems and from cultivation in Tarangire-Manyara ecosystem. Land use change, primarily expansion in agriculture, roads, settlements and fencing, increasingly restrict migratory wildebeest from accessing traditional grazing resources in unprotected lands. Privatization of land tenure in group ranches in Kenya and settlement policy (villagization) in Tanzania have accelerated land subdivision, fencing and growth in permanent settlements, leading to loss of key wildebeest habitats including their migratory routes and wet season calving and feeding grounds. These processes, coupled with increasing human population pressures and climatic variability, are exerting tremendous pressures on wildebeest migrations. Urgent conservation interventions are necessary to conserve and protect the critical wildebeest habitats and migration routes in East Africa.

ecology↗

bioRxiv2019

Long-Term historical and Projected Herbivore Population Dynamics in Ngorongoro Crater, Tanzania

The Ngorongoro Crater is an intact caldera with an area of approximately 310 km2. Long term records on herbivore populations, vegetation and rainfall made it possible to analyze historic and project future herbivore population dynamics. In 1974 there was a perturbation in that resident Maasai and their livestock were removed from the Crater. Vegetation structure changed in 1967 from predominately short grassland to mid and tall grasses dominating in 1995. Even with a change in grassland structure, total herbivore biomass remained relatively stable from 1963 to 2012, implying that the crater has a stable multi-herbivore community. However, in 1974, Maasai pastoralists were removed from the Ngorongoro Crater and there were significant changes in population trends for some herbivore species. Buffalo, elephant and ostrich numbers increased significantly during 1974-2012. The zebra population was stable from 1963 to 2012 whereas numbers of other eight species declined substantially between 1974 and 2012 relative to their peak numbers during 1974-1976. Numbers of Grants and Thomsons gazelles, eland, kongoni, waterbuck (wet season only) declined significantly in the Crater in both seasons after 1974. Wildebeest numbers decreased in the Crater between 1974 and 2012 but this decrease was not statistically significant. In addition, some herbivore species were consistently more abundant inside the Crater during the wet than the dry season. This pattern was most evident for the large herbivore species requiring bulk forage, comprising buffalo, eland, and elephant. Analyses of rainfall indicated that there was a persistent annual cycle of 4.83 years. Herbivore population size was correlated with rainfall in both the wet and dry seasons. The relationships established between the time series of historic animal counts in the wet and dry seasons and lagged wet and dry season rainfall series were used to forecast the likely future trajectories of the wet and dry season population size for each species under three alternative climate change scenarios.

ecology↗