How dynamics and drivers of land use/land cover change impact elephant conservation and agricultural livelihood development in Rombo,Tanzania

Land use/land cover (LULC) change affects the provision of ecosystem services for humans and habitat for wildlife. Hence, it is crucial to monitor LULC particularly adjacent to protected areas. In this study, we measured LULC change in Rombo, Tanzania, an area with high-potential agro-ecological zones that is dominated by human–elephant conflicts (HECs). We used remote sensing and geographical information system techniques, questionnaires and village meetings to assess spatio-temporal patterns of the LULC changes in the study area. Using Landsat imagery, digital elevation model (DEM) and ground truthing, we classified and monitored changes in LULC from the years 1987 to 2015. We found that within Rombo, settlements were increasing, while agricultural and agroforestry lands were decreasing and respondents’ perceptions varied along the altitudinal gradient. Patterns of HEC and LULC were observed to change along the gradient and the later threatened the agricultural land and ecological integrity for elephant habitat, leading to high tension and competition between elephants and people. This research offers baseline information for land use planning to balance wildlife conservation with livelihood development in Rombo and highlights that managing the impacts of LULC changes on HEC and elephant habitat loss is a matter of urgency.     

Modelling llama population development under environmental and market constraints in the Bolivian highlands

Changes in the size of animal populations over time are mainly determined by demographic and environmental factors. Livestock population dynamics are additionally influenced by harvesting decisions taken by herders. In Bolivia, not much is known about current llama husbandry and the main influencing factors determining population sizes. We collected data on demography, environmental factors and market values affecting the current and future llama population in three different regions in Bolivia. We generated a population model and assessed the future development of the llama population including environmental factors (rangeland carrying capacity, disturbance phenomena), herd structure and dynamics, and economic market demands. We calibrated and validated the llama model on the basis of 20-year data sets of the regions of Oruro, Potosi and La Paz, respectively. Model calibration by means of the Gauss-Marquardt-Levenberg algorithm yielded a model efficiency of 0.94. For model validation, however, the simulation slightly overestimated the observed llama population yielding model efficiencies of 0.91 and 0.87 for Potosi and La Paz, respectively. Model outcomes were most sensitive to death and birth rates of juveniles and death rate of females compared to environmental or other demographic factors. Population trajectories approached an overall carrying capacity for Oruro, Potosi and La Paz of 8.8 × 10⁵, 9.1 × 10⁵, and 9.0 × 10⁵ llama individuals after 100 years of simulation. Hence, detailed monitoring of demographic, environmental, and economic factors can improve predictions of llama population development over time. Further management should focus on improving birth rates and lowering female mortality through providing supplemental food and shelters against the harsh environmental conditions of the Andean highlands.