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Rivers play a relevant role in the nutrient turnover during the transport from land to ocean. Here, highly dynamic planktonic processes are more important compared to streams making it necessary to link the dynamics of nutrient turnover to control mechanisms of phytoplankton. We investigated the basic conditions leading to high phytoplankton biomass and corresponding nutrient dynamics in eutrophic, 8th order River Elbe (Germany). In a first step, we performed six Lagrangian sampling campaigns in the lower river section at different hydrological conditions. While nutrient concentrations remained high at low algal densities in autumn and at moderate discharge in summer, high algal concentrations occurred at low discharge in summer. Under these conditions, concentrations of silica and nitrate decreased and rates of nitrate assimilation were high. Soluble reactive phosphorus was depleted and particulate phosphorus increased inversely. Rising molar C:P ratios of seston indicated a phosphorus limitation of phytoplankton, so far rarely observed in eutrophic large rivers. Global radiation combined with mixing depth had a strong predictive power to explain maximum chlorophyll concentration. In a second step, we estimated nutrient turnover exemplarily for N during the campaign with the lowest discharge based on mass balances and metabolism-based process measurements. Mass balance calculations revealed a total nitrate uptake of 423 mg N m(-2)d(-1). Increasing phytoplankton density dominantly explained whole river gross primary production and related assimilatory nutrient uptake. In conclusion, riverine nutrient uptake strongly depends on the growth conditions for phytoplankton, which are favored at high irradiation and low discharge.
Ambitious climate policies, as well as economic development, education, technological progress and less resource-intensive lifestyles, are crucial elements for progress towards the UN Sustainable Development Goals (SDGs). However, using an integrated modelling framework covering 56 indicators or proxies across all 17 SDGs, we show that they are insufficient to reach the targets. An additional sustainable development package, including international climate finance, progressive redistribution of carbon pricing revenues, sufficient and healthy nutrition and improved access to modern energy, enables a more comprehensive sustainable development pathway. We quantify climate and SDG outcomes, showing that these interventions substantially boost progress towards many aspects of the UN Agenda 2030 and simultaneously facilitate reaching ambitious climate targets. Nonetheless, several important gaps remain; for example, with respect to the eradication of extreme poverty (180 million people remaining in 2030). These gaps can be closed by 2050 for many SDGs while also respecting the 1.5 °C target and several other planetary boundaries.
Rooted in Eccles and colleagues' expectancy-value theory, this study aimed to examine how expectancies and different facets of task value combine to diverse profiles of motivational beliefs, how such complex profiles develop across a school year, and how they relate to gender and career plans. Despite abundant research on the association between gender and motivational beliefs, there is a paucity of knowledge regarding the gendered development of student motivational belief profiles in specific domains. Using latent-transition analysis in a sample of N = 751 ninth to tenth graders (55.9% girls), we investigated girls' and boys' development of motivational belief profiles (profile paths) in mathematics across a school year. We further analyzed the association between these profile paths and math-related career plans. The results revealed four motivational belief profiles: high motivation (intrinsic and attainment oriented), balanced above average motivation, average motivation (attainment and cost oriented), and low motivation (cost oriented). Girls were less likely than expected by chance to remain in the high motivation profile, while the opposite was true for boys. The math-relatedness of students' career plans was significantly higher in the "stable high motivation" profile path than in all other stable profile paths.
Person-centered research has shown that individuals can be assigned to different motivational profiles, but only scattered studies have addressed motivational profiles in specific domains. We investigated the stability and change in motivational profiles in mathematics classrooms and examined how perceived teaching predicted changes in profile membership. Data for this study stemmed from the PISA-I Plus study (N=6020). Latent profile analysis identified four motivational patterns: Medium, Low, High and Highly confident, hardly interested. Stability in profiles from grade 9 to 10 was typical. Instructional clarity and teaching for meaning predicted changes in profile membership.