Defensive reactions of freshwater ecosystems against external influences

AbstractEutrophication and toxic loading of freshwater occurred even in early geological epochs as a result of natural factors (e.g., large animals, volcanism), and nutrients and xenobiotics are more quickly integrated in material cycling in aquatic than in terrestrial systems. Therefore, aquatic ecosystems show many defensive mechanisms against organic and toxic loading. Many other defensive reactions can be described in addition to the well-known example of microbial self-purification.Freshwater ecosystems possess compartments which cooperate towards the function and protection of the whole system but, in opposition to these “euoecisms”, there are also “dysoecisms”. The defensive reactions of an ecosystem are founded largely on species-egoistic adaptations that have an (accidental) system-altruistic effect. The whole ecosystem reacts only seldom, and it is not clear whether there are selection processes which favour water bodies with a slow eutrophication and therefore slow silting-up, because the freshwaters are important for the global water balance.It is possible to compare organismic with ecosystemic defensive reactions but the origin of both reactions is very different

Diagrammatic Literacy in Secondary Science Education

Students in secondary science education seem to have difficulties with understanding diagrams. The present study focused on explanatory factors that predict students’ difficulties with process diagrams, i.e., diagrams that describe a process consisting of components that are related by arrows. From 18 compulsory national Biology exams of secondary school pre-university students, all process diagram tasks (n = 64) were included in corpus. Features of the task, student, and diagram were related to the difficulty of that particular task, indicated by the cohort mean exam score. A hierarchical regression analysis showed main effects for (1) the cognitive task demand, (2) the familiarity of the components, and (3) the number of components in a diagram. All these main effects were in the expected direction. We also observed interactions. Within the category of tasks with a high cognitive demand, tasks about a diagram of which students have low prior content knowledge were more difficult than tasks about a diagram of which students have high prior content knowledge. Tasks with a high cognitive demand about a diagram with familiar arrows were, surprisingly, more difficult than tasks with a high cognitive demand about a diagram with unfamiliar arrows. This latter finding might be attributed to compensation for task difficulty by the large number of components in the diagrams involved. The final model explained 46 % of the variance in exam scores. These results suggest that students have difficulties (1) with tasks that require a deeper understanding when the content is new, (2) with diagrams that use unfamiliar component conventions, and (3) with diagrams that have a small number of components and are therefore probably more abstract