Savannah ecosystems play a prominent role in the global carbon (C) cycle, yet fluxes are poorly quantified, and the key processes regulating vegetation dynamics are uncertain. Insight is particularly deficient in southern Africa’s miombo woodlands, a woody savannah that is home to over 100 million people. This biome is heavily disturbed, with widespread deforestation and degradation associated with agriculture, charcoal and timber extraction, and frequent fires from anthropogenic sources. In this thesis I combine plot inventory data with remote sensing and modelling techniques to improve our understanding of the miombo woodland C cycle. Using a network of forest inventory plots, I characterise floristic and functional diversity in a savannah-forest mosaic in southeastern Tanzania. Divergent vegetation structures are associated with variation in fire frequency, water supply, and soil chemo-physical properties. Corresponding differences are noted in fire resilience, water-use, and nutrient acquisition plant functional traits, suggesting that multiple interrelated environmental filters act to assemble heterogeneous tree communities. Re-inventory of forest plots was used to quantify key aspects of the woody C cycle. Tree growth rates are slow, calling for careful management of woodland resources, and significantly reduced where stems were damaged. Stem mortality is rare, though elevated in the smallest trees and where damage was recorded. Contemporary strategies to incentivise the conservation of miombo woodland ecosystems, such as the REDD+ programme of the United Nations, advocate payments for sustaining ecosystem services such as C sequestration. I report on a pilot REDD+ project aiming to reduce woodland degradation from frequent high intensity fires in southeastern Tanzania. Model simulations suggest that woody biomass is being gradually lost from the region, and that setting early season fires has the potential to reverse this trend. Realising substantial changes in C storage requires a demanding reduction to late fire frequency, and uncertainty in model predictions remains high. I quantify the C cycle of southern African woodlands by combining observational data with a diagnostic C cycle model under a model-data fusion framework. Model outputs show substantial variation in primary production, C allocation patterns, and foliar and canopy traits, which are associated with differences in woody cover, fire, and precipitation properties. C cycle dynamics correspond poorly to conventional land cover maps, indicating they may be unsuited to upscaling measurements and models of the terrestrial C cycle.

Diese Promotion befasst sich in drei unterschiedlichen Studien mit der Vorhersage schulischer Leistungen in der chinesischen Kultur. Die Arbeit befasst sich demzufolge sowohl mit Konstrukten der fluiden Intelligenz (Gf), den Persönlichkeitsdomänen (Big Five), schmaler gefassten Persönlichkeitskonstrukten (Glaube an sich Selbst, Lernstrategien) sowie dem komplexen Zusammenspiel dieser Konstrukte als Prädiktoren für schulische Leistungen. Nach einer generellen Einführung und der Herleitung des Big Five Narrow Trait (B5NT) Modells werden die drei Studien dargestellt. Studie 1 untersucht bei chinesischen Sekundarschülern figurale Verarbeitungsfähigkeit als Indikator für Gf und Persönlichkeitseigenschaften als Indikatoren für Schulnoten in den Fächern Mathematik, Chinesisch und Englisch sowie mögliche Interaktionen. Die zweite Studie integriert diese Ergebnisse in das B5NT Modell, das zudem mit anderen Modellen, wie etwa dem Double Mediation model (DM), verglichen wird. Der Glaube an sich selbst sowie Lernstrategien werden in den Analysen als wichtige Mediatoren betrachtet. Studie 3 überprüft die Ergebnisse in einem längsschnittlichen Design. Während bereits in Studie 2 starke Evidenz für das B5NT Modell gefunden werden konnte, kann dies auch in Studie 3 repliziert werden. Zudem können in einem Revisionsmodell reziproke Effekte von Performanz auf Persönlichkeitsdomänen angenommen werden. Die Promotion stellt daher ein theoretisches Modell zur Verfügung, das den Einfluss von den Big Five Domänen auf die schulischen Leistungen erklärt und durch querschnittliche sowie längsschnittliche Daten gestützt wird / This dissertation deals with the prediction of scholastic performance in Chinese culture. The thesis uses the constructs of fluid intelligence (Gf), broad personality traits (Big Five), narrow personality traits (i.e., self-beliefs and learning approaches), and their complex interplay as predictors of scholastic performance. Following a general introduction summarizing the theoretical foundations as well as outlining the derivation of the Big Five Narrow Trait (B5NT) Model, three papers are presented. In the context of Chinese secondary school students, Paper 1 examined the predictive power of figural reasoning as an indicator of Gf and personality traits on school grades in three subjects (i.e., Mathematics, Chinese, and English), and further investigated their potential interactions. Paper 2 integrated the findings of Paper 1 with the aforementioned B5NT. Within the study, the B5NT is empirically tested and compared to an alternative model proposed in earlier work, the Double Mediation model [DM]. Self-beliefs and learning approaches were considered as relevant mediators within those analyses. In this cross-sectional study, the B5NT model was strongly supported, whereas the DM model did not find strong empirical support. In order to empirically verify the underlying processes from a longitudinal perspective, Paper 3 expanded on the B5NT related findings in a three-wave longitudinal panel design. The findings supported the B5NT model and further warranted a revision model in which reciprocal effects from performance to big traits are suggested. Thus, the presented thesis provides a theoretical model explaining the influence of the Big Five on scholastic performance. Moreover, empirical support for the proposed model from cross-sectional and longitudinal data was found. Finally, integrating interactions with cognitive ability rounds off the perspective.