Land system science and sustainable development of the earth system: A global land project perspective

Land systems are the result of human interactions with the natural environment. Understanding the drivers, state, trends and impacts of different land systems on social and natural processes helps to reveal how changes in the land system affect the functioning of the socio-ecological system as a whole and the tradeoff these changes may represent. The Global Land Project has led advances by synthesizing land systems research across different scales and providing concepts to further understand the feedbacks between social-and environmental systems, between urban and rural environments and between distant world regions. Land system science has moved from a focus on observation of change and understanding the drivers of these changes to a focus on using this understanding to design sustainable transformations through stakeholder engagement and through the concept of land governance. As land use can be seen as the largest geo-engineering project in which mankind has engaged, land system science can act as a platform for integration of insights from different disciplines and for translation of knowledge into action.

Downward Causation – The Way How Mind and Matter Interact?

The paper analyzes Karl Popper’s and John Eccles’ account of mind-matter interaction and compares their use of the concept of downward causation with other more recent accounts of it, especially those of Nancey Murphy and George Ellis. The argument includes John Polkinghorne’s take on Divine action, as it provides an interesting version of downward mind/matter-interaction. It will be argued that while downward causation is a speculative concept, it nevertheless remains the best approximation to a scientific perspective on mind/matter interaction that we can obtain. As a result, Popper’s and Eccles’ account seems to be more interesting in these regards than usually assumed, and should not continue to be overlooked in the debate.

Source Memory for Mental Imagery: Influences of the Stimuli’s Ease of Imagery.

The present study investigated how ease of imagery influences source monitoring accuracy. Two experiments were conducted in order to examine how ease of imagery influences the probability of source confusions of perceived and imagined completions of natural symmetric shapes. The stimuli consisted of binary pictures of natural objects, namely symmetric pictures of birds, butterflies, insects, and leaves. The ease of imagery (indicating the similarity of the sources) and the discriminability (indicating the similarity of the items) of each stimulus were estimated in a pretest and included as predictors of the memory performance for these stimuli. It was found that confusion of the sources becomes more likely when the imagery process was relatively easy. However, if the different processes of source monitoring-item memory, source memory and guessing biases-are disentangled, both experiments support the assumption that the effect of decreased source memory for easily imagined stimuli is due to decision processes and misinformation at retrieval rather than encoding processes and memory retention. The data were modeled with a Bayesian hierarchical implementation of the one high threshold source monitoring model.

Internal Models, Vestibular Cognition, and Mental Imagery: Conceptual Considerations

Vestibular cognition has recently gained attention. Despite numerous experimental and clinical demonstrations, it is not yet clear what vestibular cognition really is. For future research in vestibular cognition, adopting a computational approach will make it easier to explore the underlying mech- anisms. Indeed, most modeling approaches in vestibular science include a top-down or a priori component. We review recent Bayesian optimal observer models, and discuss in detail the conceptual value of prior assumptions, likelihood and posterior estimates for research in vestibular cognition. We then consider forward models in vestibular processing, which are required in order to distinguish between sensory input that is induced by active self-motion, and sensory input that is due to passive self-motion. We suggest that forward models are used not only in the service of estimating sensory states but they can also be drawn upon in an offline mode (e.g., spatial perspective transformations), in which interaction with sensory input is not desired. A computational approach to vestibular cogni- tion will help to discover connections across studies, and it will provide a more coherent framework for investigating vestibular cognition.

Disentangling mental imagery and perceptual expectation

Mental imagery and perception are thought to rely on similar neural circuits, and many recent behavioral studies have attempted to demonstrate interactions between actual physical stimulation and sensory imagery in the corresponding sensory modality. However, there has been a lack of theoretical understanding of the nature of these interactions, and both interferential and facilitatory effects have been found. Facilitatory effects appear strikingly similar to those that arise due to experimental manipulations of expectation. Using a self-motion discrimination task, we try to disentangle the effects of mental imagery from those of expectation by using a hierarchical drift diffusion model to investigate both choice data and response times. Manipulations of expectation are reasonably well understood in terms of their selective influence on parameters of the drift diffusion model, and in this study, we make the first attempt to similarly characterize the effects of mental imagery. We investigate mental imagery within the computational framework of control theory and state estimation. • Mental imagery and perception are thought to rely on similar neural circuits; however, on more theoretical grounds, imagery seems to be closely related to the output of forward models (sensory predictions). • We reanalyzed data from a study of imagined self-motion. • Bayesian modeling of response times may allow us to disentangle the effects of mental imagery on behavior from other cognitive (top-down) effects, such as expectation.

Comparisons between analogue and numerical models of thrust wedge development

Analogue and finite element numerical models with frictional and viscous properties are used to model thrust wedge development. Comparison between model types yields valuable information about analogue model evolution, scaling laws and the relative strengths and limitations of the techniques. Both model types show a marked contrast in structural style between ‘frictional-viscous domains’ underlain by a thin viscous layer and purely ‘frictional domains’. Closely spaced thrusts form a narrow and highly asymmetric fold-and-thrust belt in the frictional domain, characterized by in-sequence propagation of forward thrusts. In contrast, the frictional-viscous domain shows a wide and low taper wedge and a thrust belt with a more symmetrical vergence, with both forward and back thrusts. The frictional-viscous domain numerical models show that the viscous layer initially simple shears as deformation propagates along it, while localized deformation resulting in the formation of a pop-up structure occurs in the overlying frictional layers. In both domains, thrust shear zones in the numerical model are generally steeper than the equivalent faults in the analogue model, because the finite element code uses a non-associated plasticity flow law. Nevertheless, the qualitative agreement between analogue and numerical models is encouraging. It shows that the continuum approximation used in numerical models can be used to model frictional materials, such as sand, provided caution is taken to properly scale the experiments, and some of the limitations are taken into account.