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Assessment of subjective workload in an anaesthesia simulator environment: reliability and validity
(2011)
Recently, it was shown that patients with Parkinson's disease (PD) who exhibit an “Alzheimer's disease (AD)-like” pattern of brain atrophy are at greater risk for future cognitive decline. This study aimed to investigate whether this association is domain-specific and whether atrophy associated with brain aging also relates to cognitive impairment in PD. SPARE-AD, an MRI index capturing AD-like atrophy, and atrophy-based estimates of brain age were computed from longitudinal structural imaging data of 178 PD patients and 84 healthy subjects from the LANDSCAPE cohort. All patients underwent an extensive neuropsychological test battery. Patients diagnosed with mild cognitive impairment or dementia were found to have higher SPARE-AD scores as compared to patients with normal cognition and healthy controls. All patient groups showed increased brain age. SPARE-AD predicted impairment in memory, language and executive functions, whereas advanced brain age was associated with deficits in attention and working memory. Data suggest that SPARE-AD and brain age are differentially related to domain-specific cognitive decline in PD. The underlying pathomechanisms remain to be determined.
Atmosphere-surface fluxes modeling for the high Andes: The case of páramo catchments of Ecuador
(2020)
Interest in atmosphere-surface flux modeling over the mountainous regions of the globe has increased recently, with a major focus on the prediction of water, carbon and other functional indicators in natural and disturbed conditions. However, less research has been centered on exploring energy fluxes (net radiation; sensible, latent and soil heat) and actual evapotranspiration (ETa) over the Neotropical Andean biome of the páramo. The present study assesses the implementation and parameterization of a state-of-art Land-Surface Model (LSM) for simulation of these fluxes over two representative páramo catchments of southern Ecuador. We evaluated the outputs of the LSM Community Land Model (CLM ver. 4.0) with (i) ground-level flux observations from the first (and highest) Eddy Covariance (EC) tower of the Northern Andean páramos; (ii) spatial ETa estimates from the energy balance-based model METRIC (based on Landsat imagery); and (iii) derived ETa from the closure of the water balance (WB). CLM’s energy predictions revealed a significant underestimation on net radiation, which impacts the sensible and soil heat fluxes (underestimation), and delivers a slight overestimation on latent heat flux. Modeled CLM ETa showed acceptable goodness-of-fit (Pearson R = 0.82) comparable to ETa from METRIC (R = 0.83). Contrarily, a poor performance of ETa WB was observed (R = 0.46). These findings provide solid evidence on the CLM’s accuracy for the ETa modeling, and give insights in the selection of other ETa methods. The study contributes to a better understanding of ecosystem functioning in terms of water loss through evaporative processes, and might help in the development of future LSMs’ implementations focused on climate / land use change scenarios for the páramo.
Beiträge zur Jahrestagung des Vereins für Socialpolitik 2021: Climate Economics
A slow-fast trait continuum at the whole community level in relation to land-use intensification
(2024)
AbstractOrganismal functional strategies form a continuum from slow- to fast-growing organisms, in response to common drivers such as resource availability and disturbance. However, whether there is synchronisation of these strategies at the entire community level is unclear. Here, we combine trait data for 2800 above- and belowground taxa from 14 trophic guilds spanning a disturbance and resource availability gradient in German grasslands. The results indicate that most guilds consistently respond to these drivers through both direct and trophically mediated effects, resulting in a ‘slow-fast’ axis at the level of the entire community. Using 15 indicators of carbon and nutrient fluxes, biomass production and decomposition, we also show that fast trait communities are associated with faster rates of ecosystem functioning. These findings demonstrate that ‘slow’ and ‘fast’ strategies can be manifested at the level of whole communities, opening new avenues of ecosystem-level functional classification.