Suchergebnisse

Zur Indienststellung des Forschungsschiffes PLANET im Jahr 2005 durch die Forschungsanstalt der Bundeswehr für Wasserschall und Geophysik veröffentlicht die Forschungsanstalt die Erinnerungen eines Soldaten, der von 1907 bis 1909 auf einem Vermessungsschiff der Kaiserlichen Marine in der Südsee fuhr, das auch den Namen PLANET trug. Der in Tagebuchform gefasste Erlebnisbericht soll nicht nur eine Tradition begründen, sondern Einblicke gewähren in eine vergangene Zeit und die vergangene Welt der Südsee-Kolonien des deutschen Kaiserreichs. Die damalige PLANET ließ schon die Entwicklung in Richtung auf die moderne Forschungsschiffahrt erkennen.

Mapping forest aboveground biomass (AGB) using satellite data is an important task, particularly for reporting of carbon stocks and changes under climate change legislation. It is known that AGB can be mapped using synthetic aperture radar (SAR), but relationships between AGB and radar backscatter may be confounded by variations in biophysical forest structure (density, height or cover fraction) and differences in the resolution of satellite and ground data. Here, we attempt to quantify the effect of these factors by relating L-band ALOS PALSAR HV backscatter and unique country-wide LiDAR-derived maps of vegetation penetrability, height and AGB over Denmark at different spatial scales (50 m to 500 m). Trends in the relations indicate that, first, AGB retrieval accuracy from SAR improves most in mapping at 100-m scale instead of 50 m, and improvements are negligible beyond 250 m. Relative errors (bias and root mean squared error) decrease particularly for high AGB values (>110 Mg ha -1 ) at coarse scales, and hence, coarse-scale mapping (≥150 m) may be most suited for areas with high AGB. Second, SAR backscatter and a LiDAR-derived measure of fractional forest cover were found to have a strong linear relation (R 2 = 0.79 at 250-m scale). In areas of high fractional forest cover, there is a slight decline in backscatter as AGB increases, indicating signal attenuation. The two results demonstrate that accounting for spatial scale and variations in forest structure, such as cover fraction, will greatly benefit establishing adequate plot-sizes for SAR calibration and the accuracy of derived AGB maps.

Funding: AG and TFMA were supported by the Munich Cluster for Systems Neurology (SyNergy). AG 535 was supported by Fondazione Umberto Veronesi. SP is a Royal Society University Research fellow. BMM, CF, BSP and SEF are supported by the Max Planck Society. AW, BM and HK were funded by the Fraunhofer Society and the Max Planck Society within the 'Pakt für Forschung und Innovation'. HK was also supported by LIFE – Leipzig Research Center for Civilization Diseases funded by means of the European Union; the European Regional Development Fund (ERDF); and the Free State of Saxony within the excellence initiative. FR is supported by Agence Nationale de la Recherche (ANR-06-NEURO-019-01, ANR-17-EURE-542 0017 IEC, ANR-10-IDEX-0001-02 PSL, ANR-11-BSV4-014-01), European Commission (LSHM-CT-2005-018696). TFMA was supported by the BMBF through the DIFUTURE consortium of the Medical Informatics Initiative Germany (grant 01ZZ1804A) and by the European Union's Horizon 2020 Research and Innovation Programme (grant MultipleMS, EU RIA 733161). ; Developmental dyslexia (DD) is a learning disorder affecting the ability to read, with a heritability of 40–60%. A notable part of this heritability remains unexplained, and large genetic studies are warranted to identify new susceptibility genes and clarify the genetic bases of dyslexia. We carried out a genome-wide association study (GWAS) on 2274 dyslexia cases and 6272 controls, testing associations at the single variant, gene, and pathway level, and estimating heritability using single-nucleotide polymorphism (SNP) data. We also calculated polygenic scores (PGSs) based on large-scale GWAS data for different neuropsychiatric disorders and cortical brain measures, educational attainment, and fluid intelligence, testing them for association with dyslexia status in our sample. We observed statistically significant (p < 2.8 × 10−6) enrichment of associations at the gene level, for LOC388780 (20p13; uncharacterized gene), and for VEPH1 (3q25), a gene implicated in brain development. We estimated an SNP-based heritability of 20–25% for DD, and observed significant associations of dyslexia risk with PGSs for attention deficit hyperactivity disorder (at pT = 0.05 in the training GWAS: OR = 1.23[1.16; 1.30] per standard deviation increase; p = 8 × 10−13), bipolar disorder (1.53[1.44; 1.63]; p = 1 × 10−43), schizophrenia (1.36[1.28; 1.45]; p = 4 × 10−22), psychiatric cross-disorder susceptibility (1.23[1.16; 1.30]; p = 3 × 10−12), cortical thickness of the transverse temporal gyrus (0.90[0.86; 0.96]; p = 5 × 10−4), educational attainment (0.86[0.82; 0.91]; p = 2 × 10−7), and intelligence (0.72[0.68; 0.76]; p = 9 × 10−29). This study suggests an important contribution of common genetic variants to dyslexia risk, and novel genomic overlaps with psychiatric conditions like bipolar disorder, schizophrenia, and cross-disorder susceptibility. Moreover, it revealed the presence of shared genetic foundations with a neural correlate previously implicated in dyslexia by neuroimaging evidence. ; Publisher PDF ; Peer reviewed