Determining LAI and leafy tree roughness using terrestrial laser scanning.

International audienceVegetation roughness, and more specifically forest roughness, is a necessary component in better defining flood dynamics both in the sense of changes in river catchment characteristics and the dynamics of forest changes and management. Extracting roughness parameters from riparian forests can be a complicated process involving different components for different required scales and flow depths. For flow depths that enter a forest canopy, roughness at both the woody branch and foliage level is necessary. This study attempts to extract roughness for this leafy component using a relatively new remote sensing technique in the form of terrestrial laser scanning. Terrestrial laser scanning is used in this study due to its ability to obtain millions of points within relatively small forest stands. This form of lidar can be used to determine the gaps present in foliaged canopies in order to determine the leaf area index. The leaf area index can then be directly input into resistance equations to determine the flow resistance at different flow depths. Leaf area indices created using ground scanning are compared in this study to indices calculated using simple regression equations. The dominant riparian forests investigated in this study are planted and natural poplar forests over a lowland section of the Garonne River in Southern France. Final foliage roughness values were added to woody branch roughness from a previous study, resulting in total planted riparian forest roughness values of around Manning's n = 0.170–0.195 and around n = 0.245–330 for in-canopy flow of 6 and 8 m, respectively, and around n = 0.590 and around n = 0.750 for a natural forest stand at the same flow depths

Determining LAI and leafy tree roughness using terrestrial laser scanning.

International audienc

Biallelic variants in LINGO1 are associated with autosomal recessive intellectual disability, microcephaly, speech and motor delay.

To elucidate the novel molecular cause in two unrelated consanguineous families with autosomal recessive intellectual disability. A combination of homozygosity mapping and exome sequencing was used to locate the plausible genetic defect in family F162, while only exome sequencing was followed in the family PKMR65. The protein 3D structure was visualized with the University of California-San Francisco Chimera software. All five patients from both families presented with severe intellectual disability, aggressive behavior, and speech and motor delay. Four of the five patients had microcephaly. We identified homozygous missense variants in LINGO1, p.(Arg290His) in family F162 and p.(Tyr288Cys) in family PKMR65. Both variants were predicted to be pathogenic, and segregated with the phenotype in the respective families. Molecular modeling of LINGO1 suggests that both variants interfere with the glycosylation of the protein. LINGO1 is a transmembrane receptor, predominantly found in the central nervous system. Published loss-of-function studies in mouse and zebrafish have established a crucial role of LINGO1 in normal neuronal development and central nervous system myelination by negatively regulating oligodendrocyte differentiation and neuronal survival. Taken together, our results indicate that biallelic LINGO1 missense variants cause autosomal recessive intellectual disability in humans