A simple and efficient GIS tool for volume calculations of submarine landslides

A numeric tool is presented for calculating volumes of topographic voids such as slump scars of landslides, canyons or craters (negative/concave morphology), or alternatively, bumps and hills (positive/convex morphology) by means of digital elevation models embedded within a geographical information system (GIS). In this study, it has been used to calculate landslide volumes. The basic idea is that a (singular) event (landslide, meteorite impact, volcanic eruption) has disturbed an intact surface such that it is still possible to distinguish between the former (undisturbed) landscape and the disturbance (crater, slide scar, debris avalanche). In such cases, it is possible to reconstruct the paleo-surface and to calculate the volume difference between both surfaces, thereby approximating the volume gain or loss caused by the event. I tested the approach using synthetically generated land surfaces that were created on the basis of Shuttle Radar Topography Mission data. Also, I show the application to two real cases, (1) the calculation of the volume of the Masaya Slide, a submarine landslide on the Pacific continental slope of Nicaragua, and (2) the calculation of the void of a segment of the Fish River Canyon, Namibia. The tool is provided as a script file for the free GIS GRASS. It performs with little effort, and offers a range of interpolation parameters. Testing with different sets of interpolation parameters results in a small range of uncertainty. This tool should prove useful in surface studies not exclusively on earth

Novel loci achieving genome-wide significance (P<5x10^-8) in meta-analyses for PA-adjusted SNP main effect (P_adjPA) or the joint test of SNP main effect and SNP-PA interaction (P_joint).

<p>Novel loci achieving genome-wide significance (P<5x10^-8) in meta-analyses for PA-adjusted SNP main effect (P_adjPA) or the joint test of SNP main effect and SNP-PA interaction (P_joint).</p

Genes of biological interest within 500 kb of lead SNPs associated with WC_adjBMI or WHR_adjBMI.

<p>Genes of biological interest within 500 kb of lead SNPs associated with WC_adjBMI or WHR_adjBMI.</p

Genes of biological interest within 500 kb of lead SNPs associated with BMI.

<p>Genes of biological interest within 500 kb of lead SNPs associated with BMI.</p

Power to identify PA-adjusted main, joint or GxPA interaction effects in 200,000 individuals (45,000 inactive, 155,000 active).

<p>The plots compare power to identify genome-wide significant main effects (P_adjPA<5x10^-8, dashed black), joint effects (P_JOINT<5x10^-8, dotted green) or GxPA interaction effects (P_INT<5x10^-8, solid magenta) as well as the power to identify Bonferroni-corrected interaction effects (P_INT<0.05/number of loci, solid orange) for the SNPs that reached a genome-wide significant PA-adjusted main effect association (P_adjPA<5x10^-8). The power computations were based on analytical power formulae provided elsewhere [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006528#pgen.1006528.ref050" target="_blank">50</a>] and were conducted a-priori based on various types of known realistic BMI effect sizes [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006528#pgen.1006528.ref051" target="_blank">51</a>]. <b>Panels A, C, E</b>: Assuming an effect in inactive individuals similar to a small (, comparable to the known BMI effect of the <i>NUDT3</i> locus), medium (, comparable to the known BMI effect of the <i>BDNF</i> locus) and large (, comparable to the known BMI effect of the <i>FTO</i> locus) realistic effect on BMI and for various effects in physically active individuals (varied on the x axis); <b>Panels B,D,F</b>: Assuming an effect in physically active individuals similar to the small, medium and large realistic effects of the <i>NUDT3</i>, <i>BDNF and FTO</i> loci on BMI and for various effects in inactive individuals (varied on x axis).</p