Thank You to Our 2019 Peer Reviewers

On behalf of the journal, AGU, and the scientific community, the editors would like to sincerely thank those who reviewed the manuscripts for Geophysical Research Letters in 2019. The hours reading and commenting on manuscripts not only improve the manuscripts but also increase the scientific rigor of future research in the field. We particularly appreciate the timely reviews in light of the demands imposed by the rapid review process at Geophysical Research Letters. With the revival of the “major revisions” decisions, we appreciate the reviewers’ efforts on multiple versions of some manuscripts. With the advent of AGU’s data policy, many reviewers have helped immensely to evaluate the accessibility and availability of data associated with the papers they have reviewed, and many have provided insightful comments that helped to improve the data presentation and quality. We greatly appreciate the assistance of the reviewers in advancing open science, which is a key objective of AGU’s data policy. Many of those listed below went beyond and reviewed three or more manuscripts for our journal, and those are indicated in italics.Key PointThe editors thank the 2019 peer reviewersPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/162718/2/grl60415.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162718/1/grl60415_am.pd

Thank You to Our 2018 Peer Reviewers

On behalf of the journal, AGU, and the scientific community, the Editors would like to sincerely thank those who reviewed manuscripts for Geophysical Research Letters in 2018. The hours reading and commenting on manuscripts not only improves the manuscripts but also increases the scientific rigor of future research in the field. We particularly appreciate the timely reviews, in light of the demands imposed by the rapid review process at Geophysical Research Letters. With the revival of the “major revisions” decisions, we appreciate the reviewers’ efforts on multiple versions of some manuscripts. Many of those listed below went beyond and reviewed three or more manuscripts for our journal, and those are indicated in italics. In total, 4,484 referees contributed to 7,557 individual reviews in journal. Thank you again. We look forward to the coming year of exciting advances in the field and communicating those advances to our community and to the broader public.Key PointIn total, 4,484 referees contributed to 7,557 individual reviews in journalPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152982/1/grl59194.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/152982/2/grl59194_am.pd

Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus

A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10-20), ER-negative BC (P=1.1 × 10-13), BRCA1-associated BC (P=7.7 × 10-16) and triple negative BC (P-diff=2 × 10-5). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10-3) and ABHD8 (P<2 × 10-3). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 3′-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk

Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus

A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P = 9.2 x 10(-20)), ER-negative BC (P = 1.1 x 10(-13)), BRCA1-associated BC (P = 7.7 x 10(-16)) and triple negative BC (P-diff = 2 x 10(-5)). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P = 2 x 10(-3)) and ABHD8 (PPeer reviewe

Gravitational potential energy and regional stress and strain rate fields for continental plateaus: Examples from the central Andes and Colorado Plateau

The commonly observed extension in areas of elevated and thickened crust is an expected consequence of having excess gravitational potential energy (GPE) compared to the low GPE of the surrounding crust. While this conceptual model is well founded, it is less clear how well GPE-related stress orientations compare quantitatively to observed stress and strain rate orientations and what any inconsistency tells us about the presence of other competing forces. We estimate the GPE distribution for the central Andes and the greater Colorado Plateau area using topography and crustal thickness variations, respectively, and compare the related stress fields with the World Stress Map as well as with a geodetic strain rate field (for the Colorado Plateau only). In both areas, deviatoric stresses associated with GPE variations alone cannot fully account for the observed deformation rate field. For the central Andes only a combination of deviatoric stresses associated with GPE and relative plate motions can account for the near N–S tensional stress observed in the Peruvian Andes and the margin–normal compressional stress along the eastern Cordillera and sub-Andean fold-and-thrust belt. The observed deformation field around the Colorado Plateau shows E–W extension, largely inconsistent with the deviatoric stresses associated with GPE variations except for the area east of the Rio Grande Rift. The NE–SW oriented stress observed on the southwestern Colorado Plateau is consistent with the orientations of tensional deviatoric stresses associated with GPE variations. We argue that this consistency could be haphazard; stress observations may not reflect the current state of stress due to inherited structure, or could result from the relative high strength of Colorado Plateau that allows for regional GPE variations (and possibly basal shear) to be more significant forces than far-field plate interactions. For the central Andes and Colorado Plateau, stresses associated with GPE variations have a strong influence on the total stress field, and can thus be used to calibrate the overall level of deviatoric stress acting within the lithosphere

Contribution of gravitational potential energy differences to the global stress field

Modelling the lithospheric stress field has proved to be an efficient means of determining the role of lithospheric versus sublithospheric buoyancies and also of constraining the driving forces behind plate tectonics. Both these sources of buoyancies are important in generating the lithospheric stress field. However, these sources and the contribution that they make are dependent on a number of variables, such as the role of lateral strength variation in the lithosphere, the reference level for computing the gravitational potential energy per unit area (GPE) of the lithosphere, and even the definition of deviatoric stress. For the mantle contribution, much depends on the mantle convection model, including the role of lateral and radial viscosity variations, the spatial distribution of density buoyancies, and the resolution of the convection model. GPE differences are influenced by both lithosphere density buoyancies and by radial basal tractions that produce dynamic topography. The global lithospheric stress field can thus be divided into (1) stresses associated with GPE differences (including the contribution from radial basal tractions) and (2) stresses associated with the contribution of horizontal basal tractions. In this paper, we investigate only the contribution of GPE differences, both with and without the inferred contribution of radial basal tractions. We use the Crust 2.0 model to compute GPE values and show that these GPE differences are not sufficient alone to match all the directions and relative magnitudes of principal strain rate axes, as inferred from the comparison of our depth integrated deviatoric stress tensor field with the velocity gradient tensor field within the Earth\u27s plate boundary zones. We argue that GPE differences calibrate the absolute magnitudes of depth integrated deviatoric stresses within the lithosphere; shortcomings of this contribution in matching the stress indicators within the plate boundary zones can be corrected by considering the contribution from horizontal tractions associated with density buoyancy driven mantle convection. Deviatoric stress magnitudes arising from GPE differences are in the range of 1–4 TN m−1, a part of which is contributed by dynamic topography. The EGM96 geoid data set is also used as a rough proxy for GPE values in the lithosphere. However, GPE differences from the geoid fail to yield depth integrated deviatoric stresses that can provide a good match to the deformation indicators. GPE values inferred from the geoid have significant shortcomings when used on a global scale due to the role of dynamically support of topography. Another important factor in estimating the depth integrated deviatoric stresses is the use of the correct level of reference in calculating GPE. We also elucidate the importance of understanding the reference pressure for calculating deviatoric stress and show that overestimates of deviatoric stress may result from either simplified 2-D approximations of the thin sheet equations or the assumption that the mean stress is equal to the vertical stress

Gravitational potential energy of the Tibetan Plateau and the forces driving the Indian plate

ABSTRACT We present a study of the vertically integrated deviatoric stress field for the Indian plate and the Tibetan Plateau associated with gravitational potential energy (GPE) differences. Although the driving forces for the Indian plate have been attributed solely to the mid-oceanic ridges that surround the entire southern boundary of the plate, previous estimates of vertically integrated stress magnitudes of ϳ6-7 ؋ 10 12 N/m in Tibet far exceed those of ϳ3 ؋ 10 12 N/m associated with GPE at mid-oceanic ridges, calling for an additional force to satisfy the stress magnitudes in Tibet. We use the Crust 2.0 data set to infer gravitational potential energy differences in the lithosphere. We then apply the thin sheet approach in order to obtain a global solution of vertically integrated deviatoric stresses associated only with GPE differences. Our results show large N-S extensional deviatoric stresses in Tibet that the ridge-push force fails to cancel. Our results calibrate the magnitude of the basal tractions, associated with density buoyancy driven mantle flow, that are applied at the base of the lithosphere in order to drive India into Tibet and cancel the N-S extensional stresses within Tibet. Moreover, our deviatoric stress field solution indicates that both the ridge-push influence (ϳ1 ؋ 10 12 N/m) and the vertically integrated deviatoric stresses associated with GPE differences around the Tibetan Plateau (ϳ3 ؋ 10 12 N/m) have previously been overestimated by a factor of two or more. These overestimates have resulted from either simplified two-dimensional approximations of the thin sheet equations, or from an assumption about the mean stress that is unlikely to be correct