Dataset Information

Glacial Steady State Topography Controlled by the Coupled Influence of Tectonics and Climate.

ABSTRACT: Glaciers and rivers are the main agents of mountain erosion. While in the fluvial realm empirical relationships and their mathematical description, such as the stream power law, improved the understanding of fundamental controls on landscape evolution, simple constraints on glacial topography and governing scaling relations are widely lacking. We present a steady state solution for longitudinal profiles along eroding glaciers in a coupled system that includes tectonics and climate. We combined the shallow ice approximation and a glacial erosion rule to calculate ice surface and bed topography from prescribed glacier mass balance gradient and rock uplift rate. Our approach is inspired by the classic application of the stream power law for describing a fluvial steady state but with the striking difference that, in the glacial realm, glacier mass balance is added as an altitude-dependent variable. From our analyses we find that ice surface slope and glacial relief scale with uplift rate with scaling exponents indicating that glacial relief is less sensitive to uplift rate than relief in most fluvial landscapes. Basic scaling relations controlled by either basal sliding or internal deformation follow a power law with the exponent depending on the exponents for the glacial erosion rule and Glen's flow law. In a mixed scenario of sliding and deformation, complicated scaling relations with variable exponents emerge. Furthermore, a cutoff in glacier mass balance or cold ice in high elevations can lead to substantially larger scaling exponents which may provide an explanation for high relief in high latitudes.

SUBMITTER: Prasicek G

PROVIDER: S-EPMC6055901 | biostudies-other | 2018 Jun

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Glacial Steady State Topography Controlled by the Coupled Influence of Tectonics and Climate.

Prasicek Günther G Herman Frédéric F Robl Jörg J Braun Jean J

Journal of geophysical research. Earth surface 20180619 6

Glaciers and rivers are the main agents of mountain erosion. While in the fluvial realm empirical relationships and their mathematical description, such as the stream power law, improved the understanding of fundamental controls on landscape evolution, simple constraints on glacial topography and governing scaling relations are widely lacking. We present a steady state solution for longitudinal profiles along eroding glaciers in a coupled system that includes tectonics and climate. We combined t ...[more]

PMID: 30069424

Similar Datasets

Project description:BackgroundA number of biotic and abiotic factors have been proposed as drivers of geographic variation in species richness. As biotic elements, inter-specific interactions are the most widely recognized. Among abiotic factors, in particular for plants, climate and topographic variables as well as their historical variation have been correlated with species richness and endemism. In this study, we determine the extent to which the species richness and endemism of monocot geophyte species in Mesoamerica is predicted by current climate, historical climate stability and topography.MethodsUsing approximately 2,650 occurrence points representing 507 geophyte taxa, species richness (SR) and weighted endemism (WE) were estimated at a geographic scale using grids of 0.5 × 0.5 decimal degrees resolution using Mexico as the geographic extent. SR and WE were also estimated using species distributions inferred from ecological niche modeling for species with at least five spatially unique occurrence points. Current climate, current to Last Glacial Maximum temperature, precipitation stability and topographic features were used as predictor variables on multiple spatial regression analyses (i.e., spatial autoregressive models, SAR) using the estimates of SR and WE as response variables. The standardized coefficients of the predictor variables that were significant in the regression models were utilized to understand the observed patterns of species richness and endemism.ResultsOur estimates of SR and WE based on direct occurrence data and distribution modeling generally yielded similar results, though estimates based on ecological niche modeling indicated broader distribution areas for SR and WE than when species richness was directly estimated using georeferenced coordinates. The SR and WE of monocot geophytes were highest along the Trans-Mexican Volcanic Belt, in both cases with higher levels in the central area of this mountain chain. Richness and endemism were also elevated in the southern regions of the Sierra Madre Oriental and Occidental mountain ranges, and in the Tehuacán Valley. Some areas of the Sierra Madre del Sur and Sierra Madre Oriental had high levels of WE, though they are not the areas with the highest SR. The spatial regressions suggest that SR is mostly influenced by current climate, whereas endemism is mainly affected by topography and precipitation stability.ConclusionsBoth methods (direct occurrence data and ecological niche modeling) used to estimate SR and WE in this study yielded similar results and detected a key area that should be considered in plant conservation strategies: the central region of the Trans-Mexican Volcanic Belt. Our results also corroborated that species richness is more closely correlated with current climate factors while endemism is related to differences in topography and to changes in precipitation levels compared to the LGM climatic conditions.

Project description:ObjectiveTo identify genetic variants that influence steady-state etonogestrel concentrations among contraceptive implant users.MethodsWe enrolled healthy, reproductive-age women in our pharmacogenomic study using etonogestrel implants for 12-36 months without concomitant use of hepatic enzyme inducers or inhibitors. We collected participant characteristics, measured serum etonogestrel concentrations, and genotyped each participant for 120 single nucleotide variants in 14 genes encoding proteins involved in steroid hormone (ie, estrogens, progestins) metabolism, regulation, or function. We performed generalized linear modeling to identify genetic variants associated with steady-state etonogestrel concentrations.ResultsWe enrolled 350 women, who had a median serum etonogestrel concentration of 137.4 pg/mL (range 55.8-695.1). Our final generalized linear model contained three genetic variants associated with serum etonogestrel concentrations: NR1I2(PXR) rs2461817 (β=13.36, P=.005), PGR rs537681 (β=-29.77, P=.007), and CYP3A7*1C (β=-35.06, P=.025). Variant allele frequencies were 69.4%, 84.9%, and 5.1%, respectively. Our linear model also contained two nongenetic factors associated with etonogestrel concentrations: body mass index (BMI) (β=-3.08, P=7.0×10) and duration of implant use (β=-1.60, P=5.8×10); R for the model =0.17.ConclusionOnly BMI and duration of implant use remained significantly associated with steady-state etonogestrel concentrations. Of the three novel genetic associations found, one variant associated with increased etonogestrel metabolism (CYP3A7*1C) causes adult expression of fetal CYP3A7 proteins and can consequently alter steroid hormone metabolism. Women with this variant may potentially have increased metabolism of all steroid hormones, as 27.8% (5/18) of CYP3A7*1C carriers had serum etonogestrel concentrations that fell below the threshold for consistent ovulatory suppression (less than 90 pg/mL). More pharmacogenomic investigations are needed to advance our understanding of how genetic variation can influence the effectiveness and safety of hormonal contraception, and lay the groundwork for personalized medicine approaches in women's health.Clinical trial registrationClinicalTrials.gov, NCT03092037.

Dataset Information

Glacial Steady State Topography Controlled by the Coupled Influence of Tectonics and Climate.

Publications

Glacial Steady State Topography Controlled by the Coupled Influence of Tectonics and Climate.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets