scholarly journals Depositional patterns constrained by slope topography changes on seamounts

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Dewen Du ◽  
Shijuan Yan ◽  
Gang Yang ◽  
Fengdeng Shi ◽  
Zhiwei Zhu ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Drill Core ◽  
Core Samples ◽  
Depositional Patterns ◽  
Slope Topography ◽  
Depositional Units ◽  
Analyse Data ◽  
Over Time

AbstractSlope topography is known to control the spatial distribution of deposits on intraplate seamounts; however, relatively little is known about how slope topography changes constrain those depositional patterns. In this study, we analyse data on four lithotypes found on seamount slopes, including colloidal chemical deposits comprising mainly cobalt-rich crusts, and examine the relationships between the spatial distribution of these lithotypes and current slope topography. We use these relationships to discuss depositional patterns constrained by slope topography changes. Some depositional units in drill core samples are interpreted to have resulted from past topographic changes that created the current slope topography. Two or more types of deposits that accumulated at the same location implies that the slope topography changed over time and that the depositional patterns on seamount slopes are constrained by changes in slope topography.

SPATIAL DISTRIBUTION AND MORPHOMETRIC ANALYSIS OF DOLINES OVER TIME IN A WASTEWATER SPRAY IRRIGATED LANDSCAPE

2017 ◽  
Author(s):  
Timothy J. Daniel ◽  
◽  
John Richendrfer ◽  
Henry Lin ◽  
Heather Gall ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Morphometric Analysis ◽  
Over Time

scholarly journals Host density predicts the probability of parasitism by avian brood parasites

2019 ◽  
Vol 374 (1769) ◽  
pp. 20180204 ◽  
Author(s):  
Iliana Medina ◽  
Naomi E. Langmore
Keyword(s):  
Spatial Distribution ◽  
Reproductive Success ◽  
Host Species ◽  
Field Data ◽  
Host Density ◽  
Brood Parasites ◽  
Parasitism Rates ◽  
Analyse Data ◽  
First Time ◽  
Determining Factor

The spatial distribution of hosts can be a determining factor in the reproductive success of parasites. Highly aggregated hosts may offer more opportunities for reproduction but can have better defences than isolated hosts. Here we connect macro- and micro-evolutionary processes to understand the link between host density and parasitism, using avian brood parasites as a model system. We analyse data across more than 200 host species using phylogenetic comparative analyses and quantify parasitism rate and host reproductive success in relation to spatial distribution using field data collected on one host species over 6 years. Our comparative analysis reveals that hosts occurring at intermediate densities are more likely to be parasitized than colonial or widely dispersed hosts. Correspondingly, our intraspecific field data show that individuals living at moderate densities experience higher parasitism rates than individuals at either low or high densities. Moreover, we show for the first time that the effect of host density on host reproductive success varies according to the intensity of parasitism; hosts have greater reproductive success when living at high densities if parasitism rates are high, but fare better at low densities when parasitism rates are low. We provide the first evidence of the trade-off between host density and parasitism at both macro- and micro-evolutionary scales in brood parasites. This article is part of the theme issue ‘The coevolutionary biology of brood parasitism: from mechanism to pattern’.

scholarly journals Drill-Core Mineral Abundance Estimation Using Hyperspectral and High-Resolution Mineralogical Data

2020 ◽  
Vol 12 (7) ◽  
pp. 1218
Author(s):  
Laura Tuşa ◽  
Mahdi Khodadadzadeh ◽  
Cecilia Contreras ◽  
Kasra Rafiezadeh Shahi ◽  
Margret Fuchs ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Resolution ◽  
Ore Deposits ◽  
Machine Learning Algorithms ◽  
Training Data ◽  
Support Vector ◽  
Drill Core ◽  
Data Types ◽  
Mineralogical Characterization ◽  
Core Samples

Due to the extensive drilling performed every year in exploration campaigns for the discovery and evaluation of ore deposits, drill-core mapping is becoming an essential step. While valuable mineralogical information is extracted during core logging by on-site geologists, the process is time consuming and dependent on the observer and individual background. Hyperspectral short-wave infrared (SWIR) data is used in the mining industry as a tool to complement traditional logging techniques and to provide a rapid and non-invasive analytical method for mineralogical characterization. Additionally, Scanning Electron Microscopy-based image analyses using a Mineral Liberation Analyser (SEM-MLA) provide exhaustive high-resolution mineralogical maps, but can only be performed on small areas of the drill-cores. We propose to use machine learning algorithms to combine the two data types and upscale the quantitative SEM-MLA mineralogical data to drill-core scale. This way, quasi-quantitative maps over entire drill-core samples are obtained. Our upscaling approach increases result transparency and reproducibility by employing physical-based data acquisition (hyperspectral imaging) combined with mathematical models (machine learning). The procedure is tested on 5 drill-core samples with varying training data using random forests, support vector machines and neural network regression models. The obtained mineral abundance maps are further used for the extraction of mineralogical parameters such as mineral association.

The magnetization of oceanic crust: contribution to knowledge from the Troodos, Cyprus, ophiolite

1991 ◽  
Vol 28 (11) ◽  
pp. 1812-1826 ◽  
Author(s):  
James M. Hall ◽  
Charles C. Walls ◽  
Jing-Sui Yang ◽  
S. Lata Hall ◽  
Abdul Razzak Bakor
Keyword(s):  
Lower Limit ◽  
Oceanic Crust ◽  
Drill Hole ◽  
Extensive Study ◽  
Drill Core ◽  
Average Depth ◽  
Ocean Drilling Program ◽  
Ocean Drilling ◽  
Core Samples ◽  
Key Questions

An extensive study of a segment of the Troodos, Cyprus, ophiolite using both outcrop and drill-core samples, and extending from the sediment–extrusive interface through sheeted dikes to cumulate ultramafics, has allowed a number of key questions regarding the magnetization of oceanic crust to be addressed. These include the number of strongly magnetized intervals with depth, their lateral variability and controls on their occurrence. Comparison has also been made with the section in Ocean Drilling Program (ODP) hole 504B, and a reinterpretation of its constructional setting is offered.Two strongly magnetized intervals occur in the area studied. The upper is in the extrusive sequence, extends on average from 0.2 to 0.6 km depth, and has a thickness of ~0.4 km. Here magnetization is dominated by remanence. The lower interval extends from the lowest level at which flows occur with dikes (average depth = 0.9 km) into the Sheeted Complex (average depth = 1.2 km) and has a thickness of 0.3 km. Here magnetization is dominantly induced. No other strongly magnetized intervals occur in the section. The extent of dike intrusion is closely related to the position of the lower limit of the high-remanence layer and to the occurrence of the high induced magnetization layer. In both cases the replacement of primary magnetite, which can carry a strong remanence, by magnetically soft secondary magnetite appears to be the controlling process.Comparison of the Troodos and hole 504B magnetization profiles shows close similarity in the upper, remanence-dominated magnetic interval. The absence of the deeper interval of high induced magnetization in the hole 504B profile is interpreted as meaning that sheeted dikes have not been penetrated by the drill hole.

scholarly journals Modern weathering in outcrop samples versus ancient paleoredox information in drill core samples from a Mesoarchaean marine oxygen oasis in Pongola Supergroup, South Africa

2019 ◽  
Vol 265 ◽  
pp. 330-353 ◽  
Author(s):  
Gülüm Albut ◽  
Balz S. Kamber ◽  
Annika Brüske ◽  
Nicolas J. Beukes ◽  
Albertus J.B. Smith ◽  
...  
Keyword(s):  
South Africa ◽  
Drill Core ◽  
Core Samples
Sign in / Sign up

Export Citation Format

Share Document