Subsurface weathering has traditionally been measured using cores and boreholes to quantify vertical variations in weathered material properties. However, these measurements are typically available at only a few, potentially unrepresentative points on hillslopes. Geophysical surveys, conversely, span many more points and, as shown here, can be used to obtain a representative, site‐integrated perspective on subsurface weathering. Our approach aggregates data from multiple seismic refraction surveys into a single frequency distribution of porosity and depth for the surveyed area. We calibrated the porosities at a site where cores are coincident with seismic refraction surveys. Modeled porosities from the survey data match measurements at the core locations but reveal a frequency distribution of porosity and depth that differs markedly from the cores. Our results highlight the value of using the site‐integrated perspective obtained from the geophysical data to quantify subsurface weathering and water‐holding capacity.
The Kinkajou Potos flavus (Carnivora: Procyonidae) is a nocturnal, arboreal species that feeds opportunistically, mostly on fruits and insects. The implications for the management of these aspects of the ecology of P. flavus in captivity have received little attention in the literature. Captive Kinkajous often show stereotypic behaviour, indicating sub‐optimal welfare and probably reflecting insufficient opportunity to display important aspects of natural behaviour. This study assessed the individual and additive effects of complex feeders and scented cloths as enrichment for a pair of Kinkajous at Newquay Zoo. Feeding enrichment, alone and in combination with scented cloths, elicited most positive active behaviours and space utilization, and least stereotypic and inactive behaviours. Food provision requiring species‐typical exploration and manipulation may improve the welfare and educational value of Kinkajous.
Seismic interferometry is a technique for extracting deterministic signals (i.e., ambient-noise Green's functions) from recordings of ambient-noise wavefields through cross-correlation and other related signal processing techniques. The extracted ambient-noise Green's functions can be used in ambient-noise tomography for constructing seismic structure models of the Earth's interior. The amount of calculations involved in the seismic interferometry procedure can be significant, especially for ambient-noise datasets collected by large seismic sensor arrays (i.e., "large-N" data). We present an efficient parallel algorithm, named pSIN (Parallel Seismic INterferometry), for solving seismic interferometry problems on conventional distributedmemory computer clusters. The design of the algorithm is based on a two-dimensional partition of the ambient-noise data recorded by a seismic sensor array. We pay special attention to the balance of the computational load, inter-process communication overhead and memory usage across all MPI processes and we minimize the total number of I/O operations. We have tested the algorithm using a real ambient-noise dataset and obtained a significant amount of savings in processing time. Scaling tests have shown excellent strong scalability from 80 cores to over 2000 cores.
Multiply By To obtain foot (ft) 0.3048 meter (m) mile (mi) 1.609 kilometer (km) Datum Vertical coordinate information is referenced to the North American Vertical Datum of 1988 (NAVD 88). Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83) within the various State plane coordinate systems. Elevation, as used in this report, refers to the orthometric height, defined as a distance along a plumb line, from any objective point to the reference height of the vertical datum.
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