A High Resolution Chronology for Steward’s Promontory Culture Collections, Promontory Point, Utah

2014 ◽  
Vol 79 (4) ◽  
pp. 616-637 ◽  
Author(s):  
John W. Ives ◽  
Duane G. Froese ◽  
Joel C. Janetski ◽  
Fiona Brock ◽  
Christopher Bronk Ramsey

AbstractDespite the rich array of perishables Julian Steward (1937) recovered during his 1930s excavations, the Promontory Cave assemblages were dated in relative terms with just a handful of radiocarbon assays until recently. Yet Promontory Caves 1 and 2 are the type sites from which the Promontory Culture was defined, and these assemblages have a critical bearing on our conception of three significant issues in western North American prehistory: the terminal Fremont transition, Numic expansion, and the potential presence of migrating ancestral Apachean populations. To better fix the age of the Promontory Phase, we have undertaken an additional 45 AMS determinations for Promontory perishables. Because of a research focus concerning Promontory footwear, most age estimates come from moccasins, but we have also dated gaming pieces, a bow, an arrow, netting, basketry, matting, and cordage. With the exception of a winnowing basket fragment and some ceramic residue dates, all Promontory Phase assays are tightly focused in an interval running from 662 to 826 radiocarbon years before present (a calibrated 2s range spanning A.D. 1166–1391). Bayesian analyses of the Cave 1 and 2 Promontory Phase perishables suggest that this late period occupation comprised one or two human generations, centering on the interval running from ca. A.D. 1250–1290.

2021 ◽  
Vol 13 (22) ◽  
pp. 4528
Author(s):  
Xin Yang ◽  
Lei Hu ◽  
Yongmei Zhang ◽  
Yunqing Li

Remote sensing image change detection (CD) is an important task in remote sensing image analysis and is essential for an accurate understanding of changes in the Earth’s surface. The technology of deep learning (DL) is becoming increasingly popular in solving CD tasks for remote sensing images. Most existing CD methods based on DL tend to use ordinary convolutional blocks to extract and compare remote sensing image features, which cannot fully extract the rich features of high-resolution (HR) remote sensing images. In addition, most of the existing methods lack robustness to pseudochange information processing. To overcome the above problems, in this article, we propose a new method, namely MRA-SNet, for CD in remote sensing images. Utilizing the UNet network as the basic network, the method uses the Siamese network to extract the features of bitemporal images in the encoder separately and perform the difference connection to better generate difference maps. Meanwhile, we replace the ordinary convolution blocks with Multi-Res blocks to extract spatial and spectral features of different scales in remote sensing images. Residual connections are used to extract additional detailed features. To better highlight the change region features and suppress the irrelevant region features, we introduced the Attention Gates module before the skip connection between the encoder and the decoder. Experimental results on a public dataset of remote sensing image CD show that our proposed method outperforms other state-of-the-art (SOTA) CD methods in terms of evaluation metrics and performance.


2020 ◽  
Vol 1 ◽  
Author(s):  
Olivier Hamant

Abstract Like many scientific communities, plant science has moved to a new era with the rise of quantitative approaches. This is not merely about high-resolution quantification methods or the generation of massive datasets through omics; the quantitative revolution is much deeper because it unfolds the rich complexity behind plant life.


2019 ◽  
Vol 132 (4) ◽  
pp. 389-393
Author(s):  
Michael J. Oldham ◽  
William D. Van Hemessen ◽  
Sean Blaney

Round-fruited St. John’s-wort (Hypericum sphaerocarpum), a native North American herbaceous, perennial vascular plant, is reported from four sites in southern Ontario, Canada. All four sites are along abandoned railway lines. Although the rich association of native flora suggests native status at one site, H. sphaerocarpum is believed to be introduced elsewhere in its Canadian range in Ontario.


2015 ◽  
Vol 15 (12) ◽  
pp. 6801-6814 ◽  
Author(s):  
Z. Jiang ◽  
D. B. A. Jones ◽  
J. Worden ◽  
H. M. Worden ◽  
D. K. Henze ◽  
...  

Abstract. Chemical transport models (CTMs) driven with high-resolution meteorological fields can better resolve small-scale processes, such as frontal lifting or deep convection, and thus improve the simulation and emission estimates of tropospheric trace gases. In this work, we explore the use of the GEOS-Chem four-dimensional variational (4D-Var) data assimilation system with the nested high-resolution version of the model (0.5° × 0.67°) to quantify North American CO emissions during the period of June 2004–May 2005. With optimized lateral boundary conditions, regional inversion analyses can reduce the sensitivity of the CO source estimates to errors in long-range transport and in the distributions of the hydroxyl radical (OH), the main sink for CO. To further limit the potential impact of discrepancies in chemical aging of air in the free troposphere, associated with errors in OH, we use surface-level multispectral MOPITT (Measurement of Pollution in The Troposphere) CO retrievals, which have greater sensitivity to CO near the surface and reduced sensitivity in the free troposphere, compared to previous versions of the retrievals. We estimate that the annual total anthropogenic CO emission from the contiguous US 48 states was 97 Tg CO, a 14 % increase from the 85 Tg CO in the a priori. This increase is mainly due to enhanced emissions around the Great Lakes region and along the west coast, relative to the a priori. Sensitivity analyses using different OH fields and lateral boundary conditions suggest a possible error, associated with local North American OH distribution, in these emission estimates of 20 % during summer 2004, when the CO lifetime is short. This 20 % OH-related error is 50 % smaller than the OH-related error previously estimated for North American CO emissions using a global inversion analysis. We believe that reducing this OH-related error further will require integrating additional observations to provide a strong constraint on the CO distribution across the domain. Despite these limitations, our results show the potential advantages of combining high-resolution regional inversion analyses with global analyses to better quantify regional CO source estimates.


2014 ◽  
Vol 79 (4) ◽  
pp. 596-615 ◽  
Author(s):  
Loren G. Davis ◽  
Alex J. Nyers ◽  
Samuel C. Willis

AbstractThe discovery of an artifact cache containing Western Stemmed Tradition (WST) projectile points in a clearly defined pit feature at the Cooper’s Ferry site offers a unique perspective on early lithic technology and logistical organization in western North America. A description and analysis of the cache feature reveals several new insights, including: a rocky cairn capped the surface of the pit feature; some of the artifacts were made from cryptocrystalline silicates found 16 km away; debitage analysis, including aggregate and attribute based measures, identified two distinct lithic reduction stages present in the cache; new radiocarbon assays suggest that the cache is probably not early Holocene in age and may date to associated age estimates of 11,410–11,370 radiocarbon years before present (B.P.). Unlike Clovis caches, the Pit Feature A2 cache at Cooper’s Ferry appears to be a generalized toolkit that was probably placed at the site for future use. If the 11,410–11,370 radiocarbon years B.P. assays date the creation of the Pit Feature A2 cache, then its creators were probably not pioneers in the lower Salmon River canyon but possessed local knowledge about the landscape and raw material sources; these patterns suggest greater time depth for WST foragers.


2007 ◽  
Vol 41 (16) ◽  
pp. 5756-5762 ◽  
Author(s):  
Greg Yarwood ◽  
Susan Kemball-Cook ◽  
Michael Keinath ◽  
Robert L. Waterland ◽  
Stephen H. Korzeniowski ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document