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Catherine V. Davis

Publications and source records attributed to Catherine V. Davis.

2 recordsLinked to original sources

Sea surface temperature across the Subarctic North Pacific and marginal seas through the past 20,000 years: A paleoceanographic synthesis

Deglacial sea surface conditions in the subarctic North Pacific and marginal seas are the subject of increasing interest in paleoceanography. However, a cohesive picture of near-surface oceanography from which to compare inter and intra-regional variability through the last deglaciation is lacking. We present a synthesis of sea surface temperature covering the open North Pacific and its marginal seas, spanning the past 20 ka using proxy records from foraminiferal calcite (δ 18 O and Mg/Ca) and coccolithophore alkenones (U k’ 37 ). Sea surface temperature proxies tend to be in agreement through the Holocene, though U k’ 37 records are often interpreted as warmer than adjacent δ 18 O or Mg/Ca records during the Last Glacial Maximum and early deglaciation. In the Sea of Okhotsk, Holocene discrepancies between δ 18 O and U k’ 37 may be the result of changes in near-surface stratification. We find that sea-surface warming occurred prior to the onset of the Bølling-Allerød (14.7 ka) and coincident with the onset of the Holocene (11.7 ka) in much of the North Pacific and Bering Sea. Proxy records also show a cold reversal roughly synchronous with the Younger Dryas (12.9–11.7 ka). After the onset of the Holocene, the influence of an intensified warm Kuroshio Current is evident at higher latitudes in the Western Pacific, and an east-west seesaw in sea surface temperature, likely driven by changes in the strength of the North Pacific Gyre, characterizes the open interglacial North Pacific.

Quaternary Science Research

Endless forams: >34,000 modern planktonic foraminiferal images for taxonomic training and automated species recognition using convolutional neural networks

Accurate planktonic foraminiferal species identification is central to many paleoceanographic studies, from selecting specific species for geochemical research to elucidating the biotic dynamics of microfossil communities relevant to physical oceanographic processes and interconnected phenomena such as climate change. However, species identification varies among taxonomic schools, few resources exist to train students in the difficult task of discerning amongst closely related species, and the number of taxonomic experts is limited. Here, we take the first steps towards removing these rate-limiting steps by generating the first extensive image library of modern planktonic foraminifera, providing taxonomic training tools and resources, and automating species-level taxonomic identification of planktonic foraminifera via machine learning using convolution neural networks. Taxonomic experts identified 34,640 images of modern planktonic foraminifera to the species level. These images are served as species exemplars through the online portal Endless Forams (endlessforams.org) and a taxonomic training portal hosted on the citizen science platform Zooniverse (zooniverse.org/projects/ahsiang/endless-forams/). A supervised machine learning classifier was then trained with more than 24,000 images of planktonic foraminifera and tested using the remaining ~10,000 images (i.e., the validation set). The best classifier provided the correct species name for an image in the validation set 87.4% of the time. Together, these resources provide a rigorous set of training tools in modern planktonic foraminiferal taxonomy and a means of rapidly generating assemblage data via machine learning in future studies.

Paleoceanography and Paleoclimatology