A Unilateral Connate Incisor in a ca. 2,000 Year Old Mandible from the Middle Columbia River Plateau

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Seeing Themselves: Jean Barman’s French Canadians, Furs, and Indigenous Women in the Making of the Pacific Northwest as a Resource for the Region’s People

Dr. Barman’s award-winning study is a resource to the Indigenous and non-Indigenous people of the Columbia River Plateau and the Pacific Northwest, an environmentally and culturally diverse region that now encompasses two countries, two provinces, three states, and many Indigenous communities. For Indigenous communities of the region, French Canadians, Furs, and Indigenous Women in the Making of the Pacific Northwest provides an important context of colonialism, global economics, and the complicated nature of cross-cultural encounters. For non-Indigenous communities, the book also encourages an appreciation for the complexities of history often overlooked by celebratory histories of colonization. French Canadians, Furs, and Indigenous Women in the Making of the Pacific Northwest is a resource in which people see themselves and their families in a complicated, accessible, and inspiring story of the past.

Phase‐smoothed robust M-estimation of magnetotelluric impedance functions

Accurate estimation of impedance functions is essential for the correct interpretation of magnetotelluric (MT) measurements. Noise is inevitably encountered when MT observations are conducted and, consequently, impedance estimates are usually based on least‐squares (LS) regression. Least squares ultimately assumes simple Gaussian statistics. However, estimation procedures based on LS would not be statistically optimal, as outliers (abnormal data) are frequently superimposed on a normal ambient MT noise field which is approximately Gaussian. In this situation, the estimation can be seriously misleading. An alternative method for making unbiased robust estimates of MT impedance functions is based on regression M-estimation and the Hilbert Transform, operating on minimum‐phase MT impedance functions. In the resulting regression estimates, outlier contamination is removed and other departures from Gauss‐Markov optimality are not critical. Using MT data from the Columbia River Plateau and the EMSLAB Lincoln line, it is shown that the method can produce usable MT impedance functions even under conditions of severe noise contamination and in the absence of remote reference data.