Azimuthal anisotropy is a powerful tool to reveal information about both the present structure and past evolution of the mantle. Anisotropic images of the upper mantle are usually obtained by analysing various types of seismic observables, such as surface wave dispersion curves or waveforms, SKS splitting data, or receiver functions. These different data types sample different volumes of the earth, they are sensitive to different length scales, and hence are associated with different levels of uncertainties. They are traditionally interpreted separately, and often result in incompatible models. We present a Bayesian inversion approach to jointly invert these different data types. Seismograms for SKS and P phases are directly inverted using a cross-convolution approach, thus avoiding intermediate processing steps, such as numerical deconvolution or computation of splitting parameters. Probabilistic 1-D profiles are obtained with a transdimensional Markov chain Monte Carlo scheme, in which the number of layers, as well as the presence or absence of anisotropy in each layer, are treated as unknown parameters. In this way, seismic anisotropy is only introduced if required by the data. The algorithm is used to resolve both isotropic and anisotropic layering down to a depth of 350 km beneath two seismic stations in North America in two different tectonic settings: the stable Canadian shield (station FFC) and the tectonically active southern Basin and Range Province (station TA-214A). In both cases, the lithosphere-asthenosphere boundary is clearly visible, and marked by a change in direction of the fast axis of anisotropy. Our study confirms that azimuthal anisotropy is a powerful tool for detecting layering in the upper mantle.
Artisanal and small-scale mining is a significant and growing livelihood across the global South, which all too often leaves a legacy of contaminated landscapes. Given the increasing reliance of economies on metals and minerals, it is critical to understand what controls contamination outcomes in this rapidly developing extractive practice. Here, we demonstrate that the emerging concept of co-production offers a novel way to elucidate the joint contributions of natural and societal factors in shaping contaminant exposure from artisanal and small-scale mining. Specifically, understanding the co-production of contaminated landscapes requires attention to both the political economy of mining, including how labor and extraction methods differ across mines, as well as the sources and pathways of mercury exposure. In Madre de Dios, Peru, we measured mercury levels in wildlife inhabiting abandoned gold mining sites worked with different extraction technologies. We found that the type of technology used, whether heavy machinery or suction-pump based, influenced mercury loading into mines, and together with differences in food-web structure, mediated mercury biomagnification rates. Mercury concentration increased 2.1 to 3.7-fold per trophic level, and bioaccumulation levels were high in both mined and unmined sites—indicating elevated background levels in the region. We also found evidence of lateral transfer of mercury from abandoned mining pits to terrestrial food webs. This observation indicates that the footprint of mercury contamination extends well beyond individual mines, affecting the larger landscape. Our findings underscore the necessity of understanding the entangled ways in which social and ecological factors contribute to the production of toxic landscapes.
Rapidly increasing mining in rivers across the global tropics has major, interrelated consequences for ecosystems and human health. River mining involves intensive excavation and sediment processing in river corridors, altering river form and releasing excess sediment to river waters. Contaminants such as mercury and cyanide are used in some operations and are also released to the environment. Although river mining has been investigated at local and regional scales, no global synthesis of its physical footprint and impacts on hydrologic systems exists, so its full environmental consequences are not known. We assemble and analyze a 37 yr satellite database showing that river mining is pervasive globally. We identify 381 mining districts in 49 countries, concentrated in tropical waterways that are almost universally degraded. Of 173 mining-affected rivers, 80% have suspended sediment concentrations double pre-mining levels. In countries where mining affects large (>50 m wide) rivers, 23 ± 19% of large river length is altered by mining-derived sediment, a globe-spanning effect representing 5–7% of all large tropical river reaches. Mining intensity has rapidly increased during 21st-century global financial insecurity and rising demand for precious minerals. The ubiquity and intensity of mining degradation in tropical river systems is a global crisis.
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