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Results for “International Statistical Review”

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USGS2023

Quantification of geodetic strain rate uncertainties and implications for seismic hazard estimates

Geodetic velocity data provide first-order constraints on crustal surface strain rates, which in turn are linked to seismic hazard. Estimating the 2-D surface strain tensor everywhere requires knowledge of the surface velocity field everywhere, while geodetic data such as Global Navigation Satellite System (GNSS) only have spatially scattered measurements on the surface of the Earth. To use these data to estimate strain rates, some type of interpolation is required. In this study, we review methodologies for strain rate estimation and compare a suite of methods, including a new implementation based on the geostatistical method of kriging, to compare variation between methods with uncertainty based on one method. We estimate the velocity field and calculate strain rates in southern California using a GNSS velocity field and five different interpolation methods to understand the sources of variability in inferred strain rates. Uncertainty related to data noise and station spacing (aleatoric uncertainty) is minimal where station spacing is dense and maximum far from observations. Differences between methods, related to epistemic uncertainty, are usually highest in areas of high strain rate due to differences in how gradients in the velocity field are handled by different interpolation methods. Parameter choices, unsurprisingly, have a strong influence on strain rate field, and we propose the traditional L -curve approach as one method for quantifying the inherent trade-off between fit to the data and models that are reflective of tectonic strain rates. Doing so, we find total variability between five representative strain rate models to be roughly 40 per cent, a much lower value than roughly 100 per cent that was found in previous studies (Hearn et al .). Using multiple methods to tune parameters and calculate strain rates provides a better understanding of the range of acceptable models for a given velocity field. Finally, we present an open-source Python package (Materna et al .) for calculating strain rates, Strain_2D, which allows for the same data and model grid to be used in multiple strain rate methods, can be extended with other methods from the community, and provides an interface for comparing strain rate models, calculating statistics and estimating strain rate uncertainty for a given GNSS data set.

Geophysical Journal International↗

USGS2015

Critical metals in manganese nodules from the Cook Islands EEZ, abundances and distributions

The Cook Islands (CIs) Exclusive Economic Zone (EEZ) encompasses 1,977,000 km 2 and includes the Penrhyn and Samoa basins abyssal plains where manganese nodules flourish due to the availability of prolific nucleus material, slow sedimentation rates, and strong bottom currents. A group of CIs nodules was analyzed for mineralogical and chemical composition, which include many critical metals not before analyzed for CIs nodules. These nodules have varying sizes and nuclei material; however all are composed predominantly of δ-MnO 2 and X-ray amorphous iron oxyhydroxide. The mineralogy, Fe/Mn ratios, rare earth element contents, and slow growth rates (mean 1.9 mm/10 6 years) reflect formation primarily by hydrogenetic precipitation. The paucity of diagenetic input can be explained by low primary productivity at the surface and resultant low organic matter content in seafloor sediment, producing oxic seafloor and sub-seafloor environments. The nodules contain high mean contents of Co (0.41%), Ni (0.38%), Ti (1.20%), and total rare earth elements plus yttrium (REY; 0.167%), and also high contents of Mo, Nb, V, W, and Zr. Compiled data from a series of four cruises by the Japan International Cooperation Agency and the Mining agency of Japan from 1985 to 2000 were used to generate a map that defines the statistical distribution of nodule abundance throughout the EEZ, except the Manihiki Plateau. The abundance distribution map shows a belt of high nodule abundance (19–45 kg/m 2 ) that starts in the southeast corner of the EEZ, runs northwest, and also bifurcates into a SW trending branch. Small, isolated areas contain abundances of nodules of up to 58 kg/m 2 . Six ~ 20,000 km 2 areas of particularly high abundance were chosen to represent potential exploration areas, and maps for metal concentration were generated to visualize metal distribution and to extrapolate estimated metal tonnages within the six sites and the EEZ as a whole. Grades for Mn, Cu, and Ni are low in CIs nodules in areas of high abundance; however, Ti, Co, and REY show high contents where nodule abundances are high. Of the six areas identified to represent a range of metal contents, one at the northern end of the N-S abundance main belt optimizes the most metals and would yield the highest dry metric tons for Mn (61,002,292), Ni (1,247,834), Mo (186,166), V (356,247), W (30,215), and Zr (195,323). When compared with the Clarion–Clipperton Zone, the CIs nodules show higher nodule abundances (> 25 kg/m 2 over ~ 123,844 km 2 ), and are more enriched in the green-tech, high-tech, and energy metals Co, Ti, Te, Nb, REY, Pt, and Zr. The CIs EEZ shows a significant resource potential for these critical metals due to their high prices, high demand, and the high nodule abundance, which will allow for a smaller footprint for a 20-year mine site and therefore smaller environmental impact.

Ore Geology Reviews↗

USGS2021

Characterization of historical and stochastically generated climate and streamflow conditions in the Souris River Basin, United States and Canada

The Souris River Basin is a 61,000-square-kilometer basin in the Provinces of Saskatchewan and Manitoba in Canada and the State of North Dakota in the United States. Greater than average snowpack during the winter of 2010–11, along with record-setting rains in May and June 2011, resulted in historically unprecedented flooding in the Souris River Basin. The severity of the 2011 flood led the United States and Canada to request a review of the operating plan for any improvements of reservoir operations and flood control measures in the basin, and the Souris River Basin Task Force was formed. The International Souris River Study Board was then formed in 2017 to carry out the recommendations of the Souris River Basin Task Force laid out in a plan of study. To support the International Souris River Study Board, the U.S. Geological Survey (USGS), in cooperation with the North Dakota State Water Commission and the International Joint Commission, used the previously developed unregulated and regulated streamflow models and data for stochastic streamflow in the Souris River Basin to characterize climate and streamflow and support selection of streamflow traces based on their characterization. Components of the original stochastic hydrology models and their outputs were used in this phase of the study to (1) characterize historical and stochastic climate and streamflow for the Souris River Basin, (2) disaggregate monthly stochastic streamflow spatially and temporally to meet the needs of the U.S. Army Corps of Engineers, Hydrologic Engineering Center, Reservoir System Simulation model for the Souris River Basin, and (3) discuss selection of disaggregated streamflow traces (simulations) using the characteristics of climate and streamflow. A trace is a time series of a stochastic variable such as streamflow, potential evapotranspiration, or precipitation. To characterize climate conditions, precipitation, potential evapotranspiration (PET), and moisture deficit for the Souris River Basin and individual points at Rafferty, Grant Devine, and Lake Darling Reservoirs were determined annually and seasonally. The annual basin (November 1–October 31) precipitation for the 50-percent nonexceedance probability is 452 millimeters (mm). Spring (March–May) is the wettest season, followed by summer (June–August), fall (September–November), and winter (December–February). Annual moisture deficit was largest at Lake Darling Reservoir, followed by Rafferty Reservoir, and then Grant Devine Reservoir. Annual maximum monthly mean streamflow was determined for the Souris River below Rafferty Reservoir, Saskatchewan (Canadian streamgage 05NB036); Long Creek near Noonan (above Boundary Reservoir), North Dakota (USGS streamgage 05113600); Moose Mountain Creek near Oxbow, Saskatchewan (Canadian streamgage 05ND004); the Souris River near Sherwood, N. Dak. (USGS streamgage 05114000); the Des Lacs River at Foxholm, N. Dak. (USGS streamgage 05116500); and the Souris River above Minot, N. Dak. (USGS streamgage 05117500). When the seasonal maximum monthly mean streamflows are evaluated in contrast to annual maximum monthly mean streamflows separated by their seasonal occurrence, summer months of annual maximum monthly mean streamflows have a higher 50-percent exceedance probability of streamflow compared to annual maximum monthly mean streamflows that occur in spring, seasonal maximum monthly mean streamflows that occur in spring, and seasonal maximum monthly mean streamflows that occur in summer. When annual maximum monthly mean streamflows in summer are compared to annual maximum monthly mean streamflows in spring, they are consistently higher in streamflow but occur in less than 4.2 percent of years. Evaluation of whether the annual maximum monthly mean streamflows that occur in summer can be described as a separate population from annual maximum monthly mean streamflows that occur in spring was outside the scope of this study, and the summer and spring annual maximum monthly mean streamflows were not tested for statistical differences in mean or variance. Further investigation of seasonal weather patterns that induce flooding could lead to a better understanding of the seasonal differences in flooding. Long-term hydrologic drought was characterized by evaluating multiyear mean streamflow. Shorter averaging periods have greater streamflow variability than longer periods and hence have a wider range of values. As the averaging period is extended to a longer period, the variability of mean streamflow decreases, and the more extreme streamflow volumes seen in shorter averaging periods cannot be sustained. Stochastic streamflow time series were disaggregated spatially and temporally for use in a HEC–ResSim model. The combination of monthly and daily stochastic streamflow data was used to select traces with qualities that could be used to test alternatives focused on water supply, summer flooding, and apportionment.

Manitoba, North Dakota, Saskatchewan↗

USGS2022

Quantitative meta-analysis reveals no association between mercury contamination and body condition in birds

Mercury contamination is a major threat to the global environment, and is still increasing in some regions despite international regulations. The methylated form of mercury is hazardous to biota, yet its sublethal effects are difficult to detect in wildlife. Body condition can vary in response to stressors, but previous studies have shown mixed effects of mercury on body condition in wildlife. Using birds as study organisms, we provide the first quantitative synthesis of the effect of mercury on body condition in animals. In addition, we explored the influence of intrinsic, extrinsic and methodological factors potentially explaining cross-study heterogeneity in results. We considered experimental and correlative studies carried out in adult birds and chicks, and mercury exposure inferred from blood and feathers. Most experimental investigations (90%) showed a significant relationship between mercury concentrations and body condition. Experimental exposure to mercury disrupted nutrient (fat) metabolism, metabolic rates, and food intake, resulting in either positive or negative associations with body condition. Correlative studies also showed either positive or negative associations, of which only 14% were statistically significant. Therefore, the overall effect of mercury concentrations on body condition was null in both experimental (estimate ± SE = 0.262 ± 0.309, 20 effect sizes, five species) and correlative studies (−0.011 ± 0.020, 315 effect sizes, 145 species). The single and interactive effects of age class and tissue type were accounted for in meta-analytic models of the correlative data set, since chicks and adults, as well as blood and feathers, are known to behave differently in terms of mercury accumulation and health effects. Of the 15 moderators tested, only wintering status explained cross-study heterogeneity in the correlative data set: free-ranging wintering birds were more likely to show a negative association between mercury and body condition. However, wintering effect sizes were limited to passerines, further studies should thus confirm this trend in other taxa. Collectively, our results suggest that ( i ) effects of mercury on body condition are weak and mostly detectable under controlled conditions, and ( ii ) body condition indices are unreliable indicators of mercury sublethal effects in the wild. Food availability, feeding rates and other sources of variation that are challenging to quantify likely confound the association between mercury and body condition in natura . Future studies could explore the metabolic effects of mercury further using designs that allow for the estimation and/or manipulation of food intake in both wild and captive birds, especially in under-represented life-history stages such as migration and overwintering.

Biological Reviews↗