Mesoscale and microscale shock effects in the LL6 S4 chondrites Saint‐Séverin and Elbert: A tale of two breccias

Saint‐Séverin and Elbert, two LL6 chondrite breccias, were systematically studied to evaluate multiple deformation effects on spatial scales ranging from thin section (mesoscale) to micron‐submicron (microscale) using optical microscopy, electron backscatter diffraction (EBSD), and transmission electron microscopy (TEM). The different techniques provide consistent results but have complementary strengths, together providing a powerful approach to unravel even complex impact histories. Both meteorites have an S4 conventional shock stage, but interclast areas are more deformed, and clasts are more deformed in Elbert than in Saint‐Séverin. TEM and EBSD data provide compelling evidence that Saint‐Séverin experienced significant shock deformation while already hot, and cooled rapidly afterward, as a result of a major, possibly disruptive impact on the LL chondrite parent body ~4.4 Ga ago. In contrast, Elbert was shocked from a cold initial state but was heated significantly during shock, and cooled in a localized hot impact deposit on the LL asteroid. Both meteorites probably were shocked at least twice; data for Saint‐Séverin are best reconciled with a three‐impact model.     

Exploring Spatially Non-stationary Relationships in the Determinants of Mineralization in 3D Geological Space

Exploring the spatial relationships between various geological features and mineralization is not only conducive to understanding the genesis of ore deposits but can also help to guide mineral exploration by providing predictive mineral maps. However, most current methods assume spatially constant determinants of mineralization and therefore have limited applicability to detecting possible spatially non-stationary relationships between the geological features and the mineralization. In this paper, the spatial variation between the distribution of mineralization and its determining factors is described for a case study in the Dingjiashan Pb–Zn deposit, China. A local regression modeling technique, geological weighted regression (GWR), was leveraged to study the spatial non-stationarity in the 3D geological space. First, ordinary least-squares (OLS) regression was applied, the redundancy and significance of the controlling factors were tested, and the spatial dependency in Zn and Pb ore grade measurements was confirmed. Second, GWR models with different kernel functions in 3D space were applied, and their results were compared to the OLS model. The results show a superior performance of GWR compared with OLS and a significant spatial non-stationarity in the determinants of ore grade. Third, a non-stationarity test was performed. The stationarity index and the Monte Carlo stationarity test demonstrate the non-stationarity of all the variables throughout the area. Finally, the influences of the degree of non-stationary of all controlling factors on mineralization are discussed. The existence of significant non-stationarity of mineral ore determinants in 3D space opens up an exciting avenue for research into the prediction of underground ore bodies.

     

Organic Carbon in the Surface Sediments from the Intensive Mariculture Zone of Sanggou Bay: Distribution,Seasonal Variations and Sources

Mariculture has rapidly grown worldwide, which might greatly influence the biogeochemical cycle of organic carbon in coastal seas. In this study, several geochemical parameters, including grain size composition, sedimentary total organic carbon(TOC), total nitrogen(TN), stable carbon(δ13 C) and nitrogen(δ15 N) isotopic compositions, were analyzed for surface sediments collected from different mariculture zones of Sanggou Bay and in different seasons. We investigated the composition and distribution of organic matter in surface sediments and further evaluated the contribution of mariculture activities to TOC sources. The TOC and TN contents(mass percentage) in the bay were in the range of 0.14% to 1.45% and 0.03% to 0.20%, respectively. The spatial distribution indicated that sedimentary TOC and TN contents in shellfish monoculture and shellfish-kelp polyculture zones were higher than in other mariculture zones, which might be related to grain size composition and mariculture organisms. Seasonal variations of TOC contents were observed in different mariculture zones. The TOC/TN atomic ratio(C/N), δ13 C and δ15 N were in the ranges of 5.97 to 10.97,-21.76‰ to-13.14‰ and 2.13‰ to 8.08‰, respectively, implying that sedimentary organic matter in Sanggou Bay was the mixture of marine phytoplankton, terrestrial and maricultural sources. A simple mixing model based on δ13 C was applied and the results indicated that the relative contributions of organic carbon sources in Sanggou Bay followed the order kelp(36.6%) ? marine phytoplankton(28.7%) ? shellfish bio-deposition(23.8%) ? terrestrial input(10.9%). Surface sediments in Sanggou Bay were dominated by mariculture-derived organic carbon, which on average accounted for 60.4% of TOC.     

Long‐term temporal and spatial patterns in bioeroding sponge distribution at the Abrolhos Bank,Brazil, Southwestern Atlantic

Bioeroding sponges belong to the most dominant bioeroders, significantly contributing to the erosion of coral reefs. Some species are tolerant or even benefit from environmental conditions such as ocean warming, acidification, and eutrophication. In consequence, increases in sponge bioerosion have been observed on some coral reefs over the last decades. The Abrolhos Bank is the largest coral reef system in the South Atlantic. It has been affected by sedimentation, eutrophication, overfishing, and climate change, mainly affecting coastal reefs, and at lesser intensity outer ones as well. This study aimed to describe spatial and temporal patterns in bioeroding sponge distribution in carbonate substrates in the Abrolhos Bank. Photo‐quadrats were used to compare bioeroding sponge abundance between two shallow reefs: a coastal, Pedra de Leste (PL), and an outer reef, Parcel dos Abrolhos (PAB). Each individual was delimitated over the substrate by determining the sponge surface through a line connecting the outermost papillae. The study was conducted over 6 years in 2008–2009 and 2013–2016. Four species of bioeroding sponges were identified: Cliona carteri Ridley, 1881, C. delitrix Pang, 1973, C. cf. schmidtii Ridley, 1881, and Siphonodictyon coralliphagum Rützler, 1971. The distribution and abundance of species varied between the inner and outer reefs and across the years, and displayed certain selectivity for the calcareous substrates recorded. Crustose coralline algae (CCA) were the main substrate excavated by the most abundant bioeroding species, C. carteri, and represented 70% of the substrate types occupied by this sponge (CCA, coral overgrown by CCA and plain coral). The highest abundance of bioeroding sponges observed in photo‐quadrats was 21.3 individuals/m² at the outer reefs (PAB) in 2014. The abundances or areal extents of bioeroding sponges were up to 10 times greater on the outer reefs than on the coastal ones, where sedimentation is higher and more strongly influenced by siliciclastic material. Moreover, a higher herbivorous fish biomass has been reported on outer reefs which could also influence the higher abundance of bioeroding sponges in outer reefs. During the study period of 6 years, an increase in bioeroding sponge abundance was observed at the outer reefs (PAB), with the sea surface temperature increase. As CCA have an important role in reefal cementation and carbonate production in the Abrolhos reefs, a bioerosion impact might be expected, in particular, on the outer reefs.     

Effect of food quality on energy uptake

The dynamic energy budget (DEB) theory assumes that the feeding of an organism in relation to food density follows the type-II functional response when food consists of purely digestible organic matter. However when faced with a food source high in inorganic content, an organism needs to adapt physiologically to maximise organic extraction. Indeed filter-feeding marine bivalves inhabiting turbid coastal waters cope with large fluctuations in food quality by selectively ingesting and pseudofaeces production. Data from feeding experiments with the New Zealand greenshell mussel Perna canaliculus have demonstrated that inorganic particles contribute some uncertainty to the estimate of the half-saturation coefficient. Incorporating inorganic matter into the functional response would improve the prediction of energy uptake.     

Evaluation of Inference Adequacy in Cumulative Logistic Regression Models: An Empirical Validation of ISWRidge Relationships

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p 〈0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to cheek the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height （X1 ） and potential energy （X2 ） significantly impact （p 〈 0. 0001 ） the amplitude-based refleeted rate; the P-values for the deviance and Pearson are all 〉 0.05 （0.2839, 0.3438, respectively）. That is, the goodness-of-fit between ridge height （ X1 ） and potential energy （X2） can further predict parameters under the scenario of the best parsimonious model. Investigation of 6 predictive powers （ R2, Max-rescaled R^2, Sorners＇ D, Gamma, Tau-a, and c, respectively） indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.     

Evaluation of Inference Adequacy in Cumulative Logistic Regression Models： An Empirical Validation of ISW-Ridge Relationships

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p<0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to check the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height (X1) and potential energy (X2) significantly impact (p<0.0001) the amplitude-based reflected rate; the P-values for the deviance and Pearson are all >0.05 (0.2839, 0.3438, respectively). That is, the goodness-of-fit between ridge height (X1) and potential energy (X2) can further predict parameters under the scenario of the best parsimonious model.Investigation of 6 predictive powers (R2, Max-rescaled R2, Somers'D, Gamma, Tau-a, and c, respectively) indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.     

Mitigating damage costs from hurricane strikes along the southeastern U.S. Coast: A role for insurance markets

Damage costs from hurricanes have increased dramatically as hurricane strikes, populations, and property values have increased along the U.S. southeastern and Gulf Coast states. Federal expenditures in hurricane affected areas and coastal property insurance costs have increased as well. We discuss current public and private sector actions that impact damage costs and consider ways to mitigate future damage costs and government financial exposure. Encouraging adaptive and avoidance measures through market signals and government policies, and protecting areas such as wetlands which mitigate storm damage will help limit damage from hurricanes.