ResearchPad - biogeosciences https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Stringent Emission Control Policies Can Provide Large Improvements in Air Quality and Public Health in India]]> https://www.researchpad.co/article/Nb1098b2b-f8d1-46e9-80dc-86448468f6a3 Air pollution is a major risk factor for human health in IndiaPopulation aging and growth will increase the disease burden due to exposure to particulate air pollution even under no emission changeStringent emission control reduces mortality rate in 2050 below 2015 levels although total premature mortality increases

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<![CDATA[New Approaches to Identifying and Reducing the Global Burden of Disease From Pollution]]> https://www.researchpad.co/article/Nbf7723dd-5647-4f8e-be7f-e9600ebe8e30

Abstract

Pollution from multiple sources causes significant disease and death worldwide. Some sources are legacy, such as heavy metals accumulated in soils, and some are current, such as particulate matter. Because the global burden of disease from pollution is so high, it is important to identify legacy and current sources and to develop and implement effective techniques to reduce human exposure. But many limitations exist in our understanding of the distribution and transport processes of pollutants themselves, as well as the complicated overprint of human behavior and susceptibility.

New approaches are being developed to identify and eliminate pollution in multiple environments. Community‐scale detection of geogenic arsenic and fluoride in Bangladesh is helping to map the distribution of these harmful elements in drinking water. Biosensors such as bees and their honey are being used to measure heavy metal contamination in cities such as Vancouver and Sydney. Drone‐based remote sensors are being used to map metal hot spots in soils from former mining regions in Zambia and Mozambique. The explosion of low‐cost air monitors has allowed researchers to build dense air quality sensing networks to capture ephemeral and local releases of harmful materials, building on other developments in personal exposure sensing. And citizen science is helping communities without adequate resources measure their own environments and in this way gain agency in controlling local pollution exposure sources and/or alerting authorities to environmental hazards. The future of GeoHealth will depend on building on these developments and others to protect a growing population from multiple pollution exposure risks.

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<![CDATA[Prevalence and Characterization of Staphylococcus aureus and Methicillin‐Resistant Staphylococcus aureus on Public Recreational Beaches in Northeast Ohio]]> https://www.researchpad.co/article/Nc2cf7d05-879f-4ce2-8ce7-439c7751833c

Abstract

Staphylococcus aureus can cause severe life‐threatening illnesses such as sepsis and endocarditis. Although S. aureus has been isolated from marine water and intertidal beach sand, only a few studies have been conducted to assess prevalence of S. aureus at freshwater recreational beaches. As such, we aimed to determine prevalence and molecular characteristics of S. aureus in water and sand at 10 freshwater recreational beaches in Northeast Ohio, USA. Samples were analyzed using standard microbiology methods, and resulting isolates were typed by spa typing and multilocus sequence typing. The overall prevalence of S. aureus in sand and water samples was 22.8% (64/280). The prevalence of methicillin‐resistant S. aureus (MRSA) was 8.2% (23/280). The highest prevalence was observed in summer (45.8%; 55/120) compared to fall (4.2%; 5/120) and spring (10.0%; 4/40). The overall prevalence of Panton‐Valentine leukocidin genes among S. aureus isolates was 21.4% (15/70), and 27 different spa types were identified. The results of this study indicate that beach sand and freshwater of Northeast Ohio were contaminated with S. aureus, including MRSA. The high prevalence of S. aureus in summer months and presence of human‐associated strains may indicate the possibility of role of human activity in S. aureus contamination of beach water and sand. While there are several possible routes for S. aureus contamination, S. aureus prevalence was higher in sites with wastewater treatment plants proximal to the beaches.

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<![CDATA[A case for Planetary Health/GeoHealth]]> https://www.researchpad.co/article/Nde3a46c2-5f2a-4a0f-9786-dd3e01de56f2

Abstract

Concern has been spreading across scientific disciplines that the pervasive human transformation of Earth's natural systems is an urgent threat to human health. The simultaneous emergence of “GeoHealth” and “Planetary Health” signals recognition that developing a new relationship between humanity and our natural systems is becoming an urgent global health priority—if we are to prevent a backsliding from the past century's great public health gains. Achieving meaningful progress will require collaboration across a broad swath of scientific disciplines as well as with policy makers, natural resource managers, members of faith communities, and movement builders around the world in order to build a rigorous evidence base of scientific understanding as the foundation for more robust policy and resource management decisions that incorporate both environmental and human health outcomes.

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<![CDATA[Identifying Environmental Risk Factors and Mapping the Distribution of West Nile Virus in an Endemic Region of North America]]> https://www.researchpad.co/article/N1df86112-92c0-47c4-bc7e-b31b90b1d872

Abstract

Understanding the geographic distribution of mosquito‐borne disease and mapping disease risk are important for prevention and control efforts. Mosquito‐borne viruses (arboviruses), such as West Nile virus (WNV), are highly dependent on environmental conditions. Therefore, the use of environmental data can help in making spatial predictions of disease distribution. We used geocoded human case data for 2004–2017 and population‐weighted control points in combination with multiple geospatial environmental data sets to assess the environmental drivers of WNV cases and to map relative infection risk in South Dakota, USA. We compared the effectiveness of (1) land cover and physiography data, (2) climate data, and (3) spectral data for mapping the risk of WNV in South Dakota. A final model combining all data sets was used to predict spatial patterns of disease transmission and characterize the associations between environmental factors and WNV risk. We used a boosted regression tree model to identify the most important variables driving WNV risk and generated risk maps by applying this model across the entire state. We found that combining multiple sources of environmental data resulted in the most accurate predictions. Elevation, late‐season humidity, and early‐season surface moisture were the most important predictors of disease distribution. Indices that quantified interannual variability of climatic conditions and land surface moisture were better predictors than interannual means. We suggest that combining measures of interannual environmental variability with static land cover and physiography variables can help to improve spatial predictions of arbovirus transmission risk.

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<![CDATA[Half‐Century Ammonia Emissions From Agricultural Systems in Southern Asia: Magnitude, Spatiotemporal Patterns, and Implications for Human Health]]> https://www.researchpad.co/article/N6ce220af-6a1d-4bf2-8e7a-31de41e56df3

Abstract

Much concern has been raised about the increasing threat to air quality and human health due to ammonia (NH3) emissions from agricultural systems, which is associated with the enrichment of reactive nitrogen (N) in southern Asia (SA), home of more than 60% the world's population (i.e., the people of West, central, East, South, and Southeast Asia). Southern Asia consumed more than half of the global synthetic N fertilizer and was the dominant region for livestock waste production since 2004. Excessive N application could lead to a rapid increase of NH3 in the atmosphere, resulting in severe air and water pollution in this region. However, there is still a lack of accurate estimates of NH3 emissions from agricultural systems. In this study, we simulated the agricultural NH3 fluxes in SA by coupling the Bidirectional NH3 exchange module (Bi‐NH3) from the Community Multi‐scale Air Quality model with the Dynamic Land Ecosystem Model. Our results indicated that NH3 emissions were 21.3 ± 3.9 Tg N yr−1 from SA agricultural systems with a rapidly increasing rate of ~0.3 Tg N yr−2 during 1961−2014. Among the emission sources, 10.8 Tg N yr−1 was released from synthetic N fertilizer use, and 10.4 ± 3.9 Tg N yr−1 was released from manure production in 2014. Ammonia emissions from China and India together accounted for 64% of the total amount in SA during 2000−2014. Our results imply that the increased NH3 emissions associated with high N inputs to croplands would likely be a significant threat to the environment and human health unless mitigation efforts are applied to reduce these emissions.

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<![CDATA[Spatial Accessibility and Social Inclusion: The Impact of Portugal's Last Health Reform]]> https://www.researchpad.co/article/Nfdc1fbe5-ff6a-4d7a-b20c-9f51d93f1a6a

Abstract

Health policies seek to promote access to health care and should provide appropriate geographical accessibility to each demographical functional group. The dispersal demand of health‐care services and the provision for such services at fixed locations contribute to the growth of inequality in their access. Therefore, the optimal distribution of health facilities over the space/area can lead to accessibility improvements and to the mitigation of the social exclusion of the groups considered most vulnerable. Requiring for such, the use of planning practices joined with accessibility measures. However, the capacities of Geographic Information Systems in determining and evaluating spatial accessibility in health system planning have not yet been fully exploited. This paper focuses on health‐care services planning based on accessibility measures grounded on the network analysis. The case study hinges on mainland Portugal. Different scenarios were developed to measure and compare impact on the population's accessibility. It distinguishes itself from other studies of accessibility measures by integrating network data in a spatial accessibility measure: the enhanced two‐step floating catchment area. The convenient location for health‐care facilities can increase the accessibility standards of the population and consequently reduce the economic and social costs incurred. Recently, the Portuguese government implemented a reform that aimed to improve, namely, the access and equity in meeting with the most urgent patients. It envisaged, in terms of equity, the allocation of 89 emergency network points that ensured more than 90% of the population be within 30 min from any one point in the network. Consequently, several emergency services were closed, namely, in rural areas. This reform highlighted the need to improve the quality of the emergency care, accessibility to each care facility, and equity in their access. Hence, accessibility measures become an efficient decision‐making tool, despite its absence in effective practice planning. According to an application of this type of measure, it was possible to verify which levels of accessibility were decreased, including the most disadvantaged people, with a larger time of dislocation of 12 min between 2001 and 2011.

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<![CDATA[How Can Phytoplankton Pigments Be Best Used to Characterize Surface Ocean Phytoplankton Groups for Ocean Color Remote Sensing Algorithms?]]> https://www.researchpad.co/article/N63e13cf1-730b-4762-810d-15dc971439a3

Abstract

High‐performance liquid chromatography (HPLC) remains one of the most widely applied methods for estimation of phytoplankton community structure from ocean samples, which are used to create and validate satellite retrievals of phytoplankton community structure. HPLC measures the concentrations of phytoplankton pigments, some of which are useful chemotaxonomic markers for phytoplankton groups. Here, consistent suites of HPLC phytoplankton pigments measured on global surface water samples are compiled across spatial scales. The global dataset includes >4,000 samples from every major ocean basin and representing a wide range of ecological regimes. The local dataset is composed of six time series from long‐term observatory sites. These samples are used to quantify the potential and limitations of HPLC for understanding surface ocean phytoplankton groups. Hierarchical cluster and empirical orthogonal function analyses are used to examine the associations between and among groups of phytoplankton pigments and to diagnose the main controls on these associations. These methods identify four major groups of phytoplankton on global scales (cyanobacteria, diatoms/dinoflagellates, haptophytes, and green algae) that can be identified by diagnostic biomarker pigments. On local scales, the same methods identify more and different taxonomic groups of phytoplankton than are detectable in the global dataset. Notably, diatom and dinoflagellate pigments group together on global scales, but dinoflagellate marker pigments always separate from diatoms on local scales. Together, these results confirm that HPLC pigments can be used for satellite algorithm quantification of no more than four phytoplankton groups on global scales, but can provide higher resolution for local‐scale algorithm development and validation.

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<![CDATA[Magma Degassing as a Source of Long‐Term Seismicity at Volcanoes: The Ischia Island (Italy) Case]]> https://www.researchpad.co/article/N978e9b20-749d-4a9f-ac68-8956762af4c2

Abstract

Transient seismicity at active volcanoes poses a significant risk in addition to eruptive activity. This risk is powered by the common belief that volcanic seismicity cannot be forecast, even on a long term. Here we investigate the nature of volcanic seismicity to try to improve our forecasting capacity. To this aim, we consider Ischia volcano (Italy), which suffered similar earthquakes along its uplifted resurgent block. We show that this seismicity marks an acceleration of decades‐long subsidence of the resurgent block, driven by degassing of magma that previously produced the uplift, a process not observed at other volcanoes. Degassing will continue for hundreds to thousands of years, causing protracted seismicity and will likely be accompanied by moderate and damaging earthquakes. The possibility to constrain the future duration of seismicity at Ischia indicates that our capacity to forecast earthquakes might be enhanced when seismic activity results from long‐term magmatic processes, such as degassing

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<![CDATA[Insignificant QBO‐MJO Prediction Skill Relationship in the SubX and S2S Subseasonal Reforecasts]]> https://www.researchpad.co/article/N80d62339-fdd5-4539-8af8-fbb9aaf795dd

Abstract

The impact of the stratospheric quasi‐biennial oscillation (QBO) on the prediction of the tropospheric Madden‐Julian oscillation (MJO) is evaluated in reforecasts from nine models participating in subseasonal prediction projects, including the Subseasonal Experiment (SubX) and Subseasonal to Seasonal (S2S) projects. When MJO prediction skill is analyzed for December to February, MJO prediction skill is higher in the easterly phase of the QBO than the westerly phase, consistent with previous studies. However, the relationship between QBO phase and MJO prediction skill is not statistically significant for most models. This insignificant QBO‐MJO skill relationship is further confirmed by comparing two subseasonal reforecast experiments with the Community Earth System Model v1 using both a high‐top (46‐level) and low‐top (30‐level) version of the Community Atmosphere Model v5. While there are clear differences in the forecasted QBO between the two model top configurations, a negligible change is shown in the MJO prediction, indicating that the QBO in this model may not directly control the MJO prediction and supporting the insignificant QBO‐MJO skill relationship found in SubX and S2S models.

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<![CDATA[Considering the Role of Adaptive Evolution in Models of the Ocean and Climate System]]> https://www.researchpad.co/article/Nfe9152c8-e79c-4817-9ec2-593d8a0ca732

Abstract

Numerical models have been highly successful in simulating global carbon and nutrient cycles in today's ocean, together with observed spatial and temporal patterns of chlorophyll and plankton biomass at the surface. With this success has come some confidence in projecting the century‐scale response to continuing anthropogenic warming. There is also increasing interest in using such models to understand the role of plankton ecosystems in past oceans. However, today's marine environment is the product of billions of years of continual evolution—a process that continues today. In this paper, we address the questions of whether an assumption of species invariance is sufficient, and if not, under what circumstances current model projections might break down. To do this, we first identify the key timescales and questions asked of models. We then review how current marine ecosystem models work and what alternative approaches are available to account for evolution. We argue that for timescales of climate change overlapping with evolutionary timescales, accounting for evolution may to lead to very different projected outcomes regarding the timescales of ecosystem response and associated global biogeochemical cycling. This is particularly the case for past extinction events but may also be true in the future, depending on the eventual degree of anthropogenic disruption. The discipline of building new numerical models that incorporate evolution is also hugely beneficial in itself, as it forces us to question what we know about adaptive evolution, irrespective of its quantitative role in any specific event or environmental changes.

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<![CDATA[Including Stable Carbon Isotopes to Evaluate the Dynamics of Soil Carbon in the Land‐Surface Model ORCHIDEE]]> https://www.researchpad.co/article/N50d35cde-1e20-4abc-8ba9-8eb87f5d9f22

Abstract

Soil organic carbon (SOC) is a crucial component of the terrestrial carbon cycle and its turnover time in models is a key source of uncertainty. Studies have highlighted the utility of δ13C measurements for benchmarking SOC turnover in global models. We used 13C as a tracer within a vertically discretized soil module of a land‐surface model, Organising Carbon and Hydrology In Dynamic Ecosystems‐ Soil Organic Matter (ORCHIDEE‐SOM). Our new module represents some of the processes that have been hypothesized to lead to a 13C enrichment with soil depth as follows: 1) the Suess effect and CO2 fertilization, 2) the relative 13C enrichment of roots compared to leaves, and 3) 13C discrimination associated with microbial activity. We tested if the upgraded soil module was able to reproduce the vertical profile of δ13C within the soil column at two temperate sites and the short‐term change in the isotopic signal of soil after a shift in C3/C4 vegetation. We ran the model over Europe to test its performance at larger scale. The model was able to simulate a shift in the isotopic signal due to short‐term changes in vegetation cover from C3 to C4; however, it was not able to reproduce the overall vertical profile in soil δ13C, which arises as a combination of short and long‐term processes. At the European scale, the model ably reproduced soil CO2 fluxes and total SOC stock. These findings stress the importance of the long‐term history of land cover for simulating vertical profiles of δ13C. This new soil module is an emerging tool for the diagnosis and improvement of global SOC models.

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<![CDATA[Reassessing Southern Ocean Air‐Sea CO 2 Flux Estimates With the Addition of Biogeochemical Float Observations]]> https://www.researchpad.co/article/N52b24823-1e08-4ca3-a65d-a54e81e297ed

Abstract

New estimates of pCO2 from profiling floats deployed by the Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) project have demonstrated the importance of wintertime outgassing south of the Polar Front, challenging the accepted magnitude of Southern Ocean carbon uptake (Gray et al., 2018, https://doi:10.1029/2018GL078013). Here, we put 3.5 years of SOCCOM observations into broader context with the global surface carbon dioxide database (Surface Ocean CO2 Atlas, SOCAT) by using the two interpolation methods currently used to assess the ocean models in the Global Carbon Budget (Le Quéré et al., 2018, https://doi:10.5194/essd-10-2141-2018) to create a ship‐only, a float‐weighted, and a combined estimate of Southern Ocean carbon fluxes (<35°S). In our ship‐only estimate, we calculate a mean uptake of −1.14 ± 0.19 Pg C/yr for 2015–2017, consistent with prior studies. The float‐weighted estimate yields a significantly lower Southern Ocean uptake of −0.35 ± 0.19 Pg C/yr. Subsampling of high‐resolution ocean biogeochemical process models indicates that some of the differences between float and ship‐only estimates of the Southern Ocean carbon flux can be explained by spatial and temporal sampling differences. The combined ship and float estimate minimizes the root‐mean‐square pCO2 difference between the mapped product and both data sets, giving a new Southern Ocean uptake of −0.75 ± 0.22 Pg C/yr, though with uncertainties that overlap the ship‐only estimate. An atmospheric inversion reveals that a shift of this magnitude in the contemporary Southern Ocean carbon flux must be compensated for by ocean or land sinks within the Southern Hemisphere.

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<![CDATA[Hybrid Mass Balance/4D‐Var Joint Inversion of NO x and SO 2 Emissions in East Asia]]> https://www.researchpad.co/article/Ne104e45a-33d7-45d3-b79c-9974fe345cef

Abstract

Accurate estimates of NOx and SO2 emissions are important for air quality modeling and management. To incorporate chemical interactions of the two species in emission estimates, we develop a joint hybrid inversion framework to estimate their emissions in China and India (2005–2012). Pseudo observation tests and posterior evaluation with surface measurements demonstrate that joint assimilation of SO2 and NO2 can provide more accurate constraints on emissions than single‐species inversions. This occurs through synergistic change of O3 and OH concentrations, particularly in conditions where satellite retrievals of the species being optimized have large uncertainties. The percentage changes of joint posterior emissions from the single‐species posterior emissions go up to 242% at grid scales, although the national average of monthly emissions, seasonality, and interannual variations are similar. In China and India, the annual budget of joint posterior SO2 emissions is lower, but joint NOx posterior emissions are higher, because NOx emissions increase to increase SO2 concentration and better match Ozone Monitoring Instrument SO2 observations in high‐NOx regions. Joint SO2 posterior emissions decrease by 16.5% from 2008 to 2012, while NOx posterior emissions increase by 24.9% from 2005 to 2011 in China—trends which are consistent with the MEIC inventory. Joint NOx and SO2 posterior emissions in India increase by 15.9% and 19.2% from 2005 to 2012, smaller than the 59.9% and 76.2% growth rate using anthropogenic emissions from EDGARv4.3.2. This work shows the benefit and limitation of joint assimilation in emission estimates and provides an efficient framework to perform the inversion.

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<![CDATA[SO 2 Emission Estimates Using OMI SO 2 Retrievals for 2005–2017]]> https://www.researchpad.co/article/N6a783255-8e13-48df-b62e-7af6e7554ff5

Abstract

SO2 column densities from Ozone Monitoring Instrument provide important information on emission trends and missing sources, but there are discrepancies between different retrieval products. We employ three Ozone Monitoring Instrument SO2 retrieval products (National Aeronautics and Space Administration (NASA) standard (SP), NASA prototype, and BIRA) to study the magnitude and trend of SO2 emissions. SO2 column densities from these retrievals are most consistent when viewing angles and solar zenith angles are small, suggesting more robust emission estimates in summer and at low latitudes. We then apply a hybrid 4D‐Var/mass balance emission inversion to derive monthly SO2 emissions from the NASA SP and BIRA products. Compared to HTAPv2 emissions in 2010, both posterior emission estimates are lower in United States, India, and Southeast China, but show different changes of emissions in North China Plain. The discrepancies between monthly NASA and BIRA posterior emissions in 2010 are less than or equal to 17% in China and 34% in India. SO2 emissions increase from 2005 to 2016 by 35% (NASA)–48% (BIRA) in India, but decrease in China by 23% (NASA)–33% (BIRA) since 2008. Compared to in situ measurements, the posterior GEOS‐Chem surface SO2 concentrations have reduced NMB in China, the United States, and India but not in South Korea in 2010. BIRA posteriors have better consistency with the annual growth rate of surface SO2 measurement in China and spatial variability of SO2 concentration in China, South Korea, and India, whereas NASA SP posteriors have better seasonality. These evaluations demonstrate the capability to recover SO2 emissions using Ozone Monitoring Instrument observations.

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<![CDATA[Geodetic Observations of Weak Determinism in Rupture Evolution of Large Earthquakes]]> https://www.researchpad.co/article/5c756541d5eed0c484cbd883

Abstract

The moment evolution of large earthquakes is a subject of fundamental interest to both basic and applied seismology. Specifically, an open problem is when in the rupture process a large earthquake exhibits features dissimilar from those of a lesser magnitude event. The answer to this question is of importance for rapid, reliable estimation of earthquake magnitude, a major priority of earthquake and tsunami early warning systems. Much effort has been made to test whether earthquakes are deterministic, meaning that observations in the first few seconds of rupture can be used to predict the final rupture extent. However, results have been inconclusive, especially for large earthquakes greater than M w7. Traditional seismic methods struggle to rapidly distinguish the size of large‐magnitude events, in particular near the source, even after rupture completion, making them insufficient to resolve the question of predictive rupture behavior. Displacements derived from Global Navigation Satellite System data can accurately estimate magnitude in real time, even for the largest earthquakes. We employ a combination of seismic and geodetic (Global Navigation Satellite System) data to investigate early rupture metrics, to determine whether observational data support deterministic rupture behavior. We find that while the earliest metrics (~5 s of data) are not enough to infer final earthquake magnitude, accurate estimates are possible within the first tens of seconds, prior to rupture completion, suggesting a weak determinism. We discuss the implications for earthquake source physics and rupture evolution and address recommendations for earthquake and tsunami early warning.

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<![CDATA[Correlating carbon and oxygen isotope events in early to middle Miocene shallow marine carbonates in the Mediterranean region using orbitally tuned chemostratigraphy and lithostratigraphy]]> https://www.researchpad.co/article/5b0173a6463d7e4814341d99

Abstract

During the Miocene prominent oxygen isotope events (Mi‐events) reflect major changes in glaciation, while carbonate isotope maxima (CM‐events) reflect changes in organic carbon burial, particularly during the Monterey carbon isotope excursion. However, despite their importance to the global climate history they have never been recorded in shallow marine carbonate successions. The Decontra section on the Maiella Platform (central Apennines, Italy), however, allows to resolve them for the first time in such a setting during the early to middle Miocene. The present study improves the stratigraphic resolution of parts of the Decontra section via orbital tuning of high‐resolution gamma ray (GR) and magnetic susceptibility data to the 405 kyr eccentricity metronome. The tuning allows, within the established biostratigraphic, sequence stratigraphic, and isotope stratigraphic frameworks, a precise correlation of the Decontra section with pelagic records of the Mediterranean region, as well as the global paleoclimatic record and the global sea level curve. Spectral series analyses of GR data further indicate that the 405 kyr orbital cycle is particularly well preserved during the Monterey Event. Since GR is a direct proxy for authigenic uranium precipitation during increased burial of organic carbon in the Decontra section, it follows the same long‐term orbital pacing as observed in the carbon isotope records. The 405 kyr GR beat is thus correlated with the carbon isotope maxima observed during the Monterey Event. Finally, the Mi‐events can now be recognized in the δ18O record and coincide with plankton‐rich, siliceous, or phosphatic horizons in the lithology of the section.

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