ResearchPad - Oceanography https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Quantifying the Effect of Xiluodu Reservoir on the Temperature of the Surrounding Mountains]]> https://www.researchpad.co/product?articleinfo=N73c564b8-053e-4513-84ea-c86d6e471b77

Abstract

To quantitatively determine the effect of Xiluodu Reservoir on the temperature of the surrounding mountains, the temperature differences between various locations and the reservoir were calculated based on Landsat 8 thermal infrared sensor (TIRS) data. Elevation, slope, aspect, normalized difference vegetation index (NDVI), and visual field were selected as the impact factors, and the most significant grid size used to explore the effect of reservoir on the surrounding mountains was determined by spatial analysis and partial correlation analysis. The effect of the Xiluodu Reservoir on the surrounding mountains' temperature was then quantitatively studied while accounting for the effect of water surface width on temperature. The results are summarized as follows. The most significant grid size for determining the influence of Xiluodu Reservoir on the surrounding mountains' temperature is 90 m. The effect range threshold of the entire reservoir on the temperature of the surrounding mountains is approximately 600 m, and the partial correlation coefficient in each buffer area decreases gradually with increasing distance from the reservoir. The effect threshold of the reservoir on the temperature of the surrounding mountains is approximately 1,500 m in the head area with a water surface width approximately 1,000 m, but it is negligible in the tributary area where the width is approximately 60 m.

]]>
<![CDATA[The Propagation Effects of Lightning Electromagnetic Fields Over Mountainous Terrain in the Earth‐Ionosphere Waveguide]]> https://www.researchpad.co/product?articleinfo=N1dfcb8d9-37b3-4eb7-8743-ae3fafeb31fd

Abstract

In this paper, a full‐wave two‐dimensional Finite‐Difference‐Time‐Domain model is developed to evaluate the propagation effects of lightning electromagnetic fields over mountainous terrain in the Earth‐ionosphere waveguide. In the model, we investigate the effect of the Earth‐ionosphere waveguide structure and medium parameters, including the effect of the ionospheric cold plasma characteristics, the effect of the Earth curvature, and the propagation effects over mountainous terrain. For the first time, the obtained results are validated against simultaneous experimental data consisting of lightning currents measured at the Säntis Tower and electric fields measured in Neudorf, Austria, located at 380‐km distance from the tower. It is shown that both the time delays and amplitudes of the lightning electromagnetic fields at 380‐km distance can be strongly affected by the ionospheric electron density profile, the mountainous terrain, and the Earth curvature. After taking into account the effect of the irregular terrain between the Säntis Tower and the field measurement station, the vertical electric fields calculated by using our model are found to be in good agreement with the corresponding measured cases occurred in both daytime and nighttime. The ideal approximation used in either the classical solutions or the simplified models might lead to inaccuracies in the estimated reflection height. Furthermore, we discuss the sensitivity of our results by considering different return stroke models, as well as different typical values of the return stroke speed and of the ground conductivity.

]]>
<![CDATA[Land Use, Not Stream Order, Controls N2O Concentration and Flux in the Upper Mara River Basin, Kenya]]> https://www.researchpad.co/product?articleinfo=Nb2cade8a-1394-4f7d-b436-62478769eb74

Abstract

Anthropogenic activities have led to increases in nitrous oxide (N2O) emissions from river systems, but there are large uncertainties in estimates due to lack of data in tropical rivers and rapid increase in human activity. We assessed the effects of land use and river size on N2O flux and concentration in 46 stream sites in the Mara River, Kenya, during the transition from the wet (short rains) to dry season, November 2017 to January 2018. Flux estimates were similar to other studies in tropical and temperate systems, but in contrast to other studies, land use was more related to N2O concentration and flux than stream size. Agricultural stream sites had the highest fluxes (26.38 ± 5.37 N2O‐N μg·m–2·hr–1) compared to both forest and livestock sites (5.66 ± 1.38 N2O‐N μg·m–2·hr–1 and 6.95 ± 2.96 N2O‐N μg·m–2·hr–1, respectively). N2O concentrations in forest and agriculture streams were positively correlated to stream carbon dioxide (CO2‐C(aq)) but showed a negative correlation with dissolved organic carbon, and the dissolved organic carbon:dissolved inorganic nitrogen ratio. N2O concentration in the livestock sites had a negative relationship with CO2‐C(aq) and a higher number of negative fluxes. We concluded that in‐stream chemoautotrophic nitrification was likely the main biogeochemical process driving N2O production in agricultural and forest streams, whereas complete denitrification led to the consumption of N2O in the livestock stream sites. These results point to the need to better understand the relative importance of nitrification and denitrification in different habitats in producing N2O and for process‐based studies.

]]>
<![CDATA[Analysis of the Spatial Nonuniformity of the Electric Field in Spectroscopic Diagnostic Methods of Atmospheric Electricity Phenomena]]> https://www.researchpad.co/product?articleinfo=N4ee2dca9-9c17-4481-b682-58634ff16627

Abstract

The spatial nonuniformity of the electric field in air discharges, such as streamers, can influence the accuracy of spectroscopic diagnostic methods and hence the estimation of the peak electric field. In this work, we use a self‐consistent streamer discharge model to investigate the spatial nonuniformity in streamer heads and streamer glows. We focus our analysis on air discharges at atmospheric pressure and at the low pressure of the mesosphere. This approach is useful to investigate the spatial nonuniformity of laboratory discharges as well as sprite streamers and blue jet streamers, two types of transient luminous events taking place above thunderclouds. This characterization of the spatial nonuniformity of the electric field in air discharges allows us to develop two different spectroscopic diagnostic methods to estimate the peak electric field in cold plasmas. The commonly employed method to derive the peak electric field in streamer heads underestimates the electric field by about 40–50% as a consequence of the high spatial nonuniformity of the electric field. Our diagnostic methods reduce this underestimation to about 10–20%. However, our methods are less accurate than previous methods for streamer glows, where the electric field is uniformly distributed in space. Finally, we apply our diagnostic methods to the measured optical signals in the second positive system of N2 and the first negative system of N2+ of sprites recorded by Armstrong et al. (1998, https://doi.org/10.1016/S1364-6826(98)00026-1) during the SPRITE's 1995 and 1996 campaigns.

]]>
<![CDATA[New Approaches to Identifying and Reducing the Global Burden of Disease From Pollution]]> https://www.researchpad.co/product?articleinfo=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.

]]>
<![CDATA[Substrate rugosity and temperature matters: patterns of benthic diversity at tropical intertidal reefs in the SW Atlantic]]> https://www.researchpad.co/product?articleinfo=N7c59bde4-0dbb-4a33-a228-9eb85bb49e49

Modeling and forecasting ocean ecosystems in a changing world will require advances in observational efforts to monitor marine biodiversity. One of the observational challenges in coastal reef ecosystems is to quantify benthic and climate interactions which are key to community dynamics across habitats. Habitat complexity (i.e., substrate rugosity) on intertidal reefs can be an important variable explaining benthic diversity and taxa composition, but the association between substrate and seasonal variability is poorly understood on lateritic reefs in the South Atlantic. We asked if benthic assemblages on intertidal reefs with distinct substrate rugosity would follow similar seasonal patterns of succession following meteo-oceanographic variability in a tropical coastal area of Brazil. We combined an innovative 3D imaging for measuring substrate rugosity with satellite monitoring to monitor spatio-temporal patterns of benthic assemblages. The dataset included monthly in situ surveys of substrate cover and taxon diversity and richness, temporal variability in meteo-oceanographic conditions, and reef structural complexity from four sites on the Eastern Marine Ecoregion of Brazil. Additionally, correlation coefficients between temperature and both benthic diversity and community composition from one year of monitoring were used to project biodiversity trends under future warming scenarios. Our results revealed that benthic diversity and composition on intertidal reefs are strongly regulated by surface rugosity and sea surface temperatures, which control the dominance of macroalgae or corals. Intertidal reef biodiversity was positively correlated with reef rugosity which supports previous assertions of higher regional intertidal diversity on lateritic reefs that offer increased substrate complexity. Predicted warming temperatures in the Eastern Marine Ecoregion of Brazil will likely lead to a dominance of macroalgae taxa over the lateritic reefs and lower overall benthic diversity. Our findings indicate that rugosity is not only a useful tool for biodiversity mapping in reef intertidal ecosystems but also that spatial differences in rugosity would lead to very distinct biogeographic and temporal patterns. This study offers a unique baseline of benthic biodiversity on coastal marine habitats that is complementary to worldwide efforts to improve monitoring and management of coastal reefs.

]]>
<![CDATA[Spatial Accessibility and Social Inclusion: The Impact of Portugal's Last Health Reform]]> https://www.researchpad.co/product?articleinfo=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.

]]>
<![CDATA[Half‐Century Ammonia Emissions From Agricultural Systems in Southern Asia: Magnitude, Spatiotemporal Patterns, and Implications for Human Health]]> https://www.researchpad.co/product?articleinfo=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.

]]>
<![CDATA[Impact of Deadly Dust Storms (May 2018) on Air Quality, Meteorological, and Atmospheric Parameters Over the Northern Parts of India]]> https://www.researchpad.co/product?articleinfo=N8387ef6b-b75b-4aaa-bb39-241535d00866

Abstract

The northern part of India, adjoining the Himalaya, is considered as one of the global hot spots of pollution because of various natural and anthropogenic factors. Throughout the year, the region is affected by pollution from various sources like dust, biomass burning, industrial and vehicular pollution, and myriad other anthropogenic emissions. These sources affect the air quality and health of millions of people who live in the Indo‐Gangetic Plains. The dust storms that occur during the premonsoon months of March–June every year are one of the principal sources of pollution and originate from the source region of Arabian Peninsula and the Thar desert located in north‐western India. In the year 2018, month of May, three back‐to‐back major dust storms occurred that caused massive damage, loss of human lives, and loss to property and had an impact on air quality and human health. In this paper, we combine observations from ground stations, satellites, and radiosonde networks to assess the impact of dust events in the month of May 2018, on meteorological parameters, aerosol properties, and air quality. We observed widespread changes associated with aerosol loadings, humidity, and vertical advection patterns with displacements of major trace and greenhouse gasses. We also notice drastic changes in suspended particulate matter concentrations, all of which can have significant ramifications in terms of human health and changes in weather pattern.

]]>
<![CDATA[Quantification of Rotavirus Diarrheal Risk Due to Hydroclimatic Extremes Over South Asia: Prospects of Satellite‐Based Observations in Detecting Outbreaks]]> https://www.researchpad.co/product?articleinfo=N1c514245-56ef-4185-b93e-7462d32dd374

Abstract

Rotavirus is the most common cause of diarrheal disease among children under 5. Especially in South Asia, rotavirus remains the leading cause of mortality in children due to diarrhea. As climatic extremes and safe water availability significantly influence diarrheal disease impacts in human populations, hydroclimatic information can be a potential tool for disease preparedness. In this study, we conducted a multivariate temporal and spatial assessment of 34 climate indices calculated from ground and satellite Earth observations to examine the role of temperature and rainfall extremes on the seasonality of rotavirus transmission in Bangladesh. We extracted rainfall data from the Global Precipitation Measurement and temperature data from the Moderate Resolution Imaging Spectroradiometer sensors to validate the analyses and explore the potential of a satellite‐based seasonal forecasting model. Our analyses found that the number of rainy days and nighttime temperature range from 16°C to 21°C are particularly influential on the winter transmission cycle of rotavirus. The lower number of wet days with suitable cold temperatures for an extended time accelerates the onset and intensity of the outbreaks. Temporal analysis over Dhaka also suggested that water logging during monsoon precipitation influences rotavirus outbreaks during a summer transmission cycle. The proposed model shows lag components, which allowed us to forecast the disease outbreaks 1 to 2 months in advance. The satellite data‐driven forecasts also effectively captured the increased vulnerability of dry‐cold regions of the country, compared to the wet‐warm regions.

]]>
<![CDATA[WRF 1960–2014 Winter Season Simulations of Particulate Matter in the Sahel: Implications for Air Quality and Respiratory Health]]> https://www.researchpad.co/product?articleinfo=N4dbdd16f-7dfe-4144-8d3d-a37f1cc7a940

Abstract

We use the Weather Research and Forecast model using the Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) dust module (WRF‐CHEM) to simulate the particulate matter (PM) variations in the Sahel during the winter seasons (January–March) of 1960–2014. Two simulations are undertaken where the direct aerosol feedback is turned off, and only transport is considered and where the direct aerosol feedback is turned on. We find that simulated Sahelian PM10 and PM2.5 concentrations were lower in the 1960s and after 2003 and higher during the period between 1988 and 2002. Higher Sahelian PM10 concentrations are due to stronger winds between the surface and 925 hPa over the Sahara, which transport dust into the Sahel. Negative PM10 concentration anomalies are found over the Bodele Depression and associated with weaker 925 wind anomalies after 1997 through 2014. Further west, positive PM10 concentration anomalies are found across the Adrar Plateau in the Sahara and responsible for dust transport to the Western Sahel. The North Atlantic Oscillation (NAO) is positively correlated to Sahelian dust concentrations especially during the periods of 1960–1970 and 1988–2002. The temporal/spatial patterns of PM10 concentrations have significant respiratory health implications for inhabitants of the Sahel.

]]>
<![CDATA[Prevalence and Characterization of Staphylococcus aureus and Methicillin‐Resistant Staphylococcus aureus on Public Recreational Beaches in Northeast Ohio]]> https://www.researchpad.co/product?articleinfo=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.

]]>
<![CDATA[Identifying Environmental Risk Factors and Mapping the Distribution of West Nile Virus in an Endemic Region of North America]]> https://www.researchpad.co/product?articleinfo=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.

]]>
<![CDATA[Holistic Environmental Approaches and Aichi Biodiversity Targets: accomplishments and perspectives for marine ecosystems]]> https://www.researchpad.co/product?articleinfo=N02cf04e4-8823-442e-aadb-c7b55a396ab1

In order to help safeguard biodiversity from global changes, the Conference of the Parties developed a Strategic Plan for Biodiversity for the period 2011–2020 that included a list of twenty specific objectives known as the Aichi Biodiversity Targets. With the end of that timeframe in sight, and despite major advancements in biodiversity conservation, evidence suggests that the majority of the Targets are unlikely to be met. This article is part of a series of perspective pieces from the 4th World Conference on Marine Biodiversity (May 2018, Montréal, Canada) to identify next steps towards successful biodiversity conservation in marine environments. We specifically reviewed holistic environmental assessment studies (HEA) and their contribution to reaching the Targets. Our analysis was based on multiple environmental approaches which can be considered as holistic, and we discuss how HEA can contribute to the Aichi Biodiversity Targets in the near future. We found that only a few HEA articles considered a specific Biodiversity Target in their research, and that Target 11, which focuses on marine protected areas, was the most commonly cited. We propose five research priorities to enhance HEA for marine biodiversity conservation beyond 2020: (i) expand the use of holistic approaches in environmental assessments, (ii) standardize HEA vocabulary, (iii) enhance data collection, sharing and management, (iv) consider ecosystem spatio-temporal variability and (v) integrate ecosystem services in HEA. The consideration of these priorities will promote the value of HEA and will benefit the Strategic Plan for Biodiversity.

]]>
<![CDATA[Seasonal variability and vertical distribution of autotrophic and heterotrophic picoplankton in the Central Red Sea]]> https://www.researchpad.co/product?articleinfo=N86fbcbe5-6bc6-403c-9be6-00549d798c7b

The Red Sea is characterized by higher temperatures and salinities than other oligotrophic tropical regions. Here, we investigated the vertical and seasonal variations in the abundance and biomass of autotrophic and heterotrophic picoplankton. Using flow cytometry, we consistently observed five groups of autotrophs (Prochlorococcus, two populations of Synechococcus separated by their relative phycoerythrin fluorescence, low (LF-Syn) and high (HF-Syn), and two differently-sized groups of picoeukaryotes, small (Speuk) and large (Lpeuk)) and two groups of heterotrophic prokaryotes of low and high nucleic acid content (LNA and HNA, respectively). Samples were collected in 15 surveys conducted from 2015 to 2017 at a 700-m depth station in the central Red Sea. Surface temperature ranged from 24.6 to 32.6 °C with a constant value of 21.7 °C below 200 m. Integrated (0–100 m) chlorophyll a concentrations were low, with maximum values in fall (24.0 ± 2.7 mg m−2) and minima in spring and summer (16.1 ± 1.9 and 1.1 mg m−2, respectively). Picoplankton abundance was generally lower than in other tropical environments. Vertical distributions differed for each group, with Synechococcus and LNA prokaryotes more abundant at the surface while Prochlorococcus, picoeukaryotes and HNA prokaryotes peaked at the deep chlorophyll maximum, located between 40 and 76 m. Surface to 100 m depth-weighted abundances exhibited clear seasonal patterns for Prochlorococcus, with maxima in summer (7.83 × 104 cells mL−1, July 2015) and minima in winter (1.39 × 104 cells mL−1, January 2015). LF-Syn (0.32 – 2.70 × 104 cells mL−1 ), HF-Syn (1.11 – 3.20 × 104 cells mL−1) and Speuk (0.99 – 4.81 × 102 cells mL−1) showed an inverse pattern to Prochlorococcus, while Lpeuk (0.16 – 7.05 × 104 cells mL−1) peaked in fall. Synechococcus unexpectedly outnumbered Prochlorococcus in winter and at the end of fall. The seasonality of heterotrophic prokaryotes (2.29 – 4.21×105 cells mL−1 ) was less noticeable than autotrophic picoplankton. The contribution of HNA cells was generally low in the upper layers, ranging from 36% in late spring and early summer to ca. 50% in winter and fall. Autotrophs dominated integrated picoplankton biomass in the upper 100 m, with 1.4-fold higher values in summer than in winter (mean 387 and 272 mg C m–2, respectively). However, when the whole water column was considered, the biomass of heterotrophic prokaryotes exceeded that of autotrophic picoplankton with an average of 411 mg C m–2. Despite being located in tropical waters, our results show that the picoplankton community seasonal differences in the central Red Sea are not fundamentally different from higher latitude regions.

]]>
<![CDATA[How Can Phytoplankton Pigments Be Best Used to Characterize Surface Ocean Phytoplankton Groups for Ocean Color Remote Sensing Algorithms?]]> https://www.researchpad.co/product?articleinfo=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.

]]>
<![CDATA[The Land‐Sea Breeze of the Red Sea: Observations, Simulations, and Relationships to Regional Moisture Transport]]> https://www.researchpad.co/product?articleinfo=Na2316739-693c-4b23-a87b-686438623071

Abstract

Unique in situ observations of atmospheric conditions over the Red Sea and the coastal Arabian Peninsula are examined to study the dynamics and regional impacts of the local land‐sea breeze cycle (LSBC). During a 26‐month data record spanning 2008–2011, observed LSBC events occurred year‐round, frequently exhibiting cross‐shore wind velocities in excess of 8 m/s. Observed onshore and offshore features of both the land‐ and sea‐breeze phases of the cycle are presented, and their seasonal modulation is considered. Weather Research and Forecasting climate downscaling simulations and satellite measurements are used to extend the analysis. In the model, the amplitude of the LSBC is significantly larger in the vicinity of the steeper terrain elements encircling the basin, suggesting an enhancement by the associated slope winds. Observed and simulated conditions also reflected distinct gravity‐current characteristics of the intrinsic moist marine air mass during both phases of the LSBC. Specifically, the advance and retreat of marine air mass was directly tied to the development of internal boundary layers onshore and offshore throughout the period of study. Convergence in the lateral moisture flux resulting from this air mass ascending the coastal topography (sea‐breeze phase) as well as colliding with air masses from the opposing coastline (land‐breeze phase) further resulted in cumulous cloud formation and precipitation.

]]>
<![CDATA[Identifying Source Regions and the Distribution of Cross‐Tropopause Convective Outflow Over North America During the Warm Season]]> https://www.researchpad.co/product?articleinfo=Nba38a661-9ecf-4b13-ba55-b636e4f23237

Abstract

We analyzed the interaction between the North American monsoon anticyclone (NAMA) and summertime cross‐tropopause convective outflow by applying a trajectory analysis to a climatology of convective overshooting tops (OTs) identified in GOES satellite images, which covers the domain from 29°S to 68°N and from 205 to 1.25°W for the time period of May through September 2013. With this analysis we identified seasonally, geographically, and altitude‐dependent variability in NAMA strength and in cross‐tropopause convection that control their interaction. We find that the NAMA has the strongest impact on the circulation of convectively influenced air masses in August. Over the entire time period examined the intertropical convergence zone contributes the majority of OTs with a larger fraction of total OTs at 370 K (on average 70%) than at 400 K (on average 52%). During August at 370 K, the convectively influenced air masses within the NAMA circulation, as determined by the trajectory analysis, are primarily sourced from the intertropical convergence zone (monthly average of 66.1%), while at 400 K the Sierra Madres and the Central United States combined constitute the dominant source region (monthly average of 44.1%, compared to 36.6% of the combined Intertropical Convergence Zone regions). When evaluating the impact of cross‐tropopause convection on the composition and chemistry of the upper troposphere and lower stratosphere, the effects of the NAMA on both the distribution of convective outflow and the residence time of convectively influenced air masses within the NAMA region must be considered.

]]>
<![CDATA[Bacterial inoculations can perturb the growth trajectory of diatoms with an existing microbiome]]> https://www.researchpad.co/product?articleinfo=N82780146-bca0-4e01-ad55-22110442c2f7

Inoculation of axenic diatom monocultures with individual bacterial strains has been used effectively to examine the relationship between bacteria and a diatom host. Both beneficial and harmful effects on diatom fitness have been observed. Yet, diatoms commonly host a consortium of bacteria that could influence their response to perturbation by bacterial inoculations. In this study, diatom cultures with an existing microbiome were inoculated with individual bacterial strains. Strains of two genera of bacteria commonly found associated with diatoms (Alteromonas and Marinobacter) were isolated from a culture of the diatom Chaetoceros sp. KBDT20. To evaluate whether bacterial inoculations can impact the growth, peak abundance, or decline of diatoms with an intact microbiome, individual bacterial strains were inoculated into batch cultures of the original host as well as two non-origin diatom hosts (Chaetoceros sp. KBDT32 and Amphiprora sp. KBDT35). Inoculations were repeated under vitamin-replete and vitamin-deficient conditions to assess whether vitamin concentration modulates the impact of bacterial inoculations on the host. The origin Chaetoceros culture was largely unperturbed by bacterial inoculations. In contrast, non-origin hosts experienced long-term impacts on their growth trajectory, and those impacts were found to be dependent on the concentration of vitamins in the growth medium. For the non-origin Chaetoceros, all positive impacts were observed in vitamin-replete conditions and all negative impacts were observed in vitamin-deficient conditions. Amphiprora was only impacted by inoculation with Marinobacter strains in vitamin-deficient conditions, and the effect was negative. Neither individual bacterial strains nor genera resulted in exclusively beneficial nor detrimental impacts, and the magnitude of effect varied among bacterial strains. This study demonstrates that bacterial inoculations can have long-lasting impacts on the growth trajectory of diatoms with an existing microbiome, that this impact can differ even between congeneric diatoms, and that the impact can be significantly modulated by vitamin concentration.

]]>
<![CDATA[Including Stable Carbon Isotopes to Evaluate the Dynamics of Soil Carbon in the Land‐Surface Model ORCHIDEE]]> https://www.researchpad.co/product?articleinfo=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.

]]>