Application of Aqua MODIS sensor data for estimating chlorophyll a in the turbid Case 2 waters of Lake Erie using bio-optical models

There is considerable interest in accurately estimating water quality parameters in turbid (Case 2) and eutrophic waters such as the Western Basin of Lake Erie (WBLE). Lake Erie is a large, open freshwater body that supports diverse ecosystem, and over 12 million people in the mid-western part of the United States depend on it for drinking water, fisheries, navigational, and recreational purposes. The increasing utilization of the freshwater has deteriorated the water severely and currently the lake is experiencing recurring harmful algal blooms (HABs). Improving the water quality of Lake Erie requires the use of robust monitoring tools that help water quality managers understand sources and pathways of influxes that trigger HABs. Satellite-based remote sensing sensor such as the moderate resolution imaging spectroradiometer (MODIS) may provide frequent and synoptic view of the water quality indices. In this study, data set from field measurements was used to evaluate the performance of 14 existing ocean color algorithms. Results indicated that MODIS data consistently underestimated the chlorophyll a concentrations in the WBLE, with the largest source of errors from dissolved organic matter and xanthophyll accessory pigments in this data set. Most of the global algorithms, including OC4v4 and the Baltic model, generated near-identical statistical parameters with an average R² of ~0.57 and RMSE ~2.9 μg/l. MODIS performed poorly (R² ~0.18) when its NIR/red bands were used. A slightly improved model was developed using similar band ratio approach generating R² of ~0.62 and RMSE ~1.8 μg/l.     

Developing Data-Rich Video of Surface Water–Groundwater Interactions for Public Engagement

Communication of hydrologic data to the public can be improved by connecting data to the places they represent. In our example of data communication, we coupled hydrologic data with simultaneously collected video as both a scientific and public engagement tool. This note presents a method for collecting spatially and temporally dense datasets of water-quality and geophysical data on small streams and lakes, and for displaying the data in a user-friendly format using commercially available software. With this method, multiple instruments are mounted on a canoe and a controlled survey float is carried out to collect data. The data stream is georeferenced and logged using an Arduino microcontroller to provide detailed information about spatial variability. We employed these continuous data-collection methods at small streams and lakes across Wisconsin, USA. Comparison of stream-float sensor data to lab reported data, data collected by alternative sensors, and previously collected data in our study areas indicates that the low-cost temperature, electrical conductivity, pH, and dissolved oxygen sensors performed well. GoPro cameras recorded video throughout the duration of data collection. Our established water-quality and geophysical data collection methods are inexpensive, fast, and reliable, which qualify them as excellent tools for fine-scale spatial understanding of stream and lake habitats' health. Data-rich video connects point measurements of water properties to the appearance of the native environment. This method helps improve our understanding of groundwater and surface water interactions in complex hydrogeologic systems, enhance communication amongst stakeholders, and provide context when monitoring and managing sensitive habitats.     

On the coattails of climate? Opportunities and threats of a warming Earth for biodiversity conservation

The relationship between climate change and biodiversity was a central issue at the 10th Conference of the Parties (COP 10) to the Convention on Biological Diversity (CBD). In this paper we draw from participant observation data collected at COP 10, and related policy documentation, to examine how concerns about climate change are shaping the conservation policy landscape – in terms of the knowledge and rationales used as inputs, networks of actors involved, objectives sought, and actions proposed. We find that debates at the intersection of climate and biodiversity were overwhelmingly framed in relation to, or through the lens of carbon. Through a discussion of four core Climate-Motivated Responses, we illustrate how “carbon-logic”, and the initiatives that it generates, simultaneously creates threats to the objectives sought by some actors, and opportunities for the objectives sought by others. We situate our observations in the context of some of the historical dilemmas that have faced conservation, and discuss this current moment in the dynamic trajectory of conservation governance: a moment when decisions about conserving biodiversity are becoming entangled with carbon-logic and the market. In this case, while some actors seek opportunities for biodiversity ends by riding the coattails of the climate agenda, the threats of doing so may undermine the biological and social objectives of the CBD convention itself.     

Decadal evolution of anthropogenic CO2 in the northwestern Mediterranean Sea from the mid-1990s to the mid-2000s

Monthly observations accumulated over more than a decade at the DYFAMED time-series station allow us to estimate the temporal evolution of anthropogenic CO₂ in the western Mediterranean Sea. This objective is reached by using recognized interpolation procedures to reconstruct the incomplete distributions of measured total dissolved inorganic carbon and total alkalinity. These reconstructed fields, associated with those available for dissolved oxygen and temperature, are used to estimate the distribution of anthropogenic CO₂. This is done with the recently developed Tracer combining Oxygen, inorganic Carbon, and total alkalinity (TrOCA) approach. The main results indicate that (1) the concentrations of anthropogenic CO₂ are much higher than those found in the Atlantic Ocean (the minimum concentration at the DYFAMED site is 50 μmol kg⁻¹), and (2) the temporal trend for anthropogenic CO₂ is decreasing, especially in the intermediate and the deep layers of the water column at the DYFAMED site. This decrease in anthropogenic CO₂ is significantly correlated with a decrease in the dissolved oxygen and with an increase in both salinity and temperature. These trends are discussed in the light of recent published works that propose explanations for the observed increases in salinity and temperature that occurred in the western basin since the 1950s. We conclude that the decrease in anthropogenic CO₂ probably resulted from an invasion of old water masses. Different hypotheses on the origin of these water masses are considered and several arguments indicate that the eastern Mediterranean transient (EMT) could have played an important role in the observed decrease in anthropogenic CO₂ concentrations at the DYFAMED site.     

Semipermeable membrane devices link site-specific contaminants to effects: PART II - A comparison of lingering Exxon Valdez oil with other potential sources of CYP1A inducers in Prince William Sound, Alaska

We deployed semipermeable membrane devices (SPMDs) on beaches for 28 days at 53 sites in Prince William Sound (PWS), Alaska, to evaluate the induction potential from suspected sources of cytochrome P450 1A (CYP1A)-inducing contaminants. Sites were selected to assess known point sources, or were chosen randomly to evaluate the region-wide sources. After deployment, SPMD extracts were analyzed chemically for persistent organic pollutants (POPs) and polycyclic aromatic hydrocarbons (PAH). These results were compared with hepatic CYP1A enzyme activity of juvenile rainbow trout injected with the same extracts prior to clean-up for the chemical analyses. Increased CYP1A activity was strongly associated with PAH concentrations in extracts, especially chrysene homologues but was not associated with POPs. The only apparent sources of chrysene homologues were lingering oil from Exxon Valdez, asphalt and bunker fuels released from storage tanks during the 1964 Alaska earthquake, creosote leaching from numerous pilings at one site, and PAH-contaminated sediments at Cordova Harbor. Our results indicate that PWS is remarkably free of pollution from PAH when nearby sources are absent as well as from pesticides and PCBs generally.     

JPEG2000 Image Compression on Solar EUV Images

For future solar missions as well as ground-based telescopes, efficient ways to return and process data have become increasingly important. Solar Orbiter, which is the next ESA/NASA mission to explore the Sun and the heliosphere, is a deep-space mission, which implies a limited telemetry rate that makes efficient onboard data compression a necessity to achieve the mission science goals. Missions like the Solar Dynamics Observatory (SDO) and future ground-based telescopes such as the Daniel K. Inouye Solar Telescope, on the other hand, face the challenge of making petabyte-sized solar data archives accessible to the solar community. New image compression standards address these challenges by implementing efficient and flexible compression algorithms that can be tailored to user requirements. We analyse solar images from the Atmospheric Imaging Assembly (AIA) instrument onboard SDO to study the effect of lossy JPEG2000 (from the Joint Photographic Experts Group 2000) image compression at different bitrates. To assess the quality of compressed images, we use the mean structural similarity (MSSIM) index as well as the widely used peak signal-to-noise ratio (PSNR) as metrics and compare the two in the context of solar EUV images. In addition, we perform tests to validate the scientific use of the lossily compressed images by analysing examples of an on-disc and off-limb coronal-loop oscillation time-series observed by AIA/SDO.     

An automated cross‐validation method to assess seismic time‐to‐depth conversion accuracy: a case study on the Cooper and Eromanga basins,Australia

Selecting a seismic time‐to‐depth conversion method can be a subjective choice that is made by geophysicists, and is particularly difficult if the accuracy of these methods is unknown. This study presents an automated statistical approach for assessing seismic time‐to‐depth conversion accuracy by integrating the cross‐validation method with four commonly used seismic time‐to‐depth conversion methods. To showcase this automated approach, we use a regional dataset from the Cooper and Eromanga basins, Australia, consisting of 13 three‐dimensional (3D) seismic surveys, 73 two‐way‐time surface grids and 729 wells. Approximately 10,000 error values (predicted depth vs. measured well depth) and associated variables were calculated. The average velocity method was the most accurate overall (7.6 m mean error); however, the most accurate method and the expected error changed by several metres depending on the combination and value of the most significant variables. Cluster analysis tested the significance of the associated variables to find that the seismic survey location (potentially related to local geology (i.e. sedimentology, structural geology, cementation, pore pressure, etc.), processing workflow, or seismic vintage), formation (potentially associated with reduced signal‐to‐noise with increasing depth or the changes in lithology), distance to the nearest well control, and the spatial location of the predicted well relative to the existing well data envelope had the largest impact on accuracy. Importantly, the effect of these significant variables on accuracy were found to be more important than choosing between the four methods, highlighting the importance of better understanding seismic time‐to‐depth conversions, which can be achieved by applying this automated cross‐validation method.