Benchmarking Optical/Thermal Satellite Imagery for Estimating Evapotranspiration and Soil Moisture in Decision Support Tools

Generally, one expects evapotranspiration (ET) maps derived from optical/thermal Landsat and MODIS satellite imagery to improve decision support tools and lead to superior decisions regarding water resources management. However, there is lack of supportive evidence to accept or reject this expectation. We “benchmark” three existing hydrologic decision support tools with the following benchmarks: annual ET for the ET Toolbox developed by the United States Bureau of Reclamation, predicted rainfall‐runoff hydrographs for the Gridded Surface/Subsurface Hydrologic Analysis model developed by the U.S. Army Corps of Engineers, and the average annual groundwater recharge for the Distributed Parameter Watershed Model used by Daniel B. Stephens & Associates. The conclusion of this benchmark study is that the use of NASA/USGS optical/thermal satellite imagery can considerably improve hydrologic decision support tools compared to their traditional implementations. The benefits of improved decision making, resulting from more accurate results of hydrologic support systems using optical/thermal satellite imagery, should substantially exceed the costs for acquiring such imagery and implementing the remote sensing algorithms. In fact, the value of reduced error in estimating average annual groundwater recharge in the San Gabriel Mountains, California alone, in terms of value of water, may be as large as $1 billion, more than sufficient to pay for one new Landsat satellite.     

Recycling food and agriculture by-products to mitigate climate change: a review

Food loss and waste is a major issue affecting food security, environmental pollution, producer profitability, consumer prices, and climate change. About 1.3 billion tons of food products are yearly lost globally, with China producing approximately 20 million tons of soybean dregs annually. Here, we review food and agricultural byproducts with emphasis on the strategies to convert this waste into valuable materials. Byproducts can be used for animal and plant nutrition, biogas production, food, extraction of oils and bioactive substances, and production of vinegar, wine, edible coatings and organic fertilizers. For instance, bioactive compounds represent approximately 8–20% of apple pomace, 5–17% of orange peel, 10–25% of grape seeds, 3–15% of pomegranate peel, and 2–13% of date palm seeds. Similarly, the pharmaceutical industry uses approximately 6.5% of the total output of gelatin derived from fish bones and animal skin. Animals fed with pomegranate peel and olive pomace improved the concentration of deoxyribonucleic acid and protein, the litter size, the milk yield, and nest characteristics. Biogas production amounts to 57.1% using soybean residue, 53.7% using papaya peel, and 49.1% using sugarcane bagasse.

     

Trauma demography and clinical epidemiology of motorcycle crash–related head injury in a neurosurgery practice in an African developing country

Objective: Though motor vehicle crashes (MVCs) were the main cause of head trauma from road traffic injuries (RTIs), motorcycle crashes (MCCs) are now a major cause of RTI-related head injury (HI) in many developing countries.

Methods: Using a prospective database of HIs from a neurosurgical practice in a sub-Saharan African developing country, a cross-sectional survey was conducted for the trauma demography and clinical epidemiology of this MCC-related HI.

Results: Motorcycle crashes accounted for 57% (473/833) of all RTI-related HIs in this registry. The victims, with a mean age of 33.1 years (SD = 18.3), consisted mainly of males (83.1%), those of low socioeconomic status (>90%), and those aged between 20 and 40 years old (56%). MCCs involved only riders in 114 cases (114/473, 32.1%), of which 69% were motorcycle–motorcycle crashes. The HI was moderate–severe in 50.8%; clinical symptomatology of significant HI included loss of consciousness (92%), anisocoria (35%), Abbreviated Injury Scale head (AIS–head) score > 3 (28%), and CT-Rotterdam score > 3 (30%). Extracranial systemic injury involved the limbs most frequently, with an Injury Severity Score (ISS) >25 in 49%. The fatality rate was 24%.

MCC-related HI among pedestrian victims involved more vulnerable age groups (the young and elderly) but have lower mean ISS compared to motorcycle passengers (mean ISS = 23.5 [11.6] vs. 27.4 [13.0]; 95% confidence interval [CI], 1.27–6.49; P = .004). In addition, compared to a contemporary cohort of MVC-related HIs in our registry, MCC victims were older (mean age 34.8 years [18.0] vs. 30.8 [18.4]; P = .002); had higher proportions of certain extracranial trauma like long bone fractures (71 vs. 29%; P = .02); and suffered fewer surgical brain lesions (25.5 vs. 17.2%; P = .004).

Conclusions: Motorcycle crashes are now a significant threat to the heads, limbs, and lives of vulnerable road users in developing countries.     

Motivated to disengage: The ethical consequences of goal commitment and moral disengagement in goal setting

A growing literature has suggested that high performance goals can have unintended consequences within organizations as employees engage in unethical behavior to achieve outcomes associated with goal attainment. Extending research on the dark side of goal setting, we suggest that high performance goals not only create a desire to achieve a particular outcome but also alter moral reasoning processes related to goal attainment. Integrating goal-setting theory with motivated moral reasoning, we hypothesize an indirect effect of high performance goals on unethical behavior via state moral disengagement. We also examine goal commitment—which tends to amplify the relationship between high goals and performance—as a key boundary condition associated with this indirect effect. We build this conditional indirect effect model across three studies conducted in the field and the laboratory. Our results provide new insight into both when and why high goals can facilitate moral disengagement and unethical behavior within organizations.     

Use of Predictive Weather Uncertainties in an Irrigation Scheduling Tool Part II: An Application of Metrics and Adjoints

We apply predictive weather metrics and land model sensitivities to improve the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE is an irrigation decision aid that integrates environmental and user information for optimizing water use. Rainfall forecasts and verification performance metrics are used to estimate predictive rainfall probabilities that are used as input data within the irrigation decision aid. These input data errors are also used within a land model sensitivity study to diagnose important prognostic water movement behaviors for irrigation tool development purposes simultaneously performing the analysis in space and time. Thus, important questions such as “how long can a crop water application be delayed while maintaining crop yield production?” are addressed by evaluating crop growth stage interactions as a function of soil depth (i.e., space), rainfall events (i.e., time), and their probabilistic uncertainties. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

Adaptation of Climate Model Projections of Streamflow to Account for Upstream Anthropogenic Impairments

A statistical procedure is developed to adjust natural streamflows simulated by dynamical models in downstream reaches, to account for anthropogenic impairments to flow that are not considered in the model. The resulting normalized downstream flows are appropriate for use in assessments of future anthropogenically impaired flows in downstream reaches. The normalization is applied to assess the potential effects of climate change on future water availability on the Rio Grande at a gage just above the major storage reservoir on the river. Model‐simulated streamflow values were normalized using a statistical parameterization based on two constants that relate observed and simulated flows over a 50‐year historical baseline period (1964–2013). The first normalization constant is a ratio of the means, and the second constant is the ratio of interannual standard deviations between annual gaged and simulated flows. This procedure forces the gaged and simulated flows to have the same mean and variance over the baseline period. The normalization constants can be kept fixed for future flows, which effectively assumes that upstream water management does not change in the future, or projected management changes can be parameterized by adjusting the constants. At the gage considered in this study, the effect of the normalization is to reduce simulated historical flow values by an average of 72% over an ensemble of simulations, indicative of the large fraction of natural flow diverted from the river upstream from the gage. A weak tendency for declining flow emerges upon averaging over a large ensemble, with tremendous variability among the simulations. By the end of the 21st Century the higher‐emission scenarios show more pronounced declines in streamflow.     

A framework for understanding climate change impacts on coral reef social–ecological systems

Corals and coral-associated species are highly vulnerable to the emerging effects of global climate change. The widespread degradation of coral reefs, which will be accelerated by climate change, jeopardizes the goods and services that tropical nations derive from reef ecosystems. However, climate change impacts to reef social–ecological systems can also be bi-directional. For example, some climate impacts, such as storms and sea level rise, can directly impact societies, with repercussions for how they interact with the environment. This study identifies the multiple impact pathways within coral reef social–ecological systems arising from four key climatic drivers: increased sea surface temperature, severe tropical storms, sea level rise and ocean acidification. We develop a novel framework for investigating climate change impacts in social–ecological systems, which helps to highlight the diverse impacts that must be considered in order to develop a more complete understanding of the impacts of climate change, as well as developing appropriate management actions to mitigate climate change impacts on coral reef and people.     

Integrated spatial health assessment of yellow perch (<Emphasis Type="Italic">Perca flavescens</Emphasis>) populations from the St. Lawrence River,Quebec, Canada) part A: physiological parameters and pathogen assessment

A multi-disciplinary approach was used to evaluate the health of yellow perch (Perca flavescens) in the St. Lawrence River (Quebec, Canada), which is experiencing a severe population decline in the downstream portion of the river. Physiological parameters, liver alterations, trace metal concentrations, parasite prevalence and abundance, stable isotope composition, and the presence/absence of the viral hemorragic septicemia virus (VHSV) were evaluated in perch collected at six sites along the river: Lake St. François, Lake St. Louis (north and south), Beauregard Island, and Lake St. Pierre (north and south). Trace metal concentrations in surface water were higher in Lake St. Louis and downstream of a major urban wastewater treatment plant discharge, indicating that this effluent was a significant source of Cu, As, Ag, Zn, and Cd. Levels of Pb in surface water exceeded thresholds for the protection of aquatic life in Lake St. Louis and were negatively correlated with body condition index in this lake. In Lake St. Pierre, Cu, Ag, and Cd bioaccumulated significantly in perch liver and lower body condition index and greater liver damage were observed compared to upstream sites. Parasite analyses indicated a higher abundance of metacercariae of the trematodes Apophallus brevis and Diplostomum spp. in Lake St. Louis, and VHSV was not detected in the liver of yellow perch for all studied sites. Overall, results suggested that the global health of yellow perch from Lake St. Pierre is lower compared to upstream studied sites, which could contribute to the documented population collapse at this site.     

Fatty acids composition of Caenorhabditis elegans using accurate mass GCMS-QTOF

The free living nematode Caenorhabditis elegans is a proven model organism for lipid metabolism research. Total lipids of C. elegans were extracted using chloroform and methanol in 2:1 ratio (v/v). Fatty acids composition of the extracted total lipids was converted to their corresponding fatty acids methyl esters (FAMEs) and analyzed by gas chromatography/accurate mass quadrupole time of flight mass spectrometry using both electron ionization and chemical ionization techniques. Twenty-eight fatty acids consisting of 12 to 22 carbon atoms were identified, 65% of them were unsaturated. Fatty acids containing 12 to17 carbons were mostly saturated with stearic acid (18:0) as the major constituent. Several branched-chain fatty acids were identified. Methyl-14-methylhexadecanoate (iso- 17:0) was the major identified branched fatty acid. This is the first report to detect the intact molecular parent ions of the identified fatty acids in C. elegans using chemical ionization compared to electron ionization which produced fragmentations of the FAMEs.