Satellite Rainfall Estimates Over South America – Possible Applicability to the Water Management of Large Watersheds1

Pereira Filho, Augusto J., Richard E. Carbone, John E. Janowiak, Phillip Arkin, Robert Joyce, Ricardo Hallak, and Camila G.M. Ramos, 2010. Satellite Rainfall Estimates Over South America – Possible Applicability to the Water Management of Large Watersheds. Journal of the American Water Resources Association (JAWRA) 46(2):344-360. DOI: 10.1111/j.1752-1688.2009.00406.x Abstract: This work analyzes high-resolution precipitation data from satellite-derived rainfall estimates over South America, especially over the Amazon Basin. The goal is to examine whether satellite-derived precipitation estimates can be used in hydrology and in the management of larger watersheds of South America. High spatial-temporal resolution precipitation estimates obtained with the CMORPH method serve this purpose while providing an additional hydrometeorological perspective on the convective regime over South America and its predictability. CMORPH rainfall estimates at 8-km spatial resolution for 2003 and 2004 were compared with available rain gauge measurements at daily, monthly, and yearly accumulation time scales. The results show the correlation between satellite-derived and gauge-measured precipitation increases with accumulation period from daily to monthly, especially during the rainy season. Time-longitude diagrams of CMORPH hourly rainfall show the genesis, strength, longevity, and phase speed of convective systems. Hourly rainfall analyses indicate that convection over the Amazon region is often more organized than previously thought, thus inferring that basin scale predictions of rainfall for hydrological and water management purposes have the potential to become more skillful. Flow estimates based on CMORPH and the rain gauge network are compared to long-term observed average flow. The results suggest this satellite-based rainfall estimation technique has considerable utility. Other statistics for monthly accumulations also suggest CMORPH can be an important source of rainfall information at smaller spatial scales where in situ observations are lacking.     

Leveraging social media and deep learning to detect rare megafauna in video surveys

Deep learning has become a key tool for the automated monitoring of animal populations with video surveys. However, obtaining large numbers of images to train such models is a major challenge for rare and elusive species because field video surveys provide few sightings. We designed a method that takes advantage of videos accumulated on social media for training deep-learning models to detect rare megafauna species in the field. We trained convolutional neural networks (CNNs) with social media images and tested them on images collected from field surveys. We applied our method to aerial video surveys of dugongs (Dugong dugon) in New Caledonia (southwestern Pacific). CNNs trained with 1303 social media images yielded 25% false positives and 38% false negatives when tested on independent field video surveys. Incorporating a small number of images from New Caledonia (equivalent to 12% of social media images) in the training data set resulted in a nearly 50% decrease in false negatives. Our results highlight how and the extent to which images collected on social media can offer a solid basis for training deep-learning models for rare megafauna detection and that the incorporation of a few images from the study site further boosts detection accuracy. Our method provides a new generation of deep-learning models that can be used to rapidly and accurately process field video surveys for the monitoring of rare megafauna.     

Sunlight-driven environmental photodegradation of 2-chlorobiphenyl (PCB-1) in surface waters: kinetic study and mathematical simulations

Environmental Science and Pollution Research - Polychlorinated biphenyls (PCBs) are a family of highly toxic, resistant, and persistent organic pollutants, among which 2-chlorobiphenyl (PCB-1) is...     

The Incidence of Tariff Schedules and Price Information on Inattentive Consumers: a Lab Experiment

We design an induced value laboratory consumption choice experiment where complex tariff schemes trigger nonlinear simplification heuristics that lead individuals to over- or underconsume public goods such as electricity, gas, or drinking water. By studying this “schmeduling” bias, we investigate how an informational nudge could reduce it. Participants choose consumption levels repeatedly under different tariff schemes, where the marginal price per unit either remains constant (constant block rate, i.e., CBR) or increases above a certain threshold (increasing block rate, or IBR). We observe that the vast majority of choices are optimal, but a significant number of them reveal overconsumption. To investigate the impact of the informational nudge on these errors, some of our participants received a marginal price reminder. In that case, the learning effect helps to achieve convergence towards the optimal consumption value. To explain these effects, we use econometric models relying on microeconomic behavioral inattention to price to capture the magnitude of consumers’ inattention, observing, in particular, how the informational nudge is decreasing it.

     

A review of postfeeding larval dispersal in blowflies: implications for forensic entomology

Immature and adult stages of blowflies are one of the primary invertebrate consumers of decomposing animal organic matter. When the food supply is consumed or when the larvae complete their development and migrate prior to the total removal of the larval substrate, they disperse to find adequate places for pupation, a process known as postfeeding larval dispersal. Several important ecological and physiological aspects of this process were studied since the work by Green (Ann Appl Biol 38:475, 1951) 50 years ago. An understanding of postfeeding larval dispersal can be useful for determining the postmortem interval (PMI) of human cadavers in legal medicine, particularly because this interval may be underestimated if older dispersing larvae or those that disperse longer, faster, and deeper are not taken into account. In this article, we review the process of postfeeding larval dispersal and its implications for legal medicine, in particular showing that aspects such as burial behavior and competition among species of blowflies can influence this process and consequently, the estimation of PMI.     

Biotransformation of the flame retardant tetrabromo-bisphenol A by human and rat sub-cellular liver fractions

The comparative in vitro metabolism of the flame retardant tetrabromo-bisphenol A was studied in rat and human using a [(14)C]-radio-labelled molecule. Tetrabromo-bisphenol A is metabolised into the corresponding glucuronide (liver S9 fractions) and several other metabolites produced by cytochrome P450 dependent pathways (liver microsomes and liver S9 fractions). No major qualitative differences were observed between rat and human, regardless of the selected concentration, within the 20-200 microM range. Tetrabromo-bisphenol A undergoes an oxidative cleavage near the central carbon of the molecule, that leads to the production of hydroxylated dibromo-phenol, hydroxylated dibromo-isopropyl-phenol and glutathione conjugated dibromo-isopropyl-phenol. The main metabolites of tetrabromo-bisphenol A are two molecules of lower polarity than the parent compound, characterised as a hexa-brominated compound with three aromatic rings and a hepta-brominated dimer-like compound, respectively. Both structures, as well as the lower molecular weight metabolites resulting from the breakdown of the molecule, suggest the occurrence of chemically reactive intermediates formed following a first step oxidation of tetrabromo-bisphenol A.     

Modelling of paralytic shellfish toxin biotransformations in the course of Crassostrea gigas detoxification kinetics

The aim of this study was to evaluate the importance of biotransformation of paralytic shellfish toxins during the detoxification process in contaminated oysters. Mathematical models based upon the detoxification patterns of digestive gland and other tissues were developed. It was demonstrated that biotransformations do not seem to play an important role in digestive gland or other tissue detoxification kinetics with our data set. Moreover, different toxin transfers from digestive gland toward other tissues were investigated. No significant transfer was highlighted in our data set. These first conclusions were drawn after comparing the results obtained from 13 biotransformations and identifiable transfer scenarios. Finally, to determine a more robust model, all 12 states corresponding to toxic compounds and tissues were aggregated into a single state model. The best adjustment was obtained with a simple one-compartment model based on total flesh toxicity with elimination rate expressed by a function depending on initial concentrations of GTX3 and GTX2 (i.e. the two major toxic compounds found in contaminated oysters).