A Possible Role Of Alpha-Amylase Isoenzymes From The Style Of The Mussel Choromytilus-Meridionalis (Krauss) Following Thermal-Acclimation

Separation of the proteins comprising the crystalline style of the mussel Choromytilus meridionalis (Krauss) by anion exchange chromatography shows that there are three fractions displaying α-amylase activity in both warm- and cold-acclimated mussels. These fractions correspond with one or more proteins which remain unbound to the resin (Peak I), a bound fraction which is eluted at 100–150 mM NaCl (Peak II) and a further fraction which is eluted at 200–250 mM NaCl (Peak III) but which may represent contamination carried over from Peak II. Cold-acclimation to 8°C results in the appearance of a fourth α-amylase fraction (Peak IV) which is eluted from the column between 300–400 mM NaCl. Thermal acclimation also results in changes in the activities of Fractions I–IV such that a specific activity of 0.47 mg glucose liberated per A280 unit of protein per 8 min incubation at 8°C in Fraction IV is increased nearly 10-fold to a specific rate of 4.10 in protein Fraction I following acclimation to 22°C. It is suggested that an increased of digestive activity may be of equal importance to a suppression of metabolic costs in the maintenance of energy flow into growth and reproduction in ectothermic organisms which experience an increase of environmental temperature, especially in bivalves such as C. meridionalis which do not show a compensatory increase in filtration rate.

Evaluating the SEVIRI Fire Thermal Anomaly Detection Algorithm across the Central African Republic Using the MODIS Active Fire Product

Satellite-based remote sensing of active fires is the only practical way to consistently and continuously monitor diurnal fluctuations in biomass burning from regional, to continental, to global scales. Failure to understand, quantify, and communicate the performance of an active fire detection algorithm, however, can lead to improper interpretations of the spatiotemporal distribution of biomass burning, and flawed estimates of fuel consumption and trace gas and aerosol emissions. This work evaluates the performance of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) Fire Thermal Anomaly (FTA) detection algorithm using seven months of active fire pixels detected by the Moderate Resolution Imaging Spectroradiometer (MODIS) across the Central African Republic (CAR). Results indicate that the omission rate of the SEVIRI FTA detection algorithm relative to MODIS varies spatially across the CAR, ranging from 25% in the south to 74% in the east. In the absence of confounding artifacts such as sunglint, uncertainties in the background thermal characterization, and cloud cover, the regional variation in SEVIRI's omission rate can be attributed to a coupling between SEVIRI's low spatial resolution detection bias (i.e., the inability to detect fires below a certain size and intensity) and a strong geographic gradient in active fire characteristics across the CAR. SEVIRI's commission rate relative to MODIS increases from 9% when evaluated near MODIS nadir to 53% near the MODIS scene edges, indicating that SEVIRI errors of commission at the MODIS scene edges may not be false alarms but rather true fires that MODIS failed to detect as a result of larger pixel sizes at extreme MODIS scan angles. Results from this work are expected to facilitate (i) future improvements to the SEVIRI FTA detection algorithm; (ii) the assimilation of the SEVIRI and MODIS active fire products; and (iii) the potential inclusion of SEVIRI into a network of geostationary sensors designed to achieve global diurnal active fire monitoring.