Remote sensing of assimilation number for marine phytoplankton

Estimating primary production at large spatial scales is key to our understanding of the global carbon cycle. Algorithms to estimate primary production are well established and have been used in many studies with success. One of the key parameters in these algorithms is the chlorophyll-normalised production rate under light saturation (referred to as the light saturation parameter or the assimilation number). It is known to depend on temperature, light history and nutrient conditions, but assigning a magnitude to it at particular space-time points is difficult. In this paper, we explore two models to estimate the assimilation number at the global scale from remotely-sensed data that combine methods to estimate the carbon-to-chlorophyll ratio and the maximum growth rate of phytoplankton. The inputs to the algorithms are the surface concentration of chlorophyll, seasurface temperature, photosynthetically-active radiation af the surface of the sea, sea surface nutrient concentration and mixed-layer depth. A large database of in situ estimates of the assimilation number is used to develop the models and provide elements of validation. The comparisons with in situ observations are promising and global maps of assimilation number are produced.

Ovariole number - a predictor of differential reproductive success among worker subfamilies in queenless honeybee (Apis mellifera L.) colonies

A honeybee queen normally mates with 10-20 drones, and reproductive conflicts may arise among a colony's different worker patrilines, especially after a colony has lost its single queen and the workers commence egg laying. In this study, we employed microsatellite markers to study aspects of worker reproductive competition in two queenless Africanized honeybee colonies. First, we determined whether there was a bias among worker patrilines in their maternity of drones and, second, we asked whether this bias could be attributed to differences in the degree of ovary activation of workers. Third, we relate these behavioral and physiological factors to ontogenetic differences between workers with respect to ovariole number. Workers from each of three (colony A) and one (colony B) patrilineal genotypes represented less than 6% of the worker population, yet each produced at least 13% of the drones in a colony, and collectively they produced 73% of the drones. Workers representing these genotypes also had more developed follicles and a greater number of ovarioles per ovary. Across all workers, ovariole development and number were closely correlated. This suggests a strong effect of worker genotype on the development of the ovary already in the postembryonic stages and sets a precedent to adult fertility, so that

CO multipulse TAP studies of 2% Pt/CeO2 catalyst: Influence of catalyst pretreatment and temperature on the number of active sites observed

CO multipulse temporal analysis of products (TAP) experiments were used to characterize a ceria-supported platinum catalyst after various oxidative and reductive pretreatments using O-2, H2O, CO2, and H-2. Based on the amount of CO consumed, using the final CO-saturated catalyst composition as the common state point, the oxidatively pretreated catalyst could be described using a general scale. From a kinetic analysis of the CO multipulse responses, two kinetic regimes corresponding to two types of active sites could be identified. As the temperature was raised, the number of the most active sites did not change while the amount of the less active site increased. Comparison of the number of active sites determined from the TAP data reported herein with that determined by a previous steady-state isotope transient kinetic analysis experiment showed excellent agreement. This correlation indicates that the (very fast response) TAP experiments can provide information regarding the number and type of active sites that are relevant to a catalyst under real reaction conditions. (c) 2007 Elsevier Inc. All rights reserved.

Finding the magic number

Paul Wilson and Colin Cooper investigate methods used to extract the number of factors in a factor analysis