How wave exposure, group size and habitat complexity influence foraging and population densities in fishes of the genus Halichoeres (Perciformes: Labridae) on tropical rocky shores

Wave exposure and habitat complexity have been used to explain variations in the distribution patterns and behavior of many reef fishes. This study analyzed the influence of both factors on density and foraging activity, and the influence of group size on foraging in three species of the genus Halichoeres (Labridae) on tropical rocky shores. It was shown that initial phases (IP) and terminal phases (TP) Halichoeres, were influenced by wave exposure, although foraging in Halichoeres brasiliensis TP was not influenced by wave exposure. The IP in all three species were positively associated with rugosity and algal cover while the TP was positively associated with depth. Habitat complexity also influences foraging in these species. Group size influenced foraging activity, except in H. brasiliensis TP. We also found variations in microhabitat patches used for foraging between species and differences in the stomach contents between species and phases, showing that functional roles change in response to ontogenetic shifts.     

Environmental performance evaluation of agro-industrial innovations – Part 2: methodological approach for performing vulnerability analysis of watersheds

Environmental vulnerability analysis has been sparsely used in environmental performance evaluation (EPE) of technological innovations. The present paper proposes a methodological approach to carry out vulnerability analysis of watersheds and to integrate this analysis into methods of environmental performance evaluation of agro-industrial innovations. This approach is applied to the Ambitec-Life Cycle method, described in Part 1 (this issue) of this study. The case study of green coconut substrate compared to ripe coconut substrate, also described in Part 1 (this issue), is now presented considering the vulnerability analysis of the watersheds where the life cycle stages of these products occur. The integration of vulnerability analysis in Ambitec-Life Cycle contributes to a better understanding of the environmental aspects of agro-industrial technological innovations with potential to cause significant impacts in watersheds where these innovations are implemented.     

Preimplantation genetic diagnosis using FISH for carriers of Robertsonian translocations: the Portuguese experience

Preimplantation genetic diagnosis (PGD) is an alternative to prenatal diagnosis for couples at risk of transmitting genetic disorders to their offspring. We present a fluorescence in situ hybridization (FISH) analysis of embryos obtained after seven PGD cycles in six couples with Robertsonian translocations and male factor infertility: 4 der(13;14), 1 der(14;21) and 1 der(15;21). Of 74 metaphase II (MII) injected oocytes, 61 (82.4%) fertilized normally and cleaved. Of these, 37/61 (60.7%) embryos were of high morphological quality with ≥6 blastomeres. After biopsy of 44 embryos at day 3 of development, seven degenerated, seven arrested in development and 30/44 (68.2%) evolved, of which 25/30 (83.3%) reached the morula/blastocyst stage. Analysis of biopsied blastomeres showed 23/44 (52.3%) of normal/balanced embryos, of which 15 (11 at the morula/blastocyst stage) were transferred in six cycles. One term pregnancy was achieved, which ended by cesarean section at 37 weeks of gestation, giving birth to two healthy newborn. Analysis of 49 embryos (excluding 12 inconclusive cases) showed a predominance of alternate segregation (38/49, 77.6%) over adjacent segregation (7/49, 14.3%), with one (2%) being a polyploid mosaic and three (6.1%) chaotic. Copyright © 2002 John Wiley & Sons, Ltd.     

Artificial neural network modeling of caste odor discrimination based on cuticular hydrocarbons in termites

Summary. Individuals in an insect colony need to identify one another according to caste. Nothing is known about the sensory process allowing nestmates to discriminate minute variations in the cuticular hydrocarbon mixture. The purpose of this study was to attempt to model caste odors discrimination in four species of Reticulitermes termites for the first time by a non-linear mathematical approach using an "artificial neural network" (ANN). Several rounds of testing were carried out using 1 – the whole hydrocarbon mixtures 2 – mixtures containing the hydrocarbons selected by principal component analysis (PCA) as the most implicated in caste discrimination. Discrimination between worker and soldier castes was tested in all four species. For two species we tested discrimination of four castes (workers, soldiers, nymphs, neotenics). To test cuticular pattern similarity in two sibling species (R. santonensis and R. flavipes), we performed two experiments using one species for training and the other for query. Using whole hydrocarbons mixtures, worker/soldier discrimination was always successful in all species. Network performance decreased with the number of hydrocarbons used as inputs. Four-caste discrimination was less successful. In the experiment with the sibling species, the ANN was able to distinguish soldiers but not workers. The results of this study suggest that non-linear mathematical analysis is a good tool for classification of castes based on cuticular hydrocarbon mixture. In addition this study confirms that hydrocarbon mixtures observed are real chemical entities and constitute a true chemical signature or odor. Whole mixtures are not always necessary for discrimination. Received 23 July 1998; accepted 9 October 1998.     

Chemical and bacterial changes during laboratory conditioning of formulated and natural sediments

Within the framework of toxicity testing using formulated sediment, a conditioning treatment prior to toxic contamination has been examined. This preliminary step enables the bacterial colonisation of the sediment, the initiation of organic matter degradation, and the establishment of stable biological and physico-chemical conditions. The treatment involved in keeping the formulated sediment under water in conditions similar to that chosen for toxicity tests. The behaviour of a formulated sediment was compared with a natural sediment. The monitoring of physico-chemical and biological parameters of sediment and water column was carried out over a 30-day incubation in two laboratories. The parameters of pH and redox, dissolved organic carbon (DOC), NH4 and NO2, total organic carbon (TOC) were measured. The bacterial community was characterised by the determination of bacterial density, in total bacteria number or colony forming units (CFU), several exoenzymatic activities (P-glucosidase, xylosidase, leucine-amino-peptidase phosphatase and sulfatase activities), and three gas productions (CO2, N2O and CH4). The same experiment was carried out with a natural sediment. A 10- to 15-day conditioning allowed a physico-chemical stabilisation and corresponded to kinetic changes in hydrolysis activities. As compared to data of the natural sediment, the biological activity of the formulated sediment showed a different dynamic with lower activity levels. For both sediments, an important decrease of activities levels was observed after 15 days because of a substrate limitation. The work showed that a preliminary conditioning treatment of a formulated sediment provides the stabilisation of parameters that can affect toxicant bioavailability. Additional research is needed to determine the real influence of conditioning on the bioavailability of contaminants. The possible advisability of organic matter input, to maintain the sediment bacterial activity, has to be studied.     

Remote sensing for mapping algal blooms in freshwater lakes: a review

Environmental Science and Pollution Research - A large number of freshwater lakes around the world show recurring harmful algal blooms, particularly cyanobacterial blooms, that affect public health...     

Bayesian estimation of species relative abundances and habitat preferences using opportunistic data

We develop a new statistical procedure to monitor relative species abundances and their respective preferences for different habitat types, using opportunistic data. Following Giraud et al. (Biometrics 72(2):649–658, 2015), we combine the opportunistic data with some standardized data in order to correct the bias inherent to the opportunistic data collection. Species observations are modeled by Poisson distributions whose parameters quantify species abundances and habitat preferences, and are estimated using Bayesian computations. Our main contributions are (i) to tackle the bias induced by habitat selection behaviors, (ii) to handle data where the habitat type associated to each observation is unknown, (iii) to estimate probabilities of selection of habitat for the species. As an illustration, we estimate common bird species habitat preferences and abundances in the region of Aquitaine (France).