Spatio-temporal Bayesian network models with latent variables for revealing trophic dynamics and functional networks in fisheries ecology

Ecosystems consist of complex dynamic interactions among species and the environment, the understanding of which has implications for predicting the environmental response to changes in climate and biodiversity. However, with the recent adoption of more explorative tools, like Bayesian networks, in predictive ecology, few assumptions can be made about the data and complex, spatially varying interactions can be recovered from collected field data. In this study, we compare Bayesian network modelling approaches accounting for latent effects to reveal species dynamics for 7 geographically and temporally varied areas within the North Sea. We also apply structure learning techniques to identify functional relationships such as prey–predator between trophic groups of species that vary across space and time. We examine if the use of a general hidden variable can reflect overall changes in the trophic dynamics of each spatial system and whether the inclusion of a specific hidden variable can model unmeasured group of species. The general hidden variable appears to capture changes in the variance of different groups of species biomass. Models that include both general and specific hidden variables resulted in identifying similarity with the underlying food web dynamics and modelling spatial unmeasured effect. We predict the biomass of the trophic groups and find that predictive accuracy varies with the models' features and across the different spatial areas thus proposing a model that allows for spatial autocorrelation and two hidden variables. Our proposed model was able to produce novel insights on this ecosystem's dynamics and ecological interactions mainly because we account for the heterogeneous nature of the driving factors within each area and their changes over time. Our findings demonstrate that accounting for additional sources of variation, by combining structure learning from data and experts' knowledge in the model architecture, has the potential for gaining deeper insights into the structure and stability of ecosystems. Finally, we were able to discover meaningful functional networks that were spatially and temporally differentiated with the particular mechanisms varying from trophic associations through interactions with climate and commercial fisheries.

The Juniper formations in the Djurdjura (Algerie): an interpretation of the importance of their ecology, dynamics and syntoxonomy in the Kabylian cedar forest as a whole

The authors propose a new phyiosociologic interpretation of Juniperas comniunis subsp. hemisphaerica and Juniperus sabina shrublands in the Djurdjura. They make up two new associations: the Cynosuro balansae-Juniperetun, hemisphaericae and the Daphno oleoidis-Juniperetum sabinae, belonging to the new alliance Lonicero kabylicae-Juniperion hemisphaericae included in the order Querco Cedretalia atlanticae. The ecologic and biogeograpbic value of these communities is analized in a Westem-mediterrancan context as well as their dynamic importance. On this mountain, they correspond to ihe preforested level of cedar forests. For this reason, an attempt to inlerprel Kabylian cedar forests as a whole was made they belong to the new association Senecio perralderlani-Cedretum atlanticae. A diachronic evaluation of changes in native plant communities over a 30 year period is made, in particular as related to the creation of several local structures to protect natural resources.

Brassica oleracea L. distribution and ecology in the Iberian atlantic coasts

The distribution and ecology of Brassica oleracea in the atlantic coasts of Iberian Peninsule are studied. A new association or nitrified maritime cliffs is described: Crithmo-Brassicetum oleraceae. This community has been included in the Alliance Crithmo-Armerion due to the high presence of halophitic species.

Xanthoria parietina as a biomonitor of airborne heavy metal pollution in forest sites in the North East of Morocco

Xanthoria parietina, common foliose lichen, growing in its natural habitat, was analysed for the concentration of five heavy metals (Fe, Cr, Zn, Pb and Cu) from different forest sites of North East of Morocco (Kenitra, Sidi Boughaba, Mkhinza, Ceinture Verte near Temara city, Skhirate, Bouznika and Mohammedia). The quantification was carried out by inductively coupled plasma - atomic emission spectrometry (ICP-AES). Results were highly significant p<0,001. The concentration of metals is correlated with the vehicular activity and urbanization. The total metal concentration is highest at the Kenitra area, followed by Ceinture Verte site near Temara city, which experience heavy traffic throughout the year. Scanning electron microscopy (SEM) of particulate matter on lichen of Xanthoria parietina was assessed as a complementary technique to wet chemical analysis for source apportionment of airborne contaminant. Analysis revealed high level of Cu, Cr, Zn and Pb in samples near roads.  

Chloroplast microsatellites: new tools for studies in plant ecology and systematics

The nonrecombinant, uniparentally inherited nature of organelle genomes
makes them useful tools for evolutionary studies. However, in plants, detecting
useful polymorphism at the population level is often difficult because of the
low level of substitutions in the chloroplast genome, and because of the slow
substitution rates and intramolecular recombination of mtDNA. Chloroplast
microsatellites represent potentially useful markers to circumvent this problem
and, to date, studies have demonstrated high levels of intraspecific variability.
Here,we discuss the use of these markers in ecological and evolutionary
studies of plants, as well as highlighting some of the potential problems
associated with such use.

Structural and functional basis for ADP-ribose and poly(ADP-ribose) binding by viral macro domains.

Macro domains constitute a protein module family found associated with specific histones and proteins involved in chromatin metabolism. In addition, a small number of animal RNA viruses, such as corona- and toroviruses, alphaviruses, and hepatitis E virus, encode macro domains for which, however, structural and functional information is extremely limited. Here, we characterized the macro domains from hepatitis E virus, Semliki Forest virus, and severe acute respiratory syndrome coronavirus (SARS-CoV). The crystal structure of the SARS-CoV macro domain was determined at 1.8-Å resolution in complex with ADP-ribose. Information derived from structural, mutational, and sequence analyses suggests a close phylogenetic and, most probably, functional relationship between viral and cellular macro domain homologs. The data revealed that viral macro domains have relatively poor ADP-ribose 1"-phosphohydrolase activities (which were previously proposed to be their biologically relevant function) but bind efficiently free and poly(ADP-ribose) polymerase 1-bound poly(ADP-ribose) in vitro. Collectively, these results suggest to further evaluate the role of viral macro domains in host response to viral infection.

Long-term ecology of native pinewood communities in East Glen Affric, Scotland

Fossil pollen, stomata and charcoal were examined from a lake sedimentary sequence in the Glen Affric National Nature Reserve, one of the largest areas of remnant native pine woodland in Scotland, in order to assess ecosystem dynamics over the last 11 000 years. Results reveal that pinewood communities have been continuously present in East Glen Affric for the last 8300 years. Pinus sylvestris fi rst arrived in the area around 9900 cal. BP, but occurred in only low abundance for the subsequent 1600 years. Pine populations expanded around 8300 cal. BP and remained in relatively constant abundance throughout the remainder of the Holocene. There is no evidence of a hypothesized regional mid-Holocene ‘ pine decline ’ at the site. Charcoal results reveal that pinewood communities in East Glen Affric do not appear to have been dependent on fire for either their establishment or their maintenance as has previously been suggested.

Marine micro and macro algal species as biosorbents for heavy metals

This paper reviews some practical aspects of the application of algal biomass for the biosorption of heavy metals from wastewater. The ability of different algal species to remove metals varies with algal group and morphology, with the speciation of specific metals and their competition with others in wastewater, and with environmental or process factors. The scattered literature on the uptake of heavy metals by both living and dead algal biomass - both macroalgae and immobilized microalgae - has been reviewed, and the uptake capacity and efficiency of different species, as well as what is known about the mechanisms of biosorption, are presented. Data on metal uptake have commonly been fitted to equilibrium models, such as the Langmuir and Freundlich isotherm models, and the parameters of these models permit the uptake capacity of different algal species under different process conditions to be compared. Higher uptake capacities have been found for brown algae than for red and green algae. Kelps and fucoids are the most important groups of algae used for biosorption of heavy metals, probably because of their abundant cell wall polysacchrides and extracellular polymers. Another important practical aspect is the possibility of re-using algal biomass in several adsorption/desorption cycles (up to 10 have been used with Sargassum spp), and the influence of morphology and environmental conditions on the re-usability of algal tissue is also considered.