Basking sharks and oceanographic fronts: quantifying associations in the north-east Atlantic

Understanding the mechanisms linking oceanographic processes and marine vertebrate habitat use is critical to effective management of populations of conservation concern. The basking shark Cetorhinus maximus has been shown to associate with oceanographic fronts – physical interfaces at the transitions between water masses – to exploit foraging opportunities resulting from aggregation of zooplankton. However, the scale, significance and variability of these observed associations have not yet been established. Here, we quantify the influence of mesoscale (10s – 100s km) frontal activity on habitat use over timescales of weeks to months. We use animal-mounted archival tracking with composite front mapping via Earth Observation (EO) remote sensing to provide an oceanographic context to individual shark movements. We investigate levels of association with fronts occurring over two spatio-temporal scales, (i) broad-scale seasonally persistent frontal zones and (ii) contemporaneous mesoscale thermal and chl-a fronts. Using random walk simulations and logistic regression within an iterative generalised linear mixed modelling (GLMM) framework, we find that seasonal front frequency is a significant predictor of shark presence. Temporally-matched oceanographic metrics also indicate that sharks demonstrate a preference for productive regions, and associate with contemporaneous thermal and chl-a fronts more frequently than could be expected at random. Moreover, we highlight the importance of cross-frontal temperature change and persistence, which appear to interact to affect the degree of prey aggregation along thermal fronts. These insights have clear implications for understanding the preferred habitats of basking sharks in the context of anthropogenic threat management and marine spatial planning in the northeast Atlantic.

Basking sharks and oceanographic fronts: quantifying associations in the north-east Atlantic

Understanding the mechanisms linking oceanographic processes and marine vertebrate habitat use is critical to effective management of populations of conservation concern. The basking shark Cetorhinus maximus has been shown to associate with oceanographic fronts – physical interfaces at the transitions between water masses – to exploit foraging opportunities resulting from aggregation of zooplankton. However, the scale, significance and variability of these observed associations have not yet been established. Here, we quantify the influence of mesoscale (10s – 100s km) frontal activity on habitat use over timescales of weeks to months. We use animal-mounted archival tracking with composite front mapping via Earth Observation (EO) remote sensing to provide an oceanographic context to individual shark movements. We investigate levels of association with fronts occurring over two spatio-temporal scales, (i) broad-scale seasonally persistent frontal zones and (ii) contemporaneous mesoscale thermal and chl-a fronts. Using random walk simulations and logistic regression within an iterative generalised linear mixed modelling (GLMM) framework, we find that seasonal front frequency is a significant predictor of shark presence. Temporally-matched oceanographic metrics also indicate that sharks demonstrate a preference for productive regions, and associate with contemporaneous thermal and chl-a fronts more frequently than could be expected at random. Moreover, we highlight the importance of cross-frontal temperature change and persistence, which appear to interact to affect the degree of prey aggregation along thermal fronts. These insights have clear implications for understanding the preferred habitats of basking sharks in the context of anthropogenic threat management and marine spatial planning in the northeast Atlantic.

Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species

The effect of different factors (spawning biomass, environmental conditions) on recruitment is a subject of great importance in the management of fisheries, recovery plans and scenario exploration. In this study, recently proposed supervised classification techniques, tested by the machine-learning community, are applied to forecast the recruitment of seven fish species of North East Atlantic (anchovy, sardine, mackerel, horse mackerel, hake, blue whiting and albacore), using spawning, environmental and climatic data. In addition, the use of the probabilistic flexible naive Bayes classifier (FNBC) is proposed as modelling approach in order to reduce uncertainty for fisheries management purposes. Those improvements aim is to improve probability estimations of each possible outcome (low, medium and high recruitment) based in kernel density estimation, which is crucial for informed management decision making with high uncertainty. Finally, a comparison between goodness-of-fit and generalization power is provided, in order to assess the reliability of the final forecasting models. It is found that in most cases the proposed methodology provides useful information for management whereas the case of horse mackerel is an example of the limitations of the approach. The proposed improvements allow for a better probabilistic estimation of the different scenarios, i.e. to reduce the uncertainty in the provided forecasts.

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.  

The Tamaricetea arceuthoidis: a new class for the continental riparian thickets of the Middle East, Central Asia and the subarid regions of the Lower Volga valley

The new class, the Tamaricetea arceuthoidis, is described covering riparian and intermittent shrubby vegetation of the Irano-Turanian Region in the southwestern and Central Asia and the Lower Volga valley. The dominating species are species of the genus Tamarix that refer high water table in arid and semi-arid habitats with high to moderate salinity. This new class is an ecological analogon of the Nerio-Tamaricetea occurring in the Mediterranean Basin.