Marine Strategy, una sfida ed un'opportunità per la Biologia Marina italiana

The Marine Strategy Framework Directive, which came into force in 2008, can be regarded as the environmental pillar for the Integrated European Maritime Policy. In the first phase of its implementation EU member Countries carried out an initial assessment of the ecological status, set environmental targets and defined the concept of Good Ecological Status. While marine biologists from Italian Universities and other research Institutions actively participated in this process, new challenges will be brought by its next phases, requiring a deeper involvement of the scientific community and a truly holistic approach

A Machine learning approach to the study of a red coral <i>Corallium rubrum</i> (l.) population = Un'Applicazione del machine learning per lo studio di una popolazione di corallo rosso <i>Corallium rubrum</i> (L.)

This study deals with the application of a machine learning algorithm (a classification tree) to assess the weight of Corallium rubrum (Cnidaria, Octocorallia) ramifications on the basis of the number of apices. Our approach can be easily applied to obtain in situ estimates of weight and basal diameter of colonies. Future developments include the integration with image acquisition and processing hardware

Applications of Self-Organizing Maps for Ecomorphological Investigations through Early Ontogeny of Fish

We propose a new graphical approach to the analysis of multi-temporal morphological and ecological data concerning the life history of fish, which can typically serves models in ecomorphological investigations because they often undergo significant ontogenetic changes. These changes can be very complex and difficult to describe, so that visualization, abstraction and interpretation of the underlying relationships are often impeded. Therefore, classic ecomorphological analyses of covariation between morphology and ecology, performed by means of multivariate techniques, may result in non-exhaustive models. The Self Organizing map (SOM) is a new, effective approach for pursuing this aim. In this paper, lateral outlines of larval stages of gilthead sea bream (Sparus aurata) and dusky grouper (Epinephelus marginatus) were recorded and broken down using by means of Elliptic Fourier Analysis (EFA). Gut contents of the same specimens were also collected and analyzed. Then, shape and trophic habits data were examined by SOM, which allows both a powerful visualization of shape changes and an easy comparison with trophic habit data, via their superimposition onto the trained SOM. Thus, the SOM provides a direct visual approach for matching morphological and ecological changes during fish ontogenesis. This method could be used as a tool to extract and investigate relationships between shape and other sinecological or environmental variables, which cannot be taken into account simultaneously using conventional statistical methods

Optimizing interpolation of shoot density data from a Posidonia oceanica seagrass bed

A case study on the optimization of Posidonia oceanica density interpolation, using a data set from a large meadow at Porto Conte Bay (NW Sardinia, Italy), is presented. Ordinary point kriging, cokriging and a weighted average based on inverse square distance were used to interpolate density data measured in 36 sampling stations. The results obtained from different methods were then compared by means of a leave-one-out cross-validation procedure. The scale at which interpolation was carried out was defined on the basis of the Hausdorff dimension of the variogram. Optimizing spatial scale and data points search strategy allowed obtaining more accurate density estimates independently of the interpolation method

Long-term changes and recurrent patterns in fisheries landings from Large Marine Ecosystems (1950–2004)

The regional dynamics of industrial fisheries within Large Marine Ecosystems (LMEs) boundaries were investigated by means of a historical-descriptive approach. Landings data from the Sea Around Us Project database were used to detect trends in total yields and variations in landings composition by functional groups over time. The temporal and spatial scales covered by this study allowed general issues to be addressed such as the detection of recurrent patterns and synchronies in fisheries landings. An unsuper-vised artificial neural network, Self Organizing Map (SOM), is used as a tool to analyze fisheries landings composition variation over five decades in 51 LMEs all over the world. From the historical analysis of “fishing behaviors” within LMEs a broad distinction between two main types of fisheries emerged: (1) small and medium pelagics fisheries, with stable compositions or cyclic behaviors, occurred in LMEs which share common productive features, despite different geographical locations and (2) demersal fisheries, which are more affected by economic drivers and tend to concentrate in LMEs in the Northern Hemisphere. Our analysis can be regarded as a first step towards the challenging scope of describing the relative influence of environmental and economic drivers on exploited ecosystems

Composition of arthropod species assemblages in Bt-expressing and near isogenic eggplants in experimental fields

The environmental impact of genetically modified (GM) plants in experimental fields has been examined in several ways, in particular with respect to the dynamics of specific nontarget organisms. The approach of sampling for biodiversity in agroecosystems to compare complex patterns could also be useful in studying potential disruptions caused by GM crops. In this study, we set up replicated field plots of Bt-expressing eggplants and near isogenic untransformed eggplants as a control. We monitored the presence and abundance of herbivore and predator arthropods in weekly visual samplings of the plant canopy for three growing seasons (2001-2003). Insect species were pooled in organismal taxonomic units (OTUs); three multivariate methods were used to compare species assemblage as an estimate of insect biodiversity. This multistep statistical approach proved to be efficient in recognizing association patterns, as evidenced by the data for the target species Leptinotarsa decemlineata Say (Coleoptera: Chrysomelidae) clearly showing a significant association with the control plots. All the analyses indicate a comparable species assemblage between transgenic and near isogenic eggplant areas. Our results suggest that some taxa may warrant more specific study. For example, Alticinae beetles (Coleoptera: Chrysomelidae) were alternatively more abundant in either of the two treatments, and their overall abundance was significantly higher on transgenic eggplants. In light of these results and because of their taxonomic proximity to the target species, these herbivores may represent an important nontarget group to be further studied. Moreover, some sap feeders (e.g., Homoptera: Cicadellidae) were more abundant on Bt-expressing plants in some samples in all 3 yr

Structure and morphology of shape-controlled Pd nanocrystals

Pd nanocrystals were produced with uniform truncated-cube shape and a narrow size distribution, yielding controlled surface area fractions from low Miller index ({100}, {110}, {111}) crystalline facets. Details on the structure and morphology of the nanocrystals were obtained by combining X-ray powder diffraction line profile analysis, high-resolution transmission electron microscopy and surface electrochemistry based on Cu underpotential deposition.ML acknowledges support from the Italian government (Ministero dell’Istruzione, dell’Università e della Ricerca) through the project FIRB Futuro in Ricerca RBFR10CWDA. JMF acknowledges financial support from the MINECO (Spain) project CTQ2013-44083-P and Generalitat Valenciana project PROMETEOII/2014/013