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

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

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

Skeletal Anomaly Monitoring in Rainbow Trout (Oncorhynchus mykiss, Walbaum 1792) Reared under Different Conditions

The incidence of skeletal anomalies could be used as an indicator of the "quality" of rearing conditions as these anomalies are thought to result from the inability of homeostatic mechanisms to compensate for environmentally-induced stress and/or altered genetic factors. Identification of rearing conditions that lower the rate of anomalies can be an important step toward profitable aquaculture as malformed market-size fish have to be discarded, thus reducing fish farmers' profits. In this study, the occurrence of skeletal anomalies in adult rainbow trout grown under intensive and organic conditions was monitored. As organic aquaculture animal production is in its early stages, organic broodstock is not available in sufficient quantities. Non-organic juveniles could, therefore, be used for on-growing purposes in organic aquaculture production cycle. Thus, the adult fish analysed in this study experienced intensive conditions during juvenile rearing. Significant differences in the pattern of anomalies were detected between organically and intensively-ongrown specimens, although the occurrence of severe, commercially important anomalies, affecting 2-12.5% of individuals, was comparable in the two systems. Thus, organic aquaculture needs to be improved in order to significantly reduce the incidence of severe anomalies in rainbow trout

RNA/DNA ratios as estimate of metabolic and functional traits in diatom species from the northwestern Adriatic Sea

Different phytoplankton biomass estimations can provide information about abundance variation, but they are not able to describe the metabolic activity of species or groups within assemblages. Conversely, molecular traits are key for the metabolic dynamics in pelagic ecosystems. To investigate if the RNA/DNA and taxon-specific 18S ribosomal RNA (rRNA)/ribosomal DNA (rDNA) ratios could be used to assess and be indicators of metabolic activity in marine phytoplankton species, two Adriatic diatom species, Chaetoceros socialis and Skeletonema marinoi, were studied. Significant correlations between abundance, chlorophyll a, carbon content and proteins were found in individual and co-cultured growth experiments (from r(s) = 0.570 to r(s) = 0.986, P < 0.001). The biomass trend followed a logistic curve without providing additional information regarding diatom metabolic activity. In both experiments, the RNA/DNA and taxon-specific 18S rRNA/rDNA ratios of C. socialis and S. marinoi showed maximum values at the beginning of the growth phase, i.e as 23.2 +/- 1.5 and 15.3 +/- 0.8, and 16.2 +/- 1.6 and 30.1 +/- 5.4 after 2 and 6 days, respectively, in individual cultures, with a subsequent significant decrease in these values for both species in individual and co-culture experiments. Our results showed that these molecular rRNA/rDNA ratios expressed an activation of metabolism before the abundance increases, even in the presence of interspecific interaction between C. socialis and S. marinoi

Predicting Fishing Footprint of Trawlers From Environmental and Fleet Data: An Application of Artificial Neural Networks

The increasing use of tracking devices, such as the Vessel Monitoring System (VMS) and the Automatic Identification System (AIS), have allowed, in the last decade, detailed spatial and temporal analyses of fishing footprints and of their effects on environments and resources. Nevertheless, tracking devices usually allow monitoring of the largest length classes composing different fleets, whereas fishing vessels below a regulatory threshold (i.e., 15 m in length-over-all) are not mandatorily equipped with these tools. This issue is critical, since 36% of the vessels in the European Union (EU) fleets belong to these “hidden” length classes. In this study, a model [namely, a cascaded multilayer perceptron network (CMPN)] is devised to predict the annual fishing footprints of vessels without tracking devices. This model uses information about fleet structures, environmental characteristics, human activities, and fishing effort patterns of vessels equipped with tracking devices. Furthermore, the model is able to take into account the interactions between different components of the fleets (e.g., fleet segments), which are characterized by different operating ranges and compete for the same marine space. The model shows good predictive performance and allows the extension of spatial analyses of fishing footprints to the relevant, although still unexplored, fleet segments

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

Small-scale perturbation on soft bottom macrozoobenthos after mechanical cleaning operations in a Central-Western Mediterranean lagoon

1 - Sardinia Island (Italy), even if relatively small, has over 100 lagoons totalling some 12,000 ha. Yet their potential yield remain often unexpressed because they are subjected to environmental stress and degradation. As far as benthic communities are concerned, one of the main disturbances is certainly the accumulation of shell detritus, which progressively modifies the way benthic organisms interact with the sediment. 2 - An experimental dredging study was therefore performed in the Calich lagoon (NW Sardinia), due to its particular interest for fishing activities and potential semi-intensive mollusc culture. Changes in benthic community structure were examined in two areas of the lagoon by analysing both the demographic profile of several abundant species and the features of sedimentary matrix immediately after the cleaning operations and seven months later. Data obtained were compared with those collected in undisturbed areas of the lagoon. This allowed us to evaluate the effects of dredging operations on the benthic assemblages unaffected by natural temporal shifts of the system. 3 - Univariate and multivariate analyses indicated a strong relationship between macrofaunal community structure and intensity of the cleaning activities. At the dredged sites benthic fauna was not depleted but did exhibit higher diversity and evenness indexes than at the undisturbed sites. This seemed to be a consequence of decrease in the density of some abundant species at the dredged sites. Furthermore, a general reduction of total organic content was observed in the upper sediment layer. Lastly, the cleaning method employed is discussed in relation to its potential for impacting the benthos