2 resultados para FUNCTIONAL-GROUPS

em AMS Tesi di Laurea - Alm@DL - Università di Bologna


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The first part of my work consisted in samplings conduced in nine different localities of the salento peninsula and Apulia (Italy): Costa Merlata (BR), Punta Penne (BR), Santa Cesarea terme (LE), Santa Caterina (LE), Torre Inserraglio (LE), Torre Guaceto (BR), Porto Cesareo (LE), Otranto (LE), Isole Tremiti (FG). I collected data of species percentage covering from the infralittoral rocky zone, using squares of 50x50 cm. We considered 3 sites for location and 10 replicates for each site, which has been taken randomly. Then I took other data about the same places, collected in some years, and I combined them together, to do a spatial analysis. So I started from a data set of 1896 samples but I decided not to consider time as a factor because I have reason to think that in this period of time anthropogenic stressors and their effects (if present), didn’t change considerably. The response variable I’ve analysed is the covering percentage of an amount of 243 species (subsequently merged into 32 functional groups), including seaweeds, invertebrates, sediment and rock. 2 After the sampling, I have been spent a period of two months at the Hopkins Marine Station of Stanford University, in Monterey (California,USA), at Fiorenza Micheli's laboratory. I've been carried out statistical analysis on my data set, using the software PRIMER 6. My explorative analysis starts with a nMDS in PRIMER 6, considering the original data matrix without, for the moment, the effect of stressors. What comes out is a good separation between localities and it confirms the result of ANOSIM analysis conduced on the original data matrix. What is possible to ensure is that there is not a separation led by a geographic pattern, but there should be something else that leads the differences. Is clear the presence of at least three groups: one composed by Porto cesareo, Torre Guaceto and Isole tremiti (the only marine protected areas considered in this work); another one by Otranto, and the last one by the rest of little, impacted localities. Inside the localities that include MPA(Marine Protected Areas), is also possible to observe a sort of grouping between protected and controlled areas. What comes out from SIMPER analysis is that the most of the species involved in leading differences between populations are not rare species, like: Cystoseira spp., Mytilus sp. and ECR. Moreover I assigned discrete values (0,1,2) of each stressor to all the sites I considered, in relation to the intensity with which the anthropogenic factor affect the localities. 3 Then I tried to estabilish if there were some significant interactions between stressors: by using Spearman rank correlation and Spearman tables of significance, and taking into account 17 grades of freedom, the outcome shows some significant stressors interactions. Then I built a nMDS considering the stressors as response variable. The result was positive: localities are well separeted by stressors. Consequently I related the matrix with 'localities and species' with the 'localities and stressors' one. Stressors combination explains with a good significance level the variability inside my populations. I tried with all the possible data transformations (none, square root, fourth root, log (X+1), P/A), but the fourth root seemed to be the best one, with the highest level of significativity, meaning that also rare species can influence the result. The challenge will be to characterize better which kind of stressors (including also natural ones), act on the ecosystem; and give them a quantitative and more accurate values, trying to understand how they interact (in an additive or non-additive way).

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Global warming and ocean acidification, due to rising atmospheric levels of CO2, represent an actual threat to terrestrial and marine environments. Since Industrial Revolution, in less of 250 years, pH of surface seawater decreased on average of 0.1 unit, and is expected to further decreases of approximately 0.3-0.4 units by the end of this century. Naturally acidified marine areas, such as CO2 vent systems at the Ischia Island, allow to study acclimatation and adaptation of individual species as well as the structure of communities, and ecosystems to OA. The main aim of this thesis was to study how hard bottom sublittoral benthic assemblages changed trough time along a pH gradient. For this purpose, the temporal dynamics of mature assemblages established on artificial substrates (volcanic tiles) over a 3 year- period were analysed. Our results revealed how composition and dynamics of the community were altered and highly simplified at different level of seawater acidification. In fact, extreme low values of pH (approximately 6.9), affected strongly the assemblages, reducing diversity both in terms of taxa and functional groups, respect to lower acidification levels (mean pH 7.8) and ambient conditions (8.1 unit). Temporal variation was observed in terms of species composition but not in functional groups. Variability was related to species belonging to the same functional group, suggesting the occurrence of functional redundancy. Therefore, the analysis of functional groups kept information on the structure, but lost information on species diversity and dynamics. Decreasing in ocean pH is only one of many future global changes that will occur at the end of this century (increase of ocean temperature, sea level rise, eutrophication etc.). The interaction between these factors and OA could exacerbate the community and ecosystem effects showed by this thesis.