Epiphytic foraminifera as potential bioindicators in posidonia oceanica meadows in the balearic archipelago (western Mediterranean)

Resumo

Marine ecosystems in the Mediterranean have experienced a significant increase in anthropogenic activities over the past century, leading to environmental pollution in the littoral zone. Coastal water quality has degraded due to human activity, and the ecological importance and fragility of Posidonia oceanica habitats have highlighted the need for effective bioindicators. Foraminifera assemblages have been found to be useful in monitoring coastal and shelf environments due to their well-studied ecologies and stress-tolerant species. The aim of this thesis is to develop three specific objectives that exploit the stable association between P. oceanica seagrass and the epiphytic foraminiferal assemblage as an environmental monitoring tool. Firstly, to evaluate the ecological groups (morphotypes) that serve as the basis for bioindicator indices. Secondly, to conduct a comparative analysis of the environmental conditions of different P. oceanica meadows in the Balearic Islands that are subject to various types of anthropogenic pressure, using foraminiferal indices, abnormal-growth form frequencies, and trace-elemental concentrations within their tests to evaluate the impact of heavy-metal pollution exposure. Finally, to review published and grey literature on foraminiferal assemblages from P. oceanica meadows in the Balearic Islands and apply the new bioindicator indices to this historical dataset to detect the effects of human impact over the past 60 years (Chapter I). The analysis was performed on samples collected from P. oceanica seagrass meadows in the Balearic Islands, with the exception of multispecific seagrass meadows from tropical settings in Madagascar. The methodology employed included isotopic analysis to characterize the trophic structure of the foraminiferal assemblage using N and C stable isotopes, taxonomic and ecological description of foraminiferal assemblages for subsequent application of bioindicator indices (FI’, ILS, FSI, H’), detection of abnormal growth patterns, and geochemical analysis of foraminiferal tests to identify the presence of heavy metals (Cu, Zn, Cd, Pb, Co, Ni, As, Sn). In addition, a thorough review of theses, reports, and repositories from the 1960s to 2020s was conducted, based on foraminiferal assemblages described in seagrass meadows from the Balearic Islands (Mallorca, Cabrera, and Menorca) to gather a significant amount of information (Chapter II). In regions with limited anthropogenic activity, such as the Cabrera Archipelago National Park, foraminiferal indices were found to be highest. This observation was supported by historical data analysis, which showed that the highest values were recorded in the 1960s, at the beginning of tourism development, and from areas with minimal human influence. Furthermore, it was evident that the FI' and ILS indices have been increasing and stabilizing over the last two decades. However, there were contrasting results between high index values and anomalous foraminiferal tests with changes in geochemical test composition, which do not reflect the same environmental impacts (Chapter III). This apparent contradiction could be explained by differences in spatial scales. The FI' and ILS reflect conditions over a large area and suggest an improvement in the marine environment and P. oceanica conditions, particularly after legislative protection was enforced. On the other hand, morphological and geochemical analyses of foraminiferal samples reveal localized but long-lasting impacts (Chapter IV). The reliable classification of ecological groups was confirmed by the analysis of stable isotopes of carbon and nitrogen, which determined the trophic position of morphotypes in the food web. Thus, the FI' and ILS indices, which are based on these morphotypes, along with other indicators such as FAI and heavy metal content in tests, were able to identify different stressors. The simplicity and ease of application of these indices make them ideal for use with a wide range of databases, allowing for powerful analysis of long-term trends in the health and environmental variability of P. oceanica meadows (Chapter V).