| Popis: |
Freshwater lakes are among the most important ecosystems for both human and other biological communities. They account for about 87% of surface freshwater in the planet, thus constituting a major source of drinking water. They also provide a wide range of ecosystem services that go from the sustenance of a rich biodiversity to the regulation of hydrological extremes; from the provision of a means for recreation to the support of local economies, e.g., through tourism and fisheries, just to cite a few. Lakes are now also widely recognised as natural early warning systems, their responses potentially being effective indicators of local, regional and global scale phenomena such as acidification and climate change, respectively. This is because of their high sensitivity to environmental factors of the most diverse nature that can rapidly alter the course of their evolution. Examples of this are the observed abrupt shifts between alternative stable states in shallow lakes, which led them to become the archetype, go-to example in alternative stable state theory. Therefore, attaining a good scientific understanding of the many processes that take place within these ecosystems is fundamental for their adequate management. Among the tools that serve this purpose, ecological models are particularly powerful ones. Since their introduction in the 1960s, the development of mechanistic ecological models has been driven by their wide spectrum of potential applications. Nevertheless, these models often fall into one of the two following categories: overly simplistic representations of isolated processes, with limited potential to explain real-world observations as they fail to see the bigger picture; or overly complex and over-parameterised models that can hardly improve scientific understanding, their results being too difficult to analyse in terms of fundamental processes and controls. Moreover, it is now well known that an increased complexity in the mechanistic description of ecological processes, does not necessarily improve model accuracy, predictive capability or overall simulation results. To the contrary, a simpler representation allows for the inclusion of more links between model components, feedbacks which are usually overlooked in highly-complex models that partially couple a hydro-thermodynamic module to a biogeochemical one. However, ecological processes are now known to have the potential to significantly alter the physical response of aquatic ecosystems to environmental forcing. For example, steadily increasing concentrations of coloured dissolved organic carbon, a process known as brownification (also browning), as well as the intense phytoplankton blooms that characterise lakes undergoing severe nutrient enrichment, a process known as eutrophication, have been shown to have the potential to alter the duration of the stratified period, thermal structure and mixing regime of some lakes. In this thesis, with the aim of addressing the limitation of partially-coupled models to account for such feedbacks, we further develop a process-based model previously reported in scientific literature. Subsequent studies have already built upon this model in the last few years. In Chapter 2, we do so too by integrating hydro-thermodynamics and biogeochemistry in a reduced complexity framework, i.e., customising the model so that each version only includes the fundamental processes that, brought together, sufficiently describe the studied phenomena. Two case studies served the purpose of testing the adaptability and applicability of the developed model under different configurations and requirements. Limnological data for these two studies were measured at high spatial and temporal resolutions by means of an automated profiling system and recorded as part of two large-scale mesocosm experiments conducted in 2015 and 2016 at the IGB LakeLab in Lake Stechlin, Brandenburg, Germany. Meteorological datasets were also made available to us for both periods by the German Federal Environment Agency. The scope of the first experiment, which we describe in Chapter 3, was that of detecting any changes attributable to eutrophication and browning, in the competition for nutrients and light between four different groups of lake primary producers. These four groups are phytoplankton, periphyton, epiphyton and macrophytes. The model version for this study, therefore, includes equations for all four groups. By tailoring the model to these very specific needs with relative ease, we demonstrate its versatility and hint at its potential. The second experiment, described in Chapter 4, sought to shed light on the largely unknown effects of an increase in the diffuse luminance of the night sky that is due to artificial light at night (artificial skyglow) on lake metabolic rates, i.e., gross primary productivity, ecosystem respiration and net ecosystem productivity (the difference between the first two). For this purpose, an empirical equation for dissolved oxygen concentration was included, the parameters of which were estimated by means of a Markov Chain Monte Carlo sampling method within a Bayesian statistical framework, showing the compatibility, with these statistical methods, of our otherwise fully deterministic model. In Chapter 5, we present a theoretical study on the ecological controls of light and thermal patterns in lake ecosystems. A series of simulations were performed to determine in which cases ecological processes such as eutrophication and brownification may have an observable effect on the physical response of lakes to environmental forcing, which we assessed along a latitudinal gradient. Results show that, in general, across all examined latitudes, and consistent with previous studies, accounting for phytoplankton biomass results in higher surface temperatures during the warm-up phase, slightly lower water temperatures during the cool-down phase, and a shallower thermocline throughout the entire stratified period. This effect is relatively more important in eutrophic lakes where intense blooms are likely. This importance, however, decreases as lakes get browner. Finally, in line with the overall scope of the SMART EMJD, in Chapter 6 we illustrate the case of Ypacaraí Lake, the most important lake in landlocked Paraguay, hoping to provide an example of how interdisciplinary research and international intersectoral collaboration can help bridge the gap between science and management of freshwater ecosystems. This lake presents very special hydro-ecological conditions, such as very high turbidity that can impair phytoplankton growth despite its nutrient-based trophic state indices having consistently fallen within the hyper-eutrophic range in recent years. A strong interest in its complex functioning, through modelling, was taken early on. This led to a collaborative research line being established among several public and private institutions in Italy, Germany and Paraguay. Results so far include: • three concluded UniTN Master theses in Environmental Engineering, partly developed in Paraguay, the first two in collaboration with the “Nuestra Señora de la Asunción” Catholic University (UCNSA) and the third one with the National University of Asunción (UNA); • a collaborative UCNSA-UniTN research proposal submitted for consideration to receive funding through the PROCIENCIA Programme of the National Council of Science and Technology of Paraguay (CONACYT); and • the first multidisciplinary review that has ever been published about the case of Ypacaraí Lake, which highlights the importance of such a collaborative and integrative approach to further advance scientific knowledge and effectively manage this ecosystem. |
