4 resultados para natural ecosystems

em Universitat de Girona, Spain


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La present tesi intenta obtenir noves dades referents a la biologia i ecologia de la formiga argentina que poden arribar a ser cabdals per al disseny o millora de noves metodologies de control de l'expansió de la plaga en ecosistemes naturals. Així doncs, l'estudi de l'activitat de cerca d'aliment i del seu espectre dietari en ecosistemes naturals, juntament amb el de les fluctuacions estacionals de la densitat de reines en nius naturals, obre les portes a la millora de mètodes de control de la plaga mitjançant esquers tòxics d'efecte retardat i a l'aplicació de noves metodologies de control sense l'ús d'agents químics basats en l'eliminació massiva de reines. La tesi també aporta noves dades sobre la fisiologia reproductiva de l'espècie en relació a la temperatura, la qual cosa permet la integració de l'aspecte fisiològic en models de predicció del rang potencial d'establiment de la plaga en ecosistemes naturals, aspecte fins ara pràcticament oblidat en aquest tipus de models predictius.

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L'activitat humana és una de les majors causes d'elevades concentracions de nutrients i substàncies tòxiques en els ecosistemes fluvials. Entre la gran varietat de factors que alteren aquests ecosistemes, l'eutrofització i la contaminació per metalls pesants són dos dels principals problemes ambientals en països desenvolupats. Els biofilms fluvials (també anomenats comunitats perifítiques) representen una eina valuosa per avaluar els efectes dels contaminants (ex. nutrients i metalls) en els ecosistemes aquàtics. Aquest treball pretén investigar el destí i els efectes del Cu en els ecosistemes fluvials centrant-se en les comunitats perifítiques. Diferents metodologies han estat desenvolupades i/o adaptades per investigar específicament la dinàmica del Cu, la seva toxicitat i bioacumulació en comunitats perifítiques naturals, i la interacció entre l'eutrofització i la toxicitat del Cu en aquests ecosistemes.

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Human activities have been interfering with the natural biogeochemical cycles of trace elements since the ancient civilizations. Although they are inaccessible and remote, high mountain lake catchments are irrefutably trace-element contaminated by anthropogenic emissions, which can travel by long-range atmospheric transport before they are deposited. This has been revealed by several natural archives. High mountain lake catchments are thus excellent sentinels of long-range contamination. Continuous accumulation can lead to a build up of potentially toxic trace elements in these remote, or relatively remote, ecosystems. The thesis focuses on the biogeochemistry of a suite of trace elements of environmental concern (Ni, Cu, Zn, As, Se, Cd and Pb) in Pyrenean lake catchments, with special emphasis on discerning the “natural” components from the “anthropogenic” contributions. Five other metallic elements (Al, Fe, Ti, Mn and Zr) have also been studied to trace natural fluxes and biogeochemical processes within the lake catchment systems.

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This thesis addresses the problem of learning in physical heterogeneous multi-agent systems (MAS) and the analysis of the benefits of using heterogeneous MAS with respect to homogeneous ones. An algorithm is developed for this task; building on a previous work on stability in distributed systems by Tad Hogg and Bernardo Huberman, and combining two phenomena observed in natural systems, task partition and hierarchical dominance. This algorithm is devised for allowing agents to learn which are the best tasks to perform on the basis of each agent's skills and the contribution to the team global performance. Agents learn by interacting with the environment and other teammates, and get rewards from the result of the actions they perform. This algorithm is specially designed for problems where all robots have to co-operate and work simultaneously towards the same goal. One example of such a problem is role distribution in a team of heterogeneous robots that form a soccer team, where all members take decisions and co-operate simultaneously. Soccer offers the possibility of conducting research in MAS, where co-operation plays a very important role in a dynamical and changing environment. For these reasons and the experience of the University of Girona in this domain, soccer has been selected as the test-bed for this research. In the case of soccer, tasks are grouped by means of roles. One of the most interesting features of this algorithm is that it endows MAS with a high adaptability to changes in the environment. It allows the team to perform their tasks, while adapting to the environment. This is studied in several cases, for changes in the environment and in the robot's body. Other features are also analysed, especially a parameter that defines the fitness (biological concept) of each agent in the system, which contributes to performance and team adaptability. The algorithm is applied later to allow agents to learn in teams of homogeneous and heterogeneous robots which roles they have to select, in order to maximise team performance. The teams are compared and the performance is evaluated in the games against three hand-coded teams and against the different homogeneous and heterogeneous teams built in this thesis. This section focuses on the analysis of performance and task partition, in order to study the benefits of heterogeneity in physical MAS. In order to study heterogeneity from a rigorous point of view, a diversity measure is developed building on the hierarchic social entropy defined by Tucker Balch. This is adapted to quantify physical diversity in robot teams. This tool presents very interesting features, as it can be used in the future to design heterogeneous teams on the basis of the knowledge on other teams.