Descripción del proyecto
Un método innovador para desarrollar modelos mecanicistas de la biodiversidad
Los modelos mecanicistas de comunidades surgieron como respuesta a las limitaciones de los métodos de modelización de la biodiversidad. Si bien varias opciones pueden servir como base para estos modelos mecanicistas, su uso en proyectos de modelización avanzada de la biodiversidad suele ser limitado. El objetivo del proyecto financiado con fondos europeos CLIMB es desarrollar un método estadístico innovador que responda a preguntas fundamentales y apremiantes en ecología y modelización de la biodiversidad y proporcione información nueva para afrontar retos medioambientales clave. En el proyecto se probarán funciones de transferencia que permitan la medición rápida de modelos mecanicistas con datos de calidad disponibles, lo que posibilitará que estos modelos sean adecuados para realizar previsiones fiables de la biodiversidad. El equipo de CLIMB desarrollará modelos mecanicistas de comunidades apropiados, recopilará datos útiles para especies vegetales de pastizales locales y analizará datos empíricos.
Objetivo
Mechanistic community models have been advocated as a response to the conceptual and practical limitations of correlative approaches to modeling biodiversity. Building from ecological theory, there are multiple frameworks that could potentially act as a basis for such mechanistic models. However, these options often include a the large number of demographic rates to estimate in species-rich ecosystems, and their direct connection to empirical data has often been limited to simplified settings, something that strongly limits their use for ambitious biodiversity-modeling projects. With CLIMB, we propose an innovative statistical methodology to overcome this challenge: we will connect community data with functional trait data in an array of carefully designed mechanistic community models.
More precisely, CLIMB aims to propose and test adequate transfer function(s) that allow
rapid calibration of mechanistic models with available trait data and make these models suitable for reliable biodiversity predictions. The CLIMB framework will be developed and tested with simulations and two empirical study cases of temporal dynamics of grassland plant communities dynamics in two different biomes. CLIMB consists in an outgoing phase focused on (1) studying the theoretical fundations of the framework and developing appropriate mechanistic community models; and (2) collecting functional data for local grassland plant species. The return phase will focus on (3) completing the development of the modelling framework and (4) analyzing empirical data.
Ultimately, CLIMB will answer pressing fundamental questions of ecology and biodiversity modelling and will offer the ground-breaking perspectives necessary to meet key environmental challenges faced by society today.
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MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinador
93053 Regensburg
Alemania