Descripción del proyecto
Una nueva estrategia de modelización para unificar datos marinos
Los ecosistemas con un gran número de especies han demostrado ser más resistentes a los fenómenos climáticos extremos, lo que incluye los largos períodos de lluvias y de sequía. Es difícil estudiar las especies en entornos marinos, aunque se están utilizando diferentes métodos de muestreo. El proyecto MultiSeaSpace, financiado con fondos europeos, desarrollará una nueva estrategia de modelización espacial para integrar estos métodos en un único marco de modelización, que utilizará un paquete de «software» para permitir una comparación más sencilla y la unificación de la información a través de diferentes estudios. Los resultados del proyecto contribuirán a comprender cómo los recursos marinos vivos responden a nuestro cambio climático.
Objetivo
Healthy ecosystems are productive and resilient to climate change. However, their conservation through ecosystem based management remains a challenging task. This is due to a lack of understanding of both the many complex interactions among all the components within the ecosystem and the impact of management action on their health. Hence, successful conservation relies on studies that use suitable data collection methods and appropriate statistical modelling approaches that reflect this complexity and help predict the impact of different management actions.
Collecting data on species in marine ecosystems is particularly challenging as the marine environment is largely inaccessible and species are mostly invisible to researchers. Surveys can typically only collect information on some aspects of the distribution of individuals in space, mainly in dependence on the behaviour of a specific species within space and practical limitations. As a result, different sampling methods have been used, resulting in different data structures (e.g. point-process data, line transect data, telemetry data, fishery acoustic data, point-pattern data). Separate statistical modelling approaches along with different software packages have been developed for each of the different survey data structures.
MultiSeaSpace seeks to develop an integrated general spatial modelling strategy that allow us to integrate different sampling methods in a unified modelling framework that include trophic interactions. This unification provides a huge advantage since it: (a) allows us to operate within the same framework, avoiding the use of different software packages, facilitating comparison; (b) allows the pooling of information across different surveys, even if these resulted in different data structures; (c) avoids considering single species in isolation. To do so, we will use the recently developed software package inlabru, which is based on integrated nested Laplace aproximation (INLA).
Ámbito científico
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Régimen de financiación
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinador
KY16 9AJ St Andrews
Reino Unido