Description du projet
Une nouvelle stratégie de modélisation pour mettre les données marines en commun
Les écosystèmes comptant un plus grand nombre d’espèces se sont avérés plus résistants aux phénomènes climatiques extrêmes, y compris les périodes humides et sèches prolongées. Il est compliqué d’étudier les espèces en milieu marin, car différentes méthodes d’échantillonnage sont utilisées. Le projet MultiSeaSpace, financé par l’UE, développera une nouvelle stratégie de modélisation spatiale afin d’intégrer ces différentes méthodes dans un seul cadre de modélisation. Il utilisera un nouveau progiciel pour faciliter la comparaison et la mise en commun des informations dans différentes enquêtes. Les résultats du projet contribueront à la compréhension de la façon dont les ressources marines vivantes réagissent à notre climat changeant.
Objectif
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).
Champ scientifique
Mots‑clés
Programme(s)
Régime de financement
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinateur
KY16 9AJ St Andrews
Royaume-Uni