نبذة مختصرة : There has been a rapid rise in the development of end-to-end models for marine ecosystems over the past decade. Some reasons for this rise include need for predicting effects of climate change on biota and dissatisfaction with existing models. While the benefits of a well-implemented end-to-end model are straightforward, there are many challenges. In the short term, my view is that the major role of end-to-end models is to push the modelling community forward, and to identify critical data so that these data can be collected now and thus be available for the next generation of end-to-end models. I think we should emulate physicists and build theoretically-oriented models first, and then collect the data. In the long-term, end-to-end models will increase their skill, data collection will catch up, and end-to-end models will move towards site-specific applications with forecasting and management capabilities. One pathway into the future is individual efforts, over-promise, and repackaging of poorly performing component submodels (“lipstick on a pig”). The other pathway is a community-based collaborative effort, with appropriate caution and thoughtfulness, so that the needed improvements are achieved (“significant advance”). The promise of end-to-end modelling is great. We should act now to avoid missing a great opportunity. ; Durante la última década ha habido un rápido incremento en el desarrollo de modelos integrales para ecosistemas marinos. Las razones incluyen la necesidad de predecir los efectos de cambios globales sobre la biota y la falta de satisfacción con los modelos existentes. Mientras que los beneficios de un modelo integral bien aplicado son claros, hay muchos retos. A corto plazo, mi opinión es que el papel principal de los modelos integrales es hacer avanzar a la comunidad de expertos en modelado, e identificar datos cruciales para el desarrollo de la siguiente generación de estos modelos. Creo que debemos emular a los físicos y construir modelos teóricos primero, para pasar luego a recoger los datos necesarios. Una posible opción para avanzar sería continuar a base de esfuerzos individuales, promesas desproporcionadas, y pequeñas reformulaciones de sub-modelos con escaso potencial (“vestir la mona de seda”). El otro camino es realizar un esfuerzo comunitario de colaboración, con las necesarias reflexiones y precauciones, para que haya avances significativos y se implementen las mejoras necesarias. Las expectativas del modelado integral son grandes. Debemos actuar ahora para evitar perder una gran oportunidad.
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