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| Pethybridge, Heidi; Weijerman, Mariska; Perrymann, Holly; Audzijonyte, Asta; Porobic, Javier; Mcgregor, Vidette; Girardin, Raphael; Bulman, Cathy; Ortega-cisneros, Kelly; Sinerchia, Matteo; Hutton, Trevor; Lozano-montes, Hector; Mori, Mao; Novaglio, Camilla; Fay, Gavin; Gorton, Rebecca; Fulton, Elizabeth. |
| Calibration of complex, process-based ecosystem models is a timely task with modellers challenged by many parameters, multiple outputs of interest and often a scarcity of empirical data. Incorrect calibration can lead to unrealistic ecological and socio-economic predictions with the modeller’s experience and available knowledge of the modelled system largely determining the success of model calibration. Here we provide an overview of best practices when calibrating an Atlantis marine ecosystem model, a widely adopted framework that includes the parameters and processes comprised in many different ecosystem models. We highlight the importance of understanding the model structure and data sources of the modelled system. We then focus on several model outputs... |
| Tipo: Text |
Palavras-chave: Best practices; Model diagnostics; Food web; Pedigree; Parameter estimation. |
| Ano: 2019 |
URL: https://archimer.ifremer.fr/doc/00516/62723/67160.pdf |
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| Darnaude, Audrey M; Labonne, Maylis; Petit, Cécile; Médieu, Anais; Pernak, Marianne; Nikolic, Natacha; Artetxe-arrate, Iraide; Clear, Naomi; Farley, Jessica; Eveson, Paige; Lozano-montes, Hector; Davies, Campbell; Marsac, Francis. |
| Variation in otolith elemental fingerprints was investigated in the broadbill swordfish (Xiphias gladius) to complement genetic data obtained by next generation sequencing in the framework of a collaborative project on population stock structure of tuna, billfish and sharks of the Indian Ocean (PSTBS-IO). Swordfish specimens for this work were sampled in the southwest (SWI), west central (WCI) and southeast (SEI) regions of the Indian Ocean. A total of 70 otoliths (30 from SWI and 20 from each WCI and SEI) were selected and the elemental signatures of their cores were analysed by LA-ICP-MS to investigate potential differences in spawning origin among regions. Among the 15 chemical elements analysed, only Mg, P, Sr, Ba and B were above detection limits and... |
| Tipo: Text |
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| Ano: 2020 |
URL: https://archimer.ifremer.fr/doc/00652/76400/77439.pdf |
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| Yates, Katherine L.; Bouchet, Phil J.; Caley, M. Julian; Mengersen, Kerrie; Randin, Christophe F.; Parnell, Stephen; Fielding, Alan H.; Bamford, Andrew J.; Ban, Stephen; Marcia Barbosa, A.; Dormann, Carsten F.; Elith, Jane; Embling, Clare B.; Ervin, Gary N.; Fisher, Rebecca; Gould, Susan; Graf, Roland F.; Gregr, Edward J.; Halpin, Patrick N.; Heikkinen, Risto K.; Heinanen, Stefan; Jones, Alice R; Krishnakumar, Periyadan K.; Lauria, Valentina; Lozano-montes, Hector; Mannocci, Laura; Mellin, Camille; Mesgaran, Mohsen B.; Moreno-amat, Elena; Mormede, Sophie; Novaczek, Emilie; Oppel, Steffen; Crespo, Guillermo Ortuno; Peterson, A. Townsend; Rapacciuolo, Giovanni; Roberts, Jason J.; Ross, Rebecca E.; Scales, Kylie L.; Schoeman, David; Snelgrove, Paul; Sundblad, Goran; Thuiller, Wilfried; Torres, Leigh G.; Verbruggen, Heroen; Wang, Lifei; Wenger, Seth; Whittingham, Mark J.; Zharikov, Yuri; Zurell, Damaris; Sequeira, Ana M. M.. |
| Predictive models are central to many scientific disciplines and vital for informing management in a rapidly changing world. However, limited understanding of the accuracy and precision of models transferred to novel conditions (their 'transferability') undermines confidence in their predictions. Here, 50 experts identified priority knowledge gaps which, if filled, will most improve model transfers. These are summarized into six technical and six fundamental challenges, which underlie the combined need to intensify research on the determinants of ecological predictability, including species traits and data quality, and develop best practices for transferring models. Of high importance is the identification of a widely applicable set of transferability... |
| Tipo: Text |
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| Ano: 2018 |
URL: https://archimer.ifremer.fr/doc/00466/57728/59909.pdf |
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