People > Dr Jorn Bruggeman

Dr Jorn Bruggeman

Marine Ecosystem Modeller



Contact Details

+44 (0)1752 633434

jbr23/10/2019 06:16:01@pml.ac.uk

Jorn Bruggeman has worked as Senior Scientist at PML since 2013. His primary interest is the representation of species composition, biodiversity and size structure in marine ecosystem models. His work on this topic involves development of unified, species-agnostic population models, exploration of quantitative traits and trade-offs, and the development of efficient methods for simulating species diversity and adaptation. At PML, these ideas are combined to develop the European Regional Seas Ecosystem Model (ERSEM) into a modular model that adjusts its detail and complexity in response to scientific questions and computational constraints.

Jorn has a background in theoretical biology. He obtained his PhD, entitled “Succession in plankton communities: a trait-based perspective”, in 2009 at the Department of Theoretical Biology of the Vrije Universiteit Amsterdam. From 2009 till 2013, Jorn worked at the Department of Earth Sciences, University of Oxford as Junior Research Fellow attached to St. John’s College.

Projects

CAMPUS

Combining Autonomous observations and Models for Predicting and Understanding Shelf seas

Contact: Dr Stefano Ciavatta

CAMPUS is a three-year project (2018–2021), funded by the Natural Environment Research Council, combining state-of-the-art computer modelling...

OPTIMA

Optical data modelling and assimilation (OPTIMA)

Contact: Dr Stefano Ciavatta

OPTIMA will advance the capacity of the Copernicus Marine Environment Monitoring Service (CMEMS) to accurately assess the state of the marine...

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Other key projects

MERP - Marine Ecosystems Research Programme (NERC/Defra)


Recent publications

  • Talbot, E; Bruggeman, J; Hauton, C; Widdicombe, S. 2019 Uncovering the environmental drivers of short-term temporal dynamics in an epibenthic community from the Western English Channel. Journal of the Marine Biological Association of the United Kingdom. 1-13. https://doi.org/10.1017/S0025315419000663
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  • Lessin, G; Bruggeman, J; McNeill, CL; Widdicombe, S. 2019 Time scales of benthic macrofaunal response to pelagic production differ between major feeding groups. Frontiers in Marine Science, 6, supplement https://www.frontiersin.org/articles/10.3389/fmars.2019.00015/full#supplementary-material. 15, pp. https://doi.org/10.3389/fmars.2019.00015
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  • Leles, SG; Polimene, L; Bruggeman, J; Blackford, JC; Ciavatta, S; Mitra, A; Flynn, KJ. 2018 Modelling mixotrophic functional diversity and implications for ecosystem function. Journal Of Plankton Research. https://doi.org/10.1093/plankt/fby044
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  • Talbot, SE; Widdicombe, S; Hauton, C; Bruggeman, J. 2018 Adapting the dynamic energy budget (DEB) approach to include non-continuous growth (moulting) and provide better predictions of biological performance in crustaceans. ICES Journal of Marine Science. https://doi.org/10.1093/icesjms/fsy164
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  • Beecham, J; Bruggeman, J; Aldridge, J; Mackinson, S. 2016 Couplerlib: a metadata-driven library for the integration of multiple models of higher and lower trophic level marine systems with inexact functional group matching. Geoscientific Model Development, 9 (3). 947-964. https://doi.org/10.5194/gmd-9-947-2016
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  • Yakushev, EV; Protsenko, EA; Bruggeman, J; Wallhead, P; Pakhomova, SV; Yakubov, SK; Bellerby, RGJ; Couture, R-M. 2017 Bottom RedOx Model (BROM v.1.1): a coupled benthic–pelagic model for simulation of water and sediment biogeochemistry. Geoscientific Model Development, 10 (1). 453-482. https://doi.org/10.5194/gmd-10-453-2017
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View more publications

Selected key publications

Terseleer N, Bruggeman J, Lancelot C, Gypens N. In press. Trait-based representation of diatom functional diversity in a Plankton Functional Type model of the eutrophied Southern North Sea. Limnology and Oceanography

Bruggeman J, Bolding K. In press. A general framework for aquatic biogeochemical models. Environmental Modelling & Software. DOI: 10.1016/j.envsoft.2014.04.002

Young JN, Bruggeman J, Rickaby REM, Erez J, Conte M. 2013. Evidence for changes in carbon isotopic fractionation by phytoplankton between 1960 and 2010. Global Biogeochemical Cycles 27: 505–515. DOI: 10.1002/gbc.20045

Trolle D, Hamilton DP, Hipsey MR, Bolding K, Bruggeman J, Mooij WM, Janse JH, Nielsen A, Jeppesen E, Elliott A, and others. A community-based framework for aquatic ecosystem models. 2012. Hydrobiologia 683 (1): 25-34. DOI: 10.1007/s10750-011-0957-0

Bruggeman J. 2011. A phylogenetic approach to the estimation of phytoplankton traits. Journal of Phycology 47(1): 52-65. DOI: 10.1111/j.1529-8817.2010.00946.x

Saba VS, Friedrichs MAM, Carr M-E, Antoine D, Armstrong RA, Asanuma I, Aumont O, Bates NR, Behrenfeld MJ, Bennington V, Bopp L, Bruggeman J and others. 2010. Challenges of modeling depth-integrated marine primary productivity over multiple decades: A case study at BATS and HOT. Global Biogeochemical Cycles 24, GB3020. DOI: 10.1029/2009GB003655

Bruggeman J, Heringa J, Brandt BW. 2009. PhyloPars: estimation of missing parameters values using phylogeny. Nucleic Acids Research 37(Web Server issue): W179-W184. DOI: 10.1093/nar/gkp370

Merico A, Bruggeman J, Wirtz KW. 2009. A trait-based approach for downscaling complexity in plankton ecosystem models. Ecological Modelling 220(21): 3001-3010. DOI: 10.1016/j.ecolmodel.2009.05.005

Omta AW, Bruggeman J, Kooijman SALM, Dijkstra H. 2009. The organic carbon pump in the Atlantic. Journal of Sea Research 62: 179–187. DOI: 10.1016/j.seares.2009.06.005

Bruggeman J, Kooijman SALM. 2007. A biodiversity-inspired approach to aquatic ecosystem modeling. Limnology and Oceanography 52: 1533-1544. DOI: 10.4319/lo.2007.52.4.1533
 

Other activities

Member of the international advisory board of the Centre for Ocean Life, Denmark.