Simons Collaboration on Computational Biogeochemical Modeling of Marine Ecosystems
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The Irwin Group uses statistical modeling techniques to understand niches, traits, and interactions within marine microbial communities. A new paper confirms the value of trait-based approaches in investigating the mechanisms underlying phytoplankton biomass dynamics, and in predicting the community response to environmental changes. Continue reading “Turning to Traits to Understand Phytoplankton Biomass Patterns”
Mutshinda. C.M., Finkel, Z.V., Widdicombe, C.E. & Irwin, A.J. (2020), A trait-based taxonomy for phytoplankton biomass modeling and prediction, Diversity, doi: 10.3390/d12080295
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CBIOMES members please log in to access. Password issues contact cbiomesweb@gmail.com
CBIOMES members please log in to access. Password issues contact cbiomesweb@gmail.com
Crispin M. Mutshinda, Andrew J. Irwin, Mikko J. Sillanpää (2020), A Bayesian Framework for Robust Quantitative Trait Locus Mapping and Outlier Detection, The International Journal of Biostatistics, doi: 10.1515/ijb-2019-0038
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C. Mutshinda, C. Widdicombe, Z.V. Finkel, A.J. Irwin (2019), Bayesian inference to partition determinants of community dynamics from observational time series, Community Ecology, doi: 10.1556/168.2019.20.3.4
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In December, several from CBIOMES traveled to London, England, to present their work at CMStatistics2019, a conference organized by the European Research Consortium for Informatics (ERCIM) Working Group on Computational and Methodological Statistics (CMStatistics) and Birkbeck University of London. Continue reading “CBIOMES at CMStatistics2019”