Which environmental factors control phytoplankton populations? A Bayesian variable selection approach

Crispin M. Mutshinda, Zoe V. Finkel and Andrew J. Irwin

Ecological Modelling, 2013, vol. 269, issue C, 1-8

Abstract: The structure of phytoplankton communities is thought to influence total productivity, trophic structure and the export of carbon below the mixed layer. Community structure is determined by a complex interaction between the physiological characteristics of each species, environmental conditions, resource availability, competition among species, and numerous loss terms. This complexity makes it very difficult to predict how changes in environmental conditions will alter the structure of phytoplankton communities. Here we develop a hierarchical Bayesian model with variable selection to identify how temperature, salinity, irradiance, and macronutrient concentrations determine the abundance of the 67 dominant identified species at Station CARIACO in the Caribbean Sea. This approach allows us to overcome the statistical challenge presented by the highly correlated environmental variables. Approximately three-quarters of the variables for each species have little effect on phytoplankton abundance. About half of the species decline in abundance with increasing temperature. Diatom species’ abundances are much more likely to respond to changes in irradiance and nitrate concentration than dinoflagellates and dinoflagellate species’ abundances are more likely to respond to changes in salinity.

Keywords: Bayesian variable selection; Environmental forcing; Multicollinearity; Overfitting; Phytoplankton (search for similar items in EconPapers)
Date: 2013
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304380013003803
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:269:y:2013:i:c:p:1-8

DOI: 10.1016/j.ecolmodel.2013.07.025

Access Statistics for this article

Ecological Modelling is currently edited by Brian D. Fath

More articles in Ecological Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().