Picture of two heads

Open Access research that challenges the mind...

The Strathprints institutional repository is a digital archive of University of Strathclyde research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including those from the School of Psychological Sciences & Health - but also papers by researchers based within the Faculties of Science, Engineering, Humanities & Social Sciences, and from the Strathclyde Business School.

Discover more...

Understanding demography in an advective environment: Modelling Calanus finmarchicus in the Norwegian Sea

Speirs, D. and Gurney, W.S.C. and Holmes, S.J. and Heath, M.R. and Wood, S.N. and Clarke, E.D. and Harms, I.H. and Hirche, H. and McKenzie, E. (2004) Understanding demography in an advective environment: Modelling Calanus finmarchicus in the Norwegian Sea. Journal of Animal Ecology, 73. pp. 897-910. ISSN 0021-8790

Full text not available in this repository. (Request a copy from the Strathclyde author)

Abstract

Attempts to understand the demography of natural populations from time-series can be hampered by the fact that changes due to births and deaths may be confounded with those due to movement in and out of the sampling area. We illustrate the problem using a stage-structured time-series of the marine copepod Calanus finmarchicus sampled in the vicinity of a fixed location but where the demography is shown to be inconsistent with the assumption of a closed population. Using an empirical relationship between C. finmarchicus egg production and the abundance of phytoplanktonic food, the spatio-temporal patterns in chlorophyll a can be inferred. The distributions during the spring bloom are spatially heterogeneous, and we estimate that the phytoplankton patches are of the order of 30 km across. This result is robust to substantial variations in the assumed stage-dependent mortalities. We conclude that information on advective transport can be used to make testable predictions about the scale of spatial heterogeneities. These, in turn, imply the appropriate spatial scale over which time-series might be replicated in order to obtain more information about unknown processes such as mortality.