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Volume 31, issue 2 | Copyright
J. Micropalaeontol., 31, 111-119, 2012
https://doi.org/10.1144/0262-821X11-009
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 4.0 License.

  01 Jul 2012

01 Jul 2012

Determining carrying capacity from foraminiferal time-series

Brent Wilson1 and Benjamin P. Horton2 Brent Wilson and Benjamin P. Horton
  • 1Petroleum Geoscience Programme, Department of Chemical Engineering, The University of the West Indies, St Augustine, Trinidad and Tobago
  • 2Sea Level Research, Department of Earth & Environmental Science, University of Pennsylvania, 240 South 33rd Street, Philadelphia, PA 19104, USA

Keywords: Nonion depressulus, Quinqueloculina, Haynesina germanica, Exe estuary, Indian River Lagoon, Cowpen Marsh, population dynamic, seasonality, carrying capacity

Abstract. The carrying capacity K is the equilibrium population density of a species that an area can support while adequately meeting the needs of every individual. Although widely used in ecology, it has yet to be applied rigorously to living foraminifera. K is readily determined from time-series of population densities. Given that Nt+1 = Nt + RNt, in which Nt is the population densities at time t, Nt+1 is the density at a subsequent time t+1 and R is the per capita rate of change in population density, then linear regression gives Rt = RmsNt, in which Rt is the per capita rate of increase at time t, the constant Rm is the maximum possible individual rate of increase, and the negative slope s represents the strength of intraspecific interactions. Setting Rt = 0, so that Nt = K and RmsK = 0, gives K = Rm/s, which is applicable in aseasonal environments. There are two carrying capacities in seasonal environments, depending on whether the season is favourable (Kmax) or unfavourable (Kmin). Values of Kmax and Kmin are estimated for Nonion depressulus in the Exe estuary, UK (25 monthly samples), Quinqueloculina spp. in the Indian River Lagoon, USA (60 monthly samples) and Haynesina germanica in Cowpen Marsh, UK (25 fortnightly samples). The most precise estimate was for H. germanica, but it was unclear if this was due to the high rate of sampling or the large number of replicates used to erect this time-series.

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