An empirically based minimalistic model for 1 representing seasonal phytoplankton dynamics

Sofia Helena Piltz, Poul G. Hjorth, Øystein Varpe

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Supported by chl-a satellite data in the North Atlantic (and phytoplankton division rate computed from therein), the disturbance-recovery hypothesis for the initiation of phytoplankton blooms posits that the change in chl-a concentration is proportional to the rel18 ative change in the phytoplankton division rate. Here, we use this hypothesis introduced by Behrenfeld as a principal model assumption and construct a non-autonomous ordinary differential equation model for seasonally varying chl-a concentration. Our quantitative comparison between model simulations and in situ measurements of chl-a and primary production collected from a Swedish fjord is two-fold: First, by using approximate Bayesian computation, we find distributions of values for the three model parameters that best describe the chl-a data. Then, we validate our model by comparing the simulated (not fitted)1 division rate to the data on division rate. Our minimalistic model is able to capture (1) the yearly trend in the chl-a concentration, (2) the pattern of growth and decline in the phytoplankton division rate, and (3) the decreasing trend in the relative change of the division rate exhibited in the data for several individual years. Moreover, the modeling efficiency (which is a measure of the goodness of fit of a (deterministic) model and nearly identical to R2 for statistical models) is positive (between 0.3 and 0.9 with an average of 0.63) for all 11 years included in this study. Thus, we conclude that the change in chl-a concentra8 tion being proportional to the relative change in the division rate is a possible explanation for the bloom dynamics in the Gullmar fjord. In addition, our work provides a simple and empirically based differential equation for representing yearly dynamics of primary
production, e.g., for generating ecological hypotheses using models of other trophic levels.
Original languageEnglish
JournalMarine Ecology - Progress Series
Number of pages35
ISSN0171-8630
Publication statusAccepted/In press - 2020

Keywords

  • Non-autonomous ordinary differential equations
  • Primary production
  • Chlorophylla
  • Division rate
  • Gullmar fjord
  • Approximate Bayesian computation inference

Cite this

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title = "An empirically based minimalistic model for 1 representing seasonal phytoplankton dynamics",
abstract = "Supported by chl-a satellite data in the North Atlantic (and phytoplankton division rate computed from therein), the disturbance-recovery hypothesis for the initiation of phytoplankton blooms posits that the change in chl-a concentration is proportional to the rel18 ative change in the phytoplankton division rate. Here, we use this hypothesis introduced by Behrenfeld as a principal model assumption and construct a non-autonomous ordinary differential equation model for seasonally varying chl-a concentration. Our quantitative comparison between model simulations and in situ measurements of chl-a and primary production collected from a Swedish fjord is two-fold: First, by using approximate Bayesian computation, we find distributions of values for the three model parameters that best describe the chl-a data. Then, we validate our model by comparing the simulated (not fitted)1 division rate to the data on division rate. Our minimalistic model is able to capture (1) the yearly trend in the chl-a concentration, (2) the pattern of growth and decline in the phytoplankton division rate, and (3) the decreasing trend in the relative change of the division rate exhibited in the data for several individual years. Moreover, the modeling efficiency (which is a measure of the goodness of fit of a (deterministic) model and nearly identical to R2 for statistical models) is positive (between 0.3 and 0.9 with an average of 0.63) for all 11 years included in this study. Thus, we conclude that the change in chl-a concentra8 tion being proportional to the relative change in the division rate is a possible explanation for the bloom dynamics in the Gullmar fjord. In addition, our work provides a simple and empirically based differential equation for representing yearly dynamics of primaryproduction, e.g., for generating ecological hypotheses using models of other trophic levels.",
keywords = "Non-autonomous ordinary differential equations, Primary production, Chlorophylla, Division rate, Gullmar fjord, Approximate Bayesian computation inference",
author = "Piltz, {Sofia Helena} and Hjorth, {Poul G.} and {\O}ystein Varpe",
year = "2020",
language = "English",
journal = "Marine Ecology - Progress Series",
issn = "0171-8630",
publisher = "Inter Research",

}

An empirically based minimalistic model for 1 representing seasonal phytoplankton dynamics. / Piltz, Sofia Helena; Hjorth, Poul G.; Varpe, Øystein.

In: Marine Ecology - Progress Series, 2020.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - An empirically based minimalistic model for 1 representing seasonal phytoplankton dynamics

AU - Piltz, Sofia Helena

AU - Hjorth, Poul G.

AU - Varpe, Øystein

PY - 2020

Y1 - 2020

N2 - Supported by chl-a satellite data in the North Atlantic (and phytoplankton division rate computed from therein), the disturbance-recovery hypothesis for the initiation of phytoplankton blooms posits that the change in chl-a concentration is proportional to the rel18 ative change in the phytoplankton division rate. Here, we use this hypothesis introduced by Behrenfeld as a principal model assumption and construct a non-autonomous ordinary differential equation model for seasonally varying chl-a concentration. Our quantitative comparison between model simulations and in situ measurements of chl-a and primary production collected from a Swedish fjord is two-fold: First, by using approximate Bayesian computation, we find distributions of values for the three model parameters that best describe the chl-a data. Then, we validate our model by comparing the simulated (not fitted)1 division rate to the data on division rate. Our minimalistic model is able to capture (1) the yearly trend in the chl-a concentration, (2) the pattern of growth and decline in the phytoplankton division rate, and (3) the decreasing trend in the relative change of the division rate exhibited in the data for several individual years. Moreover, the modeling efficiency (which is a measure of the goodness of fit of a (deterministic) model and nearly identical to R2 for statistical models) is positive (between 0.3 and 0.9 with an average of 0.63) for all 11 years included in this study. Thus, we conclude that the change in chl-a concentra8 tion being proportional to the relative change in the division rate is a possible explanation for the bloom dynamics in the Gullmar fjord. In addition, our work provides a simple and empirically based differential equation for representing yearly dynamics of primaryproduction, e.g., for generating ecological hypotheses using models of other trophic levels.

AB - Supported by chl-a satellite data in the North Atlantic (and phytoplankton division rate computed from therein), the disturbance-recovery hypothesis for the initiation of phytoplankton blooms posits that the change in chl-a concentration is proportional to the rel18 ative change in the phytoplankton division rate. Here, we use this hypothesis introduced by Behrenfeld as a principal model assumption and construct a non-autonomous ordinary differential equation model for seasonally varying chl-a concentration. Our quantitative comparison between model simulations and in situ measurements of chl-a and primary production collected from a Swedish fjord is two-fold: First, by using approximate Bayesian computation, we find distributions of values for the three model parameters that best describe the chl-a data. Then, we validate our model by comparing the simulated (not fitted)1 division rate to the data on division rate. Our minimalistic model is able to capture (1) the yearly trend in the chl-a concentration, (2) the pattern of growth and decline in the phytoplankton division rate, and (3) the decreasing trend in the relative change of the division rate exhibited in the data for several individual years. Moreover, the modeling efficiency (which is a measure of the goodness of fit of a (deterministic) model and nearly identical to R2 for statistical models) is positive (between 0.3 and 0.9 with an average of 0.63) for all 11 years included in this study. Thus, we conclude that the change in chl-a concentra8 tion being proportional to the relative change in the division rate is a possible explanation for the bloom dynamics in the Gullmar fjord. In addition, our work provides a simple and empirically based differential equation for representing yearly dynamics of primaryproduction, e.g., for generating ecological hypotheses using models of other trophic levels.

KW - Non-autonomous ordinary differential equations

KW - Primary production

KW - Chlorophylla

KW - Division rate

KW - Gullmar fjord

KW - Approximate Bayesian computation inference

M3 - Journal article

JO - Marine Ecology - Progress Series

JF - Marine Ecology - Progress Series

SN - 0171-8630

ER -