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. 2019 Jan 25;19(1):4.
doi: 10.1186/s12898-019-0221-4.

A model for the biomass-density dynamics of seagrasses developed and calibrated on global data

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A model for the biomass-density dynamics of seagrasses developed and calibrated on global data

Vasco M N C S Vieira et al. BMC Ecol. .

Abstract

Background: Seagrasses are foundation species in estuarine and lagoon systems, providing a wide array of services for the ecosystem and the human population. Understanding the dynamics of their stands is essential in order to better assess natural and anthropogenic impacts. It is usually considered that healthy seagrasses aim to maximize their stand biomass (g DW m-2) which may be constrained by resource availability i.e., the local environment sets a carrying capacity. Recently, this paradigm has been tested and reassessed, and it is believed that seagrasses actually maximize their efficiency of space occupation-i.e., aim to reach an interspecific boundary line (IBL)-as quick as possible. This requires that they simultaneously grow in biomass and iterate new shoots to increase density. However, this strategy depresses their biomass potential.

Results: to comply with this new paradigm, we developed a seagrass growth model that updates the carrying capacities for biomass and shoot density from the seagrass IBL at each time step. The use of a joint biomass and density growth rates enabled parameter estimation with twice the sample sizes and made the model less sensitive to episodic error in either of the variables. The use of instantaneous growth rates enabled the model to be calibrated with data sampled at widely different time intervals. We used data from 24 studies of six seagrass species scattered worldwide. The forecasted allometric biomass-density growth trajectories fit these observations well. Maximum growth and decay rates were found consistently for each species. The growth rates varied seasonally, matching previous observations.

Conclusions: State-of-art models predicting both biomass and shoot density in seagrass have not previously incorporated our observation across many seagrass species that dynamics depend on current state relative to IBL. Our model better simulates the biomass-density dynamics of seagrass stands while shedding light on its intricacies. However, it is only valid for established patches where dynamics involve space-filling, not for colonization of new areas.

Keywords: Above-ground biomass; Cymodoceae; Halodule; Interspecific boundary line; Logistic growth; Thalassia; Zostera.

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Figures

Fig. 1
Fig. 1
Biomass–density relations. Theoretical schematic of self-thinning under different resource levels and observed interspecific boundary line (IBL) of algae, terrestrial plants and seagrasses
Fig. 2
Fig. 2
Biomass–density relations of seagrasses. Observed (obs) and estimated by the allometric instantaneous growth model (model) or the isometric null hypothesis (H0)
Fig. 3
Fig. 3
Iterative update of the biomass and density carrying capacities
Fig. 4
Fig. 4
Model calibration. Inferred for six seagrass species using data retrieved from stands worldwide. Data relative to biomass (triangle) or density (circle)
Fig. 5
Fig. 5
Growth seasonality. Inferred for six seagrass species using data retrieved from stands worldwide
Fig. 6
Fig. 6
Seagrass demographic models. Left panels have the b and d time series yield by our model run in operational mode and of MEZO-1D in long range forecast. Right panels have model validation

References

    1. Nordlund LM, Koch EW, Barbier EB, Creed JC. Seagrass ecosystem services and their variability across genera and geographical regions. PLoS ONE. 2016;11(10):e0163091. doi: 10.1371/journal.pone.0163091. - DOI - PMC - PubMed
    1. Valiela I, McClelland J, Hauxwell J, Behr PJ, Hersh D, Foreman K. Macroalgal blooms in shallow estuaries: controls and ecophysiological and ecosystem consequences. Limnol Oceanogr. 1997;42:1105–1118. doi: 10.4319/lo.1997.42.5_part_2.1105. - DOI
    1. Burkholder JM, Tomasko DA, Touchette BW. Seagrasses and eutrophication. J Exp Mar Biol Ecol. 2007;350:46–72. doi: 10.1016/j.jembe.2007.06.024. - DOI
    1. Brun FG, Olivé I, Malta EJ, Vergara JJ, Hernández I, Pérez-Lloréns J. Increased vulnerability of Zostera noltii to stress caused by low light and elevated ammonium levels under phosphate deficiency. Mar Ecol Prog Ser. 2008;365:67–75. doi: 10.3354/meps07512. - DOI
    1. Pergent G, Boudouresque C-F, Dumay O, Pergent-Martini C, Wyllie-Echeverria S. Competition between the invasive macrophyte Caulerpa taxifolia and the seagrass Posidonia oceanica: contrasting strategies. BMC Ecol. 2008;8:20. doi: 10.1186/1472-6785-8-20. - DOI - PMC - PubMed

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