Linking phytoplankton community size composition with temperature, plankton food web structure and sea–air CO2 flux

Hilligsøe, Karen Marie; Richardson, Katherine; Bendtsen, Jørgen; Sørensen, Lise Lotte; Nielsen, Torkel Gissel; Lyngsgaard, Maren Moltke

doi:10.1016/j.dsr.2011.06.004

Cited by 88 publications

(84 citation statements)

References 35 publications

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“…These environmental changes will likely have consequences for the biogeochemistry and ecology of the Arctic pelagic system (e.g., Piepenburg & Bluhm 2009;Weslawski et al 2009;Bluhm et al 2011;Wassmann 2011). Major impacts are expected for species composition, the pelagic food web, elemental and matter fluxes, i.e., carbon sequestering (e.g., Fortier et al 2002;Hirche & Kosobokova 2007;Li et al 2009;Morán et al 2010;Hilligsøe et al 2011;Lalande et al 2011;Engel et al 2013). Warming and rapid decrease in sea-ice extent and thickness in the Arctic Ocean eventually have an impact on primary productivity, species composition and thus on carbon export Wassmann 2011; Arrigo et al 2012;Boetius et al 2013).…”

Section: Discussionmentioning

confidence: 99%

Summertime plankton ecology in Fram Strait—a compilation of long- and short-term observations

et al. 2015

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Section: Discussionmentioning

confidence: 99%

Summertime plankton ecology in Fram Strait—a compilation of long- and short-term observations

et al. 2015

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“…Shifts in community size spectrum in response to rising temperatures are suggested by some studies (e.g., Hilligsøe et al, 2011), yet in others they are shown to depend primarily on total biomass and productivity (e.g., Maranón et al, 2012). Hence, ANNs could prove useful in examining these interactions in the context of variability among biogeochemical provinces rather than global average trends.…”

Section: Discussionmentioning

confidence: 99%

Distribution of phytoplankton functional types in high-nitrate, low-chlorophyll waters in a new diagnostic ecological indicator model

et al. 2013

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Abstract.Modeling and monitoring plankton functional types (PFTs) is challenged by the insufficient amount of field measurements of ground truths in both plankton models and biooptical algorithms. In this study, we combine remote sensing data and a dynamic plankton model to simulate an ecologically sound spatial and temporal distribution of phytoPFTs. We apply an innovative ecological indicator approach to modeling PFTs and focus on resolving the question of diatom-coccolithophore coexistence in the subpolar highnitrate and low-chlorophyll regions. We choose an artificial neural network as our modeling framework because it has the potential to interpret complex nonlinear interactions governing complex adaptive systems, of which marine ecosystems are a prime example. Using ecological indicators that fulfill the criteria of measurability, sensitivity and specificity, we demonstrate that our diagnostic model correctly interprets some basic ecological rules similar to ones emerging from dynamic models. Our time series highlight a dynamic phyto-PFT community composition in all high-latitude areas and indicate seasonal coexistence of diatoms and coccolithophores. This observation, though consistent with in situ and remote sensing measurements, has so far not been captured by state-of-the-art dynamic models, which struggle to resolve this "paradox of the plankton". We conclude that an ecological indicator approach is useful for ecological modeling of phytoplankton and potentially higher trophic levels. Finally, we speculate that it could serve as a powerful tool in advancing ecosystem-based management of marine resources.

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“…at the species, population and community scales (Brown et al 2004, Petchey et al 2008, Reuman et al 2008. Phytoplankton community size structure, in turn, influences carbon cycling in the ocean and, thereby, the global carbon cycle (Michaels & Silver 1988, Laws et al 2000, Hilligsøe et al 2011. Understanding the mechanisms controlling phytoplankton community size structure and how size structure may interact with climate change is thus imperative for predicting future ocean function.…”

Section: Introductionmentioning

confidence: 99%

Global patterns in phytoplankton community size structure—evidence for a direct temperature effect

Mousing

Ellegaard²,

Richardson³

2014

Mar. Ecol. Prog. Ser.

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Linking phytoplankton community size composition with temperature, plankton food web structure and sea–air CO2 flux

Cited by 88 publications

References 35 publications

Summertime plankton ecology in Fram Strait—a compilation of long- and short-term observations

Summertime plankton ecology in Fram Strait—a compilation of long- and short-term observations

Distribution of phytoplankton functional types in high-nitrate, low-chlorophyll waters in a new diagnostic ecological indicator model

Global patterns in phytoplankton community size structure—evidence for a direct temperature effect

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