Carbon cycling in the deep eastern North Pacific benthic food web: Investigating the effect of organic carbon input
Dunlop, K.M.; Van Oevelen, D.; Ruhl, H.A.; Huffard, C.L.; Kuhnz, L.A.; Smith, K.L. (2016). Carbon cycling in the deep eastern North Pacific benthic food web: Investigating the effect of organic carbon input. Limnol. Oceanogr. 61(6): 1956–1968. dx.doi.org/10.1002/lno.10345
In: Limnology and Oceanography. American Society of Limnology and Oceanography: Waco, Tex., etc. ISSN 0024-3590; e-ISSN 1939-5590, meer
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| Auteurs | | Top |
- Dunlop, K.M.
- Van Oevelen, D., meer
- Ruhl, H.A.
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- Huffard, C.L.
- Kuhnz, L.A.
- Smith, K.L.
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| Abstract |
The deep ocean benthic environment plays a role in long-term carbon sequestration. Understanding carbon cycling in the deep ocean floor is critical to evaluate the impact of changing climate on the oceanic systems. Linear inverse modeling was used to quantify carbon transfer between compartments in the benthic food web at a long time-series study site in the abyssal northeastern Pacific (Station M). Linear inverse food web models were constructed for three separate years in the time-series when particulate organic carbon (POC) flux was relatively high (1990: 0.63 mean mmol C m−2 d−1), intermediate (1995: 0.24) and low (1996: 0.12). Carbon cycling in all years was dominated by the flows involved in the microbial loop; dissolved organic carbon uptake by microbes (0.80–0.95 mean mmol C m−2 d−1), microbial respiration (0.52–0.61), microbial biomass dissolution (0.09–0.18) and the dissolution of refractory detritus (0.46–0.65). Moreover, the magnitude of carbon flows involved in the microbial loop changed in relation to POC input, with a decline in contribution during the high POC influxes, such as those recently experienced at Station M. Results indicate that during high POC episodic pulses the role of faunal mediated carbon cycling would increase. Semi-labile detritus dominates benthic faunal diets and the role of labile detritus declined with increased total POC input. Linear inverse modeling represents an effective framework to analyze high-resolution time-series data and demonstrate the impact of climate change on the deep ocean carbon cycle in a coastal upwelling system. |
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