4 resultados para Compartments

em DigitalCommons - The University of Maine Research


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Peatlands deform elastically during precipitation cycles by small (+/- 3 cm) oscillations in surface elevation. In contrast, we used a Global Positioning System network to measure larger oscillations that exceeded 20 cm over periods of 4 - 12 hours during two seasonal droughts at a bog and fen site in northern Minnesota. The second summer drought also triggered 19 depressuring cycles in an overpressured stratum under the bog site. The synchronicity between the largest surface deformations and the depressuring cycles indicates that both phenomena are produced by the episodic release of large volumes of gas from deep semi-elastic compartments confined by dense wood layers. We calculate that the three largest surface deformations were associated with the release of 136 g CH4 m(-2), which exceeds by an order of magnitude the annual average chamber fluxes measured at this site. Ebullition of gas from the deep peat may therefore be a large and previously unrecognized source of radiocarbon depleted methane emissions from northern peatlands.

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A basin-wide interdecadal change in both the physical state and the ecology of the North Pacific occurred near the end of 1976. Here we use a physical-ecosystem model to examine whether changes in the physical environment associated with the 1976-1977 transition influenced the lower trophic levels of the food web and if so by what means. The physical component is an ocean general circulation model, while the biological component contains 10 compartments: two phytoplankton, two zooplankton, two detritus pools, nitrate, ammonium, silicate, and carbon dioxide. The model is forced with observed atmospheric fields during 1960-1999. During spring, there is a similar to 40% reduction in plankton biomass in all four plankton groups during 1977-1988 relative to 1970-1976 in the central Gulf of Alaska (GOA). The epoch difference in plankton appears to be controlled by the mixed layer depth. Enhanced Ekman pumping after 1976 caused the halocline to shoal, and thus the mixed layer depth, which extends to the top of the halocline in late winter, did not penetrate as deep in the central GOA. As a result, more phytoplankton remained in the euphotic zone, and phytoplankton biomass began to increase earlier in the year after the 1976 transition. Zooplankton biomass also increased, but then grazing pressure led to a strong decrease in phytoplankton by April followed by a drop in zooplankton by May: Essentially, the mean seasonal cycle of plankton biomass was shifted earlier in the year. As the seasonal cycle progressed, the difference in plankton concentrations between epochs reversed sign again, leading to slightly greater zooplankton biomass during summer in the later epoch.

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Application of biogeochemical models to the study of marine ecosystems is pervasive, yet objective quantification of these models' performance is rare. Here, 12 lower trophic level models of varying complexity are objectively assessed in two distinct regions (equatorial Pacific and Arabian Sea). Each model was run within an identical one-dimensional physical framework. A consistent variational adjoint implementation assimilating chlorophyll-a, nitrate, export, and primary productivity was applied and the same metrics were used to assess model skill. Experiments were performed in which data were assimilated from each site individually and from both sites simultaneously. A cross-validation experiment was also conducted whereby data were assimilated from one site and the resulting optimal parameters were used to generate a simulation for the second site. When a single pelagic regime is considered, the simplest models fit the data as well as those with multiple phytoplankton functional groups. However, those with multiple phytoplankton functional groups produced lower misfits when the models are required to simulate both regimes using identical parameter values. The cross-validation experiments revealed that as long as only a few key biogeochemical parameters were optimized, the models with greater phytoplankton complexity were generally more portable. Furthermore, models with multiple zooplankton compartments did not necessarily outperform models with single zooplankton compartments, even when zooplankton biomass data are assimilated. Finally, even when different models produced similar least squares model-data misfits, they often did so via very different element flow pathways, highlighting the need for more comprehensive data sets that uniquely constrain these pathways.

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Animal guts have been idealized as axially uniform plug-flow reactors (PFRs) without significant axial mixing or as combinations in series of such PFRs with other reactor types. To relax these often unrealistic assumptions and to provide a means for relaxing others, I approximated an animal gut as a series of n continuously stirred tank reactors (CSTRs) and examined its performance as a Function of n. For the digestion problem of hydrolysis and absorption in series, I suggest as a first approximation that a tubular gut of length L and diameter D comprises n=L/D tanks in series. For n greater than or equal to 10, there is little difference between performance of the nCSTR model and an ideal PFR in the coupled tasks of hydrolysis and absorption. Relatively thinner and longer guts, characteristic of animals feeding on poorer forage, prove more efficient in both conversion and absorption by restricting axial mixing, in the same total volume, they also give a higher rate of absorption. I then asked how a fixed number of absorptive sites should be distributed among the n compartments. Absorption rate generally is maximized when absorbers are concentrated in the hindmost few compartments, but high food quality or suboptimal ingestion rates decrease the advantage of highly concentrated absorbers. This modeling approach connects gut function and structure at multiple scales and can be extended to include other nonideal reactor behaviors observed in real animals.