42 resultados para Factorial experiment designs.


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Concentrations of dimethylsulfide (DMS) and its precursor dimethylsulfoniopropionate (DMSP) are highly variable in time and space. What is driving the variability in DMS(P), and can those variability be explained by physical processes and changes in the biological community? During the Southern Ocean Gas Exchange Experiment (SO GasEx) in the austral fall of 2008, two 3He/SF6 labeled patches were created in the surface water. SF6 and DMS were surveyed continuously in a Lagrangian framework, while direct measurements of air-sea exchange further constrained the gas budgets. Turbulent diffusivity at the base of the mixed layer was estimated from SF6 profiles and used to calculate the vertical fluxes of DMS and nutrients. Increasing mixed layer nutrient concentrations due to mixing were associated with a shift in the phytoplankton community structure, which in turned likely affected the sulfur dynamics on timescales of days. DMS concentration as well as air-sea DMS flux appeared to be decoupled from the DMSP concentration, possibly due to grazing and bacterial DMS production. Contrary to expectations, in an environment with high winds and modest productivity, physical processes (air-sea exchange, photochemistry, vertical mixing) only accounted for a small fraction of DMS loss from the surface water. Among the DMS sinks, inferred biological consumption most likely dominated during SO GasEx.

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Largely used as a natural biological tag in studies of dispersal/connectivity of fish, otolith elemental fingerprinting is usually analyzed by laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS). LA-ICP-MS produces an elemental fingerprint at a discrete time-point in the life of a fish and can generate data on within-otolith variability of that fingerprint. The presence of within-otolith variability has been previously acknowledged but not incorporated into experimental designs on the presumed, but untested, grounds of both its negligibility compared to among-otolith variability and of spatial autocorrelation among multiple ablations within an otolith. Here, using a hierarchical sampling design of spatial variation at multiple scales in otolith chemical fingerprints for two Mediterranean coastal fishes, we explore: 1) whether multiple ablations within an otolith can be used as independent replicates for significance tests among otoliths, and 2) the implications of incorporating within-otolith variability when assessing spatial variability in otolith chemistry at a hierarchy of spatial scales (different fish, from different sites, at different locations on the Apulian Adriatic coast). We find that multiple ablations along the same daily rings do not necessarily exhibit spatial dependency within the otolith and can be used to estimate residual variability in a hierarchical sampling design. Inclusion of within-otolith measurements reveals that individuals at the same site can show significant variability in elemental uptake. Within-otolith variability examined across the spatial hierarchy identifies differences between the two fish species investigated, and this finding leads to discussion of the potential for within-otolith variability to be used as a marker for fish exposure to stressful conditions. We also demonstrate that a 'cost'-optimal allocation of sampling effort should typically include some level of within-otolith replication in the experimental design. Our findings provide novel evidence to aid the design of future sampling programs and improve our general understanding of the mechanisms regulating elemental fingerprints.

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The seeding of an expanse of surface waters in the equatorial Pacific Ocean with low concentrations of dissolved iron triggered a massive phytoplankton bloom which consumed large quantities of carbon dioxide and nitrate that these microscopic plants cannot fully utilize under natural conditions. These and other observations provide unequivocal support for the hypothesis that phytoplankton growth in this oceanic region is limited by iron bioavailability.

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Carbon capture and storage is a mitigation strategy that can be used to aid the reduction of anthropogenic CO2 emissions. This process aims to capture CO2from large point-source emitters and transport it to a long-term storage site. For much of Europe, these deep storage sites are anticipated to be sited below the sea bed on continental shelves. A key operational requirement is an understanding of best practice of monitoring for potential leakage and of the environmental impact that could result from a diffusive leak from a storage complex. Here we describe a controlled CO2release experiment beneath the seabed, which overcomes the limitations of laboratory simulations and natural analogues. The complex processes involved in setting up the experimental facility and ensuring its successful operation are discussed, including site selection, permissions, communications and facility construction. The experimental design and observational strategy are reviewed with respect to scientific outcomes along with lessons learnt in order to facilitate any similar future.

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Scepticism over stated preference surveys conducted online revolves around the concerns over “professional respondents” who might rush through the questionnaire without sufficiently considering the information provided. To gain insight on the validity of this phenomenon and test the effect of response time on choice randomness, this study makes use of a recently conducted choice experiment survey on ecological and amenity effects of an offshore windfarm in the UK. The positive relationship between self-rated and inferred attribute attendance and response time is taken as evidence for a link between response time and cognitive effort. Subsequently, the generalised multinomial logit model is employed to test the effect of response time on scale, which indicates the weight of the deterministic relative to the error component in the random utility model. Results show that longer response time increases scale, i.e. decreases choice randomness. This positive scale effect of response time is further found to be non-linear and wear off at some point beyond which extreme response time decreases scale. While response time does not systematically affect welfare estimates, higher response time increases the precision of such estimates. These effects persist when self-reported choice certainty is controlled for. Implications of the results for online stated preference surveys and further research are discussed.