Abstract. The current article describes statistical power analysis as an efficient strategy for the estimation of the optimum sample size. The principle aim is constructively to criticise and enrich the results presented by Mouillot et al. (1999) , who estimate the optimum sample size for evaluating possible perturbations. The authors did not make any reference to statistical power analysis, even though their objective clearly went beyond a simple stock evaluation to assess management strategies in a particular marine ecosystem. Surprisingly, they proposed (a priori) an ANOVA design to test a hypothesis considering both space and temporal scales. However, the authors did not cover important topics related with power analysis and the precautionary principle, both used into environment impact assessment programmes for marine ecosystems. Based on their results and on statistical power analysis, it is demonstrated that the variability (dispersion statistics), a key factor they used to estimate the sample size, is less relevant than the magnitude of perturbation (effect size). Therefore, a greater effort must be devoted to estimate the effect size of a particular phenomenon rather than a desired variability. 相似文献
A fluorescent sand-tracer experiment was performed at Comporta Beach (Portugal) with the aim of acquiring longshore sediment transport data on a reflective beach, the optimization of field and laboratory tracer procedures and the improvement of the conceptual model used to support tracer data interpretation.
The field experiment was performed on a mesotidal reflective beach face in low energetic conditions (significant wave height between 0.4 and 0.5 m). Two different colour tracers (orange and blue) were injected at low tide and sampled in the two subsequent low tides using a high resolution 3D grid extending 450 m alongshore and 30 m cross-shore. Marked sand was detected using an automatic digital image processing system developed in the scope of the present experiment.
Results for the two colour tracers show a remarkable coherence, with high recovery rates attesting data validity. Sand tracer displayed a high advection velocity, but with distinct vertical distribution patterns in the two tides: in the first tide there was a clear decrease in tracer advection velocity with depth while in the second tide, the tracer exhibited an almost uniform vertical velocity distribution. This differing behaviour suggests that, in the first tide, the tracer had not reached equilibrium within the transport system, pointing to a considerable time lag between injection and complete mixing. This issue has important implications for the interpretation of tracer data, indicating that short term tracer experiments tend to overestimate transport rates. In this work, therefore, longshore estimates were based on tracer results obtained during the second tide.
The estimated total longshore transport rate at Comporta Beach was 2 × 10− 3 m3/s, more than four times larger than predicted using standard empirical longshore formulas. This discrepancy, which results from the unusually large active moving layer observed during the experiment, confirms the idea that most common longshore transport equations under-estimate total sediment transport in plunging/surging waves. 相似文献
A seamount chain with an approximately WNW trend is observed in the northeastern Ulleung Basin. It has been argued that these
seamounts, including two islands called Ulleung and Dok islands, were formed by a hotspot process or by ridge related volcanism.
Many geological and geophysical studies have been done for all the seamounts and islands in the chain except Anyongbok Seamount,
which is close to the proposed spreading ridge. We first report morphological characteristics, sediment distribution patterns,
and the crustal thickness of Anyongbok Seamount using multibeam bathymetry data, seismic reflection profiles, and 3D gravity
modeling. The morphology of Anyongbok Seamount shows a cone shaped feature and is characterized by the development of many
flank cones and flank rift zones. The estimated surface volume is about 60 km3, and implies that the seamount is smaller than the other seamounts in the chain. No sediments have been observed on the seamount
except the lower slope, which is covered by more than 1,000 m of strata. The crustal structure obtained from a 3D gravity
modeling (GFR = 3.11, SD 3.82 = mGal) suggests that the seamount was formed around the boundary of the Ulleung Plateau and
the Ulleung Basin, and the estimated crustal thickness is about 20 km, which is a little thicker than other nearby seamounts
distributed along the northeastern boundary of the Ulleung Basin. This significant crustal thickness also implies that Anyongbok
Seamount might not be related to ridge volcanism. 相似文献