Publications

Measurement Uncertainty

D.A. Demer and R. P. Hewitt, “Bias in acoustic biomass estimates of Euphausia superba due to diel migration,” Deep-Sea Res. II, 42 (4): 455-475. (1995). (pdf)

Abstract: The die1 vertical migration (DVM) of Antarctic krill (Euphausia superba) can greatly bias the results of qualitative and quantitative hydroacoustic surveys which are conducted with a down-looking sonar and irrespective of the time of day. To demonstrate and quantify these negative biases on both the estimates of biomass distribution and abundance, a time-depth-density analysis was performed. Data were collected, as part of the United States Antarctic Marine Living Resources Program (AMLR). in the vicinities of Elephant Island, Antarctica, during the austral summers of 1992 and 1993. Five surveys were conducted in 1992: two covered a 105 by 105 n.mi. area centered on Elephant Island, two encompassed a 60 by 35 n.mi. arca immediately to the north of the Island, and one covered a 1 n.mi.’ area centered on a large krill swarm to the west of Seal Island. The 1993 data include repetitions of the two small-area and two large-area surveys. Average krill volume dcnsitics were calculated for each hour as well as for three daily periods: day, twilight and night. These data were normalized and presented as a probability of daily average density. With spectral analysis to identify the frequencies of migration, a four-term periodic function was fitted to the probability density function of average daily biomass versus local apparent time. This function was transformed to create a temporal compensation function (TCF) for upwardly adjusting acoustic biomass estimates. The TCF was then applied to the original 19Y2 survey data; the resulting biomass estimates are an average of 49.5% higher than those calculated disregarding biases due to die1 vertical migration. The effect of DVM on the estimates of krill distribution are illustrated by a comparison of compensated and uncompensated density maps of two 1992 surveys. Through this technique, high density krill areas are revealed where uncompensated maps indicated low densities.

D.A. Demer, "An estimate of error for the CCAMLR 2000 survey estimate of krill biomass," Deep-Sea Research II, 51:1237-1251. (2004). (pdf)

Abstract: Combined sampling and measurement error was estimated for the CCAMLR 2000 acoustic estimate of krill abundance in the Scotia Sea. First, some potential sources of uncertainty in generic echo-integration surveys are reviewed. Then, specific to the CCAMLR 2000 survey, some of the primary sources of measurement error is explored. The error in system calibration is evaluated in relation to the effects of variations in water temperature and salinity on sound speed, sound absorption, and acoustic-beam characteristics. Variation in krill target strength is estimated using a distorted-wave Born approximation model fitted with measured distributions of animal lengths and orientations. The variable effectiveness of two-frequency species classification methods is also investigated using the same scattering model. Most of these components of measurement uncertainty are frequency-dependent and covariant. Ultimately, the total random error in the CCAMLR 2000 acoustic estimate of krill abundance is estimated from a Monte Carlo simulation which assumes independent estimates of krill biomass are derived from acoustic backscatter measurements at three frequencies (38, 120, and 200 kHz). The overall coeficient of variation (10.2<CV<11.6%; 95% CI) is not significantly different from the sampling variance alone (CV = 11.4%). That is, the measurement variance is negligible relative to the sampling variance due to the large number of measurements averaged to derive the ultimate biomass estimate. Some potential sources of bias (e.g., stemming from uncertainties in the target strength model, the krill length-to-weight model, the species classification method, bubble attenuation, signal thresholding, and survey area definition) may be more appreciable components of measurement uncertainty.

Last modified: 12/24/2014