Comparisons among ten models of acoustic backscattering used in aquatic ecosystem research

Author Posting. © Acoustical Society of America, 2015. This article is posted here by permission of Acoustical Society of America for personal use, not for redistribution. The definitive version was published in Journal of the Acoustical Society of America 138 (2015); 3742, doi:10.1121/1.4937607.Analytical and numerical scatteringmodels with accompanying digital representations are used increasingly to predict acoustic backscatter by fish and zooplankton in research and ecosystem monitoring applications. Ten such models were applied to targets with simple geometric shapes and parameterized (e.g., size and material properties) to represent biological organisms such as zooplankton and fish, and their predictions of acoustic backscatter were compared to those from exact or approximate analytical models, i.e., benchmarks. These comparisons were made for a sphere, spherical shell, prolate spheroid, and finite cylinder, each with homogeneous composition. For each shape, four target boundary conditions were considered: rigid-fixed, pressure-release, gas-filled, and weakly scattering. Target strength (dB re 1 m2) was calculated as a function of insonifying frequency (f = 12 to 400 kHz) and angle of incidence (θ = 0° to 90°). In general, the numerical models (i.e., boundary- and finite-element) matched the benchmarks over the full range of simulation parameters. While inherent errors associated with the approximate analytical models were illustrated, so were the advantages as they are computationally efficient and in certain cases, outperformed the numerical models under conditions where the numerical models did not convergeThis work was supported by the NOAA Fisheries Advanced Sampling Technologies Working Group, the Office of Naval Research, and the National Oceanic Partnership Program. Josiah S. Renfree

Prediction and confirmation of seasonal migration of Pacific sardine (Sardinops sagax) in the California Current Ecosystem

During the last century, the population of Pacific sardine (Sardinops sagax) in the California Current Ecosystem has exhibited large fluctuations in abundance and migration behavior. From approximately 1900 to 1940, the abundance of sardine reached 3.6 million metric tons and the “northern stock” migrated from offshore of California in the spring to the coastal areas near Oregon, Washington, and Vancouver Island in the summer. In the 1940s, the sardine stock collapsed and the few remaining sardine schools concentrated in the coastal region off southern California, year-round, for the next 50 years. The stock gradually recovered in the late 1980s and resumed its seasonal migration between regions off southern California and Canada. Recently, a model was developed which predicts the potential habitat for the northern stock of Pacific sardine and its seasonal dynamics. The habitat predictions were successfully validated using data from sardine surveys using the daily egg production method; scientific trawl surveys off the Columbia River mouth; and commercial sardine landings off Oregon, Washington, and Vancouver Island. Here, the predictions of the potential habitat and seasonal migration of the northern stock of sardine are validated using data from “acoustic–trawl” surveys of the entire west coast of the United States during the spring and summer of 2008. The estimates of sardine biomass and lengths from the two surveys are not significantly different between spring and summer, indicating that they are representative of the entire stock. The results also confirm that the model of potential sardine habitat can be used to optimally apply survey effort and thus minimize random and systematic sampling error in the biomass estimates. Furthermore, the acoustic–trawl survey data are useful to estimate concurrently the distributions and abundances of other pelagic fishes

Target strength of skipjack tuna (Katsuwanus pelamis) associated with fish aggregating devices (FADs)

[EN] This paper presents measures of target strength (TS; dB re 1 m(2)) and models of TS vs. fork length (L; cm), i.e. TS = 20log(L) + b(20), for skip-jack tuna associated with fish aggregating devices (FADs) in the Central Pacific Ocean. Measurements were made using 38-, 120-, and 200-kHz split-beam echosounders on a purse-seine workboat during fishing operations. To mitigate potential bias due to unresolved targets, TS measurements were rejected if they were not simultaneously detected with multiple echosounder frequencies in approximately the same location. The filtered TS and concomitantly sampled L data were used to estimate b(20) = -76, -71, and -70.5 dB for 38, 120, and 200 kHz, respectively, using the method of least squares. For comparison, quasi-independent estimates of TS and b(20) were calculated from acoustic echo-integration and catch data representing entire aggregations around the FADs. The results differed by <= 1 dB for all three frequencies. The sensitivities of these results to variations in fish morphology and behaviour were explored using a simulation of TS for fish without swimbladders. The utility of the results on acoustic properties of skipjack tuna and next research steps to achieve selective fishing at FADs are discussed.We thank the following organizations and people for their support of this work: the governments of Kiribati, Tuvalu, and Tokelau which permitted this research in their EEZs; Albacora for allowing this work aboard F/V ALBATUN TRES; Fishing Master Euken Mujika; the captain and crew; the scientists and divers J. Filmalter and F. Forget are thanked for invaluable insight about fish behaviour, vertical stratification and non-target species composition at FADs; Hector Pena for providing instruction on the sonar setup and analysis; Yolanda Lacalle for the illustration in Figure 2; and Andres Uriarte for advice concerning transmission of statistical errors. The research reported in the present document was funded by the International Seafood Sustainability Foundation (ISSF) and conducted independently by the authors. The report and its results, professional opinions and conclusions are solely the work of the authors. This paper is contribution 843 from AZTI (Marine or Food Research).Boyra, G..; Moreno, G.; Sobradillo, B.; Pérez Arjona, I.; Sancristóbal, I.; Demer, D. (2018). Target strength of skipjack tuna (Katsuwanus pelamis) associated with fish aggregating devices (FADs). ICES Journal of Marine Science. 75(5):1790-1802. https://doi.org/10.1093/icesjms/fsy041S1790180275

Identification of KIF21A mutations as a rare cause of congenital fibrosis of the extraocular muscles type 3 (CFEOM3).

PURPOSE. Three congenital fibrosis of the extraocular muscles phenotypes (CFEOM1-3) have been identified. Each represents a specific form of paralytic strabismus characterized by congenital restrictive ophthalmoplegia, often with accompanying ptosis. It has been demonstrated that CFEOM1 results from mutations in KIF21A and CFEOM2 from mutations in PHOX2A. This study was conducted to determine the incidence of KIF21A and PHOX2A mutations among individuals with the third CFEOM phenotype, CFEOM3. METHODS. All pedigrees and sporadic individuals with CFEOM3 in the authors' database were identified, whether the pedigrees were linked or consistent with linkage to the FEOM1, FEOM2, and/or FEOM3 loci was determined, and the appropriate pedigrees and the sporadic individuals were screened for mutations in KIF21A and PHOX2A. RESULTS. Twelve CFEOM3 pedigrees and 10 CFEOM3 sporadic individuals were identified in the database. The structures of eight of the pedigrees permitted the generation of meaningful linkage data. KIF21A was screened in 17 probands, and mutations were identified in two CFEOM3 pedigrees. One pedigree harbored a novel mutation (2841G-->A, M947I) and one harbored the most common and recurrent of the CFEOM1 mutations identified previously (2860C-->T, R954W). None of CFEOM3 pedigrees or sporadic individuals harbored mutations in PHOX2A. CONCLUSIONS. The results demonstrate that KIF21A mutations are a rare cause of CFEOM3 and that KIF21A mutations can be nonpenetrant. Although KIF21A is the first gene to be associated with CFEOM3, the results imply that mutations in the unidentified FEOM3 gene are the more common cause of this phenotype