Spatial distribution of Antarctic minke whales (Balaenoptera bonaerensis) in relation to spatial distributions of krill in the Ross Sea,Antarctica

The spatial distribution of Antarctic minke whales in the Ross Sea with relation to spatial distributions of their prey – krill – was investigated in this study using generalized additive models (GAMs). Spatial distributions of two species of krill (ice and Antarctic krill) were estimated by GAMs. Three abiotic factors – distance from the continental shelf break (800 m isobaths), the mean temperature and salinity from the surface to 200 m (MTEM‐200 and MSAL‐200), and latitude and longitude – were used as covariates for models of krill. Estimated spatial distributions of krill were then used with other covariates to model the spatial distribution of Antarctic minke whales. In the selected model of Antarctic minke whales, Antarctic krill were more influential than ice krill. The number of Antarctic minke whales increased as the density of Antarctic krill increased to around 1.5 g m^?2. Beyond that, the number of Antarctic minke whales decreased as the density of Antarctic krill increased. High densities of the Antarctic minke whales were estimated along the sea ice edge in the eastern part of the Ross Sea. Specifically, the densities were high in the north of the continental shelf break where low MTEM‐200 and MSAL‐200 and intermediate densities of Antarctic krill were observed. Further data collection is needed to investigate interannual variations and trends in their relationship. The results show that the spatial distribution of Antarctic minke whales is a function of longitude, distance from the shelf break, oceanographic condition (temperature and salinity), and densities of ice and Antarctic krill.     

Density estimation of the giant jellyfish Nemopilema nomurai around Japan using an alternative modified detection function for left truncation in a line transect survey

Information on the distribution and bloom scale of the giant jellyfish Nemopilema nomurai is necessary to understand the impact on fisheries. In October 2009, we had an opportunity for visual counting of N. nomurai around Japan from a research/training vessel. To take into account possibly severe missed detection of N. nomurai in the close vicinity of the vessel, detection functions were modified by introducing an additional parameter δ expressing the proportion of detectable N. nomurai within a threshold perpendicular distance. Some covariate effects in the detection process were also investigated. The δ-modified hazard-rate detection function with δ variation parameter of jellyfish body size was chosen as the best-fit one by AIC model selection. The results suggested that a higher proportion (>30 % or more) of N. nomurai were undetected in the vicinity of vessel. The δ-modified model had an advantage of no loss of left-truncated data and provided better estimation of density with the smaller coefficient of variation than the conventional left truncation approach. It is applicable to other line transect surveys, e.g. aerial surveys. High densities of N. nomurai were found in the central part of the Sea of Japan and off Iwate Prefecture.     

Comparison of biomass estimates from multiple stratification approaches in a swept area method for Pacific saury Cololabis saira in the western North Pacific

Fishery-independent surveys using sea surface trawl nets for Pacific saury Cololabis saira in the western North Pacific since 2003 have enabled the investigation of their annual distribution patterns and total biomass during June and July, prior to the main fishing season in Japan. We compared biomass estimates and their associated variances derived based on five different post-stratification approaches in a swept area method, and then observed that these approaches have little effect on biomass estimates and their precision, owing to well-organized survey designs and homogeneously allocated sampling stations. We were able to utilize decreasing biomass estimates for 15 years as an essential abundance index in the ongoing stock assessment. Notably, examination based on stratification along with longitudinal survey lines indicated that the estimated biomass had decreased in the western survey area, resulting in an eastward shift in the gravity center of Pacific saury distribution after 2010. We recommend biomass estimation in an east–west direction based on longitudinal stratification as an effective measure to develop population dynamics models which reflect westward migration into the fishing grounds around Japanese coastal waters, and to forecast the expected catch during the subsequent fishing period.

     

Age and growth of yellowstriped butterfish, <Emphasis Type="Italic">Labracoglossa argentiventris</Emphasis>, around Izu Oshima Island

ABSTRACT:   Age and growth of the yellowstriped butterfish, Labracoglossa argentiventris , around Izu Oshima Island were studied using a total of 1450 fish. Age was determined by counting the edge of the opaque zones as a ring mark on sectioned sagittal otoliths. Formation of the first ring was observed during spring or summer, corresponding to 1.5 years after hatching. Thereafter, one ring was formed each year in the same season as the previous year. The growth of the butterfish was rapid until 2 years of age. The maximum likelihood method was applied to the age and length data for estimating parameters in von Bertalanffy, Gompertz, and Logistic growth models. The selected model, based on the Akaike Information Criterion, was the von Bertalanffy growth model, which indicated differential asymptotic length and variance by sex.     

A resource selection model for analyzing pseudoreplicated data due to grouping behavior of animals

Quantifying resource selection is of primary interest in animal ecology. Many analyses of resource selection assume spatial and temporal independence of the sampling unit. Autocorrelation between observations, which is a general property of ecological variables, causes difficulties for most standard statistical procedures of resource selection because autocorrelated data violate the assumption of independence. To overcome this problem, we develop a mixed-effects model to estimate resource selection functions from data that are autocorrelated because of unobserved grouping behavior by animals. In the application of the expectation-maximization (EM) algorithm, the computation of the conditional expectation of the complete-data log-likelihood function does not have a closed-form solution requiring numerical integration. A Monte Carlo EM algorithm with Gibbs sampling can be used effectively in such situations to find exact maximum likelihood estimates. We propose a simple automated Monte Carlo EM algorithm with multiple sequences in which the Monte Carlo sample size is increased when the EM step is swamped by Monte Carlo errors.We demonstrate that the model can detect inherent autocorrelation and provide reasonable variance estimates when applied to nocturnal bird migration data. This approach could also be applied to ecological processes with various types of spatially and temporally autocorrelated data, circumventing serious problems caused by dangerous pseudoreplication.     

Modelling the contact probability and size-selectivity of toothed dredges

ABSTRACT:   To estimate fishing gear selectivity of clam dredges from data of paired-gear tests in the SELECT analysis process, this paper presents a statistical model of the probability of a clam coming into contact with the dredge teeth and size-selectivity of the control gear. The net-mouth available selectivity is defined as the product of the probability of a clam contacting the dredge teeth and size-selectivity induced by tooth spacing. The model based on the SELECT analysis was tested by using data generated by virtual paired-gear test in which the control dredge of the smallest tooth spacing is assumed to be size-selective. No clear difference in shell length distribution between dredges of different tooth spacings was found in the simulation when the contact probability was small. The plots of proportion of clams caught in the test dredge to the total catch number of clams were U-shaped, and the model fitted the data well. For each simulation consisting of 500 replications, the sample mean and mean square error of each parameter were obtained to evaluate the performance of estimation by comparing with the true value. Parameters were properly estimated with the model.     

Correction to: Comparison of biomass estimates from multiple stratification approaches in a swept area method for Pacific saury Cololabis saira in the western North Pacific

Fisheries Science - A correction to this paper has been published: https://doi.org/10.1007/s12562-021-01506-9     

Estimation of the abundance of the sei whale <Emphasis Type="Italic">Balaenoptera borealis</Emphasis> in the central and eastern North Pacific in summer using sighting data from 2010 to 2012

The abundance of the sei whale Balaenoptera borealis in the central and eastern North Pacific (north of 40°N, south of the Alaskan coast including both the US and Canadian Exclusive Economic Zones between 170°E and 135°W), from July to August, was estimated by the line transect method using sighting data obtained during the 2010–2012 International Whaling Commission-Pacific Ocean Whale and Ecosystem Research cruises. The probability of detecting whales at a perpendicular distance from the transect was estimated using two different models: hazard rate and half-normal models. Because the difference in Akaike’s information criterion between the two models was small, the Akaike weighted average of the two models was taken, which gave an estimated abundance of 29,632 (coefficient of variation, 0.242; 95% confidence interval, 18,576–47,267). This is the first abundance estimate of sei whales in this region based on systematic sighting survey data, which contributes to an understanding of the current status of this species.     

Spatial and temporal migration modeling for stock of Pacific saury Cololabis saira (Brevoort), incorporating effect of sea surface temperature

ABSTRACT:   A model is proposed that expresses the spatial and temporal migration pattern for stock of Pacific saury Cololabis saira (Brevoort), in order to investigate the effect of sea surface temperature (SST) on migration rates. Two factors are considered: (i) Saury emigrate to waters of an optimal SST zone; and (ii) saury immigrate from water zone that is extremely cold for saury. Parameters of migration and initial levels of stock are estimated with a maximum likelihood method based on catch per unit effort (CPUE) data for 1995–2001. The best model was selected using Akaike's information criteria. The results suggested that the emigration rate to southern adjacent regions is dependent on the coverage proportion of their waters under some threshold temperatures; 20°C to Doutou and Sanriku, 23°C to Joban and Izu.