WorldCat Identities

Hanselman, Dana Henry

Works: 5 works in 6 publications in 1 language and 19 library holdings
Genres: Observations 
Roles: Author
Classifications: SH11.A2,
Publication Timeline
Most widely held works by Dana Henry Hanselman
Growth and mortality of rockfishes (Scorpaenidae) from Alaska waters by Patrick William Malecha( Book )

1 edition published in 2007 in English and held by 8 WorldCat member libraries worldwide

Gulf of Alaska Pacific ocean perch : stock assessment, survey design and sampling by Dana Henry Hanselman( )

2 editions published in 2004 in English and held by 5 WorldCat member libraries worldwide

"Pacific ocean perch (Sebastes alutus) stock size in the Gulf of Alaska has been difficult to assess because of an imprecise survey biomass index. This imprecision has been attributed to low sampling effort on a species with an aggregated distribution. In this thesis, I examined the importance of estimated survey biomass in the stock assessment and ways to improve them. First, I presented the complete stock assessment for 2003, with an analysis of uncertainty. Uncertain parameters included natural mortality, recruitment, and biomass estimates. Second, I examined adaptive cluster sampling (ACS) as a method to reduce survey uncertainty. ACS results provided lower estimates of mean abundance and lower standard errors than did simple random sampling (SRS). Bootstrapping suggested that the ACS mean may be a superior measure of central tendency. ACS results were better than SRS, but not as dramatically as suggested by previous literature. I used simulations to explore why ACS did not perform optimally. These simulations showed that it would be necessary to sample over 10% of the population to obtain large gains in precision. This is impractical for a large marine population. I explored the use of hydroacoustic data recorded on survey vessels to gain precision in biomass estimation. I used the data to (1) develop a catch prediction model based on near-bottom backscatter, (2) simulate an adaptive design, (3) apply ratio estimation in double sampling using hydroacoustic data, and (4) post-stratify survey data. Using hydroacoustic data in these designs showed gains in precision over SRS and may be useful. Finally, I used the S. alutus age structured model presented above to simulate effects of five factors: survey measurement error, catchability trends, a second biomass index, data source weighting, and sensitivity of prior distributions. Simulations showed that the stock assessment model was ineffective at high measurement error and was unable to detect trends in the data. A second biomass index yielded gains in model precision. The weight given lengths measured in the fishery was most important because of its long time series, and the prior distribution on natural mortality was most influential because it was difficult to estimate"--Leaf iii
Report to industry on the Alaska Sablefish Tag Program, 1972-2012 by K Echave( )

1 edition published in 2013 in English and held by 2 WorldCat member libraries worldwide

"This report summarizes release and recovery data within the tag database and describes the results of studies utilizing these tag data by NMFS and others on sablefish age, growth, and migration. Hopefully it will prove both interesting and informative for those who have contributed the largest share of the data: individual members of the fishing industry"--Preface
Adaptive cluster sampling of Gulf of Alaska rockfish by Dana Henry Hanselman( Book )

1 edition published in 2000 in English and held by 2 WorldCat member libraries worldwide

"National Marine Fisheries Service trawl surveys result in more variable biomass estimates for long-lived Gulf of Alaska rockfish than researchers expect. Adaptive cluster sampling (ACS) was investigated to improve these surveys. In August 1998 east of Kodiak, AK, a sampling cruise tested ACS for Pacific ocean perch (POP), and shortraker and rougheye rockfish (SR/RE). In each of six strata, simple random sampling was conducted, then ACS was performed on top stations. Stopping rules prevented sampling from continuing indefinitely. Results did not resolve whether ACS alone was better than simple random sampling. ACS, combined with stratification, increased precision of POP estimates by 30% over random sampling, suggesting that the spatial distribution has both fine-scale and habitat-scale patterns. Variograms indicated that the expected aggregation was not encountered for POP, but that POP are more aggregated than SR/RE. Some diel movement of POP was evident. Both species were concentrated at specific depths"--Leaf iii
A comparison of statistical methods to standardize catch-per-unit-effort of the Alaska longline sablefish fishery by Mathieu( )

1 edition published in 2014 in English and held by 2 WorldCat member libraries worldwide

"Improving existing catch per unit effort (CPUE) models for construction of a fishery abundance index is important to the Alaska sablefish (Anoplopoma fimbria) stock assessment. Performance of statistical methods including Generalized Linear Models (GLM), Generalized Additive Models (GAM), and Boosted Regression Trees (BRT) were evaluated using CPUE data collected by observers from the sablefish longline fishery in the Gulf of Alaska, the Bering Sea, and the Aleutian Islands during 1995-2011. Due to the nonlinearity of several important covariates found during the diagnostics, GLM was dismissed as a potential method to standardize CPUE. Fitted GAM models for the Gulf of Alaska subregions: West Yakutat, Western Gulf, Central Gulf, and Southeast accounted for 42%, 29%, 30%, and 45% of total model deviance explained, respectively. BRT models accounted for 47%, 31%, 30%, and 46 %, respectively. For the Bering Sea and Aleutian Islands subregions, fitted GAM models accounted for 58% and 54% of total model deviance explained, respectively. BRT models accounted for 63% and 60% for the Bering Sea and the Aleutian Islands subregions, respectively. Predictive performance metrics (Root Mean Square Error) and 5-fold cross-validation results showed GAM and BRT models had similar predictive power. However, variance was significantly higher in GAM model predictions. In general, the BRT model performance was superior or equally robust to traditional methods such as GLM and GAM and should be considered as a potential statistical method for CPUE standardization."
Audience Level
Audience Level
  Kids General Special  
Audience level: 0.58 (from 0.14 for Adaptive c ... to 0.73 for Report to ...)

Alternative Names
Hanselman, D. H.

Hanselman, D. H. (Dana Henry)