Trade-offs between monitoring objectives and monitoring effort when classifying regional conservation status of Pacific salmon (Oncorhynchus spp.) populations

2011 ◽  
Vol 68 (5) ◽  
pp. 880-897 ◽  
Author(s):  
Kendra R. Holt ◽  
Randall M. Peterman ◽  
Sean P. Cox
Keyword(s):  
Missing Data ◽  
Coho Salmon ◽  
Pacific Salmon ◽  
Conservation Status ◽  
Temporal Trends ◽  
Spatial And Temporal Variation ◽  
Spatial And Temporal Variability ◽  
Sampling Effort ◽  
Observation Error ◽  
Data Set

Conservation objectives aimed at maintaining the diversity of Pacific salmon ( Oncorhynchus spp.) are often expressed as a desire to ensure that spawner abundance is spread out over a number of spawning sites. However, sampling is not usually possible at all sites or in all years. For such incomplete data sets, rotating panel sampling designs and hierarchical estimation models have been suggested as ways to improve monitoring performance. To evaluate the potential benefits of using these approaches to assess the conservation status of coho salmon ( O. kisutch ), we developed a simulation procedure that modelled spatial and temporal variation in salmon abundance at multiple sites within a region. Results show that both approaches were largely unsuccessful at reducing classification errors for conservation status. Furthermore, indicators describing distributions of abundance levels and temporal trends in abundance within a region were more sensitive to missing data than to observation error variance on annual abundance estimates. Thus, sampling effort might be better spent reducing the level of missing data within a regional data set, as opposed to obtaining more precise estimates for only a few site–year combinations. Our results also show that the best monitoring plans for regions depend on monitoring objectives as well as the relative magnitudes of spatial and temporal variability.

Metrics and sampling designs for detecting trends in the distribution of spawning Pacific salmon (Oncorhynchus spp.)

2012 ◽  
Vol 69 (4) ◽  
pp. 681-694 ◽  
Author(s):  
Stephanie J. Peacock ◽  
Carrie A. Holt
Keyword(s):  
Population Dynamics ◽  
Environmental Variability ◽  
Coho Salmon ◽  
Pacific Salmon ◽  
Oncorhynchus Kisutch ◽  
Sensitivity Analyses ◽  
Observation Error ◽  
Simulated Population ◽  
Age At Maturity ◽  
Status Assessment

The distribution of individuals among populations and in space may contribute to their resilience under environmental variability. Changes in distribution may indicate the loss of genetically distinct subpopulations, the deterioration of habitat capacity, or both. The distribution of Pacific salmon ( Oncorhynchus  spp.) among spawning locations has recently been recognized as an important component of status assessment by USA and Canadian management agencies, but metrics of spawning distribution have not been rigorously evaluated. We evaluated three metrics of spawning distribution and four sampling designs for their ability to detect simulated contractions in the production of coho salmon ( Oncorhynchus kisutch ). We simulated population dynamics at 100 sites using a spawner–recruit model that incorporated natural variability in recruitment, age-at-maturity, dispersal, and measurement error in observations of abundance. Sensitivity analyses revealed that high observation error and straying of spawners from their natal streams may mask changes in distribution. Furthermore, monitoring only sites with high spawner abundance, as is often practiced, failed to capture the simulated contraction of production, emphasizing the importance of matching monitoring programs with assessment objectives.

Applying time series models with spatial correlation to identify the scale of variation in habitat metrics related to threatened coho salmon (Oncorhynchus kisutch) in the Pacific Northwest

2012 ◽  
Vol 69 (11) ◽  
pp. 1773-1782 ◽  
Author(s):  
Eric J. Ward ◽  
George R. Pess ◽  
Kara Anlauf-Dunn ◽  
Chris E. Jordan
Keyword(s):  
Time Series ◽  
Spatial Correlation ◽  
Pacific Northwest ◽  
Coho Salmon ◽  
Spatial Scales ◽  
Oncorhynchus Kisutch ◽  
Fine Sediment ◽  
Environmental Stochasticity ◽  
Observation Error ◽  
Data Set

Trend analyses are common in the analysis of fisheries data, yet the majority of them ignore either observation error or spatial correlation. In this analysis, we applied a novel hierarchical Bayesian state-space time series model with spatial correlation to a 12-year data set of habitat variables related to coho salmon ( Oncorhynchus kisutch ) in coastal Oregon, USA. This model allowed us to estimate the degree of spatial correlation separately for each habitat variable and the importance of observation error relative to environmental stochasticity. This framework allows us to identify variables that would benefit from additional sampling and variables where sampling could be reduced. Of the eight variables included in our analysis, we found three metrics related to habitat quality correlated at large spatial scales (gradient, fine sediment, shade cover). Variables with higher observation error (pools, active channel width, fine sediment) could be made more precise with more repeat visits. Our spatio-temporal model is flexible and extendable to virtually any spatially explicit monitoring data set, even with large amounts of missing data and no repeated observations. Potential extensions include fisheries catch data, abiotic indicators, invasive species, or species of conservation concern.

Historical trends in productivity of 120 Pacific pink, chum, and sockeye salmon stocks reconstructed by using a Kalman filter

2008 ◽  
Vol 65 (9) ◽  
pp. 1842-1866 ◽  
Author(s):  
Brigitte Dorner ◽  
Randall M. Peterman ◽  
Steven L. Haeseker
Keyword(s):  
Kalman Filter ◽  
Sockeye Salmon ◽  
Pacific Salmon ◽  
Stock Assessment ◽  
Temporal Trends ◽  
Survival Rates ◽  
Estimation Procedure ◽  
Oncorhynchus Gorbuscha ◽  
Oncorhynchus Keta ◽  
Observation Error

Temporal trends in productivity of Pacific salmon ( Oncorhynchus spp.) stocks are important to detect in a timely and reliable manner to permit appropriate management responses. However, detecting such trends is difficult because observation error and natural variability in survival rates tend to obscure underlying trends. A Kalman filter estimation procedure has previously been shown to be effective in such situations. We used it on a Ricker spawner–recruit model to reconstruct indices of annual productivity (recruits per spawner (R/S) at low spawner abundance) based on historical data for 120 stocks of pink ( Oncorhynchus gorbuscha ), chum ( Oncorhynchus keta ), and sockeye ( Oncorhynchus nerka ) salmon. These stocks were from Washington, British Columbia, and Alaska. The resulting estimated temporal trends in productivity show large changes (on average 60%–70% differences in R/S and average ratios of highest to lowest R/S between 5.4 and 7.9 for the three species). Such changes suggest that salmon stock assessment methods should take into account possible nonstationarity. This step will help provide scientific advice to help managers to meet conservation and management objectives. The Kalman filter results also identified some stocks that did not share temporal trends with other stocks; these exceptions may require special monitoring and management efforts.

scholarly journals Handling Complex Missing Data Using Random Forest Approach for an Air Quality Monitoring Dataset: A Case Study of Kuwait Environmental Data (2012 to 2018)

2021 ◽  
Vol 18 (3) ◽  
pp. 1333
Author(s):  
Ahmad R. Alsaber ◽  
Jiazhu Pan ◽  
Adeeba Al-Hurban 
Keyword(s):  
Air Quality ◽  
Missing Data ◽  
Random Forest ◽  
Missing Values ◽  
Imputation Method ◽  
Environmental Data ◽  
Environmental Research ◽  
Quality Data ◽  
Data Set ◽  
Air Quality Data

In environmental research, missing data are often a challenge for statistical modeling. This paper addressed some advanced techniques to deal with missing values in a data set measuring air quality using a multiple imputation (MI) approach. MCAR, MAR, and NMAR missing data techniques are applied to the data set. Five missing data levels are considered: 5%, 10%, 20%, 30%, and 40%. The imputation method used in this paper is an iterative imputation method, missForest, which is related to the random forest approach. Air quality data sets were gathered from five monitoring stations in Kuwait, aggregated to a daily basis. Logarithm transformation was carried out for all pollutant data, in order to normalize their distributions and to minimize skewness. We found high levels of missing values for NO2 (18.4%), CO (18.5%), PM10 (57.4%), SO2 (19.0%), and O3 (18.2%) data. Climatological data (i.e., air temperature, relative humidity, wind direction, and wind speed) were used as control variables for better estimation. The results show that the MAR technique had the lowest RMSE and MAE. We conclude that MI using the missForest approach has a high level of accuracy in estimating missing values. MissForest had the lowest imputation error (RMSE and MAE) among the other imputation methods and, thus, can be considered to be appropriate for analyzing air quality data.

scholarly journals Potential value of the current mental health monitoring of children in state care in England

BJPsych Open ◽  
2018 ◽  
Vol 4 (6) ◽  
pp. 486-491 ◽  
Author(s):  
Christine Cocker ◽  
Helen Minnis ◽  
Helen Sweeting
Keyword(s):  
Mental Health ◽  
Missing Data ◽  
Mental Health Problems ◽  
Population Level ◽  
Cross Sectional ◽  
Data Set ◽  
Looked After Children ◽  
Education Data ◽  
Sample Attrition ◽  
Aggregate Population

BackgroundRoutine screening to identify mental health problems in English looked-after children has been conducted since 2009 using the Strengths and Difficulties Questionnaire (SDQ).AimsTo investigate the degree to which data collection achieves screening aims (identifying scale of problem, having an impact on mental health) and the potential analytic value of the data set.MethodDepartment for Education data (2009–2017) were used to examine: aggregate, population-level trends in SDQ scores in 4/5- to 16/17-year-olds; representativeness of the SDQ sample; attrition in this sample.ResultsMean SDQ scores (around 50% ‘abnormal’ or ‘borderline’) were stable over 9 years. Levels of missing data were high (25–30%), as was attrition (28% retained for 4 years). Cross-sectional SDQ samples were not representative and longitudinal samples were biased.ConclusionsMental health screening appears justified and the data set has research potential, but the English screening programme falls short because of missing data and inadequate referral routes for those with difficulties.Declaration of interestNone.

scholarly journals Maximum Likelihood Estimation of the VAR(1) Model Parameters with Missing Observations

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Helena Mouriño ◽  
Maria Isabel Barão
Keyword(s):  
Stochastic Process ◽  
Missing Data ◽  
Maximum Likelihood ◽  
Moving Average ◽  
Practical Importance ◽  
Likelihood Estimation ◽  
Model Parameters ◽  
Missing Observations ◽  
Data Set ◽  
The Impact

Missing-data problems are extremely common in practice. To achieve reliable inferential results, we need to take into account this feature of the data. Suppose that the univariate data set under analysis has missing observations. This paper examines the impact of selecting an auxiliary complete data set—whose underlying stochastic process is to some extent interdependent with the former—to improve the efficiency of the estimators for the relevant parameters of the model. The Vector AutoRegressive (VAR) Model has revealed to be an extremely useful tool in capturing the dynamics of bivariate time series. We propose maximum likelihood estimators for the parameters of the VAR(1) Model based on monotone missing data pattern. Estimators’ precision is also derived. Afterwards, we compare the bivariate modelling scheme with its univariate counterpart. More precisely, the univariate data set with missing observations will be modelled by an AutoRegressive Moving Average (ARMA(2,1)) Model. We will also analyse the behaviour of the AutoRegressive Model of order one, AR(1), due to its practical importance. We focus on the mean value of the main stochastic process. By simulation studies, we conclude that the estimator based on the VAR(1) Model is preferable to those derived from the univariate context.

MUSCLE PROTEINS OF PACIFIC SALMON (ONCORHYNCHUS): II. AN INVESTIGATION OF MUSCLE PROTEIN AND OTHER SUBSTANCES SOLUBLE IN SALT SOLUTIONS OF LOW IONIC STRENGTH BY COLUMN CHROMATOGRAPHY

1962 ◽  
Vol 40 (7) ◽  
pp. 919-927 ◽  
Author(s):  
H. Tsuyuki ◽  
E. Roberts ◽  
R. E. A. Gadd
Keyword(s):  
Sockeye Salmon ◽  
Moving Boundary ◽  
Coho Salmon ◽  
Pacific Salmon ◽  
Muscle Protein ◽  
Deae Cellulose ◽  
Ophiodon Elongatus ◽  
The Pacific ◽  
Other Substances ◽  
Low Ionic Strength

The muscle myogens and other components of the spring salmon (O. tshawytscha), chum salmon (O. keta), coho salmon (O. kisutch), and sockeye salmon (O. nerka), as well as the lingcod (Ophiodon elongatus), were separated by the use of diethylaminoethyl (DEAE) cellulose columns. Significant amounts of slowly dialyzable inosine and inosinic acid which may lead to spurious peaks in moving-boundary electrophoretic separations have been shown to be present in the muscle myogen preparations. The basic differences in the muscle myogen components of the Pacific salmon and the lingcod are compared.

scholarly journals Evidence for Freshwater Residualism in Coho Salmon, Oncorhynchus kisutch, From a Watershed on the North Coast of British Columbia

2017 ◽  
Vol 130 (4) ◽  
pp. 336 ◽  
Author(s):  
Eric A Parkinson ◽  
Chris J Perrin ◽  
Daniel Ramos-Espinoza ◽  
Eric B Taylor
Keyword(s):  
British Columbia ◽  
Fresh Water ◽  
Coho Salmon ◽  
Pacific Salmon ◽  
Oncorhynchus Kisutch ◽  
Water Levels ◽  
North Coast ◽  
The North ◽  
Seaward Migration ◽  
Mature Fish

The Coho Salmon, Oncorhynchus kisutch, is one of seven species of Pacific salmon and trout native to northeastern Pacific Ocean watersheds. The species is typically anadromous; adults reproduce in fresh water where juveniles reside for 1–2 years before seaward migration after which the majority of growth occurs in the ocean before maturation at 2–4 years old when adults return to fresh water to spawn. Here, we report maturation of Coho Salmon in two freshwater lakes on the north coast of British Columbia apparently without their being to sea. A total of 15 mature fish (11 males and four females) were collected in two lakes across two years. The mature fish were all at least 29 cm in total length and ranged in age from three to five years old. The occurrence of Coho Salmon that have matured in fresh water without first going to sea is exceedingly rare in their natural range, especially for females. Such mature Coho Salmon may represent residual and distinct breeding populations from those in adjacent streams. Alternatively, they may result from the ephemeral restriction in the opportunity to migrate seaward owing to low water levels in the spring when Coho Salmon typically migrate to sea after 1–2 years in fresh water. Regardless of their origin, the ability to mature in fresh water without seaward migration may represent important adaptive life history plasticity in response to variable environments.

scholarly journals Impact of defined clinical population and missing data on temporal trends in HIV viral load estimation within a health care system

HIV Medicine ◽  
2015 ◽  
Vol 16 (6) ◽  
pp. 346-354 ◽  
Author(s):  
EJ Edelman ◽  
JP Tate ◽  
DA Fiellin ◽  
ST Brown ◽  
K Bryant ◽  
...  
Keyword(s):  
Health Care ◽  
Viral Load ◽  
Missing Data ◽  
Health Care System ◽  
Temporal Trends ◽  
Clinical Population ◽  
Load Estimation ◽  
Hiv Viral Load ◽  
Care System

scholarly journals Resources and fishery of Pacific salmon in Magadan region in the beginning of the 21st century

Trudy VNIRO ◽  
2020 ◽  
Vol 179 ◽  
pp. 90-102
Author(s):  
M. N. Gorokhov ◽  
V. V. Volobuev ◽  
I. S. Golovanov
Keyword(s):  
Chum Salmon ◽  
Coho Salmon ◽  
Pacific Salmon ◽  
Pink Salmon ◽  
Spawning Grounds ◽  
Magadan Region ◽  
Spawning Areas ◽  
Optimal Values ◽  
In The Beginning ◽  
Salmon Fishery

There are two main areas of pacific salmon fishing in the Magadan region: Shelikhova Gulf and Tauiskaya Bay. The main fishing species is pink salmon in the region. Its share of total salmon catch by odd-year returns reaches 85 %. Data on the dynamics of escapement to the spawning grounds of pink salmon of the Shelikhova Gulf and Tauiskaya Bay are presented. The displacement of the level of spawning returns of pink salmon into the Shelihova Gulf with the simultaneous reduction of its returns to the Tauiskaya Bay is shown. Data on the dynamics of the fishing indicators of pink salmon for the two main fishing areas are provided. The Tauiskaya Bay as the main pink salmon fishery area loses its importance is shown. Graphical data on the escapement of producers pink salmon to the spawning grounds are presented and the optimal values of spawning escapements are estimated. Chum salmon is the second largest and most fishing species. Information on the dynamics of the number of returns, catch and escapement to the spawning grounds of chum salmon is given. The indicators of escapement to the spawning areas and their compliance with the optimal passes of salmon producers are analyzed. The issues of the dynamics of returns number, catch and the escapement to the spawning grounds of coho salmon producers are considered. The level of the escapement to the spawning areas is shown and the ratio of actual to optimal values of passes is estimated. The role of coho salmon as an object of industrial fishing and amateur fishing is shown. The extent of fishing press on individual groups of salmon populations is discussed. It is concluded that it is necessary to remove the main salmon fishery from the Tauiskaya Bay to the Shelikhova Gulf.

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