A general framework for integrating environmental time series into stock assessment models: model description, simulation testing, and example

We present a method to integrate environmental time series into stock assessment models and to test the significance of correlations between population processes and the environmental time series. Parameters that relate the environmental time series to population processes are included in the stock assessment model, and likelihood ratio tests are used to determine if the parameters improve the fit to the data significantly. Two approaches are considered to integrate the environmental relationship. In the environmental model, the population dynamics process (e.g. recruitment) is proportional to the environmental variable, whereas in the environmental model with process error it is proportional to the environmental variable, but the model allows an additional temporal variation (process error) constrained by a log-normal distribution. The methods are tested by using simulation analysis and compared to the traditional method of correlating model estimates with environmental variables outside the estimation procedure. In the traditional method, the estimates of recruitment were provided by a model that allowed the recruitment only to have a temporal variation constrained by a log-normal distribution. We illustrate the methods by applying them to test the statistical significance of the correlation between sea-surface temperature (SST) and recruitment to the snapper (Pagrus auratus) stock in the Hauraki Gulf–Bay of Plenty, New Zealand. Simulation analyses indicated that the integrated approach with additional process error is superior to the traditional method of correlating model estimates with environmental variables outside the estimation procedure. The results suggest that, for the snapper stock, recruitment is positively correlated with SST at the time of spawning.

Daily rainfall along the United States Pacific Coast appears to conform to a square-root normal probability distribution

EXTRACT (SEE PDF FOR FULL ABSTRACT): As part of a study of climatic influences on landslide initiation, a statistical analysis of long-term (>40 years) records of daily rainfall from 24 Pacific coastal stations, from San Diego to Cape Flattery, disclosed an unexpected result - the square root of the daily rainfall closely approximates a normal distribution function. ... This paper illustrates the use of the square-root-normal distribution to analyze variations in precipitation along the mainland United States Pacific Coast with examples of orographic enhancement, rain shadows, and increase in precipitation frequency with geographic latitude.

A stochastic model of temporal variations in monthly temperature, precipitation, snowfall, and resulting snowpack

We report a Monte Carlo representation of the long-term inter-annual variability of monthly snowfall on a detailed (1 km) grid of points throughout the southwest. An extension of the local climate model of the southwestern United States (Stamm and Craig 1992) provides spatially based estimates of mean and variance of monthly temperature and precipitation. The mean is the expected value from a canonical regression using independent variables that represent controls on climate in this area, including orography. Variance is computed as the standard error of the prediction and provides site-specific measures of (1) natural sources of variation and (2) errors due to limitations of the data and poor distribution of climate stations. Simulation of monthly temperature and precipitation over a sequence of years is achieved by drawing from a bivariate normal distribution. The conditional expectation of precipitation. given temperature in each month, is the basis of a numerical integration of the normal probability distribution of log precipitation below a threshold temperature (3°C) to determine snowfall as a percent of total precipitation. Snowfall predictions are tested at stations for which long-term records are available. At Donner Memorial State Park (elevation 1811 meters) a 34-year simulation - matching the length of instrumental record - is within 15 percent of observed for mean annual snowfall. We also compute resulting snowpack using a variation of the model of Martinec et al. (1983). This allows additional tests by examining spatial patterns of predicted snowfall and snowpack and their hydrologic implications.

Entgiftungsstoffwechsel der Nordsee-Kliesche (Limanda limanda)

In the framework of monitoring programmes organized under several sea protection conventions (HELSINKI Conv., OSPAR Conv.) the contracting parties are requested to develop appropriate techniques for Biological-Effect- Monitoring. In following these recommendations the Institut for Fisheries Ecology studies the 7-ethoxyresorufin- O-deethylase (EROD) activity in the liver of dab. EROD represents one enzyme of the cytochrome P-450 species, also called mixed function oxygenases (MFO), which is induced by certain organic contaminants, e.g. PCBs. On the other hand, an influence of natural factors like season, temperature or spawning on the EROD activity may be possible. The present study represents an insight into the status of the EROD activity in North Sea dab. Ultimately, we intend to decide if EROD activity is an appropriate tool to detect effects of contaminants. The EROD activity in the liver of 687 dabs, caught in the North Sea at different seasons in 1995 and 1996 with the fishery research vessel “Walther Herwig III”, has been determined and the data obtained have been statistically evaluated. The logarithmically transformed values of the EROD activity are following approximately a normal distribution. Due to the wide variation of the enzyme activities and due to the small number of samples minor differences between samples are not detectable. Nevertheless, comparing the enzyme activities at different sites of the North Sea, some significant differences have been identified. A model for the discription of seasonal variations of EROD activity, developed at the Biologische Anstalt Helgoland, could be helpful for interpretation.

An evaluation of the survival of Atlantic salmon (Salmo salar L.)fry stocked in eight streams in the North West of England.

Eight streams from the North West of England were stocked with Atlantic salmon (Salmo salar L.) fed fry at densities ranging from 1 to 4/m2 over a period of up to three years to evaluate survival to the end of the first an d second growing periods and hence assess the value of stocking as a management practice. Survival to the end of the first growin g period (mean duration of 108 days) was found to vary between 7.8 and 41.3% with a mean of 22% and CV of 0.44. Survival from the end of the first growing period to the end of the second growing period (mean duration of 384 days) ranged from 19.9 to 34.1% with a mean of 26.3% and CV of 0.21. Survival was found to be positively related to 0+ trout density (P < 0.05) and negatively related to altitude (P < 0.05). A comparison of the raw survival data (non standardised with respect to duration of experiments) with that from other studies in relation to stocking densities revealed a negative relationship between fry survival and stocking density (P < 0.05). Densities in excess of 5/m2 tended to result in lower levels of survival. Post stocking fry dispersal patterns were examined for the 1991 data. On average 86.7% of the number of fry surviving remained within the stocked zone by the end of the first growing period. With the exception of one stream there was little in the way of dispersal beyond the stocked zone. The dispersal pattern approximated to the normal distribution (P < 0.05). It was estimated that stocking can result in a net gain of fish to a river system compared with natural productivity, however the numerical significance of this gain and its cost effectiveness need to be determined on a river specific basis.

Evaluating methods for estimating rare events with zero-heavy data: a simulation model estimating sea turtle bycatch in the pelagic longline fishery

Estimating rare events from zero-heavy data (data with many zero values) is a common challenge in fisheries science and ecology. For example, loggerhead sea turtles (Caretta caretta) and leatherback sea turtles (Dermochelys coriacea) account for less than 1% of total catch in the U.S. Atlantic pelagic longline fishery. Nevertheless, the Southeast Fisheries Science Center (SEFSC) of the National Marine Fisheries Service (NMFS) is charged with assessing the effect of this fishery on these federally protected species. Annual estimates of loggerhead and leatherback bycatch in a fishery can affect fishery management and species conservation decisions. However, current estimates have wide confidence intervals, and their accuracy is unknown. We evaluate 3 estimation methods, each at 2 spatiotemporal scales, in simulations of 5 spatial scenarios representing incidental capture of sea turtles by the U.S. Atlantic pelagic longline fishery. The delta-log normal method of estimating bycatch for calendar quarter and fishing area strata was the least biased estimation method in the spatial scenarios believed to be most realistic. This result supports the current estimation procedure used by the SEFSC.

Length-weight relationship of mudskippers (Gobiidae: Oxudercinae) in the coastal areas of Selangor, Malaysia

Parameters a and b of the length-weight relationship (LWR) were estimated for eleven species of mudskippers caught in the coastal areas of Selangor, Malaysia. The values of b ranged from 2.56 to 3.50 with the mean b equal to 2.95 (n=11; sd=0.302). A normal distribution of the calculated LWR exponent (b) was obtained.

Length-weight relationship of marine fish species off Sao Sebastiao system, Sao Paulo, Southeastern Brazil

The parameters a and b of the length-weight relationship of the form W = a . L super(b) were estimated for 57 fish species sampled in Sao Sebastiao Channel and shelf system in 1997, Sao Paulo, Brazil. The b values ranged from 2.746 to 3.617. The Student's t-test revealed that mot (44) species had b values significantly different from 3. A normal distribution of the calculated LWR exponents (b) was obtained.

Small-boat surveys for coastal dolphins: line-transect surveys of Hector’s dolphins (Cephalorhynchus hectori)

Management of coastal species of small cetaceans is often impeded by a lack of robust estimates of their abundance. In the Austral summers of 1997−98, 1998−99, and 1999−2000 we conducted line-transect surveys of Hector’s dolphin (Cephalorhynchus hectori) abundance off the north, east, and south coasts of the South Island of New Zealand. Survey methods were modified for the use of a 15-m sailing catamaran, which was equipped with a collapsible sighting platform giving observers an eye-height of 6 m. Eighty-six percent of 2061 km of survey effort was allocated to inshore waters (4 nautical miles [nmi] or 7.4 km from shore), and the remainder to offshore waters (4−10 nmi or 7.4–18.5 km from shore). Transects were placed at 45° to the shore and spaced apart by 1, 2, 4, or 8 nmi according to pre-existing data on dolphin density. Survey effort within strata was uniform. Detection functions for sheltered waters and open coasts were fitted separately for each survey. The effect of attraction of dolphins to the survey vessel and the fraction of dolphins missed on the trackline were assessed with simultaneous boat and helicopter surveys in January 1999. Hector’s dolphin abundance in the coastal zone to 4 nmi offshore was calculated at 1880 individuals (CV=15.7%, log-normal 95% CI=1384−2554). These surveys are the first line-transect surveys for cetaceans in New Zealand’s coastal waters.

The statistical properties of recreational catch rate data for some fish stocks off the northeast U.S. coast

Recreational fisheries in the waters off the northeast U.S. target a variety of pelagic and demersal fish species, and catch and effort data sampled from recreational fisheries are a critical component of the information used in resource evaluation and management. Standardized indices of stock abundance developed from recreational fishery catch rates are routinely used in stock assessments. The statistical properties of both simulated and empirical recreational fishery catch-rate data such as those collected by the National Marine Fisheries Service (NMFS) Marine Recreational Fishery Statistics Survey (MRFSS) are examined, and the potential effects of different assumptions about the error structure of the catch-rate frequency distributions in computing indices of stock abundance are evaluated. Recreational fishery catch distributions sampled by the MRFSS are highly contagious and overdispersed in relation to the normal distribution and are generally best characterized by the Poisson or negative binomial distributions. The modeling of both the simulated and empirical MRFSS catch rates indicates that one may draw erroneous conclusions about stock trends by assuming the wrong error distribution in procedures used to developed standardized indices of stock abundance. The results demonstrate the importance of considering not only the overall model fit and significance of classification effects, but also the possible effects of model misspecification, when determining the most appropriate model construction.

Seasonal growth of King George whiting (Sillaginodes punctata) estimated from length-at-age samples of the legal-size harvest

Samples of 11,000 King George whiting (Sillaginodes punctata) from the South Australian commercial and recreational catch, supplemented by research samples, were aged from otoliths. Samples were analyzed from three coastal regions and by sex. Most sampling was undertaken at fish processing plants, from which only fish longer than the legal minimum length were obtained. A left-truncated normal distribution of lengths at monthly age was therefore employed as model likelihood. Mean length-at-monthly-age was described by a generalized von Bertalanffy formula with sinusoidal seasonality. Likelihood standard deviation was modeled to vary allometrically with mean length. A range of related formulas (with 6 to 8 parameters) for seasonal mean length at age were compared. In addition to likelihood ratio tests of relative fit, model selection criteria were a minimum occurrence of high uncertainties (>20% SE), of high correlations (>0.9, >0.95, and >0.99) and of parameter estimates at their biological limits, and we sought a model with a minimum number of parameters. A generalized von Bertalanffy formula with t0 fixed at 0 was chosen. The truncated likelihood alleviated the overestimation bias of mean length at age that would otherwise accrue from catch samples being restricted to legal sizes.

The distribution of Corixidae in relation to the water quality of British lakes: A monitoring model

This article is an attempt to devise a method of using certain species of Corixidae as a basis for the assessment of general water quality in lakes. An empirical graphical representation of the distribution of populations or communities of Corixidae in relation to conductivity, based mainly on English and Welsh lakes, is used as a predictive monitoring model to establish the "expected" normal community at a given conductivity, representing the total ionic concentration of the water body. A test sample from another lake of known conductivity is then compared with "expected" community. The "goodness of fit" is examined visually or by calculation of indices of similarity based on the relative proportions of the constituent species of each community. A computer programme has been devised for this purpose.