Population structure and variance effective size of red snapper (Lutjanus campechanus) in the northern Gulf of Mexico*

We assayed allelic variation at 19 nuclear-encoded microsatellites among 1622 Gulf red snapper (Lutjanus campechanus) sampled from the 1995 and 1997 cohorts at each of three offshore localities in the northern Gulf of Mexico (Gulf). Localities represented western, central, and eastern subregions within the northern Gulf. Number of alleles per microsatellite per sample ranged from four to 23, and gene diversity ranged from 0.170 to 0.917. Tests of conformity to Hardy-Weinberg equilibrium expectations and of genotypic equilibrium between pairs of micro-satellites were generally nonsignificant following Bonferroni correction. Significant genic or genotypic heterogeneity (or both) among samples was detected at four microsatellites and over all microsatellites. Levels of divergence among samples were low (FST ≤0.001). Pairwise exact tests revealed that six of seven “significant” comparisons involved temporal rather than spatial heterogeneity. Contemporaneous or variance effective size (NeV) was estimated from the temporal variance in allele frequencies by using a maximum-likelihood method. Estimates of NeV ranged between 1098 and >75,000 and differed significantly among localities; the NeV estimate for the sample from the northcentral Gulf was >60 times as large as the estimates for the other two localities. The differences in variance effective size could ref lect differences in number of individuals successfully reproducing, differences in patterns and intensity of immigration, or both, and are consistent with the hypothesis, supported by life-history data, that different “demographic stocks” of red snapper are found in the northern Gulf. Estimates of NeV for red snapper in the northern Gulf were at least three orders of magnitude lower than current estimates of census size (N). The ratio of effective to census size (Ne/N) is far below that expected in an ideal population and may reflect high variance in individual reproductive success, high temporal and spatial variance in productivity among subregions or a combination of the two.

Untrawlable Bottom in Shrimp Statistical Zones of the Northwest Gulf of Mexico

The Gulf of Mexico Fisheries Management Council tasked the National Marine Fisheries Service with determining the extent, if any, of loss oft rawlable bottom in the Gulf of Mexico based upon fishing industry concerns. There are approximately 31 million hectares in the 21 shrimp statistical zones in the Gulf, approximately 23 million hectares of waters that are <35 fathoms (where most shrimp trawling effort occurs), and approximately 11 million hectares in zones 10-21, <35f athoms, which were examined. There are 31,338 known hangs, snags, artificial reefs, hazards to navigation, oil rigs, and similar obstructions which cause trawling to be unfeasible in these zones. There are several refuge (i.e. untrawlable) areas associated with the Alabama Artificial Reefs. Conservatively assuming 1 hectare for each known obstruction, coupled with the known area of each refuge, the estimate of total untrawlable bottom in zones 10-21 less than 35 fathoms in the Gulf is 185,953 hectares, or roughly 1.7% of this total trawlable area. Sensitivity analysis demonstrated the robustness of this assumption, with a range of 0.3-4.3% possible. In specific shrimp zones, untrawlable area is much less than 1% except in zones 10 (26%) and 11(2.5%), both of which possess a refuge. Other than the implementation periods of these refugia, no temporal trends were detectable with respect to the amount of untrawlable bottom.

Hydrologic variability related to El Nino in the Pacific Northwest [abstract]

A preliminary statistical analysis was undertaken to evaluate whether the effect of El Nino events is apparent in variables related to hydrologic behavior. Annual precipitation, temperature and streamflow were used for three locations in Oregon representing coastal, Willamette Valley/Cascade and eastern Oregon regions. The mean and variance for periods of El Nino occurrence vs. those with no El Nino were computed. Numerical differences were observed but were not consistent across all stations. The coastal area showed a decrease in mean precipitation and increase in mean streamflow during El Nino events. Other stations showed a positive increase in mean for both precipitation and streamflow for El Nino events. Variance of precipitation was greater in the coastal area but smaller in other areas and vice versa for streamflow during El Nino events. Statistical analyses indicated no significant differences of means, variances or distributions using nonparametric tests for El Nino vs. non-El Nino series.

An objective classification of climatic regions in the Pacific and Indian oceans

We have applied a number of objective statistical techniques to define homogeneous climatic regions for the Pacific Ocean, using COADS (Woodruff et al 1987) monthly sea surface temperature (SST) for 1950-1989 as the key variable. The basic data comprised all global 4°x4° latitude/longitude boxes with enough data available to yield reliable long-term means of monthly mean SST. An R-mode principal components analysis of these data, following a technique first used by Stidd (1967), yields information about harmonics of the annual cycles of SST. We used the spatial coefficients (one for each 4-degree box and eigenvector) as input to a K-means cluster analysis to classify the gridbox SST data into 34 global regions, in which 20 comprise the Pacific and Indian oceans. Seasonal time series were then produced for each of these regions. For comparison purposes, the variance spectrum of each regional anomaly time series was calculated. Most of the significant spectral peaks occur near the biennial (2.1-2.2 years) and ENSO (~3-6 years) time scales in the tropical regions. Decadal scale fluctuations are important in the mid-latitude ocean regions.

Statistical analyses to support guidelines for marine avian sampling: Final report. [Digital Supplements A-G attached]

Interest in development of offshore renewable energy facilities has led to a need for high-quality, statistically robust information on marine wildlife distributions. A practical approach is described to estimate the amount of sampling effort required to have sufficient statistical power to identify species specific “hotspots” and “coldspots” of marine bird abundance and occurrence in an offshore environment divided into discrete spatial units (e.g., lease blocks), where “hotspots” and “coldspots” are defined relative to a reference (e.g., regional) mean abundance and/or occurrence probability for each species of interest. For example, a location with average abundance or occurrence that is three times larger the mean (3x effect size) could be defined as a “hotspot,” and a location that is three times smaller than the mean (1/3x effect size) as a “coldspot.” The choice of the effect size used to define hot and coldspots will generally depend on a combination of ecological and regulatory considerations. A method is also developed for testing the statistical significance of possible hotspots and coldspots. Both methods are illustrated with historical seabird survey data from the USGS Avian Compendium Database.

Demersal groundfish densities in trawlable and untrawlable habitats off Washington: implications for the estimation of habitat bias in trawl surveys

Demersal groundfish densities were estimated by conducting a visual strip-transect survey via manned submersible on the continental shelf off Cape Flattery, Washington. The purpose of this study was to evaluate the statistical sampling power of the submersible survey as a tool to discriminate density differences between trawlable and untrawlable habitats. A geophysical map of the study area was prepared with side-scan sonar imagery, multibeam bathymetry data, and known locations of historical NMFS trawl survey events. Submersible transects were completed at randomly selected dive sites located in each habitat type. Significant differences in density between habitats were observed for lingcod (Ophiodon elongatus), yelloweye rockfish (Sebastes ruberrimus), and tiger rockfish (S. nigrocinctus) individually, and for “all rockfish” and “all flatfish” in the aggregate. Flatfish were more than ten times as abundant in the trawlable habitat samples than in the untrawlable samples, whereas rockfish as a group were over three times as abundant in the untrawlable habitat samples. Guidelines for sample sizes and implications for the estimation of the continental shelf trawl-survey habitat-bias are considered. We demonstrate an approach that can be used to establish sample size guidelines for future work by illustrating the interplay between statistical sampling power and 1) habitat specific-density differences, 2) variance of density differences, and 3) the proportion of untrawlable area in a habitat.

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.

A statistical model of climates in the southwestern United States

EXTRACT (SEE PDF FOR FULL ABSTRACT): We describe an empirical-statistical model of climates of the southwestern United States. Boundary conditions include sea surface temperatures, atmospheric transmissivity, and topography. Independent variables are derived from the boundary conditions along 1000-km paths of atmospheric circulation. ... Predictor equations are derived over a larger region than the application area to allow for the increased range of paleoclimate. This larger region is delimited by the autocorrelation properties of climatic data.

A multivariate statistical study with a factor analysis of recent planktonic foraminiferal distribution in the Coromandel Coast of India

A study of planktonic foraminiferal assemblages from 19 stations in the neritic and oceanic regions off the Coromandel Coast, Bay of Bengal has been made using a multivariate statistical method termed as factor analysis. On the basis of abundance, 17 foraminiferal species, species were clustered into 5 groups with row normalisation and varimax rotation for Q-mode factor analysis. The 19 stations were also grouped into 5 groups with only 2 groups statistically significant using column normalisation and varimax rotation for R-mode analysis. This assemblage grouping method is suitable because groups of species/stations can explain the maximum amount of variation in them in relation to prevailing environmental conditions in the area of study.