Spatial coherence and persistence in annual streamflow in the western United States [abstract]

EXTRACT (SEE PDF FOR FULL ABSTRACT): Four broad regions of the western United States within which annual streamflows exhibit strong spatial coherence are identified using principal component analysis with a varimax rotation. Geographically, the four regions encompass the Pacific Northwest, Far West-Great Basin, Central Rockies-High Plains, and Northern Great Plains. These regions are really consistent with previously documented, descriptively derived streamflow regimes as well as with general atmospheric circulation and precipitation modes of variation. Collectively, the four regional components account for nearly 63 percent of the total annual variation in western U.S. streamflow. The time history of most principal component patterns exhibit little or no persistence.

A tree-ring perspective on the extreme wetness of the early 1900’s in the western United States [abstract]

Ring-width indices from 136 sites in the area from northern Montana to southern New Mexico between latitudes 103°W and 111°W were examined to infer periods of anomalous wetness for the years 1700-1964. Sites were grouped into north, central and south regions, and the gross regional tree-ring fluctuations were compared. The results indicate that the period 1905-1917 was unique in the 265-year record for the combined magnitude, duration, and north/south coherence of the growth anomaly of much lesser magnitude occurred in the 1830's-1840's [sic]. Both this and the 1905-1917 anomaly appear from time-series plots to be manifestations of low-frequency growth variations at wave lengths between about 20 and 60 years.

Annual stream flow variability over the western United States [abstract]

EXTRACT (SEE PDF FOR FULL ABSTRACT): The variability of mean annual streamflow over the western United States is described and related to indices of large scale atmospheric circulation over the Pacific Ocean and western U.S. Principal component analysis reveal [sic] four statistically significant modes of streamflow variability across the region.

Temporal trends (2000–2011) and influences on fishery-independent catch rates for loggerhead sea turtles (Caretta caretta) at an important coastal foraging region in the southeastern United States

Seasonal trawling was conducted randomly in coastal (depths of 4.6–17 m) waters from St. Augustine, Florida, (29.9°N) to Winyah Bay, South Carolina (33.1°N), during 2000–03, 2008–09, and 2011 to assess annual trends in the relative abundance of sea turtles. A total of 1262 loggerhead sea turtles (Caretta caretta) were captured in 23% (951) of 4207 sampling events. Capture rates (overall and among prevalent 5-cm size classes) were analyzed through the use of a generalized linear model with log link function for the 4097 events that had complete observations for all 25 model parameters. Final models explained 6.6% (70.1–75.0 cm minimum straight-line carapace length [SCLmin]) to 14.9% (75.1–80.0 cm SCLmin) of deviance in the data set. Sampling year, geographic subregion, and distance from shore were retained as significant terms in all final models, and these terms collectively accounted for 6.2% of overall model deviance (range: 4.5–11.7% of variance among 5-cm size classes). We retained 18 parameters only in a subset of final models: 4 as exclusively significant terms, 5 as a mixture of significant or nonsignificant terms, and 9 as exclusively nonsignificant terms. Four parameters also were dropped completely from all final models. The generalized linear model proved appropriate for monitoring trends for this data set that was laden with zero values for catches and was compiled for a globally protected species. Because we could not account for much model deviance, metrics other than those examined in our study may better explain catch variability and, once elucidated, their inclusion in the generalized linear model should improve model fits.

Population genetics of Cobia (Rachycentron canadum): implications for fishery management along the coast of the southeastern United States

Cobia (Rachycentron canadum) is a pelagic, migratory species with a transoceanic distribution in tropical and subtropical waters. Recreational fishing pressure on Cobia in the United States has increased substantially during the last decade, especially in areas of its annual inshore aggregations, making this species potentially susceptible to overfishing. Although Cobia along the Atlantic and Gulf coasts of the southeastern United States are currently managed as a single fishery, the genetic composition of Cobias in these areas is unclear. On the basis of a robust microsatellite data set from collections along the U.S. Atlantic coast (2008–09), offshore groups were genetically homogenous. However, the 2 sampled inshore aggregations (South Carolina and Virginia) were genetically distinct from each other, as well as from the offshore group. The recapture of stocked fish within their release estuary 2 years after release indicates that some degree of estuarine fidelity occurs within these inshore aggregations and supports the detection of their unique genetic structure at the population level. These results complement the observed high site fidelity of Cobias in South Carolina and support a recent study that confirms that Cobia spawn in the inshore aggregations. Our increased understanding of Cobia life history will be beneficial for determining the appropriate scale of fishery management for Cobia.

A preliminary description of climatology in the western United States

We describe the climatology of the western United States as seen from two 1-month perspectives, January and July 1988, of the National Meteorological Center large-scale global analysis, the Colorado State University Regional Atmospheric Modeling System (RAMS), and various station observation sets. An advantage of the NMC analysis and the RAMS is that they provide a continuous field interpolation of the meteorological variables. It is more difficult to describe spatial meteorological fields from the available sparse station networks. We assess accuracy of the NMC analysis and RAMS by finding differences between the analysis, the model, and station values at the stations. From these comparisons, we find that RAMS has much more well-developed mesoscale circulation, especially in the surface wind field. However, RAMS climatological and transient fields do not appear to be substantially closer than the larger-scale analysis to the station observations. The RAMS model does provide other meteorological variables, such as precipitation, which are not readily available from the archives of the global analysis. Thus, RAMS could, at the least, be a tool to augment the NMC large-scale analyses.