Prediction of discard mortality for Alaskan crabs after exposure to freezing temperatures, based on a reflex impairment index

Millions of crabs are sorted and discarded in freezing conditions each year in Alaskan fisheries for Tanner crab (Chionoecetes bairdi) and snow crab (C. opilio). However, cold exposures vary widely over the fishing season and among different vessels, and mortalities are difficult to estimate. A shipboard experiment was conducted to determine whether simple behavioral observations can be used to evaluate crab condition after low-temperature exposures. Crabs were systematically subjected to cold in seven different exposure treatments. They were then tested for righting behavior and six different ref lex actions and held to monitor mortality. Crabs lost limbs, showed ref lex impairment, and died in direct proportion to increases in cold exposure. Righting behavior was a poor predictor of mortality, whereas reflex impairment (scored as the sum of reflex actions that were lost) was an excellent predictor. This composite index could be measured quickly and easily in hand, and logistic regression revealed that the relationship between reflex impairment and mortality correctly predicted 80.0% of the mortality and survival for C. bairdi, and 79.4% for C. opilio. These relationships provide substantial improvements over earlier approaches to mortality estimation and were independent of crab size and exposure temperature.

Abundance of adult horseshoe crabs (Limulus polylphemus) in Delaware Bay estimated from a bay-wide mark-recapture study

Estimates of the abundance of American horseshoe crabs (Limulus polyphemus) are important to determine egg production and to manage populations for the energetic needs of shorebirds that feed on horseshoe crab eggs. In 2003, over 17,500 horseshoe crabs were tagged and released throughout Delaware Bay, and recaptured crabs came from spawning surveys that were conducted during peak spawning. We used two release cohorts to test for a temporary effect of tagging on spawning behavior and we adjusted the number of releases according to relocation rates from a telemetry study. The abundance estimate was 20 million horseshoe crabs (90 % confidence interval: 13−28 million), of which 6.25 million (90% CI: 4.0−8.8 million) were females. The combined harvest rate for Delaware, New Jersey, Virginia, and Maryland in 2003 was 4% (90% CI: 3−6%) of the abundance estimate. Over-wintering of adults in Delaware Bay could explain, in part, differences in estimates from ocean-trawl surveys. Based on fecundity of 88,000 eggs per female, egg production was 5.5×1011 (90% CI: 3.5×1011, 7.7×1011), but egg availability for shorebirds also depended on overlap between horseshoe crab and shorebird migrations, density-dependent bioturbation, and wave-mediated vertical transport.

Analysis of multivariate stochastic signals sampled by on-line particle analyzers: Application to the quantitative assessment of occupational exposure to NOAA in multisource industrial scenarios (MSIS)

In multisource industrial scenarios (MSIS) coexist NOAA generating activities with other productive sources of airborne particles, such as parallel processes of manufacturing or electrical and diesel machinery. A distinctive characteristic of MSIS is the spatially complex distribution of aerosol sources, as well as their potential differences in dynamics, due to the feasibility of multi-task configuration at a given time. Thus, the background signal is expected to challenge the aerosol analyzers at a probably wide range of concentrations and size distributions, depending of the multisource configuration at a given time. Monitoring and prediction by using statistical analysis of time series captured by on-line particle analyzers in industrial scenarios, have been proven to be feasible in predicting PNC evolution provided a given quality of net signals (difference between signal at source and background). However the analysis and modelling of non-consistent time series, influenced by low levels of SNR (Signal-Noise Ratio) could build a misleading basis for decision making. In this context, this work explores the use of stochastic models based on ARIMA methodology to monitor and predict exposure values (PNC). The study was carried out in a MSIS where an case study focused on the manufacture of perforated tablets of nano-TiO2 by cold pressing was performed