Effects of salinity, temperature and cadmium stress on cadmium -binding protein in the grass shrimp, {\it Palaemonetes pugio}

The combined effects of salinity, temperature and cadmium stress on survival and adaptation through cadmium-binding protein (CdBP) accumulation were studied in the grass shrimp, Palaemonetes pugio. In 96-hour bioassays, shrimp were exposed to zero or one of three levels of cadmium, under one of six different salinity (15, 25, or 35$\perthous$) and temperature (20 or 30$\sp\circ$C) regimes. CdBP concentrations were quantified in survivors from the 24 exposure groups. Salinity and temperature did not affect survivorship unless the shrimp were also exposed to cadmium. Grass shrimp were most sensitive to cadmium at low salinity-high temperature, and least sensitive at high salinity-low temperature. The incidence of cadmium-associated black lesions in gill tissue was influenced by salinity and temperature stress. P. pugio produced a 10,000 dalton metallothionein-like CdBP when exposed to at least 0.1 mg Cd$\sp{2+}$/L for 96 hours. Accumulation of CdBP was increased with increases in the exposure cadmium level, increases in temperature and decreases in salinity, independently and in conjunction with one another. Maximum CdBP concentrations occurred in grass shrimp that survived the salinity-temperature-cadmium conditions creating maximum stress as measured by highest mortality, not necessarily in shrimp exposed to the highest cadmium levels. The potential utility of this method as a monitor of physiological stress in estuarine biota inhabiting metal-polluted environments is discussed. ^

Age and chemical composition of apatites from five DSDP and ODP Sites in the Pacific, Atlantic and Indian Oceans

Since studies on deep-sea cores were carried out in the early 1990s it has been known that ambient temperature may have a marked affect on apatite fission track annealing. Due to sluggish annealing kinetics, this effect cannot be quantified by laboratory annealing experiments. The unknown amount of low-temperature annealing remains one of the main uncertainties for extracting thermal histories from fission track data, particularly for samples which experienced slow cooling in shallow crustal levels. To further elucidate these uncertainties, we studied volcanogenic sediments from five deep-sea drill cores, that were exposed to maximum temperatures between ~10° and 70°C over geological time scales of ~15-120 Ma. Mean track lengths (MTL) and etch pit diameters (Dpar) of all samples were measured, and the chemical composition of each grain analyzed for age and track length measurements was determined by electron microprobe analysis. Thermal histories of the sampled sites were independently reconstructed, based on vitrinite reflectance measurements and/or 1D numerical modelling. These reconstructions were used to test the most widely used annealing models for their ability to predict low-temperature annealing. Our results show that long-term exposure to temperatures below the temperature range of the nominal apatite fission track partial annealing zone results in track shortening ranging between 4 and 11%. Both chlorine content and Dpar values explain the downhole annealing patterns equally well. Low chlorine apatite from one drill core revealed a systematic relation between Si-content and Dpar value. The question whether Si-substitution in apatite has direct and systematic effects on annealing properties however, cannot be addressed by our data. For samples, which remained at temperatures <30°C, and which are low in chlorine, the Laslett et al. [Laslett G., Green P., Duddy I. and Gleadow A. (1987) Thermal annealing of fission tracks in apatite. Chem. Geol. 65, 1-13] annealing model predicts MTL up to 0.6 µm longer than those actually measured, whereas for apatites with intermediate to high chlorine content, which experienced temperatures >30°C, the predictions of the Laslett et al. (1987) model agree with the measured MTL data within error levels. With few exceptions, predictions by the Ketcham et al. [Ketcham R., Donelick R. and Carlson W. (1999) Variability of apatite fission-track annealing kinetics. III: Extrapolation to geological time scales. Am. Mineral. 84/9, 1235-1255] annealing model are consistent with the measured data for samples which remained at temperatures below ~30°C. For samples which experienced maximum temperatures between ~30 and 70°C, and which are rich in chlorine, the Ketcham et al. (1999) model overestimates track annealing.

Fission track analyses of ODP Hole 129-800A samples

Four models of fission track annealing in apatite are compared with measured fission track lengths in samples from Site 800 in the East Mariana Basin, Ocean Drilling Program Leg 129, given an independently determined temperature history. The temperature history of Site 800 was calculated using a one-dimensional, compactive, conductive heat flow model assuming two end-member thermal cases: one for cooling of Jurassic ocean crust that has experienced no subsequent heating, and one for cooling of Cretaceous ocean crust. Because the samples analyzed were only shallowly buried and because the tectonic history of the area since sample deposition is simple, resolution of the temperature history is high. The maximum temperature experienced by the sampled bed is between 16°-21°C and occurs at 96 Ma; temperatures since the Cretaceous have dropped in spite of continued pelagic sediment deposition because heat flow has continued to decay exponentially and bottom-water temperatures have dropped. Fission tracks observed within apatite grains from the sampled bed are 14.6 +/- 0.1 µm (1 sigma) long. Given the proposed temperature history of the samples, one unpublished and three published models of fission track annealing predict mean track lengths from 14.8 to 15.9 µm. These models require temperatures as much as 40°C higher than the calculated paleotemperature maximum of the sampled bed to produce the same degree of track annealing. Measured and predicted values are different because annealing models are based on extrapolation of high temperature laboratory data to geologic times. The model that makes the closest prediction is based on the greatest number of experiments performed at low temperature and on an apatite having composition closest to that of the core samples.