Changes in nucleic acids over the molt cycle in relation to food availability and temperature in Homarus americanus postlarvae

Postlarval lobsters Homarus americanus Milne Edwards hatched from three females collected in 1989 from Block Island Sound, Rhode Island were reared individually in the laboratory under nine treatment combinations of temperature (15, 18 and 21°C) and feeding (starved, low ration and full ration). Total RNA, DNA (mgind.^-1), RNA:DNA ratios and molt stage were determined for individuals sampled at daily intervals. Postlarval lobsters had high resistance to starvation. A majority of the lobsters survive 12 d of food deprivation, with some surviving up to 24–29 d. During starvation, cell biomass (estimated from protein:DNA) decreased to a minumum size, whereas cell number (based on total DNA) was generally conserved. The molt cycle was arrested at molt stage C in the starved postalrvae. Instar duration was inversely related to temperature. However, the duration of the postlarval instar did not differ between the low and full ration treatments. Uncoupling of cell growth and the molt cycle was evident in the full and low ration treatments. In the full ration treatments, the postmolt through early premolt was characterized by a rapid increase in total RNA and DNA. Maximum cell biomass was attained by molt stage C or D₀. In the low ration treatments, total RNA and DNA were less than those in the full ration treatments and the maximum cell biomass was attained only at molt stage D_2-3. Notably, different feeding regimes resulted in different patterns in RNA:DNA ratios over the molt cycle during the postlarval instar. RNA:DNA ratio was a sensitive indicator of recent (2 to 3 d) food deprivation. However, this ratio was positively related to the level of feeding only at molt stages C to D₁ and was inversely related to temperature regime. These results indicate that the use of RNA:DNA ratios to estimate the relative nutritional state of postlarval tobsters must be qualified with respect to the period of the molt cycle and the temperature regime.     

Specific detection of organotin compounds with a recombinant luminescent bacteria

Organotin compounds are widely used as biocides in marine and terrestrial environments. Several currently used techniques allow either the measurement of the chemicals or their effects on living organisms. Our current research focuses on the development of a complementary method based on a bacterial bioluminescence-based bioassay for the specific detection of organotin compounds. The performance of the bioassay was assessed. The Escherichia coli bacterial strain used in this study is specific for TBT and DBT (with Cl, Br or I as the halogen group) with the central tin atom important for light production. The assay is conducted after overnight culture of the bacterial strain, followed by 60 min of contact time with the organotin compound for significant light production. The detection limits were found to be 0.08 microM for TBT (26 microgl(-1)) and 0.0001 microM for DBT (0.03 microgl(-1)) with a linear range of one logarithm. The repeatability of the bioassay is 8% and the reproducibility for TBT and DBT was approximately 14%. Lyophilization of the strains did not significantly modify the detection limit as well as the range of detection. Applications of the bioassay to environmental samples are discussed.     

Synthesis of 4,4′-dichloro-3,5,3′,5′-tetramethylbiphenyl by the sandmeyer reaction

4,4′-Dichloro-3,5,3′,5′-tetramethylbiphenyl was prepared by -diazotization of 3,5,3′,5′-tetramethylbenzidine followed by the Sandmeyer reaction. The starting material is a noncarcinogenic analogue of benzidine, and the product may be of interest as a model compound for studying the metabolism of chlorinated biphenyls.     

Development of emission factors for polycarbonate processing

Emission factors for selected volatile organic compounds (VOCs) and particulate emissions were developed while processing eight commercial grades of polycarbonate (PC) and one grade of a PC/acrylonitrile-butadiene-styrene (ABS) blend. A small commercial-type extruder was used, and the extrusion temperature was held constant at 304 degrees C. An emission factor was calculated for each substance measured and is reported as pounds released to the atmosphere/million pounds of polymer resin processed [ppm (wt/wt)]. Scaled to production volumes, these emission factors can be used by processors to estimate emission quantities from similar PC processing operations.     

The role of learning in the acquisition of threat-sensitive responses to predator odours

The supposition that prey animals respond to a predator with an intensity that matches the risk posed by the predator is known as the threat-sensitive predator avoidance hypothesis. Many studies have provided support for this hypothesis; yet, few studies have attempted to determine how such abilities are acquired by prey species. In this study, we investigated whether fathead minnows (Pimephales promelas) could learn to recognize an unknown predator (northern pike, Esox lucius) in such a way that they could match the intensity of their antipredator response with the threat posed by the predator. We exposed pike-naïve minnows to conspecific alarm cues paired with either a high or low concentration of pike odor. The following day, both groups were tested for a response to either high or low concentration of pike odor alone. We found that minnows conditioned with alarm cues paired with a given concentration of pike odor subsequently responded with a higher intensity to higher concentrations of pike odor, and with a lower intensity to lower concentrations of pike odor. These results demonstrate that during a single conditioning trial, minnows learn the identity of the predator in a threat-sensitive manner. Minnows use predator odor concentrations that they experience in subsequent interactions to adjust the intensity of their antipredator behavior.     

Simulating forest structure, timber production, and socioeconomic effects in a multi-owner province.

Protecting biodiversity has become a major goal in managing coastal forests in the Pacific Northwest--an area in which human activities have had a significant influence on landscape change. A complex pattern of public and private forest ownership, combined with new regulations for each owner group, raises questions about how well and how efficiently these policies achieve their biodiversity goals. To develop a deeper understanding of the aggregate effect of forest policies, we simulated forest structures, timber production, and socioeconomic conditions over time for the mixture of private and public lands in the 2.3-million-ha Coast Range Physiographic Province of Oregon. To make these projections, we recognized both vegetative complexity at the stand level and spatial complexity at the landscape level. We focused on the two major factors influencing landscape change in the forests of the Coast Range: (1) land use, especially development for houses and cities, and (2) forest management, especially clearcutting. Our simulations of current policy suggest major changes in land use on the margins of the Coast Range, a divergence in forest structure among the different owners, an increase in old-growth forests, and a continuing loss of the structural elements associated with diverse young forests. Our simulations also suggest that current harvest levels can be approximately maintained, with the harvest coming almost entirely from private lands. A policy alternative that retained live trees for wildlife would increase remnant structures but at a cost to landowners (5-7% reduction in timber production). Another alternative that precluded thinning of plantations on federal land would significantly reduce the area of very large diameter (>75 cm dbh) conifer forests 100 years into the future     

Plant volatiles affect oviposition by codling moths

Summary. Oviposition in wild codling moth females, collected as overwintering larvae from apple, pear and walnut, was stimulated by volatiles from fruit-bearing green branches of these respective hostplants. Analysis of headspace collections showed that eight compounds present in apple, pear and walnut elicited a reliable antennal response in codling moth females: (E)--ocimene, 4,8-dimethyl-1,(E)3,7-nonatriene, (Z)3-hexenyl acetate, nonanal, -caryophyllene, germacrene D, (E,E)--farnesene, and methyl salicylate. Any one of these compounds is found in many other non-host plants, and host recognition in codling moth is thus likely encoded by a blend of volatiles. A large variation in the blend proportion of these compounds released from apple, pear and walnut suggests a considerable plasticity in the female response to host plant odours. Wild females, collected as overwintering larvae in the field, laid significantly fewer eggs in the absence of host plant volatiles. The offspring of these females, however, reared on a semi-artificial diet in the laboratory, laid as many eggs with or without plant volatile stimulus. Tests with individual females showed that this rapid change in oviposition behaviour may be explained by selection for females which oviposit in the absence of odour stimuli, rather than by preimaginal conditioning of insects when rearing them on semi-artificial diet. Oviposition bioassays using laboratory-reared females are therefore not suitable to identify the volatile compounds which stimulate egglaying in wild females.     

Identification of sex pheromone components of the pea midge, Contarinia pisi (Diptera: Cecidomyiidae)

 Three components in extract of pheromone glands of female pea midges, Contarinia pisi, were found to be active on male pea midge antennae by coupled gas chromatographic-electroantennographic detection. The EAD active components were identified as 2-acetoxytridecane, (2S,11S)-diacetoxytridecane, and (2S,12S)-diacetoxytridecane. A blend of these compounds proved to be highly attractive to males in windtunnel experiments. Received: 12 November 1998 / Accepted in revised form: 26 january 1999     

Neural Network Input Selection for Hydrological Forecasting Affected by Snowmelt1

Abstract: Snowmelt largely affects runoff in watersheds in Nordic countries. Neural networks (NN) are particularly attractive for streamflow forecasting whereas they rely at least on daily streamflow and precipitation observations. The selection of pertinent model inputs is a major concern in NNs implementation. This study investigates performance of auxiliary NN inputs that allow short‐term streamflow forecasting without resorting to a deterministic snowmelt routine. A case study is presented for the Rivière des Anglais watershed (700 km²) located in Southern Québec, Canada. Streamflow (Q), precipitations (rain R and snow S, or total P), temperature (T) and snow lying (A) observations, combined with climatic and snowmelt proxy data, including snowmelt flow (Q_SM) obtained from a deterministic model, were tested. NN implemented with antecedent Q and R produced the largest gains in performance. Introducing increments of A and T to the NNs further improved the performance. Long‐term averages, seasonal data, and Q_SM failed to improve the networks.