Using DTAGs to understand sound use, behavior, and vessel and associated noise effects in Southern Resident killer whales

Prey availability and disturbance from vessels and noise are identified threats to the recovery of endangered Southern Resident killer whales. Vessels and noise can mask echolocation signals used to capture fish prey and/or disrupt foraging behavior with implications for energy acquisition. In the U.S., vessel regulations have been implemented since 2011 to protect killer whales from vessel disturbance, particularly given the extent of whale-watching activities in the Salish Sea. We utilized suction cup-attached digital acoustic recording tags (DTAGs), consisting of hydrophones and movement sensors, to measure received noise levels, understanding killer whale use of sound, and determine effects of vessels and noise on subsurface behavior. During the 29 tag deployments on individually identified killer whales, we collected detailed geo-referenced vessel data concurrently as conditions allowed, along with opportunistic observations of predation to validate feeding. Received noise levels (dB re 1microPa) were significantly different across years but not consistently lower after the implementation of vessel regulations. Of the vessel factors considered, both vessel count and speed, but not distance, explained differences in noise levels, which may reflect changes in whale-watching vessel practices after regulations implementation. Additionally, the analysis of data from these animal-borne tags allow us to better understand subsurface foraging behavior involving the use of sound, to quantify foraging rates at an individual level, and to understand detailed vessel and noise effects. The results, along with those of other related studies, inform conservation and management measures that aim to promote Southern Resident recovery

Validating a Method to Ensure the Destruction of Salmonella on Product Surfaces During Impingement Cooking

This study investigated the effectiveness of cooking processes that incorporated hydrated surface lethality (HSL) steps for ensuring the reduction of Salmonella on the surfaces of small-dimension meat and poultry products cooked using short-duration, high-temperature impingement oven processes. Whole-muscle chicken tenders (3% fat), beef patties (10% and 30% fat), pork patties (10% and 30% fat), and chicken patties (10% and 20% fat) were surface inoculated with a 5-strain mixture of Salmonella to yield 8 log colony-forming units/g, then cooked in a two-zone impingement oven using either dry heat or steam-humidified HSL processes. The HSL steps used steam injection to control the wet-bulb temperature at either 71.1°C or 82.2°C. Dry-heat cooking processes using a dry-bulb temperature of 204.4°C and no steam-injected HSL steps failed to consistently achieve a 6.5 log reduction of Salmonella on chicken tenders and the low-fat patty products (≤10% fat). In contrast, processes incorporating an HSL step using an 82.2°C wet-bulb temperature in one or both zones resulted in ≥6.5 log reductions of Salmonella for all products. Sufficient reductions were achieved regardless of whether this 82.2°C wet-bulb HSL step was incorporated before or after a dry-cook step. Processes that incorporated an HSL step using a 71.1°C wet-bulb temperature in both zones also resulted in reductions ≥6.5 log for all products. Processes using a 71.1°C wet-bulb HSL step in only one zone delivered ≥ 6.5 log reduction for all of the patty products. However, the one-zone 71.1°C HSL step achieved ≥6.5 log reduction in chicken tenders only if used in the first zone of the two-zone oven. When the 71.1°C HSL step was used in the second zone for chicken tenders after using dry heat in the first zone, the target reduction of 6.5 log was not achieved. This research successfully validated approaches to ensure ≥6.5 log reduction of Salmonella on product surfaces

Prospectus, December 13, 1989

https://spark.parkland.edu/prospectus_1989/1032/thumbnail.jp

Exploration Medical Capability Medical System Recommendations for Gateway

- Medical System Content Development - 2019: Develop clinical content to inform medical system design; Iterate on content with wider ExMC (Exploration Medical Capability) team; Capture processes used to perform these tasks. - Using model content to inform system design - SME (Subject Matter Expert) collaboration to refine systems using clinical content

Prospectus, December 3, 1990

https://spark.parkland.edu/prospectus_1990/1026/thumbnail.jp

Laboratory feeding tests on the development of gypsy moth larvae with reference to plant taxa and allelochemicals

The first through fifth instars of the gypsy moth were tested for development to adults on 326 species of dicotyledonous plants in laboratory feeding trials. Among accepted plants, differences in suitability were documented by measuring female pupal weights. The majority of accepted plants belong to the subclasses Dilleniidae, Hamamelidae, and Rosidae. Species of oak, maple, alder, madrone, eucalyptus, poplar, and sumac were highly suitable. Plants belonging to the Asteridae, Caryophyllidae, and Magnoliidae were mostly rejected. Foliage type, new or old, and instar influenced host plant suitability. Larvae of various instars were able to pupate after feeding on foliage of 147 plant species. Of these, 101 were accepted by first instars. Larvae from the first through fifth instar failed to molt on foliage of 151 species. Minor feeding occurred on 67 of these species. In general, larvae accepted new foliage on evergreen species more readily than old foliage. The results of these trials were combined with results from three previous studies to provide data on feeding responses of gypsy moth larvae on a total of 658 species, 286 genera, and 106 families of dicots. Allelochemic compositions of these plants were tabulated from available literature and compared with acceptance or rejection by gypsy moth. Plants accepted by gypsy moth generally contain tanning, but lack alkaloids, iridoid monoterpenes, sesquiterpenoids, diterpenoids, and glucosinolates.Published March 1994. Facts and recommendations in this publication may no longer be valid. Please look for up-to-date information in the OSU Extension Catalog: http://extension.oregonstate.edu/catalo

Evaluating Alternative Ebullition Models for Predicting Peatland Methane Emission and Its Pathways via Data–Model Fusion

Understanding the dynamics of peatland methane (CH4) emissions and quantifying sources of uncertainty in estimating peatland CH4 emissions are critical for mitigating climate change. The relative contributions of CH4 emission pathways through ebullition, plant-mediated transport, and diffusion, together with their different transport rates and vulnerability to oxidation, determine the quantity of CH4 to be oxidized before leaving the soil. Notwithstanding their importance, the relative contributions of the emission pathways are highly uncertain. In particular, the ebullition process is more uncertain and can lead to large uncertainties in modeled CH4 emissions. To improve model simulations of CH4 emission and its pathways, we evaluated two model structures: (1) the ebullition bubble growth volume threshold approach (EBG) and (2) the modified ebullition concentration threshold approach (ECT) using CH4 flux and concentration data collected in a peatland in northern Minnesota, USA. When model parameters were constrained using observed CH4 fluxes, the CH4 emissions simulated by the EBG approach (RMSE = 0.53) had a better agreement with observations than the ECT approach (RMSE = 0.61). Further, the EBG approach simulated a smaller contribution from ebullition but more frequent ebullition events than the ECT approach. The EBG approach yielded greatly improved simulations of pore water CH4 concentrations, especially in the deep soil layers, compared to the ECT approach. When constraining the EBG model with both CH4 flux and concentration data in model–data fusion, uncertainty of the modeled CH4 concentration profiles was reduced by 78 % to 86 % in comparison to constraints based on CH4 flux data alone. The improved model capability was attributed to the well-constrained parameters regulating the CH4 production and emission pathways. Our results suggest that the EBG modeling approach better characterizes CH4 emission and underlying mechanisms. Moreover, to achieve the best model results both CH4 flux and concentration data are required to constrain model parameterization

Evaluating alternative ebullition models for predicting peatland methane emission and its pathways via data–model fusion

Understanding the dynamics of peatland methane (CH4) emissions and quantifying sources of uncertainty in estimating peatland CH4 emissions are critical for mitigating climate change. The relative contributions of CH4 emission pathways through ebullition, plant-mediated transport, and diffusion, together with their different transport rates and vulnerability to oxidation, determine the quantity of CH4 to be oxidized before leaving the soil. Notwithstanding their importance, the relative contributions of the emission pathways are highly uncertain. In particular, the ebullition process is more uncertain and can lead to large uncertainties in modeled CH4 emissions. To improve model simulations of CH4 emission and its pathways, we evaluated two model structures: (1) the ebullition bubble growth volume threshold approach (EBG) and (2) the modified ebullition concentration threshold approach (ECT) using CH4 flux and concentration data collected in a peatland in northern Minnesota, USA. When model parameters were constrained using observed CH4 fluxes, the CH4 emissions simulated by the EBG approach (RMSE = 0.53) had a better agreement with observations than the ECT approach (RMSE = 0.61). Further, the EBG approach simulated a smaller contribution from ebullition but more frequent ebullition events than the ECT approach. The EBG approach yielded greatly improved simulations of pore water CH4 concentrations, especially in the deep soil layers, compared to the ECT approach. When constraining the EBG model with both CH4 flux and concentration data in model–data fusion, uncertainty of the modeled CH4 concentration profiles was reduced by 78 % to 86 % in comparison to constraints based on CH4 flux data alone. The improved model capability was attributed to the well-constrained parameters regulating the CH4 production and emission pathways. Our results suggest that the EBG modeling approach better characterizes CH4 emission and underlying mechanisms. Moreover, to achieve the best model results both CH4 flux and concentration data are required to constrain model parameterization