Ecology of juvenile salmon in large floodplain rivers: the influence of habitat modification by beavers (\u3ci\u3eCastor canadensis\u3c/i\u3e) on salmon growth and production

I investigated the influence of beavers on aquatic floodplain habitats and determined how juvenile salmon habitat use, growth, survival, movement, and production varied by habitat type in a large alluvial floodplain of the Kwethluk River in western Alaska. I also compared juvenile salmon production at the floodplain scale in the Kwethluk River (with beavers), to a very similar salmon river in Kamchatka (the Kol) that has no beavers. Beavers modified 87.5% of the aquatic off-channel habitat of the Kwethluk River, which was composed of three successional stages of beaver ponds (early-, mid-, and latesuccessional), and beaver-influenced spring brooks. Early-successional ponds were closer to and more connected to the main channel, while mid- and late-successional ponds were farther from the main channel with more dams and highly variable hydrology. Juvenile salmon habitat use varied by habitat type. Total fish species and salmon species richness was 2-3x higher, the proportion of young-of-the-year salmon was over 50% compared to \u3c5%, and densities of juvenile salmon were 5-7x higher in spring brooks and early-successional ponds compared to late-successional ponds. The growth of youngof- the-year coho and Chinook was almost 2x higher in early-successional ponds compared to both beaver-influenced and beaver-free spring brooks, but survival rates were consistently highest each month (46 to 80%) in beaver-free spring brooks. Within the parafluvial zone early-successional ponds produced a greater biomass of juvenile salmon than either type of spring brook (175 vs. 149 and 140kg) but only reared half the individuals as beaver-free spring brooks (24,100 vs. 41,400 salmon). In contrast to the Kwethluk, there was no difference in species richness or density by habitat type within the Kol River, suggesting that juvenile salmon are able to rear in all parafluvial and orthofluvial habitats when beavers are not present. I estimated that in the absence of beavers the entire Kwethluk floodplain could produce 2x the biomass (between June-August, 1174 vs. 667kg) and rear 3x the number of salmon (370,000 vs. 140,000). By damming off-channel habitats and blocking large amounts of orthofluvial habitats beavers could have a large effect on production of juvenile salmon in a large alluvial river floodplain

Farm-based Production Parameters and Breakeven Costs for Yellow Perch Grow-out in Ponds in Southern Wisconsin

For over 30 years the yellow perch (Perca flavescens) has been viewed as a species with great potential for aquaculture in the North Central Region (NCR). The species has been the focus of a significant amount of research over this period, and has been a priority species for research sponsored by the North Central Regional Aquaculture Center (NCRAC) since its inception in 1988. Despite these efforts almost no information has been available on “real world” production parameters and costs of raising yellow perch to market size using different system types. The lack of such basic information on production costs is a primary reason for the failure of numerous yellow perch operations in the NCR

Effects of Certain Media on the Growth and Production of Greenhouse Tomatoes

Horticultur

Detection of Cocaine Use with Wireless Electrocardiogram Sensors

In recent years, the ability to continuously monitor activities, health, and lifestyles of individuals using sensor technologies has reached unprecedented levels. Such ubiquitous physiological sensing has the potential to profoundly improve our understanding of human behavior, leading to more targeted treatments for a variety of disorders. The long terms goal of this work is development of novel computational tools to support the study of addiction in the context of cocaine use. The current paper takes the first step in this important direction by posing a simple, but crucial question: Can cocaine use be reliably detected using wearable on-body sensors and current machine learning algorithms? We select wireless ECG as the most promising sensing modality for cocaine use detection. The main contributions in this paper include the presentation of a novel clinical study of cocaine use in which a unique set of wireless ECG data were collected, the description of a computational pipeline for inferring morphological features from noisy wireless ECG waveforms, and the evaluation of cocaine use detection algorithms based on data-driven and knowledge-based feature representations. Our results show that cocaine use can be detected with AUC levels above 0.9 in both the within-subjects and between-subjects cases at the 32mg/70kg dosage level