Estimated Growth and Standing Crop of Largemouth Bass (Micropterus salmoides) from Lake Elmdale

Electro-fishing gear was used to make shoreline population estimates of largemouth bass (Micropterus salmoldes) in Lake Elmdale, Washington County, Arkansas, during September 1979. The population density was estimated to be 1541 bass/Km² with a standing crop of 30.4 kg/ha. The length-weight relationship was calculated as W = 0.00001 504L^2.97, and the total length-scale radius relationship as L = 41.75 + 1.23 St. The average condition coefficient(K) was 1.31. In comparison with four other Arkansas lakes the population density of largemouth bass was highest in Lake Elmdale while the growth rate was lowest

Empirical Models of Transitions between Coral Reef States: Effects of Region, Protection, and Environmental Change

There has been substantial recent change in coral reef communities. To date, most analyses have focussed on static patterns or changes in single variables such as coral cover. However, little is known about how community-level changes occur at large spatial scales. Here, we develop Markov models of annual changes in coral and macroalgal cover in the Caribbean and Great Barrier Reef (GBR) regions

Histopathology of Growth Anomaly Affecting the Coral, Montipora capitata: Implications on Biological Functions and Population Viability

Growth anomalies (GAs) affect the coral, Montipora capitata, at Wai'ōpae, southeast Hawai'i Island. Our histopathological analysis of this disease revealed that the GA tissue undergoes changes which compromise anatomical machinery for biological functions such as defense, feeding, digestion, and reproduction. GA tissue exhibited significant reductions in density of ova (66.1–93.7%), symbiotic dinoflagellates (38.8–67.5%), mesenterial filaments (11.2–29.0%), and nematocytes (28.8–46.0%). Hyperplasia of the basal body wall but no abnormal levels of necrosis and algal or fungal invasion was found in GA tissue. Skeletal density along the basal body wall was significantly reduced in GAs compared to healthy or unaffected sections. The reductions in density of the above histological features in GA tissue were collated with disease severity data to quantify the impact of this disease at the colony and population level. Resulting calculations showed this disease reduces the fecundity of M. capitata colonies at Wai'ōpae by 0.7–49.6%, depending on GA severity, and the overall population fecundity by 2.41±0.29%. In sum, GA in this M. capitata population reduces the coral's critical biological functions and increases susceptibility to erosion, clearly defining itself as a disease and an ecological threat

Fishery-Independent Data Reveal Negative Effect of Human Population Density on Caribbean Predatory Fish Communities

BACKGROUND: Understanding the current status of predatory fish communities, and the effects fishing has on them, is vitally important information for management. However, data are often insufficient at region-wide scales to assess the effects of extraction in coral reef ecosystems of developing nations. METHODOLOGY/PRINCIPAL FINDINGS: Here, I overcome this difficulty by using a publicly accessible, fisheries-independent database to provide a broad scale, comprehensive analysis of human impacts on predatory reef fish communities across the greater Caribbean region. Specifically, this study analyzed presence and diversity of predatory reef fishes over a gradient of human population density. Across the region, as human population density increases, presence of large-bodied fishes declines, and fish communities become dominated by a few smaller-bodied species. CONCLUSIONS/SIGNIFICANCE: Complete disappearance of several large-bodied fishes indicates ecological and local extinctions have occurred in some densely populated areas. These findings fill a fundamentally important gap in our knowledge of the ecosystem effects of artisanal fisheries in developing nations, and provide support for multiple approaches to data collection where they are commonly unavailable

Balancing the learning ability and memory demand of a perceptron-based dynamically trainable neural network

Artificial neural networks (ANNs) have become a popular means of solving complex problems in prediction-based applications such as image and natural language processing. Two challenges prominent in the neural network domain are the practicality of hardware implementation and dynamically training the network. In this study, we address these challenges with a development methodology that balances the hardware footprint and the quality of the ANN. We use the well-known perceptron-based branch prediction problem as a case study for demonstrating this methodology. This problem is perfect to analyze dynamic hardware implementations of ANNs because it exists in hardware and trains dynamically. Using our hierarchical configuration search space exploration, we show that we can decrease the memory footprint of a standard perceptron-based branch predictor by 2.3 with only a 0.6% decrease in prediction accuracy.Raytheon Missile Systems [2017-UNI-0008]12 month embargo; published online: 16 April 2018This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]