Growth and Survival of Colorado Squawfish in the Upper Colorado River

Growth and adult survival rates were estimated for the endangered Colorado squawfish Ptychocheilus lucius inhabiting the upper Colorado River by using data from fish captured during 1990–1995. Mean annual growth rates of fish aged 3–6 years ranged from 32.2 (age 6) to 82.0 (age 3) mm/year. Growth rates for older fish were highest for fish 400–449 mm total length, TL, (42.7 mm/year) and declined to 19.8 mm/year for fish 500–549 mm TL. Fish 550 mm and longer grew an average 9.5 mm/year. Survival rates for fish 550 mm and longer were estimated by comparing measured size distributions with simulated stable age and size distributions; these ranged from 0.83–0.87, with the best fit at 0.85. Though lack of historical data precludes comparisons with past growth and survival rates, our data serve as a baseline for future population monitoring efforts

Dispersal Patterns of Subadult and Adult Colorado Squawfish in the Upper Colorado River

Abstract.—We investigated distribution and dispersal patterns of subadult and adult Colorado squawfish Ptychocheilus lucius (recently renamed the Colorado pikeminnow) throughout their range in the upper Colorado River. Annual, river-wide, capture–recapture data were used to document movements during a 5-year period (1991–1995). Average total length of Colorado squawfish progressively increased upstream: juveniles and subadults occurred almost exclusively in the lowermost 105 km of the 298-km study area, whereas most adults were concentrated in the uppermost 98 km. This was most pronounced early in the study and less so later due to the effect of two or three strong year-classes that dispersed through the system. Only 16% of subadult and adult fish initially captured and tagged in the upper reach were later located more than 10 km from the previous capture site; of those tagged in the lower reach, 58% were later located more than 10 km from the previous site. Most movements greater than 10 km were directed upstream, and many fish tagged in the lower reach moved to the upper reach; the smallest of these fish was between 421 and 449 mm in total length (TL) when it moved. No movement was detected from the upper reach to the lower. Distance moved was inversely related to fish size: displacement of fish shorter than 550 mm TL averaged 33.6 km; for those longer than 550 mm, average displacement was only 7.5 km. Movement of young adults may have been a response to changing food needs. Upstream movements placed fish into areas with greater availability of larger prey, and body condition of large adults during spring was significantly higher in the upper reach than in the lower reach. Water temperatures, however, were inversely related to adult distribution despite a preference for warmer water. We suggest that portions of the upper reach offer adults the best balance between food and water temperature

Spotlite: Web Application and Augmented Algorithms for Predicting Co-Complexed Proteins from Affinity Purification – Mass Spectrometry Data

Protein-protein interactions defined by affinity purification and mass spectrometry (APMS) approaches suffer from high false discovery rates. Consequently, the candidate interaction lists must be pruned of contaminants before network construction and interpretation, historically an expensive and time-intensive task. In recent years, numerous computational methods have been developed to identify genuine interactions from hundreds revealed by APMS experiments. Here, comparative analysis of several popular algorithms revealed complementarity in their classification accuracies, which is supported by their divergent scoring strategies. As such, we used two accurate and computationally efficient methods as features for machine learning using the Random Forest algorithm. Additionally, we developed novel mathematical models to include a variety of indirect data, such as mRNA co-expression, gene ontologies and homologous protein interactions as features within the classification problem. We show that our method, which we call Spotlite, outperforms existing methods on four diverse and public APMS datasets. Because implementation of existing APMS scoring methods requires computational expertise beyond many laboratories, we created a user-friendly and fast web application for APMS data scoring, analysis, annotation and network visualization, for use on new and existing data (http://152.19.87.94:8080/spotlite). The utility of Spotlite and its visualization platform for revealing physical, functional and disease-relevant characteristics within APMS data is established through a focused analysis of the KEAP1 E3 ubiquitin ligase