Trends in Liver and Skin Tumor Prevalence in Brown Bullhead ( Ameiurus nebulosus) from the Anacostia River, Washington, DC, and Nearby Waters.

The prevalence of liver and skin tumors in brown bullhead ( Ameiurus nebulosus) from the Anacostia River (Washington, DC) and nearby areas was determined in 2014, 2015, and 2016. The objectives were to (1) compare tumor prevalence across space and time; (2) analyze the 1992-2016 Chesapeake Bay Tumor Database to identify reference locations and test age, length, weight, and sex as covariates; and (3) explore whether changes in bullhead exposure to contaminants can explain the observed trends. With logistic regression, we reported large statistically significant decreases in liver tumor probabilities in bullheads from the Anacostia CSX Bridge (ANAC) area between 1996 and 2001 (merged: female, 77.8%; male, 48.6%), 2009 to 2011 (female, 42.5%; male, 16.6%), and 2014 to 2016 (female, 18.0%; male, 5.7%). Skin tumors decreased by a factor of six in both females and males. Polycyclic aromatic compounds (PAC) initiate liver neoplasms and polychlorinated biphenyls (PCBs) and DDT compounds are promoters. The causes of skin tumors in bullhead are uncertain. Biomarker and tissue data show decreases in PAC-DNA adducts and PCB and DDT contamination in ANAC bullheads. It is likely that the decreased liver tumor prevalence is associated with decreased exposure to these contaminants.

Tuning stochastic matrix models with hydrologic data to predict the population dynamics of a riverine fish.

We developed stochastic matrix models to evaluate the effects of hydrologic alteration and variable mortality on the population dynamics of a lotic fish in a regulated river system. Models were applied to a representative lotic fish species, the flathead catfish (Pylodictis olivaris), for which two populations were examined: a native population from a regulated reach of the Coosa River (Alabama, USA) and an introduced population from an unregulated section of the Ocmulgee River (Georgia, USA). Size-classified matrix models were constructed for both populations, and residuals from catch-curve regressions were used as indices of year class strength (i.e., recruitment). A multiple regression model indicated that recruitment of flathead catfish in the Coosa River was positively related to the frequency of spring pulses between 283 and 566 m3/s. For the Ocmulgee River population, multiple regression models indicated that year class strength was negatively related to mean March discharge and positively related to June low flow. When the Coosa population was modeled to experience five consecutive years of favorable hydrologic conditions during a 50-year projection period, it exhibited a substantial spike in size and increased at an overall 0.2% annual rate. When modeled to experience five years of unfavorable hydrologic conditions, the Coosa population initially exhibited a decrease in size but later stabilized and increased at a 0.4% annual rate following the decline. When the Ocmulgee River population was modeled to experience five years of favorable conditions, it exhibited a substantial spike in size and increased at an overall 0.4% annual rate. After the Ocmulgee population experienced five years of unfavorable conditions, a sharp decline in population size was predicted. However, the population quickly recovered, with population size increasing at a 0.3% annual rate following the decline. In general, stochastic population growth in the Ocmulgee River was more erratic and variable than population growth in the Coosa River. We encourage ecologists to develop similar models for other lotic species, particularly in regulated river systems. Successful management of fish populations in regulated systems requires that we are able to predict how hydrology affects recruitment and will ultimately influence the population dynamics of fishes.