60 
Fishery Bulletin 11 7(1-2) 
monitoring are considered top priorities for manage¬ 
ment of river herring, with an emphasis on total catch 
(including bycatch), validation of age determination, 
determination of population sizes, and determination of 
the effectiveness of restoration efforts (ASMFC, 2012, 
2017). Data on the populations of river herring in the 
Potomac River have been limited to indices of juvenile 
abundance and to surveys of adults by using electro¬ 
fishing or push nets (Schlick, 2016; ASMFC, 2017). The 
catch per unit of effort for adults captured in the Po¬ 
tomac River by the District of Columbia Department 
of Energy and Environment has increased since 2012 
for both species; however, the geometric mean of catch 
of juvenile river herring does not have the same clear 
trend in seining data collected by the District of Co¬ 
lumbia Department of Energy and Environment and 
Maryland Department of Natural Resources (ASMFC, 
2017). The Potomac Environmental Research and Edu¬ 
cation Center of George Mason University has reported 
an increase in river herring catch since 1988 in Gun- 
ston Cove, a small embayment of the Potomac River 
(Schlick, 2016; Jones et al 5 ). 
Whether habitat degradation or overfishing are the 
major contributors to the decline of these populations, 
data on the characteristics of spawning populations of 
river herring are needed to help manage them. Growth 
rates can change over time because of overfishing or 
degradation of spawning habitat and through natural 
variation over time (Heino, 1998; Law, 2000; Heino and 
Godo, 2002; Wang and Hook, 2009). Additionally, these 
characteristics can differ within populations through¬ 
out their geographical range, even in close proximity 
(Sheppard et al. 6 ; Tuckey and Olney, 2010). For exam¬ 
ple, alewife had statistically higher growth rates in the 
Nemasket River, Massachusetts, than in 3 other riv¬ 
ers in Massachusetts (Sheppard et al. 6 ). Fish fecundity 
is directly related to size, with larger individuals in 
a population producing more eggs per spawning event 
(Lake and Schmidt 7 ). Therefore, body size and growth 
rates are important in population analyses. Updating 
growth parameters of the species after severe declines 
in the population is important for current stock assess¬ 
ment strategies. 
5 Jones, R. C., K. de Mutsert, and A. Fowler. 2017. An eco¬ 
logical study of Gunston Cove 2016: final report, 181 p. Po¬ 
tomac Environ. Res. Educ. Cent., George Mason Univ., Fair¬ 
fax, VA. [Available from website.] 
6 Sheppard, J. J., P. D. Brady, M. P. Armstrong, and G. A. 
Nelson. 2010. Characterizing contemporary and historic 
age structure of alewives (Alosa pseudoharengus) in Mas¬ 
sachusetts spawning runs: final report, 110 p. [Available 
from Mass. Div. Mar. Fish., 30 Emerson Ave., Gloucester, MA 
01983.] 
7 Lake, T. R., and R. E. Schmidt. 1998. The relationship be¬ 
tween fecundity of an alewife (Alosa pseudoharengus ) spawn¬ 
ing population and egg productivity in Quassaic Creek, a 
Hudson River tributary (HRM 60) in Orange County, New 
York. In Final reports of the Tiber T. Polgar Fellowship 
Program, 1997 (J. R. Waldman and W. C. Nieder.eds.), p. II- 
1-24. Hudson River Foundation, NY. [Available from web¬ 
site.] 
The von Bertalanffy growth function is the most 
commonly used model to describe the growth (in length 
or weight) of individuals within a fish population; how¬ 
ever, for many species, the von Bertalanffy growth 
model is not the best fit (Quinn and Deriso, 1999; 
Katsanevakis and Maravelias, 2008; Haddon, 2011). 
Katsanevakis and Maravelias (2008) reported that 
the von Bertalanffy growth function was the best-fit 
model in 34.6% of 133 different data sets. A difference 
in the best-fit model between populations could be due 
to the parameters used in the model or the particu¬ 
lar species not growing at an asymptotic rate, which 
is an assumption of the von Bertalanffy growth model 
(Katsanevakis and Maravelias, 2008). Today, multiple 
growth models can be constructed easily with the use 
of software programs; therefore, a useful way to de¬ 
termine the best-fit model is running multiple types 
of growth models (e.g., von Bertalanffy, Gompertz, and 
Richards) and then statistically comparing the growth 
parameters by using the Akaike’s information criterion 
(AIC) (Burnham and Anderson, 2002; Katsanevakis 
and Maravelias, 2008). 
Development of growth models is necessary for un¬ 
derstanding population size and growth potential, in¬ 
formation used to properly manage fisheries use, and 
can be achieved by using length-at-age data; how¬ 
ever, length-at-age data for river herring have been 
used with little validation or standardization of ag¬ 
ing techniques between scientists (ASMFC 8 ). Aging of 
river herring has been accomplished through reading 
annuli on whole otoliths or on scales under a dissect¬ 
ing microscope; however, validation with known ages 
of individuals has not been documented for river her¬ 
ring (ASMFC 8 ). Aging by reading scales is a nonlethal 
option but can result in less accurate age estimation 
because periods of minimal growth can result in false 
annuli on scales (Campana and Neilson, 1985; Beamish 
and McFarlane, 1987). Additionally, the methods devel¬ 
oped by Cating (1953) for American shad (A. sapidis- 
sima ) were the most cited methods for aging river her¬ 
ring by using scales until Duffy et al. (2011) reported 
that the transverse grooves on scales used in aging can 
vary over time and geographical range. 
The goal of this study was to examine lengths, ages, 
and growth of adult river herring returning to tribu¬ 
taries of the Potomac River in 2007-2015 to spawn. 
The objectives to obtain this goal were to determine 
1) the relationships between different measurements 
of length, 2) bias between using scales and using oto¬ 
liths to estimate age, 3) the best-fit model by examin¬ 
ing multiple growth models, and 4) growth parameters 
by using the best-fit model. Understanding length, age, 
and growth parameters is crucial for the determination 
of the reproductive capacity, potential restoration time 
8 ASMFC (Atlantic States Marine Fisheries Commission). 
2014. 2013 river herring ageing workshop report, 88 
p. Atl. States Mar. Fish. Comm., Washington, D.C. [Avail¬ 
able from website.] 
