Munyandorero: Climate effects on Micropogonias undulatus 
67 
these effects were statistically significant but weak 
(i.e., explaining smaller amounts of the variation in the 
dependent variables) or insignificant, hence negligible. 
With the available data, BDMs failed to fully capture 
MWET effects on the Atlantic Croaker population, al- 
though these effects are notorious. Accumulation of 
longer time series of data on fisheries, surveys, winter 
water temperature, and other relevant covariates (e.g., 
indices of habitat conditions, winter-induced kills of 
juveniles), warrant further investigations on BDM per- 
formance and their ability to detect cold winter effects 
on the Atlantic Croaker population dynamics along the 
U.S. Atlantic coast. 
Acknowledgments 
This study was prepared under award NA07N- 
MF470212 from NOAA to the Florida Fish and Wild- 
life Conservation Commission. M. D. Murphy, J. Boyett, 
and B. Crowder helped edit this manuscript. W. Cooper 
and E. H. Leone helped with R programming and ap- 
propriate literature. L. M. Lee, K. Drew, and 3 anony- 
mous reviewers offered constructive comments and 
suggestions. Members of the ASMFC Technical Com- 
mittee and Stock Assessment Subcommittee for Atlan- 
tic Croaker compiled the fishery data and life history 
information used in this study. This article is dedicated 
to the memory of my deceased father, Ngendahimana 
Jean, for having cared deeply about my education de- 
spite the fact that he was not formally educated. 
Literature cited 
Barbieri, L. R., M. E. Chittenden Jr., and C. M. Jones. 
1997. Yield-per-recruit analysis and management strate- 
gies for Atlantic croaker, Micropogonias undulatus , in 
the Middle Atlantic Bight. Fish. Bull. 95:637-645. 
Barbieri, L. R., M. E. Chittenden Jr., and S. K. Lowerre-Barbieri. 
1994. Maturity, spawning, and ovarian cycle of Atlan- 
tic croaker, Micropogonias undulatus, in the Chesa- 
peake Bay and adjacent coastal waters. Fish. Bull. 
92:671-685. 
Buckland, S. T., K. B. Newman, L. Thomas, and N. B. Koesters. 
2004. State-space models for the dynamics of wild ani- 
mal populations. Ecol. Model. 171:157-175. 
Bundy, A., J. Link, T. Miller, E. Moksness, and K. Stergiou 
(eds). 
2012. Theme section: comparative analysis of marine 
fisheries production. Mar. Ecol. Prog. Ser. 459:157-302. 
Caddy, F. J., and R. Mahon. 
1995. Reference points for fisheries management. FAO 
Fish. Tech. Pap. 347:1-83. 
Chao, L. N., and J. A. Musick. 
1977. Life history, feeding habits, and functional mor- 
phology of juvenile sciaenid fishes in the York River 
estuary, Virginia. Fish. Bull. 75:657-702. 
Ellison, A. M. 
2004. Bayesian inference in ecology. Ecol. Lett. 7:509-520. 
Evans, C. R., L. J. Opnai, and B. D. Kare. 
1997. Fishery ecology and oceanography of the prawn 
Penaeus merguiensis (de Man) in the Gulf of Papua: es- 
timation of maximum sustainable yield and modeling 
yield, effort and rainfall. Mar. Freshw. Res. 48:218-229. 
Fogarty, M. J., W. J. Overholtz, and J. S. Link. 
2012. Aggregate surplus production models for demersal 
fishery resources of the Gulf of Maine. Mar. Ecol. Prog. 
Ser. 459:247-258. 
Freon, P. 
1988. Introduction of environmental variables into glob- 
al production models. In Proceedings of the Interna- 
tional Symposium on Long Term Changes in Marine 
Fish Populations; Vigo, Spain, 18-21 November 1986 (T. 
Wyatt and M. G. Larraneta, eds.), p. 484-528. Consejo 
Superior de Investigaciones Cientificas, Vigo, Spain. 
Grosbois, V., O. Gimenez, J. -M. Gaillard, R. Pradel, C. Bar- 
braud, J. Clobert, A. P. Mqller, and H. Weimerskirch. 
2008. Assessing the impact of climate variation on sur- 
vival in vertebrate populations. Biol. Rev. 83:357-399. 
Hammond, T. R., and J. R. Ellis. 
2005. Bayesian assessment of northeast Atlantic spurdog 
using a stock production model, with prior for intrinsic 
population growth rate set by demographic methods. J. 
Northwest Atl. Fish. Sci. 35:299-308. 
Hare, J. A., and K. W. Able. 
2007. Mechanistic links between climate and fisheries 
along the East Coast of the United States: explaining 
population outbursts of Atlantic croaker (Micropogonias 
undulatus). Fish. Oceanogr. 16:31-45. 
Hare, J. A., M. A. Alexander, M. J. Fogarty, E. H. Williams, 
and J. D. Scott. 
2010. Forecasting the dynamics of a coastal fishery spe- 
cies using a coupled climate-population model. Ecol. 
Appl. 20:452-464. 
Harwood, J., and K. Stokes. 
2003. Coping with uncertainty in ecological advice: les- 
sons from fisheries. Trends Ecol. Evol. 18:617-622. 
Hatton, I. A., K. S. McCann, J. Umbanhowar, and J. B. 
Rasmussen. 
2006. A dynamic approach to evaluate risk in resource 
management. Ecol. Appl. 16:1238-1248. 
Hilborn, R., and M. Mangel. 
1997. The ecological detective: confronting models with 
data, 315 p. Princeton Univ. Press, Princeton, NJ. 
Hilborn, R., and C. J. Walters. 
1992. Quantitative fisheries stock assessment: choice, 
dynamics and uncertainty, 570 p. Routledge, Chapman 
& Hall, Inc., New York. 
lies, T. C., and R. J. H. Beverton. 
1998. Stock, recruitment and moderating processes in 
flatfish. J. Sea Res. 39:41-55. 
Jacobson, L. D., J. A. A. De Oliveira, M. Barange, M. A. Cisner- 
os-Mata, R. Felix-Urga, J. R. Hunter, J. Y. Kim, Y. Matsuura, 
M. Niquem, C. Porteiro, R. Brian, R. P. Sanchez, R. Serra, A. 
Uriarte, and T. Wade. 
2001. Surplus production, variability, and climate change 
in the great sardine and anchovy fisheries. Can. J. 
Fish. Aquat. Sci. 58:1891-1903. 
Jacobson, L. D, S. X. Cadrin, and J. R. Weinberg. 
2002. Tools for estimating surplus production and F^gy 
in any stock assessment model. N. Am. J. Fish. Man- 
age. 22:326-338. 
