TY - JOUR
T1 - A Bayesian approach to estimating target strength
AU - Fässler, Sascha M. M.
AU - Brierley, Andrew S.
AU - Fernandes, Paul G.
N1 - Funding Information:
The authors are grateful to Dezhang Chu and Gareth Lawson from the Woods Hole Oceanographic Institution, Woods Hole, MA, for providing the MATLAB code for the fish-body model. We thank Dave Borchers (CREEM, St Andrews University, UK), Liz Clarke (FRS, Aberdeen, UK), and Colin Millar (CREEM and FRS) for their expert advice and help with Bayesian statistical methods. SMMF acknowledges the support received through an ORSAS award of the British government, a studentship of the University of St Andrews (Scotland), and an Ausbildungsbeitrag of the Kanton Basel-Landschaft (Switzerland).
PY - 2009/7
Y1 - 2009/7
N2 - Currently, conventional models of target strength (TS) vs. fish length, based on empirical measurements, are used to estimate fish density from integrated acoustic data. These models estimate a mean TS, averaged over variables that modulate fish TS (tilt angle, physiology, and morphology); they do not include information about the uncertainty of the mean TS, which could be propagated through to estimates of fish abundance. We use Bayesian methods, together with theoretical TS models and in situ TS data, to determine the uncertainty in TS estimates of Atlantic herring (Clupea harengus). Priors for model parameters (surface swimbladder volume, tilt angle, and s.d. of the mean TS) were used to estimate posterior parameter distributions and subsequently build a probabilistic TS model. The sensitivity of herring abundance estimates to variation in the Bayesian TS model was also evaluated. The abundance of North Sea herring from the area covered by the Scottish acoustic survey component was estimated using both the conventional TS-length formula (5.34×10 9 fish) and the Bayesian TS model (mean = 3.17×109 fish): this difference was probably because of the particular scattering model employed and the data used in the Bayesian model. The study demonstrates the relative importance of potential bias and precision of TS estimation and how the latter can be so much less important than the former.
AB - Currently, conventional models of target strength (TS) vs. fish length, based on empirical measurements, are used to estimate fish density from integrated acoustic data. These models estimate a mean TS, averaged over variables that modulate fish TS (tilt angle, physiology, and morphology); they do not include information about the uncertainty of the mean TS, which could be propagated through to estimates of fish abundance. We use Bayesian methods, together with theoretical TS models and in situ TS data, to determine the uncertainty in TS estimates of Atlantic herring (Clupea harengus). Priors for model parameters (surface swimbladder volume, tilt angle, and s.d. of the mean TS) were used to estimate posterior parameter distributions and subsequently build a probabilistic TS model. The sensitivity of herring abundance estimates to variation in the Bayesian TS model was also evaluated. The abundance of North Sea herring from the area covered by the Scottish acoustic survey component was estimated using both the conventional TS-length formula (5.34×10 9 fish) and the Bayesian TS model (mean = 3.17×109 fish): this difference was probably because of the particular scattering model employed and the data used in the Bayesian model. The study demonstrates the relative importance of potential bias and precision of TS estimation and how the latter can be so much less important than the former.
KW - Acoustic target strength
KW - Bayesian statistics
KW - Herring
KW - Survey uncertainty
UR - http://www.scopus.com/inward/record.url?scp=84855265408&partnerID=8YFLogxK
U2 - 10.1093/icesjms/fsp008
DO - 10.1093/icesjms/fsp008
M3 - Article
AN - SCOPUS:84855265408
SN - 1054-3139
VL - 66
SP - 1197
EP - 1204
JO - ICES Journal of Marine Science
JF - ICES Journal of Marine Science
IS - 6
ER -