1. Implementing an external mortality model to estimate egg mortality and egg production for anchovy in the Gulf of Cadiz (2005-2014) ICES Working Group on Atlantic Fish Larvae and Eggs Surveys. Pasaia (Spain), 1 - 5 December 2014 1 Paz Díaz, 1 Paz Jiménez, and 2 MM Angélico 1 Instituto Español de Oceanografía (IEO) 2 Instituto Português do Mar e da Atmosfera (IPMA) Vigo - Cádiz - Lisboa

2. EstimateStd.errort valuePr(>[t])CV (%) 2005-0.039410.03137-1.2560.21379.6 2008-0.057520.01735-3.3150.00139**30.2 2011-0.012270.01397-0.8780.382113.8 2014-0.013890.01309-1.0610.29194.2 E [P] = P0 e -Z age E[P] : density of eggs per age P0 :rate of egg production (eggs/day/area) Z : rate of mortality BOCADEVA series External Mortality Model (Bernal et al., 2011) Anchovy DEPM surveys 2005-2014

3. Data set Data come from several research surveys, that included plankton sampling, carried out in waters of the Gulf of Cadiz, between 2005 to July 2014. GOLFO series (Feb. 2006 – Sep. 2007 (Monthly) STOCA series (Jul. 2009 – Nov. 2011 (Quarterly) BOCADEVA series (summer 2005,2008,2011 and 2014 (Trienal) YearJanFebMarAprMayJunJulAugSepOctNovDec 2005X 2006 XXXXXXXXXXX 2007XXXXXXXXX 2008 XX 2009 X X 2010 X X X 2011 X XX X 2014X

4. [1] Survey : Factor w/ 33 levels "","BOCADEVA 0714 [2] Sampler : Factor w/ 3 levels "","Bongo-40",..: [3] Station : Factor w/ 166 levels "","10","100", [4] Lat : num 36.6 36.6 37 36.4 36.4... [5] Long : num -6.59 -6.65 -7.38 -6.42 -6.51... [6] Date : int 20060222 20060223 20060223 [7] Time : num 15.65 14.82 15.42 8.38 9.4... [8] Depth : num 29 43 73 15 48 33 58 4 14 22... [9] Bottom : int 43 73 94 22 76 44 74 12 18 30... [10] Vol..m3. : num 55.1 79.7 106.3 49.4 35.9... [11] Efarea : num NA NA NA NA NA NA NA [12] SST : num 14.9 15 14.8 14.5 14.5 14.7 [13] I : num 0 0 0 0 0 1 0 0 0 0... [14] II : num 0 4 17 2 1 74 1 1 4 1... [15] III : num 0 0 0 1 1 0 0 0 0 0... [16] IV : num 0 0 0 0 0 0 8 0 0 0... [17] V : num 2 2 0 0 0 9 18 0 0 6... [18] VI : num 0 0 0 0 3 10 10 0 3 8... [19] VII : num 2 0 0 0 0 6 0 0 0 0... [20] VIII : num 0 0 0 1 0 0 6 0 1 0... [21] IX : num 0 0 0 0 0 1 11 0 1 0... [22] X : num 1 0 0 0 0 2 0 0 0 0... [23] XI : num 0 0 0 0 0 0 2 0 0 0... [24] Dis. : num 1 0 0 0 1 4 0 0 0 0... [25] Total staged eggs: int 6 6 17 4 6 107 56 1 9 15... Surveys within the area limits for which data on egg abundance by stage and temperature are available will used to estimate mortality Moser and Ahlstrom (1985) Egg stageing key Data set

5. A total 31119 Anchovy eggs classified into the different development stages Summary Data set

6. Egg age & mortality (All data available) Egg production (Data from DEPM) Process to estimate mortality and egg production Bernal et al., 2011

7.  Multinomial model of anchovy egg development (Duarte et al., 2007, Bernal et al., 2011) will used to relate egg stage and age for the sampled temperatures  Assumed peak spawning time will used to define the daily cohorts, cohorts abundance and mean cohort age for all stations what.control <- depm.control(spawn.mu = 22, spawn.sig = 2, how.complete=0.95)  New data with observed abundance-by-cohort used to fit the mortality curve 1. Estimation of age and cohort abundance Bernal et al., 2011

8. E [Na] = expected number of eggs in a cohort of mean age a D0 = the rate of egg production m = the mortality rate g 1 = the inverse of the link function that relates the linear predictor and the response, Na E[Na] = g −1 (offset(log(Efarea)) + log(D0) − ma)(1) Equation (1) for the dataset is then formulated as (2) to allow both egg production and mortality to vary between spatial strata and temperature E[Na] = g −1 (offset(log(Efarea)) + Sstrata + Temp + Sstrata :Temp + age + Sstrata :age + Temp: age) (2) “age” involved: mortality terms Equation (1) will fitted to the entire database using the statistical language R. 2. Mortality estimation Bernal et al., 2011

9.  Stepwise backward model selection will carried out from this model. At each step, the term with least significance (<5%) will dropped, and this procedure repeated until dropping terms led to no improvement.  A comparison with Akaike information criterion (AIC) profiles of the model selection procedure will also performed.  To avoid bias in the mortality model caused for the extremes of the data: lower limit and upper limits will set on the tails of the mortality curve 2. Mortality estimation Bernal et al., 2011

10. glm.nb(formula = cohort ~ offset(log(Efarea) - death * age) - 1 + Sstrata, data, weights = Rel.area) 3. Egg production estimates Bernal et al., 2011 1 2 Strait of Gibraltar Cape San Vicente In 2005 it was necessary poststratification In 2008 it was necessary poststratification weights = Rel.area used to account for increased sampling in areas of expected high egg densities

11. P 0 (eggs/m 2 /day)Z (day -1 ) 200551 (1) - 225 (2) -0.94 2008184 (1) - 348 (2) -1.43 2011276-0.29 2014313.5-0.33 Egg production and mortality rate comparison with data from literature (Z values in day -1 ) DEPM BOCADEVA Gulf of Cádiz (1)Stratum 1 (2)Stratum 2 Carvajalino, J.F, 2011

12. A special thanks to Miguel Bernal, for the useful help and comments about the daily egg production estimation methods and external mortality model. Thank you Acknowledgements