ALIMENTACION DE REINETA, TASA DE CONSUMO Y CONSUMO/BIOMASA

KLARIAN SA, MOLINA BE, CANALES-CERRO C & HERNANDEZ MF.

FIPA: 2015-20 ARANCIBIA ET AL. (2015)

Brama australis

2

BRAMIDAE

6 Generos y 18 spp

Brama

Ton

0

1500

3000

4500

6000

ENE FEB MAR ABR MAY JUN JUL AGO SEP OCT NOV DIC

3,309

5,072 5,289

2,5821,239 1,800 1,362

2,433 2,736 2,654 2,4663,276

DESEMBARQUES 2015

INTRODUCCIÓN

TROFODINAMICA 3

MODELOS TRÓFICOSFunción

Esctructura

dinámica predador-presa

MODELOS EBE

Multispecies virtual population analysis is an extension ofsingle-species virtual population analysis (SSVPA) and esti-mates fishing mortality, recruitment, stock abundance, andpredation mortality based on catch-at-age data and stomachcontent data. Therefore, MSVPA uses the same equations andbackward algorithm as SSVPA (Gulland 1965). Abundancefor the plus group and the final year of the assessment iscalculated from Baranov’s catch equation,

Nþa;t¼ Ca;tZa;t

Fterm;a;t 1# e#Za;tð Þ; (1)

where Ca,t represents the annual catch at age; Za,t represents thetotal mortality at age (Za,t = Fterm,a,t + Ma,t); Fterm,a,t representsthe terminal fishing mortality at age; Ma,t represents naturalmortality (described in detail below); and Nþ

a;t represents theabundance of the plus group or the abundance of age-class a inthe final year of the assessment (2007). The abundance of theremaining age-classes is backward calculated as

Na#1;t#1 ¼ Na;teZa;t : (2)

Equation (2) is also used directly to estimate recruitment (N0,t).Fishing mortality at age is also calculated iteratively fromequation (1).

The MSVPA differs from SSVPA primarily by separatingnatural mortality (M) into two components: residual mortality(M1) and predation mortality (M2). Residual mortality encom-passes several causes of mortality, such as aging, starvation,diseases, and predation by other species not included in themodel; M1 is assumed to be constant for each age-class withineach species. This separation hypothesis allows predation mor-tality to be estimated for each age-class through time. Predationmortality is calculated with the following equation (Sparre 1991),

M2;p;a ¼X

i

X

j

!Ni;jRi;jSp;a;i;j

Bof Si;of þPp

Pa

!Np;a !Wp;aSp;a;i;j; (3)

where M2,p,a is the predation mortality of prey p at age a; !Ni;j is

the average abundance of predator i at age j !Ni;j ¼ Ni;j;tþ1#Ni;j;t

Zi;j;t

! ";

Rij is the annual ration (total annual food consumption, kg) forthe predator species; Sp,a,i,j is the suitability coefficient for eachpredator–prey combination; Bof is the biomass of other prey(“other food”) available to the predator; Si,of is the suitabilitycoefficient for the predator–other prey combination; !Np;a is theaverage abundance of prey p at age a; and !Wp;a is the averageweight of the prey. For simplicity, the index t for time has beenomitted from equation (3).

Suitability coefficients reflect the predator’s diet composi-tion relative to the available food (Sparre 1991). Estimation ofsuitability is based on stomach content data according to thefollowing operational definition:

Sp;a;i;j ¼Up;a;i;j=!Np;aWp;a

Pp

PaUp;a;i;j=!Np;aWp;a

; (4)

where Up,a,i,j is the observed food composition in the preda-tor’s stomach contents; a is the age of prey p; and j is the ageof predator i. Predator/prey suitability values have also beendefined as a weighting factor determining the availability ofprey p as food for predator i (Gislason and Sparre 1987).Solution of the previous equations (1–4) requires the use ofthree nested iterative algorithms (Sparre 1991). More detailson MSVPA assumptions, equations, and algorithms areprovided by Sparre (1991) and Magnusson (1995).

Due to its complexity, MSVPA requires several types of inputdata, including stomach content data, annual predator ration,M1,catch at age, and Fterm, all of which are described below.

The food composition or stomach content data are probablythe most important data for estimating predation mortalityM2 inthe MSVPA. However, diet composition information is scarcefor SCDF species; therefore, we considered a different approachfor these fisheries based on the work of Ursin (1973). Theapproach uses parameters from the predator–prey size ratios toarrive at a theoretical estimate of Ursin’s prey selectivity index.

Using a simplification from Bogstad et al. (2003), the suit-ability coefficients were calculated with the following equation:

Sp;a;i;j ¼ e#

ln Wi;j=Wp;að Þ#ηð Þ22σ2

# $

; (5)

where Wi,j is the weight of predator i at age j; and Wp,a is theweight of prey p at age a. The constant η represents the meanlog ratio between the predator weight and prey weight,

FIGURE 1. Predation interactions for the species system used in the multispeciesvirtual population analysismodel defined for the southernChilean demersalfishery.

352 JURADO-MOLINA ET AL.

Jurado-Molina et al. 2016

METODOS EN TROFODINAMICA 4

SCA

ACDR

HM

SIA

FECAS

SCA

Provee info. presas

Incertidumbre cero

SIA

Info a largo plazo

Inferencias de consumo

‣ Sesgos debido a las TDg

‣ Info a corto plazo

‣ Alta incertidumbre - sin SCA

‣ Elevate costo para continua eva.

ENTENDIENDO SIA EN ECOLOGÍA TRÓFICA

TIEMPO δδ

PLASMA SANGREHIGADO

MUSCULOHUESO

DIAS SEMANAS MESES

HISTORIA DE VIDA

Kohn 1999

PRESA CONSUMIDA POR EL PREDATOR + PRESA ES ASIMILADA POR EL PREDADOR.

= EL VALOR DE SIA DE PREDADOR, REFLEJA LA “SEÑAL”

ISOTOPICA DE LA PRESA

5

ENTENDIENDO SIA EN ECOLOGÍA TRÓFICA

δ13C(‰)

δ15N

(‰)

HABITAT - ZONA DE ALIMENTACIÓNOCEANICOPELAGICO

NERITICOBENTONICO

NIGE

L TRÓ

FICO

CARBONO: COMO ES GASTADA ESA ENEREGIA

NITROGENO: CUANTA ENERGÍA ENTREGA LAS PRESA

6

ALIMENTACIÓN DE BRAMA AUSTRALIS

▸ Siguiendo los TTR FIPA 2015:20…

▸ 1. Describir la dieta de Reinetas durante 2016, a través de SCA - SIA

▸ 2. Calcular el consumo de ailmento for metodos SCA y SIA

▸ 3. Calcular Cosumo/Biomasa

Muñoz et al (1995)

PACIFÍCO

0

25

50

75

100

1995 2002 2014

EUFMESOPCEFSARD

Garcia & Chong (2002) Santa Cruz et al (2014)

Horn et al (2013)N. ZELANDA

45

91 MESOPCAMZOO

7

MATERIALES Y METODOS 8

1448 SCA

457 SIA

457 REINETAS +

213 PRESAS CALORIMETRIA

CONGELADAS -20º SCA; 80º SIA Y CALORIMETRÍA - UNAB -

MUESTRAS

ZONA TALCAHUANO

LEBU PTO CHACABUCO

TEMPORALIDAD ENE-ABR MAY-AGO TAMAÑO

<39 CM >40 CM

SCA 9

Lab. work - UNAB - ESTOMAGOS

LLENO VACIO

PRESAS

P, N, F>GD-

SIA

TAXON

Analisis de datos

Importancia de la presa; %P Arancibia et al. (2015)

Curva de diversidad Trófica Gelsleichther et al. (1999)

W test Zar (1999)

Consumo alimento SCA

Alimentacion frecuente Elliot & Persson (1978)

Alimentacion intermitente Diana (1979)

Q y Q/B

SIA - CALORIMETRÍA 10

Lab. work - UNAB -

0.4-0.6 MG LOPEZ ET AL. (2013)

~10 MG; EX. LIPIDOS (C:M 2:1) HUSSEY ET AL (2010)

13C, 15N, %CN; STANDARD: PEE DEE BELEMITA 13C Y N ATMOSFERICO 15N

Analisis de datos

MixSIAR, MCMC Stock & Semmens et al. (2013)

A priori (SCA), α Klarian et al (unpublished)

TP, RInSP Araujo et al (2013)

Consumo alimento SIA

Balance enegertico, combinacion calorimetria - SIA Inger et al. (2006)

ANOVA

Agrupacion de presas Fry (2013)

RESULTADOSPRUEBAS; DIAGNOSTICOS Y LIPIDOS

11

LIPIDOS

δ13C

‰

-18

-16.75

-15.5

-14.25

-13

C:N

2 3 4 5

δ15N

‰

0

6

12

18

24

LH

0 20 40 60

y = 0.1721x + 9.5723R² = 0.2016

δ13C

‰

-18

-16.75

-15.5

-14.25

-13

LH0 20 40 60

y = 0.041x - 17.64R² = 0.0951

SCA INFO 100% MATCH

RESULTADOS SCA 12

PP. SCA

50.2% 49.8%

VaciosLlenos

RESULTADOS SCA -GENERAL-

DIETA GENERALÍtem P %PCefalopodaDosidicus gigas 13.47 0.33Gonatus sp. 1.13 0.03Graneledone sp. 0.22 0.01Histioteuthis sp. 0.24 0.01Ommastrephes bartramii 23.46 0.58Onykia sp 4.19 0.10Todarodes sp. 17.81 0.44Onychoteuthidae 0.26 0.01Oegopsida 0.33 0.01Indeterminado 148.89 3.68Restos 49.83 1.23Subtotal 259.83 6.42CrustaceaEuphausia mucronata 208.38 5.15Euphausia sp. 568.95 14.05Munida gregaria 34.92 0.86Sergestes arcticus 407.86 10.07Amphipoda 57.43 1.42Larva Decapoda 1.05 0.03Larva Stomatopoda 162.13 4.00Isopoda 0.09 0.00Restos 657.12 16.23Subtotal 2097.93 51.80PecesMaurolicus parvipinnis 152.27 3.76Sprattus fueguensis 7.18 0.18Strangomera bentincki 471.25 11.64Myctophidae 274.82 6.79Restos 786.56 19.42Subtotal 1692 42TOTAL 4050 100

CAT. MAYORES

%P

0

5.5

11

16.5

22

CAM CEF CLUPE EUF MESO STOMA

13

RESULTADOS SCA -TAMAÑOS- 14

CAM

CEF

CLUPE

EUF

MESO

STOMA

%P

0 8 16 24 32 40

Tamaño 1Tamaño 2

RESULTADOS SCA -ZONA-

CAM

CEF

CLUPE

EUF

MESO

STOMA

%P

0 8 16 24 32 40

TalcahuanoLebuChacabuco

15

RESULTADOS SCA -TIEMPO-

CAM

CEF

CLUPE

EUF

MESO

STOMA

%P

0 8 16 24 32 40

ENE-ABRMAY-AGO

16

RESULTADOS SIA -BIPLOT TAMAÑOS- 17δ1

5N‰

5

9.75

14.5

19.25

24

δ13C‰

-23 -20.25 -17.5 -14.75 -12

STOMA

MESO

EUF

CLUPE CEFCAM

Tamaño 1Tamaño 2CAMCEFCLUPEEUFMESOSTOMA

RESULTADOS SIA -BIPLOT ZONAS- 18δ1

5N‰

5

9.75

14.5

19.25

24

δ13C‰-18 -16.5 -15 -13.5 -12

CHBC LEBUTHNO

RESULTADOS SIA -BIPLOT TIEMPO- 19δ1

5N‰

5

9.75

14.5

19.25

24

δ13C‰

-18 -16.5 -15 -13.5 -12

ENE-ABRMAY-AGO RESUMEN

δ13C δ15N NTGeneral -15.89 ± 0.80 16.94 ± 2.33 3.9Período Enero-Abril -15.93 ± 0.56 16.91 ± 2.30 3.9

Mayo-Agosto -15.83 ± 0.89 16.98 ± 2.37 4.0Tamaño ≤39 cm -16.06 ± 1.03 15.88 ± 1.73 3.6

≥40 cm -15.76 ± 0.55 17.71 ± 2.40 4.2Localidad

de desembarque

Talcahuano -15.75 ± 0.58 17.57 ± 2.79 4.1Lebu -15.59 ± 0.43 18.69 ± 1.48 4.5

PuertoChacabuco .-15.96 ± 1.00 15.86 ± 1.70 3.6

RESULTADOS SIA % DIETARIA 20%

con

tribu

tion

0

25

50

75

100

GENERAL ENE-ABRIL MAY-AGO TM1 TM2 THN LEBU CHBC

18.7

36.8

47.2

55.761.942.169.8

56.3

CAM CEF CLUPE EUF MESO STOMA

RESULTADOS CONSUMO SCA

CONSUMOTotal CAM CEF CLUPE EUF MESO STOMA

TEG (gr/hora) 0.30 0.26 0.38 0.27 0.22 0.23 0.37Wprom contenido (gr) 2.91 12.75 0.53 52.40 6.80 4.06 0.16

Tasa incorporación (gr/hora) 172.02 157.72 363.93 360.88 39.20 39.99 154.14

RD1 E&P (gr día) 2094.33 1920.29 4430.80 4393.69 477.26 486.90 1876.68RD2 D. (gr día) 21.08 80.76 4.81 338.93 35.23 22.21 1.40

RD1/W 10.43 1.31 3.02 2.99 0.32 0.33 1.28

RD2/W 1 0.05 0.00 0.23 0.02 0.02 0.00

Q - Q/B

30 dias 120 dias

Biomasa (toneladas) 2.12

Q (toneladas) 3.50 13.99

Q/B (adimensional) 1.65 6.60

RESULTADOS CONSUMO SIA - CALORIMETRIA

‣ 4.41 ± 0.86 calories gr Kg. 100 gr 441 peso corporal

‣ Cdr= 0.62 gr inmaduros y 0.49 gr maduros; 2.73 cal, 2.16 cal para general biomass

‣ Consumo 11.98 gr dia; TGE 0.5 gr h, lo qui equivalio 0.82% peso corporal

22

DISCUSIONNúmero de estomagos due suficiente para estudiar la dieta de la reinetas

SCA - SIA concuerdan con los reportes previous

Existen diferencias ontogeneticas

δ13C y δ15N difieren con respect a otras especies de Reinetas, presentando un TP superior

El consume de reineta se ajusta a las de un predator de alimentacion frequente

Diferencias entre los metodos.

CONCLUSIONES‣ La reineta presenta una alimentación basada en eufausidos, peces y cefalópodos. Con clara

preferencia de eufausidos.

‣ Los individuos presentaron diferenciación en relación al tamaño corporal. Peces de menor tamaño se alimentan de eufausidos en comparación con aquellos de mayor tamaño que se alimentan de pequeños pelágicos. Sin embargo, estas diferencias pueden estar asociadas a cambios espaciales de las reinetas.

‣ Los valores de estabilidad isotópica posicionan a la reineta como una especie pelágica y que se alimenta en zonas costeras.

‣ La reineta presenta un patrón de consumo del tipo frecuente, con una tasa de evacuación gástrica de 0,3 g/hora, lo cual hace que estos consuman el 1% de su peso corporal.