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
2,582
1,239 1,800 1,362
2,433 2,736 2,654 2,466 3,276
DESEMBARQUES 2015
INTRODUCCIÓN
TROFODINAMICA 3
MODELOS TRÓFICOS
Función Esctructura
dinámica predador-presa
MODELOS EBE
Multispecies virtual population analysis is an extension of single-species virtual population analysis (SSVPA) and esti- mates fishing mortality, recruitment, stock abundance, and predation mortality based on catch-at-age data and stomach content data. Therefore, MSVPA uses the same equations and backward algorithm as SSVPA (Gulland 1965). Abundance for the plus group and the final year of the assessment is calculated from Baranov’s catch equation,
Na;tþ ¼ Ca;tZa;t
Fterm;a;tð1 # e#Za;tÞ ; (1)
where Ca,t represents the annual catch at age; Za,t represents the total mortality at age (Za,t = Fterm,a,t + Ma,t); Fterm,a,t represents the terminal fishing mortality at age; Ma,t represents natural mortality (described in detail below); and Na;tþ represents the abundance of the plus group or the abundance of age-class a in the final year of the assessment (2007). The abundance of the remaining 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 from equation (1).
The MSVPA differs from SSVPA primarily by separating natural 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 the model; M1 is assumed to be constant for each age-class within each species. This separation hypothesis allows predation mor- tality to be estimated for each age-class through time. Predation mortality is calculated with the following equation (Sparre 1991),
M2;p;a ¼ X
i
X
j
N! i;jRi;jSp;a;i;j Bof Si;of þ P
p
P
a
N! p;aW! p;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;tþ1Zi;j;t#Ni;j;t"
; Rij is the annual ration (total annual food consumption, kg) for the predator species; Sp,a,i,j is the suitability coefficient for each predator–prey combination; Bof is the biomass of other prey (“other food”) available to the predator; Si,of is the suitability coefficient for the predator–other prey combination; !Np;a is the average abundance of prey p at age a; and !Wp;a is the average weight of the prey. For simplicity, the index t for time has been omitted from equation (3).
Suitability coefficients reflect the predator’s diet composi- tion relative to the available food (Sparre 1991). Estimation of suitability is based on stomach content data according to the following operational definition:
Sp;a;i;j ¼ Up;a;i;j= !Np;aWp;a P
p
P
a
Up;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 age of predator i. Predator/prey suitability values have also been defined as a weighting factor determining the availability of prey p as food for predator i (Gislason and Sparre 1987).
Solution of the previous equations (1–4) requires the use of three nested iterative algorithms (Sparre 1991). More details on MSVPA assumptions, equations, and algorithms are provided by Sparre (1991) and Magnusson (1995).
Due to its complexity, MSVPA requires several types of input data, 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 probably the most important data for estimating predation mortality M2 in the MSVPA. However, diet composition information is scarce for SCDF species; therefore, we considered a different approach for these fisheries based on the work of Ursin (1973). The approach uses parameters from the predator–prey size ratios to arrive 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#η
ð Þ2
2σ2
# $
; (5)
where Wi,j is the weight of predator i at age j; and Wp,a is the weight of prey p at age a. The constant η represents the mean log ratio between the predator weight and prey weight,
FIGURE 1. Predation interactions for the species system used in the multispecies virtual population analysis model defined for the southern Chilean demersal fishery.
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 δ
δ
PLASMA SANGRE
HIGADO
MUSCULO
HUESO
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(‰) δ15
N(‰)
HABITAT - ZONA DE ALIMENTACIÓN OCEANICO
PELAGICO
NERITICO BENTONICO NIGEL TRÓFICO
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
EUF
MESOP CEF
SARD
Garcia & Chong (2002) Santa Cruz et al (2014)
Horn et al (2013)
N. ZELANDA
5 4
91
MESOPCAM ZOO
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)
RESULTADOS
PRUEBAS; 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 + 9.5723 R² = 0.2016
δ13C‰
-18 -16.75 -15.5 -14.25 -13
LH
0 20 40 60
y = 0.041x - 17.64 R² = 0.0951
SCA INFO
100% MATCH
RESULTADOS SCA 12
PP. SCA
50.2% 49.8%
Vacios
Llenos
RESULTADOS SCA -GENERAL-
DIETA GENERAL
Ítem P %P
Cefalopoda
Dosidicus gigas 13.47 0.33
Gonatus sp. 1.13 0.03
Graneledone sp. 0.22 0.01
Histioteuthis sp. 0.24 0.01
Ommastrephes bartramii 23.46 0.58
Onykia sp 4.19 0.10
Todarodes sp. 17.81 0.44
Onychoteuthidae 0.26 0.01
Oegopsida 0.33 0.01
Indeterminado 148.89 3.68
Restos 49.83 1.23
Subtotal 259.83 6.42
Crustacea
Euphausia mucronata 208.38 5.15
Euphausia sp. 568.95 14.05
Munida gregaria 34.92 0.86
Sergestes arcticus 407.86 10.07
Amphipoda 57.43 1.42
Larva Decapoda 1.05 0.03
Larva Stomatopoda 162.13 4.00
Isopoda 0.09 0.00
Restos 657.12 16.23
Subtotal 2097.93 51.80
Peces
Maurolicus parvipinnis 152.27 3.76
Sprattus fueguensis 7.18 0.18
Strangomera bentincki 471.25 11.64
Myctophidae 274.82 6.79
Restos 786.56 19.42
Subtotal 1692 42
TOTAL 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 1
Tamaño 2
RESULTADOS SCA -ZONA-
CAM CEF CLUPE EUF MESO STOMA
%P
0 8 16 24 32 40
Talcahuano Lebu
Chacabuco
15
RESULTADOS SCA -TIEMPO-
CAM CEF CLUPE EUF MESO STOMA
%P
0 8 16 24 32 40
ENE-ABR MAY-AGO
16
RESULTADOS SIA -BIPLOT TAMAÑOS- 17
δ15N‰
5 9.75 14.5 19.25 24
δ13C‰
-23 -20.25 -17.5 -14.75 -12
STOMA MESO
EUF
CLUPE CEF
CAM
Tamaño 1 Tamaño 2 CAM
CEF
CLUPE EUF
MESO STOMA
RESULTADOS SIA -BIPLOT ZONAS- 18
δ15N‰
5 9.75 14.5 19.25 24
δ13C‰
-18 -16.5 -15 -13.5 -12
CHBC LEBU
THNO
RESULTADOS SIA -BIPLOT TIEMPO- 19
δ15N‰
5 9.75 14.5 19.25 24
δ13C‰
-18 -16.5 -15 -13.5 -12
ENE-ABR
MAY-AGO
RESUMEN
δ13C δ15N NT
General -15.89 ± 0.80 16.94 ± 2.33 3.9
Período Enero-Abril -15.93 ± 0.56 16.91 ± 2.30 3.9 Mayo-Agosto -15.83 ± 0.89 16.98 ± 2.37 4.0 Tamaño ≤39 cm -16.06 ± 1.03 15.88 ± 1.73 3.6
≥40 cm -15.76 ± 0.55 17.71 ± 2.40 4.2 Localidad
de
desembarque
Talcahuano -15.75 ± 0.58 17.57 ± 2.79 4.1 Lebu -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
% contribution
0 25 50 75 100
GENERAL ENE-ABRIL MAY-AGO TM1 TM2 THN LEBU CHBC
18.7 36.8
47.2 61.9 55.7
42.1 56.3 69.8
CAM CEF CLUPE EUF MESO STOMA
RESULTADOS CONSUMO SCA
CONSUMO
Total CAM CEF CLUPE EUF MESO STOMA
TEG (gr/hora) 0.30 0.26 0.38 0.27 0.22 0.23 0.37
Wprom 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 1876.68
RD2 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
DISCUSION
Número 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.