Developing  Small  Pelagic  Fish  DEB    (Dynamic  Energy  Budget)  modules  for  IBMs    

in  spa?al  popula?on  dynamics  studies    

Why?  How?  Issues/Challenges?  

Laure  Pecquerie  

W5  -­‐  Victoria  –  11  March  2017  

Take-­‐home  messages  

•  Current  situa+on:  not  sufficient  data  types  to  es?mate  primary  parameters  of  a  DEB  model  for  small  pelagic  fish.  Several  datasets  provide  similar  fits  

•  Taking  into  account  phylogeny  in  DEB  parameter  es?ma?on  for  small  pelagic  fish  will  reduce  uncertainty  in  parameter  es?mates.  Mul+-­‐species  es+ma+on  procedure  under  development    –  We  can  only  tackle  this  problem  as  a  community  (mul?-­‐species,  mul?-­‐popula?on  approach)  

•  More  data  types  by  designing  experimental  protocols  together  –  We  can  only  tackle  this  problem  as  a  community  (experimenters,  fielders  and  DEB  modellers  )  

•  Otoliths  are  key  to  improve  and  validate  IBMs  (…un?l  we  find  a  way  to  tag  these  fish)  à  Otolith  data  <-­‐>  Otolith  model  in  IBMs  

Take-­‐home  messages  

•  Current  situa+on:  not  sufficient  data  types  to  es?mate  primary  parameters  of  a  DEB  model  for  small  pelagic  fish.  Several  datasets  provide  similar  fits  

•  Taking  into  account  phylogeny  in  DEB  parameter  es?ma?on  for  small  pelagic  fish  will  reduce  uncertainty  in  parameter  es?mates.  Mul+-­‐species  es+ma+on  procedure  under  development    –  We  can  only  tackle  this  problem  as  a  community  (mul?-­‐species,  mul?-­‐popula?on  approach)  

•  More  data  types  by  designing  experimental  protocols  together  –  We  can  only  tackle  this  problem  as  a  community  (experimenters,  fielders  and  DEB  modellers  )  

•  Otoliths  are  key  to  improve  and  validate  IBMs  (…un?l  we  find  a  way  to  tag  these  fish)  à  Otolith  data  <-­‐>  Otolith  model  in  IBMs  

Take-­‐home  messages  

•  Current  situa+on:  not  sufficient  data  types  to  es?mate  primary  parameters  of  a  DEB  model  for  small  pelagic  fish.  Several  datasets  provide  similar  fits  

•  Taking  into  account  phylogeny  in  DEB  parameter  es?ma?on  for  small  pelagic  fish  will  reduce  uncertainty  in  parameter  es?mates.  Mul+-­‐species  es+ma+on  procedure  under  development    –  We  can  only  tackle  this  problem  as  a  community  (mul?-­‐species,  mul?-­‐popula?on  approach)  

•  More  data  types  by  designing  experimental  protocols  together  –  We  can  only  tackle  this  problem  as  a  community  (experimenters  and  DEB  modellers  )  

•  Otoliths  are  key  to  improve  and  validate  IBMs  (…un?l  we  find  a  way  to  tag  these  fish)  à  Otolith  data  <-­‐>  Otolith  model  in  IBMs  

Take-­‐home  messages  

•  Current  situa+on:  not  sufficient  data  types  to  es?mate  primary  parameters  of  a  DEB  model  for  small  pelagic  fish.  Several  datasets  provide  similar  fits  

•  Taking  into  account  phylogeny  in  DEB  parameter  es?ma?on  for  small  pelagic  fish  will  reduce  uncertainty  in  parameter  es?mates.  Mul+-­‐species  es+ma+on  procedure  under  development    –  We  can  only  tackle  this  problem  as  a  community  (mul?-­‐species,  mul?-­‐popula?on  approach)  

•  More  data  types  by  designing  experimental  protocols  together  –  We  can  only  tackle  this  problem  as  a  community  (experimenters,  fielders  and  DEB  modellers  )  

•  Otoliths  are  key  to  improve  and  validate  IBMs  (…un?l  we  find  a  way  to  tag  these  fish)  à  Otolith  data  <-­‐>  Otolith  model  in  IBMs  

Why  using  DEB  models  in  IBMs    

•  Full  life  cycle  model,  no  discon?nuity,  (probably)  less  parameters    

•  Growth,  Reproduc?on  AND  Development  as  a  func?on  of  food  and  temperature  condi?ons    

•  +  other  forcing  func?ons  and  tracers:  contaminant,  parasites,  δ15N,  O2,  …  

•  Individual  parameters  -­‐>  mul?-­‐genera?on  simula?ons,    selec?on,  eco-­‐evo  processes  

Issues  /  Challenges?  

We  won’t  be  able  to  include  all  the  processes  we  believe  are  at  play  

•  Model  structure  depends  on  the  research  ques+on  Ecotoxicology,  Aquaculture,  Ecology  ques?ons  may  lead  to  different  models  within  the  same  framework  

 à  Spa?al  popula?on  dynamics  –  bioenerge?c  module  for  IBM  module  –  we  need  

the  simplest  model  possible      Do  we  need  :  •  Spawning  dates  according  to  environmental  condi?ons  (seasonal  /  interannual  

variability)  ?  •  Age  at  which  swim  bladder  is  func?oning?  (ver?cal  migra?on)  •  Diges?on  processes  or  constant  assimila?on  efficiency?    Spa+al  /  +me  scales  of  these  processes    vs    Spa+al  grid  /    +me  step  of  hydro-­‐biogeochemical  models  

A  bit  of  history  

•  Bas  Kooijman,  in  1979  •  Two  ques?ons  :  

– How  can  we  quan?fy  the  effect  of  toxic  compounds  on  Daphnia  reproduc?on?  

– Which  effect  has  a  small  decrease    in  individual  reproduc?on    on  the  dynamics  of  the  popula?on?  

…

Observa?ons  :  Asympto?c  growth  

Kooijman,  2010  

maturity

1-κ maturity

maintenance

development

food faeces assimilation

reserve

structure

somatic maintenance

growth

κ

Life  events  in  a  standard  DEB  model  

reproduction buffer

reproduction

maturity

1-κmaturity

maintenance

development

food faecesassimilation

reserve

structurestructure

somaticmaintenance

growth

κ

reproductionbuffer

reproduction

maturity

1-κmaturity

maintenance

development

maturitymaturity

1-κmaturity

maintenance

development

1-κmaturity

maintenance

development

food faecesassimilation

food faecesassimilation

reserve

structurestructure

somaticmaintenance

growth

κ

reproductionbuffer

reproduction

reproductionbuffer

reproduction

Model  simula?ons  

INPUTS DEB MODEL

Food density

Temperature

Flow

Weight

Fecundity / egg size

OUTPUTS

Length

•  Oxygen  consump?on  –  Empirical  à    R  =  aLb    

Theore?cal    à  R  =  aL2  +  bL3            (Kooijman,  2000)  

Modelling  approach  

Daphnia pulex d’après Kooijman (2000)

R  =  aLb  =  0.0516  L2.437    R  =  aL2  +  bL3          =  0.0336  L2  +  0.01845  L3  

Issues  /  Challenges?  

•  State  variables  do  not  correspond  to  observables/data  

•  DEB  and  tradi?onal  bioenerge?c  models  have  different  emphases  /  processes,  thus  different  data  needs  for  calibra?on    (but  ways  to  link  them)  

•  Specific  to  SPF:  we  hardly  observe  feeding  and  full  reproduc?on  investment  (batch  spawner  /  vitellogenesis  de  novo)  

 à  Several  parameter  sets  provide  similar  fits  

Issues  /  Challenges?  

•  State  variables  do  not  correspond  to  observables/data  

•  DEB  and  tradi?onal  bioenerge?c  models  have  different  emphases  /  processes,  thus  different  data  needs  for  calibra?on    (but  ways  to  link  them)  

•  Specific  to  SPF:  we  hardly  observe  feeding  and  full  reproduc?on  investment  (batch  spawner  /  vitellogenesis  de  novo)  

 à  Several  parameter  sets  provide  similar  fits  

1-κmaturity

maintenance

maturityoffspring

maturationreproduction

food faecesassimilation

reserve

structurestructure

somaticmaintenance

growth

κ 1-κmaturity

maintenance

maturityoffspring

maturationreproduction

1-κmaturity

maintenance

maturityoffspring

maturationreproduction

1-κmaturity

maintenance

maturityoffspring

maturationreproduction

food faecesassimilation

reserve

food faecesassimilation

reserve

structurestructure

somaticmaintenance

growth

κ

structurestructure

somaticmaintenance

growth

κ

FOOD  ?  

?  

metabolic  products  in  DEB  models  

Reserve

Structure

κ κ−1

Assimilation pA

Growth pG

Somaticmaintenance pM

Maturitymaintenance pJ

Reproduction pR

Food

pC

Reproductionbuffer

Assimilation Products

Dissipation Products

Growth Products

pDpA

pA

Faeces

CO2

pD pG

pG

(b)

(c)

(d)

(a)

Reserve

Structure

κ κ−1

Assimilation pA

Growth pG

Somaticmaintenance pM

Maturitymaintenance pJ

Reproduction pR

Food

pC

Reproductionbuffer

Assimilation Products

Dissipation Products

Growth Products

pDpA

pA

Faeces

CO2

pD pG

pG

(b)

(c)

(d)

(a)

Biocarbonate  =  metabolic  product  

Reserve

Structure

κ κ−1

Assimilation pA

Growth pG

Somaticmaintenance pM

Maturitymaintenance pJ

Reproduction pR

Food

pC

Reproductionbuffer

Assimilation Products

Dissipation Products

Growth Products

pDpA

pA

Faeces

CO2

pD pG

pG

(b)

(c)

(d)

(a)

Reserve

Structure

κ κ−1

Assimilation pA

Growth pG

Somaticmaintenance pM

Maturitymaintenance pJ

Reproduction pR

Food

pC

Reproductionbuffer

Assimilation Products

Dissipation Products

Growth Products

pDpA

pA

Faeces

CO2

pD pG

pG

(b)

(c)

(d)

(a)

How  to  go  beyond?    

•  Taking  into  account  phylogeny  in  DEB  parameter  es?ma?on  for  small  pelagic  fish  will  reduce  uncertainty  in  parameter  es?mates.    

•  Mul+-­‐spcies  es+ma+on  procedure  under  development    

Standard  DEB  model  Engraulis  encrasicolus  

DEB  model  Bay  of  Biscay  

Assump?ons  

Parameter  values  Ini?al  condi?ons  

Environmental  condi?ons  

Fish  Data  

Classical  approach  

New  approach  

Standard  DEB  model  

Small  pelagic  Fish  DEB  model  

Engraulidae    DEB  model  

Phylogen

y  

Engraulis  encrasicolus  DEB  model  

Bay  of  Biscay   Gulf  of  Lion   Benguela  

Assump?ons   Parameter  values  

Environmental  condi?ons  

Clupeidae    DEB  model  

Sardina  pilchardus  DEB  model  

Bay  of  Biscay   Gulf  of  Lion  

Sardinops  sagax    DEB  model  

Benguela  

Amp  Collec?on  :  currently  600  entries  

hjp://www.bio.vu.nl/thb/deb/deblab/add_my_pet/species_list.html  

Small  pelagic  fish  entries  :  6  

Atlan?c  herring  entry  

Atlan?c  herring  entry  

How  to  go  beyond?    

•  Taking  into  account  phylogeny  in  DEB  parameter  es?ma?on  for  small  pelagic  fish  will  reduce  uncertainty  in  parameter  es?mates.    

•  Mul+-­‐spcies  es+ma+on  procedure  under  development    

•  Modelling  otolith  growth,  opacity,  δ18O,  δ13C  in  IBMs  

Why  modelling  otolith  forma+on?  

Biocarbonates  

DEB  model  Habitat  

Temperature   Growth  

A)  Calibra+on  of  proxies  

Understand  

B)  Life  history  reconstruc+on  

Improve  

C)  Environmental  scenario  studies    (2D,  3D  models)  

Predict  

 (Phil.  Trans.  Roy.  Soc.  2010    PLoS  ONE  2011,  MEPS  2012)  

VIRTUAL  LAB  

Time  

δ13 C,  δ

18O    

Food  (Quan+ty,  δ13C,…)    

δ13C  DIC  δ18O  w  

Reproduc+on  

Metabolism  

è  To  embrace  and  take  advantage  of  these  mul+-­‐factor  interac+ons  to  improve    our  interpreta+on  and  use  of  these  unique  archives  

Otolith  modeling  :  individual  history  

Environment  

Otolith  growth  and  opacity  

Length  DEB  model    

(Pecquerie  et  al.  2012)