Beyond taxonomy: A traits-based approach to fish community ecology

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Presented by Julian D. Olden at the XX Brazilian Meeting of Ichthyology (2013)

Presented by Julian D. Olden at the XX Brazilian Meeting of Ichthyology (2013)

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  • 1. Beyond  taxonomy:  A  traits-­‐based  approach  to  fish  community  ecology      Julian  D.  Olden  School  of  Aqua,c  and  Fishery  Sciences  University  of  Washington  olden@uw.edu  
  • 2. Big  Fish  Eat  Li,le  Fish  by  Pieter  Brueghel  the  Elder  (1557)  
  • 3. Threats  to  Freshwater  Fishes  Habitat loss PollutionFragmentation Climate changeInvasive speciesDisease
  • 4. Why  Trait-­‐based  Ecology?  •  Enhances  our  mechanis,c  understanding  of  ecological  paHern  and  process  •  Provides  greater  opportunity  for  generaliza,on  •  Links  biodiversity  and  ecosystem  func,on      
  • 5. Traits  in  Fish  Community  Ecology  •  The  study  of  fish  traits  can  be  used  to  understand  complex  phenomena,  including  why  organisms  live  where  they  do,  how  many  species  can  coexist  in  a  given  place,  and  how  they  will  respond  to  environmental  change  0  20  40  60  80  100  120  1991   1994   1997   2000   2003   2006   2009   2012  #  publicaFons  ISI  Web  of  Science  search  on  Jan  20,  2013  using  the  query  “fish  AND  trait*  AND  (community  OR  assemblage)”  
  • 6. Research  PrioriFes  “In  an  ideal  world,  an  understanding  of  how  fish  assemblages  change  in  response  to  natural  changes  along  different  ,me  scales  would  be  necessary  …      This  is  no  longer  always  possible,  however,  since  most  aqua,c  environments  are  already  subject  to  some  form  of  human  interven,on  …    Therefore,  it  is  necessary  to  deal  with  mixed  signals,  and  part  of  the  challenge  lies  in  numerically  dis,nguishing  these  signals,  as  well  as  pucng  them  in  perspec,ve.”  
  • 7. Today’s  PresentaFon  1.  Do  species  traits  provide  predic,ve  insight  into  those  fish  species  at  greatest  risk  to  ex,nc,on?    2.  Does  a  traits-­‐based  approach  represent  a  unifying  framework  for  an,cipa,ng  how  fish  species  and  communi,es  will  response  to  environmental  change?  Biodiversity  and    Ecosystem  Func,oning  Ex,nc,on   Invasion  
  • 8. 1.  ExFncFon  Risk  of  Fishes  •  Conserva,on  biology  is  faced  with  a  growing  urgency  to  iden,fy  and  protect  species  facing  the  greatest  risk  of  ex,nc,on  (Pimm  and  Jenkins  2005)  •  This  is  a  challenging  task  because  direct  es,mates  of  ex,nc,on  risk  for  most  species  are  lacking  (O’Grady  et  al.  2004)  •  Ecological  traits  can  help  iden,fy  species  that  are  vulnerable  to  ex,nc,on  
  • 9. Body  Size  and  Global  ExFncFon  Risk    •  Body  size  is  a  fundamental  ecological  parameter  correlated  with  many  other  life-­‐history  characteris,cs  •  Ecological  theory  and  global-­‐scale  analyses  of  bird  and  mammal  faunas  suggest  that  small-­‐bodied  species  are  less  vulnerable  to  ex,nc,on  •  We  compared  body-­‐size  distribu,ons  of  22,800  freshwater  and  marine  fishes  under  different  levels  of  global  ex,nc,on  risk  
  • 10. YES.  Dip  sta,s,c  =  0.12,  d.f.  =  14,  P  =  0.042    NO.  Dip  sta,s,c  =  0.07,  d.f.  =  16,  P  =  0.889    Olden,  J.D.,  Hogan,  Z.S.,  and  M.J.  Vander  Zanden.  2007.  Small  fish,  big  fish,  red  fish,  blue  fish:  size-­‐biased  ex,nc,on  risk  of  the  world’s  freshwater  and  marine  fishes.  Global  Ecology  and  Biogeography  16:694-­‐701.  Is  the  distribu,on  significantly  bi-­‐modal?  
  • 11. ImplicaFons  •  Given  limited  resources  for  conduc,ng  detailed  species  assessments,  iden,fying  trait-­‐based  indicators  of  ex,nc,on  risk  could  be  extremely  valuable  for  conserva,on  ranking  schemes  •  Traits  may  provide  insight  into  the  ecosystem  implica,ons  of  species  losses  (and  invasions)  Castello  et  al.,  in  press.  The  vulnerability  of  Amazon  freshwater  ecosystems.  Conserva;on  Le,ers.      
  • 12. 2.  Life-­‐histories  and  the  habitat  templet  Trade-­‐offs  among  energeFc  investments  in  growth,  reproducFon,  and  survivorship  have  resulted  in  the  evoluFon  of  life  history  strategies  that  enable  an  organism  to  cope  with  ecological  challenges  Southwood  (1988)  
  • 13. Fish  Life-­‐history  Theory  •  Life  history  theory  has  sparked  new  perspec,ves  in  understanding  the  paHerns  and  drivers  of  freshwater  biodiversity    Olden  &  Kennard  (2010)  •  Life-­‐history  strategies  have  evolved  from  trade-­‐offs  among  traits  that  have  direct  consequences  for  fitness  in  different  environments                    (Winemiller  and                                            Rose  1992)    Fecundity  
  • 14. Fish  Life-­‐history  Theory  Fecundity  OPPORTUNISTIC  •   small  •   rapidly  matura,on  •   low  fecundity  •   unpredictable  env.  PERIODIC  •   large  •   late  matura,on  •   high  fecundity  •   seasonal  env.  EQUILIBRIUM  •   medium  •   low  fecundity  •   ↑parental  care  •   constant  env.  
  • 15. OpportunisFc  Periodic  Equilibrium  Life-­‐histories  of  North  American  fishes  Mims,  M.C.,  Olden,  J.D.,  ShaHuck,  Z.R.,  and  N.L.  Poff.  2010.  Life  history  trait  diversity  of  na,ve  freshwater  fishes  in  North  America.  Ecology  of  Freshwater  Fish  19:390-­‐400.  
  • 16. •  It  is  hypothesized  that  a  species’  life  history  strategy  dictates,  in  large  part,  its  response  to  environmental  factors  describing  the  variability,  predictability,  and  seasonality  of  favorable  habitat  condi,ons  Modified  from  Bunn  and  Arthington  (2002,  Env.  Man.)  
  • 17. •  Hydrological  variability  plays  a  dominant  role  in  shaping  physical  processes  in  riverine  ecosystems,  and  a  number  of  recent  studies  have  supported  the  associa,on  between  hydrology  and  fish  life  history  strategies  
  • 18. ObjecFve  Test  life  history  theory  by  quan,fying  rela,onships  between  variability,  predictability,  and  seasonality  of  natural  flow  regimes  and  the  life  history  composi,on  of  na,ve  fish  assemblages  throughout  the  con,nental  United  States.    
  • 19. Meryl  Mims  
  • 20. Approach  >15  years  con,nuous  gage  data  prior  to  fish  survey?  Gage-­‐survey  pair  within  10  river  km?    Any  tributaries  between  the  pair?  YES  YES  NO   Acceptable  pair  (n=109)  Flow  Gages  Fish  Surveys  
  • 21. Approach  •  Assign  each  fish  species  to  a  life  history  strategy  and  calculate  rela,ve  strategy    richness  for  each  site  •  Calculate  hydrologic  metrics  that  summarize  the  major  components  of  the  flow  regime    Predictability  Variability  Seasonality  
  • 22. PredicFons  from  Life  History  Theory  Flow  dimension   Hydrologic  metric  Predicted  relaFonship  with  proporFonal  LH  (slope  direcFon)       OpportunisFc   Periodic   Equilibrium  VARIABILITY   Annual  Coef.  Varia,on   +   -­‐   -­‐  High  Pulse  Count   +   -­‐   -­‐  PREDICTABILITY   Base  Flow  Index   -­‐   0   +  Flow  Predictability   -­‐   +   +  SEASONALITY   Constancy/Predictability   0   -­‐   +  High  Pulse  Dura,on   -­‐   +   0  Used  quan,le  regression  to  test  for  rela,onships  between  LHs  and  hydrologic  metrics  
  • 23. •  The  majority  (two-­‐thirds)  of  rela,onships  were  sta,s,cally  significant  (P<0.05)  for  at  least  one  quan,le  •  82%  of  significant  rela,onships  supported  predic,ons  from  life  history  theory  Opp   Per   Equ  Mims,  M.C.,  and  J.D.  Olden.  2012.  Life  history  theory  predicts  streamflow  effects  on  fish  assemblage  response  to  hydrologic  regimes.  Ecology  93:35-­‐45.  
  • 24. •  The  majority  (two-­‐thirds)  of  rela,onships  were  sta,s,cally  significant  (P<0.05)  for  at  least  one  quan,le  •  82%  of  significant  rela,onships  supported  predic,ons  from  life  history  theory  Opp   Per   Equ  Mims,  M.C.,  and  J.D.  Olden.  2012.  Life  history  theory  predicts  streamflow  effects  on  fish  assemblage  response  to  hydrologic  regimes.  Ecology  93:35-­‐45.  Flow  Variability  
  • 25. •  The  majority  (two-­‐thirds)  of  rela,onships  were  sta,s,cally  significant  (P<0.05)  for  at  least  one  quan,le  •  82%  of  significant  rela,onships  supported  predic,ons  from  life  history  theory  Mims,  M.C.,  and  J.D.  Olden.  2012.  Life  history  theory  predicts  streamflow  effects  on  fish  assemblage  response  to  hydrologic  regimes.  Ecology  93:35-­‐45.  Flow  Seasonality  
  • 26. Flow  dimension   Hydrologic  metric  Predicted  relaFonship  with  proporFonal  LH  (slope  direcFon)       OpportunisFc   Periodic   Equilibrium  VARIABILITY   Annual  Coef.  Varia,on   +   -­‐   -­‐  High  Pulse  Count   +   -­‐   -­‐  PREDICTABILITY   Base  Flow  Index   -­‐   0   +  Flow  Predictability   -­‐   +   +  SEASONALITY   Constancy/Predictability   0   -­‐   +  High  Pulse  Dura,on   -­‐   +   0  =  Supported  by  theory  =  Inconclusive  =  Not  support  by  theory  Life  history  theory  predicts  fish  assemblage  response  to  hydrologic  regimes  
  • 27. ImplicaFons  •  The  flow  regime  as  a  key  determinant  of  fish  life  history  composi,on  across  a  broad  biogeographical  scale  •  A  traits-­‐based  approach  is  useful  because  it  facilitates  the  transfer  of  scien,fic  knowledge  between  regions  that  naturally  differ  due  to  zoogeography,  but  in  which  life  history  strategies  and  trait  adapta,ons  are  hypothesized  to  converge  across  diverse  taxonomies  •  These  findings  have  implica,ons  for  predic,ng  the  consequences  of  flow  altera,on  and  for  informing  flow-­‐management  recommenda,ons  
  • 28. •  Fish  life-­‐history  strategies  are  predic,ve  of  how  fish  assemblages  response  to  damming  and  altered  flow  regimes  Mims,  M.C.,  and  J.D.  Olden.  2013.  Fish  assemblages  respond  to  altered  flow  regimes  via  ecological  filtering  of  life  history  strategies.  Freshwater  Biology  58:50-­‐62.  
  • 29. Key  Challenges  Does  a  trait-­‐based  approach  provide  new  insight  into  paHerns  and  processes  of  fish  biogeography,  and  if  so,  can  this  informa,on  inform  conserva,on  strategies?    What  traits  predispose  fish  species  to  ex,nc,on  vs.  invasion?  Given  the  lack  of  trait  data  for  many  fish  species  in  par,cular  regions,  which  subset  of  traits  are  most  appropriate  for  defining  func,onal  diversity  and  offer  the  most  promise  for  predic,ng  responses  to  environmental  change?    What  are  the  ecosystem  consequences  of  changes  in  fish  func,onal  composi,on?  
  • 30. PredicFng  ExFncFon  Risk  “More  appropriate  biological  knowledge  is  s;ll  required  to  improve  species  assignment  to  the  IUCN  Red  List  categories  at  the  regional  level”  Transferring  Knowledge  “One  of  the  major  problems  facing  fish  conserva;on  in  South  America  is  the  lack  of  basin-­‐wide  approaches.  Usually,  both  knowledge  and  interest  are  limited  to  the  local  …”  
  • 31. Julian  D.  Olden  University  of  Washington  olden@uw.edu  Special  thanks  to  Meryl  Mims!