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Beyond taxonomy: A traits-based approach to fish community ecology
This document discusses using traits-based approaches to understand fish community ecology. It begins by outlining threats to freshwater fishes like habitat loss and pollution. The author argues that traits-based ecology enhances understanding of ecological patterns and processes, provides opportunities for generalization, and links biodiversity and ecosystem function. Research on fish traits can explain where species live, how many coexist in an area, and how they respond to environmental change. The author presents on using traits to predict extinction risk of fishes and anticipate how communities will respond to environmental change. Body size correlates with extinction risk, with smaller-bodied fishes less vulnerable. Life histories have evolved trade-offs that enable coping with ecological challenges. Traits may indicate ecosystem implications
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Beyond taxonomy: A traits-based approach to fish community ecology
- 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 Pollution Fragmentation Climate change Invasive species Disease
- 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.
- 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
- 23. 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
- 24. 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
- 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 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.
- 26. • 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
- 27. • 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
- 28. 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
- 29. 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
- 30. • 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.
- 31. 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?
- 32. 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 …”
- 33. Julian D. Olden University of Washington olden@uw.edu Special thanks to Meryl Mims!