Aquatic Ecology

, Volume 46, Issue 1, pp 55–71 | Cite as

Trophic and functional cascades in tropical versus temperate aquatic microcosms

Article

Abstract

Inverse trophic cascades are a well explored and common consequence of the local depletion or extinction of top predators in natural ecosystems. Despite a large body of research, the cascading effects of predator removal on ecosystem functions are not as well understood. Developing microcosm experiments, we explored food web changes in trophic structure and ecosystem functioning following biomass removal of top predators in representative temperate and tropical rock pool communities that contained similar assemblages of zooplankton and benthic invertebrates. We observed changes in species abundances following predator removal in both temperate and tropical communities, in line with expected inverse effects of a trophic cascade, where predation release benefits the predator’s preys and competitors and impacts the preys of the latter. We also observed several changes at the community and ecosystem levels including a decrease in total abundance and mean trophic level of the community, and changes in chlorophyll-a and total dissolved particles. Our results also showed an increase in variability of both community and ecosystem processes following the removal of predators. These results illustrate how predator removal can lead to inverse trophic cascades both in structural and functioning properties, and can increase variability of ecosystem processes. Although observed patterns were consistent between tropical and temperate communities following an inverse cascade pattern, changes were more pronounced in the temperate community. Therefore, aquatic food webs may have inherent traits that condition ecosystem responses to changes in top-down trophic control and render some aquatic ecosystems especially sensitive to the removals of top predators.

Keywords

Microcosms Food webs Rock pools Predator removal Trophic cascade Ecosystem functioning 

References

  1. Arner M (1997) Organisms and food webs in rock pools: responses to environmental stress and trophic manipulation. Zoologiska Institutionen—Stockholms Universitet, StockholmGoogle Scholar
  2. Bascompte J, Melian CJ, Sala E (2005) Interaction strength combinations and the overfishing of a marine food web. Proc Natl Acad Sci USA 102:5443–5447PubMedCrossRefGoogle Scholar
  3. Baum JK, Worm B (2009) Cascading top-down effects of changing oceanic predator abundances. J Anim Ecol 78:699–714PubMedCrossRefGoogle Scholar
  4. Borer ET, Seabloom EW, Shurin JB, Anderson KE, Blanchette CA, Broitman B, Cooper SD, Halpern BS (2005) What determines the strength of a trophic cascade? Ecology 86:528–537CrossRefGoogle Scholar
  5. Bruno JF, O’Connor MI (2005) Cascading effects of predator diversity and omnivory in a marine food web. Ecol Lett 8:1048–1056CrossRefGoogle Scholar
  6. Carpenter SR, Kitchell JF, Hodgson JR, Cochran PA, Elser JJ, Elser MM, Lodge DM, Kretchmer D, He X, Von Ende CN (1987) Regulation of lake primary productivity by food web structure. Ecology 68:1863–1876CrossRefGoogle Scholar
  7. Chapin III FS, Zavaleta ES, Eviner VT, Naylor RL, Vitousek PM, Reynolds HL, Hooper DU, Lavorel S, Sala OE, Hobbie SE (2000) Consequences of changing biodiversity. Nature 405:234–242Google Scholar
  8. Clarke K (1993) Non-parametric multivariate analyses of changes in community structure. Aust J Ecol 18:117–143CrossRefGoogle Scholar
  9. Clarke K, Warwick R (2001) Change in marine communities: an approach to statistical analysis and interpretation, 2nd edn. Primer-E Ltd, PlymouthGoogle Scholar
  10. Coll M, Lotze HK, Romanuk TN (2008) Structural degradation in Mediterranean Sea food webs: testing ecological hypotheses using stochastic and mass-balance modelling. Ecosystems 11:939–960CrossRefGoogle Scholar
  11. Coll M, Palomera I, Tudela S (2009) Decadal changes in a NW Mediterranean Sea food web in relation to fishing exploitation. Ecol Model 220:2088–2102CrossRefGoogle Scholar
  12. Cranford PJ, Hargrave BT (1994) In situ time-series measurements of ingestion and absorption rates of suspension-feeding bivalves: Placopecten magellanicus. Limnol Oceanogr 39:730–738CrossRefGoogle Scholar
  13. Duffy JE (2003) Biodiversity loss, trophic skew and ecosystem functioning. Ecol Lett 6:680–687CrossRefGoogle Scholar
  14. Duffy JE (2009) Why biodiversity is important to the functioning of real-world ecosystems. Front Ecol Environ 7:437–444CrossRefGoogle Scholar
  15. Duffy JE, Carinale BJ, France KE, McIntyre PB, Thebault E, Loreau M (2007) The functional role of biodiversity in ecosystems: incorporating trophic complexity. Ecol Lett 10:522–538PubMedCrossRefGoogle Scholar
  16. Elliott ET, Castanares LG, Perlmutter D, Porter KG (1983) Trophic-level control of production and nutrient dynamics in an experimental planktonic community. Oikos 41:7–16CrossRefGoogle Scholar
  17. Estes JA, Duggins DO (1995) Sea otters and kelp forests in Alaska: generality and variation in a community ecological paradigm. Ecol Monogr 65:75–100CrossRefGoogle Scholar
  18. Fagan WF (1997) Omnivory as a stabilizing feature of natural communities. Amer Nat 150:554–567CrossRefGoogle Scholar
  19. Frank KT, Petrie B, Choi JS, Leggett WC (2005) Trophic cascades in a formerly cod-dominated ecosystem. Science 308:1621PubMedCrossRefGoogle Scholar
  20. Frank KT, Petrie B, Shackell NL, Choi JS (2006) Reconciling differences in trophic control in mid-latitude marine ecosystems. Ecol Lett 9:1096–1105PubMedCrossRefGoogle Scholar
  21. Frank KT, Petrie B, Shackell NL (2007) The ups and downs of trophic control in continental shelf ecosystems. Trends Ecol Evol 22:236–242PubMedCrossRefGoogle Scholar
  22. Fretwell SD (1977) The regulation of plant communities by food chains exploiting them. Perspect Biol Med 20:169–185Google Scholar
  23. Gillooly JF (2000) Effect of body size and temperature on generation time in zooplankton. J Plankton Res 22:241CrossRefGoogle Scholar
  24. Griffin JN, Méndez V, Johnson AF, Jenkins SR, Foggo A (2009) Functional diversity predicts overyielding effect of species combination on primary productivity. Oikos 118:37–44CrossRefGoogle Scholar
  25. Gripenberg S, Roslin T (2007) Up or down in space? Uniting the bottom-up versus top-down paradigm and spatial ecology. Oikos 116:181–188CrossRefGoogle Scholar
  26. Hall CAS, Moll R (1975) Methods of assessing aquatic primary productivity. In: Lieth H, Whittaker RH (eds) Primary productivity of the biosphere. Spriger-Verlag, New York, NY, pp 19–53 Google Scholar
  27. Halpern BS, Borer ET, Seabloom EW, Shurin JB (2005) Predator effects on herbivore and plant stability. Ecol Lett 8:189–194CrossRefGoogle Scholar
  28. Halpern BS, Cottenie K, Broitman BR (2006) Strong top-down control in southern California kelp forest ecosystems. Science 312:1230–1232PubMedCrossRefGoogle Scholar
  29. Hooper DU, Chapin FS, Ewel JJ, Hector A, Inchausti P, Lavorel S, Lawton JH, Lodge DM, Loreau M, Naeem S, Schmid B, Setala H, Symstad AJ, Vandermeer J, Wardle DA (2005) Effects of biodiversity on ecosystem functioning: a consensus of current knowledge. Ecol Monogr 75:3–35CrossRefGoogle Scholar
  30. Jackson JBC, Kirby MX, Berger WH, Bjorndal KA, Botsford LW, Bourque BJ, Bradbury RH, Cooke R, Erlandson J, Estes JA, Hughes TP, Kidwell S, Lange CB, Lenihan HS, Pandolfi JM, Peterson CH, Steneck RS, Tegner MJ, Warner RR (2001) Historical overfishing and the recent collapse of coastal ecosystems. Science 293:629–638PubMedCrossRefGoogle Scholar
  31. Jennings S, Kaiser MJ (1998) The effects of fishing on marine ecosystems. Adv Mar Biol 34:268–352Google Scholar
  32. Knowlton N, Jackson JBC (2008) Shifting baselines, local impacts, and global change on coral reefs. PLoS Biol 6(2):e54Google Scholar
  33. Krebs CJ (2001) Ecology: the experimental analysis of distribution and abundance, 5th edn. Benjamin Cummings, New YorkGoogle Scholar
  34. Lande R, Engen S, Sæther BE (2003) Stochastic population dynamics in ecology and conservation. Oxford University Press, OxfordCrossRefGoogle Scholar
  35. Larkin PA (1979) Predator-prey relations in fishes: an overview of the theory. Sport Fishing Institute, WashingtonGoogle Scholar
  36. Michener LK, Kaufman L (2007) Stable isotope ratios as tracers in marine food webs: an update. In: Michener R, Lajtha K (eds) Stable isotopes and ecology in environmental science. Blackwell, Oxford, pp 238–282Google Scholar
  37. Mooney K, Halitschke R, Kessler A, Agrawal A (2010) Evolutionary trade-offs in plants mediate the strength of trophic cascades. Science 327:1642–1644PubMedCrossRefGoogle Scholar
  38. Myers RA, Baum JK, Shepherd TD, Powers SP, Peterson CH (2007) Cascading effects of the loss of apex predatory sharks from a Coastal Ocean. Science 315:1846–1850PubMedCrossRefGoogle Scholar
  39. Naeem S, Li S (1997) Biodiversity enhances ecosystem reliability. Nature 390:507–509CrossRefGoogle Scholar
  40. Pace LP, Cole JJ, Carpenter SR, Kitchell JF (1999) Trophic cascades revealed in diverse ecosystems. Trends Ecol Evol 14:483–488PubMedCrossRefGoogle Scholar
  41. Pimm SL, Russell GJ, Gittleman JL, Brooks TM (1995) The future of biodiversity. Science 269:347–350PubMedCrossRefGoogle Scholar
  42. Post DM (2002) Using stable isotopes to estimate trophic position: models, methods, and assumptions. Ecology 83:703–718CrossRefGoogle Scholar
  43. Power ME (1990) Effects of fish in river food webs. Science 250:811PubMedCrossRefGoogle Scholar
  44. Pringle CM, Hamazaki T (1998) The role of omnivory in a neotropical stream: separating diurnal and nocturnal effects. Ecology 79:269–280CrossRefGoogle Scholar
  45. Romanuk TN, Kolasa J (2002) Abundance and species richness in natural aquatic microcosms: a test and refinement of the Niche-limitation hypothesis. Community Ecol 3:87–94CrossRefGoogle Scholar
  46. Romanuk TN, Beisner BE, Martinez ND, Kolasa J (2006) Non-omnivorous generality promotes population stability. Biol Lett 2:374PubMedCrossRefGoogle Scholar
  47. Romanuk T, Vogt R, Young A, Tuck C, Carscallen M (2010) Maintenance of positive diversity-stability relations along a Gradient of environmental stress. PLoS ONE 5:e10378PubMedCrossRefGoogle Scholar
  48. Shurin JB, Borer ET, Seabloom EW, Anderson K, Blanchette CA, Broitman B, Cooper SD, Halpern BS (2002) A cross-ecosystem comparison of the strength of trophic cascades. Ecol Lett 5:785–791CrossRefGoogle Scholar
  49. Smith VH, Foster BL, Grover JP, Holt RD, Leibold MA, DeNoyelles F (2005) Phytoplankton species richness scales consistently from laboratory microcosms to the world’s oceans. Proc Natl Acad Sci USA 102:4393PubMedCrossRefGoogle Scholar
  50. Srivastava DS, Kolasa J, Bengtsson J, Gonzalez A, Lawler SP, Miller TE, Munguia P, Romanuk T, Schneider DC, Trzcinski MK (2004) Are natural microcosms useful model systems for ecology? Trends Ecol Evol 19:379–384PubMedCrossRefGoogle Scholar
  51. Strickland JDH, Parsons TR (1972) A practical handbook of seawater analysis. Bull J Fish Res Board Can 167:185–206Google Scholar
  52. Taylor BW, Flecker AS, Hall RO Jr (2006) Loss of a harvested fish species disrupts carbon flow in a diverse tropical river. Science 313:833PubMedCrossRefGoogle Scholar
  53. Underwood AJ (1997) Experiments in ecology. Their logical design and interpretation using analysis of variance. Cambridge University Press, CambridgeGoogle Scholar
  54. Wetzel R (1975) Linmology. W. B. Saunders Co, OrlandoGoogle Scholar
  55. Williamson CE (1983) Behavioral interactions between a cyclopoid copepod predator and its prey. J Plankton Res 5:701–711CrossRefGoogle Scholar
  56. Worsfold NT, Warren PH, Petchey OL (2009) Context-dependent effects of predator removal from experimental microcosm communities. Oikos 118:1319–1326CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.Institute of Marine Science (ICM-CSIC)BarcelonaSpain
  2. 2.Biology DepartmentDalhousie UniversityHalifaxCanada

Personalised recommendations