Estimating interaction strengths in nature: Experimental support for an observational approach

Ecology

Volumn 91, Issue 8, 2010, Pages 2394-2405

  Novak, Mark ^a,b  

^a UNIVERSITY OF CHICAGO   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Attack rates; Food webs; Functional response; Haustrum scobina; New Zealand intertidal; Parameter estimation; Per capita interaction strengths; Species interactions; Whelks; Xenostrobus pulex

Indexed keywords

BIVALVE; COMMUNITY STRUCTURE; EMPIRICAL ANALYSIS; EXPERIMENTAL STUDY; FOOD WEB; FUNCTIONAL RESPONSE; HYPOTHESIS TESTING; INTERTIDAL ENVIRONMENT; KEYSTONE SPECIES; NONLINEARITY; NUMERICAL MODEL; OBSERVATIONAL METHOD; PARAMETERIZATION; POPULATION DYNAMICS; POPULATION STRUCTURE; PREDATOR-PREY INTERACTION; SNAIL; TIME SERIES; TROPHIC INTERACTION; TROPHIC LEVEL;

ANIMAL; ARTICLE; BIOLOGICAL MODEL; FOOD CHAIN; GASTROPOD; PHYSIOLOGY; PREDATION; SEA;

ANIMALS; FOOD CHAIN; GASTROPODA; MODELS, BIOLOGICAL; OCEANS AND SEAS; PREDATORY BEHAVIOR;

NEW ZEALAND;

XENOSTROBUS PULEX;

EID: 77955447395     PISSN: 00129658     EISSN: None     Source Type: Journal    
DOI: 10.1890/09-0275.1     Document Type: Article

References (69)

1. Abrams, P. 1980. Are competition coefficients constant? Inductive versus deductive approaches. The American Naturalist 116:730-735.
2. Abrams, P. A. 2001. Describing and quantifying interspecific interactions: a commentary on recent approaches. Oikos 94:209-218.
3. Abrams, P. A., and L. R. Ginzburg. 2000. The nature of predation: prey dependent, ratio dependent or neither? Trends in Ecology and Evolution 15:337-341.
4. Agrawal, A. A., et al. 2007. Filling key gaps in population and community ecology. Frontiers in Ecology and the Environment 5:145-152.
5. Aschaffenburg, M. D. 2008. Different crab species influence feeding of the snail Nucella lapillus through trait-mediated indirect interactions. Marine Ecology 29:348-353.
6. Baird, D., and R. E. Ulanowicz. 1989. The seasonal dynamics of the Chesapeake Bay ecosystem. Ecological Monographs 59:329-364.
7. Bascompte, J., C. J. Melian, and E. Sala. 2005. Interaction strength combinations and the overfishing of a marine food web. Proceedings of the National Academy of Sciences USA 102:5443-5447.
8. Bender, E. A., T. J. Case, and M. E. Gilpin. 1984. Perturbation experiments in community ecology: theory and practice. Ecology 65:1-13.
9. Berlow, E. L., et al. 2004. Interaction strengths in food webs: issues and opportunities. Journal of Animal Ecology 73:585-598.
10. Boggs, C. H., J. A. Rice, J. A. Kitchell, and J. F. Kitchell. 1984. Predation at a snail's pace: What's time to a gastropod? Oecologia 62:13-17.
11. Bolker, B. 2007. Maximum likelihood estimation and analysis with the bbmle package. R package. Version 0.8.1. R Foundation for Statistical Computing, Vienna, Austria. Bolker, B. M. 2008. Ecological models and data in R. Princeton University Press, Princeton, New Jersey, USA.
12. Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. Second edition. Springer, New York, New York, USA.
13. Carpenter, S. R., K. L. Cottingham, and C. A. Stow. 1994. Fitting predator-prey models to time series with observation errors. Ecology 75:1254-1264.
14. Carriker, M. R. 1981. Shell penetration and feeding by Naticacean and Muricacean predatory gastropods: a synthesis. Malacologia 20:403-422.
15. Chesson, J. 1983. The estimation and analysis of preference and its relationship to foraging models. Ecology 64:1297-1304.
16. Connell, J. H., and W. P. Sousa. 1983. On the evidence needed to judge ecological stability or persistence. American Naturalist 121:789-824.
17. Duffy, J. E. 2002. Biodiversity and ecosystem function: the consumer connection. Oikos 99:201-219.
18. Efron, B., and R. J. Tibshirani. 1994. An introduction to the bootstrap. Chapman and Hall, New York, New York, USA.
19. Emmerson, M. C., and D. Raffaelli. 2004. Predator-prey body size, interaction strength and the stability of a real food web. Journal of Animal Ecology 73:399-409.
20. Fairweather, P. G. 1988. Movements of intertidal whelks (Morula marginalba and Thais orbita) in relation to availability of prey and shelter. Marine Biology 100:63-68.
21. Gascoigne, J. C., and R. N. Lipcius. 2004. Allee effects driven by predation. Journal of Applied Ecology 41:801-810.
22. Hall, R. O., J. B. Wallace, and S. L. Eggert. 2000. Organic matter flow in stream food webs with reduced detrital resource base. Ecology 81:3445-3463.
23. Hall, S. J., D. Raffaelli, and W. R. Turrell. 1990. Predatorcaging experiments in marine systems: a reexamination of their value. American Naturalist 136:657-672.
24. Hassell, M. P., J. H. Lawton, and J. R. Beddington. 1977. Sigmoid functional responses by invertebrate predators and parasitoids. Journal of Animal Ecology 46:249-262.
25. Holling, C. S. 1959. Some characteristics of simple types of predation and parasitism. Canadian Entomologist 91:385-398.
26. Jeschke, J. M., M. Kopp, and R. Tollrian. 2002. Predator functional responses: discriminating between handling and digesting prey. Ecological Monographs 72:95-112.
27. Jeschke, J. M., M. Kopp, and R. Tollrian. 2004. Consumerfood systems: why type I functional responses are exclusive to filter feeders. Biological Reviews 79:337-349.
28. Katz, C. H. 1985. A nonequilibrium marine predator-prey interaction. Ecology 66:1426-1438.
29. Largen, M. J. 1967. The influence of water temperature upon the life of the dog-whelk Thais lapillus (Gastropoda: Prosobranchia). Journal of Animal Ecology 36:207-214.
30. Laska, M. S., and J. T. Wootton. 1998. Theoretical concepts and empirical approaches to measuring interaction strength. Ecology 79:461-476.
31. Lipcius, R. N., and A. H. Hines. 1986. Variable functional responses of a marine predator in dissimilar homogeneous microhabitats. Ecology 67:1361-1371.
32. Luckens, P. A. 1975a. Competition and intertidal zonation of barnacles at Leigh, New Zealand. New Zealand Journal of Marine and Freshwater Research 9:379-394.
33. Luckens, P. A. 1975b. Predation and intertidal zonation of barnacles at Leigh, New Zealand. New Zealand Journal of Marine and Freshwater Research 9:355-378.
34. McCann, K. S. 2000. The diversity-stability debate. Nature 405:228-233.
35. Menge, B. A., B. A. Daley, J. Lubchenco, E. Sanford, E. Dahlhoff, P. M. Halpin, G. Hudson, and J. L. Burnaford. 1999. Top-down and bottom-up regulation of New Zealand rocky intertidal communities. Ecological Monographs 69:297-330.
36. Menge, B. A., et al. 2003. Coastal oceanography sets the pace of rocky intertidal community dynamics. Proceedings of the National Academy of Sciences USA 100:12229-12234.
37. Miller, L. P., and B. Gaylord. 2007. Barriers to flow: the effects of experimental cage structures on water velocities in highenergy subtidal and intertidal environments. Journal of Experimental Marine Biology and Ecology 344:215-228.
38. Moore, J. C., P. C. de Ruiter, and H. W. Hunt. 1993. Influence of productivity on the stability of real and model ecosystems. Science 261:906-908.
39. Moran, M. J. 1985. Effects of prey density, prey size and predator size on rates of feeding by an intertidal predatory gastropod Morula marginalba Blainville (Muricidae), on several species of prey. Journal of Experimental Marine Biology and Ecology 90:97-105.
40. Morton, J., and M. Miller. 1968. The New Zealand sea shore. Collins, Auckland, New Zealand.
41. Murdoch, W. W. 1969. Switching in general predators: experiments on predator specificity and stability of prey populations. Ecological Monographs 39:335-354.
42. Murdoch, W. W. 1973. Functional response of predators. Journal of Applied Ecology 10:335-342.
43. Murdoch, W. W., and A. Oaten. 1975. Predation and population stability. Advances in Ecological Research 9:1-130.
44. Navarrete, S. A., and J. C. Castilla. 2003. Experimental determination of predation intensity in an intertidal predator guild: dominant versus subordinate prey. Oikos 100:251-262.
45. Novak, M. 2008. Trophic omnivory and the structure, strength, and nonlinear nature of species interactions across a productivity gradient. Dissertation. University of Chicago, Chicago, Illinois, USA.
46. Novak, M., and J. T. Wootton. 2008. Estimating nonlinear interaction strengths: an observation-based method for species-rich food webs. Ecology 89:2083-2089.
47. Novak, M., and J. T. Wootton. In press. The use of experimental indices to estimate per capita interaction strengths. Oikos. [doi: 10.1111/j.1600-0706. 2009.18147.x]
48. Paine, R. T. 1992. Food-web analysis through field measurement of per capita interaction strength. Nature 355:73-75.
49. Peacor, S. D., and E. E. Werner. 2004. How independent are species-pair interaction strengths on other species in the food web? Ecology 85:2754-2763.
50. Pfister, C. A. 1995. Estimating competition coefficients from census data: a test with field manipulations of tidepool fishes. American Naturalist 146:271-291.
51. Pinheiro, J., and D. M. Bates. 2000. Mixed-effects models in S and S-PLUS. Springer, New York, New York, USA.
52. Pinheiro, J., D. Bates, S. DebRoy, D. Sarkar, and The R Core Team. 2009. nlme: linear and nonlinear mixed effects models. R package version 3.1-93. R Foundation for Statistical Computing, Vienna, Austria.
53. Power, M. E., D. Tilman, J. A. Estes, B. A. Menge, W. J. Bond, L. S. Mills, G. Daily, J. C. Castilla, J. Lubchenco, and R. T. Paine. 1996. Challenges in the quest for keystones. BioScience 46:609-620.
54. R Development Core Team. 2008. R: a language and environment for statistical computing, version 2.8.1. R Foundation for Statistical Computing, Vienna, Austria. Ruesink, J. L. 1998. Variation in per capita interaction strength: thresholds due to nonlinear dynamics and nonequilibrium conditions. Proceedings of the National Academy of Sciences USA 95:6843-6847.
55. Ruesink, J. L. 2000. Intertidal mesograzers in field microcosms: linking laboratory feeding rates to community dynamics. Journal of Experimental Marine Biology and Ecology 248:163-176.
56. Sala, E., and M. H. Graham. 2002. Community-wide distribution of predator-prey interaction strength in kelp forests. Proceedings of the National Academy of Sciences USA 99:3678-3683.
57. Sarnelle, O. 2003. Nonlinear effects of an aquatic consumer: causes and consequences. American Naturalist 161:478-496.
58. Schmitz, O. J. 1997. Press perturbations and the predictability of ecological interactions in a food web. Ecology 78:55-69.
59. Seitz, R. D., R. N. Lipcius, A. H. Hines, and D. B. Eggleston. 2001. Density-dependent predation, habitat variation, and the persistence of marine bivalve prey. Ecology 82:2435-2451.
60. Tschanz, B., L.-F. Bersier, and S. Bacher. 2007. Functional responses: a question of alternative prey and predator density. Ecology 88:1300-1308.
61. Ward, E. J. 2008. A review and comparison of four commonly used Bayesian and maximum likelihood model selection tools. Ecological Modelling 211:1-10.
62. West, L. 1986. Interindividual variation in prey selection by the snail Nucella (= Thais) emarginata. Ecology 67:798-809.
63. West, L. 1988. Prey selection by the tropical snail Thais melones: a study of interindividual variation. Ecology 69:1839-1854.
64. Woodward, G., D. C. Spiers, and A. G. Hildrew. 2005. Quantification and resolution of a complex, size-structured food web. Advances in Ecological Research 36:85-135.
65. Wootton, J. T. 1994. Predicting direct and indirect effects: an integrated approach using experiments and path analysis. Ecology 75:151-165.
66. Wootton, J. T. 1997. Estimates and tests of per capita interaction strength: Diet, abundance, and impact of intertidally foraging birds. Ecological Monographs 67:45-64.
67. Wootton, J. T., and M. Emmerson. 2005. Measurement of interaction strength in nature. Annual Review of Ecology, Evolution, and Systematics 36:419-444.
68. Yodzis, P. 1988. The indeterminacy of ecological interactions as perceived through perturbation experiments. Ecology 69:508-515.
69. Zuur, A. F., E. N. Ieno, N. J. Walker, A. A. Saveliev, and G. M. Smith. 2009. Mixed effects models and extensions in ecology with R. Springer, New York, New York, USA.