Host Suppression and Stability in a Parasitoid-Host System: Experimental Demonstration William Murdoch, et al. Science 309, 610 (2005); DOI: 10.1126/science.1114426 The following resources related to this article are available online at www.sciencemag.org (this information is current as of April 2, 2009 ): Updated information and services, including high-resolution figures, can be found in the online version of this article at: http://www.sciencemag.org/cgi/content/full/309/5734/610 Supporting Online Material can be found at: http://www.sciencemag.org/cgi/content/full/309/5734/610/DC1 This article cites 11 articles, 1 of which can be accessed for free: http://www.sciencemag.org/cgi/content/full/309/5734/610#otherarticles
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REPORTS 24. T. M. Shenk, G. C. White, K. P. Burnham, Ecol. Monogr. 68, 445 (1998). 25. To identify the effects of measurement error on q estimation, we carried out computer simulations of time series governed by Eq. 1 but subject to lognormal environmental perturbations and with measurement errors also being log-normally distributed. Preliminary results suggested that over the range of parameters of interest, q can be recovered without appreciable bias, provided that measurement error is less than half of environmental variation, and that useful information is still obtainable when measurement error and environmental variation are equal. 26. J. Halley, P. Inchausti, Oikos 99, 518 (2002). 27. A. R. E. Sinclair, in Ecological Concepts, J. M. Cherrett, Ed. (Blackwell Scientific, Oxford, 1989), pp. 197–241. 28. A. R. E. Sinclair, in Frontiers of Population Ecology, R. B. Floyd, A. W. Sheppard, P. J. De Barro, Eds. (CSIRO, Melbourne, 1996), pp. 127–154. 29. A. R. E. Sinclair, C. J. Krebs, Philos. Trans. R. Soc. London Ser. B 357, 1221 (2002). 30. R. Lande, S. Engen, B.-E. Saether, Stochastic Popula-
Host Suppression and Stability in a Parasitoid-Host System: Experimental Demonstration William Murdoch,1* Cheryl J. Briggs,2 Susan Swarbrick1 We elucidate the mechanisms causing stability and severe resource suppression in a consumer-resource system. The consumer, the parasitoid Aphytis, rapidly controlled an experimentally induced outbreak of the resource, California red scale, an agricultural pest, and imposed a low, stable pest equilibrium. The results are well predicted by a mechanistic, independently parameterized model. The key mechanisms are widespread in nature: an invulnerable adult stage in the resource population and rapid consumer development. Stability in this biologically nondiverse agricultural system is a property of the local interaction between these two species, not of spatial processes or of the larger ecological community. Although some consumer-resource (e.g., predator-prey) populations famously cycle in abundance, most appear to be stable, even when the predator strongly suppresses prey abundance (1). Yet, any theory that includes only a few basic predator properties—time lags and limited killing capacity of individual predators—generally predicts instability, i.e., large-amplitude oscillations or even predatordriven extinction of the prey (2, 3). Model stability is particularly difficult to achieve when the predator can drive the prey to densities far below the limits set by the prey_s own resources Ethe Bparadox of enrichment[ (4)^, and almost all theoretically stabilizing mechanisms achieve stability only by causing the prey density to increase close to that limit (1). California red scale (Aonidiella aurantii), an insect pest of citrus worldwide, is controlled by the parasitoid Aphytis melinus (5). This 1 Department of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, CA 93106, USA. 2Department of Integrative Biology, University of California, Berkeley, CA 94720–3140, USA.
*To whom correspondence should be addressed. E-mail:
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system exemplifies in extreme the features— ecological simplicity, high productivity, and severe suppression of the pest—that should engender instability. (i) It is an almost pure specialist consumer-resource interaction. Citrus groves contain, in addition to red scale, only a few, scarce, herbivore species. Under biological control, red scale are attacked mainly by Aphytis melinus; one other parasitoid and one or two predator species are typically present but scarce. (ii) Citrus provides a rich resource for scale. deBach (6) showed that when dichloro-diphenyl-trichloroethane (DDT) was applied to citrus trees (which killed Aphytis but not the resistant scale), scale outbreak density reached several hundred times higher than controlled populations and was not brought back under control for more than 3 years (presumably, when Aphytis was able to reinvade the tree). Yet, in our study area, red scale under control have persisted for 940 years (80 scale generations) with little temporal variation, at densities G1% of the limit set by the citrus plant. Over two decades, we and our colleagues have tested and ruled out many mechanisms
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tion Dynamics in Ecology and Conservation (Oxford Univ. Press, Oxford, 2003). 31. S. Jennings, M. J. Kaiser, J. D. Reynolds, Marine Fisheries Ecology (Blackwell Science, Oxford, 2001). 32. C. J. Krebs, Philos. Trans. R. Soc. London Ser. B 357, 1211 (2002). 33. We are grateful to E. Bazely-White and the NERC Centre for Population Biology at Silwood Park for generous and efficient help in supplying the data and to B.-E. Saether and A. Berryman for extensive constructive comments on an earlier version of the manuscript. Supported by NERC grant no. NER/B/S/2001/00867 (R.M.S. and M.P.). Supporting Online Material www.sciencemag.org/cgi/content/full/309/5734/607/ DC1 Materials and Methods SOM Text Figs. S1 to S3 Table S1 7 February 2005; accepted 18 May 2005 10.1126/science.1110760
by which Aphytis might achieve this remarkable control with stability, including parasitoid aggregation to, or independent of, local host density (7), as well as density-dependence in the parasitoid sex-ratio (8). Stability also does not depend on spatial processes, including metapopulation dynamics. Dynamics were not altered when a spatial refuge from parasitism was removed, or when populations in individual trees were isolated from the larger population in the grove (9): Control and stabilizing mechanisms act locally within a single tree. Feasible remaining mechanisms explored in models involve life-history details, e.g., a long adult host stage invulnerable to parasitism (10). In previous studies, we could not detect temporal density-dependence in parasitism, hostfeeding, or predation (11), a difficult task within the narrow range of densities of a stable system near equilibrium (12). A density-perturbation experiment might uncover both density-dependence and the mechanisms causing return to equilibrium. Density manipulations at the appropriate spatial scale typically are logistically daunting, but in the Aphytis–red scale system, the appropriate spatial scale is the individual tree (9). We created experimental red scale outbreaks (13). We caged individual trees and increased scale recruitment over a period somewhat longer than it takes scale to develop from birth to adult (this development period defines the time unit, t). We followed the dynamics of these outbreak populations, together with caged and uncaged control populations, over three to five scale development times. Three separate experiments gave the same result. We present only the third experiment, which had four outbreak trees. Control of the outbreak and stability— return to equilibrium density—occurred rapidly (Fig. 1). Scale density began to decline even before crawler additions stopped and before one scale development period had passed, and most suppression occurred by t 0 2; i.e., within 2 months after we added scale. By
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13. B.-E. Saether, Trends Ecol. Evol. 12, 143 (1997). 14. T. H. Clutton-Brock et al., Am. Nat. 149, 195 (1997). 15. R. M. Sibly, J. Hone, Philos. Trans. R. Soc. London Ser. B 357, 1153 (2002). 16. S. R. Beissinger, D. R. McCullough, Eds., Population Viability Analysis (Univ. of Chicago Press, Chicago, 2002). 17. G. Caughley, A. R. E. Sinclair, Wildlife Ecology and Management (Blackwell Science, Cambridge, MA, 1994). 18. R. A. Pastorok, S. M. Bartell, S. Ferson, L. R. Ginzburg, Eds., Ecological Modeling in Risk Assessment (CRC/ Lewis, London, 2002). 19. R. M. Anderson, R. M. May, Infectious Diseases of Humans: Dynamics and Control (Oxford Univ. Press, Oxford, 1991). 20. P. Turchin, Oikos 84, 153 (1999). 21. National Environment Research Council (NERC) Centre for Population Biology, Imperial College (1999), Global Population Dynamics Database, available at www.sw. ic.ac.uk/cpb/cpb/gpdd.html 22. Materials and methods are available as supporting material on Science Online. 23. B.-E. Saether, T. H. Ringsby, E. Roskaft, Oikos 77, 217 (1996).
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Fig. 1. Mean densities in four outbreak and 10 control trees over five scale development times (16 months).
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accuracy (Fig. 3B). Predicted peak adult parasitoid density is higher than the observed mean, but close to the peak in the densest tree. Increases or decreases by 10% in each parameter value or set of values (excluding scale development time, which sets the time scale that all other parameters relate to) change predictions little and are as likely to improve as to worsen predictions; Fig. 3B shows the lowest and highest densities induced by these changes. More important, the general result is robust to substantial changes in the value of parameters we expected would affect dynamics most strongly, and even to changes in aspects of model structure. We doubled Aphytis development lag, immature death rates, adult longev-
The model was parameterized independently of the outbreak experiment (13) and used to predict the experiment_s outcome. It was run for t 9 20, until the populations had reached their approximate long-term dynamics, then scale crawlers were added every day over the same period and at the same rate as in the experiment. The model predicted that, in the absence of Aphytis, live scale should reach a first-generation density about 80 times control density, then increase roughly threefold during each scale development time (Fig. 3A). This rate of increase is the maximum observed by deBach in the DDT experiment described above (6). The model predicted the mean densities of the experimental populations with remarkable
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t 0 3, scale densities in outbreak trees almost exactly equaled control densities: This is dynamic stability. Little variation in density was seen in experimental and control populations thereafter. The resident Aphytis populations controlled the outbreak by rapidly increasing in abundance. Scale stages suitable for parasitism (Bhost stages[) became abundant only at the second sampling date, yet by the next sample (less than one scale development period into the experiment), the immature Aphytis population was 920 times denser than in control trees. Adult Aphytis density then increased with only a short delay. Between t 0 1 and t 0 2, the average host_s lifetime probability of parasitism by Aphytis reached 95% in outbreak populations versus 66% in controls (13). Immature and adult Aphytis populations also returned rapidly to control densities as soon as the outbreak was suppressed (Fig. 1). We developed and parameterized a detailed day-by-day stage-structured model of the system, based on extensive laboratory and field investigations (13). The model is an extension of a simpler one that distinguished major red scale life stages and their differential treatment by Aphytis and that suggested that stability might be achieved via three mechanisms. (i) There is a long-lived invulnerable adult scale stage. (ii) Aphytis develops (about 3 times) faster than scale. (iii) An attack on older immature scale yields a higher gain to the parasitoid than does an attack on younger immature scale (the Bgain[ mechanism); for example, older scale yield one or more female parasitoid offspring while the youngest scale are eaten, yielding nutrients for egg development (1, 10). The model recognizes every ecologically distinguishable scale stage and how it is used (or not used) by Aphytis, which can either feed on hosts or lay a clutch of one or two, male or female, eggs (Fig. 2). It classifies adult Aphytis by their egg load and Bgut fullness[; both affect how the parasitoid responds to encountered scale. Egg load increases with a brief delay after a meal and decreases after oviposition. Gut and egg capacity are limited. The model runs on physiological time (degree-days), because in the field, development and search rates are temperature-dependent; simulations use the actual sequence of temperatures experienced during the experiment. Stage durations in degree-days are known, and the model keeps track of the physiological age of all groups. The model also contains two new potentially stabilizing processes discovered during other field experiments. (iv) Hosts containing an Aphytis egg can be reattacked; the existing egg is killed, and the new immature Aphytis survives about half as well as would the original. Subsequent reparasitizations do not produce live offspring. (v) Aphytis adults live longer when scale density is higher (13).
ity, or attack rate; we doubled scale fecundity, or halved adult scale longevity or the attack rate on already parasitized scale. In all cases, model output is little different from that with the default parameters: The outbreak is brought under control by about t 0 3, fluctuations in density remain small over the long run, and long-term average scale density changes little. The three worst cases are shown in Fig. 4: Doubling parasitoid lag slightly delays control; doubling Aphytis immature death rates roughly doubles long-term scale density; keeping Aphytis longevity fixed, independent of scale density, delays control until just after t 0 3, but does not alter longterm dynamics. The pattern is also not altered when we remove the Bgain[ mechanism. Considering the five mechanisms, stability is impossible if the adult invulnerable stage is brief, regardless of other parameter values. A large enough increase (fourfold) in parasitoid time lag causes instability. Changes in intensity of the other three stabilizing mechanisms generally have only small effects on stability. Aphytis longevity that increases with scale density, however, contributes strongly to timely control, especially when the parasitoid delay is long. Although these three mechanisms are individually less important, the combination of mechanisms creates a Bfail-safe[ system that is robust to variation in the environment (parameter values) and major life history properties. Aphytis causes the low scale equilibrium density by efficiently producing female offspring, by means of its search rate and its ability to produce females from relatively small scale (14, 15). Although stabilizing mechanisms in general increase prey density, rapid Aphytis development decreases pest prey density, and adult scale longevity has little effect (1). The field experiment demonstrates remarkable stability in a consumer-resource interaction. The model uncovers the mechanisms that explain such stability, together with concomitant severe suppression of the resource (host) population far below the density set by its own resource (the citrus tree). A simpler version of the model explains how Aphytis melinus re-
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Fig. 3. (A) Density of live scale predicted by the model. Scale eventually increase exponentially in absence of Aphytis, but return to control density with Aphytis present. (B) (Top) Dark curves, model prediction; light curves, highest (Aphytis lag shorter) and lowest (immature scale death rates higher) densities predicted when parameters increased or decreased, individually, by 10%. Vertical lines, range of live scale densities (four experimental trees) on dates when prediction is furthest from observed mean. (Bottom) Vertical lines, range for date closest to peak when counts were made in all four trees. The model parameters were estimated independently of the experimental data.
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Fig. 4. Predicted long-term dynamics in the outbreak experiment when key parameter values were doubled (2) or a mechanism was deleted from the model. Shown are the default prediction and the three worst cases.
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REPORTS
REPORTS Aphytis from Iran) from their natural ecological communities and are now in an unnatural, species-poor, human-created system. Stability is achieved without diversity at any trophic level. Although appeal to spatial processes has come to dominate explanations of persistence and stability, they are not important to the stability or dynamics of this system. Instead, suppression and stability are consequences of the purely life-history and physiological properties of the interacting organisms. References and Notes 1. W. W. Murdoch, C. J. Briggs, R. M. Nisbet, in Consumer
