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Direct observation of increasing recovery length before collapse of a marine benthic ecosystem

Abstract

Ecosystems can experience catastrophic transitions to alternative states, yet recent results have suggested that slowing down in rates of recovery after a perturbation may provide advance warning that a critical transition is approaching. Perturbation experiments with microbial populations have supported this hypothesis under controlled laboratory conditions, but evidence from natural ecosystems remains rare. Here, we manipulated rocky intertidal canopy algae to test the hypothesis that the spatial scale at which the system recovers from a perturbation in space should increase as the system approaches the tipping point, marking the transition from a canopy-dominated to a turf-dominated state. Empirical estimates of recovery length, a recently proposed spatial indicator of an approaching tipping point, were obtained by comparing the spatial scale at which algal turfs propagated into canopy-degraded regions with decreasing canopy cover. We show that recovery length increased along the gradient in canopy degradation, providing field-based evidence of spatial signatures of critical slowing down in natural conditions.

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Figure 1: Canopy degradation leads to a regime shift from a canopy- to a turf-dominated state.
Figure 2: Schematic illustration of the experiment and measurement of the recovery length.
Figure 3: Canopy degradation enhanced the propagation of algal turfs into the experimental transects.
Figure 4: Simulations of the spatial version of turf– Cystoseiramodel show an increase in the spatial scale of turf propagation along a gradient of canopy degradation.
Figure 5: Recovery length.

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References

  1. Scheffer, M., Carpenter, S., Foley, J. A., Folke, C. & Walker, B. Catastrophic shifts in ecosystems. Nature 413, 591–596 (2001).

    Article  CAS  Google Scholar 

  2. Hughes, T. P. Catastrophes, phase shifts, and large-scale degradation of a Caribbean coral reef. Science 265, 1547–1551 (1994).

    Article  CAS  Google Scholar 

  3. Staver, A. C., Archibald, S. & Levin, S. A. The global extent and determinants of savanna and forest as alternative biome states. Science 334, 230–232 (2011).

    Article  CAS  Google Scholar 

  4. Wissel, C. A universal law of the characteristic return time near thresholds. Oecologia 65, 101–107 (1984).

    Article  CAS  Google Scholar 

  5. Scheffer, M. et al. Anticipating critical transitions. Science 338, 344–348 (2012).

    Article  CAS  Google Scholar 

  6. Scheffer, M. et al. Early-warning signals for critical transitions. Nature 461, 53–59 (2009).

    Article  CAS  Google Scholar 

  7. van Nes, E. H. & Scheffer, M. Slow recovery from perturbations as a generic indicator of a nearby catastrophic shift. Am. Nat. 169, 738–747 (2007).

    Article  Google Scholar 

  8. Dai, L., Vorselen, D., Korolev, K. S. & Gore, J. Generic indicators for loss of resilience before a tipping point leading to population collapse. Science 336, 1175–1177 (2012).

    Article  CAS  Google Scholar 

  9. Veraart, A. J. et al. Recovery rates reflect distance to a tipping point in a living system. Nature 481, 357–359 (2012).

    Article  CAS  Google Scholar 

  10. Benedetti-Cecchi, L., Tamburello, L., Maggi, E. & Bulleri, F. Experimental perturbations modify the performance of early warning indicators of regime shift. Curr. Biol. 25, 1867–1872 (2015).

    Article  CAS  Google Scholar 

  11. Carpenter, S. R. et al. Early warnings of regime shifts: a whole-ecosystem experiment. Science 332, 1079–1082 (2011).

    Article  CAS  Google Scholar 

  12. Cline, T. J. et al. Early warnings of regime shifts: evaluation of spatial indicators from a whole-ecosystem experiment. Ecosphere 5, 1–13 (2014).

    Article  Google Scholar 

  13. Drake, J. M. & Griffen, B. D. Early warning signals of extinction in deteriorating environments. Nature 467, 456–459 (2010).

    Article  CAS  Google Scholar 

  14. Dakos, V. et al. Slowing down as an early warning signal for abrupt climate change. Proc. Natl Acad. Sci. USA 105, 14308–14312 (2008).

    Article  CAS  Google Scholar 

  15. Lade, S. J. & Gross, T. Early warning signals for critical transitions: a generalized modeling approach. PLoS Comput. Biol. 8, e1002360 (2012).

    Article  CAS  Google Scholar 

  16. Kéfi, S., Dakos, V., Scheffer, M., Van Nes, E. H. & Rietkerk, M. Early warning signals also precede non-catastrophic transitions. Oikos 122, 641–648 (2013).

    Article  Google Scholar 

  17. Boettiger, C. & Hastings, A. Early warning signals and the prosecutor’s fallacy. Proc. R. Soc. B 279, 4734–4739 (2012).

    Article  Google Scholar 

  18. Dakos, V. et al. Methods for detecting early warnings of critical transitions in time series illustrated using simulated ecological data. PLoS ONE 7, e41010 (2012).

    Article  CAS  Google Scholar 

  19. Bestelmeyer, B. T. et al. Analysis of abrupt transitions in ecological systems. Ecosphere 2, 1–26 (2011).

    Article  Google Scholar 

  20. Lenton, T. M., Livina, V. N., Dakos, V., van Nes, E. H. & Scheffer, M. Early warning of climate tipping points from critical slowing down: comparing methods to improve robustness. Phil. Trans. R. Soc. A 370, 1185–1204 (2012).

    Article  CAS  Google Scholar 

  21. Kefi, S. et al. Early warning signals of ecological transitions: methods for spatial patterns. PLoS ONE 9, e92097 (2014).

    Article  Google Scholar 

  22. Dakos, V., van Nes, E. H., Donangelo, R., Fort, H. & Scheffer, M. Spatial correlation as leading indicator of catastrophic shifts. Theor. Ecol. 3, 163–174 (2010).

    Article  Google Scholar 

  23. Guttal, V. & Jayaprakash, C. Spatial variance and spatial skewness: leading indicators of regime shifts in spatial ecological systems. Theor. Ecol. 2, 3–12 (2000).

    Article  Google Scholar 

  24. Streeter, R. & Dugmore, A. J. Anticipating land surface change. Proc. Natl Acad. Sci. USA 110, 5779–5784 (2013).

    Article  CAS  Google Scholar 

  25. Litzow, M. A., Urban, J. D. & Laurel, B. J. Increased spatial variance accompanies reorganization of two continental shelf ecosystems. Ecol. Appl. 18, 1331–1337 (2008).

    Article  Google Scholar 

  26. Carpenter, S. R. & Brock, W. A. Early warnings of regime shifts in spatial dynamics using the discrete Fourier transform. Ecosphere 1, 1–15 (2010).

    Article  Google Scholar 

  27. Kefi, S. et al. Spatial vegetation patterns and imminent desertification in Mediterranean arid ecosystems. Nature 449, 213–217 (2007).

    Article  CAS  Google Scholar 

  28. Kefi, S. et al. Robust scaling in ecosystems and the meltdown of patch size distributions before extinction. Ecol. Lett. 14, 29–35 (2011).

    Article  Google Scholar 

  29. Rietkerk, M., Dekker, S. C., de Ruiter, P. C. & van de Koppel, J. Self-organized patchiness and catastrophic shifts in ecosystems. Science 305, 1926–1929 (2004).

    Article  CAS  Google Scholar 

  30. Dakos, V., Kefi, S., Rietkerk, M., van Nes, E. H. & Scheffer, M. Slowing down in spatially patterned ecosystems at the brink of collapse. Am. Nat. 177, E153–E166 (2011).

    Article  Google Scholar 

  31. Dai, L., Korolev, K. S. & Gore, J. Slower recovery in space before collapse of connected populations. Nature 496, 355–358 (2013).

    Article  CAS  Google Scholar 

  32. Dai, L., Korolev, K. S. & Gore, J. Relation between stability and resilience determines the performance of early warning signals under different environmental drivers. Proc. Natl Acad. Sci. USA 112, 10056–10061 (2015).

    Article  CAS  Google Scholar 

  33. Scheffer, M., Carpenter, S. R., Dakos, V. & van Nes, E. H. Generic indicators of ecological resilience: inferring the chance of a critical transition. Annu. Rev. Ecol. Evol. Syst. 46, 145–167 (2015).

    Article  Google Scholar 

  34. Livina, V. N., Kwasniok, F. & Lenton, T. M. Potential analysis reveals changing number of climate states during the last 60 kyr. Clim. Past 6, 77–82 (2010).

    Article  Google Scholar 

  35. Konar, B. & Estes, J. A. The stability of boundary regions between kelp beds and deforested areas. Ecology 84, 174–185 (2003).

    Article  Google Scholar 

  36. Robles, C. D., Garza, C., Desharnais, R. A. & Donahue, M. J. Landscape patterns in boundary intensity: a case study of mussel beds. Landscape Ecol. 25, 745–759 (2010).

    Article  Google Scholar 

  37. Scheffer, M. et al. Vegetated areas with clear water in turbid shallow lakes. Aquat. Bot. 49, 193–196 (1994).

    Article  Google Scholar 

  38. Silliman, B. R., van de Koppel, J., Bertness, M. D., Stanton, L. E. & Mendelssohn, I. A. Drought, snails, and large-scale die-off of southern U.S. salt marshes. Science 310, 1803–1806 (2005).

    Article  CAS  Google Scholar 

  39. Da Silveira Lobo Sternberg, L. Savanna–forest hysteresis in the tropics. Global Ecol. Biogeogr. 10, 369–378 (2001).

    Article  Google Scholar 

  40. Batt, R. D., Carpenter, S. R., Cole, J. J., Pace, M. L. & Johnson, R. A. Changes in ecosystem resilience detected in automated measures of ecosystem metabolism during a whole-lake manipulation. Proc. Natl Acad. Sci. USA 110, 17398–17403 (2013).

    Article  CAS  Google Scholar 

  41. Rietkerk, M. & van de Koppel, J. Regular pattern formation in real ecosystems. Trends Ecol. Evol. 23, 169–175 (2008).

    Article  Google Scholar 

  42. Barbier, N., Couteron, P., Lejoly, J., Deblauwe, V. & Lejeune, O. Self-organized vegetation patterning as a fingerprint of climate and human impact on semi-arid ecosystems. J. Ecol. 94, 537–547 (2006).

    Article  Google Scholar 

  43. Steneck, R. S. et al. Kelp forest ecosystems: biodiversity, stability, resilience and future. Environ. Conserv. 29, 436–459 (2002).

    Article  Google Scholar 

  44. Benedetti-Cecchi, L. et al. Predicting the consequences of anthropogenic disturbance: large-scale effects of loss of canopy algae on rocky shores. Mar. Ecol. Prog. Ser. 214, 137–150 (2001).

    Article  Google Scholar 

  45. Connell, S. D. et al. Recovering a lost baseline: missing kelp forests from a metropolitan coast. Mar. Ecol. Prog. Ser. 360, 63–72 (2008).

    Article  Google Scholar 

  46. Beck, M. & Airoldi, L. Loss, status and trends for coastal marine habitats of Europe. Oceanogr. Mar. Biol. 45, 345–405 (2007).

    Article  Google Scholar 

  47. Pace, M. L., Carpenter, S. R. & Cole, J. J. With and without warning: managing ecosystems in a changing world. Front. Ecol. Environ. 13, 460–467 (2015).

    Article  Google Scholar 

  48. Lenton, T. M. & Williams, H. T. On the origin of planetary-scale tipping points. Trends Ecol. Evol. 28, 380–382 (2013).

    Article  Google Scholar 

  49. Brook, B. W., Ellis, E. C., Perring, M. P., Mackay, A. W. & Blomqvist, L. Does the terrestrial biosphere have planetary tipping points? Trends Ecol. Evol. 28, 396–401 (2013).

    Article  Google Scholar 

  50. Worm, B. & Lotze, H. K. Effects of eutrophication, grazing, and algal blooms on rocky shores. Limnol. Oceanogr. 51, 569–579 (2006).

    Article  Google Scholar 

  51. Benedetti-Cecchi, L. et al. Linking patterns and processes across scales: the application of scale-transition theory to algal dynamics on rocky shores. J. Exp. Biol. 215, 977–985 (2012).

    Article  Google Scholar 

  52. Tamburello, L., Bulleri, F., Bertocci, I., Maggi, E. & Benedetti-Cecchi, L. Reddened seascapes: experimentally induced shifts in 1/fspectra of spatial variability in rocky intertidal assemblages. Ecology 94, 1102–1111 (2013).

    Article  Google Scholar 

  53. Connell, S. D., Foster, M. S. & Airoldi, L. What are algal turfs? Towards a better description of turfs. Mar. Ecol. Prog. Ser. 495, 299–307 (2014).

    Article  Google Scholar 

  54. Lahti, L., Salojärvi, J., Salonen, A., Scheffer, M. & de Vos, W. M. Tipping elements in the human intestinal ecosystem. Nat. Commun. 5, 4344 (2014).

    Article  CAS  Google Scholar 

  55. Bolker, B. M. Ecological Models and Data in R. (Princeton Univ. Press, 2008).

    Book  Google Scholar 

  56. Hijmans, R. J. & van Etten, J. raster: geographic analysis and modeling with raster data, R package version 2.0-12. (2012).

  57. Genz, A. & Bretz, F. Computation of Multivariate Normal and t Probabilities . (Springer Berlin Heidelberg, 2009).

    Book  Google Scholar 

  58. Soetaert, K., Cash, J. & Mazzia, F. Solving Differential Equations in R. (Springer Berlin Heidelberg, 2012).

    Book  Google Scholar 

  59. Soetaert, K. & Meysman, F. Reactive transport in aquatic ecosystems: rapid model prototyping in the open source software R. Environ. Model. Softw. 32, 49–60 (2012).

    Article  Google Scholar 

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Acknowledgements

We thank E. Maggi, F. Bulleri, C. Ravaglioli and L. Tamburello for field and technical assistance, A. Rattray for useful comments on the manuscript, A. Perez-Escudero for helping to develop the model, R. Casagrandi and L. Mari for their feedback. The authors acknowledge financial support from University of Pisa through the PRA (PRA_2015_055) and MISTI projects, the latter in collaboration with MIT. J.G. also acknowledges support from an NIH New Innovator Award (DP2 AG044279).

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L.R. and L.B.-C. designed the study. L.R. did the analyses and wrote the first draft of the manuscript. M.D.B., L.D. and J.G. assisted with the analysis. L.R., M.D.B and L.B.-C. performed the experiment. All authors contributed to interpreting the results and commented on the manuscript.

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Correspondence to Luca Rindi.

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The authors declare no competing financial interest.

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Supplementary Information

Supplementary Methods; Supplementary Figures 1–7; Supplementary Table 1 (PDF 3240 kb)

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Rindi, L., Bello, M., Dai, L. et al. Direct observation of increasing recovery length before collapse of a marine benthic ecosystem. Nat Ecol Evol 1, 0153 (2017). https://doi.org/10.1038/s41559-017-0153

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