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Critical slowing down as an indicator of transitions in two-species models Ryan Chisholm Smithsonian Tropical Research Institute Workshop on Critical Transitions in Complex Systems 21 March 2012 Imperial College London Acknowledgements • Elise Filotas, Centre for Forest Research at the University of Quebec in Montreal • Simon Levin, Princeton University, Department of Ecology and Evolutionary Biology • Helene Muller-Landau, Smithsonian Tropical Research Institute • Santa Fe Institute, Complex Systems Summer School 2007: NSF Grant No. 0200500 Question When is critical slowing down likely to be a useful leading indicator of a critical transition in ecological models? Outline • • • • • • Smithsonian Tropical Research Institute Background: critical slowing down Competition model Predator-prey model Grasslands model Future work Outline • • • • • • Smithsonian Tropical Research Institute Background: critical slowing down Competition model Predator-prey model Grasslands model Future work Smithsonian Tropical Research Institute • “…dedicated to understanding biological diversity” • What determines patterns of diversity? • What factors regulate ecosystem function? • How will tropical forests respond to climate change and other anthropogenic disturbances? Smithsonian Tropical Research Institute Panama Smithsonian Tropical Research Institute 50 ha plot Smithsonian Tropical Research Institute • • • • Green iguana (Iguana iguana) 1500 ha 2551 mm yr-1 rainfall 381 bird species 102 mammal species (nearly half are bats) • ~100 species of amphibians and reptiles • 1316 plant species Pentagonia macrophylla Keel-billed Toucan (Ramphastos sulfuratus) Jaguar (Panthera onca) Photo: Christian Ziegler Smithsonian Tropical Research Institute Photo: Marcos Guerra, STRI Photo: Leonor Alvarez sciencedaily.com Center for Tropical Forest Science Forest resilience Staver et al. 2011 Science Chisholm, Condit, et al. in prep Outline • • • • • • Smithsonian Tropical Research Institute Background: critical slowing down Competition model Predator-prey model Grasslands model Future work Transitions in complex systems • • • • • Eutrophication of shallow lakes Sahara desertification Climate change Shifts in public opinion Forest-savannah transitions Scheffer et al. 2009 Nature, Scheffer 2009 Critical Transitions in Nature and Society Critical transitions May 1977 Nature Detecting impending transitions • Decreasing return rate • Rising variance • Rising autocorrelation => All arise from critical slowing down Carpenter & Brock 2006 Ecol. Lett., van Nes & Scheffer 2007 Am. Nat., Scheffer et al. 2009 Nature Critical slowing down • Recovery rate: return rate after disturbance to the equilibrium • Critical slowing down: dominant eigenvalue tends to zero; recovery rate decreases as transition approaches van Nes & Scheffer 2007 Am. Nat. Critical slowing down van Nes & Scheffer 2007 Am. Nat. Critical slowing down van Nes & Scheffer 2007 Am. Nat. Question When is critical slowing down likely to be a useful leading indicator of a critical transition in ecological models? What is the length/duration of the warning period? Outline • • • • • • Smithsonian Tropical Research Institute Background: critical slowing down Competition model Predator-prey model Grasslands model Future work Competition model Ni = abundance of species i Ki = carrying capacity of species i ri = intrinsic rate of increase of species i αij = competitive impact of species j on species i Equilibria: Lotka 1925, 1956 Elements of Physical Biology; Chisholm & Filotas 2009 J. Theor. Biol. Competition model Case 1: Interspecific competition greater than intraspecific competition Stable Stable Unstable Unstable Chisholm & Filotas 2009 J. Theor. Biol. Question When is critical slowing down likely to be a useful leading indicator of a critical transition in ecological models? What is the length/duration of the warning period? Competition model Ni = abundance of species i Ki = abundance of species i ri = intrinsic rate of increase of species i αij = competitive impact of species j on species i Recovery rate: When species 1 dominates, recovery rate begins to decline at: Chisholm & Filotas 2009 J. Theor. Biol. Competition model Chisholm & Filotas 2009 J. Theor. Biol. Competition model Ni = abundance of species i Ki = abundance of species i ri = intrinsic rate of increase of species i αij = competitive impact of species j on species i Recovery rate begins to decline at: More warning of transition if the dynamics of the rare species are slow relative to those of the dominant species Chisholm & Filotas 2009 J. Theor. Biol. Competition model Case 2: Interspecific competition less than intraspecific competition Stable Stable Unstable Stable Chisholm & Filotas 2009 J. Theor. Biol. Competition model Case 2: Interspecific competition less than intraspecific competition More warning of transition if the dynamics of the rare species are slow relative to those of the dominant species Chisholm & Filotas 2009 J. Theor. Biol. Outline • • • • • • Smithsonian Tropical Research Institute Background: critical slowing down Competition model Predator-prey model Grasslands model Future work Predator-prey model V = prey abundance P = predator abundance Rosenzweig 1971 Science Predator-prey model 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 V = prey abundance P = predator abundance r = intrinsic rate of increase of prey 0 k = predation rate J = equilibrium prey population size A = predator-prey conversion efficiency K = carrying capacity of prey f(V) = effects of intra-specific competition among prey f(V) > 0; f ’(V) < 0; f(K) = 0; df/dK > 0 h(V) = per-capita rate at which predators kill prey h(V) > 0; h’(V) > 0; h’’(V) < 0; h(0) = 0 h(V) f(V) 20 40 60 VV Rosenzweig 1971 Science, Chisholm & Filotas 2009 J. Theor. Biol. 80 100 Predator-prey model Equilibria: Unstable Stable for K ≤ J V = prey abundance P = predator abundance r = intrinsic rate of increase of prey k = predation rate J = equilibrium prey population size A = predator-prey conversion efficiency K = carrying capacity of prey f(V) = effects of intra-specific competition among prey f(V) > 0; f ’(V) < 0; f(K) = 0; df/dK > 0 h(V) = per-capita rate at which predators kill prey h(V) > 0; h’(V) > 0; h’’(V) < 0; h(0) = 0 Exists for K ≥ J Stable for J ≤ K ≤ Kcrit Rosenzweig 1971 Science, Chisholm & Filotas 2009 J. Theor. Biol. Predator-prey model Predator isocline V = prey abundance P = predator abundance r = intrinsic rate of increase of prey k = predation rate J = equilibrium prey population size A = predator-prey conversion efficiency f(V) = effects of intra-specific competition among prey f(V) > 0; f ’(V) < 0; f(K) = 0; df/dK > 0 h(V) = per-capita rate at which predators kill prey h(V) > 0; h’(V) > 0; h’’(V) < 0; h(0) = 0 Prey isoclines Rosenzweig 1971 Science, Chisholm & Filotas 2009 J. Theor. Biol. Predator-prey model Unstable equilibrium V = prey abundance P = predator abundance r = intrinsic rate of increase of prey k = predation rate J = equilibrium prey population size A = predator-prey conversion efficiency f(V) = effects of intra-specific competition among prey f(V) > 0; f ’(V) < 0; f(K) = 0; df/dK > 0 h(V) = per-capita rate at which predators kill prey h(V) > 0; h’(V) > 0; h’’(V) < 0; h(0) = 0 Stable equilibrium Rosenzweig 1971 Science, Chisholm & Filotas 2009 J. Theor. Biol. Predator-prey model Scheffer 1998 The Ecology of Shallow Lakes Predator-prey model Hopf bifurcation occurs when K = Kcrit : Critical slowing down begins when K = Kr : Predator-prey model Chisholm & Filotas 2009 J. Theor. Biol. Predator-prey model Chisholm & Filotas 2009 J. Theor. Biol. Predator-prey model Kr and Kcrit converge as: More warning of transition when: • Predator-prey conversion efficiency (A) is high • Predation rate (k) is high • Prey growth rate (r) is low Prey controlled by predators rather than intrinsic density dependence Increases tendency for oscillations Larger K makes oscillations larger and hence rates of return slower Chisholm & Filotas 2009 J. Theor. Biol. Predator-prey model Chisholm & Filotas 2009 J. Theor. Biol. Multi-species models van Nes & Scheffer 2007 Am. Nat. Multi-species models Expect that multi-species models will exhibit longer warning periods of transitions induced by changes in resource abundance when: • Dynamics of rare species are slow relative to those of the dominant species • Prey species are controlled by predation rather than intrinsic density dependence Chisholm & Filotas 2009 J. Theor. Biol. Outline • • • • • • Smithsonian Tropical Research Institute Background: critical slowing down Competition model Predator-prey model Grasslands model Future work Practical utility of critical slowing down Chisholm & Filotas 2009 J. Theor. Biol. “…even if an increase in variance or AR1 is detected, it provides no indication of how close to a regime shift the ecosystem is…” Biggs et al. 2008 PNAS Western Basalt Plains Grasslands Western Basalt Plains Grasslands Western Basalt Plains Grasslands Williams et al. 2005 J. Ecol.; Williams et al. 2006 Ecology Grasslands invasion model Agricultural fertiliser run-off Native grass biomass Sugar addition Nutrient input rate Grasslands invasion model A = plant-available N pool Bi = biomass of species i ωi = N-use efficiency of species i νi = N-use efficiency of species i μi = N-use efficiency of species i αij = light competition coefficients I = abiotic N-input flux K = soil leaching rate of plant-available N δ = proportion of N in litterfall lost from the system Parameterized so that species 2 (invader) has a higher uptake rate and higher turnover rate. Chisholm & Levin in prep.; Menge et al. 2008 PNAS Grasslands invasion model B2 B1 Relatively safe, but higher control Nutrient input costs. Riskier, but lower control costs. Conclusions & Future work Critical slowing down provides an earlier indicator of transitions in two-species models where: • Dynamics of rare species are slow relative to those of the dominant species • Prey species are controlled by predation rather than intrinsic density dependence But utility of early/late indicators depends on socio-economic considerations