Qualitative and quantitative responses to press perturbations in ecological networks

Scientific Reports

Volumn 7, Issue 1, 2017, Pages

  Giordano, Giulia ^a   Altafini, Claudio ^b  

^a LUND UNIVERSITY   (Sweden)

^b LINKÖPING UNIVERSITY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

HUMAN; ALGORITHM; BACTERIUM; BIODIVERSITY; ECOLOGY; ECOSYSTEM; PLANKTON; PROCEDURES; THEORETICAL MODEL;

ALGORITHMS; BACTERIA; BIODIVERSITY; ECOLOGY; ECOSYSTEM; MODELS, THEORETICAL; PLANKTON;

EID: 85029301941     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/s41598-017-11221-0     Document Type: Article

References (59)

1. Bender, E. A., Case, T. J. & Gilpin, M. E. Perturbation experiments in community ecology: Theory and practice. Ecology 65, 1-13 (1984).
2. Yodzis, P. The indeterminacy of ecological interactions as perceived through perturbation experiments. Ecology 69, 508-515 (1988).
3. Schmitz, O. J. Press perturbations and the predictability ofecological interactions in a food web. Ecology 78, 55-69 (1997).
4. Montoya, J. M., Woodward, G., Emmerson, M. C. & Solé, R. V. Press perturbations and indirect effects in real food webs. Ecology 90, 2426-2433 (2009).
5. Novak, M. et al. Characterizing species interactions to understand press perturbations: What is the community matrix Annual Review of Ecology, Evolution, and Systematics 47, 409-432 (2016).
6. May, R. M. Stability and Complexity in Model Ecosystems, 2nd ed. (Princeton University Press, 1974).
7. Levins, R. The qualitative analysis of partially specified systems. Annals of the New York Academy of Science 231, 123-138 (1974).
8. Levins, R. Evolution in communities near equilibrium. In Cody, M. & Diamond, J. M. (eds) Ecology and evolution of communities, 16-50 (Harvard University Press, 1975).
9. Dambacher, J., Li, H. & Rossignol, P. Relevance of community structure in assessing indeterminacy of ecological predictions. Ecology 83, 1372-1385 (2002).
10. Dambacher, J., Li, H. & Rossignol, P. Qualitative predictions in model ecosystems. Ecological Modelling 161, 79-93 (2003).
11. Dambacher, J. M., Luh, H.-K., Li, H. W. & Rossignol, P. A. Qualitative stability and ambiguity in model ecosystems. The American Naturalist 161, 876-888 (2003).
12. Dambacher, J., Levins, R. & Rossignol, P. Life expectancy change in perturbed communities: Derivation and qualitative analysis. Mathematical Biosciences 197, 1-14 (2005).
13. Dambacher, J. M. & Ramos Jiliberto, R. Understanding and predicting effects of modified interactions through a qualitative analysis of community structure. The Quarterly Review of Biology 82, 227-250 (2007).
14. Koslicki, D. & Novak, M. Exact probabilities for the indeterminacy of complex networks as perceived through press perturbations. ArXiv:1610. 07705v1 (2016).
15. Novak, M. et al. Predicting community responses to perturbations in the face of imperfect knowledge and network complexity. Ecology 92, 836-846 (2011).
16. Iles, A. & Novak, M. Complexity increases predictability in allometrically constrained food webs. The American Naturalist 188, 87-98 (2016).
17. Bascompte, J., Jordano, P., Melián, C. J. & Olesen, J. M. The nested assembly of plant-animal mutualistic networks. Proceedings of the National Academy of Sciences 100, 9383-9387 (2003).
18. Bastolla, U. et al. The architecture of mutualistic networks minimizes competition and increases biodiversity. Nature 458, 1018-1020 (2009).
19. Smith, H. L. Systems of ordinary differential equations which generate an order preserving flow. A survey of results. SIAM Rev. 30, 87-113 (1988).
20. Smith, H. L. Monotone Dynamical Systems: An Introduction to the Theory of Competitive and Cooperative Systems, vol. 41 of Mathematical Surveys and Monographs (AMS, Providence, RI, 1995).
21. Sontag, E. D. Monotone and near-monotone biochemical networks. Syst. Synth. Biol. 1, 59-87 (2007).
22. Noutsos, D. On Perron-Frobenius property of matrices having some negative entries. Linear Algebra and its Applications 412, 132-153 (2006).
23. Altafini, C. & Lini, G. Predictable dynamics of opinion forming for networks with antagonistic interactions. IEEE Transactions on Automatic Control 60, 342-357 (2015).
24. Gantmacher, F. R. Applications of the theory of matrices (Interscience, New York, 1959).
25. Facchetti, G., Iacono, G. & Altafini, C. Computing global structural balance in large-scale signed social networks. PNAS 108, 20953-20958 (2011).
26. Altafini, C. Dynamics of opinion forming in structurally balanced social networks. PLoS ONE 7, e38135 (2012).
27. Giordano, G., Cuba Samaniego, C., Franco, E. & Blanchini, F. Computing the structural influence matrix for biological systems. Journal of Mathematical Biology 72, 1927-1958 (2016).
28. Giordano, G. Structural Analysis and Control of Dynamical Networks. Ph. D. Thesis, Università degli Studi di Udine (2016).
29. Farina, L. & Rinaldi, S. Positive Linear Systems: Theory and Applications (Wiley, New York, 2000).
30. Blanchini, F., Franco, E. & Giordano, G. A structural classification of candidate oscillatory and multistationary biochemical systems. Bulletin of Mathematical Biology 76, 2542-2569 (2014).
31. Fiedler, M. & Grone, R. Characterizations of sign patterns of inverse-positive matrices. Linear Algebra and its Applications 40, 237-245 (1981).
32. Noutsos, D. & Tsatsomeros, M. J. Reachability and holdability of nonnegative states. SIAM Journal on Matrix Analysis and Applications 30, 700-712 (2008).
33. Le, H. T. & McDonald, J. J. Inverses of M-type matrices created with irreducible eventually nonnegative matrices. Linear Algebra and its Applications 419, 668-674 (2006).
34. Blanchini, F., Franco, E. & Giordano, G. Determining the structural properties of a class of biological models. In Proceedings of the IEEE Conference on Decision and Control, 5505-5510 (Maui (HI), USA, 2012).
35. Blanchini, F. & Giordano, G. Piecewise-linear Lyapunov functions for structural stability of biochemical networks. Automatica 50, 2482-2493 (2014).
36. Yi, T. M., Huang, Y., Simon, M. I. & Doyle, J. Robust perfect adaptation in bacterial chemotaxis through integral feedback control. Proceedings of the National Academy of Sciences of the USA 97, 4649-4653 (2000).
37. Sontag, E. Adaptation and regulation with signal detection implies internal model. Systems & Control Letters 50, 119-126 (2003).
38. Drengstig, T., Ueda, H. R. & Ruoff, P. Predicting perfect adaptation motifs in reaction kinetic networks. The Journal of Physical Chemistry B 112, 16752-16758 (2008).
39. Stone, L. Phytoplankton-bacteria-protozoa interactions: A qualitative model portraying indirect effects. Marine Ecology Progress Series 64, 137-145 (1990).
40. Hosack, G. R., Li, H. W. & Rossignol, P. A. Sensitivity of system stability to model structure. Ecological Modelling 220, 1054-1062 (2009).
41. Scheffer, M., Carpenter, S., Foley, J. A., Folke, C. & Walker, B. Catastrophic shifts in ecosystems. Nature 413, 591-596 (2001).
42. Allesina, S. & Tang, S. The stability-complexity relationship at age 40: A random matrix perspective. Population Ecology 57, 63-75 (2015).
43. Wood, P. M. Universality and the circular law for sparse random matrices. Ann. Appl. Probab. 22, 1266-1300 (2012).
44. Arnoldi, J.-F., Bideault, A., Loreau, M. & Haegeman, B. How ecosystems recover from pulse perturbations: A theory of short-to long-term responses. http://biorxiv. org/content/early/2017/03/08/115048 (2017).
45. Sander, E. L., Wootton, J. T. & Allesina, S. What can interaction webs tell us about species roles PLoS Comput Biol 11, 1-22 (2015).
46. Chase, J. M. et al. The interaction between predation and competition: A review and synthesis. Ecology Letters 5, 302-315 (2002).
47. Mougi, A. & Kondoh, M. Diversity of interaction types and ecological community stability. Science 337, 349-351 (2012).
48. Thébault, E. & Fontaine, C. Stability of ecological communities and the architecture of mutualistic and trophic networks. Science 329, 853-856 (2010).
49. Puccia, C. & Levins, R. Qualitative Modeling of Complex Systems: An Introduction to Loop Analysis and Time Averaging (Harvard University Press, 1985).
50. Higashi, M. & Nakajima, H. Indirect effects in ecological interaction networks i. The chain rule approach. Mathematical Biosciences 130, 99-128 (1995).
51. Wootton, J. Indirect effects in complex ecosystems: recent progress and future challenges. Journal of Sea Research 48, 157-172 Structuring Factors of Shallow Marine Coastal Communities, Part I (2002).
52. Brualdi, R. & Shader, B. Matrices of Sign-Solvable Linear Systems (Cambridge Univ. Press, 1995).
53. Berman, A. & Plemmons, R. Nonnegative Matrices in the Mathematical Sciences. No. pt. 11 in Classics in Applied Mathematics (Society for Industrial and Applied Mathematics, 1994).
54. Martinez, N. D. Constant connectance in community food webs. American Naturalist 139, 1208-1218 (1992).
55. Martinez, N. D. Effects of resolution on food web structure. Oikos 66, 403-412 (1993).
56. Martinez, N. D. Scale-dependent constraints on food-web structure. American Naturalist 144, 935-953 (1994).
57. Olesky, D. D., Tsatsomeros, M. J. & van den Driessche, P. Mv matrices: A generalization of m-matrices based on eventually nonnegative matrices. Electronic Journal of Linear Algebra 18, 339-351 (2009).
58. Barmish, B. R. New tools for robustness of linear systems (McMillan, New York, 1994).
59. Garulli, A., Prattichizzo, D. & Vicino, A. A set theoretic approach for time to contact estimation in dynamic vision. In Proceedings of the IEEE Conference on Decision and Control, 2001-2006 (1998).