Aizen, M. A., Sabatino, M. & Tylianakis, J. M. Specialization and rarity predict nonrandom loss of interactions from mutualist networks. Science 335, 1486–1489 (2012).
Google Scholar
Aanen, D. K. et al. The evolution of fungus-growing termites and their mutualistic fungal symbionts. Proc. Natl Acad. Sci. USA 99, 14887–14892 (2002).
Google Scholar
Lello, J., Boag, B., Fenton, A., Stevenson, I. R. & Hudson, P. J. Competition and mutualism among the gut helminths of a mammalian host. Nature 428, 840–844 (2004).
Google Scholar
Jaeggi, A. V. & Gurven, M. Natural cooperators: food sharing in humans and other primates. Evol. Anthropol. 22, 186–195 (2013).
Google Scholar
Van Der Maas, H. L., Kan, K.-J., Marsman, M. & Stevenson, C. E. Network models for cognitive development and intelligence. J. Intell. 5, 16 (2017).
Google Scholar
Bascompte, J. & Jordano, P. Plant-animal mutualistic networks: the architecture of biodiversity. Annu. Rev. Ecol. Evol. Syst. 38, 567–593 (2007).
Google Scholar
Bastolla, U. et al. The architecture of mutualistic networks minimizes competition and increases biodiversity. Nature 458, 1018 (2009).
Google Scholar
Valverde, S. et al. The architecture of mutualistic networks as an evolutionary spandrel. Nat. Ecol. Evol. 2, 94–99 (2018).
Google Scholar
Vizentin-Bugoni, J. et al. Structure, spatial dynamics, and stability of novel seed dispersal mutualistic networks in Hawai’i. Science 364, 78–82 (2019).
Google Scholar
Bascompte, J. Disentangling the web of life. Science 325, 416–419 (2009).
Google Scholar
Liu, X. et al. Network resilience. Phys. Rep. 971, 1–108 (2022).
Google Scholar
Rezende, E. L., Lavabre, J. E., Guimarães, P. R., Jordano, P. & Bascompte, J. Non-random coextinctions in phylogenetically structured mutualistic networks. Nature 448, 925–928 (2007).
Google Scholar
Pocock, M. J., Evans, D. M. & Memmott, J. The robustness and restoration of a network of ecological networks. Science 335, 973–977 (2012).
Google Scholar
Fowler, J. H. & Christakis, N. A. Cooperative behavior cascades in human social networks. Proc. Natl Acad. Sci. USA 107, 5334–5338 (2010).
Google Scholar
May, R. M., Levin, S. A. & Sugihara, G. Complex systems: ecology for bankers. Nature 451, 893–894 (2008).
Google Scholar
Thébault, E. & Fontaine, C. Stability of ecological communities and the architecture of mutualistic and trophic networks. Science 329, 853–856 (2010).
Google Scholar
Berdugo, M. et al. Global ecosystem thresholds driven by aridity. Science 367, 787–790 (2020).
Google Scholar
Diaz, R. J. & Rosenberg, R. Spreading dead zones and consequences for marine ecosystems. Science 321, 926–929 (2008).
Google Scholar
Biggs, R. O., Peterson, G. & Rocha, J. C. The regime shifts database: a framework for analyzing regime shifts in social-ecological systems. Ecol. Soc. 23, 3 (2018).
Google Scholar
Walker, B. & Meyers, J. A. Thresholds in ecological and social-ecological systems: a developing database. Ecol. Soc. 9, 2 (2004).
Hirota, M., Holmgren, M., Van Nes, E. H. & Scheffer, M. Global resilience of tropical forest and savanna to critical transitions. Science 334, 232–235 (2011).
Google Scholar
Barnosky, A. D. et al. Approaching a state shift in earth’s biosphere. Nature 486, 52–58 (2012).
Google Scholar
Dakos, V. & Bascompte, J. Critical slowing down as early warning for the onset of collapse in mutualistic communities. Proc. Natl Acad. Sci. USA 111, 17546–17551 (2014).
Google Scholar
Lever, J. J., van Nes, E. H., Scheffer, M. & Bascompte, J. The sudden collapse of pollinator communities. Ecol. Lett. 17, 350–359 (2014).
Google Scholar
Lever, J. J. et al. Foreseeing the future of mutualistic communities beyond collapse. Ecol. Lett. 23, 2–15 (2020).
Google Scholar
Hillebrand, H. et al. Thresholds for ecological responses to global change do not emerge from empirical data. Nat. Ecol. Evol. 4, 1502–1509 (2020).
Google Scholar
Dudney, J. & Suding, K. N. The elusive search for tipping points. Nat. Ecol. Evol. 4, 1449–1450 (2020).
Google Scholar
Scheffer, M. et al. Anticipating critical transitions. Science 338, 344–348 (2012).
Google Scholar
Martin, S., Deffuant, G. & Calabrese, J. M. in Viability and Resilience of Complex Systems (eds. Deffuant, G., & Gilbert, N.) 15–36 (Springer, 2011).
Cohen, R., Erez, K., Ben-Avraham, D. & Havlin, S. Resilience of the internet to random breakdowns. Phys. Rev. Lett. 85, 4626–4628 (2000).
Google Scholar
Gao, J., Barzel, B. & Barabási, A.-L. Universal resilience patterns in complex networks. Nature 530, 307–312 (2016).
Google Scholar
Scheffer, M. et al. Early-warning signals for critical transitions. Nature 461, 53–59 (2009).
Google Scholar
Boettiger, C. & Hastings, A. Quantifying limits to detection of early warning for critical transitions. J. R. Soc. Interface 9, 2527–2539 (2012).
Google Scholar
Blanchard, J. L. A rewired food web. Nature 527, 173–174 (2015).
Google Scholar
Campbell, C., Yang, S., Shea, K. & Albert, R. Topology of plant-pollinator networks that are vulnerable to collapse from species extinction. Phys. Rev. E 86, 021924 (2012).
Google Scholar
Revilla, T. A., Encinas-Viso, F. & Loreau, M. Robustness of mutualistic networks under phenological change and habitat destruction. Oikos 124, 22–32 (2015).
Google Scholar
Vizentin-Bugoni, J. et al. Ecological correlates of species’ roles in highly invaded seed dispersal networks. Proc. Natl Acad. Sci. USA 118, (2021).
Whanpetch, N. et al. Temporal changes in benthic communities of seagrass beds impacted by a tsunami in the Andaman Sea, Thailand. Estuar. Coast. Shelf Sci. 87, 246–252 (2010).
Google Scholar
Orth, R. J. et al. Restoration of seagrass habitat leads to rapid recovery of coastal ecosystem services. Sci. Adv. 6, eabc6434 (2020).
Google Scholar
Veraart, A. J. et al. Recovery rates reflect distance to a tipping point in a living system. Nature 481, 357–359 (2012).
Google Scholar
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).
Google Scholar
Dakos, V., van Nes, E. H., d’Odorico, P. & Scheffer, M. Robustness of variance and autocorrelation as indicators of critical slowing down. Ecology 93, 264–271 (2012).
Google Scholar
van Belzen, J. et al. Vegetation recovery in tidal marshes reveals critical slowing down under increased inundation. Nat. Commun. 8, 15811 (2017).
Google Scholar
Rohr, R. P., Saavedra, S. & Bascompte, J. On the structural stability of mutualistic systems. Science 345, 1253497 (2014).
Google Scholar
Wright, D. H. A simple, stable model of mutualism incorporating handling time. Am. Nat.134, 664–667 (1989).
Google Scholar
Newman, M. E. J. Networks: An Introduction (Oxford Univ. Press, 2010).
Jiang, J. et al. Predicting tipping points in mutualistic networks through dimension reduction. Proc. Natl Acad. Sci. USA 115, E639–E647 (2018).
Google Scholar
Gao, J., Buldyrev, S. V., Stanley, H. E. & Havlin, S. Networks formed from interdependent networks. Nat. Phys. 8, 40–48 (2012).
Google Scholar
May, R. M. Thresholds and breakpoints in ecosystems with a multiplicity of stable states. Nature 269, 471–477 (1977).
Google Scholar
Moreno, Y., Pastor-Satorras, R., Vázquez, A. & Vespignani, A. Critical load and congestion instabilities in scale-free networks. Europhys. Lett. 62, 292–298 (2003).
Google Scholar
Martinez, N. D., Williams, R. J., Dunne, J. A. & Pascual, M. in Ecological Networks: Linking Structure to Dynamics in Food Webs (eds. Pascual, M., Dunne, J. A., & Dunne, J. A.) 163–185 (Oxford University Press, 2006).
Chen, S., O’Dea, E. B., Drake, J. M. & Epureanu, B. I. Eigenvalues of the covariance matrix as early warning signals for critical transitions in ecological systems. Sci. Rep. 9, 1–14 (2019).
Google Scholar
Suweis, S., Simini, F., Banavar, J. R. & Maritan, A. Emergence of structural and dynamical properties of ecological mutualistic networks. Nature 500, 449–452 (2013).
Google Scholar
Mariani, M. S., Ren, Z.-M., Bascompte, J. & Tessone, C. J. Nestedness in complex networks: observation, emergence, and implications. Phys. Rep. 813, 1–90 (2019).
Google Scholar
Staniczenko, P. P., Kopp, J. C. & Allesina, S. The ghost of nestedness in ecological networks. Nat. Commun. 4, 1–6 (2013).
Google Scholar
Marsh, H. et al. Optimizing allocation of management resources for wildlife. Conserv. Biol. 21, 387–399 (2007).
Google Scholar
Dakos, V. et al. Slowing down as an early warning signal for abrupt climate change. Proc. Natl Acad. Sci. USA 105, 14308–14312 (2008).
Google Scholar
Reyer, C. P. et al. Forest resilience and tipping points at different spatio-temporal scales: approaches and challenges. J. Ecol. 103, 5–15 (2015).
Google Scholar
Dakos, V. et al. Ecosystem tipping points in an evolving world. Nat. Ecol. Evol. 3, 355–362 (2019).
Google Scholar
Hurwicz, L. The design of mechanisms for resource allocation. Am. Econ. Rev. 63, 1–30 (1973).
Almeida-Neto, M. & Ulrich, W. A straightforward computational approach for measuring nestedness using quantitative matrices. Environ. Model. Softw. 26, 173–178 (2011).
Google Scholar
Atmar, W. & Patterson, B. D. The measure of order and disorder in the distribution of species in fragmented habitat. Oecologia 96, 373–382 (1993).
Google Scholar
Kéfi, S. et al. Spatial vegetation patterns and imminent desertification in Mediterranean arid ecosystems. Nature 449, 213–217 (2007).
Google Scholar
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).
Google Scholar
Buldyrev, S. V., Parshani, R., Paul, G., Stanley, H. E. & Havlin, S. Catastrophic cascade of failures in interdependent networks. Nature 464, 1025–1028 (2010).
Google Scholar
Web of Life, Ecological Networks Database (Bascompte Lab, accessed 12 June 2017); http://www.web-of-life.es/map.php?type=5/
Gleeson, J. P., Melnik, S., Ward, J. A., Porter, M. A. & Mucha, P. J. Accuracy of mean-field theory for dynamics on real-world networks. Phys. Rev. E 85, 026106 (2012).
Google Scholar
Strogatz, S. H. Nonlinear Dynamics and Chaos: with Applications to Physics, Biology, Chemistry, and Engineering (CRC Press, 2018).
Vázquez, D. P. Interactions Among Introduced Ungulates, Plants, and Pollinators: a Field Study in the Temperate Forest of the Southern Andes PhD thesis, University of Tennessee (2002).
Kaiser-Bunbury, C. N., Vázquez, D. P., Stang, M. & Ghazoul, J. Determinants of the microstructure of plant-pollinator networks. Ecology 95, 3314–3324 (2014).
Google Scholar
Memmott, J. The structure of a plant-pollinator food web. Ecol. Lett. 2, 276–280 (1999).
Google Scholar
Dicks, L., Corbet, S. & Pywell, R. Compartmentalization in plant-insect flower visitor webs. J. Anim. Ecol. 71, 32–43 (2002).
Google Scholar
SMITH-RAMÍREZ, C., Martinez, P., Nunez, M., González, C. & Armesto, J. J. Diversity, flower visitation frequency and generalism of pollinators in temperate rain forests of Chiloé Island, Chile. Bot. J. Linn. Soc. 147, 399–416 (2005).
Google Scholar
Dupont, Y. L., Hansen, D. M. & Olesen, J. M. Structure of a plant-flower-visitor network in the high-altitude sub-alpine desert of Tenerife, Canary Islands. Ecography 26, 301–310 (2003).
Google Scholar
Dupont, Y. L. & Olesen, J. M. Ecological modules and roles of species in heathland plant-insect flower visitor networks. J. Anim. Ecol. 78, 346–353 (2009).
Google Scholar
Source: Ecology - nature.com