Skip to main content Accessibility help
×
Hostname: page-component-586b7cd67f-rcrh6 Total loading time: 0 Render date: 2024-11-23T00:40:32.839Z Has data issue: false hasContentIssue false

Ecological Complexity

Published online by Cambridge University Press:  20 July 2023

Alkistis Elliott-Graves
Affiliation:
Universität Bielefeld, Germany

Summary

Complexity has received substantial attention from scientists and philosophers alike. There are numerous, often conflicting, accounts of how complexity should be defined and how it should be measured. Much less attention has been paid to the epistemic implications of complexity, especially in Ecology. How does the complex nature of ecological systems affect ecologists' ability to study them? This Element argues that ecological systems are complex in a rather special way: they are causally heterogeneous. Not only are they made up of many interacting parts, but their behaviour is variable across space or time. Causal heterogeneity is responsible for many of the epistemic difficulties that ecologists face, especially when making generalisations and predictions. Luckily, ecologists have the tools to overcome these difficulties, though these tools have historically been considered suspect by philosophers of science. The author presents an updated philosophical account with an optimistic outlook of the methods and status of ecological research.
Get access
Type
Element
Information
Online ISBN: 9781108900010
Publisher: Cambridge University Press
Print publication: 10 August 2023

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Bibliography

Akamatsu, T., Wang, D., Wang, K., & Wei, Z. (2001). Comparison between visual and passive acoustic detection of finless porpoises in the Yangtze River, China. The Journal of the Acoustical Society of America, 109(4), 1723–7.Google Scholar
Anand, M., & Orlóci, L. (1996). Complexity in plant communities: The notion and quantification. Journal of Theoretical Biology, 179, 179–86.Google Scholar
Arthur, W.B. (1999). The End of Certainty in Economics. In: Aerts, D., Broekaert, J., Mathijs, E. (eds) Einstein Meets Magritte: An Interdisciplinary Reflection. Einstein Meets Magritte: An Interdisciplinary Reflection on Science, Nature, Art, Human Action and Society, vol 1. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-4704-0_14Google Scholar
Barkai, A., & McQuaid, C. (1988). Predator-prey role reversal in a marine benthic ecosystem. Science, 242(4875), 62–4.Google Scholar
Barnes, E. C. (2018). Prediction versus accommodation. In E. N. Zalta (Ed.), The Stanford Encyclopedia of Philosophy. https://plato.stanford.edu/archives/fall2018/entries/prediction-accommodation/Google Scholar
Barrett, J., & Stanford, P. K. (2006). Prediction. In Pfeifer, J. & Sarkar, S. (Eds.), The Philosophy of Science: An Encyclopedia (pp. 585599). Routledge.Google Scholar
Bartram, I., & Jeschke, J. (2019). Do cancer stem cells exist? A pilot study combining a systematic review with the hierarchy-of-hypotheses approach. PLoS One, 14(12), e0225898.Google Scholar
Barua, M. (2011). Mobilizing metaphors: The popular use of keystone, flagship and umbrella species concepts. Biodiversity & Conservation, 20(7), 1427–40.Google Scholar
Bascompte, J., & Solé, R. (1995). Rethinking complexity: Modelling spatiotemporal dynamics in ecology. Trends in Ecology & Evolution, 10(9), 361–6.Google Scholar
Beck, M. W. (1997). Inference and generality in ecology: Current problems and an experimental solution. Oikos, 78(2), 265–73.Google Scholar
Beckage, B., Gross, L. J., & Kauffman, S. (2011). The limits to prediction in ecological systems. Ecosphere, 2(11), 112.Google Scholar
Benincà, E., Huisman, J., Heerkloss, R. et al. (2008). Chaos in a long-term experiment with a plankton community. Nature, 451(7180), 822–5.Google Scholar
Berec, L., Angulo, E., & Courchamp, F. (2007). Multiple Allee effects and population management. Trends in Ecology & Evolution, 22(4), 185–91.Google Scholar
Bishop, R. C. (2011). Metaphysical and Epistemological Issues in Complex Systems (Hooker, C., Ed.; Vol. 10, pp. 105136). Elsevier.Google Scholar
Boakes, E. H., Fuller, R. A., McGowan, P. J. K., & Mace, G. M. (2016). Uncertainty in identifying local extinctions: The distribution of missing data and its effects on biodiversity measures. Biology Letters, 12(3), 20150824.Google Scholar
Bonenfant, C., Gaillard, J. M., Coulson, T. et al. (2009). Empirical evidence of density‐dependence in populations of large herbivores. Advances in Ecological Research, 41, 313–57.Google Scholar
Brashares, J. S., Werner, J. R., & Sinclair, A. R. E. (2010). ‘Social meltdown’ in the demise of an island endemic: Allee effects and the Vancouver Island marmot. Journal of Animal Ecology, 79(5), 967–53.Google Scholar
Brown, K., Elliott, J. I., & Kemp, J. (2015). Ship rat, stoat and possum control on mainland New Zealand [Scientific Report]. New Zealand Department of Conservation.Google Scholar
Brush, S. G. (1994). Dynamics of theory change: The role of predictions. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association, 1994(2), 133–45.Google Scholar
Cartwright, N. (1989). Nature’s Capacities and Their Measurement. Oxford University Press.Google Scholar
Casper, B. B., & Castelli, J. P. (2007). Evaluating plant-soil feedback together with competition in a serpentine grassland. Ecology Letters, 10(5), 394400.Google Scholar
Clark, A. T., Ann Turnbull, L., Tredennick, A. et al. (2019). Predicting species abundances in a grassland biodiversity experiment: Trade‐offs between model complexity and generality. Journal of Ecology, 108(2), 774–87.Google Scholar
Clarkson, K., Eden, S. F., Sutherland, W. J., & Houston, A. I. (1986). Density dependence and magpie food hoarding. Journal of Animal Ecology, 55(1), 111–21.Google Scholar
Colautti, R. I., & MacIsaac, H. J. (2004). A neutral terminology to define ‘invasive’ species. Diversity and Distributions, 10(2), 135–41.Google Scholar
Colyvan, M., & Ginzburg, L. R. (2003). Laws of nature and laws of ecology. Oikos, 101(3), 649–53.Google Scholar
Comita, L. S., Muller-Landau, H. C., Aguilar, S., & Hubbell, S. P. (2010). Asymmetric density dependence shapes species abundances in a tropical tree community. Science, 329(5989), 330–2.Google Scholar
Cooper, G. (1998). Generalizations in ecology: A philosophical taxonomy. Biology & Philosophy, 13(4), 555–86.Google Scholar
Cottee-Jones, H. E. W., & Whittaker, R. J. (2012). Perspective: The keystone species concept: A critical appraisal. Frontiers of Biogeography, 4(3), 117–27.Google Scholar
Courchamp, F., Clutton-Brock, T., & Grenfell, B. (1999). Inverse density dependence and the Allee effect. Trends in Ecology & Evolution, 14(10), 405–10.Google Scholar
Courchamp, F., Dunne, J.A., Le Maho, Y., et al. (2015). Fundamental ecology is fundamental. Trends in Ecology and Evolution, 30, 916.Google Scholar
Cuddington, K., Sobek-Swant, S., Crosthwaite, J. C., Lyons, D. B., & Sinclair, B. J. (2018). Probability of emerald ash borer impact for Canadian cities and North America: A mechanistic model. Biological Invasions, 20(9), 2661–77.Google Scholar
Dambacher, J. M., Li, H. W., & Rossignol, P. A. (2003). Qualitative predictions in model ecosystems. Ecological Modelling, 161(1–2), 7993.Google Scholar
Doak, D. F., Estes, J. A., Halpern, B. S. et al. (2008). Understanding and predicting ecological dynamics: Are major surprises inevitable? Ecology, 89(4), 952–61.Google Scholar
Donohue, I., Hillebrand, H., Montoya, J. M. et al. (2016). Navigating the complexity of ecological stability. Ecology Letters, 19(9), 1172–85.CrossRefGoogle ScholarPubMed
D’Orangeville, L., Maxwell, J., Kneeshaw, D. et al. (2018). Drought timing and local climate determine the sensitivity of eastern temperate forests to drought. Global Change Biology, 24(6), 2339–51.Google Scholar
Douglas, H. (2009). Reintroducing prediction to explanation. Philosophy of Science, 76(4), 444–63.Google Scholar
Douglas, H., & Magnus, P. D. (2013). State of the field: Why novel prediction matters. Studies in History and Philosophy of Science, 44(4), 580–9.Google Scholar
Egler, F. E. (1986). ‘Physics envy’ in ecology. Bulletin of the Ecological Society of America, 67(3), 233–5.Google Scholar
Elliott-Graves, A. (2016). The problem of prediction in invasion biology. Biology & Philosophy, 31(3), 373–93.Google Scholar
Elliott-Graves, A. (2018). Generality and causal Interdependence in ecology. Philosophy of Science, 85(1), 1102–114.Google Scholar
Elliott-Graves, A. (2020a). The value of imprecise prediction. Philosophy, Theory, and Practice in Biology, 12 (4).CrossRefGoogle Scholar
Elliott-Graves, A. (2020b). What is a target system? Biology & Philosophy, 35(2), 128.Google Scholar
Elliott-Graves, A. (2022). What are general models about? European Journal for Philosophy of Science, 12(74).Google Scholar
Elliott-Graves, A., & Weisberg, M. (2014). Idealization. Philosophy Compass, 9(3), 176–85.Google Scholar
Fahrig, Lenore, ‘Forty years of bias in habitat fragmentation research’, in Peter Kareiva, Michelle Marvier, and Brian Silliman (eds), Effective Conservation Science: Data Not Dogma (Oxford, 2017; online edn, Oxford Academic, 21 Dec. 2017), https://doi.org/10.1093/oso/9780198808978.003.0005Google Scholar
Fischer, R., Rodig, E., & Huth, A. (2018). Consequences of a reduced number of plant functional types for the simulation of forest productivity. Forests, 9(8), 460.Google Scholar
Frigg, R. (2009). Models and fiction. Synthese, 172(2), 251–68.Google Scholar
Giere, R. N. (2004). How models are used to represent reality. Philosophy of science, 71(5), 742–52.Google Scholar
Godfrey-Smith, P. (2006). The strategy of model-based science. Biology & Philosophy, 21(5), 725–40.Google Scholar
Gonzalez, W. J. (2015). Characterization of Scientific Prediction and Its Kinds in Economics (Vol. 50, pp. 4776). Springer International.Google Scholar
Grace, J. (2019). Has ecology grown up? Plant Ecology & Diversity, 12(5), 387405.Google Scholar
Gurevitch, J. et al., (2018). Meta-analysis and the science of research synthesis. Nature, 555(7695), 175–82.Google Scholar
Hansford, D. (2016). War on pests avoids targeting pets and dinner. Radio New Zealand. www.rnz.co.nz/news/on-the-inside/309756/war-on-pests-avoids-targetting-pets-and-dinner.Google Scholar
Heger, T., Aguilar, C., Bartram, I. et al. (2021). The hierarchy-of-hypotheses approach: A synthesis method for enhancing theory development in ecology and evolution. BioScience, 71(4), 337–49.Google Scholar
Heger, T., & Jeschke, J. (2014). The enemy release hypothesis as a hierarchy of hypotheses. Oikos, 123(6), 741–50. https://doi.org/10.1111/j.1600-0706.2013.01263.x.Google Scholar
Hempel, C. G., & Oppenheim, P. (1948). Studies in the logic of explanation. Philosophy of Science, 15(2), 135–75.Google Scholar
Hitchcock, C., & Sober, E. (2004). Prediction versus accommodation and the risk of overfitting. British Journal for the Philosophy of Science, 55, 134.Google Scholar
Hooker, C. (Ed.). (2011). Philosophy of Complex Systems (Vol. 10). Elsevier.Google Scholar
Hooper, D. U., Chapin, F. S. III, Ewel, J. J., et al. (2005). Effects of biodiversity on ecosystem functioning: a consensus of current knowledge. Ecological Monographs, 75(1), 335.Google Scholar
Houlahan, J., McKinney, S., Anderson, M., & McGill, B. (2017). The priority of prediction in ecological understanding. Oikos, 126(1), 17.Google Scholar
Huang, J., Mei, Z., Chen, M. et al. (2020). Population survey showing hope for population recovery of the critically endangered Yangtze finless porpoise. Biological Conservation, 241, 108315.Google Scholar
Huang, S.-L., Mei, Z., Hao, Y. et al. (2017). Saving the Yangtze finless porpoise: Time is rapidly running out. Biological Conservation, 210, 40–6.Google Scholar
Jeschke, J., Gómez Aparicio, L., Haider, S. et al. (2012). Support for major hypotheses in invasion biology is uneven and declining. NeoBiota, 14(0), 120.Google Scholar
Johnson, K. (2007). Natural history as stamp collecting: A Brief History. Archives of Natural History, 34(2), 244–58.Google Scholar
Jones, M. R. (2005). Idealization and Abstraction: A Framework. (Jones, M. R. & Cartwright, N., Eds., pp. 173217). Rodopi.Google Scholar
Justus, J. (2005). Qualitative scientific modeling and loop analysis. Philosophy of Science, 72(5), 1272–86.Google Scholar
Justus, J. (2006). Loop analysis and qualitative modeling: Limitations and merits. Biology & Philosophy, 21(5), 647–66.Google Scholar
Justus, J. (2021). The Philosophy of Ecology: An Introduction. Cambridge University Press.Google Scholar
Kaschner, K., Quick, N. J., Jewell, R., Williams, R., & Harris, C. M. (2012). Global coverage of cetacean line-transect surveys: Status quo, data gaps and future challenges. PLoS One, 7(9).Google Scholar
Kaunisto, S., Ferguson, L. V., & Sinclair, B. J. (2016). Can we predict the effects of multiple stressors on insects in a changing climate? Current Opinion in Insect Science, 17, 5561.Google Scholar
Kelly, J. F., & Horton, K. G. (2016). Toward a predictive macrosystems framework for migration ecology. Global Ecology and Biogeography, 25(10), 1159–65.Google Scholar
Kingsland, S. (1995). Modeling Nature. University of Chicago Press.Google Scholar
Kingsland, S. (2005). The Evolution of American Ecology, 1890–2000. JHU Press.Google Scholar
Kitcher, P. (1981). Explanatory unification. Philosophy of Science, 48(4), 507–31.Google Scholar
Klironomos, J. N. (2002). Feedback with soil biota contributes to plant rarity and invasiveness in communities. Nature, 417(6884), 6770.Google Scholar
Knuuttila, T., & Loettgers, A. (2016a). Modelling as indirect representation? The Lotka– Volterra Model revisited. British Journal for the Philosophy of Science, axv055-30. https://doi.org/10.1093/bjps/axv055.Google Scholar
Knuuttila, T., & Loettgers, A. (2016b). Model templates within and between disciplines: From magnets to gases – and socio-economic systems. European Journal for Philosophy of Science, 6(3), 377400. https://doi.org/10.1007/s13194-016-0145-1.Google Scholar
Koricheva, J., Gurevitch, J., & Mengersen, K. (Eds.). (2013). Handbook of Meta-analysis in Ecology and Evolution. Princeton University Press.Google Scholar
Kulmatiski, A., Heavilin, J., & Beard, K. H. (2011). Testing predictions of a three-species plant-soil feedback model. Journal of Ecology, 99(2), 542–50.Google Scholar
Ladyman, J., Lambert, J., & Wiesner, K. (2013). What is a complex system? European Journal for Philosophy of Science, 3, 3367.CrossRefGoogle Scholar
Lange, M. (2005). Ecological laws: What would they be and why would they matter? Oikos, 110(2), 394403.Google Scholar
Lawton, J. H. (1999). Are there general laws in ecology? Oikos, 84(2), 177–92.Google Scholar
Levins, R. (1993). A response to Orzack and Sober: Formal analysis and the fluidity of science. The Quarterly Review of Biology, 68(4), 547–55. https://doi.org/10.1086/418302.Google Scholar
Levin, S. A. (1998). Ecosystems and the biosphere as complex adaptive systems. Ecosystems, 1(5), 431–6.Google Scholar
Levin, S. A. (2002). Complex adaptive systems: Exploring the known, the unknown and the unknowable. Bulletin of the American Mathematical Society, 40(1), 319.Google Scholar
Levin, S. A. (2005). Self-organization and the emergence of complexity in ecological systems. BioScience, 55(12), 1075–9.Google Scholar
Levins, R. (1966). The strategy of model building in population biology. American Scientist, 54(4), 421–31.Google Scholar
Levy, A. (2018). Idealization and abstraction: Refining the distinction. Synthese, 13(1), 118.Google Scholar
Linquist, S., Gregory, T. R., Elliott, T. A., et al. 2016. “Yes! there are resilient generalizations (or ‘laws’) in ecology.Quarterly Review of Biology, 91(2): 119–31. http://doi.org/10.1086/686809.Google Scholar
Lipton, P. (2005). Testing hypotheses: Prediction and prejudice. Science, 307(5707), 219–21.Google Scholar
Lockwood, J. L., Cassey, P., & Blackburn, T. (2005). The role of propagule pressure in explaining species invasions. Trends in Ecology & Evolution, 20(5), 223–8.Google Scholar
Loreau, M., Naeem, S., Inchausti, P., et al. (2001). Biodiversity and ecosystem functioning: current knowledge and future challenges. Science, 294(5543), 804–8.Google Scholar
Maclaurin, J., & Sterelny, K. (2008). What Is Biodiversity? University of Chicago Press.CrossRefGoogle Scholar
Marquet, P. A., Allen, A. P., Brown, J. H. et al. (2014). On theory in ecology. BioScience, 64(8), 701–10.Google Scholar
Marshall, K. E., & Sinclair, B. J. (2012). Threshold temperatures mediate the impact of reduced snow cover on overwintering freeze-tolerant caterpillars. Naturwissenschaften, 99(1), 3341.Google Scholar
Matthewson, J. (2011). Trade-offs in model-building: A more target-oriented approach. Studies in History and Philosophy of Science Part A, 42(2), 324–33.Google Scholar
May, R.M. (1973). Stability and Complexity in Model Ecosystems. Princeton University Press.Google Scholar
McCann, K. S. (2000). The diversity-stability debate. Nature, 405(6783), 228–33. https://doi.org/10.1038/35012234.Google Scholar
McIntosh, R. P. (1987). Pluralism in ecology. Annual Review of Ecology and Systematics, 18(1), 321–41.Google Scholar
McShea, D. W., & Brandon, R. N. (2010). Biology’s First Law. University of Chicago Press.Google Scholar
Miller, J. H., & Page, S. E. (2009). Complex Adaptive Systems. Princeton University Press.Google Scholar
Mills, L. S., & Doak, D. F. (1993). The keystone-species concept in ecology and conservation. BioScience, 43(4), 219–24.Google Scholar
Mitchell, Sandra D. (2000). Dimensions of scientific law. Philosophy of Science 67 (2):242265.Google Scholar
Mitchell, S. D. (2003). Biological Complexity and Integrative Pluralism. Cambridge University Press.Google Scholar
Mitchell, S. D. (2009). Unsimple Truths. University of Chicago Press.Google Scholar
Morgan, M. S. (2005). Experiments versus models: New phenomena, inference and surprise. Journal of Economic Methodology, 12(2), 317–29. http://doi.org/10.1080/13501780500086313.Google Scholar
Morgan, M. S., & Morisson, M. (1999). Models as Mediators. Cambridge University Press.Google Scholar
Novak, M., Wootton, J. T., Doak, D. F. et al. (2011). Predicting community responses to perturbations in the face of imperfect knowledge and network complexity. Ecology, 92(4), 836–46.Google Scholar
Odenbaugh, J. (2003). Complex systems, trade‐offs, and theoretical population biology: Richard Levins’s ‘strategy of model building in population biology’ revisited. Philosophy of Science (Proceedings), 70(5), 1496–507.Google Scholar
Odenbaugh, J. (2011). Complex Ecological Systems (Hooker, C., Ed., Vol. 10, pp. 421431). Elsevier.Google Scholar
Orzack, S. H. (2005). Discussion: What, if anything, is ‘The strategy of model building in population biology?’ A comment on Levins (1966) and Odenbaugh (2003). Philosophy of Science, 72(3), 479–85.Google Scholar
Orzack, S. H., & Sober, E. (1993). A critical assessment of Levins’s the strategy of model building in population biology (1966). The Quarterly Review of Biology, 68(4), 533–46.Google Scholar
Parke, E. (2014). Experiments, simulations, and epistemic privilege. Philosophy of Science, 81(4), 516–36.Google Scholar
Parker, J., Burkepile, D. E., & Hay, M. E. (2006). Opposing effects of native and exotic herbivores on plant invasions. Science, 311(5766), 1459–61.Google Scholar
Parker, W. (2010). Predicting weather and climate: Uncertainty, ensembles and probability. Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics, 41(3), 263–72.Google Scholar
Parker, W., & Risbey, J. S. (2015). False precision, surprise and improved uncertainty assessment. Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 373(2055), 20140453.Google Scholar
Parrish, J. K., & Edelstein-Keshet, L. (1999). Complexity, pattern, and evolutionary trade-offs in animal aggregation. Science, 284(5411), 99101.Google Scholar
Parrott, L. (2010). Measuring ecological complexity. Ecological Indicators, 10(6), 1069–76.Google Scholar
Peters, D., Bestelmeyer, B., & Herrick, J. 2006. Disentangling complex landscapes: New insights into arid and semiarid system dynamics. BioScience, 56(6), 491501.CrossRefGoogle Scholar
Peters, R. H. (1991). A Critique for Ecology. Cambridge University Press.Google Scholar
Phillips, R. P., Ibanez, I., & D’Orangeville, L. (2016). A belowground perspective on the drought sensitivity of forests: Towards improved understanding and simulation. Forest Ecology and Management, 380, 309–20.Google Scholar
Pine, W. E., Pollock, K. H., Hightower, J. E., Kwak, T. J., & Rice, J. A. (2003). A review of tagging methods for estimating fish population size and components of mortality. Fisheries, 28(10), 1023.Google Scholar
Potochnik, A. (2017). Idealization and the Aims of Science. University of Chicago Press.Google Scholar
Proctor, J. D., & Larson, M. (2005). Ecology, complexity, and metaphor. BioScience, 55(12), 1065–8.Google Scholar
Raerinne, J. (2011). Causal and mechanistic explanations in ecology. Acta Biotheoretica, 59 251–71.Google Scholar
Ramsey, D. S. L., Forsyth, D. M., Veltman, C. J. et al. (2012). An approximate Bayesian algorithm for training fuzzy cognitive map models of forest responses to deer control in a New Zealand adaptive management experiment. Ecological Modelling, 240, 93104.Google Scholar
Ramsey, D. S. L., & Veltman, C. J. (2005). Predicting the effects of perturbations on ecological communities: What can qualitative models offer? Journal of Animal Ecology, 74(5), 905–16.Google Scholar
Ricklefs, R. E., & Miller, G. L. (2000). Ecology. Freeman and Company. Recovery Strategy for the Vancouver Island Marmot (Marmota vancouverensis) in British Columbia. Prepared for the B.C. Ministry of Environment, Victoria, BC. 25 pp.Google Scholar
Rind, D. (1999). Complexity and climate. Science, 284(5411), 105–7.Google Scholar
Rosenberg, A. (1989). Are generic predictions enough? Philosophy of Economics: Proceedings, Munich, July 1981 (Vol. 2). Springer Science & Business Media.Google Scholar
Salmon, M. H., Earman, J., Glymour, C., & Lennox, J. G. (1992). Introduction to the Philosophy of Science. Hackett.Google Scholar
Salmon, W. C. (2006). Four Decades of Scientific Explanation. University of Pittsburgh Press.Google Scholar
Santana, C. (2014). Save the planet: Eliminate biodiversity. Biology & Philosophy, 29(6), 761–80.Google Scholar
Scerri, E. R. (2006). The Periodic Table: Its Story and Its Significance. Oxford University Press.Google Scholar
Scerri, E. R., & Worrall, J. (2001). Prediction and the periodic table. Studies in History and Philosophy of Science Part A, 32(3), 407–52.Google Scholar
Schindler, D. E., & Hilborn, R. (2015). Prediction, precaution, and policy under global change. Science, 347(6225), 953–4.Google Scholar
Shrader-Frechette, K. S. & McCoy, E. D. (1993). Method in ecology: strategies for conservation. New York, NY, USA: Cambridge University Press. Edited by Earl D. McCoy.Google Scholar
Simon, H. A. (1962). The architecture of complexity. Proceedings of the American Philosophical Society, 106(6), 467–82.Google Scholar
Sinclair, B. J., Jako Klok, C., Scott, M. B., Terblanche, J. S., & Chown, S. L. (2003). Diurnal variation in supercooling points of three species of Collembola from Cape Hallett, Antarctica. Journal of Insect Physiology, 49(11), 1049–61.Google Scholar
Sinclair, B. J., Vernon, P., Jaco Klok, C., & Chown, S. L. (2003). Insects at low temperatures: An ecological perspective. Trends in Ecology & Evolution, 18(5), 257–62.Google Scholar
Singer, M. C., & Parmesan, C. (2018). Lethal trap created by adaptive evolutionary response to an exotic resource. Nature, 557(7704), 238–41.Google Scholar
Smith, L. A., & Stern, N. (2011). Uncertainty in science and its role in climate policy. Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 369(1956), 4818–41.Google Scholar
Sobek-Swant, S., Kluza, D. A., Cuddington, K., & Lyons, D. B. (2012). Potential distribution of emerald ash borer: What can we learn from ecological niche models using Maxent and GARP? Forest Ecology and Management, 281, 2331.Google Scholar
Sober, E. (2011). A priori causal models of natural selection. Australasian Journal of Philosophy, 89(4), 571–89.Google Scholar
Stegenga, J. (2011). Is meta-analysis the platinum standard of evidence? Studies in History and Philosophy of Biological and Biomedical Sciences, 42(4), 497507.Google Scholar
Stenseth, N. C. (1999). Population cycles in voles and lemmings: Density dependence and phase dependence in a Stochastic world. Oikos, 87(3), 427–61.Google Scholar
Stillman, R. A., Railsback, S. F., Giske, J., Berger, U., & Grimm, V. (2015). Making predictions in a changing world: The benefits of individual-based ecology. BioScience, 65(2), 140–50.Google Scholar
Stockwell, D. (1999). The GARP modelling system: Problems and solutions to automated spatial prediction. International Journal of Geographical Information Science, 13(2), 143–58.Google Scholar
Storch, D., & Gaston, K. J. (2004). Untangling ecological complexity on different scales of space and time. Basic and Applied Ecology, 5(5), 389400.Google Scholar
Strevens, M. (2004). The causal and unification approaches to explanation unified – causally. Noûs, 38(1), 154–76.Google Scholar
Suding, K. N., Stanley Harpole, W., Fukami, T. et al. (2013). Consequences of plant-soil feedbacks in invasion. Journal of Ecology, 101(2), 298308.Google Scholar
Tang, Y., Wu, Y., Liu, K. et al. (2019). Investigating the distribution of the Yangtze finless porpoise in the Yangtze River using environmental DNA. PLoS One, 14(8).Google Scholar
Têmkin, I. (2021) Phenomenological Levels in Biological and Cultural Evolution in Brooks, DiFrisco, D. S., J., & Wimsatt, W. C. (Eds.). (2021). Levels of organization in the biological sciences. MIT Press. 297316Google Scholar
Thiengo, S. C., Faraco, F. A., Salgado, N. C., Cowie, R. H., & Fernandez, M. A. (2007). Rapid spread of an invasive snail in South America: The giant African snail, Achatina fulica, in Brasil. Biological Invasions, 9(6), 693702.Google Scholar
Tompkins, D. M., & Veltman, C. J. (2006). Unexpected consequences of vertebrate pest control: Predictions from a four-species community model. Ecological Applications: A Publication of the Ecological Society of America, 16(3), 1050–61.Google Scholar
Travis, J., Coleman, F. C., & Auster, P. J. (2014). Integrating the invisible fabric of nature into fisheries management. Proceedings of the National Academy of Sciences of the United States of America, 111(2), 581–4.Google Scholar
Turchin, P. (2001). Does population ecology have general laws? Oikos, 94(1), 1726.Google Scholar
Tyne, J. A., Loneragan, N. R., Johnston, D. W. et al. (2016). Evaluating monitoring methods for cetaceans. Biological Conservation, 201, 252–60.Google Scholar
USDA Forest Service. (2020). Emerald Ash Borer. Emerald Ash Borer Information Network. www.emeraldashborer.info/.Google Scholar
Valéry, L., Fritz, H., & Lefeuvre, J. C. (2013). Another call for the end of invasion biology. Oikos, 122(8), 1143–6.Google Scholar
Valls, A., Coll, M., & Christensen, V. (2015). Keystone species: Toward an operational concept for marine biodiversity conservation. Ecological Monographs, 85(1), 2947.Google Scholar
van der Putten, W. H., Bardgett, R. D., Bever, J. D. et al. (2013). Plant-soil feedbacks: The past, the present and future challenges. Journal of Ecology, 101(2), 265–76.Google Scholar
Van Fraassen, B. C. (2008). Scientific Representation: Paradoxes of Perspective (Vol. 70). Oxford University Press.Google Scholar
Wang, L., & Jackson, D. A. (2014). Shaping up model transferability and generality of species distribution modeling for predicting invasions: Implications from a study on Bythotrephes longimanus. Biological Invasions, 16(10), 2079–103.Google Scholar
Ward, E. J., Holmes, E. E., Thorson, J. T., & Collen, B. (2014). Complexity is costly: A meta-analysis of parametric and non-parametric methods for short-term population forecasting. Oikos, 123(6), 652–61.Google Scholar
Weisberg, M. (2004). Qualitative theory and chemical explanation. Philosophy of Science, 71(5), 1071–81.Google Scholar
Weisberg, M. (2006). Forty years of ‘the strategy’: Levins on model building and idealization. Biology & Philosophy, 21, 623–45.Google Scholar
Weisberg, M. (2007). Three kinds of idealization. The Journal of Philosophy, 639659.Google Scholar
Weisberg, M. (2013). Simulation and Similarity. Oxford University Press USA.Google Scholar
Weng, G., Bhalla, U. S., & Iyengar, R. (1999). Complexity in biological signaling systems. Science, 284(5411), 92–6.Google Scholar
Wenger, S. J., & Olden, J. D. (2012). Assessing transferability of ecological models: An underappreciated aspect of statistical validation. Methods in Ecology and Evolution, 3(2), 260–7.Google Scholar
Whitesides, G. M., & Ismagilov, R. F. (1999). Complexity in chemistry. Science, 284(5411), 8992.Google Scholar
Wilcox, C. (2018, 27 August). When snails attack: The epic discovery of an ecological Phenomenon. Discover. www.discovermagazine.com/planet-earth/when-snails-attack-the-epic-discovery-of-an-ecological-phenomenon.Google Scholar
Wimsatt, W. C. (1972). Complexity and organization. Proceedings of the Biennial Meeting of the Philosophy of Science Association, 1972, 6786.Google Scholar
Winther, R. G. (2011). Prediction in selectionist evolutionary theory. Philosophy of Science, 76(5), 889901.Google Scholar
Woodward, J. (2001). Law and explanation in biology: Invariance is the kind of stability that matters. Philosophy of Science, 68(1), 120.Google Scholar
Woodward, J. (2010). Causation in biology: Stability, specificity, and the choice of levels of explanation. Biology & Philosophy, 25(3), 287318.Google Scholar

Save element to Kindle

To save this element to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Ecological Complexity
Available formats
×

Save element to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Ecological Complexity
Available formats
×

Save element to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Ecological Complexity
Available formats
×