A guide to ecosystem models and their environmental applications (original) (raw)

References

  1. Lindenmayer, D. et al. The complementarity of single-species and ecosystem-oriented research in conservation research. Oikos 116, 1220–1226 (2007).
    Article Google Scholar
  2. Skern-Mauritzen, M. et al. Ecosystem processes are rarely included in tactical fisheries management. Fish Fish. 17, 165–175 (2016).
    Article Google Scholar
  3. Geary, W. L., Nimmo, D. G., Doherty, T. S., Ritchie, E. G. & Tulloch, A. I. T. Threat webs: reframing the co‐occurrence and interactions of threats to biodiversity. J. Appl. Ecol. 56, https://doi.org/10.1111/1365-2664.13427 (2019).
  4. Buckley, Y. M. & Han, Y. Managing the side effects of invasion control. Science 344, 975–976 (2014).
    Article CAS Google Scholar
  5. Zavaleta, E. S., Hobbs, R. J. & Mooney, H. A. Viewing invasive species removal in a whole-ecosystem context. Trends Ecol. Evol. 16, 454–459 (2001).
    Article Google Scholar
  6. DeFries, R. & Nagendra, H. Ecosystem management as a wicked problem. Science 356, 265–270 (2017).
    Article CAS Google Scholar
  7. Carpenter, S. R. et al. Early warnings of regime shifts: a whole-ecosystem experiment. Science 332, 1079 (2011).
    Article CAS Google Scholar
  8. Evans, M. C., Davila, F., Toomey, A. & Wyborn, C. Embrace complexity to improve conservation decision making. Nat. Ecol. Evol. 1, 1588 (2017).
    Article Google Scholar
  9. Dorresteijn, I. et al. Incorporating anthropogenic effects into trophic ecology: predator–prey interactions in a human-dominated landscape. Proc. R. Soc. B, https://doi.org/10.1098/rspb.2015.1602 (2015).
  10. Didham, R. K., Tylianakis, J. M., Gemmell, N. J., Rand, T. A. & Ewers, R. M. Interactive effects of habitat modification and species invasion on native species decline. Trends Ecol. Evol. 22, 489–496 (2007).
    Article Google Scholar
  11. Brown, C. J., Saunders, M. I., Possingham, H. P. & Richardson, A. J. Managing for interactions between local and global stressors of ecosystems. PLoS ONE 8, e65765 (2013).
    Article CAS Google Scholar
  12. Peters, D. P. C. & Okin, G. S. A Toolkit for ecosystem ecologists in the time of big science. Ecosystems 20, 259–266 (2017).
    Article Google Scholar
  13. Fulton, E. A. Approaches to end-to-end ecosystem models. J. Mar. Syst. 81, 171–183 (2010).
    Article Google Scholar
  14. Waltner-Toews, D., Kay James, J., Neudoerffer, C. & Gitau, T. Perspective changes everything: managing ecosystems from the inside out. Front. Ecol. Environ. 1, 23–30 (2003).
    Article Google Scholar
  15. Evans, M. R., Norris, K. J. & Benton, T. G. Predictive ecology: systems approaches. Philos. Trans. R. Soc. B 367, 163–169 (2012).
    Article Google Scholar
  16. Smith, A. D. M., Fulton, E. J., Hobday, A. J., Smith, D. C. & Shoulder, P. Scientific tools to support the practical implementation of ecosystem-based fisheries management. ICES J. Mar. Sci. 64, 633–639 (2007).
    Article Google Scholar
  17. Baker, C. M. et al. A novel approach to assessing the ecosystem-wide impacts of reintroductions. Ecol. Appl. 29, https://doi.org/10.1002/eap.1811 (2018).
  18. Purves, D. et al. Ecosystems: time to model all life on Earth. Nature 493, 295 (2013).
    Article CAS Google Scholar
  19. Sutherland, W. J. Predicting the ecological consequences of environmental change: a review of the methods. J. Appl. Ecol. 43, 599–616 (2006).
    Article Google Scholar
  20. Seidl, R. To model or not to model, that is no longer the question for ecologists. Ecosystems 20, 222–228 (2017).
    Article Google Scholar
  21. Rastetter, E. B. Modeling for understanding v. modeling for numbers. Ecosystems 20, 215–221 (2017).
    Article Google Scholar
  22. Yates, K. L. et al. Outstanding challenges in the transferability of ecological models. Trends Ecol. Evol. 33, 790–802 (2018).
    Article Google Scholar
  23. Schweiger, E. W., Grace, J. B., Cooper, D., Bobowski, B. & Britten, M. Using structural equation modeling to link human activities to wetland ecological integrity. Ecosphere 7, e01548 (2016).
    Article Google Scholar
  24. Evans, M. R. Modelling ecological systems in a changing world. Philos. Trans. R. Soc. B 367, 181–190 (2012).
    Article Google Scholar
  25. Fulton, E. A., Smith, A. D. M. & Johnson, C. R. Effect of complexity on marine ecosystem models. Mar. Ecol. Prog. Ser. 253, 1–16 (2003).
    Article Google Scholar
  26. Lotze, H. K. et al. Global ensemble projections reveal trophic amplification of ocean biomass declines with climate change. Proc. Natl Acad. Sci. USA 116, 12097–12912 (2019).
    Article CAS Google Scholar
  27. Lindenmayer, D. et al. A checklist for ecological management of landscapes for conservation. Ecol. Lett. 11, 78–91 (2007).
    Google Scholar
  28. Guillera-Arroita, G. et al. Is my species distribution model fit for purpose? Matching data and models to applications. Glob. Ecol. Biogeogr. 24, 276–292 (2015).
    Article Google Scholar
  29. Levins, R. The strategy of model building in population biology. Am. Sci. 54, 421–431 (1966).
    Google Scholar
  30. Dambacher, J. M., Li, H. W. & Rossignol, P. A. Qualitative predictions in model ecosystems. Ecol. Model. 161, 79–93 (2003).
    Article Google Scholar
  31. Baker, C. M., Holden, M. H., Plein, M., McCarthy, M. A. & Possingham, H. P. Informing network management using fuzzy cognitive maps. Biol. Conserv. 224, 122–128 (2018).
    Article Google Scholar
  32. Dexter, N., Ramsey, D. S., MacGregor, C. & Lindenmayer, D. Predicting ecosystem wide impacts of wallaby management using a fuzzy cognitive map. Ecosystems 15, 1363–1379 (2012).
    Article Google Scholar
  33. 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).
    Article CAS Google Scholar
  34. McDonald-Madden, E. et al. Using food-web theory to conserve ecosystems. Nat. Commun. 7, 10245 (2016).
    Article CAS Google Scholar
  35. Harfoot, M. B. et al. Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model. PLoS Biol. 12, e1001841 (2014).
    Article CAS Google Scholar
  36. Fulton, E. A. et al. Lessons in modelling and management of marine ecosystems: the Atlantis experience. Fish Fish. 12, 171–188 (2011).
    Article Google Scholar
  37. Priester, C. R., Melbourne-Thomas, J., Klocker, A. & Corney, S. Abrupt transitions in dynamics of a NPZD model across Southern Ocean fronts. Ecol. Model. 359, 372–382 (2017).
    Article CAS Google Scholar
  38. McCann, R. K., Marcot, B. G. & Ellis, R. Bayesian belief networks: applications in ecology and natural resource management. Can. J. Res. 36, 3053–3062 (2006).
    Article Google Scholar
  39. Bode, M. et al. Revealing beliefs: using ensemble ecosystem modelling to extrapolate expert beliefs to novel ecological scenarios. Methods Ecol. Evol. 8, 1012–1021 (2017).
    Article Google Scholar
  40. Lester, R. E. & Fairweather, P. G. Ecosystem states: creating a data-derived, ecosystem-scale ecological response model that is explicit in space and time. Ecol. Model. 222, 2690–2703 (2011).
    Article CAS Google Scholar
  41. Lester, R. E., Fairweather, P. G., Webster, I. T. & Quin, R. A. Scenarios involving future climate and water extraction: ecosystem states in the estuary of Australia’s largest river. Ecol. Appl. 23, 984–998 (2013).
    Article Google Scholar
  42. Dubois, D. M. A model of patchiness for prey–predator plankton populations. Ecol. Model. 1, 67–80 (1975).
    Article Google Scholar
  43. Pauly, D., Christensen, V. & Walters, C. Ecopath, Ecosim, and Ecospace as tools for evaluating ecosystem impact of fisheries. ICES J. Mar. Sci. 57, 697–706 (2000).
    Article Google Scholar
  44. Fulton, E. A., Smith, A. D., Smith, D. C. & Johnson, P. An integrated approach is needed for ecosystem based fisheries management: insights from ecosystem-level management strategy evaluation. Plos ONE 9, e84242 (2014).
    Article CAS Google Scholar
  45. Tulloch, V. J. D., Plagányi, É. E., Brown, C., Richardson, A. J. & Matear, R. Future recovery of baleen whales is imperiled by climate change. Glob. Change Biol. 25, 1263–1281 (2019).
    Article Google Scholar
  46. Rodríguez, J. P. et al. A practical guide to the application of the IUCN Red List of Ecosystems criteria. Philos. Trans. R. Soc. B 370, 20140003 (2015).
    Article Google Scholar
  47. Crabtree, S. A., Bird, D. W. & Bird, R. B. Subsistence transitions and the simplification of ecological networks in the Western Desert of Australia. Hum. Ecol. 47, https://doi.org/10.1007/s10745-019-0053-z (2019).
  48. Planque, B. Projecting the future state of marine ecosystems, “la grande illusion”? ICES J. Mar. Sci. 73, 204–208 (2015).
    Article Google Scholar
  49. Walters, C. & Maguire, J.-J. Lessons for stock assessment from the northern cod collapse. Rev. Fish. Biol. Fish. 6, 125–137 (1996).
    Google Scholar
  50. García-Díaz, P. et al. A concise guide to developing and using quantitative models in conservation management. Conserv. Sci. Pract. 1, e11 (2019).
    Article Google Scholar
  51. Morse, N. et al. Novel ecosystems in the Anthropocene: a revision of the novel ecosystem concept for pragmatic applications. Ecol. Soc. 19, https://doi.org/10.5751/ES-06192-190212 (2014).
  52. Fulton, E. & Gorton, R. Adaptive Futures for SE Australian Fisheries & Aquaculture: Climate Adaptation Simulations (FRDC/CSIRO, 2014).
  53. Kurz, W. A. et al. Mountain pine beetle and forest carbon feedback to climate change. Nature 452, 987 (2008).
    Article CAS Google Scholar
  54. Plagányi, É. E. Models for an Ecosystem Approach to Fisheries (FAO, 2007).
  55. Hunter, D. O., Britz, T., Jones, M. & Letnic, M. Reintroduction of Tasmanian devils to mainland Australia can restore top-down control in ecosystems where dingoes have been extirpated. Biol. Conserv. 191, 428–435 (2015).
    Article Google Scholar
  56. Baker, C., Bode, M. & McCarthy, M. Models that predict ecosystem impacts of reintroductions should consider uncertainty and distinguish between direct and indirect effects. Biol. Conserv. 196, 211–212 (2016).
    Article Google Scholar
  57. Bunnefeld, N., Hoshino, E. & Milner-Gulland, E. J. Management strategy evaluation: a powerful tool for conservation? Trends Ecol. Evol. 26, 441–447 (2011).
    Article Google Scholar
  58. Morello, E. B. et al. Model to manage and reduce crown-of-thorns starfish outbreaks. Mar. Ecol. Prog. Ser. 512, 167–183 (2014).
    Article Google Scholar
  59. Punt, A. E., Butterworth, D. S., de Moor, C. L., De Oliveira, J. A. A. & Haddon, M. Management strategy evaluation: best practices. Fish Fish. 17, 303–334 (2016).
    Article Google Scholar
  60. Edwards, C. T. T., Bunnefeld, N., Balme, G. A. & Milner-Gulland, E. J. Data-poor management of African lion hunting using a relative index of abundance. Proc. Natl Acad. Sci. USA 111, 539–543 (2014).
    Article CAS Google Scholar
  61. Mapstone, B. et al. Management strategy evaluation for line fishing in the Great Barrier Reef: balancing conservation and multi-sector fishery objectives. Fish. Res. 94, 315–329 (2008).
    Article Google Scholar
  62. Roemer, G. W., Donlan, C. J. & Courchamp, F. Golden eagles, feral pigs, and insular carnivores: how exotic species turn native predators into prey. Proc. Natl Acad. Sci. USA 99, 791–796 (2002).
    Article CAS Google Scholar
  63. Lurgi, M., Ritchie, E. G. & Fordham, D. A. Eradicating abundant invasive prey could cause unexpected and varied biodiversity outcomes: the importance of multispecies interactions. J. Appl. Ecol. 55, 2396–2407 (2018).
    Article Google Scholar
  64. Raymond, B., McInnes, J., Dambacher, J. M., Way, S. & Bergstrom, D. M. Qualitative modelling of invasive species eradication on subantarctic Macquarie Island. J. Appl. Ecol. 48, 181–191 (2011).
    Article Google Scholar
  65. Levins, R. Discussion paper: the qualitative analysis of partially specified systems. Ann. NY Acad. Sci. 231, 123–138 (1974).
    Article CAS Google Scholar
  66. Baker, C. M., Gordon, A. & Bode, M. Ensemble ecosystem modeling for predicting ecosystem response to predator reintroduction. Conserv. Biol. 31, 376–384 (2017).
    Article Google Scholar
  67. Amstrup, S. C. et al. Greenhouse gas mitigation can reduce sea-ice loss and increase polar bear persistence. Nature 468, 955–958 (2010).
    Article CAS Google Scholar
  68. Trifonova, N., Maxwell, D., Pinnegar, J., Kenny, A. & Tucker, A. Predicting ecosystem responses to changes in fisheries catch, temperature, and primary productivity with a dynamic Bayesian network model. ICES J. Mar. Sci. 74, 1334–1343 (2017).
    Article Google Scholar
  69. McCarthy, M. A., Andelman, S. J. & Possingham, H. P. Reliability of relative predictions in population viability analysis. Conserv. Biol. 17, 982–989 (2003).
    Article Google Scholar
  70. Jamiyansharav, K., Fernández-Giménez, M. E., Angerer, J. P., Yadamsuren, B. & Dash, Z. Plant community change in three Mongolian steppe ecosystems 1994–2013: applications to state-and-transition models. Ecosphere 9, https://doi.org/10.1002/ecs2.2145 (2018).
  71. Rayner, M. J., Hauber, M. E., Imber, M. J., Stamp, R. K. & Clout, M. N. Spatial heterogeneity of mesopredator release within an oceanic island system. Proc. Natl Acad. Sci. USA 104, 20862–20865 (2007).
    Article CAS Google Scholar
  72. Melbourne-Thomas, J. et al. Regional‐scale scenario modeling for coral reefs: a decision support tool to inform management of a complex system. Ecol. Appl. 21, 1380–1398 (2011).
    Article Google Scholar
  73. Briscoe, N. J. et al. Forecasting species range dynamics with process-explicit models: matching methods to applications. Ecol. Lett. 22, 1940–1956 (2019).
    Article Google Scholar
  74. Fordham, D. A. et al. Adapted conservation measures are required to save the Iberian lynx in a changing climate. Nat. Clim. Change 3, 899–903 (2013).
    Article Google Scholar
  75. Fedriani, J. M. et al. Assisting seed dispersers to restore oldfields: an individual‐based model of the interactions among badgers, foxes and Iberian pear trees. J. Appl. Ecol. 55, 600–611 (2018).
    Article Google Scholar
  76. Breckling, B., Müller, F., Reuter, H., Hölker, F. & Fränzle, O. Emergent properties in individual-based ecological models—introducing case studies in an ecosystem research context. Ecol. Model. 186, 376–388 (2005).
    Article Google Scholar
  77. Grimm, V., Ayllón, D. & Railsback, S. F. Next-generation individual-based models integrate biodiversity and ecosystems: yes we can, and yes we must. Ecosystems 20, 229–236 (2017).
    Article Google Scholar
  78. Walters, C., Christensen, V. & Pauly, D. Structuring dynamic models of exploited ecosystems from trophic mass-balance assessments. Rev. Fish. Biol. Fish. 7, 139–172 (1997).
    Article Google Scholar
  79. Pachzelt, A., Rammig, A., Higgins, S. & Hickler, T. Coupling a physiological grazer population model with a generalized model for vegetation dynamics. Ecol. Model. 263, 92–102 (2013).
    Article Google Scholar
  80. Pimm, S. L., Lawton, J. H. & Cohen, J. E. Food web patterns and their consequences. Nature 350, 669–674 (1991).
    Article Google Scholar
  81. Bodini, A. Reconstructing trophic interactions as a tool for understanding and managing ecosystems: application to a shallow eutrophic lake. Can. J. Fish. Aquat. Sci. 57, 1999–2009 (2000).
    Article Google Scholar
  82. Greenville, A. C., Wardle, G. M. & Dickman, C. R. Desert mammal populations are limited by introduced predators rather than future climate change. R. Soc. Open Sci. 4, https://doi.org/10.1098/rsos.170384 (2017).
  83. Pasanen‐Mortensen, M. et al. The changing contribution of top-down and bottom-up limitation of mesopredators during 220 years of land use and climate change. J. Anim. Ecol. 86, 566–576 (2017).
    Article Google Scholar
  84. Vitousek, P. M., Mooney, H. A., Lubchenco, J. & Melillo, J. M. Human domination of Earth’s ecosystems. Science 277, 494–499 (1997).
    Article CAS Google Scholar
  85. Bliege Bird, R. & Nimmo, D. Restore the lost ecological functions of people. Nat. Ecol. Evol. 2, https://doi.org/10.1038/s41559-018-0576-5 (2018).
  86. Côté, I. M., Darling, E. S. & Brown, C. J. Interactions among ecosystem stressors and their importance in conservation. Proc. R. Soc. B 283, 20152592 (2016).
    Article Google Scholar
  87. Kuijper, D. et al. Paws without claws? Ecological effects of large carnivores in anthropogenic landscapes. Proc. R. Soc. B 283, 20161625 (2016).
    Article Google Scholar
  88. Moran, D., Laycock, H. & White, P. C. L. The role of cost-effectiveness analysis in conservation decision-making. Biol. Conserv. 143, 826–827 (2010).
    Article Google Scholar
  89. Evans, M. R. et al. Predictive systems ecology. Proc. R. Soc. B 280, https://doi.org/10.1098/rspb.2013.1452 (2013).
  90. Adams, M. P. et al. Informing management decisions for ecological networks, using dynamic models calibrated to noisy time-series data. Ecol. Lett. 23, 607–619 (2020).
    Article Google Scholar
  91. Plagányi, É. E. et al. Multispecies fisheries management and conservation: tactical applications using models of intermediate complexity. Fish Fish. 15, 1–22 (2014).
    Article Google Scholar
  92. Hui, C. & Richardson, D. M. How to invade an ecological network. Trends Ecol. Evol. 34, 121–131 (2018).
    Article Google Scholar
  93. Chadès, I., Curtis, J. M. R. & Martin, T. G. Setting realistic recovery targets for two interacting endangered species, sea otter and northern abalone. Conserv. Biol. 26, 1016–1025 (2012).
    Article Google Scholar
  94. Pesendorfer, M. et al. Oak habitat recovery on California’s largest islands: scenarios for the role of corvid seed dispersal. J. Appl. Ecol. 55, 1185–1194 (2017).
    Article Google Scholar
  95. Schuwirth, N. et al. How to make ecological models useful for environmental management. Ecol. Model. 411, 108784 (2019).
    Article Google Scholar
  96. Davis, K. J., Chadès, I., Rhodes, J. R. & Bode, M. General rules for environmental management to prioritise social–ecological systems research based on a value of information approach. J. Appl. Ecol. 56, https://doi.org/10.1111/1365-2664.13425 (2019).
  97. Mokany, K. et al. Integrating modelling of biodiversity composition and ecosystem function. Oikos 125, 10–19 (2015).
    Article Google Scholar
  98. Tulloch, A. I. T., Chadès, I. & Lindenmayer, D. B. Species co-occurrence analysis predicts management outcomes for multiple threats. Nat. Ecol. Evol. 2, 465–474 (2018).
    Article Google Scholar
  99. Lohr, C. A. et al. Modeling dynamics of native and invasive species to guide prioritization of management actions. Ecosphere 8, e01822 (2017).
    Article Google Scholar
  100. Nicol, S., Fuller Richard, A., Iwamura, T. & Chadès, I. Adapting environmental management to uncertain but inevitable change. Proc. R. Soc. B 282, 20142984 (2015).
    Article Google Scholar
  101. Blanchard, J. L., Heneghan, R. F., Everett, J. D., Trebilco, R. & Richardson, A. J. From bacteria to whales: using functional size spectra to model marine ecosystems. Trends Ecol. Evol. 32, 174–186 (2017).
    Article Google Scholar
  102. Andersen, K. H., Jacobsen, N. S. & Farnsworth, K. D. The theoretical foundations for size spectrum models of fish communities. Can. J. Fish. Aquat. Sci. 73, 575–588 (2015).
    Article Google Scholar
  103. Nicol, S., Sabbadin, R., Peyrard, N. & Chadès, I. Finding the best management policy to eradicate invasive species from spatial ecological networks with simultaneous actions. J. Appl. Ecol. 54, 1989–1999 (2017).
    Article Google Scholar
  104. Milner‐Gulland, E. J., Shea, K. & Punt, A. Embracing uncertainty in applied ecology. J. Appl. Ecol. 54, 2063–2068 (2017).
    Article Google Scholar
  105. Dietze, M. C. et al. Iterative near-term ecological forecasting: needs, opportunities, and challenges. Proc. Natl Acad. Sci. USA 115, 1424–1432 (2018).
    Article CAS Google Scholar
  106. Gregr, E. J. & Chan, K. M. A. Leaps of faith: how implicit assumptions compromise the utility of ecosystem models for decision-making. BioScience 65, 43–54 (2015).
    Article Google Scholar
  107. Hill, S. L. et al. Model uncertainty in the ecosystem approach to fisheries. Fish Fish. 8, 315–336 (2007).
    Article Google Scholar
  108. Spence, M. A. et al. A general framework for combining ecosystem models. Fish Fish. 19, 1031–1042 (2018).
    Article Google Scholar
  109. Wood, S. N. & Thomas, M. B. Super-sensitivity to structure in biological models. Proc. R. Soc. B 266, 565–570 (1999).
    Article Google Scholar
  110. Runge, M. C., Converse, S. J. & Lyons, J. E. Which uncertainty? Using expert elicitation and expected value of information to design an adaptive program. Biol. Conserv. 144, 1214–1223 (2011).
    Article Google Scholar
  111. Bal, P. et al. Quantifying the value of monitoring species in multi‐species, multi‐threat systems. Methods Ecol. Evol. 9, 1706–1717 (2018).
    Article Google Scholar
  112. Fulton, E. A., Blanchard, J. L., Melbourne-Thomas, J., Plagányi, É. E. & Tulloch, V. J. D. Where the ecological gaps remain, a modelers’ perspective. Front. Ecol. Evol. 7, 424 (2019).
    Article Google Scholar
  113. Wallach, A. D. et al. Trophic cascades in 3D: network analysis reveals how apex predators structure ecosystems. Methods Ecol. Evol. 8, 135–142 (2017).
    Article Google Scholar
  114. Ruscoe, W. A. et al. Unexpected consequences of control: competitive vs. predator release in a four‐species assemblage of invasive mammals. Ecol. Lett. 14, 1035–1042 (2011).
    Article Google Scholar
  115. Bower, S. D. et al. Making tough choices: picking the appropriate conservation decision‐making tool. Conserv. Lett. 11, e12418 (2017).
    Article Google Scholar
  116. Stouffer, D. B. All ecological models are wrong, but some are useful. J. Anim. Ecol. 88, 192–195 (2019).
    Article Google Scholar
  117. Olsen, E. et al. Ecosystem model skill assessment. Yes we can! PLoS ONE 11, e0146467 (2016).
    Article CAS Google Scholar
  118. Cattarino, L. et al. Information uncertainty influences conservation outcomes when prioritizing multi‐action management efforts. J. Appl. Ecol. 55, https://doi.org/10.1111/1365-2664.13147 (2018).
  119. Greenville, A. C. et al. Biodiversity responds to increasing climatic extremes in a biome-specific manner. Sci. Total Environ. 634, 382–393 (2018).
    Article CAS Google Scholar
  120. de Visser, S. N., Freymann, B. P. & Olff, H. The Serengeti food web: empirical quantification and analysis of topological changes under increasing human impact. J. Anim. Ecol. 80, 484–494 (2011).
    Article Google Scholar
  121. Curtsdotter, A. et al. Ecosystem function in predator–prey food webs — confronting dynamic models with empirical data. J. Anim. Ecol. 88, 196–210 (2019).
    Article Google Scholar
  122. Greenville, A. C., Nguyen, V., Wardle, G. M. & Dickman, C. R. Making the most of incomplete long-term datasets: the MARSS solution. Aust. Zool. 39, 733–747 (2018).
    Article Google Scholar
  123. Tulloch, A. I. T., Chadès, I. & Possingham, H. P. Accounting for complementarity to maximize monitoring power for species management. Conserv. Biol. 27, 988–999 (2013).
    Article Google Scholar
  124. Araújo, M. B. & New, M. Ensemble forecasting of species distributions. Trends Ecol. Evol. 22, 42–47 (2007).
    Article Google Scholar
  125. Bode, M., Bode, L., Choukroun, S., James, M. K. & Mason, L. B. Resilient reefs may exist, but can larval dispersal models find them? PLoS Biol. 16, e2005964 (2018).
    Article CAS Google Scholar
  126. Tittensor, D., Coll, M. & Walker, N. D. A protocol for the intercomparison of marine fishery and ecosystem models: Fish-MIP v1.0. Geosci. Model Dev. 11, 1421–1442 (2018).
    Article Google Scholar
  127. Prowse, T. A. A. et al. An efficient protocol for the global sensitivity analysis of stochastic ecological models. Ecosphere 7, e01238 (2016).
    Article Google Scholar
  128. McGowan, C. P., Runge, M. C. & Larson, M. A. Incorporating parametric uncertainty into population viability analysis models. Biol. Conserv. 144, 1400–1408 (2011).
    Article Google Scholar
  129. Chee, Y. E. & Wintle, B. A. Linking modelling, monitoring and management: an integrated approach to controlling overabundant wildlife. J. Appl. Ecol. 47, 1169–1178 (2010).
    Article Google Scholar
  130. Plagányi, É. E. & Butterworth, D. S. The Scotia Sea krill fishery and its possible impacts on dependent predators: modeling localized depletion of prey. Ecol. Appl. 22, 748–761 (2012).
    Article Google Scholar
  131. Kinzey, D. & Punt, A. E. Multispecies and single‐species models of fish population dynamics: comparing parameter estimates. Nat. Resour. Model. 22, 67–104 (2009).
    Article Google Scholar
  132. Bode, M. & Possingham, H. Can culling a threatened species increase its chance of persisting? Ecol. Model. 201, 11–18 (2007).
    Article Google Scholar
  133. Poudel, D. & Sandal, L. K. Stochastic optimization for multispecies fisheries in the Barents Sea. Nat. Resour. Model. 28, 219–243 (2015).
    Article Google Scholar
  134. Gray, R. & Wotherspoon, S. Increasing model efficiency by dynamically changing model representations. Environ. Model. Softw. 30, 115–122 (2012).
    Article Google Scholar
  135. Punt, A. E. & Hobday, D. Management strategy evaluation for rock lobster, Jasus edwardsii, off Victoria, Australia: accounting for uncertainty in stock structure. N. Zeal. J. Mar. Freshw. Res. 43, 485–509 (2009).
    Article Google Scholar
  136. Colléter, M. et al. Global overview of the applications of the Ecopath with Ecosim modeling approach using the EcoBase models repository. Ecol. Model. 302, 42–53 (2015).
    Article Google Scholar
  137. Angelini, S. et al. An ecosystem model of intermediate complexity to test management options for fisheries: a case study. Ecol. Model. 319, 218–232 (2016).
    Article Google Scholar
  138. Tulloch, V. J., Plagányi, É. E., Matear, R., Brown, C. J. & Richardson, A. J. Ecosystem modelling to quantify the impact of historical whaling on Southern Hemisphere baleen whales. Fish. Fish. 19, 117–137 (2018).
    Article Google Scholar
  139. Geary, W. L., Ritchie, E. G., Lawton, J. A., Healey, T. R. & Nimmo, D. G. Incorporating disturbance into trophic ecology: fire history shapes mesopredator suppression by an apex predator. J. Appl. Ecol. 55, https://doi.org/10.1111/1365-2664.13125 (2018).
  140. Marcot, B. G., Holthausen, R. S., Raphael, M. G., Rowland, M. M. & Wisdom, M. J. Using Bayesian belief networks to evaluate fish and wildlife population viability under land management alternatives from an environmental impact statement. Ecol. Manag. 153, 29–42 (2001).
    Article Google Scholar
  141. Elmhagen, B., Ludwig, G., Rushton, S. P., Helle, P. & Lindén, H. Top predators, mesopredators and their prey: interference ecosystems along bioclimatic productivity gradients. J. Anim. Ecol. 79, 785–794 (2010).
    CAS Google Scholar
  142. Ritchie, E. et al. Ecosystem restoration with teeth: what role for predators? Trends Ecol. Evol. 27, 265–271 (2012).
    Article Google Scholar
  143. Borsuk, M. E., Stow, C. A. & Reckhow, K. H. A Bayesian network of eutrophication models for synthesis, prediction, and uncertainty analysis. Ecol. Model. 173, 219–239 (2004).
    Article Google Scholar
  144. Christensen, V. & Walters, C. J. Ecopath with Ecosim: methods, capabilities and limitations. Ecol. Model. 172, 109–139 (2004).
    Article Google Scholar

Download references