Towards building a sustainable future: positioning ecological modelling for impact in ecosystems management

Donald L. DeAngelis, Daniel Franco, Alan Hastings, Frank M. Hilker, Suzanne Lenhart, Frithjof Lutscher*, Natalia Petrovskaya, Sergei Petrovskii, Rebecca C. Tyson

*Corresponding author for this work

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As many ecosystems worldwide are in peril, efforts to manage them sustainably require scientific advice. While numerous researchers around the world use a great variety of models to understand ecological dynamics and their responses to disturbances, only a small fraction of these models are ever used to inform ecosystem management. There seems to be a perception that ecological models are not useful for management, even though mathematical models are indispensable in many other fields. We were curious about this mismatch, its roots, and potential ways to overcome it. We searched the literature on recommendations and best practices for how to make ecological models useful to the management of ecosystems and we searched for ‘success stories’ from the past. We selected and examined several cases where models were instrumental in ecosystem management. We documented their success and asked whether and to what extent they followed recommended best practices. We found that there is not a unique way to conduct a research project that is useful in management decisions. While research is more likely to have impact when conducted with many stakeholders involved and specific to a situation for which data are available, there are great examples of small groups or individuals conducting highly influential research even in the absence of detailed data. We put the question of modelling for ecosystem management into a socio-economic and national context and give our perspectives on how the discipline could move forward.

Original languageEnglish
Article number107
Number of pages28
JournalBulletin of Mathematical Biology
Issue number10
Early online date4 Sept 2021
Publication statusPublished - Oct 2021

Bibliographical note

Funding Information:
The authors are thankful to colleagues who pointed out the success stories and/or provided direct input with regard to the details of the corresponding studies as well as useful comments with regards to the practices used by some of the governmental agencies in their decision-making: Jean-Noel Candeau, Steve Carpenter, Edward Codling, Scott Findlay, Volker Grimm, Silvana Hudjetz, Marty Krkošek, Mark Lewis, Birgit Müller, Steve Railsback, and Axel Rossberg. The authors thank Jacoby Carter for internal review of the manuscript at USGS. The authors are very thankful to the Banff International Research Station (BIRS) for supporting workshop ‘New Mathematical Methods for Complex Systems in Ecology’ (July 28–August 2, 2019) where this study was initiated. Discussion of the early stage of the study with all the workshop participants is appreciated. This work was funded in part by NSERC Discovery Grants to RCT (RGPIN-2016-05277) and FL (RGPIN-2016-04795). DF was supported by Grant MTM2017-85054-C2-2-P (AEI/FEDER, UE). DLD was supported by the U.S. Geological Survey’s Greater Everglades Priority Ecosystem Science program. SP was supported by the RUDN University Strategic Academic Leadership Program. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Funding Information:
In the USA, the Environmental Protection Agency (EPA) is the main environmental regulatory agency and responsible for policy and regulatory decisions. Environmental models ‘[...] are becoming a key component of science that is used not only within the EPA but throughout federal agencies’ (Borg ). An example of a model used by EPA is the AQUATOX model, developed by a private company, which simulates an aquatic environment, tracking the fate and transport of pollutants and predicting the effects they will have on an ecosystem (Park et al. ; Galic et al. ; Forbes et al. ). Although AQUATOX is a complex model, it has been well enough peer reviewed and tested to meet the three issues of importance to regulatory decision-making: uncertainty, transparency, and consistency (Borg ; Galic et al. ). The work by Springborn et al. () was partially funded by USDA-APHIS and resulted in changes in inspection procedures at US ports. A list of all funding opportunities from federal agencies can be found on and are generally available to universities and private companies. The Cooperative Extension System provides funding to Land-Grant universities, in order to bring science directly to the regional and country level.

Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Society for Mathematical Biology.


  • Ecological modelling
  • Ecosystem management
  • Knowledge Translation

ASJC Scopus subject areas

  • Neuroscience(all)
  • Immunology
  • Mathematics(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Environmental Science(all)
  • Pharmacology
  • Agricultural and Biological Sciences(all)
  • Computational Theory and Mathematics


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