1 of 10

Evidence Synthesis in the Biological and Natural Sciences: Discipline-Specific Challenges and Opportunities for Librarian Engagement

Isobel Flindall (they/them) & Ian Gordon (he/him)

​

​

2 of 10

Research questions

  • What distinctions or peculiarities do researchers in the natural and biological sciences encounter using evidence synthesis methodologies?
  • How can academic librarians best support researchers that utilize evidence synthesis research designs?

​

​

3 of 10

Evidence synthesis training 1

What we found:

  • A wide range of experiences, most researchers learn informally, by doing, mentorship, etc., and not through formal training. 
  • “...mostly shooting from the hip.” 

4 of 10

Evidence synthesis training 2

How librarians can help:

  • Establish formal training opportunities and/or adapt preexisting training opportunities to serve the biological/natural sciences.
  • Proactively promote library supports and training opportunities.

​

5 of 10

Disciplinary nuances 1

What we found:

  • The variety of data types, sample sizes, and contexts in biological/natural science research makes synthesis challenging.
  • "I think natural systems have a lot more variability between them especially in environmental systems, where there is a lot less of an ability to control things in an experimental way."

6 of 10

Disciplinary nuances 2

How librarians can help:

  • Participate in discipline-specific evidence synthesis workshops (e.g., Collaboration for Environmental Evidence).
  • Study and promote the applicability of emerging disciplinary conducting and reporting standards.

7 of 10

Stages of evidence synthesis 1

What we found:

  • Researchers are more confident with quality of data assessment, risk of bias assessment, data selection, and synthesizing results.
  • Researchers are less confident with database selection, article/citation screening, drafting questions, search strategies, and citation/export management.

​

​

8 of 10

Stages of evidence synthesis 2

How librarians can help:

  • Participate in evidence synthesis trainings (e.g., Evidence Synthesis Institute Canada).
  • Identify your institutional researchers' needs and target support accordingly.
  • Review the Responsible use of AI in evidence SynthEsis recommendations (RAISE) and stay up to date with the quickly evolving Generative AI landscape.

9 of 10

Further reading

  • Boden, C., Bolton, S., & Gerrard, A. (2025). Health Sciences and Beyond: An Investigation into Canadian Librarian Participation in Systematic Reviews Across Disciplines. College & Research Libraries, 86(1), 79-100. https://doi.org/10.5860/crl.86.1.79 
  • Fabiano, N., et al. (2024). How to optimize the systematic review process using AI tools. JCPP Advances, 4(2), e12234. https://doi.org/10.1002/jcv2.12234
  • Flemyng, E., Norl-Storr, A., Macura, B., Gartlehner, G., Thomas, J., Meerpohl, J. J., Jordan, Z., Minx, J., Eisele-Metzger, A., Hamel, C., Jemioło, P., Porritt, K., & Grainger, M. (2025). Position statement on artificial intelligence (AI) use in evidence synthesis across Cochrane, the Campbell Collaboration, JBI and the Collaboration for Environmental Evidence 2025. Cochrane Database Systematic Reviews. https://doi.org/10.1002/14651858.ED000178 
  • Kallaher, A., et al. (2020). Library systematic review service supports evidence-based practice outside of medicine. Journal of Academic Librarianship, 46(6). https://doi.org/10.1016/j.acalib.2020.102222 
  • Scott, M. C., & Vogus, B. (2022). Academic librarians and systematic reviews: trends and services. Public Services Quarterly, 18(3), 202–208. https://doi.org/10.1080/15228959.2022.2086664 
  • Siemens, W., Von Elm, E., Binder, H., Böhringer, D., Eisele-Metzger, A., Gartlehner, G., Hanegraaf, P., Metzendorf, M.-I., Mosselman, J.-J., Nowak, A., Qureshi, R., Thomas, J., Waffenschmidt, S., Labonté, V., & Meerpohl, J. J. (2025). Opportunities, challenges and risks of using artificial intelligence for evidence synthesis. BMJ Evidence-Based Medicine, 30(6), 381–384. https://doi.org/10.1136/bmjebm-2024-113320 
  • Thomas J, Hair K, Noel-Storr, A. et al. Responsible use of AI in evidence SynthEsis (RAISE): recommendations for practice (version 3; updated 13 March 2026). In: Open Science Framework [https://osf.io/], Washington DC: Center for Open Science. https://doi.org/10.17605/OSF.IO/FWAUD

10 of 10

Publication details & Contact info

Isobel (iflindal@uwo.ca) & Ian (igordon@brocku.ca)

​

​

​

​

​

​

Flindall, I., Vlahiotis, K., & Gordon, I. D. (2026). Evidence synthesis in the biological and natural sciences: Discipline-specific challenges and opportunities for librarian engagement. Science & Technology Libraries. 45. http://dx.doi.org/10.1080/0194262X.2026.2662996

​Brock Digital Repository:​

https://brocku.scholaris.ca/items/05ed9275-b54d-422e-8a60-66b949fab27d

​