Article open access publication

Biotic interactions in species distribution modelling: 10 questions to guide interpretation and avoid false conclusions

Global Ecology and Biogeography, Wiley, ISSN 1466-8238

Volume 27, 9, 2018

DOI:10.1111/geb.12759, Dimensions: pub.1105804586,



  1. (1) University of Freiburg, grid.5963.9
  2. (2) University of Hamburg, grid.9026.d
  3. (3) University of Canterbury, grid.21006.35
  4. (4) University of Florida, grid.15276.37
  5. (5) University of Regensburg, grid.7727.5
  6. (6) Swiss Federal Institute for Forest, Snow and Landscape Research, grid.419754.a
  7. (7) University of Hohenheim, grid.9464.f
  8. (8) Philipp University of Marburg, grid.10253.35
  9. (9) Senckenberg Biodiversity and Climate Research Centre (BiK‐F), Frankfurt (Main), Germany
  10. (10) University of Koblenz and Landau, grid.5892.6
  11. (11) Aarhus University, grid.7048.b, AU
  12. (12) University of Erlangen-Nuremberg, grid.5330.5
  13. (13) Stockholm University, grid.10548.38
  14. (14) Alfred Wegener Institute for Polar and Marine Research, grid.10894.34
  15. (15) Carl von Ossietzky University of Oldenburg, grid.5560.6


Recent studies increasingly use statistical methods to infer biotic interactions from co‐occurrence information at a large spatial scale. However, disentangling biotic interactions from other factors that can affect co‐occurrence patterns at the macroscale is a major challenge. We present a set of questions that analysts and reviewers should ask to avoid erroneously attributing species association patterns to biotic interactions. Our questions relate to the appropriateness of data and models, the causality behind a correlative signal, and the problems associated with static data from dynamic systems. We summarize caveats reported by macroecological studies of biotic interactions and examine whether conclusions on the presence of biotic interactions are supported by the modelling approaches used. Irrespective of the method used, studies that set out to test for biotic interactions find statistical associations in species’ co‐occurrences. Yet, when compared with our list of questions, few purported interpretations of such associations as biotic interactions hold up to scrutiny. This does not dismiss the presence or importance of biotic interactions, but it highlights the risk of too lenient interpretation of the data. Combining model results with information from experiments and functional traits that are relevant for the biotic interaction of interest might strengthen conclusions. Moving from species‐ to community‐level models, including biotic interactions among species, is of great importance for process‐based understanding and forecasting ecological responses. We hope that our questions will help to improve these models and facilitate the interpretation of their results. In essence, we conclude that ecologists have to recognize that a species association pattern in joint species distribution models will be driven not only by real biotic interactions, but also by shared habitat preferences, common migration history, phylogenetic history and shared response to missing environmental drivers, which specifically need to be discussed and, if possible, integrated into models.


Research Categories

Main Subject Area

Links & Metrics

NORA University Profiles

Aarhus University

Dimensions Citation Indicators

Times Cited: 44

Field Citation Ratio (FCR): 17.89

Open Access Info

Green, Submitted