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

Title data

Dormann, Carsten F. ; Bobrowski, Maria ; Dehling, D. Matthias ; Harris, David J. ; Hartig, Florian ; Lischke, Heike ; Moretti, Marco D. ; Pagel, Jörn ; Pinkert, Stefan ; Schleuning, Matthias ; Schmidt, Susanne I. ; Sheppard, Christine S. ; Steinbauer, Manuel J. ; Zeuss, Dirk ; Kraan, Casper:
Biotic interactions in species distribution modelling : 10 questions to guide interpretation and avoid false conclusions.
In: Global Ecology and Biogeography. Vol. 27 (September 2018) Issue 9 . - pp. 1004-1016.
ISSN 1466-822X
DOI: https://doi.org/10.1111/geb.12759

Abstract in another language

Aim 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. ApproachFindingsWe 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. Main conclusionsMoving 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.

Further data

Item Type: Article in a journal
Refereed: Yes
Additional notes: ISI:000448647200001
Institutions of the University: Profile Fields > Advanced Fields > Ecology and the Environmental Sciences
Research Institutions > Research Centres > Bayreuth Center of Ecology and Environmental Research- BayCEER
Profile Fields
Profile Fields > Advanced Fields
Research Institutions
Research Institutions > Research Centres
Result of work at the UBT: No
DDC Subjects: 500 Science > 500 Natural sciences
500 Science > 570 Life sciences, biology
500 Science > 580 Plants (Botany)
Date Deposited: 03 Sep 2019 12:09
Last Modified: 22 Oct 2019 11:54
URI: https://eref.uni-bayreuth.de/id/eprint/51877