title: Biotic interactions in the face of climate change: a comparison of three modelling approaches.
abstract: Climate change is expected to alter biotic interactions, and may lead to temporal and spatial mismatches of interacting species. Although the importance of interactions for climate change risk assessments is increasingly acknowledged in observational and experimental studies, biotic interactions are still rarely incorporated in species distribution models. We assessed the potential impacts of climate change on the obligate interaction between Aeshna viridis and its egg-laying plant Stratiotes aloides in Europe, based on an ensemble modelling technique. We compared three different approaches for incorporating biotic interactions in distribution models: (1) We separately modelled each species based on climatic information, and intersected the future range overlap ('overlap approach'). (2) We modelled the potential future distribution of A. viridis with the projected occurrence probability of S. aloides as further predictor in addition to climate ('explanatory variable approach'). (3) We calibrated the model of A. viridis in the current range of S. aloides and multiplied the future occurrence probabilities of both species ('reference area approach'). Subsequently, all approaches were compared to a single species model of A. viridis without interactions. All approaches projected a range expansion for A. viridis. Model performance on test data and amount of range gain differed depending on the biotic interaction approach. All interaction approaches yielded lower range gains (up to 667% lower) than the model without interaction. Regarding the contribution of algorithm and approach to the overall uncertainty, the main part of explained variation stems from the modelling algorithm, and only a small part is attributed to the modelling approach. The comparison of the no-interaction model with the three interaction approaches emphasizes the importance of including obligate biotic interactions in projective species distribution modelling. We recommend the use of the 'reference area approach' as this method allows a separation of the effect of climate and occurrence of host plant.
authors.affiliation: Department of Biogeography, BayCEER, University of Bayreuth, Bayreuth, Germany. anja.jaeschke@uni-bayreuth.de
authors.forename: Anja
authors.initials: A
authors.lastname: Jaeschke
authors.forename: Torsten
authors.initials: T
authors.lastname: Bittner
authors.forename: Anke
authors.initials: A
authors.lastname: Jentsch
authors.forename: Björn
authors.initials: B
authors.lastname: Reineking
authors.forename: Helmut
authors.initials: H
authors.lastname: Schlumprecht
authors.forename: Carl
authors.initials: C
authors.lastname: Beierkuhnlein
mesh_terms: D000818:Animals; D057231:Climate Change; D003198:Computer Simulation; D003710:Demography; D005060:Europe; D005843:Geography; D031321:Hydrocharitaceae / Q000502:physiology*; D008954:Models, Biological; D063191:Odonata / Q000502:physiology*; D013045:Species Specificity; D013559:Symbiosis