Incorporating biotic interactions in the distribution models of African wild silk moths (Gonometa species, Lasiocampidae) using different representations of modelled host tree distributions

dc.contributor.authorRaath, Morgan Jade
dc.contributor.authorLe Roux, Peter Christiaan
dc.contributor.authorVeldtman, Ruan
dc.contributor.authorGreve, Michelle
dc.date.accessioned2018-08-31T10:57:54Z
dc.date.issued2018-05
dc.description.abstractBiotic interactions influence species niches and may thus shape distributions. Nevertheless, species distribution modelling has traditionally relied exclusively on environmental factors to predict species distributions, while biotic interactions have only seldom been incorporated into models. This study tested the ability of incorporating biotic interactions, in the form of host plant distributions, to increase model performance for two host‐dependent lepidopterans of economic interest, namely the African silk moth species, Gonometa postica and Gonometa rufobrunnea (Lasiocampidae). Both species are dependent on a small number of host tree species for the completion of their life cycle. We thus expected the host plant distribution to be an important predictor of Gonometa distributions. Model performance of a species distribution model trained only on abiotic predictors was compared to four species distribution models that additionally incorporated biotic interactions in the form of four different representations of host plant distributions as predictors. We found that incorporating the moth–host plant interactions improved G. rufobrunnea model performance for all representations of host plant distribution, while for G. postica model performance only improved for one representation of host plant distribution. The best performing representation of host plant distribution differed for the two Gonometa species. While these results suggest that incorporating biotic interactions into species distribution models can improve model performance, there is inconsistency in which representation of the host tree distribution best improves predictions. Therefore, the ability of biotic interactions to improve species distribution models may be context‐specific, even for species which have obligatory interactions with other organisms.en_ZA
dc.description.departmentPlant Production and Soil Scienceen_ZA
dc.description.embargo2018-12-01
dc.description.librarianhj2018en_ZA
dc.description.sponsorshipThe University of Pretoria (RDP funding to Michelle Greve), the South African National Research Foundation and the South African National Biodiversity Institute.en_ZA
dc.description.urihttp://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1442-9993en_ZA
dc.identifier.citationRaath, M.J., Le Roux, P.C., Veldtman, R. & Greve, M. 2018, 'Incorporating biotic interactions in the distribution models of African wild silk moths (Gonometa species, Lasiocampidae) using different representations of modelled host tree distributions', Austral Ecology, vol. 43, no. 3, pp. 316-327.en_ZA
dc.identifier.issn1442-9985 (print)
dc.identifier.issn1442-9993 (online)
dc.identifier.other10.1111/aec.12569
dc.identifier.urihttp://hdl.handle.net/2263/66414
dc.language.isoenen_ZA
dc.publisherWileyen_ZA
dc.rights© 2017 Ecological Society of Australia. This is the pre-peer reviewed version of the following article : 'Incorporating biotic interactions in the distribution models of African wild silk moths (Gonometa species, Lasiocampidae) using different representations of modelled host tree distributions', Austral Ecology, vol. 43, no. 3, pp. 316-327, 2018, doi : 10.1111/aec.12569. The definite version is available at : http://onlinelibrary.wiley.comjournal/10.1111/(ISSN)1442-9993.en_ZA
dc.subjectMaxenten_ZA
dc.subjectNiche modellingen_ZA
dc.subjectSpecies interactionsen_ZA
dc.subjectSpecies distribution modelsen_ZA
dc.subjectClimate changeen_ZA
dc.subjectLepidopteraen_ZA
dc.subjectFutureen_ZA
dc.subjectNichesen_ZA
dc.subjectAccuracyen_ZA
dc.subjectGlobal changeen_ZA
dc.subjectImprove predictionen_ZA
dc.subjectPopulation dynamicsen_ZA
dc.subjectGeographic distributionen_ZA
dc.subjectAfrican silk mothen_ZA
dc.subjectGonometa posticaen_ZA
dc.subjectGonometa rufobrunneaen_ZA
dc.titleIncorporating biotic interactions in the distribution models of African wild silk moths (Gonometa species, Lasiocampidae) using different representations of modelled host tree distributionsen_ZA
dc.typePostprint Articleen_ZA

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