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Geographical co-occurrence of butterfly species: the importance of niche filtering by host plant species

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Abstract

The relevance of interspecific resource competition in the context of community assembly by herbivorous insects is a well-known topic in ecology. Most previous studies focused on local species assemblies that shared host plants. Few studies evaluated species pairs within a single taxon when investigating the effects of host plant sharing at the regional scale. Herein, we explore the effect of plant sharing on the geographical co-occurrence patterns of 232 butterflies distributed across the Japanese archipelago; we use two spatial scales (10 × 10 and 1 × 1 km grids) to this end. We considered that we might encounter one of two predictable patterns in terms of the relationship between co-occurrence and host sharing among butterflies. On the one hand, host sharing might promote distributional exclusivity attributable to interspecific resource competition. On the other hand, sharing of host plants may promote co-occurrence attributable to filtering by resource niche. At both grid scales, we found significant negative correlations between host use similarity and distributional exclusivity. Our results support the hypothesis that the butterfly co-occurrence pattern across the Japanese archipelago is better explained by filtering via resource niche rather than interspecific resource competition.

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Acknowledgements

We thank K. Kadowaki for his comments and advice on the original version of our manuscript, M. U. Saito for giving us the detail information of collecting datasets of host plants, the Biodiversity Center of Japan for allowing access to butterfly data at the 1-km grid scale, and the associate editor and three reviewers for their comments, which improved our manuscript. We are particularly grateful to the entomologists and naturalists who accumulated the information on butterflies used in this study. This work was supported by a grant from the Grant-in-Aid Program for JSPS Fellows (Grant No. 15J00601).

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RN and KH conceived and designed the study; KH and RN collected the data from the literature; TI conducted the analysis of ecological niche modeling; YS and RN performed the statistical analyses; and RN, KH, YS, and TI wrote the manuscript.

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Correspondence to Ryosuke Nakadai.

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The authors declare that they have no conflict of interest.

Additional information

Communicated by Evan H. DeLucia.

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Figure S1

Histogram of the number of observed grids for each butterfly species at both 10-km and 1-km grid scales: (a) all targeted butterfly species at the 10-km grid scale, (b) butterfly species at the 10-km grid scale, with an observed grid number less than 50, (c) all targeted butterfly species at the 1-km grid scale, and (d) butterfly species at the 1-km grid scale, with an observed grid number less than 50.

Supplementary File 1

Details of the methods used for ecological niche modeling.

442_2018_4062_MOESM3_ESM.xlsx

Table S1–S6 Table S1. Japanese butterfly species analyzed in this study. Table S2. Summary of the MaxEnt data at the 10-km grid scale. Table S3. Summary of the MaxEnt data at the 1-km grid scale. Table S4. Correlations among host use similarity (Host), taxonomic relatedness (Taxon), climate niche similarity (Climate), and total dispersal ability (Dispersal), at two spatial scales. (a) Summary of Mantel test data on pairwise correlations between the explanatory matrices. (b) Summary of partial Mantel test data on standardized Cstd scores between pairs of butterfly species. The “Taxon-Dispersal” data (b) were obtained using the datasets at either grid mesh scale. Table S5. Results using the datasets that excluded rare species. This table corresponds to Table 2. Table S6. Results using the datasets that excluded rare species. This table corresponds to Table S4. (XLSX 149 kb)

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Nakadai, R., Hashimoto, K., Iwasaki, T. et al. Geographical co-occurrence of butterfly species: the importance of niche filtering by host plant species. Oecologia 186, 995–1005 (2018). https://doi.org/10.1007/s00442-018-4062-1

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