The integration of the small‐island effect and nestedness pattern

Abstract

Aim:The small-island effect (SIE) and nestedness are two important patterns in the fields of island biogeography and community ecology. However, to date, no study has tried to integrate the SIE and nestedness pattern. Therefore, the aim of this study was to integrate these two biogeographical patterns by proposing a new integrative hypothesis. The integrative hypothesis posits that the degree of nestedness of the large island matrix will be larger than that of the small island matrix split by the threshold of the SIE. Location: Global.Taxon: Plants, invertebrates and vertebrates. Methods:We compiled 219 global datasets with both the presence-absence matrices and the variables of area and species richness. We also collected six island characteristics influencing the SIE and nestedness patterns, that is island type, taxonomic group, area range, the number of islands, species range and matrix fill. We applied breakpoint regressions to detect SIEs and used the metric NODF (Nestedness metric based on Overlap and Decreasing Fill) to quantify nestedness. We then employed logistic regressions and an information-theoretic approach to determine which combination of island characteristics was important in determining whether the integrative hypothesis was supported.Results: Among the 92 datasets in which SIEs were unambiguously detected, nestedness analyses showed that in 64 cases (69.6%) the values of NODFc (nestedness among sites) for the large island matrices were larger than those of the small island matrices. Matrix fill and area range were substantially important in determining whether the integrative hypothesis was supported. By contrast, island type, taxonomic group, the number of islands and species range received considerably less support. Main Conclusions:Our study was the first to integrate the SIE and nestedness pattern. Overall, we found prevalent support for our integrative hypothesis. The integration of the SIE and nestedness provides new and interesting insights into these two biogeographical patterns.