The role of island physiography and oceanographic factors in shaping species richness and turnover of nesting seabird assemblages on islands across the south‐eastern Pacific. (3rd October 2020)

• Record Type: Journal Article
• Authors: Gusmao, Joao B.; Luna‐Jorquera, Guillermo; Fernández, Claudia; Luna, Nicolás; Plaza, Paula; Portflitt‐Toro, Matías; Serratosa, Juan; Nuñez, Pamela; Varela, Andrea I.; Rivadeneira, Marcelo M.
• Is Part Of: Journal of biogeography. Volume 47:Number 12(2020:Dec.)
• Page Start: 2611
• Page End: 2621
• Publication Date: 2020-10-03
• Subjects: assemblage structure -- beta diversity -- biogeography -- coastal islands -- oceanic islands -- seabirds -- species richness; Biogeography -- Periodicals; 578.09
• DOI: 10.1111/jbi.13973
• Languages: English
• ISSNs: 0305-0270

Abstract

Abstract: Aim: For seabirds, food supplies and nest sites are largely driven by oceanographic gradients and island habitats, respectively. Research into seabirds' ecological roles in insular ecosystems is crucial to understanding processes that structure seabird nesting assemblages. We examined the influence of island physiography and oceanographic factors on the spatial variation in α‐ and β‐diversity of nesting seabird assemblages. Location: South‐eastern Pacific Ocean. Taxon: Birds. Methods: We compiled data from 53 seabirds breeding on 41 coastal and oceanic islands using different sources: our field records, online databases, environmental reports and literature. We used generalized linear models (GLM) to describe the effect of island physiography (area, elevation and isolation) and oceanographic factors (surface temperature, salinity and primary productivity) on seabird species richness (α‐diversity). We applied multivariate GLM to test the effects of physiographic and oceanographic predictors on species composition (β‐diversity). We used Jaccard dissimilarities on species occurrences per island to calculate β‐diversity partitioned into turnover and nestedness. Polynomial models allowed us to model these metrics against geographical and environmental gradients and so analyse patterns in seabird β‐diversity across spatial scales. Results: Species richness was highest in Galápagos, Pitcairn and Rapa Nui. Changes in seabird α‐diversity across islands were determined by island area and distance to South America but not by oceanographic variables. Physiographic and oceanographic factors were significant in determining β‐diversity. Changes in β‐diversity were mostly due to species replacement (β‐turnover) across three major island Systems (Galápagos Archipelago, Chilean coastal islands and oceanic islands of the south‐eastern Pacific). The contribution of β‐nestedness was restricted to small scales (within archipelagos). Main conclusions: Physiographic and oceanographic factors explain species diversity of seabird assemblages on islands of the south‐eastern Pacific. Oceanographic variables did not affect species richness but significantly influenced species composition. Change in species composition reflects gradients across three marine biogeographical realms: Temperate South, Eastern Indo‐Pacific and Tropical Eastern Pacific. The low degree of species nestedness may reflect multiple evolutionary origins.