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Islands in the tropical Pacific Ocean are renowned for high biodiversity and endemism despite having relatively small landmasses. However, our knowledge of how this biodiversity is formed remains limited. The taxon cycle, where well‐dispersed, earlier colonizers become displaced from coastal to inland habitats by new waves of colonizers, producing isolated, range‐restricted species, has been proposed to explain current biodiversity patterns. Here, we integrate the outcomes of phylogenetic studies in the region to investigate the sources, age, number of colonizations, and diversification of 16 archipelagos in the tropical and subtropical South Pacific. We then evaluate whether the results support the taxon cycle as a plausible mechanism for these observations. We find that most species in the Pacific arrived less than 5 Mya from geographically close sources, suggesting that colonization by new taxa is a frequent and ongoing process. Therefore, our findings are broadly consistent with the theory of the Taxon Cycle, which posits that ongoing colonization results in the gradual displacement of established lineages. Only the oldest archipelagos, New Caledonia and Fiji, do not conform to this trend, having proportionally less recent colonization events, suggesting that the taxon cycle may slow on older islands. This conclusion is further validated by New Caledonia having lower diversification rate estimates than younger islands. We found that diversification rates across archipelagos are negatively correlated with area and age. Therefore, a taxon cycle that slows with island age appears to be a suitable concept for understanding the dynamic nature and biodiversity patterns of the Pacific Islands. [ABSTRACT FROM AUTHOR]

Aim: The island species–area relationship (ISAR) assumes that the area of islands is homogeneous, or scales with environmental heterogeneity across an archipelago, which is not always the case. We compare the performance of models that adjust or substitute for island area with measures of habitat diversity, island age and resource availability for two taxonomic groups. Location: Five hotspot archipelagos (Azores, Galapagos, Hawaii, Cape Verde, Canary Islands). Taxa: Vascular plants, birds. Methods: We used the mathematical framework of the power law to compare relevant models, treating the one containing only area as a null model against which others were compared. Data were collated from databases and the literature. Models were compared using linear regression within archipelagos and via mixed effect models with archipelago as a random effect. Results: Weighting of island area by habitat diversity and resource availability systematically improved statistical significance and model fits versus the area only power law. Models including island age did not show the same systematic improvement in model fits. For vascular plants, weighting islands by resource availability (energy and water) performed better than weighting by habitat diversity, although for birds these weightings performed equally well. Main Conclusions: Given that islands within archipelagos are fairly heterogeneous in climate, topography and geology, it is worth accounting for this in ISARs. Our results suggest that, for islands in volcanic hotspot archipelagos, this is best done by using direct measures of habitat diversity and resource availability rather than using island age as a proxy. We, therefore, recommend using direct measures, rather than proxies, when investigating the drivers of biodiversity patterns on islands. [ABSTRACT FROM AUTHOR]

Aim: The General Dynamic Model of island biogeography (GDM) explains patterns of species richness on volcanic hotspot archipelagos with respect to island age (T) and area (A), most commonly employing what we here call semi‐log ATT2 and LogATT2 models. These can be considered direct extensions of semi‐log and power law species‐area relationships (SARs), with a hump‐shaped function of T modelling drivers of biodiversity over and above area per se. We compare these and related models and investigate their conceptual and mathematical connections. Location: The Azores, Galapagos, Hawaii, Marquesas, Society Islands, Cape Verde Islands, Canary Islands and Aeolian archipelagos. Taxa: Vascular plants, birds, bryophytes, arthropods and molluscs. Methods: We gathered species richness data from databases and published sources, resulting in 34 datasets for various taxa. We used the Akaike information criterion corrected for small sample size (AICc) to compare the relative performance of models. We analysed the data at archipelago level and across archipelagos by using mixed effect models. We also calculated the relative time of expected peak diversity (Tpeak) from parameter estimates. Results: In almost three‐fourth of the cases the best model overall was one that contained only A or T rather than both predictors. There was greater variance between taxa than between archipelagos. Better dispersed taxa tended to reach peak diversity earlier. The most generally applicable of the models including T were the LogATT2 and LogTT2 models. These have important, previously unrecognized mathematical properties. Main Conclusions: SARs and species–time relationships should always be considered as potentially more parsimonious options. Considering the LogATT2 model as a modification of the power law S = cAz, where a lognormal function in T replaces the constant, c allows the construction of an extended framework for the GDM with incorporation of additional predictors such as measures of environmental heterogeneity and application beyond hotspot archipelagos. [ABSTRACT FROM AUTHOR]

Aim To determine if habitat diversity, as estimated by climatic and topographic variables, can predict patterns of orchid diversity on different islands and archipelagos with similar explanatory power to biogeographical variables, such as area, isolation and age of an island. Location Sixty-three islands on eight archipelagos (Solomon Islands, Vanuatu, New Caledonia, Fiji, Samoa, Tonga, Niue and the Cook Islands) in the south-west Pacific. Methods For each island, we determined the orchid species present, age, area, isolation, and indicators of topographic heterogeneity and climatic variability. We then determined the power of various biogeographical, climatic and topographic variables to predict the number of indigenous and endemic species on archipelagos, and on islands within archipelagos, using generalized linear models ( GLMs) and generalized linear mixed models ( GLMMs) respectively. Results We identified a total of 552 species in 110 genera. Area was the only significant biogeographical variable for predicting patterns of orchid species diversity on archipelagos and islands. However, climatic and topographic predictors of habitat diversity performed similarly well. The range in curvature was the best indicator of species richness from the topographic variables, while the range of temperature was the best climatic predictor. These key variables were often strongly correlated with area. Main conclusions Climatic and topographic variables are useful indicators of habitat diversity. The high explanatory power of area and climatic and topographic predictors, and the strong correlation among these variables, suggests that increasing habitat diversity with increasing area may be the major driver of the species-area relationship. Using climatic and topographic variables as predictors of species richness therefore allows determining the key environmental factors and processes driving species diversity. [ABSTRACT FROM AUTHOR]

Aim We examine variation in woody plant species richness and endemism within tropical dry forest on oceanic islands and determine what climatic and biogeographic metrics best explain native species richness and endemism across archipelagos, islands and plots. Location Oceanic islands in the Pacific. Methods Stand-level sampling (0.1 ha) at 35 different dry forest sites across 16 islands, and five archipelagos (New Caledonia, Fiji, Marquesas, Marianas and Hawaii). Descriptors of native species richness and endemism were calculated at the plot, island and archipelago level. Biogeographic and climate metrics at the archipelago, island and plot level were drawn from the literature and computer databases. The effects of biogeographic and climate metrics were investigated using linear mixed-effects models. Results Dry forests of New Caledonia and Fiji had the highest native species richness, while New Caledonia and Hawaii had the highest endemism. Native species richness and endemism within tropical dry forests on oceanic islands are primarily influenced by biogeographic metrics, especially isolation of the archipelago, and not climatic metrics. Most variance in native species richness and endemism (60% and 64%) is at the archipelago level compared with the island (8%, 16%) and plot (32%, 15%) level. At the island level, species richness in tropical dry forest is affected by precipitation, while island area significantly affects endemism. The area of forest fragments is an important predictor of native species richness and endemism in plots. Main conclusions Although dry forests in the Pacific have been exceptionally deforested and degraded, high native species richness and endemism remains in a number of forest fragments. Biogeographic metrics explain most of the variance in native species richness and endemism across scales, while climatic metrics are important at the island level. First-order assessments of native richness and endemism at the archipelago, island and stand-level are possible for forest types on oceanic archipelagos. [ABSTRACT FROM AUTHOR]

Aim Regional patterns of forest composition in West Polynesia were analysed to determine the relative importance of dispersal limitation, speciation, environmental filtering and biotic interactions. Location West Polynesia (Fiji, Tonga, Samoa). Methods We applied clustering and indicator species analysis to presence/absence data for 397 tree taxa in 338 forest plots to detect groups of plots sharing similar species composition. Patterns of plot composition and co-occurrence of congeneric species were compared between archipelagos for evidence of dispersal limitation, speciation, and environmental filtering versus competitive displacement or niche differentiation across the three archipelagos at the local (plot) and regional scales. Results Dispersal limitation was evident in the compositional segregation of inland rain forests across the three archipelagos, whereas compositional overlap was widespread for coastal forests, which are composed of species dispersed by water. Within genera, species numbers attenuated from Fiji to Tonga to Samoa, but speciation also contributed to compositional differences in all three island groups. Environmental filtering was suggested by the distinct composition of both secondary and mature inland rain forest versus coastal forest. At the local scale, however, clumping of congeners, which might suggest fine-scale environmental filtering, was observed for only a minority of inland forest genera. Most genera showed either overdispersion, suggesting competitive displacement or niche differentiation, or patterns not significantly different from random. Main conclusions Well-established biogeographical patterns of dispersal limitation and speciation contribute to West Polynesian tree diversity at the community scale. Environmental filtering and competitive displacement further structure forest communities; the evidence from this study suggests that environmental filtering is more important at a landscape scale, while competitive displacement may be more important at a local scale, although their relative importance varies considerably among taxa. [ABSTRACT FROM AUTHOR]