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Species abundance distributions (SADs) characterise the distribution of individuals among species. SADs have rarely been explored on islands and the ecological processes shaping SADs are still not fully understood. Notably, the relative importance of disturbance regime in shaping plant SADs remains poorly known. We investigate the relative importance of disturbance regime and island geography on the shape of SADs. We computed SADs for local tree communities in 1‐ha forest plots on 20 tropical islands in the Indo‐Pacific region. We used generalized linear models to analyse how the shape parameter of the gambin SAD model was related to the number of trees and the number of species. Regression analyses were also used to investigate how the shape of SADs, the number of trees and the number of species were related to cyclone disturbance (power dissipation index) and geography (island area and isolation), with direct and indirect (i.e. through the number of trees and species) effects assessed using variance partitioning. Cyclone disturbance was the best predictor of the shape of SADs, with higher power dissipation index producing more lognormal‐like distributions. This effect was mostly due to cyclones increasing the number of trees and decreasing the number of species. Island area affected the shape of SADs through its effect on the number of species, and larger islands were associated with higher species richness and more logseries‐like distributions. The effect of cyclones was stronger on smaller islands. Our results illustrate that disturbances can affect SADs in complex ways; directly and indirectly by impacting the number of species and individuals in communities, and these effects may be moderated by island‐specific characteristics, such as island area or isolation. Our results therefore suggest that multiple, interacting processes shape SADs and that studying SADs has the potential to contribute important new insights to the field of island biogeography. [ABSTRACT FROM AUTHOR]

Despite worldwide knowledge of the importance of the Galápagos archipelago, there is little comparative plot data from the forests in the dry regions. We examined patterns of woody plant (≥2.5 cm diameter at breast height (DBH)) species richness and structure using Gentry's transect method (0.1 ha) on the three largest islands in the Galápagos. We identified the conservation status of woody plants within the dry forest region, assessed forest cover and change in the region, and compared field results to other tropical dry forests in the Pacific. Of the 22 species encountered (11 native, 11 endemic), there were no non-native species and only one threatened species. Isabela, Santa Cruz and San Cristóbal have similar overall levels of species, genera, family and liana richness per site, but significantly different tree species richness, density and tree height per transect. Geospatial databases identified 51 species (native 40%, endemic 60%) of woody plants (≥2.5 cm DBH) within the dry forest region of the Galápagos and 13 species (10 from the genus Scalesia) on the IUCN Red List. There is an estimated 551.97 km2 of dry forest in the Galápagos and there has been little change (<0.01%) in forest cover from 2000 to 2015. Dry forests of the Galápagos have similar levels of species richness to Hawaii and the Marquesas but contain lower densities, basal areas and tree heights than other dry forests in the Pacific. These dry forests appear to be the best preserved and protected tropical dry forest in the Pacific. This research examines patterns of woody plant species richness and structure in dry forests on the three largest islands in the Galápagos. We identify the conservation status of woody plants within the dry forest region, assess forest cover change, and compare results to other tropical dry forests in the Pacific. [ABSTRACT FROM AUTHOR]

Abstract: Aim: To determine the role of regional forcing on plot‐level species diversity and composition, and to quantify the relative importance of biogeographical and climatic factors in explaining woody plant diversity and composition at the local‐, island‐ and archipelago‐scale. Location: Forty‐one tropical islands of the Indo‐Pacific region from Madagascar to Hawai‘i Island. Methods: We analysed the diversity and composition of tropical woody plant communities located across 113 plots, 41 islands and 19 archipelagos. We used generalized linear mixed‐effects models and generalized dissimilarity models to determine the role of regional forcing at the island and archipelago scale and to assess the relative importance of biogeographical (area and isolation of islands or archipelagos, geographical distance between plots) and climatic factors in explaining differences in local diversity and composition (species turnover). Analyses were conducted at different geographical scales (local, island and archipelago) and taxonomic levels (species, genus and family). Results: Variation in local (plot‐level) diversity (as species density, the number of species per 100 woody plants) was primarily explained by island and archipelago identity. Maximum species density was positively correlated with the area of an island (or archipelago) and negatively correlated with the isolation of an archipelago. Local climatic variability was also a significant predictor of species density, but less important than regional forcing. Climate variables explained < 20% of the variation in species turnover across all plots. The importance of geographical distance between plots relative to climate in driving species turnover decreased from the species to family level, and from the regional to island level. Main conclusions: Regional forcing was the key driver of local diversity and composition on islands. Island area and archipelago isolation are likely driving local diversity through their effects on the pool of island species. Geographical distance between plots is the main factor explaining species turnover, while at higher taxonomic levels, climatic factors and niche conservatism are the main drivers. [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]

Understanding how species diversity is related to sampling area and spatial scale is central to ecology and biogeography. Small islands and small sampling units support fewer species than larger ones. However, the factors influencing species richness may not be consistent across scales. Richness at local scales is primarily affected by small‐scale environmental factors, stochasticity and the richness at the island scale. Richness at whole‐island scale, however, is usually strongly related to island area, isolation and habitat diversity. Despite these contrasting drivers at local and island scales, island species–area relationships (SARs) are often constructed based on richness sampled at the local scale. Whether local scale samples adequately predict richness at the island scale and how local scale samples influence the island SAR remains poorly understood. We investigated the effects of different sampling scales on the SAR of trees on 60 small islands in the Raja Ampat archipelago (Indonesia) using standardised transects and a hierarchically nested sampling design. We compared species richness at different grain sizes ranging from single (sub)transects to whole islands and tested whether the shape of the SAR changed with sampling scale. We then determined the importance of island area, isolation, shape and habitat quality at each scale on species richness. We found strong support for scale dependency of the SAR. The SAR changed from exponential shape at local sampling scales to sigmoidal shape at the island scale indicating variation of species richness independent of area for small islands and hence the presence of a small‐island effect. Island area was the most important variable explaining species richness at all scales, but habitat quality was also important at local scales. We conclude that the SAR and drivers of species richness are influenced by sampling scale, and that the sampling design for assessing the island SARs therefore requires careful consideration. [ABSTRACT FROM AUTHOR]

To identify forests of high priority for conservation in tropical dry forests of New Caledonia, Fiji, the Marquesas and Hawaii, we examined patterns of woody plant species richness (total, native and endemic) and threatened species (IUCN categorization and density) at the stand level, using Gentry's transect method. There were associations between total, native and endemic plant species richness in all four Pacific dry forest regions but we found no significant association with the presence or density of species listed on the IUCN Red List. Dry forests in New Caledonia and Hawaii merit the highest conservation priority in the Pacific, based on level of endemism and number of threatened species. The study sites that merit high conservation priority are Metzdorf, Nekoro and Pindai, in New Caledonia, Kokee and Kaupulehu, in Hawaii, and Vatia, in Fiji. New Caledonia and Fiji have a small dry forest extent and protected area extent compared with other dry forests in biodiversity hotspots. Although we identified priority areas for dry forest conservation, more comparative plot data, presence/absence data in fragments and regional geographical data are needed to adequately manage and protect dry forests in the Pacific. [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: The General Dynamic Model (GDM) links island biogeographical processes to island geological history. A key premise of the GDM implies that environmental factors shaping the ecology and evolution of biota on oceanic islands follow a hump‐shaped trend over the island's life span and drive dynamics in carrying capacity, species diversity and endemism. An important component of the GDM is environmental heterogeneity (EH), but its effects on insular diversity remain poorly understood. Here, we first quantified EH, tested whether EH follows the expected hump‐shaped trend along island ontogeny and evaluated how EH relates to plant diversity. Location: 135 oceanic islands of volcanic origin. Taxon: Vascular plants. Methods: We calculated 20 EH metrics focusing on topographic and climatic components of EH, and compared whole‐island metrics (e.g. range) and moving‐window metrics (e.g. roughness). Using linear mixed‐effects models, we evaluated the trends of EH with island age and the EH–plant diversity relationship expected based on the GDM. Results: Our analysis revealed some EH components to be collinear, for example, elevation and temperature heterogeneity but also that EH metrics capture different aspects of EH, for example, climatic gradients versus climatic complexity. EH generally followed a hump‐shaped trend with island age, peaking early during island ontogeny. Among the EH components, climatic heterogeneity had the strongest effect on plant species richness and elevational heterogeneity on endemism. Lastly, including EH metrics in GDMs (traditionally, only island age and area were included) improved their predictive power. Main conclusions: The EH metrics compared here captured various attributes of the environment that influence insular plant diversity. In line with the GDM, our results strongly support a hump‐shaped relationship between EH and island age, suggesting that islands become highly heterogeneous early in their ontogeny. Finally, the contribution of EH to GDM‐based models of species richness and endemism suggests that EH is a main driver of the diversity of oceanic island biotas. [ABSTRACT FROM AUTHOR]

Determining patterns of plant diversity on granite inselbergs is an important task for conservation biogeography due to mounting threats. However, beyond the tropics there are relatively few quantitative studies of floristic diversity, or consideration of these patterns and their environmental, biogeographic, and historical correlates for conservation. We sought to contribute broader understanding of global patterns of species diversity on granite inselbergs and inform biodiversity conservation in the globally significant Southwest Australian Floristic Region (SWAFR). We surveyed floristics from 16 inselbergs (478 plots) across the climate gradient of the SWAFR stratified into three major habitats on each outcrop. We recorded 1,060 species from 92 families. At the plot level, local soil and topographic variables affecting aridity were correlated with species richness in herbaceous (HO) and woody vegetation (WO) of soil‐filled depressions, but not in woody vegetation on deeper soils at the base of outcrops (WOB). At the outcrop level, bioclimatic variables affecting aridity were correlated with species richness in two habitats (WO and WOB) but, contrary to predictions from island biogeography, were not correlated with inselberg area and isolation in any of the three habitats. Species turnover in each of the three habitats was also influenced by aridity, being correlated with bioclimatic variables and with interplot geographic distance, and for HO and WO habitats with local site variables. At the outcrop level, species replacement was the dominant component of species turnover in each of the three habitats, consistent with expectations for long‐term stable landscapes. Our results therefore highlight high species diversity and turnover associated with granite outcrop flora. Hence, effective conservation strategies will need to focus on protecting multiple inselbergs across the entire climate gradient of the region. [ABSTRACT FROM AUTHOR]