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Explaining the mechanisms underlying spatial and temporal variation in community composition is a major challenge. Nevertheless, the processes controlling temporal variation at a site (i.e. temporal β‐diversity, including its turnover and nestedness components) are less understood than those affecting variation among sites (i.e. spatial β‐diversity). Short‐term temporal turnover (e.g. throughout an annual cycle) is expected to correlate positively with seasonal environmental variability and landscape connectivity, but also species pool size (γ‐diversity). We use the megadiverse Amazonian freshwater ichthyofauna as a model to ask whether seasonality and landscape connectivity drive variation in temporal species turnover among geomorphological habitat types, while accounting for between‐habitat variation in γ‐diversity. We collected 11 397 fish representing 260 species during a year‐long sampling program from an area containing the lowland Amazon's four major geomorphological habitat types: rivers, floodplains, terra firme streams, and shield streams. River‐floodplain systems exhibit strong but predictable seasonality (via a high‐amplitude annual flood pulse), high connectivity, and high species richness with many rare species. Terra firme and shield streams exhibit low seasonality, low connectivity, and low species richness with proportionally fewer rare species. Based on these parameters we predicted that river‐floodplain systems should have higher temporal turnover than stream systems. Using a null model approach combined with β‐deviation calculations, we confirmed that rivers and floodplains do exhibit higher turnover (but not nestedness) than terra firme and shield streams, even when controlling for the potentially confounding effect of higher species richness in river‐floodplain systems. All habitats exhibit low temporal nestedness, indicating that short‐term changes in community composition result primarily from temporal species turnover. Our results provide a timely reminder that efforts to conserve the Amazon's threatened aquatic biodiversity should account for the distinct temporal dynamics of habitat types and variation in hydrological seasonality. [ABSTRACT FROM AUTHOR]

Abstract Understanding how species are non‐randomly distributed in space and how the resulting spatial structure responds to ecological, biogeographic, and anthropogenic drivers is a critical piece of the biodiversity puzzle. However, most metrics that quantify the spatial structure of diversity (i.e., community differentiation), such as Whittaker’s β‐diversity, depend on sampling effort and are influenced by species pool size, species abundance distributions, and numbers of individuals. Null models are useful for identifying the degree of differentiation among communities due to spatial structuring relative to that expected from sampling effects, but do not accommodate the influence of sample completeness (i.e., the proportion of the species pool in a given sample). Here, we develop an approach that makes use of individual‐ and coverage‐based rarefaction and extrapolation, to derive a metric, βC, which captures changes in intraspecific aggregation independently of changes in the species pool size. We illustrate the metric using spatially explicit simulations and two case studies: (1) a re‐analysis of the “Gentry” plot data set consisting of small forest plots spanning a latitudinal gradient from North to South America and (2) comparing a large plot in high diversity tropical forests of Barro Colorado Island, Panama, with a plot in a lower diversity temperate forest in Harvard Forest, Massachusetts, USA. We find no evidence for systematic changes in spatial structure with latitude in these data sets. As it is rooted in biodiversity sampling theory and explicitly controls for sample completeness, our approach represents an important advance over existing null models for spatial aggregation. Potential applications range from better descriptors of biogeographic diversity patterns to the consolidation of local and regional diversity trends in the current biodiversity crisis.

Understanding how species are non‐randomly distributed in space and how the resulting spatial structure responds to ecological, biogeographic, and anthropogenic drivers is a critical piece of the biodiversity puzzle. However, most metrics that quantify the spatial structure of diversity (i.e., community differentiation), such as Whittaker's β‐diversity, depend on sampling effort and are influenced by species pool size, species abundance distributions, and numbers of individuals. Null models are useful for identifying the degree of differentiation among communities due to spatial structuring relative to that expected from sampling effects, but do not accommodate the influence of sample completeness (i.e., the proportion of the species pool in a given sample). Here, we develop an approach that makes use of individual‐ and coverage‐based rarefaction and extrapolation, to derive a metric, βC, which captures changes in intraspecific aggregation independently of changes in the species pool size. We illustrate the metric using spatially explicit simulations and two case studies: (1) a re‐analysis of the "Gentry" plot data set consisting of small forest plots spanning a latitudinal gradient from North to South America and (2) comparing a large plot in high diversity tropical forests of Barro Colorado Island, Panama, with a plot in a lower diversity temperate forest in Harvard Forest, Massachusetts, USA. We find no evidence for systematic changes in spatial structure with latitude in these data sets. As it is rooted in biodiversity sampling theory and explicitly controls for sample completeness, our approach represents an important advance over existing null models for spatial aggregation. Potential applications range from better descriptors of biogeographic diversity patterns to the consolidation of local and regional diversity trends in the current biodiversity crisis. [ABSTRACT FROM AUTHOR]

The relationship between β-diversity and latitude still remains to be a core question in ecology because of the lack of consensus between studies. One hypothesis for the lack of consensus between studies is that spatial scale changes the relationship between latitude and β-diversity. Here, we test this hypothesis using tree data from 15 large-scale forest plots (greater than or equal to 15 ha, diameter at breast height ≥ 1 cm) across a latitudinal gradient (3–30o) in the Asia-Pacific region. We found that the observed β-diversity decreased with increasing latitude when sampling local tree communities at small spatial scale (grain size ≤0.1 ha), but the observed β-diversity did not change with latitude when sampling at large spatial scales (greater than or equal to 0.25 ha). Differences in latitudinal β-diversity gradients across spatial scales were caused by pooled species richness (γ-diversity), which influenced observed β-diversity values at small spatial scales, but not at large spatial scales. Therefore, spatial scale changes the relationship between β-diversity, γ-diversity and latitude, and improving sample representativeness avoids the γ-dependence of β-diversity.

The relationship between β-diversity and latitude still remains to be a core question in ecology because of the lack of consensus between studies. One hypothesis for the lack of consensus between studies is that spatial scale changes the relationship between latitude and β-diversity. Here, we test this hypothesis using tree data from 15 large-scale forest plots (greater than or equal to 15 ha, diameter at breast height ≥ 1 cm) across a latitudinal gradient (3-30 o ) in the Asia-Pacific region. We found that the observed β-diversity decreased with increasing latitude when sampling local tree communities at small spatial scale (grain size ≤0.1 ha), but the observed β-diversity did not change with latitude when sampling at large spatial scales (greater than or equal to 0.25 ha). Differences in latitudinal β-diversity gradients across spatial scales were caused by pooled species richness (γ-diversity), which influenced observed β-diversity values at small spatial scales, but not at large spatial scales. Therefore, spatial scale changes the relationship between β-diversity, γ-diversity and latitude, and improving sample representativeness avoids the γ-dependence of β-diversity., Competing Interests: The authors have no competing interests.