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Sampling along a precipitation gradient in tropical South America extending from ca. 0.8 to 2.0 m a−1, savanna soils had consistently lower exchangeable cation concentrations and higher C / N ratios than nearby forest plots. These soil differences were also reflected in canopy averaged leaf traits with savanna trees typically having higher leaf mass per unit area but lower mass-based nitrogen (Nm) and potassium (Km). Both Nm and Km also increased with declining mean annual precipitation (PA), but most area-based leaf traits such as leaf photosynthetic capacity showed no systematic variation with PA or vegetation type. Despite this invariance, when taken in conjunction with other measures such as mean canopy height, area-based soil exchangeable potassium content, [K]sa , proved to be an excellent predictor of several photosynthetic properties (including 13C isotope discrimination). Moreover, when considered in a multivariate context with PA and soil plant available water storage capacity (θP) as covariates, [K]sa also proved to be an excellent predictor of stand-level canopy area, providing drastically improved fits as compared to models considering just PA and/or θP. Neither calcium, nor magnesium, nor soil pH could substitute for potassium when tested as alternative model predictors (ΔAIC > 10). Nor for any model could simple soil texture metrics such as sand or clay content substitute for either [K]sa or θP. Taken in conjunction with recent work in Africa and the forests of the Amazon Basin, this suggests – in combination with some newly conceptualised interacting effects of PA and θP also presented here – a critical role for potassium as a modulator of tropical vegetation structure and function.

Aboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (H). We estimate the effect of incorporating H on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 H and diameter measurements and harvested trees from 20 sites to answer the following questions: 1. What is the best H-model form and geographic unit to include in biomass models to minimise site-level uncertainty in estimates of destructive biomass? 2. To what extent does including H estimates derived in (1) reduce uncertainty in biomass estimates across all 327 plots? 3. What effect does accounting for H have on plot- and continental-scale forest biomass estimates? The mean relative error in biomass estimates of destructively harvested trees when including H (mean 0.06), was half that when excluding H (mean 0.13). Power- and Weibull-H models provided the greatest reduction in uncertainty, with regional Weibull-H models preferred because they reduce uncertainty in smaller-diameter classes (≤40 cm D) that store about one-third of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows that including H reduces errors from 41.8 Mg ha−1 (range 6.6 to 112.4) to 8.0 Mg ha−1 (−2.5 to 23.0). For all plots, aboveground live biomass was −52.2 Mg ha−1 (−82.0 to −20.3 bootstrapped 95% CI), or 13%, lower when including H estimates, with the greatest relative reductions in estimated biomass in forests of the Brazilian Shield, east Africa, and Australia, and relatively little change in the Guiana Shield, central Africa and southeast Asia. Appreciably different stand structure was observed among regions across the tropical continents, with some storing significantly more biomass in small diameter stems, which affects selection of the best height models to reduce uncertainty and biomass reductions due to H. After accounting for variation in H, total biomass per hectare is greatest in Australia, the Guiana Shield, Asia, central and east Africa, and lowest in east-central Amazonia, W. Africa, W. Amazonia, and the Brazilian Shield (descending order). Thus, if tropical forests span 1668 million km2 and store 285 Pg C (estimate including H), then applying our regional relationships implies that carbon storage is overestimated by 35 Pg C (31–39 bootstrapped 95% CI) if H is ignored, assuming that the sampled plots are an unbiased statistical representation of all tropical forest in terms of biomass and height factors. Our results show that tree H is an important allometric factor that needs to be included in future forest biomass estimates to reduce error in estimates of tropical carbon stocks and emissions due to deforestation.

We explored the floristic composition of terra firme forests across Amazonia using 55 plots. Firstly, we examined the floristic patterns using both genus- and species-level data and found that the species-level analysis more clearly distinguishes among forests. Next, we compared the variation in plot floristic composition at regional- and continental-scales, and found that average among-pair floristic similarity and its decay with distance behave similarly at regional- and continental-scales. Nevertheless, geographical distance had different effects on floristic similarity within regions at distances

Leaf size influences many aspects of tree function such as rates of transpiration and photosynthesis and, consequently, often varies in a predictable way in response to environmental gradients. The recent development of pan-Amazonian databases based on permanent botanical plots has now made it possible to assess trends in leaf size across environmental gradients in Amazonia. Previous plot-based studies have shown that the community structure of Amazonian trees breaks down into at least two major ecological gradients corresponding with variations in soil fertility (decreasing from southwest to northeast) and length of the dry season (increasing from northwest to south and east). Here we describe the geographic distribution of leaf size categories based on 121 plots distributed across eight South American countries. We find that the Amazon forest is predominantly populated by tree species and individuals in the mesophyll size class (20.25–182.25 cm2). The geographic distribution of species and individuals with large leaves (>20.25 cm2) is complex but is generally characterized by a higher proportion of such trees in the northwest of the region. Spatially corrected regressions reveal weak correlations between the proportion of large-leaved species and metrics of water availability. We also find a significant negative relationship between leaf size and wood density.

Leaves in tropical forests come in an enormous variety of sizes and shapes, each of which can be ultimately viewed as an adaptation to the complex problem of optimising the capture of light for photosynthesis. However, the fact that many different shape "strategies" coexist within a habitat demonstrate that there are many other intrinsic and extrinsic factors involved, such as the differential investment in support tissues required for different leaf lamina shapes. Here, we take a macrogeographic approach to understanding the function of different lamina shape categories. Specifically, we use 106 permanent plots spread across the Amazon rainforest basin to: 1) describe the geographic distribution of some simple metrics of lamina shape in plots from across Amazonia, and; 2) identify and quantify relationships between key environmental parameters and lamina shape in tropical forests. Because the plots are not randomly distributed across the study area, achieving this latter objective requires the use of statistics that can account for spatial auto-correlation. We found that between 60–70% of the 2791 species and 83 908 individual trees in the dataset could be classified as having elliptic leaves (= the widest part of the leaf is on an axis in the middle fifth of the long axis of the leaf). Furthermore, the average Amazonian tree leaf is 2.5 times longer than it is wide and has an entire margin. Contrary to theoretical expectations we found little support for the hypothesis that narrow leaves are an adaptation to dry conditions. However, we did find strong regional patterns in leaf lamina length-width ratios and several significant correlations with precipitation variables suggesting that water availability may be exerting an as yet unrecognised selective pressure on leaf shape of rainforest trees. Some support was found for the hypothesis that narrow leaves are an adaptation to low nutrient soils. Furthermore, we found a strong correlation between the proportion of trees with non-entire laminas (dissected, toothed, etc.) and mean annual temperature once again supporting the well documented association that provides a basis for reconstructing past temperature regimes.

Understanding the relationships between plant traits and ecosystem properties at large spatial scales is important for predicting how compositional change will affect carbon cycling in tropical forests. In this study, we examine the relationships between species wood density, maximum height and above-ground, coarse wood production of trees ≥10 cm diameter (CWP) for 60 Amazonian forest plots. Average species maximum height and wood density are lower in Western than Eastern Amazonia and are negatively correlated with CWP. To test the hypothesis that variation in these traits causes the variation in CWP, we generate plot-level estimates of CWP by resampling the full distribution of tree biomass growth rates whilst maintaining the appropriate tree-diameter and functional-trait distributions for each plot. These estimates are then compared with the observed values. Overall, the estimates do not predict the observed, regional-scale pattern of CWP, suggesting that the variation in community-level trait values does not determine variation in coarse wood productivity in Amazonian forests. Instead, the regional gradient in CWP is caused by higher biomass growth rates across all tree types in Western Amazonia. Therefore, the regional gradient in CWP is driven primarily by environmental factors, rather than the particular functional composition of each stand. These results contrast with previous findings for forest biomass, where variation in wood density, associated with variation in species composition, is an important driver of regional-scale patterns in above-ground biomass. Therefore, in tropical forests, above-ground wood productivity may be less sensitive than biomass to compositional change that alters community-level averages of these plant traits.