ALBERT

Description: 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.

Description: We contrast regional and continental-scale comparisons of the floristic composition of terra firme forest in South Amazonia, using 55 plots across Amazonia and a subset of 30 plots from northern Peru and Ecuador. Firstly, we examine the floristic patterns using both genus- or species-level data and find that the species-level analysis more clearly distinguishes different plot clusters. Secondly, we compare the patterns and causes of floristic differences at regional and continental scales. At a continental scale, ordination analysis shows that species of Lecythidaceae and Sapotaceae are gradually replaced by species of Arecaceae and Myristicaceae from eastern to western Amazonia. These floristic gradients are correlated with gradients in soil fertility and to dry season length, similar to previous studies. At a regional scale, similar patterns are found within north-western Amazonia, where differences in soil fertility distinguish plots where species of Lecythidaceae, characteristic of poor soils, are gradually replaced by species of Myristicaceae on richer soils. The main coordinate of this regional-scale ordination correlates mainly with concentrations of available calcium and magnesium. Thirdly, we ask at a regional scale within north-western Amazonia, whether soil fertility or other distance dependent processes are more important for determining variation in floristic composition. A Mantel test indicates that both soils and geographical distance have a similar and significant role in determining floristic similarity across this region. Overall, these results suggest that regional-scale variation in floristic composition can rival continental scale differences within Amazonian terra firme forests, and that variation in floristic composition at both scales is dependent on a range of processes that include both habitat specialisation related to edaphic conditions and other distance-dependent processes. To fully account for regional scale variation in continental studies of floristic composition, future floristic studies should focus on forest types poorly represented at regional scales in current datasets such as terra firme forests with high soil fertility from north-western Amazonia.

Description: 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 elliptic (=the widest part of a 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 and low nutrient soils. 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. 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.

Description: 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 (e.g. RAINFOR, ATDN) 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 south to northeast) and length of the dry season (increasing from northwest to south and east). Here we describe the results of the geographic distribution of leaf size categories based on 121 plots distributed across eight South American countries. We find that, as predicted, 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 north-west 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.

Description: Above-ground tropical tree biomass and carbon storage estimates commonly ignore tree height. We estimate the effect of incorporating height (H) on forest biomass estimates using 37 625 concomitant H and diameter measurements (n = 327 plots) and 1816 harvested trees (n = 21 plots) tropics-wide to answer the following questions: 1. For trees of known biomass (from destructive harvests) which H-model form and geographic scale (plot, region, and continent) most reduces biomass estimate uncertainty? 2. How much does including H relationship estimates derived in (1) reduce uncertainty in biomass estimates across 327 plots spanning four continents? 3. What effect does the inclusion of H in biomass estimates have on plot- and continental-scale forest biomass estimates? The mean relative error in biomass estimates of the destructively harvested trees was half (mean 0.06) when including H, compared to excluding H (mean 0.13). The power- and Weibull-H asymptotic model provided the greatest reduction in uncertainty, with the regional Weibull-H model preferred because it reduces uncertainty in smaller-diameter classes that contain the bulk 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 errors are reduced from 41.8 Mg ha−1 (range 6.6 to 112.4) to 8.0 Mg ha−1 (−2.5 to 23.0) when including $H$. For all plots, above-ground live biomass was 52.2±17.3 Mg ha−1 lower when including H estimates (13%), with the greatest reductions in estimated biomass in Brazilian Shield forests and relatively no change in the Guyana Shield, central Africa and southeast Asia. We show fundamentally different stand structure across the four forested tropical continents, which affects biomass reductions due to $H$. African forests store a greater portion of total biomass in large-diameter trees and trees are on average larger in diameter. This contrasts to forests on all other continents where smaller-diameter trees contain the greatest fractions of total biomass. After accounting for variation in $H$, total biomass per hectare is greatest in Australia, the Guyana Shield, and Asia and lowest in W. Africa, W. Amazonia, and the Brazilian Shield (descending order). Thus, if closed canopy tropical forests span 1668 million km2 and store 285 Pg C, then the overestimate is 35 Pg C if H is ignored, and 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 pantropical carbon stocks and emissions due to deforestation.

Description: Long-term studies using the RAINFOR network of forest plots have generated significant insights into the spatial and temporal dynamics of forest carbon cycling in Amazonia. In this work, we map and explore the landscape context of several major RAINFOR plot clusters using Landsat ETM+ satellite data. In particular, we explore how representative the plots are of their landscape context, and test whether bias in plot location within landscapes may be influencing the regional mean values obtained for important forest biophysical parameters. Specifically, we evaluate whether the regional variations in wood productivity, wood specific density and above ground biomass derived from the RAINFOR network could be driven by systematic and unintentional biases in plot location. Remote sensing data covering 45 field plots were aggregated to generate landscape maps to identify the specific physiognomy of the plots. In the Landsat ETM+ data, it was possible to spectrally differentiate three types of terra firme forest, three types of alluvial terrain forest, two types of bamboo-dominated forest, palm forest, Heliconia monodominant vegetation, swamp forest, disturbed forests and land use areas. Overall, the plots were generally representative of the forest physiognomies in the landscape in which they are located. Furthermore, the analysis supports the observed regional trends in those important forest parameters. This study demonstrates the utility of landscape scale analysis of forest physiognomies for validating and supporting the finds of plot based studies. Moreover, the more precise geolocation of many key RAINFOR plot clusters achieved during this research provides important contextual information for studies employing the RAINFOR database.

Description: 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.

Description: 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. Here, we examine the relationships between species wood density, maximum height and wood production for 60 Amazonian forest plots. Firstly, we examine how community-level species traits vary across Amazonia. Average species maximum height and wood density are low in western, compared to eastern, Amazonia and are negatively correlated with aboveground wood productivity and soil fertility. Secondly, we compare biomass growth rates across functional groups defined on the basis of these two traits. In similar size classes, biomass growth rates vary little between trees that differ in wood density and maximum height. However, biomass growth rates are generally higher in western Amazonia across all functional groups. Thirdly, we ask whether the data on the abundance and average biomass growth rates of different functional groups is sufficient to predict the observed, regional-scale pattern of wood productivity. We find that the lower rate of wood production in eastern compared to western Amazonia cannot be estimated on the basis of this information. Overall, these results suggest that the correlations between community-level trait values and wood productivity in Amazonian forests are not causative: direct environmental control of biomass growth rates appears to be the most important driver of wood production at regional scales. This result contrasts with findings for forest biomass where variation in wood density, associated with variation in species composition, is an important driver of regional-scale patterns. Tropical forest wood productivity may therefore be less sensitive than biomass to compositional change that alters community-level averages of these plant traits.

Description: 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

Description: Long-term studies using the RAINFOR network of forest plots have generated significant insights into the spatial and temporal dynamics of forest carbon cycling in Amazonia. In this work, we map and explore the landscape context of several major RAINFOR plot clusters using Landsat ETM+ satellite data. In particular, we explore how representative the plots are of their landscape context, and test whether bias in plot location within landscapes may be influencing the regional mean values obtained for important forest biophysical parameters. Specifically, we evaluate whether the regional variations in wood productivity, wood specific density and above ground biomass derived from the RAINFOR network could be driven by systematic and unintentional biases in plot location. Remote sensing data covering 45 field plots were aggregated to generate landscape maps to identify the specific physiognomy of the plots. In the Landsat ETM+ data, it was possible to spectrally differentiate three types of terra firme forest, three types of forests over Paleovarzea geomorphologycal formation, two types of bamboo-dominated forest, palm forest, Heliconia monodominant vegetation, swamp forest, disturbed forests and land use areas. Overall, the plots were generally representative of the forest physiognomies in the landscape in which they are located. Furthermore, the analysis supports the observed regional trends in those important forest parameters. This study demonstrates the utility of landscape scale analysis of forest physiognomies for validating and supporting the finds of plot based studies. Moreover, the more precise geolocation of many key RAINFOR plot clusters achieved during this research provides important contextual information for studies employing the RAINFOR database.