Journal of Tropical Ecology (2002) 18:499–525. With 3 figures. Copyright  2002 Cambridge University Press DOI:10.1017/S0266467402002341 Printed in the United Kingdom Different floristic patterns of woody understorey and canopy plants in Colombian Amazonia ALVARO DUQUE1, MAURICIO SÁNCHEZ, JAIME CAVELIER and JOOST F. DUIVENVOORDEN Institute for Biodiversity and Ecosystem Dynamics (IBED), Centre for Geo-ecological Research (ICG), Universiteit van Amsterdam, Postbus 94062, 1090 GB Amsterdam, The Netherlands (Accepted 28th July 2001) ABSTRACT. Distribution patterns of vascular plants with diameter at breast height (dbh) 욷 2.5 cm were studied on the basis of compositional data from 30 small plots located in a rain-forest area in Colombian Amazonia. The research questions were: How are distribution patterns of species in relation to local abundance in plots? Do understorey species (defined as species with individuals that never attained dbh 욷 10 cm anywhere) show better correlations with soils and environment than canopy species (defined as species with individuals that attained dbh 욷 10 cm)? Are patterns found in the entire range of landscape units comparable to those found in well-drained uplands alone? Species that occurred in more than one plot showed higher local abundances. This pattern was consistent among environmental generalists and specialists. Locally rare species (with only one individual in a plot) occurred mostly in well-drained uplands. Considering all landscape units, Mantel tests showed substantial correlations between environmental data (soil chemical data, drainage and flooding) and species composition. Canopy species were only slightly less correlated with environmental data than understorey species. Elimination of the spatial component in the data did not reduce these correlations. In well-drained uplands, understorey species were better correlated with soils than canopy species. Here, however, the spatial configuration of the plots became more important in explaining species patterns. KEY WORDS: beta diversity, Gower’s coefficient, Mantel correlation, rain forest, rarity, soil, spatial effect, Steinhaus similarity coefficient I N T R OD U C T I O N The identification and explanation of plant distributions at local and regional scales in Amazonia, and the humid tropics in general, are gaining increasing 1 Corresponding author, c/o J. F. Duivenvoorden, Institute for Biodiversity and Ecosystem Dynamics (IBED), Universiteit van Amsterdam, Postbus 94062, 1090 GB Amsterdam, The Netherlands. 499 500 ALVARO DUQUE ET AL. attention (Caley & Schluter 1997, Hubbell 1997, Pitman et al. 1999, Terborgh & Andresen 1998). In humid tropical forests, spatial patterns of species are aggregated (Condit et al. 2000, Denslow 1987, Hubbell 1979), and tend to show high numbers of scattered and rare species (Hubbell 1995, 1997). Recent comparisons at regional scales in Peruvian Amazonia show that many locally rare tree species have wide regional distributions (Pitman et al. 1999, see also Murray et al. 1999). In upper Amazonia, Gentry (1988, see also Tuomisto et al. 1995) suggested that forests are a fine-grained mosaic of many different forest types, each characterized by local assemblages of edaphic specialists. Spatial studies of canopy trees (in this study defined as plants with diameter at breast height (dbh) 욷 10 cm) in Colombian (Duivenvoorden 1995, Duivenvoorden & Lips 1998) and Peruvian Amazonia (Pitman et al. 1999), however, showed that beta diversity at mesoscales (i.e. over geographical distances of 1–103 km) is low, especially in the well-drained upland forests which are the most widespread forest type in this region. Better understanding of plant distribution patterns is highly relevant as forests with high levels of local endemic species occurring in fine-grained patches require completely different strategies of conservation than forests built up by populations of locally scarce but widely distributed generalist species. Insights into the degree of environmental preference of forest taxa are also highly necessary for calibration of the growing body of palynological data from the lowland tropics (van der Hammen & Hooghiemstra 2000). Most studies on plant-edaphic relationships in tropical forests (e.g. Baillie et al. 1987, Clark et al. 1998, 1999; Duivenvoorden 1995) focused on canopy trees. However, tropical forests contain many more plant species among the individuals in the understorey (Duivenvoorden 1994, Gentry & Dodson 1987). It may well be that understorey species show greater edaphic specificity than large, well-established trees (Zagt & Werger 1998). Chance elements related to unpredictable events of gap formation influence the successful establishment of large trees. Also, it might be argued that for understorey plants which live predominantly in shaded conditions, edaphic heterogeneity might be an important source of variation for genetic selection. On the other hand, several authors have reported on evidence for spatially heterogeneous light conditions at forest floors and their effects on plant performance (Nicotra et al. 1999, Terborgh & Mathews 1999, Svenning 2000). The current study was set up to compare patterns of these species groups in a series of 0.1-ha plots, well distributed in the principal landscape units of a part of Colombian Amazonia. The research questions were: How are the principal distribution patterns of species in relation to local abundance in plots? Do understorey species show better correlations with soils and environment than canopy species? Are patterns found in the entire range of landscape units comparable to those found in well-drained uplands alone? Amazonian understorey and canopy patterns 501 S TU D Y A R E A The study area comprises about 1000 km2 and is situated along the middle stretch of the Caquetá River in Colombian Amazonia, roughly between 1°– 2°S and 70°–73°W. The principal landscape units found here are well-drained floodplains, swampy areas (including permanently inundated backswamps and basins in floodplains or fluvial terraces), areas covered with white-sand soils (found on high terraces of the Caquetá River and in less dissected parts of the Tertiary sedimentary plain), and well-drained uplands (which are never flooded by river water and include low and high fluvial terraces of the Caquetá River and a Tertiary sedimentary plain) (Duivenvoorden & Lips 1993, Lips & Duivenvoorden 1996). Soils and landscape units are called well-drained when soil drainage (according to FAO 1977) is imperfectly to well-drained (FAO drainage class 욷 2), and poorly drained when soils are poorly to very poorly drained (FAO drainage class < 2). A previous ordination analysis of forest compositional patterns of the current data set (Duque et al. 2001), allowed the recognition of four forest types which correspond closely to the main landscape units: well-drained floodplain forests, well-drained upland forests (tierra firme), swamp forests (excluding any white-sand forests) and white-sand forests. The area receives a mean annual precipitation of about 3060 mm (1979–1990) and monthly rainfall is never below 100 mm (Duivenvoorden & Lips 1993). Mean annual temperature is 25.7 °C (1980–1989) (Duivenvoorden & Lips 1993). M ET H O D S Vegetation sampling and identification of botanical vouchers In each of the above-mentioned landscape units, 30 plots were located (Figure 1). In order to establish the plots, starting locations along the Caquetá River and the direction of the tracks along which the forests were entered, were planned on the basis of the interpretation of aerial photographs (Duivenvoorden 2001). During the walk through the forests, soils and terrain forms were rapidly described, and the forest was visually examined. In this way sites with homogeneous soils and physiognomically homogeneous forest stands were identified. In these stands, rectangular plots were delimited by compass, tape and stakes, working from a random starting point, with the restriction that the long side of the plot was parallel to the contour line. Plots were located without bias with respect to floristic composition or forest structure (including aspects of tree density, tree size and presence of lianas). All plots were established in mature forests that did not show signs of recent human intervention, at a minimum distance of 500 m between plots (Figure 1). Plots were mapped with GPS. Plot size was 0.1 ha and most plots were rectangular in shape (20 × 50 m). Plots were subdivided into subplots of 10 × 10 m, in which all vascular plant individuals with dbh 욷 2.5 cm (dbh = diameter at 1.30 m height) were numbered. The dbh of all individuals was measured with tape. Their height 502 ALVARO DUQUE ET AL. 71˚40' r ío N 5 Km tá Me 0 71˚30' approximate scale río Caquetá isla La Culebra Dos Islas 1˚00'S well-drained floodplains swamps white sand well-drained uplands Tres Islas Figure 1. 1˚10'S Location of 0.1-ha sample plots in the Metá area (Colombian Amazonia). was estimated using long poles as a reference measure. Fieldwork took place in 1997 and 1998. Botanical collections (numbers MS2900-7049 and AD3900-4092) were made of all species found in each plot. Identification took place at the Herbario Amazónico (COAH), the herbarium of the Missouri Botanical Garden (MO), the herbarium of the Universidad de los Andes in Santafé de Bogotá, and the Herbarium of the University of Aarhus (AAU). The nomenclature of families and genera follows Mabberley (1989). Within families or groups of closely allied families, specimens that could not be identified as species because of a lack of Amazonian understorey and canopy patterns 503 sufficient diagnostic characteristics, were clustered into morphospecies on the basis of simultaneous morphological comparisons with all other specimens. Soil data Roughly in the central part of each plot, a soil core was taken to 1.20 m depth in order to describe the mineral soil horizons (in terms of colour, mottling, horizon boundaries, presence of concretions and texture) and to define soil drainage (in classes of FAO 1977). At each augering position a soil sample was taken at a depth of 65–75 cm. Due to an unplanned delay in soil sampling in one floodplain plot and two plots in white-sand forests, samples from only 27 plots were analysed. For analyses, soil samples were dried at temperatures below 40 °C, crumbled and passed through a 2-mm sieve. At the soil laboratory of the Institute for Biodiversity and Ecosystem Dynamics at the Universiteit van Amsterdam, total content of Ca, Mg, K, Na and P was determined by means of atomic emission spectrometry of a subsample of 100–200 mg from the sieved fraction, that had been digested in a solution of 48% HF and 2M H2SO4 (after Lim & Jackson 1982). Total content of C and N was determined for the sieved fraction by means of a Carlo Erba 1106 elemental analyser. Categories of floristic composition Three categories of floristic data are considered in the analysis: all species (dbh 욷 2.5 cm); canopy species (species with individuals that were found with dbh 욷 10 cm); and understorey species (species with individuals recorded with a maximal dbh of less than 10 cm, anywhere in the plots). Understorey species are thus represented by plants that will never attain dbh 욷 10 cm, or by juvenile individuals of plants that may develop into big canopy trees. For the speciesenvironment analysis in well-drained uplands (see Table 6), only understorey species among individuals with heights below 10 m are considered (Welden et al. 1991). Distribution patterns and forest preference Species found with a maximum density of 1 stem per plot, are defined as locally rare (after Pitman et al. 1999). Otherwise species are referred to as locally abundant. Species are called environmental specialists when found in only one of the main landscape units defined in this study. When recorded in more than one of these landscape units, species are considered environmental generalists. Correlation of species with soils, landscape units and geographical space The correlations between species, environmental variables, and geographical space, were calculated by Mantel and partial Mantel tests (Leduc et al. 1992, Legendre & Legendre 1998), as made available in R-Package (Casgrain & Legendre 2000). In these tests, geographical space is used in much the same 504 ALVARO DUQUE ET AL. way as environmental variables, to define and test correlation between matrices (Legendre 1993). In all Mantel tests, matrices of similarity coefficients were used. Species matrices were calculated with the Steinhaus index. This asymmetrical quantitative coefficient permits usage of species abundance data (Legendre & Legendre 1998). Environmental matrices were calculated with Gower’s symmetrical similarity coefficient. This coefficient permits simultaneous incorporation of both nominal and quantitative variables (Legendre & Legendre 1998). Spatial information was quantified by means of Euclidean distances between plots. Probabilities of r-values were defined on the basis of 999 permutations. R ES U L T S Floristic data A total of 13,989 individual vascular plants (dbh 욷 2.5 cm) was recorded in the 30 plots of 0.1 ha each. A total number of 4343 botanical collections were made, representing 89 families, 378 genera and 1502 species, including 478 morphospecies (31% of all species). The most common species found in the area are listed in Appendix 1 (a complete species listing is annexed to Sánchez et al. 2001); 303 morphospecies (20% of all species) were identified only to genus, and 159 only to family (10% of all species). In the 15 plots of 0.1 ha established in the well-drained uplands, 81 families, 310 genera and 1124 species were found. Altogether 650 canopy species were recorded (43% of all species found), 16 of which were liana species, and 852 understorey species (57% of all species) were found. Of these, 161 species were lianas. Distribution patterns Average plot densities of individuals (dbh 욷 2.5 cm) in the main landscape units ranged between 273–669 per 0.1 ha (Table 1). A proportion of 15–32% of these individuals had dbh 욷 10 cm. Average species densities (dbh 욷 2.5 cm) fluctuated between 36–183 per 0.1 ha. Average canopy species densities were between 16–54 per 0.1 ha. Table 1. Densities of species and plant individuals in two dbh classes, recorded in 0.1-ha plots in the main landscape units of the Metá area (Colombian Amazonia). Shown are averages ± SD of n plots. Species Individuals dbh 욷 2.5 cm Well-drained floodplains Swamps White sands Well-drained uplands Species Individuals n dbh 욷 10 cm 93 ± 16 273 ± 53 35 ± 9 57 ± 9 5 72 ± 18 36 ± 18 183 ± 21 669 ± 302 521 ± 212 436 ± 68 27 ± 8 16 ± 7 54 ± 7 160 ± 115 111 ± 40 79 ± 14 5 5 15 Amazonian understorey and canopy patterns 505 800 All landscape units Well-drained uplands 700 Number of species 600 500 400 300 200 100 0 1 2 3 4 5 6 7 8 9 10 11 Number of plots 12 13 14 15 16 17 Figure 2. Number of species (dbh 욷 2.5 cm) recorded in an increasing number of plots of 0.1 ha, in the Metá area (Colombian Amazonia). Many species were restricted to only a few plots (Figure 2). For example, almost half of all the species (dbh 욷 2.5 cm) were found in only one plot, and 80% of the species were found in three plots or less. Most species were also represented by only a few individuals (Figure 3). About 43% of all species were only found as one individual, and 80% of the species as three individuals or less (Figure 3). In both cases, patterns in well-drained uplands were quite similar to patterns in all landscape units together. There were slightly more locally abundant species (57% of all species dbh 욷 2.5 cm) than locally rare species (43% of all species dbh 욷 2.5 cm) (Table 2). Most species occurred in only one landscape unit. Those species that were found in more than one plot tended to achieve higher local abundance than species restricted to a single plot. Among the entire set of species recorded, including the species that were found in only one plot, the number of locally rare species in relation to that of the locally abundant species was higher. In the well-drained uplands the locally rare species contributed almost 50% of the total species richness (Table 3). In all other landscape units, locally abundant species prevailed. When the species that were found in only one plot were excluded, local abundance became proportionately more important, especially in the well-drained uplands. 506 ALVARO DUQUE ET AL. 700 All landscape units Well-drained uplands 600 Number of species 500 400 300 200 100 0 1 2 3 4 5 6 7 8 9 10 11-20 21-50 51-100 >100 Maximum local density (individuals per 0.1 ha) Figure 3. Number of species (dbh 욷 2.5 cm) recorded with an increasing number of individuals in plots of 0.1 ha, in the Metá area (Colombian Amazonia). Table 2. Number of locally rare and locally abundant vascular plant species (dbh 욷 2.5 cm) in view of species presence in one or more landscape units in the Metá area (Colombian Amazonia). Landscape units considered are well-drained floodplains, swamps, well-drained uplands and white-sand areas. Species in two or more plots All species Number of landscape units where species are found Locally abundant species Locally rare species 4 3 2 1 3 0 42 2 170 29 404 127 861 641 Table 3. Number of locally rare and locally abundant vascular plant species (dbh 욷 2.5 cm) in different landscape units, in the Metá area (Colombian Amazonia). Landscape units Well-drained flood plains All species Locally abundant 200 (61%) Locally rare 127 (39%) Species found in two or more plots Locally abundant 137 (71%) Locally rare 57 (29%) Swamps Well-drained uplands White sands All 141 (62%) 88 (38%) 563 (50%) 555 (50%) 85 (69%) 38 (31%) 861 (57%) 641 (43%) 108 (68%) 52 (32%) 436 (68%) 201 (32%) 62 (75%) 21 (25%) 614 (79%) 163 (21%) Amazonian understorey and canopy patterns 507 Species–environment correlations The abiotic variables used to correlate species data with environmental information included flooding, drainage and physico-chemical soil variables (Table 4). When the entire data set derived from plots in all landscape units was analysed, the species composition of both canopy and understorey was strongly correlated with soils and flooding (Mantel r = 0.55 and Mantel r = 0.64, respectively; see Table 5). The spatial configuration of the plots correlated rather poorly with species patterns, even though this correlation was just significant (P = 0.05) for understorey species. When the effect of soils and flooding was removed, the correlation between species patterns and spatial positioning of the plots improved. The environmental information and location of the plots were just significantly correlated (Mantel r = 0.11, P = 0.04). Restricting the analyses to the well-drained uplands, the species–environment relationships were less pronounced (Table 6). It became particularly poor among canopy species (Mantel r = 0.15, P = 0.12). Understorey species composition continued to show a significant correlation with soils and flooding (Mantel r = 0.30; P = 0.004), even when the spatial effect of the positioning of the plots was taken away (partial Mantel r = 0.33; P = 0.0002). Conversely, the location of the plots became an important factor in explaining species patterns, particularly among understorey species (Mantel r = 0.52), after correction for the environmental effect on species patterns (partial Mantel r = 0.53 for understorey species). The environmental information and location of the plots were not significantly correlated (Mantel r = 0.04, P = 0.27). D I S C US S I O N Floristic patterns The proportion of identified species (69% of all species) in the current study is quite comparable to identification results found in other studies applying similar diameter limits in the same region (e.g. 65% reported by Grandez et al. (2001) in Peruvian Amazonia, and 74% claimed by Romero-Saltos et al. (2001) in Ecuadorian Amazonia). The unidentified specimens in this study (31% of all species) were mostly sterile and largely taken from juvenile individuals, which tend to show high morphological variability (Romoleroux et al. 1997). Some of the morphospecies might turn out to represent species new to science (R. Liesner and H. van der Werff, pers. comm.). However, other morphospecies may well correspond to one of the identified species, despite the efforts simultaneously to compare all specimens from the same genus or family. Species distribution Species that occurred in more than one plot showed higher local abundances. Positive abundance–distribution relationships are often found in many organisms and at a variety of spatial scales (see an overview in Gaston & Kunin Number of plots Quantitative variables Drainage Soil elemental concentration Ca (mmol kg-1) Mg (mmol kg-1) K (mmol kg-1) Na (mmol kg-1) P (mmol kg-1) C (%) N (%) Nominal variables (frequencies in %) Flooding by river water Texture Sand Clay-loam Sandy clay Silty clay Organic clay Clay 100 0 0 0 0 60 40 100 0 0 0 0 0 100 1.8 34.8 77.9 12.7 8.2 15.3 0.7 ± ± ± ± ± ± ± 5 83 173 29 17 15 1 ± ± ± ± ± ± ± 92 119 41 174 4 0.1 0.0 0 ± 0.0 3 ± 0.6 130 320 370 290 10 0 0 5 Swamps 4 Well-drained flood plains 2 30 53 9 5 0 0 0 0.6 20.1 37.5 6.8 1.4 0.1 0.0 0 20 7 7 0 67 ± ± ± ± ± ± ± 4 ± 0.0 15 Well-drained uplands 100 0 0 0 0 0 0 2 ± 1.2 2 ± 0.3 1 ± 0.7 0 ± 0.0 1 ± 0.3 3 ± 1.0 0 ± 0.0 0 ± 0.0 3 White sands 11 11 4 4 11 59 40 20 ± 56 80 ± 114 120 ± 129 50 ± 117 10 ± 6 3 ± 8.2 0 ± 0.5 2 ± 1.9 27 All Table 4. Environmental variables used in the Mantel analyses, and their variation (average ± SD in case of quantitative variables and frequencies in case of nominal variables) recorded in 27 plots distributed over all landscape units, in the Metá area (Colombian Amazonia) (see also Figure 1). 508 ALVARO DUQUE ET AL. Amazonian understorey and canopy patterns 509 Table 5. Mantel and partial Mantel correlation of species composition with space and environment in all landscape units (27 plots). Matrix A is composed of Steinhaus similarity coefficients between species data. Environment is the matrix composed of Gower’s similarity coefficients between environmental data. Space is the matrix composed of Euclidean distances between plots. Mantel r is the Mantel correlation coefficient between matrix A and matrix B. Partial Mantel r is the Mantel correlation between matrix A and matrix B when the effect of matrix C is removed. All landscape units Matrix A = All species (dbh 욷 2.5 cm) Matrix B Environment Space Matrix B Matrix C Environment Space Space Environment Matrix A = Canopy species Matrix B Environment Space Matrix B Matrix C Environment Space Space Environment Matrix A = Understorey species Matrix B Environment Space Matrix B Matrix C Environment Space Space Environment Mantel r Partial Mantel r 0.63 0.08 Probability 0.001 0.105 0.65 0.19 0.55 0.09 0.001 0.004 0.001 0.09 0.57 0.17 0.64 0.11 0.001 0.005 0.001 0.05 0.66 0.24 0.001 0.002 1997, see also Brown 1984, Hanski et al. 1993). The most important explanations mentioned are sampling artifacts (locally rare species are less likely to be included in small sample plots and hence may appear with a more limited regional distribution), metapopulation dynamics (details in Hanski 1982, Hanski et al. 1993) and different degrees of ecological specialization (generalists would be able to exploit a wider range of resources and show less habitat specialization). In the current study generalist species (found in more than one main landscape unit) and specialist species (found in only one main landscape unit), showed a more-or-less similar abundance–distribution pattern. However, the estimates of local population size or environmental preference of many species were crude as the plot samples contained only a few individuals of these species. Also, the applied definition of local rareness and local abundance is arbitrary. It should be stressed that the great majority of the so-called locally abundant species are found with a low number of individuals per plot (see Figure 3). The term ‘locally abundant’ may be considered as somewhat misleading in this context (Pitman et al. 1999). When poorly distributed species (found in only one plot) are removed, the contribution of locally rare species to the entire species pool decreases most in well-drained upland forests. Species that occur with one individual in only one plot are therefore relatively common in well-drained uplands, and contribute to the high alpha diversity in these uplands. 510 ALVARO DUQUE ET AL. Table 6. Mantel and partial Mantel correlation of species composition with space and environment in the well-drained uplands (15 plots). Matrix A is composed of Steinhaus similarity coefficients between species data. Environment is the matrix composed of Gower’s similarity coefficients between environmental data. Space is the matrix composed of Euclidean distances between plots. Mantel r is the Mantel correlation coefficient between matrix A and matrix B. Partial Mantel r is the Mantel correlation between matrix A and matrix B when the effect of matrix C is removed. Uplands well-drained Matrix A = All species (dbh 욷 2.5 cm) Matrix B Environment Space Matrix B Matrix C Environment Space Space Environment Matrix A = Canopy species Matrix B Environment Space Matrix B Matrix C Environment Space Space Environment Matrix A = Understorey species (height < 10 m) Matrix B Environment Space Matrix B Matrix C Environment Space Space Environment Mantel r Partial Mantel r 0.24 0.56 Probability 0.034 0.001 0.26 0.57 0.15 0.29 0.034 0.001 0.12 0.002 0.15 0.29 0.3 0.52 0.14 0.002 0.004 0.001 0.33 0.53 0.002 0.001 Species–environment patterns in all landscape units (whole area) Most species occur in only one landscape unit (Table 2). Because the plots are well distributed in the area this result suggests that species have rather strong preferences for one of the principal landscape units in the area. However, processes of dispersal among species may have led to relatively high species overlap between neighbouring plots in one landscape unit. The Mantel tests serve to quantify these spatial effects. The Mantel analysis of species found among all individuals (dbh 욷 2.5 cm) recorded in all landscape units (Table 5) shows a substantial amount of correlation between the matrices of species and environmental data (Table 5). Despite their rather low plot densities, canopy species are only slightly less correlated with environmental variables than understorey species. Elimination of the spatial component in the data, does not reduce these correlations. It seems therefore that forest plots which share certain properties of flooding, drainage and soil fertility (including white-sand soils) contain more-or-less similar assemblages of vascular plant species. Conclusions about environmental preferences of species should always be corroborated by experiments to discover causative mechanisms and underlying eco-physiological processes. Indications for recurrent patterns of vascular plant species composition in similar landscape units in north-west Amazonia are not new (e.g. Duivenvoorden 1995, Tuomisto et al. 1995). Pitman et al. (1999) concluded that beta Amazonian understorey and canopy patterns 511 diversity among tree species in south-west Amazonia (Manu area, Peru) is weak, and found that 26% of tree species (dbh 욷 10 cm) were restricted to one forest type (with species from two or more plots). In the present study, this percentage is slightly higher (35%). Perhaps the variation in soils and flooding among the plots studied by Pitman et al. was lower than in the current study. This may be due to their larger plot size (0.825–2.5 ha) which increases withinplot environmental heterogeneity or to smaller gradients among soils in the footslope zone of the Andes (less white-sand soils, ubiquitous enrichment by volcanic ash) compared with wider soil gradients found further downstream. Pitman et al. found plot densities of individuals with dbh 욷 10 cm ranging between 282–858 ha-1. These densities are in the same range as those found with dbh 욷 2.5 cm in the 0.1-ha plots (Table 1). Species–environment patterns in well-drained uplands In the well-drained uplands, where the factor of flooding and drainage is held more or less constant, the Mantel correlation between the overall set of species (found among all individuals of dbh 욷 2.5 cm) and soils is low but significant (Table 6). This correlation is due to understorey elements, because patterns in canopy species are no longer associated with soils. The understorey species-to-soil correlation remains significant when effects of space are removed. In a comparable sampling design of well-distributed 0.1-ha plots, Duivenvoorden (1995) claimed low but significant species-to-soil relationships in well-drained uplands of the middle Caquetá area (Colombia) for trees (dbh 욷 10 cm). When correcting for effects of space and forest structure a partial canonical correspondence analysis showed that about 6% of the tree species patterns were significantly correlated with soils (Duivenvoorden 1995). The lack of correlation with canopy species in the current study might be due to the comparatively low number of plots analysed (15 vs. 39 by Duivenvoorden 1995). Comparison of Mantel tests and correspondence analysis is outside the scope of this study (see Legendre & Legendre 1998). In the well-drained uplands, the spatial configuration of the plots is more important than soils in explaining species patterns. Many soil-independent processes (Condit 1996), like herbivory, seed dispersal by animals, plagues and attacks by fungi, species migration, colonization and competition for space and light in dynamic forest ecosystems affect species composition at scales wide enough to influence species composition in neighbouring plots in the area of the current study. The spatial effect is more pronounced in well-drained uplands than in the whole of the study area, both in absolute terms and in comparison to the environmental effect. Apparently, the wider the gradient in soils and flooding, the less important the role of the above-mentioned spatial processes. Canopy species vs. understorey species in relation to environment In the well-drained uplands, just as in the whole data set, understorey species are better correlated with soils than canopy species. Also, the spatial 512 ALVARO DUQUE ET AL. configuration of plots has a greater effect on understorey species patterns than on canopy species patterns. It seems likely that the current presence of many canopy individuals in the plots is an unpredictable result of light-induced growth due to events of gap formation in the recent past. The presence of understorey individuals, on the other hand, might be more limited by seed dispersal, germination and survival in heterogeneous light environments (Hubbell 1997, Nicotra et al. 1999, Terborgh & Mathews 1999). Better adaptation to specific local soil properties might improve the competitive strength of these species. As indicated above, such processes might take place at scales sufficiently wide to facilitate some spatial dependence among the plots included in the current survey. 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Vascular plant species recorded with more than four individuals (dbh = 2.5 cm) in 30 plots of 0.1 ha, in the Metá area (Colombian Amazonia). n = total number of individuals; Min dbh = minimal dbh; max dbh = maximal dbh; F = number of individuals in well-drained floodplains; S = number of individuals in swamps; U = number of individuals in well-drained uplands; W = number of individuals in white-sand areas. n Min Max dbh dbh (cm) (cm) Anacardiaceae Anacardium giganteum Hancock ex Engler Campnosperma gummiferum (Bentham) Marchand Tapirira guianensis Aublet Thyrsodium herrerense Encarnacion Annonaceae Anaxagorea cf. angustifolia Timmerman Anaxagorea rufa Timmerman Annona dolichophylla R.E. Fries Annona hypoglauca Martius Annona MS3648 Bocageopsis canescens (Spruce ex Bentham) R.E. Fr. Bocageopsis multiflora (Martius) R.E. Fries Diclinanona calycina (Diels) R.E. Fries Diclinanona tessmannii Diels Duguetia flagellaris Huber Duguetia macrophylla R.E. Fries Duguetia odorata (Diels) J.F. Macbride Duguetia stenantha R.E. Fries Duguetia cf. ulei (Diels) R.E. Fries Ephedranthus amazonicus R.E. Fries Guatteria cf. decurrens R.E. Fries Guatteria ferruginea St.Hilaire Guatteria insculpta R.E. Fries Guatteria macrocarpa R.E. Fries Guatteria macrophylla Blume Guatteria MS3131 9 10 46 6 2.5 6 2.6 4.3 37.7 21.6 21.5 14.8 27 8 15 7 9 9 20 6 16 7 6 10 5 7 5 40 7 23 6 46 5 2.6 2.5 2.6 4.5 2.7 2.8 2.8 2.5 2.5 2.5 2.6 2.6 2.5 2.7 2.7 2.7 2.7 2.5 2.8 2.6 2.7 6.2 4.7 24.5 29.7 8 14.8 11.4 29.8 17 3.8 5.6 14.8 5.3 4.2 12 16.6 8.3 33.3 9.3 11.6 5 F S U W 9 10 27 3 24 9 7 1 15 5 2 4 6 6 6 5 1 18 6 1 8 5 9 3 5 6 7 5 2 4 5 5 5 10 7 16 6 39 6 4 2 24 1 2 4 Amazonian understorey and canopy patterns A P P E ND I X cont. n Min Max dbh dbh (cm) (cm) Guatteriasa tabapensis Aristeg. ex D.M. Johnson & A. Murray Guatteriella tomentosa R.E. Fries Oxandra euneura Diels Oxandra leucodermis (Spruce ex Bentham) Warming Oxandra mediocris Diels Oxandra polyantha R.E. Fries Oxandra xylopioides Diels Pseudoxandra leucophylla (Diels) R.E. Fries Pseudoxandra aff. polyphleba (Diels) R.E. Fries Unonopsis elegantissima R.E. Fries Unonopsis floribunda Diels Unonopsis guatterioides (A.DC.) R.E. Fries Unonopsis stipitata Diels Unonopsis veneficiorum (C. Martius) R.E. Fries Xylopia cf. calophylla R.E. Fries Xylopia cuspidata Diels Xylopia nervosa (R.E. Fries) Maas Apocynaceae Aspidosperma excelsum Bentham Aspidosperma MS3230 Aspidosperma MS6443 Aspidosperma cf. multiflorum A.DC. Couma catingae Ducke Forsteronia affinis Muell. Arg. Lacmellea foxii (Stapf) Markgraf Macoubea guianensis Aublet Malouetia tamaquarina (Aublet) A.DC. Odontadenia funigera Woodson Tabernaemontana disticha A. DC. Aquifoliaceae Ilex guayusa Loesener Ilex MS6237 Araliaceae Dendropanax palustris (Ducke) Harms Bignoniaceae Arrabidaea fanshawei Sandwith Arrabidaea prancei A.Gentry Digomphia densicoma (Martius ex DC) Pilger Distictis pulverulenta (Sandwith) A.Gentry Jacaranda macrocarpa Bureau & K. Schumann ex K. Schumann Memora bracteosa (DC.) Bureau ex K. Schumann Memora cladotricha Sandwith Paragonia pyramidata (L.C. Richard) Bureau Tabebuia insignis (Miquel) Sandwith var. monophylla Sandwith Tabebuia ochracea (Chamisso) Standley Bombacaceae Matisia lasiocalyx K. Schumann Matisia aff. malacocalyx (A. Robyns & Nilsson) W.S. Alverson Pachira brevipes (A. Robyns) W.S. Alverson Pachira foscolepidota (Steyermark) W.S. Alverson Scleronema micranthum (Ducke) Ducke Boraginaceae Cordia nodosa Lamarck 515 F S U 18 2.5 26.5 7 6 49 91 8 1710 11 43 7 8 15 21 48 9 34 7 7 4.2 2.7 2.5 2.6 2.5 2.8 2.6 2.7 2.6 2.5 2.5 2.5 2.6 2.5 2.6 4 13.5 7.3 17.5 17.6 23.2 3.6 13 6.6 3.7 12.8 15.2 7.8 12.1 19.3 4.2 24.3 45 21 10 6 5 7 11 18 26 11 10 2.5 2.6 4 2.5 3.5 3.2 2.7 3.8 2.6 3 3.3 27.3 16 37.4 48.7 29.6 7.3 10.8 28.7 12.7 5 6.4 7 6 4 2.7 20 6.6 225 2.5 21 12 8 572 8 28 2.7 2.5 2.5 2.8 2.5 8.5 7 52.5 5.5 17.5 6 13 17 84 2.7 2.5 3 2.7 5.6 4.3 7.6 9.3 92 2.5 32 14 25 3.7 2.5 17.8 11 96 14 103 2.5 3.6 2.5 28.2 13 73.5 33 14 2.7 7.5 14 W 11 6 49 91 8 1710 11 1 1 15 4 31 11 6 8 11 6 48 33 1 7 9 2 4 10 6 5 41 17 4 5 7 10 7 4 1 11 22 11 10 2 6 1 4 225 12 8 572 8 28 5 1 13 17 1 83 92 14 25 96 14 70 516 ALVARO DUQUE ET AL. A P P E ND I X cont. n Min Max dbh dbh (cm) (cm) Burseraceae Crepidospermum prancei Daly Crepidospermum rhoifolium (Bentham) Swart Dacryodes MS2998 Dacryodes MS3430 Dacryodes nitens Cuatrecasas Dacryodes cf. peruviana (Loesener) J.F. Macbride Dacryodes cf. roraimensis Cuatrecasas Protium altsonii Sandwith Protium apiculatum Swart Protium aracouchini (Aublet) Marchand Protium cf. crassipetalum Cuatrecasas Protium decandrum (Aublet) Marchand Protium cf. divaricatum Engler Protium hebetatum Daly Protium cf. laxiflorum Engler Protium MS2901 Protium MS5830 Protium nodulosum Swart Protium opacum Swart Protium paniculatum Engler var. paniculatum Protium unifoliolatum Engler Tetragastris cf. altissima (Aublet) Swart Trattinnickia cf. lawrencei Standley Capparidaceae Capparis schunkei Macbride Caryocaraceae Caryocar glabrum (Aublet) Persoon Caryocar cf. nuciferum Linnaeus Cecropiaceae Cecropia distachya Huber Coussapoa cf. orthoneura Standley Pourouma cucura Standley & Cuatrecasas Pourouma myrmecophila Ducke Pourouma tomentosa Martius ssp. tomentosa Celastraceae Goupia glabra Aublet Hippocratea MS3216 Salacia bullata Mennega Salacia gigantea Loesener Salacia macrantha A.C. Smith Tontelea cf. coriacea A.C. Smith Tontelea aff. corymbosa (Huber) A.C. Smith Chrysobalanaceae Couepia canomensis (Martius) Bentham ex Hooker f. Couepia chrysocalyx (Poeppig & Endlicher)Benth ex Hooker Couepia guianensis Aublet Couepia MS4947 Hirtella duckei Huber Hirtella guainiae Spruce ex Hooker f. Licania apetala (E.Meyer) Fritsch Licania granvillei Prance Licania guianensis (Aublet) Grisebach Licania harlingii Prance Licania heteromorpha (Martius ex Hooker f.) Bentham Licania heteromorpha (Martius ex Hooker f.) Bentham var. glabra (Martius ex Hooker f.) Prance 8 6 11 17 8 22 24 31 18 7 10 11 7 66 7 6 5 10 12 51 13 6 5 2.5 2.7 2.5 2.5 2.8 2.5 2.6 2.6 2.7 2.7 2.8 3.3 3 2.5 2.7 2.6 2.7 3.5 3.3 2.5 2.6 2.7 2.7 17 5.3 13.5 31.4 19.5 34.2 13.3 22.3 19 6.8 30 24.8 11.6 22.3 8.3 6.6 3.7 20.2 27.8 17.3 16.5 16.6 8.2 15 2.5 7.3 6 9 4 2.8 25.8 11.4 8 5 6 14 15 4 2.5 5.6 2.7 2.7 22.7 6.4 45.2 15.2 15.8 8 5 6 23 6 6 6 6.3 2.6 2.7 2.5 2.5 2.7 2.5 61.6 4.2 4.3 16.5 5.5 8.3 7.5 5 22 5 7 8 15 18 18 8 5 41 7 2.8 2.6 3 2.6 2.7 2.7 2.7 2.7 2.8 3.8 2.5 2.5 28 22.2 11.3 25.7 5.2 6.8 24.3 23 7.7 16.4 22.6 21.6 F S 3 2 U W 8 6 11 17 8 19 24 15 18 7 10 11 7 66 7 16 4 5 2 12 51 8 13 1 5 5 15 1 6 8 8 5 6 14 15 8 5 22 1 2 11 2 1 2 1 6 1 5 6 6 5 20 5 7 8 2 18 18 8 4 41 4 Amazonian understorey and canopy patterns A P P E ND I X 517 cont. n Min Max dbh dbh (cm) (cm) Licania intrapetiolaris Spruce ex Hooker f. Licania laevigata Prance Licania lata J.F.Macbride Licania longistyla (Hooker f.) Fritsch Licania micrantha Miquel Licania mollis Bentham Licania MS5402 Licania octandra (Hoffsgg. ex Roemer & Schultes) Kuntze ssp. grandifolia Prance Licania triandra Martius ex Hooker f. Licania urceolaris Hooker f. MS3602 Parinari klugii Prance Parinari cf. rodolphii Huber Combretaceae Buchenavia macrophylla Spruce ex Eichler Buchenavia MS6194 Buchenavia cf. viridiflora Ducke Connaraceae Connarus ruber (Poeppig) Planchon Pseudoconnarus macrophyllus (Poeppig) Radlkofer Convolvulaceae Dicranostyles ampla Ducke Dicranostyles holostyla Ducke Maripa glabra Choisy Maripa janusiana D’Austin Turbina MS6375 Costaceae Costus scaber Ruiz & Pavón Cucurbitaceae Cayaponia oppositifolia Harms Cyatheaceae Cyathea macrosora (Baker) Domin Dichapetalaceae Tapura peruviana K. Krause var. petioliflora Prance Dilleniaceae Doliocarpus cf. macrocarpus Martius ex Eichler Pinzona coriacea Martius & Zuccarini Dipterocarpaceae Pseudomonotes tropenbosii Londoño, Alvarez & Forero Ebenaceae Diospyros aff. glomerata Spruce Diospyros cf. tetrandra Hiern Elaeocarpaceae Sloanea AD4020 Sloanea durissima Spruce ex Bentham Sloanea gracilis Uittien Sloanea guianensis (Aublet) Bentham Sloanea laxiflora Spruce ex Bentham Sloanea longipes Ducke Sloanea parvifructa J.A. Steyermark Ericaceae Satyria panurensis (Bentham ex Meisner) Bentham & Hooker f. Euphorbiaceae Alchornea aff. schomburgkii Klotzsch Amanoa guianensis Aublet F S 2 U W 4 40 2 8 40 6 21 15 15 6 11 2.8 2.5 2.5 2.8 3.3 2.5 3.4 2.6 41.4 27.5 62.3 12 28.3 19.7 21.7 13 9 11 9 10 36 2.5 3 3.4 4 2.5 27.7 14.5 24.5 91.3 19.7 3 7 9 17 2.7 4.8 3.5 10.8 100 20.3 1 5 22 3.2 2.5 5.5 5 5 11 10 8 18 8 2.6 2.5 3.5 2.5 2.5 8.2 5.8 6.8 9.5 5.8 8 16 3 3 16 7 3.2 14 7 6 2.7 5.5 7 2.7 5.3 5 11 3.8 3 11.4 10.6 5 11 20 2.5 77.5 20 8 6 2.6 2.8 4.2 3.7 19 12 5 6 5 5 20 2.7 2.6 2.5 3 3.8 3.2 2.8 12 21.6 13.5 10 35.8 9.9 11.6 19 2.8 5 10 7 2.5 4.8 22.4 14.6 6 1 21 3 10 11 15 6 1 6 11 9 10 35 5 9 16 1 1 1 22 1 3 16 11 6 8 2 6 1 6 1 8 5 4 11 2 6 5 1 19 1 3 20 19 1 6 3 7 518 ALVARO DUQUE ET AL. A P P E ND I X cont. n Min Max dbh dbh (cm) (cm) Conceveiba guianensis Aublet Drypetes amazonica Steyermark Hevea nitida Martius ex Muell.Arg. Hevea pauciflora (Spruce ex Bentham) Muell.Arg. Hyeronima alchorneoides Allemão var. alchorneoides Hyeronima oblonga (Tulasne) Muell.Arg. Mabea aff. angularis G. Den Hollander Mabea maynensis Muell.Arg. Mabea cf. occidentalis Bentham Mabea speciosa Muell.Arg. Micrandra siphonioides Bentham Micrandra spruceana (Baillon) R.E. Schultes Nealchornea yapurensis Huber Omphalea diandra Linnaeus Podocalyx loranthoides Klotzsch Richeria grandis Vahl Sandwithia heterocalyx Secco Sapium marmierii Huber Senefeldera macrophylla Ducke Senefeldera cf. verticillata (Vell.) Croizat Flacourtiaceae Casearia cf. arborea (L.C. Richard) Urban Lindackeria paludosa (Bentham) Gilg MS6960 Neoptychocarpus killipii (Monachino) Buchheim Ryania speciosa Vahl var. tomentosa (Miquel) Monachino Guttiferae Calophyllum AD3923 Calophyllum AD3969 Calophyllum longifolium Kunth Caraipa grandifolia Martius Caraipa myrcioides Ducke Chrysochlamys membranacea Planchon & Triana Clusia amazonica Planchon & Triana Clusia columnaris Engler Clusia decussata Ruı́z & Pavón Clusia gaudichaudii Choisy ex Planchon & Triana Clusia magnifolia Cuatrecasas Clusia MS6280 Clusia spathulifolia Engler Dystovomita AD3976 Dystovomita MS4875 Garcinia macrophylla Martius Garcinia spruceana (Engler) Hammel Haploclathra cf. paniculata (Martius) Bentham Lorostemon bombaciflorus Ducke Lorostemon colombianum Maguire Symphonia globulifera Linnaeus f. Tovomita cf. brevistaminea Engler Tovomita cf. eggersii Vesque Tovomita laurina Planchon & Triana Tovomita MS4222 Tovomita MS4610 Tovomita cf. pyrifolia A.C. Smith Humiriaceae Sacoglottis amazonica Martius Vantanea MS3381 16 22 27 85 5 11 24 17 6 6 24 67 8 6 24 5 97 8 40 53 2.6 2.5 2.6 2.5 7.6 3.3 2.5 2.7 3 3 5.3 2.6 2.6 3.8 2.7 2.7 2.5 6.5 2.5 2.5 15.5 70 20.2 41 65 14.2 10.2 8.2 3.8 4.3 63.5 53.3 15.5 7.2 39 3.7 13.8 25.4 10.6 14.4 9 6 10 54 7 2.6 2.7 3.2 2.5 2.7 28.7 11.3 7.1 6 5.8 12 6 6 30 5 6 6 5 11 6 179 11 67 5 52 14 5 10 23 13 5 13 6 13 44 7 6 2.5 5.2 4 2.6 2.8 2.5 2.8 3 2.7 2.7 3 2.5 3.5 2.5 2.5 2.6 2.5 2.8 2.6 2.5 3.1 2.7 2.7 2.7 2.5 2.7 4.3 12.5 51.7 7.3 17.3 41.8 12 5 5 7.6 4.8 13.5 6 21.8 6.4 13.2 26.6 17 35.5 42.3 18 5.5 11.3 6.5 13.4 6.8 5.2 13.1 10 16 2.5 2.7 16.6 23.3 F S U 15 1 14 60 2 11 24 17 W 22 2 3 27 9 6 6 24 67 8 6 6 9 9 5 97 8 40 53 7 2 6 10 54 7 12 6 6 29 2 3 1 5 4 3 4 11 6 1 22 9 3 10 5 2 23 1 13 5 12 6 13 44 7 6 10 16 1 179 10 67 5 30 Amazonian understorey and canopy patterns A P P E ND I X cont. n Min Max dbh dbh (cm) (cm) Vantanea spichigeri A. Gentry Vantanea? MS3304 Icacinaceae Dendrobangia boliviana Rusby Discophora froesii Pires Discophora guianensis Miers Lacistemaceae Lacistema aggregatum (Bergius) Rusby Lauraceae Anaueria brasiliensis Kostermans Aniba cf. panurensis (Meissner) Mez Aniba cf. williamsii O.C. Schmidt Endlicheria bracteata Mez Endlicheria krukovii (A.C. Smith) Kostermans Licaria aurea (Huber) Kostermans Licaria cannella (Meissner) Kostermans Licaria macrophylla (A.C. Smith) Kostermans Licaria MS4941 Mezilaurus itauba (Meissner) Taubert ex Mez Mezilaurus sprucei (Meissner) Taubert ex Mez MS2926 MS3340 MS3378 MS3385 MS3475 Ocotea aciphylla (Nees) Mez Ocotea amazonica (Meissner) Mez Ocotea argyrophylla Ducke Ocotea bofo H.B.K. Ocotea cf. javitensis (H.B.K.) Pittier Ocotea matogrossensis Vattimo Ocotea MS4959 Ocotea neblinae C.K. Allen Ocotea olivacea A.C. Smith Ocotea cf. petalanthera (Meissner) Mez Ocotea rubrinervis Mez Ocotea cf. tomentella Sandwith Pleurothyrium panurense (Meisn.) Mez Lecythidaceae Cariniana decandra Ducke Cariniana multiflora Ducke Couratari oligantha A.C. Smith Couratari stellata A.C. Smith Eschweilera alata A.C. Smith Eschweilera albiflora (A.DC.) Miers Eschweilera andina (Rusby) J.F. Macbride Eschweilera bracteosa (Poeppig ex O. Berg) Miers Eschweilera coriaceae (A.DC.) S.A. Mori Eschweilera itayensis R. Knuth Eschweilera MS3354 Eschweilera MS3719 Eschweilera MS3776 Eschweilera parvifolia Martius ex A.DC. Eschweilera punctata S.A. Mori Eschweilera rufifolia S.A. Mori Eschweilera tessmannii R. Knuth 519 F S U 5 16 2.7 3 38.5 19.5 5 16 10 3 2.5 2.7 9.8 10 9.5 10 20 2.7 17.5 20 11 5 6 11 7 9 11 8 5 6 9 5 7 11 15 8 63 12 20 17 44 9 8 20 12 8 5 5 9 2.7 14 2.5 6 2.8 13.3 2.8 4.3 2.5 9.6 2.7 8.4 2.5 25.3 2.5 8.2 2.6 5.5 9.3 135.4 2.5 35.4 2.7 6 2.7 14.8 2.5 7.3 2.5 11.6 2.5 4.4 2.7 28.5 3.2 61.5 2.8 21.3 2.5 14.7 2.6 15.3 3 10.3 2.9 13.4 2.7 23.7 2.5 17.3 2.7 26.3 3 10.3 3 5.6 2.7 6.8 11 2 6 2 1 6 10 8 5 6 5 4 7 11 15 8 61 12 20 15 5 9 8 6 5 28 14 41 11 5 5 95 10 24 21 67 78 52 22 29 2.7 3.4 2.5 2.5 2.6 4.5 3 4.1 2.5 2.6 2.6 2.5 2.8 2.5 2.7 2.7 2.5 6.3 63 32.8 18.2 51.5 26.3 8.8 18.2 39.5 23.2 7.8 25.8 34.7 30 63.5 34.5 25.2 W 5 16 5 16 9 6 2 1 1 4 1 2 2 1 8 5 5 9 6 5 28 5 3 3 39 19 12 1 5 3 14 41 7 5 90 7 24 21 67 78 52 22 29 520 ALVARO DUQUE ET AL. A P P E ND I X cont. n Min Max dbh dbh (cm) (cm) Gustavia poeppigiana O. Berg Lecythis chartacea O. Berg Leguminosae Abarema claviflora (Spruce ex Bentham) Keinhoonte Acacia MS6430 Bauhinia guianensis Aublet Brownea cf. macrophylla Linden ex Masters Clathrotropis macrocarpa Ducke Clathrotropis nitida (Bentham) Harms Derris longifolia Bentham Diplotropis martiusii Bentham Dipteryx nudipes Tulasne Heterostemon conjugatus Spruce ex Bentham Heterostemon mimosoides Desfontaines Inga acrocephala Steudel Inga aggregata G. Don Inga archeri Britton & Killip Inga bourgoni (Aublet) DC. Inga cf. brachyrhachis Harms Inga capitata Desvaux Inga chartaceae Poeppig Inga edulis Martius Inga marginata Willdenow Inga pruriens Poeppig Inga ruiziana G. Don Inga tenuistipula Ducke Inga umbellifera (Vahl) Steudel Lonchocarpus nicou (Aublet) DC. Machaerium acutifolium Vogel Machaerium cf. cuspidatum Kuhlmann & Hoehne Machaerium inundatum (Martius ex Bentham) Ducke Machaerium macrophyllum Martius ex Bentham Machaerium madeirense Pittier Machaerium quinata (Aublet) Sandwith Macrolobium cf. angustifolium (Bentham) R.S. Cowan Macrolobium discolor Bentham Macrolobium gracile Spruce ex Bentham Macrolobium cf. limbatum Spruce ex Bentham Macrolobium multijugum (DC.) Bentham Macrolobium suaveolens Spruce ex Bentham Macrosamanea amplissima (Ducke) Barneby & Grimes Monopteryx cf. inpae W. Rodrigues Monopteryx uaucu Spruce ex Bentham MS3170 MS3208 MS3300 MS3451 MS4865 MS6749 Parkia basijuga Benth. Parkia cf. panurensis Bentham & Hopkins Pithecellobium cauliflorum (Willdenow) Martius Swartzia cardiosperma Spruce ex Bentham Swartzia laurifolia Bentham Swartzia MS3534 Swartzia parvifolia Schery Swartzia cf. pendula Spruce ex Bentham 9 10 3.3 2.7 26.8 37.5 14 5 6 70 177 22 13 21 8 48 11 13 5 5 6 43 6 8 6 9 8 16 14 5 7 13 9 8 47 9 9 28 101 36 31 35 57 18 6 13 10 5 12 7 7 5 10 13 82 9 34 41 9 6 2.8 3.4 2.7 2.7 2.5 2.8 2.5 2.8 2.6 2.6 4.2 2.8 2.8 3.2 2.7 2.5 2.6 3 5 3.5 2.6 2.5 2.7 3 2.7 2.8 3.2 2.8 2.5 2.6 2.5 2.6 2.5 2.5 2.8 2.5 2.6 2.6 2.8 4 3.8 3.1 2.5 2.7 2.8 2.8 2.8 2.5 2.5 2.5 2.6 2.5 2.7 2.6 8.8 7.4 6.3 23.3 19.6 35 58 27.7 37.3 12.6 48 25.7 18 9.4 5.3 25.6 6.4 6 43.6 17.2 23.3 6.5 13.8 17.8 5.1 18.5 8 8.6 7.7 5.3 12 39 33.7 21 15.6 28.6 36.5 6.3 12.6 67.5 52.2 8.5 9.2 14.3 15.4 3.7 18.5 38 16.8 17.7 16.5 12.6 7.3 6.6 F S U W 9 10 1 5 5 70 13 1 177 22 13 2 3 17 3 1 5 33 7 2 5 48 11 9 5 5 1 10 6 1 6 3 2 14 5 2 2 12 8 6 8 7 28 4 5 8 12 5 1 1 2 47 1 2 2 5 3 1 26 101 36 3 26 54 18 6 13 7 3 5 6 2 5 80 20 5 6 7 7 5 10 5 7 14 41 9 1 3 2 Amazonian understorey and canopy patterns A P P E ND I X cont. n Min Max dbh dbh (cm) (cm) Swartzia racemosa Bentham Swartzia schomburgkii Bentham Tachigali cf. colombiana Dwyer Tachigali formicarum Harms Tachigali MS3476 Tachigali MS3827 Tachigali MS3846 Tachigali paniculata Aublet Tachigali polyphylla Poeppig & Endlicher Tachigali ptychophysca Spruce ex Bentham Tachigali tessmannii Harms Tachigali ulei Harms Vatairea guianensis Aublet Zygia basijuga (Ducke) Barneby & Grimes Zygia latifolia (Linnaeus) Fawcett & Rendle Zygia macrophylla (Spruce ex Bentham) L. Rico Linaceae Hebepetalum humiriifolium (Planchon) Bentham Roucheria calophylla Planchon Roucheria punctata (Ducke) Ducke Loganiaceae MS3065 Strychnos erichsonii Ri. Schomburgk ex Progel Strychnos cf. peckii B.L. Robinson Malpighiaceae Byrsonima coniophylla A. Juss. MS3315 Marcgraviaceae Marcgravia cf. parviflora L.C. Richard ex Wittmack MS2921 Norantea guianensis Aublet Souroubea guianensis Aublet Melastomataceae Bellucia MS3064 Bellucia MS6188 Graffenrieda cf. limbata Triana Macairea spruceana O. Berg ex Triana Miconia cf. elaeagnoides Cogniaux Miconia spichigera Wurdack Miconia cf. tomentosa (L.C. Richard) D.Don Miconia cf. trinervia (Swartz) D. Don ex Loudon Mouriri cauliflora Martius ex DC. Mouriri huberi Cogniaux Mouriri nigra (DC.) Morley Mouriri vernicosa Naudin Meliaceae Guarea cinnamomea Harms Guarea MS4514 Guarea grandifolia DC. Guarea kunthiana Adrien Jussieu Guarea macrophylla Vahl Guarea purusana C.DC. Trichilia martiana C.DC. Trichilia micrantha Bentham Trichilia cf. obovata W. Palacios Trichilia pallida Swartz 521 17 45 6 13 24 15 7 7 6 19 19 6 35 26 13 18 2.5 2.6 3.2 2.8 2.6 2.5 2.7 4.3 2.5 3 2.5 4.2 3.3 2.6 2.6 2.7 27.8 73.5 27.3 27.2 40.8 14 49.5 68 13.4 10.8 25.8 42.5 27.5 9 27.2 5.9 7 9 17 3.3 2.8 2.7 14 16.6 22.4 5 5 20 2.8 2.5 2.5 3.7 6.5 9.8 12 6 3.5 3.2 6.6 9 7 5 5 9 3 2.8 3.3 2.7 6 4.3 6.8 5.4 5 5 10 11 22 8 6 24 17 5 19 6 4.7 2.5 2.5 3 2.5 2.7 2.8 2.7 2.5 2.7 2.5 3 20.8 7.4 10.5 5.2 7.9 4.5 3.8 8 7.4 22.5 14 15.6 6 12 14 16 5 41 7 11 12 7 3.5 3 2.5 2.5 2.6 2.6 3 2.7 4.5 2.6 32.7 27.1 6.6 6.7 5 49.5 9.4 13.4 18.7 7 F S 12 7 5 1 1 33 13 4 14 8 U W 5 45 1 5 24 15 7 7 6 17 6 1 26 1 1 13 19 2 6 4 5 5 20 12 4 2 6 5 1 5 1 8 5 5 10 11 16 4 2 22 1 2 8 6 17 5 18 6 6 12 14 1 5 15 41 2 1 4 11 12 1 6 522 ALVARO DUQUE ET AL. A P P E ND I X cont. n Min Max dbh dbh (cm) (cm) Trichilia septentrionalis C.DC. Trichilia stipitata T.D. Pennington Menispermaceae Abuta grandifolia (Martius) Sandwith Abuta imene (Martius) Eichler Abuta obovata Diels Sciadotenia cf. toxifera Krukoff & A.C. Smith Telitoxicum minutiflora (Diels) Moldenke Telitoxicum MS3816 Monimiaceae Siparuna decipiens (Tulasne) A.DC. Siparuna guianensis Aublet Siparuna MS3160 Siparuna MS6928 Siparuna pachyantha A.C. Smith Moraceae Brosimum lactescens (S. Moore) C. Berg Brosimum rubescens Taubert Brosimum utile (H.B.K.) Pittier ssp. longifolium (Ducke) C. Berg Brosimum utile (H.B.K.) Pittier ssp. ovatifolium (Ducke) C. Berg Clarisia racemosa Ruı́z & Pavón Ficus cf. juruensis Warburg ex Dugand Helicostylis elegans (J.F. Macbride) C. Berg Helicostylis scabra (J.F. Macbride) Helicostylis tomentosa (Poeppig & Endlicher) J.F. Macbride Maquira MS3114 Naucleopsis glabra Spruce ex Pittier Perebea guianensis Aublet Perebea mennegae C. Berg Pseudolmedia laevigata Trécul Pseudolmedia laevis (Ruı́z & Pavón) J.F. Macbride Sorocea hirtella Mildbraed ssp. hirtella Sorocea hirtella Mildbraed ssp. oligotricha Akkermans & C. Berg Sorocea muriculata Miquel Trymatococcus amazonicus Poeppig & Endlicher Myristicaceae Compsoneura cf. capitellata (A.DC.) Warburg Iryanthera elliptica Ducke Iryanthera juruensis Warburg Iryanthera cf. laevis Markgraf Iryanthera lancifolia Ducke Iryanthera MS5064 Iryanthera polyneura Ducke Iryanthera tricornis Ducke Iryanthera ulei Warburg Osteophloeum platyspermum (A.DC.) Warburg Virola calophylla Warburg Virola duckei A.C. Smith Virola elongata (Bentham) Warburg Virola marlenei W.A. Rodrigues Virola MS3102 Virola MS3311 Virola MS3344 Virola MS3580 6 11 2.7 2.5 9.6 6 8 25 8 5 6 15 2.7 2.5 3 3 3 2.6 12.7 7 12.1 11.5 5.4 7.8 5 18 7 5 5 2.6 2.6 2.7 3.6 3.4 10.5 8 5.3 43 9.5 17 11 13 2.5 2.7 2.5 105 29 23.1 14 2.7 48.5 6 5 12 11 6 5 6 12 10 32 15 23 24 4.2 6.4 2.8 2.8 2.6 3 3.2 2.7 2.7 2.6 2.8 2.7 2.5 37.4 10 24.2 29 9 69.3 26.8 6 5.5 16.5 25.7 10.6 22 20 16 2.5 2.7 6.6 9.4 19 28 7 5 13 9 113 34 56 6 37 5 45 15 6 5 30 18 2.5 2.6 2.5 2.7 2.6 3.3 2.5 2.6 2.5 2.5 2.7 6.6 2.7 2.5 6.3 2.7 2.5 2.5 12.7 29 6.6 23 17.8 13.5 22.8 44 16.5 43.6 31.8 21 18 6.7 30 5.2 25.4 21.7 F S U 8 6 3 3 W 8 25 8 5 3 15 5 18 7 5 5 11 1 5 11 13 3 9 2 5 2 4 12 11 6 5 3 3 10 1 1 1 12 13 19 3 12 10 29 15 23 14 18 16 19 28 4 5 13 9 78 34 44 6 24 5 26 15 6 5 30 18 3 34 Amazonian understorey and canopy patterns A P P E ND I X cont. n Min Max dbh dbh (cm) (cm) Virola MS4508 Virola MS5088 Virola MS6222 Virola aff. multinervia Ducke Virola pavonis (A.DC.) A.C. Smith Virola surinamensis (Rolander) Warburg Myrsinaceae Stylogine cf. longifolia (Martius ex Miquel) Mez Myrtaceae Eugenia cf. beaurepairiana (Kiaersk.) Legrand Eugenia coffeifolia DC. Eugenia florida DC. Eugenia patens Poiret Marlierea caudata McVaugh Marlierea cf. schomburgkiana Berg Marlierea aff. spruceana O. Berg Marlierea cf. umbraticola (H.B.K.) O. Berg MS3412 Myrcia fallax (L.C. Richard) DC. Myrcia splendens (Swartz) DC. Myrciaria cf. floribunda (West ex Willdenow) O. Berg Plinia cf. duplipilosa McVaugh Nyctaginaceae Neea cf. macrophylla Poeppig & Endlicher Neea parviflora Poeppig & Endlicher Neea spruceana Heimerl Neea verticillata Ruı́z & Pavón Ochnaceae Ouratea chiribiquetensis Sastre Ouratea MS3608 Olacaceae Aptandra caudata A. Gentry & Ortiz Aptandra cf. tubicina (Poeppig) Bentham ex Miers Heisteria acuminata (Humboldt & Bonpland) Engler Heisteria barbata Cuatrecasas Heisteria duckei Sleumer Minquartia guianensis Aublet Tetrastylidium cf. peruvianum Sleumer Palmae Astrocaryum sciophillum (Miquel) Pulle Bactris maraja Martius var. maraja Euterpe precatoria Martius Iriartea deltoidea Ruı́z & Pavón Iriartella setigera (Martius) H. Wendland Lepidocaryum tenue Martius Mauritia carana Wallace Mauritia flexuosa L.f. Mauritiella aculeata (Kunth) Burret Oenocarpus bacaba Martius Oenocarpus bataua Martius Socratea exhorriza (Martius) H. Wendland Wettinia augusta Poeppig & Endlicher Polygalaceae Moutabea cf. guianensis Aublet Quiinaceae Quiina peruviana Engler 523 F 8 5 18 9 44 78 2.5 2.5 2.7 3.5 2.5 2.5 6.8 21.5 11.6 30.6 36 22.2 5 12 2.6 6.4 12 5 16 28 8 39 17 30 18 6 9 5 5 11 2.7 2.5 2.5 3 2.6 3.3 2.5 2.6 3.3 2.6 3 3.3 2.6 15.6 12.5 15 8 6.6 10.2 7.7 7.7 21.7 15.3 11.9 6 4.5 5 8 7 12 9 2.5 2.8 2.7 2.7 5.5 17.6 10.5 5.4 13 6 2.8 2.6 16.8 9.8 9 31 5 11 5 11 6 2.7 2.6 3 2.7 3 3.6 2.6 4.8 38 4.8 10 19 29.8 26 9 19 70 18 33 22 12 72 11 5 28 28 21 2.8 2.5 2.5 4.4 2.5 2.6 10.6 3.2 10 3.4 2.8 2.7 2.6 19 5.5 18 25.5 5.5 4 48.5 44.7 14.8 11.6 25.7 14.5 9.2 9 19 24 16 24 2.6 14.7 9 13 2.9 11.6 S U W 3 5 18 1 5 31 9 38 1 46 16 21 7 28 1 8 3 8 17 29 15 6 9 5 5 11 8 7 11 4 1 5 13 6 9 1 1 11 5 9 6 4 2 44 30 2 2 33 22 12 72 11 1 1 4 26 28 21 15 13 1 524 ALVARO DUQUE ET AL. A P P E ND I X cont. n Min Max dbh dbh (cm) (cm) Rhamnaceae Ampelozizyphus amazonicus Ducke Rhizophoraceae Sterigmapetalum obovatum Kuhlman Rubiaceae Alibertia cf. hispida Ducke Alseis MS3154 Botryarrhena pendula Ducke Calycophyllum MS4415 Calycophyllum obovatum (Ducke) Ducke Chimarrhis gentryana Delprete Coussarea brevicaulis Krause Coussarea cf. cephaeloides C.M. Taylor Coussarea aff. macrophylla Muell.Arg. Duroia bolivarensis Steyermark Duroia saccifera (Martius ex Roemer & Schultes) Hooker f. ex K. Schumann Faramea capillipes Muell.Arg. Faramea sessilifolia (H.B.K.) DC. Ferdinandusa chlorantha (Wedd.) Standley Ferdinandusa cf. loretensis Standley Pagamea macrophylla Spruce ex Bentham Palicourea nigricans Krause Platycarpum rugosum Steyermark Posoqueria panamensis (Walp. & Duchass.) Walp. Psychotria cf. sororiella Muell.Arg. Remijia pedunculata (H. Karsten) Flueck. Rudgea cf. duidae (Standley) Steyermark Rudgea loretensis Standley Warszewiczia coccinea (Vahl) Klotzsch Warszewiczia schwackei K. Schumann Sabiaceae Ophiocaryon heterophyllum (Bentham) Urban Ophiocaryon cf. klugii Barneby Ophiocaryon manausense (W. Rodrigues) Barneby Sapindaceae Matayba inelegans Radlkofer Talisia eximia K.U. Kramer Talisia nervosa Radlkofer Sapotaceae Chrysophyllum prieurii A.DC. Chrysophyllum sanguinolentum (Pierre) Baehni Chrysophyllum sanguinolentum (Pierre) Baehni ssp. balata (Ducke) Pennington Chrysophyllum superbum Pennington Ecclinusa lanceolata (Martius & Eichler) Pierre Micropholis casiquiarensis Aubréville Micropholis egensis (A. De Candolle) Pierre Micropholis guyanensis (A. De Candolle) Pierre Micropholis maguirei Aubréville Micropholis melinoniana Pierre Micropholis venulosa (Martius & Eichler) Pierre MS3653 Pouteria bangii (Rusby) Pennington Pouteria cuspidata (A. de Candolle) Baehni Pouteria cf. gongrijpii Eyma Pouteria guianensis Aublet F S U 21 2.5 7.4 21 5 2.5 16.4 5 24 8 9 5 83 5 12 5 7 21 17 2.5 3.2 2.7 3 2.5 4.2 2.5 2.8 2.7 2.6 2.7 9.6 11 7.4 20.8 21.8 23.4 17.5 9 6.8 21.6 8.8 6 5 16 14 34 7 14 8 6 8 7 7 6 17 2.5 2.6 2.7 2.7 2.5 2.5 4.2 2.8 2.5 2.6 2.5 2.7 2.8 2.7 3.8 9 9.3 45.4 19.4 14 51.8 7.2 4.2 16.6 4.1 6.8 58.2 17.6 23 8 25 2.6 2.8 2.6 12.3 11.4 8.8 6 13 17 2.7 2.7 2.7 5.8 7.4 7.3 5 52 8 2.5 2.5 7.6 26.8 45.8 34.8 6 16 13 5 58 35 8 6 5 8 49 11 34 2.8 2.5 2.7 2.6 2.5 2.6 2.8 3.7 5.8 2.7 2.5 2.8 2.5 5.2 6.6 16.5 7.6 31 39.8 23 31.8 25.4 33.6 20.4 10.6 23.8 23 W 1 8 7 2 5 83 5 12 5 7 20 1 17 6 4 1 7 4 4 3 5 5 1 1 2 7 2 2 3 5 6 24 9 22 8 25 6 11 8 1 5 25 4 27 4 6 14 13 3 1 8 5 3 10 10 7 1 5 6 8 7 2 1 17 7 33 4 8 4 5 22 31 36 11 29 1 1 Amazonian understorey and canopy patterns A P P E ND I X cont. n Min Max dbh dbh (cm) (cm) Pouteria MS3953 Pouteria MS4770 Pouteria MS5774 Pouteria oblanceolata Pires Pouteria reticulata (Engler) Eyma ssp. reticulata Pouteria rostrata (Huber) Baehni Pouteria torta (Martius) Radlkofer Pouteria cf. williamii (Aubréville & Pellegrin) Pennington Simaroubaceae Picramnia latifolia Tulasne Picramnia MS3384 Sterculiaceae Theobroma cacao Linnaeus Theobroma microcarpum Martius Theobroma subincanum Martius Violaceae Leonia cymosa Martius Leonia glycycarpa Ruı́z & Pavón Leonia MS6512 Rinorea MS3183 Rinorea neglecta Sandwith Rinorea racemosa (Martius) Kuntze Vochysiaceae Erisma bicolor Ducke Erisma splendens Stafleu Qualea acuminata Spruce ex Warming Qualea ingens Warming Qualea paraensis Ducke Vochysia lomatophylla Standley Vochysia MS6230 View publication stats 525 F 7 5 5 5 9 14 31 19 3.2 3.8 4 3.8 2.8 2.7 2.6 2.6 34.5 5.2 35.3 15.5 19 26.8 30.5 20.4 10 7 2.7 2.7 10 8.8 6 66 9 13 2.7 3 2.8 25.5 35.8 12.3 66 9 27 8 18 15 17 64 2.5 2.5 2.6 2.7 2.5 2.5 6 30.5 31.3 8.8 6.5 13 11 5 26 11 11 16 19 2.6 3.3 2.7 3.6 2.7 2.5 2.6 16.2 10.8 15 75.5 41.3 5.3 39.5 S 2 23 U 7 5 5 2 3 10 8 19 4 6 13 27 2 18 6 15 17 24 40 11 5 6 26 5 11 15 1 19 W 3 4 4 1