Folia Geobot DOI 10.1007/s12224-015-9225-9
Effects of the hydroedaphic gradient on tree species composition and aboveground wood biomass of oligotrophic forest ecosystems in the central Amazon basin Natália Targhetta & Jürgen Kesselmeier & Florian Wittmann
Received: 10 June 2013 / Revised: 15 January 2015 / Accepted: 2 August 2015 # Institute of Botany, Academy of Sciences of the Czech Republic 2015
Abstract Amazonian forests in black-water floodplains (igapó) and upon hydromorphic white-sand soils (campinarana) cover at least 500,000 km2 of the area of the Amazon basin, but are poorly investigated ecosystems. We compared variation in tree species richness and composition (≥ 10 cm diameter at breast height), as well as forest structure and aboveground wood biomass (AGB) along hydroedaphic gradients in an igapó and a campinarana in the central Brazilian Amazon, in an area totalling 6 ha. Inundation height (igapó) and groundwater level oscillations (campinarana) were monitored during a one year period. Soil grain sizes and chemical variables were analysed. Variation in tree species composition was assessed using non-metric multidimensional scaling, and soil parameters using principal component analysis. The influence of hydroedaphic gradients on tree species richness, composition and AGB was investigated using partial and multiple regression analyses. Significant differences in soil texture, soil chemical variables, and tree species richness and composition were detected between both forest types, while AGB amounted to similar values, ranging from 141 ± 62 Mg·ha−1 in the igapó to 164 ± 121 Mg·ha−1 in the
N. Targhetta (*) Instituto Nacional de Pesquisas da Amazônia, Programa de Pós-Graduação em Ecologia, Av. André Araújo, 2936 Manaus, AM, Brazil e-mail:
[email protected] J. Kesselmeier : F. Wittmann Biogeochemistry Department, Max Planck Institute for Chemistry, Mainz-Germany, Hahn-Meitner-Weg 1, 55128 Mainz, Germany
campinarana. Although both forest types were floristically distinct, inundations in the igapó and groundwater table oscillations in the campinarana influenced patterns of species richness and forest structure in similar ways, indicating decreasing species richness, forest stature and AGB in plots subjected to higher inundations and/or groundwater levels. Given the comparatively low AGB in the ecosystems studied, we call attention to the need for more studies in oligotrophic ecosystems of the Amazon basin with emphasis on their contribution to global carbon cycles. Keywords Amazon . flood-pulse . groundwater level . soil texture . white sand forest
Introduction Coarse forest aboveground wood biomass (AGB) plays an important role in the global carbon cycle, and its estimations are important because they are both a reservoir of carbon and a source of greenhouse gas emissions from deforestation (Houghton et al. 2000; Malhi et al. 2006). Tropical forests play a crucial role in the global carbon cycle, as they comprise approximately 40 % of all carbon estimated to be stored in terrestrial vegetation (Houghton 2005; Malhi et al. 2006). There are numerous AGB estimations for Amazonian forests, ranging from local plot-levels to extrapolations on a continental-wide scale (Houghton et al. 2001; Baker et al. 2004a; Chave et al. 2005; Malhi et al. 2004, 2006; Saatchi et al. 2007). However, the
N. Targhetta et al.
Amazon basin contains a variety of different ecosystems with strong differences in tree species composition, forest structure and AGB. Some of these have been scarcely studied despite their extension comprising several thousands of square kilometres. Amongst the less studied ecosystems in the Amazon are seasonally flooded black-water forests (igapó sensu Sioli 1954) and forests growing on white-sand soils (campinarana sensu Takeuchi 1960). The area covered by these ecosystems covers at least 500,000 km2 (see Prance and Daly 1985 for campinarana, and Melack and Hess 2010 for igapó). To date, floristic inventories covering only a total sample area of < 50 ha are available in the literature about Amazonian igapó and white-sand forest (Wittmann et al. 2010; Stropp et al. 2011), and only few of them provide biomass estimations on the plot level. Although being scarcely inventoried in comparison to other Amazonian forest types, igapó and campinarana forests have been repeatedly reported as ecosystems where tree species share similar environmental constraints. Both ecosystems are oligotrophic with lowproductivity, characterized by nutrient-poor, mostly sandy substrates combined with episodically (campinarana) or periodically (igapó) inundations by rain or river waters (Junk et al. 2011). Besides inundations, igapó and campinarana forests undergo droughts when low precipitation coincides with lowered groundwater tables during the dry seasons, which are aggravated by low water-retention capacity of sandy soils (Parolin et al. 2009). As a consequence, forests of both ecosystems are dominated by small trees and shrubs, harbour comparatively low species diversity, and house many endemic tree species (Kubitzki 1989; Fine et al. 2010). In addition, both ecosystems are considered to share many tree species (i.e. Klinge and Medina 1979; Vicentini 2004; Damasco et al. 2013). There are, however, some substantial environmental differences between both ecosystems. While the central Amazonian igapó forests undergo seasonal inundations where trees are subject to inundations of up to 230 days year−1, trees of many campinaranas are shallowly flooded during the rainy season by an oscillating ground-water table (Coomes 1997; Vicentini 2004). Campinaranas harbour a continuum of different forest physiognomies that range from open grasslands (campinas sensu Prance 1975) to closed-canopy forests. In the central part of the Amazon, campinaranas are mostly small in extension and occupy areas of a few
square kilometres geographically interspersed in the uplands (Veloso et al. 1991; Vicentini 2004). By contrast, the seasonally flooded igapó forests occur linearly along rivers such as the Negro and its tributaries, where they cover an area of > 100,000 km2 (Melack and Hess 2010). Tree species are strongly zoned along the floodlevel gradient (Ferreira 1997; Wittmann et al. 2010), and many tree species are characterized by the development of specific adaptations to seasonal inundations and associated oxygen deprivation, such as the development of hypertrophic lenticels, the formation of aboveground roots, pronounced leaf shedding and reduced metabolism and growth during flooding (Worbes 1989; Parolin et al. 2004; Schöngart et al. 2005). The few AGB estimations available for Amazonian campinarana and igapó forests indicate high variability, ranging from 15.9 Mg·ha−1 in a shrubby, northAmazonian campina (Barbosa and Ferreira 2004) to 237 Mg·ha−1 in a tall Amazonian Caatinga (Klinge and Herrera 1983). More recently, Baraloto et al. (2011) estimated the AGB in several white-sand forest plots in Peru and French Guiana, where AGB ranged from 78 (Peru) to up to 300 Mg·ha−1 (French Guiana). In Amazonian igapó, AGB estimations from the central Amazon range from 68–360 Mg·ha −1 (Schöngart et al. 2010). In summary, these values suggest that both campinarana and igapó forests have lower AGB than Amazonian upland forests (300–370 Mg·ha−1, Malhi et al. 2004; Baraloto et al. 2011) and also lower AGB than Amazonian white-water floodplain (várzea) forests (170–400 Mg·ha−1; Nebel et al. 2001; Schöngart et al. 2010). Despite sharing similar abiotic constraints for vegetation, to the best of our knowledge comparative studies of the floristic composition, forest structure and AGB in campinarana and igapó forests have never been performed. In the present study, we inventoried the tree vegetation of a campinarana and an igapó forest in the central Brazilian Amazon, and compared its species composition, richness, forest structure and AGB in relation to height and duration of inundation and/or groundwater-level oscillations, as well as in relation to edaphic variables. Specifically, we address the following questions: (1) Are there any differences in species composition and richness between both ecosystems? (2) Is AGB different between ecosystems? (3) How do edaphic variables and seasonal inundation (igapó) and groundwater table oscillations (campinarana)
Effects of the hydroedaphic gradient on tree species composition
affect species composition, richness and AGB in each of the inventoried ecosystems?
The study was performed at the Uatumã Sustainable Development Reserve (USDR), approximately 150 km NE of the city of Manaus, central Brazilian Amazon, in close proximity to the Amazonian Tall Tower Observatory (ATTO, Fig. 1). ATTO is a long-term Brazilian-German scientific project established in 2008. The project involves the construction of a tall tower with a height of > 300 m in a pristine Amazonian forest to monitor gas exchanges
between the biosphere and the atmosphere. The USDR is cut by the river Uatumã through its entire NE-SW extension. The climate is tropical humid, with a pronounced rainy season from February to May and a dry season from June to October, with mean annual temperature of 28°C and mean annual precipitation of 2,376 mm (IBGE 2012). The USDR consists of different forested ecosystems. While the tower site is located approximately 12 km SE of the river Uatumã, where dense, non-flooded upland forests (terra firme) prevail on plateaus at a maximum altitude of approximately 130 m a.s.l., igapó forests dominate along the main-river channel and oxbow lakes of the river Uatumã (approximately 25 m a.s.l.). Intercalated within these formations are non-flooded terra firme forests on ancient river terraces and
Fig. 1 Location of half-hectare plots in igapó (I) and campinarana (C) forests of the Uatumã Sustainable Development Reserve (Map source: Google Earth), which is located in the eastern part of
Amazon State, Brazil. a – modified from CEUC (2009), b – obtained from CBERS satellite images provided by the Brazilian National Institute for Space Research (INPE).
Material and methods Study area
N. Targhetta et al.
campinaranas (35–45 m a.s.l.), located between the river terraces and the plateau slopes.
Environmental variables
During the dry season 2010/2011, six half-hectare (50 × 100 m) plots were established in each of the investigated ecosystems, totalling an inventoried area of six ha (three ha per ecosystem). The plots were allocated on different topographic levels in order to capture maximum variation of forests along the hydrological gradient (Table 1). Distances between plots of the same ecosystem ranged from 0.5–3.5 km, while average distance of plots between the two ecosystems was approximately 6 km. To facilitate the floristic inventory, each plot was divided into eight 25 × 25 m (625 m2) sub-plots. All trees ≥ 10 cm DBH were numbered and measured in diameters. Tree heights were determined using a clinometer (Suunto PM5/360 PC, Finland). Sterile and fertile material was collected and voucher specimens transported to the INPA herbarium in Manaus for identification.
Mean flooded period (days year−1) of igapó trees was calculated by using maximum flood marks of the last high-water period on trunks relative to the daily waterlevels of the Balbina P8-gauge from 1977–2011 at the river Uatumã provided by the Brazilian National Water Agency (ANA). In the campinarana, five sensors of water pressure equipped with dataloggers (Levelogger, Solinst, Canada) were installed in plastic tubes to depths ranging from 1.0–3.3 m below surface to monitor groundwater oscillation during the period of one year (June 2011 – June 2012). The data-loggers convert water pressure to their equivalent water column above it. However, at one campinarana topographic level, the groundwater table was below 4-m depth, thus we were not able to establish the tubes and sensor. This plots had to be excluded from analyses investigating the influence of hydrology on composition and structural parameters. For chemical and physical soil characterization, one soil sample was collected to 20 cm depth from the centre of each of the forty-eight 625 m2 sub-plots. The samples
Table 1 Area inventoried, number of individuals and species, aboveground wood volume (AGV), aboveground biomass (AGB) and hydrological variables for the six topographic levels (0.5-ha plots) of the investigated igapó and campinarana. AGVand AGB represent mean values (± SD) of each eight 625-m2 subplots. AGB represents average values derived from both models A
and B (see text for explanation). In the igapó, inundation represents the average for the eight 625-m2 sub-plots (± SD). In the campinarana, groundwater depth represents the average of the daily measurements from June 2011 until June 2012 (SD). Min/ Max values represent minimum and maximum groundwater depths in campinarana plots
Floristic inventories
Area [ha]
Individuals [n]
Species [n]
AGV [m3]
AGB [Mg]
Hydrological variables Inundation [days·year-1]
Igapó P1
0.5
344
27
7.9 ± 2.1
5.9 ± 1.6
78 ± 43
P2
0.5
196
31
18.5 ± 8.3
12.2 ± 6.0
20 ± 7
P3
0.5
526
29
12.6 ± 2.8
9.6 ± 2.0
62 ± 32
P4
0.5
402
24
16.3 ± 3.7
12.0 ± 2.4
11 ± 5
P5
0.5
306
14
10.0 ± 4.9
5.5 ± 2.7
203 ± 13
P6
0.5
389
9.9 ± 2.4
15 ± 1
Total
3.0
2,163
20 69
22.3 ± 7.2 701.1
440.8
Campinarana
Groundwater depth [cm]
Min/Max [cm]
P1
0.5
331
71
21.6 ± 7.6
15.4 ± 5.7
281.2 ± 56.9
147.5 / 328.4
P2
0.5
229
26
11.4 ± 4.3
8.4 ± 3.2
198.1 ± 24.3
125.9 / 218.3
P3
0.5
298
36
6.9 ± 3.8
5.2 ± 2.9
P4
0.5
205
30
9.4 ± 6.9
7.1 ± 5.4
P5
0.5
456
29
10.6 ± 5.0
7.4 ± 3.3
P6
0.5
330
52
22.4 ± 15.5
15.2 ± 12.3
Total
3.0
1,849
122
659.9
474.2
119 ± 40.7 244.7 ± 3.5 74.6 ± 27.5 No data
21.8 / 153.6 215.7 / 248.9 10.3 / 98.7 No data
Effects of the hydroedaphic gradient on tree species composition
were joined and mixed to form two composite soil samples for each 0.5-ha plot. Soil samples were ovendried and analysed at the Brazilian Agricultural Research Company, following standardized protocols described in EMBRAPA (1997). The following variables were analysed: contents of sand, silt and clay (pipette method), content of C (dry combustion), N (Kjeldahl digestion), P (digestion in H2SO4), K+, Ca2+, Mg2+, Al3+, Sum of Bases – SB (K+ + Ca2+ + Mg2+), Fe, Zn+, Mn2+, Cu (atomic absorption spectrophotometry) and pH (pH-meter).
Biomass estimations Tree allometric models were chosen considering that AGB estimates in tropical forests are most accurate when taking into account diameter (DBH), tree height (H) and specific wood density (ρ – Chave et al. 2005). Tree AGB was estimated using two allometric models. Model I was developed by Cannel (1984) and is widely used in tropical floodplain forest AGB estimations (Worbes 1997; Nebel et al. 2001; Wittmann et al. 2008; Schöngart et al. 2010). In model I, tree biomass is estimated as a function of the individual aboveground wood volume [(AGV = π (DBH/2)2 × H × F)] multiplied by (ρ – specific wood density), where F is the correction factor which takes into account biomass losses of the aboveground wood due to ramifications in the canopy. Model II was developed by Chave et al. (2005) based on 2,410 harvested trees from tropical moist forest [Tree Biomass = 0.0509 × ρ × H × (DBH)2], and also takes into account DBH, H and ρ. Palm (Arecaceae) biomass (Palm Biomass = 10 + 6.4 × H) was developed by Frangi and Lugo (1985) and takes into consideration only H, due to the different architecture of palms and the lack of timber production (Brown 2002). Tree and palm allometric models were then combined and resulted in two different total AGB models (AGB = model I + model III; AGB = model II + model III). In our tree species, we obtained ρ based on available data in literature (Appendix 1). For those species with no available information on ρ, we applied the mean specific wood density available for species of the same genus. Although ρ may vary between species of the same genus, this variation is generally small (Fearnside 1997; Chave et al. 2005). When no information on ρ was available at the generic level we applied the average ρ-value of the respective plot to this
individual and/or species (Baker et al. 2004b; Wittmann et al. 2008). Data analysis Species richness (S) was determined by the total species numbers in each plot, and diversity by Fisher’s alpha coefficient (Fisher et al. 1943). To test if the sampled area is representative, rarefaction curves were produced based on 1,000 random iterations. These curves used data pooled from all plots within the same ecosystem and indicated the expected number of species added per 100 sampled individuals. Family and species importance in each plot and ecosystem were determined using total importance values (TIV, Curtis and McIntosh 1951). The quantitative variation on species composition within and between the investigated ecosystems was calculated using BrayCurtis’ dissimilarity index (Bray and Curtis 1957). In order to reduce the dimensionality of the floristic data, we performed two-dimensional non-metric multidimensional scaling (NMDS) considering all plots from both the igapó and the campinarana, based on the matrix of pair-wise Bray-Curtis distances between plots. Twodimensional NMDS was also performed in both ecosystems separately. As stated above, one campinarana 0.5 ha-plot without hydrological data was excluded from this latter analysis. In the campinarana, groundwater depths were attributed to all other plots when they were located at similar topographic positions. Average inundation period (days·year−1) in the igapó was calculated for each 625 m2 sub-plot based on measurements on all present individuals. The 12 edaphic variables on physical and chemical soil properties were standardized by its maximum value and analysed in a principal component analysis (PCA). As we were interested in the influence of soil parameters on vegetation patterns, we considered only the first axis (PC1) resulting from the PCA in further analyses. To analyse the influence of single soil variables on floristic composition, we additionally performed a simple regression analysis between them and the NMDS. To examine the relation between floristic composition and AGB with abiotic variables [flooding period in igapó, groundwater depth in campinarana and soil characteristics (PC1) in both ecosystems], floristic composition (NMDS) and an indirect measure of biomass, the structural conversion factor (SCF; plot AGB/plot basal area; Baker et al.
N. Targhetta et al.
2004a; Malhi et al. 2006) were used as dependent variables in linear and/or multiple regression models. For analysis and results considering AGB and SCF, we considered average values of AGB from both models A and B. All analyses were performed using R version 2.14.1 (R Development Core Team 2011).
Results Environmental variables Mean flood duration in the 0.5 ha-plots of igapó ranged from 11 to 203 days·year−1 (Table 1). Mean groundwater depth in the five 0.5 ha-plots ranged from 281 to 74 cm below the ground surface during June 2011 – June 2012. Groundwater amplitudes between the dry and rainy season were variable, and ranged from the minimum of 10 cm (plot 5) to the maximum of 328 cm (plot 1; Table 1). Both ecosystems were characterized by nutrient-poor soils of comparatively high acidity. Soil texture in the campinarana plots was homogeneously sandy, whereas the igapó plots possessed variable textures, with predomination of silt and clay (Table 2). Contents of most analysed elements and exchangeable bases in igapó soils were more variable than in campinarana soils. Exchangeable bases, C, N, P, K in the igapó were twoto three-fold higher than those in the campinarana and 10-fold for Fe (Table 2). The first axis (PC1) resulting from the PCA ordination explained 43 % and 34 % of the variation on soil characteristics, respectively for the igapó and the campinarana. In the igapó, edaphic variables that highly loaded onto PC1 were C, N, Al, Fe and Mn. In the campinarana, edaphic variables highly loaded onto PC1 were sand, clay, N, Al and Fe (Table 2). Tree species composition, richness and diversity The floristic inventory yielded a total of 4,012 trees ≥ 10 cm DBH, belonging to 47 families, 125 genera and 187 species (igapó: 2,163 individuals, 35 families, 57 genera, 69 species; campinarana: 1,849 individuals, 38 families, 87 genera, 122 species, Appendix 1). Tree species composition between both ecosystems was markedly different at family and generic taxonomic levels (Table 3). Twenty-six families were common to
both ecosystems, while the campinarana harboured 12 and the igapó harboured nine exclusive families. Only 19 genera were common to both ecosystems, while the campinarana had 68 and the igapó had 38 exclusive genera. The 10 most important tree species accounted for 62 % of all individuals and 51 % of total importance in the igapó, and for 44 % of all individuals and 43 % of total importance in the campinarana (Table 4). Tree species richness per 625 m2 sub-plot ranged from 5–18 species in the igapó and alpha diversity (Fisher) from 1.81 to 25.98 (mean: 5.99 ± 4.01). In the campinarana, tree species richness per 625 m2 sub-plot ranged from 7–28 species and alpha diversity from 3.43 to 30.35 (mean: 10.74 ± 6). Species richness between the investigated ecosystems was significantly different (t-test: mean of x = 11.33, mean of y = 15.10, P < 0.001). Species rarefaction curves indicated that sampling effort was sufficient in the igapó, while an asymptote could not be reached in the campinarana (Fig. 2). Floristic dissimilarity between the ecosystems amounted to 0.97, with only four shared tree species (Cordia sp., Couepia paraensis, Macrolobium bifolium and Pouteria elegans). Mean floristic dissimilarity within igapó plots amounted to 0.82 ± 0.21, and within campinarana plots to 0.81 ± 0.16. The axis from one-dimensional NMDS explained 47 % and 62 % of the variation of species composition among the igapó and campinarana plots, respectively, and 48 % considering both ecosystems (two-dimensional NMDS, Fig. 3). NMDS in the igapó was significantly related to silt, P, Al, Fe, Zn, Mn and Cu (Table 5). In the campinarana, NMDS was significantly related to all investigated soil variables with the exception of silt, C, P and Cu (Table 5). Multiple regression analysis indicated that flood duration together with soil characteristics explained 65 % of floristic variation in igapó plots (Table 6). Flood duration and PC1 were significantly correlated (R = 0.43, P < 0.01). In general, tree species that colonized the highest flood levels (e.g. Simaba guianensis, Coccoloba sp.) also occurred upon soils with elevated contents of clay whereas less flood-tolerant tree species (e.g. Erisma calcaratum, Vitex cymosa) occurred upon intermediate to sandy substrates (Fig. 4a, b). In the campinarana, groundwater depth along with soil characteristics explained 73 % of the floristic variation (Table 6). Ground water tables and PC1 were also
Effects of the hydroedaphic gradient on tree species composition Table 2 Edaphic variables of igapó and campinarana soils and their ecosystem-level differences as indicated by a t-test. Each value was derived by its average in 12 soil samples (two per topographical elevation and 0.5-ha plot, SD). Numbers in Edaphic variables
Igapó
parenthesis indicate the correlation coefficients with the first axis (PC1) resulting from a principal component analysis (PCA) using 12 textural and chemical soil variables
Campinarana
Texture
t-test Mean Igapó
93.4 ± 1.5 (0.71)
Mean Campinarana
P
Sand [%]
15.7 ±16.3 (−0.55)
15.68
93.36
< 0.001
Silt [%]
31.7 ± 7.6 (0.34)
4.8 ± 0.8 (−0.27)
31.67
4.81
< 0.001
Clay [%]
52.6 ± 12 (0.53)
1.8 ± 1.0 (−0.90)
52.65
1.83
< 0.001
C [%]
3.5 ± 0.9 (0.85)
1.2 ± 0.2 (−0.42)
3.46
1.17
< 0.001
N [%]
0.3 ± 0.07 (0.80)
0.06 ± 0.01 (−0.76)
0.26
0.06
< 0.001
P [mg·dm−3]
6.1 ± 2.2 (−0.60)
4.7 ± 1.8 (0.39)
6.08
4.75
< 0.01
39.16
13.33
< 0.001
Chemistry
K [mg·dm−3]
39.2 ± 8.2
13.3 ± 3.5
Ca [Cmolc·dm−3]
0.05 ± 0.01
0.03 ± 0.01
0.06
0.03
< 0.001
Mg [Cmolc·dm−3]
0.1 ± 0.01
0.06 ± 0.01
0.11
0.06
< 0.001
−3
Al [Cmolc·dm ]
2.8 ± 0.9 (0.79)
0.8 ± 0.2 (−0.79)
2.81
0.84
< 0.001
Sum of Bases [Cmolc·dm−3]
0.3 ± 0.03 (0.50)
0.15 ± 0.02 (0.17)
0.29
0.16
< 0.001 < 0.001
Fe [mg·dm−3]
215.9 ± 181.2 (−0.88)
13.5 ± 9.5 (−0.89)
215.91
13.50
Zn [mg·dm−3]
0.5 ± 0.1 (−0.51)
0.2 ± 0.1 (0.36)
0.51
0.24
< 0.001
Mn [mg·dm−3]
1.6 ± 1.05 (−0.89)
0.5 ± 0.1 (0.48)
1.62
0.48
< 0.001
Cu [mg·dm−3]
0.35 ± 0.4 (0.23)
0.07 ± 0.01 (−0.22)
0.35
0.07
< 0.001
pH (H2O)
4.05 ± 0.2
4.27 ± 0.32
4.05
4.27
< 0.001
significantly correlated (R = −0.49, P < 0.01). Tree species that colonized sites with deeper groundwater tables (e.g. Eschweilera bracteosa, Protium apiculatum) mostly were those upon substrates with higher amounts of clay, whereas tree species that colonized sites with higher groundwater tables (e.g. Pagamea coriacea, Mauritia carana) were those that occurred mostly upon purely sandy substrates (Fig. 5a, b).
Forest structure and AGB In both ecosystems, the distribution of trees by DBHclass showed a reverse J-shaped curve, with most individuals (50 % in the igapó and 41 % in the campinarana) belonging to the smallest diameter class of 10–15 cm. Basal area per plot averaged 1.89 ± 0.65 m2 in the igapó and 1.42 ± 0.65 m2 in the campinarana, and as such was significantly different between the investigated forest types (t-test: mean of x: 1.43, mean of y: 1.89, P > 0.001). Mean tree heights amounted to 11.4 ± 2.0 m in the igapó and to 13.1 ± 2.6 m in the campinarana, again
with significant difference (t-test: mean of x: 11.34, mean of y: 13.05, P > 0.001). Mean AGB in the igapó amounted to 141.4 ± 62.4 Mg·ha−1 for model A and to 152.4 ± 67 Mg·ha−1 for model B. AGB was most significantly related to tree height (R2 = 0.56, P < 0.001), followed by tree diameter (R2 = 0.32, P < 0.001). While tree diameter was neither significantly related to inundation nor soil characteristics, tree height was significantly related to both variables (inundation: R2 = 0.33, P < 0.001; PC1: R2 = 0.37, P < 0.001), indicating higher forests upon less flooded substrates with higher contents of sand and lower fertility. Mean AGB in the campinarana amounted to 152.1 ± 112.4 Mg·ha −1 for model A and to 164.0 ± 121.3 Mg·ha−1 for model B. AGB was similarly related to tree diameter (R2 = 0.49, P < 0.001) and tree height (R2 = 0.50, P < 0.001). Tree diameter was significantly related to groundwater depth (R2 = 0.32, P < 0.001), indicating trees with larger girth in areas with deeper water tables. Tree heights were found to relate significantly to soil characteristics and groundwater depth
N. Targhetta et al. Table 3 Relative abundance (rA), relative dominance (rD), relative frequency (rF), family importance value (IV) and total family importance value (FIV) of the 10 most important families in the inventoried ecosystems.
Family
rA
rD
rF
IV
∑ FIV (1–10) Igapó
1
Fabaceae
17.15
26.18
12.47
55.80
2
Phyllanthaceae
17.75
7.65
5.97
31.38
3
Lauraceae
10.54
13.41
7.27
31.22
4
Euphorbiaceae
10.45
7.28
10.39
24.87
5
Chrysobalanaceae
8.92
6.58
9.09
21.46
6
Sapotaceae
7.54
4.87
7.27
19.55
7
Lecythidaceae
3.28
4.05
7.27
12.10
8
Arecaceae
3.56
6.03
2.86
11.97
9
Simaroubaceae
5.69
3.56
2.34
11.63
10
Vochysiaceae
11–35 ∑
2.03
7.10
2.34
11.51
13.08
13.29
32.73
68.51
100
100
100
231.49 (77.2 %)
300 Campinarana
1
Fabaceae
17.58
39.97
8.81
66.36
2 3
Sapotaceae
11.79
9.46
7.66
28.91
Chrysobalanaceae
10.33
4.72
8.62
4
23.67
Humiriaceae
7.95
6.80
5.75
20.49
5
Primulaceae
7.19
3.35
5.75
16.29
6
Arecaceae
4.16
5.00
4.21
13.38
7
Malvaceae
4.87
3.64
4.60
13.10
8
Burseraceae
5.46
3.05
4.21
12.73
9
Rubiaceae
3.79
1.69
4.98
10.46
10
Lecythidaceae
11–38 ∑
(PC1: R2 = 0.52, P < 0.001; groundwater depth: R2 = 0.38, P < 0.001), indicating higher forests upon more fertile substrates and upon substrates with deeper water tables. There was no significant difference between mean AGB in the igapó and the campinarana (Student’s t-test, P > 0.05 for both model A and model B). Both models also showed similar AGB values for the same ecosystem. In the igapó, flooding duration as single variable explained 33 % of the AGB variation among plots (Table 7). Although soil characteristics as single variable did not show a significant relationship to plot AGB variation, its inclusion to flood duration increased the explanation of plot AGB variation to 46 %. In the campinarana, soil characteristics along with groundwater depth explained 54 % of the AGB variation, with hydrology being a more powerful explanatory variable (46 %) than PC1 (36 %).
2.54
3.88
2.68
24.34
18.44
42.73
100
100
100
214.5 (71.5 %)
9.11 85.5 300
Discussion Tree species composition, richness and diversity The results of the present study indicate that, despite a geographic distance of only a few kilometers, igapó and campinarana forests are distinct forest types in the Uatumã Sustainable Development Reserve. Species richness and diversity of the forest types under study were significantly different, with the campinarana being almost two times richer in tree species than the igapó. Among the 187 recorded tree species, we found only four shared species between both ecosystems, resulting in a very high species dissimilarity of > 97 %. Moreover, comparatively high dissimilarity between both forest types also persisted when higher taxonomic levels were compared (Bray-Curtis dissimilarity at the genus level: 82 %, at the family level: 50 %).
Effects of the hydroedaphic gradient on tree species composition Table 4 Relative abundance (rA), relative dominance (rD), relative frequency (rF), species importance value (IV) and total importance values (TIV) of the 10 most important species in both inventoried ecosystems.
Species
rA
rD
Rf
IV
∑ TIV (1–10) Igapó
1
Amanoa cf. guianensis
17.75
7.65
4.11
29.52
2
Nectandra amazonum
9.20
12.69
2.33
24.22
3
Mabea caudata
7.72
5.32
5.55
18.59
4
Pouteria elegans
6.56
4.07
3.94
14.57
5
Licania heteromorpha
4.58
3.25
3.94
11.77
6
Astrocaryum jauari
3.56
6.03
1.97
11.56
7
Eschweikera sp.
2.77
3.74
4.47
10.98
8
Simaba guianensis
5.69
3.56
1.61
10.86
9
Erisma calcaratum
2.03
7.10
1.61
10.74
10
Acosmium nitens
2.54
4.06
3.40
10.00
37.60
42.53
67.08
147.19
11–69 ∑
100
100
100
152.81 (50.9 %)
300 Campinarana
1
Aldina heterophylla
4.95
40.44
2
Sacoglottis guianensis
7.95
3
5.84
4
Pradosia schomburgkiana Macrolobium bifolium
6.80
4.13
18.87
2.76
2.75
11.36
5.79
5
Cybianthus sp.
4.49
3.45
1.10
10.34
2.12
2.75
9.36
6
Manilkara cavalcantei
7
Licania macrophylla
3.14
2.51
3.16
8.81
2.92
1.18
4.54
8
8.64
Couepia paraensis
2.87
1.26
3.16
7.29
9
Mauritia carana
2.11
3.74
1.38
7.23
10
Couepia parillo
2.70
1.07
2.61
6.38
11–122 ∑
Fig. 2 Number of accumulated species per 100 individuals in campinarana and igapó.
6.60
55.60 100
28.89
46.21 100
69.46 100
128.73 (42.9 %)
171.27 300
The strikingly different richness and compositional pattern between the investigated forest types is most probably related to the geographic position and the peculiar site conditions of our inventory in relation to previous inventories performed in white-sand and igapó forests. Compared to northern Amazonia and the Guianas, where white-sand forests extend over thousands of square kilometres with most sediments originating from the Roraima massif and/or other formations of the Guiana Shield, our central-Amazonian white-sand forest is small in extension, isolated by surrounding upland forest and developed most probably in situ from eroded sediment from adjacent hills. The small size of our campinarana and the short distance to the surrounding species-rich terra firme forest may lead to some terra firme species facultatively colonizing white-sand ecotones, especially in less hydromorphic plots. As such,
N. Targhetta et al.
Fig. 3 Non-Metric Multidimensional Scaling (NMDS) of the tree flora in 88 25 × 25 m (625 m2) sub-plots of the Uatumã Sustainable Development Reserve. Triangles represent campinarana plots, and circles represent igapó plots. The greyscale represents the content of clay in each plot: the darker the higher clay content, varying from
0.95 to 3.85 % in campinarana plots and from 33.7 to 68.1 % in igapó plots. Symbol size represents groundwater table depth in the campinarana and the duration of flooding in the igapó, both transformed to the log scale due to differences in their magnitude.
local community richness on white sand may be enriched by increased propagule dispersal from nearby forests. Conversely, this is more unlikely to occur in
highly flooded igapó forests. Here, seasonal inundations create a strong habitat filter for flood intolerant tree species. At the same time, flood-adapted specialists are
Table 5 Regression analysis of NMDS with each of 12 textural and chemical soil variables in igapó and campinarana.
† One and 46 d.f. in igapó, one and 38 d.f. in campinarana.
Igapó F†
P
R2
Campinarana F†
P
R2
Sand
0.47
0.49
–0.0113
10.66
> 0.01
0.1986
Silt
8.18
< 0.01
0.1325
0.01
0.96
−0.0262
Clay
0.54
0.47
–0.0099
95.33
> 0.001
0.7075
C
1.41
0.24
0.0085
0.01
0.89
−0.0258
N
0.68
0.41
–0.0068
29.82
> 0.001
0.425
P
97.98
< 0.001
0.6736
Al
20.98
< 0.001
0.2983
SB
2.66
0.11
2.603
0.15
0.0394
20.13
> 0.001
0.3291
0.0343
19.64
> 0.001
0.3234 0.4553
Fe
6.86
< 0.01
0.1101
33.59
> 0.001
Zn
15.42
< 0.001
0.2348
6.00
> 0.01
0.1137
Mn
19.83
< 0.001
0.286
12.66
> 0.001
0.2301
Cu
35.5
< 0.001
0.4233
0.87
0.36
0.0032
Effects of the hydroedaphic gradient on tree species composition characteristics (S – indicating PC1) on the variation of floristic composition (NMDS) in the investigated forest types.
Table 6 Results of simple and multiple regression analyses considering the effect of inundation (W) in igapó and groundwater depth (W) in campinarana, as well as soil Regression model
Standard partial slope (b)
Igapó
Inundation
PC1
S+W
0.783***
−0.745***
W
0.460 −0.405
S Campinarana
Groundwater depth
PC1
S+W
−0.400***
0.593***
W
−0.696
S *** †
0.793
F†
P
R2
44.21
< 0.001
0.65
12.38
< 0.001
0.19
9.05
< 0.01
0.15
55.24
< 0.001
0.73
35.8
< 0.001
0.47
64.47
< 0.001
0.62
P < 0.001.
Two and 45 d.f. in model 1, one and 46 d.f. in models 2 and 3, two and 37 d.f. in model 4, one and 38 d.f. in models 5 and 6.
highly competitive and often achieve high dominances that may exclude potential colonizers from nearby habitat types (i.e. Kubitzki 1989; Wittmann et al. 2013). In the igapó, our results indicate that tree species richness and composition were strongly influenced by hydroedaphic gradients. It is well known that species richness and composition of Amazonian large-river floodplain forests depend on the height and duration of annual inundations, a principal driving force shaping flood-adapted communities (Junk et al. 1989; Ferreira 1997). As a consequence, several authors report a clear turnover of species along the flooding gradient, with only few tree species establishing along its entire amplitude (i.e. Ferreira 1997; Wittmann and Junk 2003). Also, in the investigated igapó, multiple regression analysis revealed a strong compositional change along the flooding gradient, with species-poor forests in areas with longer flood duration and species-rich forests in areas of shorter flood duration. Similarly, species dominance decreased with decreasing flood duration. Our multiple regressions also indicate that soil texture is most probably related to the ‘flood-pulse’ (Junk et al. 1989). Highly flooded sites showed higher contents of clay in alluvial substrates. Although finegrained substrates are generally richer in nutrients than coarser substrates (Sollins 1998), they are also scarcely aerated during low water-levels, and as such aggravate oxygen depletion at the root level. Consequently, finegrained substrates reinforce flood-induced disturbance
even during the terrestrial phases, when tree species establish. Flood-level and soil texture are interlinked factors that sort community assemblages into two main habitats: species-poor communities on highly flooded and badly aerated, clayish substrates, and species-rich communities on weakly flooded and better aerated, intermediate grain-sized substrates. In the campinarana, tree species richness and composition were related to groundwater depth: Higher groundwater levels reduced species richness and resulted in higher dominance of fewer tree species. Similarly, sites with higher groundwater levels disposed of lower contents of clay and nutrients, and thus may additionally affect species richness negatively. These findings are contrary to those found by Damasco et al. (2013), which reported increasing species richness in areas of higher water tables in a northern Amazonian campina. There are, however, substantial differences in both studies that could explain these contradictory findings. First, our campinarana was predominately sandy and lacked superficial inundation potentially responsible for the higher clay content of some plots in that study. Secondly, the minimum DBH in Damasco et al. (2013) was 1 cm, and as such included small shrubs and tree regeneration, which could have different environmental requirements, especially considering water uptake during early stages of life. Here we show that when considering solely the tree community > 10 cm DBH, species richness in white-sand forests is negatively affected by comparatively high groundwater levels even in the absence of superficial inundation.
N. Targhetta et al.
Fig. 4 Tree species (≥ 10 individuals) distribution of seasonally flooded igapó forests along the (a) flooding gradient and (b) soil texture gradient, represented by the content of clay.
Forest structure and AGB Independent of the forest type, structure and AGB in Amazonian forests are interpreted as depending mainly on two limiting environmental factors: (1) soil drainage, waterlogging and/or inundation that cause lower AGB on poorly drained or highly flooded substrates (Coomes 1997; Wittmann et al. 2004; Baraloto et al. 2011); and (2) soil nutrient availability, with several studies reporting positive effects of fine-grained soils and
fertility including total N, soil phosphorous and exchangeable bases (Laurance et al. 1999; DeWalt and Chave 2004; Paoli et al. 2008; Quesada et al. 2010). In summary, the results of the present study indicate that differences in forest structure and AGB between our igapó and campinarana forests were not significantly different, which leads us to the interpretation that both ecosystems are similarly limited by disturbance caused by inundations and/or bad soil drainage. In addition, within-
Fig. 5 Tree species distribution (≥ 10 individuals) of campinarana forests along the (a) groundwater table depth and (b) soil texture gradient, represented by the content of clay.
Effects of the hydroedaphic gradient on tree species composition depth (W) in campinarana, as well as soil characteristics (S – indicating PC1) on AGB variation (structural conversion factor –
Table 7 Results of simple and multiple regression analyses considering the effect of inundation (W) in igapó and groundwater SCF) in the investigated forest types.
F†
Regression model
Standard partial slope (b)
Igapó
Inundation
PC1
S+W
−0.766***
0.409**
W
−0.588
S
0.077
Campinarana
Groundwater depth
PC1
S+W
0.506***
−0.360**
W
0.687 −0.613
S ** †
P
R2
20.97
< 0.001
0.46
24.36
< 0.001
0.33
0.28
> 0.05
0.01
24.41
< 0.001
0.54
33.89
< 0.001
0.46
22.94
< 0.001
0.36
P < 0.01, *** P < 0.001.
Two and 45 d.f. in model 1, one and 46 d.f. in models 2 and 3, two and 37 d.f. in model 4, one and 38 d.f. in models 5 and 6.
ecosystem variability in AGB was very high (twoand threefold between the lowest and highest plot AGB in the igapó and in the campinarana, respectively) and showed to be dependent on the analysed environmental parameters, although single soil variables and inundation/soil drainage may influence forest structure and AGB of both ecosystems in different ways. The igapó was richer in most soil nutrients than the campinarana; however, total amounts of single nutrients such as K, Ca, Mg, Al, Fe, Zn and Mn were still low when compared to those of other Amazonian ecosystems such as non-flooded terra firme and seasonally flooded várzea (i.e. Laurance et al. 1999; Haugaasen and Peres 2006; Quesada et al. 2010). In the igapó, highly flooded sites were occupied by forests of lower stature and smaller trees. That AGB decreases with height and duration of the annual inundation was formerly described for Amazonian igapó forests along the river Negro (Schöngart et al. 2010), Amazonian várzea forests (Nebel et al. 2001; Schöngart et al. 2010) and riparian forests in the Brazilian Pantanal (Wittmann et al. 2008; Schöngart et al. 2011). Highly flooded sites are usually colonized by trees that dispose of traits linked to high disturbance frequencies, such as shrubby habits, fast growth rates, short life cycles and extensive root systems (i.e. Wittmann et al. 2004; Wittmann and Parolin 2005), suggesting a trade-off between rapid growth and regeneration rates and long-term storage of AGB (i.e. Mitsch and Gosselink 2000; Hultine
et al. 2013). Moreover, with the onset of flooding, trees reduce photosynthetic activity, leading to shoot and wood growth reductions and cambial dormancy during the aquatic phases (Worbes 1997). As such, one additional explanation for low AGB in highly flooded sites might be related to comparatively short growth periods available during the terrestrial phases. In the campinarana, higher groundwater tables negatively affected tree heights and diameters, leading to lower AGB. Tree species in white-sand forests are considered habitat specialists adapted to nutrient-poor soils and edaphically induced droughts, which is reflected in the presence of key functional traits, such as low tree heights and basal areas, scleromorphic and extremeangled leaves, deep roots, and effective mechanisms against herbivory (i.e. Prance 1975; Medina et al. 1978; Kubitzki 1989; Coomes 1997; Fine et al. 2004). In such a scenario, rooting depth is possibly a crucial adaptation of tree species on white-sand substrates, as deeper roots might counterbalance drought-induced growth limitations especially during the dry seasons. However, deep roots may be of disadvantage during the rainy season, when groundwater levels rise, leading to temporarily hypoxic site conditions at the root level. While effective morpho-anatomical, physiological and biochemical adaptations to seasonal inundations are known from many seasonally flooded igapó tree species (i.e. Worbes 1997; Parolin et al. 2004), most white-sand tree species show low tolerance to superficial inundation, even when those only reach few centimetres in height. When groundwater levels surpass the surface,
N. Targhetta et al.
white-sand forests usually are replaced by shrub and grass savannas (Prance 1975; Veloso et al. 1991; Vicentini 2004). In our plots, we did not observe superficial inundation in the inventoried white-sand forest. However, the highest groundwater tables reached up to a few cm below the surface during the rainy season, and we cannot exclude the possibility that these areas may suffer superficial inundation in wetter years. We thus argue that high groundwater levels especially during the rainy seasons cause hypoxic conditions at the root level in the poorly flood-adapted community of white-sand habitat specialists. Multiple regression analysis also revealed that forest structure and AGB in the campinarana were related to soil texture along with fertility, although contents of finer grains were low in the predominately sandy substrate. However, even low amounts of clay seem to influence AGB directly through increased water retention, or indirectly through increased nutrient fixation. Zanchi et al. (2011) and Damasco et al. (2013) reported higher contents of clay and silt in campinarana soil depressions that are subject to waterlogging during the rainy seasons. These depressions may also lead to an accumulation in litter and, as such, to local higher concentrations in C, N, P and exchangeable bases, which are positively related to AGB. Conversely, Coomes (1997) found that waterlogging in white-sand areas slows the breakdown of organic matter, resulting in N limitation. Therefore, we argue that N might more available in our campinarana sites where groundwater levels are deeper, contributing to sites with taller trees. AGB in comparison to other Amazonian forest types The few AGB estimates available for Amazonian whitesand and igapó forests indicate that our estimates are comparatively low, and comprise < 60–70 % of maximal AGB values reported for each of the forest types (Klinge and Herrera 1983; Schöngart et al. 2010; Baraloto et al. 2011). High variability of biomass estimates in this and previous studies call attention to environmental and floristic variability in white-sand and igapó forests, which are still poorly understood. However, our data clearly show that AGB is lower than 50 % compared to AGB estimations in Amazonian terra firme and other types of floodplain forest (i.e. Nebel et al. 2001; Malhi et al. 2004; Baraloto et al. 2011). Given that white-sand and igapó forests cover vast areas
of the Amazon basin, we argue that many studies that do not address habitat variability within the Amazon may tend to overestimate total AGB in the basin and its contribution to global carbon cycles. More studies on AGB in relation to environmental variables are needed to properly describe, predict and map variation in AGB on a basin-wide scale.
Conclusions We show that the i nvestigated i gapó and campinarana forests are oligotrophic and nutrientpoor ecosystems where forests are similarly comprised of trees of low heights and small diameters, resulting in low AGB in comparison to other Amazonian forest types. Species richness and AGB in both forest types were related to flooding (igapó) and poor soil drainage (campinarana), and increased with decreasing impact of flooding and groundwater tables. Furthermore, both forest types were characterized by a strong species turnover along the hydrological gradient. We conclude that inundations in igapó and poor soil drainage in campinarana forests exert strong environmental filters for tree species distribution, richness, forest structure and AGB. Soil texture and chemistry showed to be dependent on the hydrological gradient in both ecosystems, but seemed to have a stronger control on species turnover and AGB in campinaranas. Although contents of fine grains (clay and silt) were generally low in campinarana soil, they concentrated in sites with deeper groundwater tables. We conclude that small fractions of fine grains in campinarana soils importantly contribute to species richness and AGB, which we interpret as the result of locally increased nutrient availability in a nutrient-poor environment and/or locally higher water retention capacity, which might mitigate drought stress during the dry seasons. Acknowledgements This work was performed within the frame of the German-Brazilian ATTO project and supported by the federal governments (grant No. MCTI-FINEP 1759/10; grant No. BMBF 01LB1001A). We acknowledge the fundamental support by the Max Planck Society, INPA and UEA. We thank the Amazonas State SDS/CEUC-RDS Uatumã, MAUA Group (Monitoring of Amazonian Wetlands, INPA/Max Planck, Manaus, Brazil) and CAPES.
Effects of the hydroedaphic gradient on tree species composition
Appendix 1
biomass (AGB). References refer to specific wood density values: *Average value for the species. **Average value for the genus.
Table 8 List of species found in the inventoried igapó and campinarana forest and their respective aboveground wood volume (AWV), specific wood density (ρ) and aboveground wood Species
Abundance AWV Igapó Campinarana
Abarema adenophora (Ducke) Barneby & Grimes Acosmium nitens (Vogel) Yakoolev
3 55
Agonandra brasiliensis Benth. & Hook Alchornea discolor Poepp. & Endl. Amanoa cf. guianensis Aubl. Amphirrhox surinamensis (Miquel) Eichler
1.24 0.567 12 **
0.73
1
0.12 0.740 4
0.09
122
205.69 0.730 4
9.62 0.404 1, 8, 12 ** 46.15 0.843 12 *
1
0.07 6
40.43 0.04 19.63 0.03
1
0.05 0.473 6, 8, 12 **
Aspidosperma excelsum Benth.
3
0.66 0.792 12
77
4.04 156.17
25.71 0.734 4, 6, 12 **
Anonna sp. Astrocaryum jauari Mart.
AGB
20.03
384
Andira sp.
References
26.75 0.720 7
44
Aldina heterophylla Spruce ex Benth.
(ρ)
41.72
0.55 14.36
Brosimum rubescens Taub.
4
8.81 0.870 4
7.97
Brosimum utile (HBK.) Pittier
4
8.40 0.430 4
3.76
0.23 0.770 8
0.18
Buchenavia cf. oxycarpa Eichler
4
Buchenavia macrophylla Eichl.
5
2.59 0.714 4, 8 **
1.92
Buchenavia sp.
2
4.81 0.714 4, 8 **
3.57
3.90 0.785 12 **
3.18
3.34 0.613 1, 4, 6, 8, 10, 12 ** 0.24 0.613 1, 4, 6, 8, 10, 12 ** 0.17 0.613 1, 4, 6, 8, 10, 12 ** 0.43 0.530 4
2.13
Burdachia sphaerocarpa Adr. Juss.
37
Byrsonima cf. garcibarrigae Cuatrec.
8
Byrsonima sp.1
5
Byrsonima sp.2
3
Calophyllum brasiliense Camb. Calyptranthes sp. Campsiandra comosa (Benth.) Cowan
2 2
0.14 0.783 12 **
18
14.72 0.810 7
0.16 0.11 0.24 0.11 12.39
Caraipa sp.
1
0.26 0.648 12 **
0.17
Cariniana decandra Ducke
7
1.61 0.559 6
0.93
Cariniana micrantha Ducke
4
4.20 0.640 4
2.79
Catostemma sclerophyllum Ducke Cecropia sp.
9 1
Chamaecrista adiantifolia (Spruce ex. Benth.) H.S. Irwin & Barneby Chaunochiton angustifolium Sleumer Chorisia sp.
3 7 6
Chrysophyllum sanguinolentum (Pierre) Baehni
24
Clusia cf. nemorosa G. Mey.
14
Coccoloba sp.
22
Conceveiba guianensis Aubl. Cordia sp.
18
0.97 0.690 12
0.7
0.04 0.330 8, 12 **
0.02
3.48 0.832 12 *
3.01
0.99 0.584 12 **
0.6
12.67 0.275 12 **
3.63
12.47 0.624 6 2.56 0.821 6, 12 **
8.1 2.19
1.50 0.583 8, 12 **
0.91
4
0.37 0.543 12 *
0.21
4
8.52 0.505 4, 8, 12 **
4.48
N. Targhetta et al. Table 8 (continued) Species
Abundance AWV Igapó Campinarana
Couepia paraensis (Mart. & Zucc) Benth.
35
Couepia parillo DC.
53 50
Couma utilis (Mart.) Mull. Arg. Crataeva benthamii Eichler Crudia amazonica Spruce ex Benth. Cupania scrobiculata L.C. Rich.
5 1 18 3
Cybianthus fulvopulverulenthus (Mez) G. Agostini
50
Cybianthus sp. Cynometra spruceana Bth.
83 16
(ρ)
References
14.26 0.770 8
AGB
11.42
4.27 0.782 6, 8, 12 **
3.47
0.60 0.660 12
0.41
0.03 0.780 10
0.02
4.07 0.870 7
3.69
0.80 0.506 6
0.42
6.23 0.550 1
3.57
9.03 14.53 0.840 12 **
6.54 12.7
Dacryoides cf. microcarpa Cuatrec
27
4.52
3.15
Diplotropis cf. triloba Gleason
16
5.82 0.750 12 **
4.54
0.16 0.752 6, 8, 12 **
0.12 0.05
Duroia cf. genipoides Hook F. ex K. Schum
1
Duroia sp.
1
0.06 0.752 6, 8, 12 **
Eclinusa guianense Eyma
1
0.45 0.549 6
0.26
0.39 0.800 12
0.32
Elvasia calophylla D.C.
3
Emmotum cf. orbiculatum (Benth.) Miers
26
2.12 0.794 12 **
1.75
Endlicheria arenosa Chanderbali
13
1.66 0.504 12 **
0.87
4.12 0.504 12 **
2.17
Endlicheria macrophylla (Meins.) Mez
29
Eperua bijuga Mart. ex Benth. Erisma calcaratum (Link.) Warm.
2 44
54.89 0.680 12
Eschweilera atropetiolata S.A. Mori
7
Eschweilera bracteosa (Poepp. ex O. Berg.) Miers
0.76 0.729 12 *
29
9.49 0.753 6
0.58 39.17 7.43
15.85 0.828 12 **
13.65
Eschweilera sp.1
60
27.09 0.828 12 **
23.04
Eschweilera sp.2
3
0.37 0.828 12 **
0.32
Eschweilera tenuifolia (Berg.) Miers
8
1.22 0.770 12
0.98
Eugenia patrisii Vahl
1
0.11 0.831 12 *
0.09
Eugenia sp.
3
0.23 0.727 6, 8, 12 **
0.18
Ferdinandusa chlorantha (Wedd.) Standl.
32
4.30 0.725 12 **
3.24
1
0.06 0.725 12 **
0.05
3
Ferdinandusa sp. Guarea convergens T.D. Penn.
0.49 0.613 4, 6, 12 **
0.31
Guatteria sp.1
15
7.81 0.532 1, 4, 8, 10, 12 **
4.32
Guatteria sp.2
2
1.32 0.532 1, 4, 8, 10, 12 **
0.73
1
0.09 0.532 1, 4, 8, 10, 12 **
0.05
Guatteria sp.3 Helicostylis scabra (J.F. Macbr.) C.C. Berg
4
Heterostemma sp.
1
Hevea guianensis Aubl. Hevea spruceana (Benth.) Mull. Arg. Homalium racemosum Benth.
15 15 6
Hortia longifolia Spruce ex Engl. Humiria sp.
1 4
Hydrochorea corymbosa (Rich.) Barneby & Grimes
80
Hydrochorea marginata (Benth.) Barneby
15
Inga alba (SW.) Willd.
1.63 0.760 10
1.29
0.14
0.09
2.95 0.600 11
1.84
4.12 0.340 8
1.46
1.49 0.820 12
1.27
0.04 0.900 12
0.04
0.70 0.665 1, 4 ** 17.02 0.550 8 1
0.49 9.74
3.83 0.533 8, 12 **
2.12
0.11 0.620 4
0.07
Effects of the hydroedaphic gradient on tree species composition Table 8 (continued) Species
Inga sp.
Abundance AWV Igapó Campinarana 14
Iryanthera sagotiana Warb. Laetia procera (Poeppig.) Eichler
21 43
Licania bracteata Prance Licania heteromorpha Benth.
References
5.64 0.603 4, 6, 8, 10 ** 42
Lacmellea arborescens (Mull. Arg.) Markgr.
(ρ)
27 99
12.01 0.570 4 3.42 0.505 12 **
AGB
3.54 7.12 1.8
3.71 0.680 4
2.62
5.50 0.811 6, 12 **
4.64
22.15 0.800 8
18.41
1
0.06 0.900 3
0.06
Licania macrophylla Benth.
54
7.37 0.760 4
5.82
Licania oblongifolia Standl.
5
1.99 0.880 4
1.82
11.45 0.770 4
9.17
Licania hypoleuca Benth.
Licania octandra (Hoffmanns ex Roenn & Schult) Kuntze Licania sp.1
58 1
Licania sp.2 Mabea caudata Pax & Hoffm.
1 167
Macoubea sprucei (Mull. Arg.) Markgr. Macrolobium acaciifolium Benth. Macrolobium bifolium (Aubl.) Pers. Macrolobium multijugum Benth.
0.2
0.14 0.811 6, 12 **
0.11
34.76 0.670 6 18
41 5
0.21 0.811 6, 12 **
2.46 27.91 0.430 9
107
25
24.23 1.8 12.48
23.11 0.670 12 *
16.10
17.38 0.603 12 **
10.9
Macrolobium sp.
2
0.18 0.603 12 **
Malouetia sp.
1
0.14 0.543 8, 12 **
0.08
0.17 0.590 8
0.1
17.13 0.834 6
14.86
41.10 0.540 11
23.08
Malouetia tamaquarina (Aubl.) A. D.C.
3
Manilkara cavalcantei Pires & Rodrigues ex T.D. Pennington Maquira coriacea (H. Karst.) C. C. Berg.
58 44
Matayba opaca Radlk.
3
Mauritia carana Wallace
39
0.11
0.26 0.820 12
0.22
9.29
2.3
Mauritia flexuosa L. f.
3
0.30
0.12
Mauritiella aculeata (Kunth) Burret
5
0.79
0.85
Mezilaurus itauba (Meisn.) Taub. ex Mez
2
0.45 0.659 6
0.31
Micrandra sp. Micropholis cf. egensis (A. de Candolle) Pierre
5 6
Micropholis cf. guyanensis (DC.) Pierre
12
2.91 0.667 6, 12 **
2.02
2.18 0.600 12
1.37
14.42 0.650 4
9.75
Minquartia guianensis Aubl.
8
3.12 0.760 3
2.47
Mollia sp.
1
0.51 0.490 12 **
0.26
Mouriri nigra (D.C.) Morley
4
Myrcia multiflora (Lam.) D. C. Nectandra amazonum Nees Neea madeirana Standl.
6 199
1.25 0.41
107.86 0.440 10 1
Neea sp.
16
Ocotea cernua (Nees) Mez.
15
Ocotea sp.
1.34 0.895 12 * 0.48 0.811 12 **
2
49.36
0.04 0.520 8
0.02
1.68 0.626 6, 8, 12 **
1.09
4.46 0.454 12 *
2.11
0.95 0.553 4, 6, 10, 12 **
0.54
Oenocarpus bacaba Mart.
17
1.93 0.650 12
1.38
Oenocarpus bataua Mart.
13
2.12 0.682 12 **
0.91
Ormosia cf. costulata (Miq.) Kleinh.
6
0.77 0.639 12 *
0.51
Ormosia nobilis Tul.
3
0.42 0.580 12
0.26
N. Targhetta et al. Table 8 (continued) Species
Abundance AWV Igapó Campinarana
Ormosia sp. Oxandra riedeliana R. E. Fr.
16 5
Pachira sp.
1
Pagamea coriacea Spruce ex Benth. Panopsis rubescens (Pohl) Pittier
36 4
Parkia discolor Spruce ex Benth.
(ρ)
References
AGB
3.95 0.621 4, 6, 12 **
2.55
0.30 0.470 8
0.15
0.12 0.439 12 **
0.05
3.37 0.560 1
1.96
1.10 0.520 12
0.59
16
2.22 0.640 7
1.47
Parkia multijuga Benth.
1
0.68 0.380 4
0.27
Parkia pendula (Willd.) Benth. ex Walp.
1
4.03 0.550 4
2.3
Parkia sp.
1
0.20 0.454 4, 6, 12 **
0.09
Paypayrola grandiflora Tulasne Peltogyne catingae Ducke
3 10
0.34 0.630 6
0.23
4.34 0.813 12 *
3.67
Pera bicolor (Klotzsch) Mull. Arg.
7
2.41 0.627 12 *
1.57
Pourouma guianensis Aubl.
1
0.06 0.330 3
0.02
Pouteria cf. venosa (Martius) Baehni
1
0.13 0.920 12
Pouteria elegans (A. DC.) Baehni
142
4
26.49 0.650 8
0.13 17.82
Pouteria glomerata (Miq.) Radlk.
5
0.40 0.730 8
0.3
Pouteria pachyphylla (A. C. Sm.) Baehni
3
0.63 0.781 6, 8, 10, 12 **
0.51
Pouteria sp.1
6
1.22 0.781 6, 8, 10, 12 **
0.99
Pouteria sp.2
1
0.47 0.781 6, 8, 10, 12 **
0.38
Pouteria sp.3
1
0.25 0.781 6, 8, 10, 12 **
0.2
Pouteria sp.4
8
4.15 0.781 6, 8, 10, 12 **
3.37
Pouteria sp.5
1
0.55 0.781 6, 8, 10, 12 **
0.44
Pradosia schomburgkiana (A. DC.) Cronquist
11.25 0.730 4
8.54
Protium apiculatum Swart
47
10.29 0.580 4, 6, 12 **
6.21
Protium llanorum Cuatrec.
26
5.85 0.580 4, 6, 12 **
3.53
0.49 0.480 2
0.24
1.08 0.663 12
0.75
Pterocarpus rohrii Vahl.
108
4
Ptychopetalum olacoides Benth.
6
Qualea paraensis Ducke
3
3.87 0.670 4
2.69
Rhabdodendron macrophyllum (Spruce ex Benth.) Huber
3
0.52 0.800 12
0.43
4.66
3.39
Rhodognaphalopsis faroensis (Ducke) A. Robyns
41
Rinorea guianensis Aubl.
2
Ruizterania retusa (Spruce ex Warm.) Marc.-Berti
22
Sacoglottis guianensis Benth. Scleronema micranthum (Ducke) Ducke Simaba guianensis (Aubl.) Engl.
Sloanea cf. laurifolia (Benth.) Benth. Sterigmapetalum colombianum Monachino Swartzia acuminata Willd. ex Vogel
5.27
39.71 0.770 4
31.8
26
19.98 0.610 4
12.67
36
Simarouba amara Aubl.
0.16
7.19 0.705 12 *
147 123
Simaba sp.
0.19 0.780 6
2 5 24 6
18.04 0.429 6, 8, 12 **
8.05
3.97 0.429 6, 8, 12 **
1.77
0.54 0.380 3
0.21
1.93 0.816 12 *
1.74
6.25
4.47
7.35 0.834 12 **
6.38
Swartzia cf. recurva Poeppig
4
1.18 1.000 5
1.23
Swartzia corrugata Benth.
1
0.29 0.913 6
0.28
Swartzia ingifolia Ducke
3
0.87 0.815 6
0.74
Effects of the hydroedaphic gradient on tree species composition Table 8 (continued) Species
Abundance AWV Igapó Campinarana
Swartzia laevicarpa Amshoff
45
Symphonia globulifera L. f. Tabebuia barbata (E. Mey.) Sandw. Tachigali paniculata Aublet
1 32 6
(ρ)
References
AGB
19.57 0.620 7
12.62
0.42 0.580 4
0.25
6.85 0.870 8
6.2
0.95 0.554 12 *
0.55 2.65
Tapirira guianensis Aubl.
6
5.09 0.500 4
Tapura guianensis Aubl.
19
6.05 0.580 12
3.65
Theobroma sylvestris Aubl. ex Mart.
13
1.13 0.668 6
0.79
Tovomita cf. acutiflora Barros & G. Mariz
8
1.16 0.724 6, 8, 10, 12 **
0.87
Trattinnickia rhoifolia Willd.
1
0.08 0.370 3
0.03
Trichilia cf. rubra C. DC.
1
Vatairea guianensis Aubl.
13
Virola caducifolia W.A. Rodrigues
1
Virola calophylla (Spruce) Warb. Virola elongata (Benth.) Warb.
0.08 0.585 12
1 1
0.04
20.92 0.600 8
13.06
0.09 0.461 6
0.04
1.25 0.700 10
0.91
0.06 0.523 12 *
0.03
Virola surinamensis (Rol.) Warb.
4
4.01 0.420 3
1.75
Virola venosa (Benth.) Warb.
1
0.23 0.622 6
0.15
3.25 0.570 10
1.93
Vitex cymosa Bertero ex Spreng.
11
Vitex duckei Huber
8
0.61 0.553 10, 12 **
0.35
Vochysia obscura Warm.
4
1.82 0.523 4, 6, 12 **
0.99
3.09 0.705 12 *
2.27
Xylopia parviflora Spruce Zygia cf. cataractae (Kunth.) L. Rico Zygia sp.
10 6 5
1.71 0.725 6, 10, 12 **
1.29
1.03 0.725 6, 10, 12 **
0.78
Barbosa RI, Cid Ferreira CA (2004) Densidade básica da madeira de um ecossistema de “campina” em Roraima, Amazônia Brasileira. Acta Amazon 43:587–591.
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2
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