Liana allometric biomass equations for Amazonian primary and secondary forest

Forest Ecology and Management 195 (2004) 69–83

Liana allometric biomass equations for Amazonian primary and secondary forest C. Gehringa,*, S. Parkb, M. Denicha a

Center for Development Research (ZEF), University of Bonn, Walter-Flex-Str. 3, 53113 Bonn, Germany b Department of Geography, College of Soil Science, Seoul National University, Silim-Dong San-56-1 Kwanak-Gu, Seoul 151-746, Republic of Korea Received 18 December 2002; received in revised form 6 January 2004; accepted 20 February 2004

Abstract This study develops allometric equations for the estimation of aboveground liana biomass in field studies. We measured diameter, length, and total and leaf biomass of 561 shoots of 26 common liana species in secondary and primary forests of central Amazonia. Liana shoots ranged in size from 0.1 to 13.8 cm diameter and 20 cm–48 m length. We developed mixed-species and species-specific regressions. Goodness of fit of the allometric equations that emerged was similar whether diameter- or lengthbased (both R2 ¼ 0:73 for mixed-species regressions). The diameter is therefore recommended as single biomass estimator. Using both, diameter and length as estimators, the R2 increased to 0.91 for mixed-species. Neither the forest type nor the number of shoots per plant individual affected the allometric relationships. With few exceptions, species-specific equations were similar and goodness of fit increased only moderately over mixed-species equations. The mixed-species equations presented here were valid over a wide range of environments and species compositions, and are recommended for the non-destructive estimation of liana biomass in tropical forests and bushlands. # 2004 Elsevier B.V. All rights reserved. Keywords: Climbers; Biomass estimation; Diameter; Length; Leaf biomass; Species’ variability; Environmental variability

1. Introduction Lianas constitute a characteristic component of disturbed vegetation. They may turn dominant in treefall gaps (Putz, 1983; Schnitzer et al., 2000), in forests affected by hurricane (Rollet, 1969) or logging damage (Pinard and Putz, 1994), or following forest fragmentation (Laurance et al., 2001). According to Phillips et al. (2002), the elevated atmospheric con* Corresponding author. Tel.: þ0055-98-2310775; fax: þ0055-98-2311067. E-mail addresses: [email protected] (C. Gehring), catena@ snu.ac.kr (S. Park), [email protected] (M. Denich).

centrations of carbon dioxide may additionally favor primary forest lianas. In central Amazonian forests, we found that the vegetation share of lianas was highest in young regrowth (6.2% of biomass and 27% of all plants >50 cm height in 3-year-old secondary forest). These percentages gradually declined with fallow age and lianas were of only minor importance in the primary forest (1.8% of biomass and 14.2% of plants >50 cm height). Fearnside (1992) gives 4.3% as the average biomass share of lianas in Amazonian primary forest as a whole. Field research requires a reliable method for the determination of liana biomass. Allometric estimation

0378-1127/$ – see front matter # 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.foreco.2004.02.054

70

C. Gehring et al. / Forest Ecology and Management 195 (2004) 69–83

Presidente Figueiredo, 110 km north of Manaus, central Amazonia. Annual rainfall is 2180 mm (average of 7 years); a dry season of approximately 4 months causes seasonal leaf-shedding of some species. Soils are nutrient-poor kaolinitic Oxisols, typical for the region (Richter and Babbar, 1991). Aboveground biomass ranged from 60 to 220 t ha1 in secondary vegetation, primary forest biomass was estimated at 440 t ha1. Multiple-stemmed lianas dominated in young or degraded vegetation, whereas single-shoot lianas dominated in primary forest. The study sites are further described in Gehring (2003). Allometric data were compiled for 26 locally common liana species, some of these are also common in other areas of Amazonia. We combined some species which we considered to be very similar in their morphological appearance, resulting in 20 ‘morphospecies’. Sampling bias was avoided by an approximately even species representation over all forest types. Species ranged from fast-growing ruderals to species typical of primary forest undergrowth, and are listed in Appendix A.

is in many cases preferable over destructive methods, as disturbance is avoided and the investigation of larger study areas is possible. A number of allometric equations have been developed to estimate aboveground biomass or carbon stocks of trees in primary forests (e.g., Overman et al., 1994; Brown et al., 1995; Arau´ jo et al., 1999; Chave et al., 2001), secondary forests (e.g., Nelson et al., 1999; Ketterings et al., 2001) and multistrata-agroforestry systems (Schroth et al., 2002). In contrast, only two case studies on liana allometry are known to the authors (Putz, 1983; Gerwing and Farias, 2000). This study develops allometric equations for the estimation of aboveground liana biomass in the field. More specific research goals are: 1. to develop allometric equations estimating total and leaf biomass of lianas; 2. to compare the adequacy of shoot length, diameter, and combinations of both as liana biomass estimators; 3. to assess the general validity of the mixed-species liana biomass equations. For this purpose, we examine the effects of a wide range of environments (fallow age) and shoot quantities per plant individual, and the degree of species-specific variation.

2.2. Allometric data Measurements were taken in the rainy season when leaf biomass is maximal. Stem length, diameter (at 30 cm shoot extension), wood and leaf biomass were recorded for 561 shoots of 439 plant individuals. Liana shoots ranged in size from 0.1 to 13.8 cm diameter and 20 cm–48 m length (Table 1). Subsamples of each individual were oven-dried at 70 8C for 1 week (leaves) and 2 weeks (wood) for dry weight determination. Diameter was measured at 30 cm shoot extension rather than at breast height (dbh, i.e. at 1.30 m height). This allowed the inclusion of small- and mid-sized

2. Material and methods 2.1. Sites and species Liana allometry was investigated both in primary forest (6 sites) and in 2- to 25-year-old secondary forests regrowing after slash-and-burn agriculture (12 sites). Field work was conducted in the municipality of

Table 1 Data structure of the 561 liana shoots investigated

Diameter (mm) Length (m) Wood biomass (kg) Leaf biomass (kg) Total biomass (kg) % Leaf biomass

Mean

Median

Minimum

Maximum

14 5.20 2.48 0.17 2.58 30.1

11 2.60 0.12 0.05 0.20 29.7

1 0.18 0.003 0.001 0.004 0.4

138 64 236 5 238 84

C. Gehring et al. / Forest Ecology and Management 195 (2004) 69–83

liana shoots and was held to be better representative for the liana vegetation of the study region. Dbh measurements can be transformed into diameters at 30 cm shoot extension, using the following transformation established by Gehring et al. (submitted): diameter ð30 cmÞ ¼ 1:235 dbh þ 0:002 ðdbhÞ2 ; n ¼ 3144 liana shoots; R2 ¼ 0:945; standard errors :  0:004 dbh; 0:0001ðdbhÞ2 For non-round liana stems, cross-sectional area is best characterized with two or more diameter measurements around the stem, as in the studies of Putz (1983) and Gerwing and Farias (2000). The disadvantage of such a procedure is in the large number of measurements required on-field, resulting in elevated labor costs. The present study, therefore, opted for a singlemeasure diameter-standard as input variable. Our definition of ‘minimum diameters’ (diameters measured in the thinnest possible direction of the stem) is both easy to use and not susceptible to measurement bias. We preferred the ‘minimum diameter’ over the likewise conceivable ‘maximum diameter’ (applied, i.e., by Dewalt et al., 2000). This decision was based on pre-tests which had shown the minimum diameter to be better correlated with shoot length than the maximum diameter. 2.3. Statistics Length, diameter, and biomass of liana shoots were positively skewed, in accordance with the plant size frequency distributions prevailing in these forest ecosystems (Gehring, 2003). Natural logarithmic (ln) data transformation was the most suitable of a series of transformations tested for attaining normal distribution both for the single- and mixed-species data sets. Though Lilliefors and Shapiro–Wilk W-tests against normal distribution were significant, deviations of frequency distributions from normality were low for all variables. Homogeneity of variance was routinely checked with partial regression plots, and possible autocorrelation problems with Durbin–Watson statistics. Allometric equations were constructed for mixedspecies and for each species separately, using length, diameter (30 cm), or a combination of both as estimate parameters. We also tested regression equations using the following two variables of calculated shoot

71

volume (in cm3) commonly encountered in literature: basal area ðpr 2 Þ  length, and squared diameter  length. Our definition of ‘minimum diameters’ causes an underestimation of the basal areas for non-round shoots. The normalized mean standard error (NMSE) is an estimator of the overall deviations between predicted (P) and measured (M) values and was calculated as follows: 1 X ðPi  Mi Þ2 NMSE ¼ M  N P i

We take the NMSE as a fit index of the allometric equations, low values indicate a good performance. Since differences on peaks have a higher weight on NMSE than differences in other values do, the NMSE is specially sensitive against the occurrence of outliers. We compared the performance of single-species versus mixed-species equations for liana biomass estimation, taking the correlation between predicted and observed values as a measure of accuracy. Liana shoots were classified into categorical variables of ‘vegetation age’ (young secondary forest: 2to 5-year-old, old secondary forest: 7- to 25-year-old, and primary forest) and of ‘shoot quantity’ (singleshoot versus more than one shoot per plant individual). The relative importance of these variables was investigated with hierarchical generalized linear models (GLM). Generalized linear models differ from the more commonly used multiple regressions as they allow the inclusion of categorical variables and permit the use of interaction terms (McCullagh and Nelder, 1989). Next to the R2, we give the deviance residuals as a measure of how close the different models fit the data set. Significance values are given as * P < 0:05, ** P < 0:01 and *** P < 0:001. Statistical analyses were conducted with STATISTICA 5.1 (StatSoft Inc., 1998), and S-Plus 2000 (MathSoft Inc., 1998).

3. Results and discussion 3.1. Mixed-species allometric equations The ln-transformed values both of length and of diameter were linearly related to the ln-transformed

72

C. Gehring et al. / Forest Ecology and Management 195 (2004) 69–83

ln (Total biomass) = -7.114 + 2.276 * ln (Diameter) 6

2- to 5-yr.-old secondary regrowth 7- to 25-yr.-old secondary regrowth Primary forest

ln (Total biomass in kg)

4

2

0

-2

-4

-6 0

1

2

3

4

5

ln (Diameter in mm) Fig. 1. Ln-linear relationship between liana diameter and biomass (mixed-species, R2 ¼ 0:73).

biomass (Figs. 1 and 2). Mixed liana species allometric equations for the estimation of total and leaf biomass are given in Tables 2 and 3. Regression models using either shoot length or shoot diameter as predictor have a similar goodness of fit (both R2 ¼ 0:73 for the estimation of total biomass). The diameter-based liana allometric equa-

tion is preferable under field conditions, as diameters are more easily and accurately measurable. Goodness of fit increased when both diameter and length are used as estimators, causing an increase of R2 from 0.73 to 0.91. Similar increases were also observed for most species-specific equations (compare Appendix D with Appendices B and C). Whether

Table 2 Mixed-species equations for the estimation of total liana biomass S.E.

Adjusted R2

NMSEa

7.114 þ2.276

0.145 0.058

0.73

0.36

c a

3.366 þ1.612

0.061 0.041

0.73

0.36

(3) Ln(total biomass) ¼ c þ a ln(diameter) þ b ln(length)

c a b

6.105 þ1.413 þ0.997

0.091 0.043 0.031

0.91

0.12

(4) Ln(total biomass) ¼ c þ a ln(basal area  length)

c a

6.267 þ0.830

0.069 0.011

0.90

0.13

(5) Ln(total biomass) ¼ c þ a ln(squared diameter  length)

c a

2.685 þ0.821

0.029 0.011

0.90

0.13

Equation

Coefficient

(1) Ln(total biomass) ¼ c þ a ln(diameter)

c a

(2) Ln(total biomass) ¼ c þ a ln(length)

a

Normalized mean square error (see Section 2.3).

C. Gehring et al. / Forest Ecology and Management 195 (2004) 69–83

73

ln (Total biomass) = -3.366 + 1.612 * ln (length) 06

2- to 5-yr.-old secondary regrowth 7- to 25-yr.-old secondary regrowth Primary forest

ln (Total biomass in kg)

04

02

00

-02

-04

-06 -2

-1

0

1

2

3

4

ln (Length in meters) Fig. 2. Ln-linear relationship between liana length and biomass (mixed-species, R2 ¼ 0:73).

(pr 2  length and squared diameter  length) as predictors (models 4 and 5 in Tables 2 and 3). Estimation of liana leaf biomass was less precise than estimation of total biomass, R2 ranged from 0.61 to 0.78 for mixed-species equations (Table 3). Species-specific differences could be one reason, as Appendices B–D show comparatively larger differences between species for leaf biomass equations than

length should be included in the estimation of liana biomass depends on the achievable precision of shootlength determination. This question is further discussed for Amazonian tree allometry by Arau´ jo et al. (1999). Allometric equations using diameter and length as separate estimate variables outperformed the equations using fixed calculations of shoot volume Table 3 Mixed-species equations for the estimation of liana leaf biomass Equation

Coefficient

(1) Ln(leaf biomass) ¼ c þ a ln(diameter)

c a c a c a b c a c a

(2) Ln(leaf biomass) ¼ c þ a ln(length) (3) Ln(leaf biomass) ¼ c þ a ln(diameter) þ b ln(length)

(4) Ln(leaf biomass) ¼ c þ a ln(basal area  length) (5) Ln(leaf biomass) ¼ c þ a ln(squared diameter  length) a

Normalized mean square error (see Section 2.3).

7.094 þ1.690 4.281 þ1.168 6.391 þ1.089 þ0.694 6.431 þ0.603 3.798 þ0.603

S.E.

Adjusted R2

NMSEa

0.133 0.053 0.058 0.039 0.112 0.053 0.038 0.083 0.013 0.035 0.014

0.64

0.09

0.61

0.10

0.78

0.05

0.78

0.06

0.78

0.06

74

C. Gehring et al. / Forest Ecology and Management 195 (2004) 69–83

% Leaf = 22.045 - 4.871 * ln (Total biomass)

Leaf biomass share in %

80

2- to 5-yr.-old secondary regrowth 7- to 25-yr.-old secondary regrowth Primary forest

60

40

20

0 -6

-4

-2

0

2

4

6

ln (Total biomass in kg) Fig. 3. Decreasing leaf biomass share with increasing liana size (mixed-species, R2 ¼ 0:38).

for total biomass equations. As expected, the leaf biomass share decreased with increasing liana shoot size (Fig. 3). 3.2. Influence of stand age and shoot quantity A key objective of this study was to ensure the validity of allometric equations within a range of environmental conditions relevant for other field studies. Our data set offered the opportunity to investigate a wide spectrum of environments both at the community level (ranging from low secondary regrowth to mature primary forest) and at the plant level (liana biomass concentrated in a single or distributed in many shoots). Table 4 summarizes the results of hierarchical GLM for the explanation of variance of total (mixed-species) liana biomass (all R2 at P < 0:05). As noted in Table 2, length and diameter explained 73% each, and together about 91% of total variance of liana biomass. Inclusion of shoot quantity did not increase, and inclusion of vegetation age only marginally increased the explanation of total variance. Mean deviance

residuals were slightly lower when considering both variables together, but R2 did not increase. The finding that a liana shoot of given dimension (diameter or length) will have the same biomass, irrespective of where and how it grows, implies insensitivity of allometric behavior within the wide range of conditions investigated in this study. Equations are, therefore, deemed valid for application in other tropical forest vegetation. Table 4 Hierarchical generalized linear model for the explanation of variance of total liana biomass (all P < 0:05, the deviance residuals are a measure of how close the respective models fit the data) Predictor

R2

Deviance residuals

Diameter Length Diameter, length Diameter, length, vegetation age Diameter, length, shoot quantity Diameter, length, vegetation age, shoot quantity

0.734 0.733 0.909 0.912 0.909 0.910

103.4 103.4 35.5 34.3 35.4 30.5

C. Gehring et al. / Forest Ecology and Management 195 (2004) 69–83

75

Table 5 Pearson correlations between the measured (total or leaf) biomass and the biomass calculated with mixed-species or species-specific allometric equations (using ln-transformed values, all P < 0:001) Model

(1) Ln(biomass) ¼ c þ a ln(diameter) (2) Ln(biomass) ¼ c þ a ln(length) (3) Ln(biomass) ¼ c þ a ln(diameter) þ b ln(length)

Total biomass

Leaf biomass

Single species

Mixed-species

Single species

Mixed-species

0.92 0.93 0.97

0.86 0.86 0.95

0.89 0.88 0.93

0.80 0.78 0.88

3.3. Species-specific differences

4. Conclusions

We present the species-specific allometric equations using diameter, length, and both length and diameter as input variables in Appendices B–D, respectively. Goodness of fit varied among species, ranging from R2 ¼ 0:610:92 for the diameter-based equations. With few exceptions, slopes and intercepts differed little among species. Allometric behavior was not related to taxonomic groups (genera or families). Our data likewise do not support systematic differences between typical pioneer versus primary forest liana species. This is in contrast to tree allometry, with substantial differences mostly caused by lower wood densities of secondary forest species (Fearnside, 1997; Nelson et al., 1999). Table 5 compares the performance of species-specific and of mixed-species allometric equations for the estimation of liana biomass. Biomass predicted with the species-specific equations consistently correlated better with the measured biomass than biomass predicted with mixed-species equations. This holds true both for diameter-, length-based or combined equations, and for the estimation of total and of leaf biomass. Thus, the species-specific equations are preferable over the mixed-species equations and should be applied in other studies whenever these common liana species are encountered. Nevertheless, both the goodness of fit and the correlations between the observed and predicted biomass obtained with mixed-species equations were also significant and only moderately lower than those obtained with species-specific equations. This allows the conclusion that liana allometry is fairly insensitive to species composition on a stand level. The mixedspecies equations presented in Tables 2 and 3 are, therefore, deemed valid for the non-destructive estimation of liana biomass in other secondary or primary forests with differing species composition.

The diameter-based mixed-species equation presented in this paper provides a simple tool for liana biomass estimation in field research. Liana shoot allometry was unaffected by environmental conditions over a wide range of vegetation types and was identical for single- and multiple-shoot plants. Species-specific variability was moderate only. This ensures the general validity of our liana allometric equations for field use in other tropical bushlands and forests.

Acknowledgements From cooperation between the Center of Development Research, University of Bonn, Germany, and the Centro de Pesquisas Agroflorestais da Amazoˆ nia Ocidental EMBRAPA/CPAA, Manaus, AM, Brazil, under the Governmental Agreement on Cooperation in the field of scientific research and technological development between Germany and Brazil. This study was financed by a grant of the German Federal Ministry of Education, Science, Research and Technology (BMBF project no. 0339723). Field research was supported by the rural extension services ‘Projeto Lumiar’ and Instituto de Desenvolvimento da Amazoˆ nia (IDAM).

Appendix A Liana species under investigation Genus Machaerium (Fabaceae) Machaerium amplum Benth. Machaerium castaneiflorum Ducke

76

C. Gehring et al. / Forest Ecology and Management 195 (2004) 69–83

Machaerium Machaerium Machaerium Machaerium Machaerium

caudatum Ducke ferox Glaziou hoehneanum Ducke madeirensis Pittier multifoliolatum Ducke

Senna tapajozensis H.S. Irwin & Barneby (Caesalpinaceae) Non-legumes Davilla rugosa Poir. (Dilleniaceae) Leucocalantha aromatica Barb. Rodr. (Bignoniaceae) Memora adenophera Sandwith (Bignoniaceae) Memora moringifolia Sandwith (Bignoniaceae) Pleonotoma jasminifolia Miers.(Bignoniaceae) Pseudoconnarus rhynchosioides (Standl.) Prance (Connaraceae) Rourea cuspidata Benth.(Connaraceae) Securidaca rivinaefolia St. Hill (Polygalaceae) Strychnos subcordata Spruce (Loganiaceae)

Other Leguminosae Acacia multipinnata Ducke (Mimosaceae) Bauhinia alata Ducke (Fabaceae) Bauhinia guianensis Aubl. (Fabaceae) Derris amazonica Killip (Fabaceae) Derris negrensis Benth. (Fabaceae) Clitoria leptostachya Benth. (Fabaceae) Mimosa guilandinae (DC) Barneby (Mimosaceae) Mimosa spruceana (Benth.)Barneby (Mimosaceae)

Appendix B Diameter-based allometric equations of 20 liana morphospecies for the estimation of total and leaf biomass Ln(total biomass) ¼ c þ a ln(diameter) Coefficient value Genus Machaerium Machaerium hoehneanum c *** 8.733 a *** þ3.054 Machaerium madeirensis c *** 7.093 a *** þ2.560

Ln(leaf biomass) ¼ c þ a ln(diameter)

S.E.

Adjusted R2

Coefficient value

0.533 0.210

0.82

*** ***

0.803 0.278

0.81

0.82

Machaerium castaneiflorum c *** 6.967 0.688

No. of shoots and range (mm)

S.E.

Adjusted R2

8.228 þ2.249

0.430 0.169

0.80

n ¼ 46, 4–60

*** ***

8.114 þ2.195

0.728 0.252

0.79

n ¼ 21, 3–75

***

5.689

0.666

0.61

n ¼ 23, 10– 77

***

þ1.138

0.192

þ2.012

0.198

Machaerium caudatum c *** 6.687 a *** þ2.029

0.661 0.232

0.67

*** ***

6.670 þ1.430

0.653 0.229

0.50

n ¼ 39, 3–70

Machaerium ferox c *** 6.242 a *** þ1.954

0.562 0.206

0.82

*** ***

7.288 þ1.726

0.656 0.241

0.73

n ¼ 20, 2–29

0.92

*** ***

9.120 þ2.484

0.433 0.159

0.95

n ¼ 15, 5–60

a

***

Machaerium multifoliolatum c *** 10.140 0.774 a *** þ3.720 0.285

C. Gehring et al. / Forest Ecology and Management 195 (2004) 69–83

77

Appendix B. (Continued ) Ln(total biomass) ¼ c þ a ln(diameter) Coefficient value

Ln(leaf biomass) ¼ c þ a ln(diameter)

S.E.

Adjusted R2

Coefficient value

0.446 0.227

0.68

*** ***

No. of shoots and range (mm)

S.E.

Adjusted R2

6.010 þ0.930

0.540 0.275

0.35

n ¼ 20, 3–24

*** ***

7.463 þ2.348

0.368 0.189

0.81

n ¼ 36, 2–40

0.89

*** ***

7.906 þ1.771

0.624 0.210

0.65

n ¼ 39, 5–51

0.61

*** ***

7.781 þ1.973

0.813 0.292

0.52

n ¼ 42, 9–38

Acacia multipinnata, Mimosa guilandinae c *** 8.494 0.665 0.86 a *** þ3.077 0.294

*** ***

8.850 þ2.579

0.979 0.433

0.86

n ¼ 18, 5–21

Mimosa spruceanum, Senna tapajozensis c *** 7.653 0.458 0.85 a *** þ2.564 0.120

*** ***

8.153 þ2.263

0.458 0.120

0.87

n ¼ 29, 4–23

Machaerium amplum c *** 5.452 a *** þ1.476

Other Leguminosae Bauhinia alata, Bauhinia guianensis c *** 7.646 0.498 0.81 a *** þ3.107 0.256 Clitoria leptostachya c *** 7.271 a *** þ2.125

0.365 0.123

Derris negrensis, Derris amazonica c *** 6.891 0.698 a *** þ2.014 0.251

Other liana species Rourea cuspidata c *** 8.667 a *** þ2.800

0.591 0.261

0.76

*** ***

8.395 þ2.190

0.606 0.267

0.65

n ¼ 37, 4–25

Davilla rugosa c *** 6.127

0.888

0.74

***

4.878

0.550

0.63

n ¼ 17, 1– 138

þ2.217

0.322

***

þ1.055

0.120

Securidaca rivinaefolia c *** 8.960 a *** þ4.182

0.859 0.596

0.74

*** ***

10.028 þ4.230

1.022 0.709

0.67

n ¼ 18, 2–6

Memora adenophera c *** 7.952 a *** þ2.356

0.389 0.170

0.88

*** ***

7.859 þ1.748

0.477 0.206

0.73

n ¼ 27, 2–30

*** ***

7.623 þ1.731

0.395 0.185

0.62

n ¼ 55, 3–20

a

***

Memora moringifolia, Pleonotoma jasminifolia c *** 7.883 0.402 0.76 a *** þ2.437 0.188

78

C. Gehring et al. / Forest Ecology and Management 195 (2004) 69–83

Appendix B. (Continued ) Ln(total biomass) ¼ c þ a ln(diameter) Coefficient value

S.E.

Ln(leaf biomass) ¼ c þ a ln(diameter) Adjusted R2

Coefficient value

Pseudoconnarus rhynchosioides c *** 7.361 0.775 a *** þ2.391 0.328

0.81

*** ***

Leucocalantha aromatica c *** 6.646 a *** þ2.332

0.896 0.365

0.62

Strychnos subcordata c *** 8.314 a *** þ2.710

0.551 0.267

0.84

No. of shoots and range (mm)

S.E.

Adjusted R2

7.191 þ1.809

0.989 0.418

0.60

n ¼ 13, 5–23

*** ***

5.580 þ1.467

1.146 0.467

0.27

n ¼ 25, 7–22

*** ***

7.411 þ1.642

0.457 0.221

0.73

n ¼ 21, 7–22

Appendix C Length-based allometric equations of 20 liana morphospecies for the estimation of total and leaf biomass Ln(total biomass) ¼ c þ a ln(length) Coefficient value

S.E.

Ln(leaf biomass) ¼ c þ a ln(length) Adjusted R2

Coefficient value

0.75

*** ***

Machaerium madeirensis c *** 3.667 0.356 a *** þ1.703 0.141

0.88

Machaerium castaneiflorum c *** 2.482 0.257 a *** þ1.822 0.177 Machaerium caudatum c *** 3.314 a *** þ1.983 Machaerium ferox c *** 3.247 a *** þ1.843

No. of shoots and range (m)

S.E.

Adjusted R2

4.494 þ1.311

0.258 0.149

0.63

n ¼ 46, 0.90–42.20

***

4.964 þ1.328

0.463 1.184

0.72

n ¼ 21, 0.65–48.00

0.83

*** ***

3.322 þ1.156

0.187 0.129

0.78

n ¼ 23, 1.10–12.50

0.211 0.154

0.81

*** ***

4.118 þ1.245

0.285 0.208

0.48

n ¼ 39, 0.80–32.70

0.379 0.287

0.68

*** **

4.296 þ1.843

0.490 0.341

0.39

n ¼ 20, 1.10–9.50

Genus Machaerium Machaerium hoehneanum c *** 3.825 0.285 a *** þ1.899 0.190

C. Gehring et al. / Forest Ecology and Management 195 (2004) 69–83

79

Appendix C. (Continued ) Ln(total biomass) ¼ c þ a ln(length)

Ln(leaf biomass) ¼ c þ a ln(length) Adjusted R2

Coefficient value

Machaerium multifoliolatum c *** 3.303 0.385 a *** þ1.847 0.174

0.89

*** ***

Machaerium amplum c *** 4.124 a *** þ1.119

0.72

No. of shoots and range (m)

S.E.

Adjusted R2

4.565 þ1.245

0.210 0.095

0.92

n ¼ 15, 0.50–63.60

*** *

4.990 þ0.564

0.341 0.225

0.22

n ¼ 20, 0.60–16.90

*** ***

4.719 þ1.265

0.223 0.123

0.75

n ¼ 36, 0.30–46.50

*** ***

4.343 þ2.084

0.198 0.216

0.71

n ¼ 39, 0.90–8.60

Derris negrensis, Derris amazonica c *** 2.968 0.148 0.79 a *** þ1.925 0.157

*** ***

3.928 þ1.873

0.195 0.206

0.67

n ¼ 42, 1.20–5.70

Acacia multipinnata, Mimosa guilandinae c *** 3.536 0.337 0.72 a *** þ1.511 0.225

*** ***

4.771 þ1.330

0.372 0.248

0.62

n ¼ 18, 0.80–13.00

Mimosa spruceanum, Senna tapajozensis c *** 4.236 0.250 0.80 a *** þ1.913 0.179

*** ***

5.063 þ1.627

0.272 0.194

0.71

n ¼ 29, 0.90–12.40

0.0.098 0.89 0.078

*** ***

4.311 þ1.105

0.092 0.073

0.86

n ¼ 37, 0.50–21.50

Davilla rugosa c *** 3.563 a *** þ1.956

0.425 0.208

0.85

*** ***

3.740 þ0.987

0.244 0.119

0.81

n ¼ 17, 0.50–47.30

Securidaca rivinaefolia c *** 5.024 a *** þ2.005

0.0.222 0.87 0.184

*** ***

5.996 þ1.976

0.330 0.274

0.75

n ¼ 18, 0.60–8.00

Memora adenophera c *** 3.212 a *** þ1.244

0.069 0.060

*** ***

4.345 þ0.929

0.107 0.093

0.80

n ¼ 27, 0.30–17.50

Coefficient value

S.E.

0.243 0.160

Other Leguminosae Bauhinia alata, Bauhinia guianensis c *** 4.065 0.275 0.78 a *** þ1.718 0.152 Clitoria leptostachya c *** 2.804 a *** þ2.251

Other liana species Rourea cuspidata c *** 3.393 a *** þ1.324

0.178 0.194

0.78

0.94

80

C. Gehring et al. / Forest Ecology and Management 195 (2004) 69–83

Appendix C. (Continued ) Ln(total biomass) ¼ c þ a ln(length) Coefficient value

S.E.

Ln(leaf biomass) ¼ c þ a ln(length) Adjusted R2

Coefficient value

S.E.

Adjusted R2

No. of shoots and range (m)

Memora moringifolia, Pleonotoma jasminifolia c *** 3.288 0.058 0.88 *** a *** þ1.113 0.055 ***

4.365 þ0.805

0.067 0.063

0.75

n ¼ 55, 0.20–10.30

Pseudoconnarus rhynchosioides c *** 3.896 0.264 a *** þ1.774 0.196

0.87

*** ***

4.636 þ1.401

0.346 0.257

0.71

n ¼ 13, 0.90–8.50

Leucocalantha aromatica c *** 2.437 0.213 a *** þ0.891 0.118

0.70

*** ***

2.997 þ0.600

0.287 0.159

0.36

n ¼ 25, 1.50–21.00

Strychnos subcordata c *** 3.646 a *** þ1.364

0.83

*** ***

4.569 þ0.802

0.127 0.121

0.68

n ¼ 21, 0.50–10.30

0.142 0.136

Appendix D Allometric equations of 20 liana morphospecies using both diameter and length as input variables (for data structure and size ranges see Appendices B and C) Ln(total biomass) ¼ c þ a ln(diameter) þ b ln(length) Coefficient value

Ln(leaf biomass) ¼ c þ a ln(diameter) þ b ln(length)

S.E.

Adjusted R2

Coefficient value

Genus Machaerium Machaerium hoehneanum c *** 7.560 a *** þ2.006 b *** þ1.035

0.300 0.035 0.096

0.95

*** *** ***

Machaerium madeirensis c *** 5.512 a ** þ1.146 b *** þ1.099

0.583 0.318 0.201

0.93

Machaerium castaneiflorum c *** 5.160 a *** þ1.095 b *** þ1.008

0.651 0.255 0.230

0.91

S.E.

Adjusted R2

7.543 þ1.637 þ0.604

0.366 0.179 0.117

0.87

*** *** ***

7.309 þ1.456 þ0.559

0.772 0.421 0.266

0.82

*** n.s. ***

3.968 þ0.264 þ0.960

0.640 0.250 0.226

0.78

C. Gehring et al. / Forest Ecology and Management 195 (2004) 69–83

81

Appendix D. (Continued ) Ln(total biomass) ¼ c þ a ln(diameter) þ b ln(length) Coefficient value

Ln(leaf biomass) ¼ c þ a ln(diameter) þ b ln(length)

S.E.

Adjusted R2

Coefficient value

Machaerium caudatum c *** 5.278 a *** þ0.943 b *** þ1.410

0.414 0.183 0.162

0.89

*** ** **

Machaerium ferox c *** a *** b ***

5.906 þ1.379 þ0.996

0.275 0.124 0.128

0.96

Machaerium multifoliolatum c *** 7.869 a ** þ2.438 b n.s. þ0.689

1.466 0.767 0.388

Machaerium amplum c *** 4.969 a * þ0.761 b ** þ0.675

0.407 0.309 0.229

Other Leguminosae Bauhinia alata, Bauhinia guianensis c *** 6.529 0.349 a *** þ1.869 0.234 b *** þ0.956 0.131 Clitoria c a b

leptostachya *** 6.073 *** þ1.472 *** þ0.917

0.366 0.159 0.179

Derris negrensis, Derris amazonica c *** 4.494 0.602 a * þ0.687 0.264 b *** þ1.487 0.223 Acacia multipinnata, Mimosa guilandinae c *** 7.811 1.057 a *** þ2.613 0.630 b n.s. þ0.281 0.336 Mimosa c a b

spruceanum, *** *** ***

Senna tapajozensis 6.601 0.406 þ1.594 0.252 þ0.924 0.194

S.E.

Adjusted R2

5.964 þ0.886 þ0.707

0.654 0.289 0.257

0.58

*** *** n.s.

7.142 þ1.476 þ0.431

0.646 0.292 0.301

0.74

0.93

*** ** *

7.350 þ1.488 þ0.537

0.712 0.372 0.188

0.96

0.78

*** n.s. n.s.

–

–

–

0.92

*** *** ***

6.701 þ1.503 þ0.653

0.286 0.192 0.107

0.91

0.93

*** ** ***

6.145 þ0.811 þ1.348

0.682 0.296 0.334

0.75

0.81

*** n.s. ***

5.478 þ0.698 þ1.429

0.819 0.359 0.303

0.69

0.86

*** n.s. n.s.

–

–

–

*** *** *

7.427 þ1.593 þ0.638

0.491 0.304 0.234

0.85

0.92

82

C. Gehring et al. / Forest Ecology and Management 195 (2004) 69–83

Appendix D. (Continued ) Ln(total biomass) ¼ c þ a ln(diameter) þ b ln(length) Coefficient value

Ln(leaf biomass) ¼ c þ a ln(diameter) þ b ln(length)

S.E.

Adjusted R2

Coefficient value

S.E.

Adjusted R2

Non-legume species Rourea cuspidata c *** a *** b ***

5.507 þ1.072 þ0.948

0.473 0.236 0.104

0.93

*** n.s. ***

5.296 þ0.499 þ0.930

0.533 0.266 0.117

0.87

Davilla rugosa c *** a ** b ***

5.183 þ1.039 þ1.313

0.526 0.273 0.228

0.92

*** n.s. ***

4.340 þ0.384 þ0.748

0.382 0.198 0.165

0.84

Securidaca rivinaefolia c *** 6.770 a ** þ1.637 b *** þ1.432

0.618 0.553 0.246

0.91

*** n.s. **

8.025 þ1.902 þ1.310

1.020 0.914 0.406

0.79

Memora c a b

adenophera *** 5.153 *** þ0.948 *** þ0.816

0.339 0.164 0.084

0.98

*** n.s. **

5.694 þ0.659 þ0.631

0.762 0.369 0.189

0.81

Memora c a b

moringifolia, Pleonotoma jasminifolia *** 5.245 0.301 0.93 *** þ1.005 0.153 *** þ0.784 0.065

*** ** ***

5.630 þ0.649 þ0.592

0.434 0.221 0.093

0.78

** n.s. n.s.

–

–

–

Pseudoconnarus rhynchosioides c *** 5.134 a * þ1.029 b ** þ1.136

0.764 0.459 0.330

0.91

Leucocalantha aromatica c *** 4.928 a ** þ1.225 b *** þ0.591

0.770 0.369 0.133

0.79

** n.s. *

4.288 þ0.635 þ0.444

1.240 0.594 0.215

0.36

Strychnos subcordata c *** 6.307 a *** þ1.499 b *** þ0.742

0.596 0.331 0.167

0.92

*** * *

6.393 þ1.028 þ0.377

0.644 0.358 0.180

0.77

C. Gehring et al. / Forest Ecology and Management 195 (2004) 69–83

References Arau´ jo, T.M., Higuchi, N., Andrade, J.C., 1999. Comparison of formulae for biomass content determination in a tropical rain forest site in the state of Para´ , Brazil. For. Ecol. Manage. 117, 43–52. Brown, I.F., Martinelli, L.A., Thomas, W.W., Moreira, M.Z., Cid Ferreira, C.A., Victoria, R.A., 1995. Uncertainty in the biomass of Amazonian forests: an example from Rondoˆ nia, Brazil. For. Ecol. Manage. 75, 175–189. Chave, J., Rie´ ra, B., Dubois, M.A., 2001. Estimation of biomass in a neotropical forest of French Guyana: spatial and temporal variability. J. Trop. Ecol. 17, 79–96. Dewalt, S.J., Schnitzer, S.A., Denslow, J.S., 2000. Density and diversity of lianas along a chronosequence in a central Panamanian lowland forest. J. Trop. Ecol. 16, 1–19. Fearnside, P.M., 1992. Forest biomass in Brazilian Amazonia: comments on the estimate by Brown and Lugo. Interciencia 17, 19–27. Fearnside, P.M., 1997. Wood density for estimating forest biomass in Brazilian Amazonia. For. Ecol. Manage. 90, 59–87. Gehring, C., 2003. The role of biological nitrogen fixation in secondary and primary forests of central Amazonia. Cuvillier, Go¨ ttingen. Gehring, C., Park, S.J., Denich, M., 2004. Close relationship between diameters at 30 cm height and at breast height (dbh). Acta Amazonica, submitted for publication. Gerwing, J.J., Farias, D.L., 2000. Integrating liana abundance and forest stature into an estimate of total aboveground biomass for an eastern Amazonian forest. J. Trop. Ecol. 16, 327–335. Ketterings, Q.M., Coe, R., van Noordwijk, M., Ambagau, Y., Palm, C.A., 2001. Reducing uncertainty in the use of allometric biomass equations for predicting above-ground tree biomass in mixed secondary forests. For. Ecol. Manage. 146, 199–209. Laurance, W.F., Pe´ rez-Salicrup, D., Delamonica, P., Fearnside, P.M., d’Angelo, S., Jerozolinski, A., Pohl, L., Lovejoy, T.E.,

83

2001. Rain forest fragmentation and the structure of Amazonian liana communities. Ecology 102 (1), 105–116. McCullagh, P., Nelder, J.A., 1989. General Linear Models, 2nd ed. Chapman & Hall, London. Nelson, B.W., Mesquita, R., Pereira, J.L.G., de Souza, S.G.A., Batista, G.T., Couto, L.B., 1999. Allometric regressions for improved estimate of secondary forest biomass in the central Amazon. For. Ecol. Manage. 117, 149–167. Overman, J.P.M., Witte, H.J.L., Saldarriaga, J.G., 1994. Evaluation of regression modes for aboveground biomass determination in Amazon rainforest. J. Trop. Ecol.10, 207–218. Phillips, O.L., Martı´nez, R.V., Arroyo, L., Baker, T., Killeen, T., Lewis, S.L., Malhi, Y., Mendoza, A.M., Neill, D., Nu´ n˜ ez Vargas, P., Alexiades, M., Cero´ n, C., di Fiore, A., Erwin, T., Jardim, A., Palacios, W., Saldias, M., Vinceti, B., 2002. Increasing dominance of large lianas in Amazonian forests. Nature 418, 770–774. Pinard, M.A., Putz, F.E., 1994. Vine infestation of large remnant trees in logged forest in Sabah, Malaysia: biomechanical facilitation in vine succession. J. Trop. For. Sci. 6, 302–309. Putz, F.E., 1983. Liana biomass and leaf area of a ‘tierra firme’ forest in the Rio Negro basin, Venezuela. Biotropica 15, 185–189. Richter, D.D., Babbar, L.I., 1991. Soil diversity in the tropics. Adv. Ecol. Res. 21, 315–389. Rollet, B., 1969. La rege´ ne´ ration naturelle en foreˆ t dense humide sempervirente de plaine de la Guyane Ve´ ne´ zue´ lienne. Revue Bois et Foreˆ ts des Tropiques 124, 19–38. Schnitzer, S.A., Dalling, J.W., Carson, W.P., 2000. The impact of lianas on tree regeneration in tropical forest canopy gaps: evidence for an alternative pathway of gap-phase regeneration. J. Ecol. 88, 655–666. Schroth, G., d’Angelo, S.A., Teixeira, W., Haag, D., Lieberei, R., 2002. Conversion of secondary forest into agroforestry and monoculture plantations in Amazonia: consequences for biomass, litter and soil carbon stocks after seven years. For. Ecol. Manage. 163, 131–150.