Comparison of biomass production, tree allometry and nutrient

use ef®ciency of multipurpose trees grown in woodlot and

silvopastoral experiments in Kerala, India

B. Mohan Kumar*, Suman Jacob George, V. Jamaludheen, T.K. Suresh

College of Forestry, Kerala Agricultural University, Vellanikkara, Thrissur 680654, India

Received 9 September 1997; accepted 5 May 1998

Abstract

In woodlot and silvopasture experiments involving a total of three age-sequences, the rates of biomass accumulation and

nutrient accumulation by multipurpose trees were evaluated. The woodlot experiment included nine multipurpose trees

(Acacia auriculiformis, Ailanthus triphysa, Artocarpus heterophyllus, Artocarpus hirsutus, Casuarina equisetifolia, Emblica

of®cinalis, Leucaena leucocephala cv. K8, Paraserianthes falcataria and Pterocarpus marsupium) and the silvopastoral

experiment involved a subset of four trees (Acacia auriculiformis, Ailanthus triphysa, Casuarina equisetifolia and Leucaena

leucocephala cv. K8). Both plantings were maintained at Thiruvazhamkunnu, Kerala, India. Trees in the woodlot experiment

were felled (partially) at 8.8 years of age and that of the silvopastoral experiment both at 5 years and 7 years of age. Rate of

biomass accumulation and nutrient accumulation was highest for Acacia and the least for Leucaena. Allometric relationships

linking above ground biomass with DBH and/or total height gave reasonable predictions. A comparison between species and

among tissue types within species indicated that nutrient use ef®ciency for N, P and K varied widely. Implications for nutrient

export from the site through whole tree harvesting systems involving fast growing multipurpose tree species are discussed.

# 1998 Elsevier Science B.V. All rights reserved.

Keywords: Woodlot; Silvopastoralism; Micro-site enrichment; Nutrient export; Whole tree harvesting

1. Introduction

Development of tropical tree plantations has been

on the ascend in recent decades, presumably to meet

the ever-increasing demands for timber and ®rewood.

A wide spectrum of tree species, usually described as

multipurpose trees (MPTs), is often involved in such

programmes. Important attributes of MPTs include

rapid juvenile growth, ef®cient dry matter production

in terms of water and nutrient inputs, crown charac-

teristics to maximise interception of solar radiation

and ease of regeneration by coppicing (Fege, 1981).

Objectives of tree planting also vary correspondingly,

from multiple use of perpetually `natural looking

forests', development of high yielding and sustainable

industrial plantations for wood production, control of

land degradation and development of agroforestry

systems (Nambiar, 1995).

Forest Ecology and Management 112 (1998) 145±163

*Corresponding author. Tel.: +91-487-370050; fax: +91-487-

370019.

0378-1127/98/$ ± see front matter # 1998 Elsevier Science B.V. All rights reserved.

P I I : S 0 3 7 8 - 1 1 2 7 ( 9 8 ) 0 0 3 2 5 - 9

High biomass production obviously is an important

consideration in all tropical tree planting programmes.

Biomass productivity of the MPTs, however, differs

enormously with species, site characteristics and stand

management practices. Nonetheless, it is useful to

know the stocks of carbon as biomass per unit area,

not only to facilitate choice of species but also to

assess the impact of deforestation and re-growth rates

on the global carbon cycle (Deans et al., 1996).

Allometric regressions developed by measuring bio-

mass or production of either trees or their components

and regressing these data against some easily mea-

sured variable, such as DBH (diameter at breast

height), form the most important method for deter-

mining stand biomass production. It is desirable to

develop equations for individual sites, owing to spe-

cies±site relationships, rotation age±stand density

interactions (Wittwer and Immel, 1978) and the strong

in¯uence of tree management practices on biomass

production. According to Pastor et al. (1983/1984),

this, however, is costly and time-consuming. More-

over, many exotics including Australian acacias,

besides many indigenous species, are often grown

in the tropical regions including peninsular India. A

comprehensive account of their biomass production

potential and allometry is, nonetheless lacking, espe-

cially in the southern Indian context.

Short rotation tropical plantations that couple inten-

sive management and rapid growth rates are also

characterised by high rates of nutrient removal in

the harvested biomass, which in turn, raises concerns

about long-term site quality and sustainable produc-

tion. The potential nutrient export, especially with

whole tree harvesting may deplete the site nutrient

capital (Jorgensen and Wells, 1986; Wang et al.,

1991). Altering the rate of nutrient removal in pro-

ducts is probably an important design criterion in

intensive short rotation silvicultural systems. Selec-

tion of tree species and parts of the tree to be removed

from the site will determine the nutrient `cost' of

biomass extraction (Wang et al., 1991). However, only

isolated attempts were made until now to characterise

the magnitude of nutrient losses associated with selec-

tion of either tree species or their parts.

In this study we evaluated the biomass production

potential of nine fast growing multipurpose tropical

taxa, four of which were grown under two land

management systems (woodlots and silvopastoral-

ism). Our objectives were to determine component

contribution to stand biomass accumulation in a three

age-series of plantations. We also developed mono-

speci®c regression relationships for the determination

of stand biomass (above ground) for the multipurpose

trees in Kerala. Additionally, we estimated the nutrient

characteristics of these taxon. Our aim was to explore

the potentially large differences in nutrient `cost'

because of species selection and harvest practice

and to examine the implications of these `costs' for

sustainable productivity. The impact of trees on soil

nutrient accumulation also was assessed.

2. Materials and methods

Two ®eld experiments were conducted at the Live-

stock Research Station, Thiruvazhamkunnu (two sites

in an over-200 ha farm), Palakkad district, Kerala,

India. (See Mathew et al., 1992; George et al., 1996

for details on site description). The location has an

elevation of ca 60 m above mean sea level and is

situated at 1182105000N latitude and 768105000E long-

itude. Mean annual rainfall is about 2569 mm, most of

which is received during the southwest monsoon

season (June±August). Mean maximum temperature

ranges from 28.18C (October) to 38.78C (April) and

mean minimum temperature, from 19.58C (January) to

26.08C (November). The soils of the experimental

sites were acidic oxisols.

2.1. Experiment no. 1 (woodlot)

Initiated in June 1985, this trial involved nine fast

growing multipurpose trees (Acacia auriculiformis A.

Cunn. ex Benth, Ailanthus triphysa (Dennst.) Alston,

Artocarpus heterophyllus Lamk., Artocarpus hirsutus

Lamk., Casuarina equisetifolia J.R & G. Forst,

Emblica of®cinalis Gaertn., Leucaena leucocephala

(Lamk) de Wit cv. K8, Paraserianthes falcataria (L)

Neilson and Pterocarpus marsupium Roxb., arranged

in a randomised block design with three replications.

Containerised stock was planted in 20 m�20 m plots

at 2 m�2 m spacing (see Jamaludheen et al., 1997;

Jamaludheen and Kumar, 1998 for related aspects on

functional dynamics of multipurpose tree production

systems). A 5 m unplanted buffer separated each plot.

The soil at the experimental site is shallow oxisols,

146 B.M. Kumar et al. / Forest Ecology and Management 112 (1998) 145±163

with a pH of 6.7. The terrain is modestly undulating

with less than half meter soil depth on ridges.

2.2. Experiment no. 2 (silvopastoral system)

Another ®eld experiment (located about 400 m

away from the previous one and having similar site

characteristics) involving 16 tree±grass combinations

(four grass and four tree species) was initiated in June

1988 (see Mathew et al., 1992; George et al., 1996 for

details on tree±grass combinations, cultural practices

and lay out plan), It had a subset of four fast growing

multipurpose tree species (Acacia auriculiformis A.

Cunn. ex Benth., Ailanthus triphysa (Dennst.) Alston,

Casuarina equisetifolia J.R.& G. Forst. and Leucaena

leucocephala (Lam.) de Wit.). Trees were planted in

plots of 6 m�6 m in two rows, 4 m apart (within row

spacing 1 m). Fertilisers were applied to the forage

crop in this experiment at the rate of 200, 50, 50 kg N,

P2O5 and K20 haÿ1 yearÿ1, as per standard recom-

mendations (KAU, 1993). The soil at the experimental

site is oxisol with a pH of 5.1 and having moderate to

substantial depth (few meters).

2.3. Estimation of tree biomass

In experiment 1, all trees forming alternate diagonal

rows in the stand were destructively sampled during

April 1994 (tree age: 8 years and 10 months). Thin-

ning reduced the initial 2500 trees per hectare planting

density to 1250 trees per hectare. Number of trees

harvested excluding the border rows ranged from 17±

32 per species. In experiment 2, all trees in eight

6 m�6 m plots (two for each species) were felled in

May 1993 (tree age: 5 years). Number of trees har-

vested per species ranged from 15 to 22. The remain-

ing trees (40 plots), ranging from 86±113 per species,

were felled 2 years later in May 1995 (tree age: 7

years).

Trees were felled at the ground level using a

mechanical chain saw (Poulan/Pro, USA). After

recording the total height and diameter at breast height

(DBH), the above ground portions of the felled trees

were separated into stem wood (main shoot; if the

main shoot is forked below BH level (1.37 m), then

such branches were also treated as stem wood), branch

wood (all branches differentiating above BH level)

and foliage. Fresh weights of all the above compo-

nents were recorded immediately after felling using

appropriate spring scales (to either nearest 0.1 kg or

10 mg). Representative foliage and branch wood sam-

ples (ca 500 g each) were collected (species-wise,

triplicate) for moisture estimation and chemical ana-

lyses, in a random fashion. Stem disks (ca 2 cm thick)

were cut at BH and at the base of the crown from three

randomly selected trees per taxa. For quantifying the

coarse root (>5 mm radius) component, three ran-

domly selected tree-stumps (by species) were com-

pletely excavated and their fresh weights recorded.

Triplicate samples (ca 500 g each, covering small,

medium and large roots; species-wise) for moisture

and chemical analyses were also collected.

The samples were immediately transferred to the

laboratory in double-sealed polythene bags. After

recording the fresh weights, they were dried to con-

stant weights at 708C, and ground to pass through a

2 mm sieve. Estimates of dry weight biomass were

obtained from the fresh weights of various tissue types

and their corresponding moisture contents. Dry:wet

ratios from felled trees were used to correct the ®eld

weight determinations and obtain biomass on a per

tree basis. The average biomass of component parts

per tree was multiplied by the number of trees per plot

and extrapolated to a hectare. Biomass of tree parts

other than roots were summed to obtain the total above

ground biomass per tree. It was then multiplied by the

number of trees per plot and extrapolated to a hectare,

as in the previous case.

Additional foliage samples (ca 500 g) were also

collected from the felled trees (three samples per

taxon) and transported to the laboratory in a refriger-

ated container for leaf area measurement. After

recording the fresh weight of the samples leaf area

measurement were made (LI 3100, Li Cor, Lincoln,

Nebraska, USA). Total leaf areas for individual trees

were calculated by multiplying the total fresh weight

of foliage with the leaf area±fresh weight ratio.

2.4. Phytochemical analyses

Triplicate samples were analysed for N, P and K

(three sub-samples were drawn from the tissue sam-

ples for this purpose). Nitrogen was estimated follow-

ing the micro-Kjeldahl method. Phosphorus and

potassium were estimated after digesting the samples

in triple acid mixture (HNO3, H2SO4 and HClO4 in

B.M. Kumar et al. / Forest Ecology and Management 112 (1998) 145±163 147

10:1:3). Phosphorus was determined following the

vanado±molybdo phosphoric yellow colour method

and potassium by ¯ame photometry (Jackson, 1958).

Total biomass nutrient content on per tree basis (nutri-

ent accumulation for each tissue and for each species)

was calculated by multiplying the mean biomass of

each species' plant part by the corresponding nutrient

concentrations. Totals for whole trees were obtained

by summing results for component parts. Average

nutrient accumulation per tree was multiplied by

the number of trees per plot and extrapolated to a

hectare. Nutrient use ef®ciency was estimated by

dividing component-wise biomass accumulation with

the corresponding nutrient accumulation ®gure.

2.5. Soil chemical analyses

Soil samples were collected from the inter-spaces

between two rows of trees at three points in each plot

(the top 0±15 cm soil layer). They were air dried and

ground to pass through a 2 mm sieve. Triplicate

samples were analysed as follows: soil pH in an

aqueous suspension of soil and water (1:2) using an

`Elico' pH meter, organic C by the Walkley±Black

method, total N by micro-Kjeldahl method, available

P by Bray and Kurtz method and available K by ¯ame

photometry following extraction with N neutral

CH3COONH4 (Jackson, 1958).

2.6. Statistical treatment of data

Biomass, photochemical and soil data (means of

three sub-samples) were analysed following the

ANOVA technique (using MSTAT). LSD test was

used to compare mean biomass yield, nutrient con-

centration, nutrient content of tree parts and whole

trees and the soil parameters. Six allometric equations

were ®tted to predict the total above ground biomass

of single trees of each species and age class using the

total tree-wise biomass yield data. For this, we used

previously published models (Alemdag and Horton,

1981; Lavinge, 1982; Campbell et al., 1985; Dudley

and Fownes, 1992; Philip, 1994). The variables

included diameter at breast height (DBH) and height

(H). Logarithmic transformation of the original bole

diameter and biomass data ensured homoscedasticity

and allowed linear regression techniques to be used in

respect of models 1±3 (see foot note in Table 4).

Equation parameters were computed using linear esti-

mation procedure in LOTUS 2.0. Biomass equations,

generalised for the geographic region were also devel-

oped using the biomass data pooled over age

sequences. Only selected equations based on R2 and

graphical examination of the residuals are presented

here.

3. Results and discussion

3.1. Biomass production

Biomass accumulation for the nine taxa studied

shows wide variations. Above-ground biomass yield

on per hectare basis was highest for Acacia (326, 184

and 141 Mg haÿ1 at 8.8, 7 and 5 years, respectively,

Table 1). Neither stand age nor cultural system (woo-

dlot vs. silvopastoralism) seemed to alter this overall

pattern. Paraserianthes registered the second highest

biomass yield of 183 Mg haÿ1 at 8.8 years and Leu-

caena, the lowest. In the silvopastoral experiment (5

and 7 years), contrary to expectations, Ailanthus

consistently recorded the lowest biomass yield. Two

insect pests (Atteva fabriciella and Eligma narcissus)

affected ailanthus trees (in both woodlot and silvo-

pastoralism) and they suffered moderate to heavy

damage. As a result, tree growth was retarded

(Tables 2 and 3). The lower biomass yield observed

can be attributed to this reduced growth.

On per tree basis also, Acacia recorded the highest

biomass production. Mean biomass accumulation on

per tree basis ranged from 3.4 kg (Casuarina at 5 years

of age) to 84 kg (Acacia at 8.8 years of age; Table 2).

On the whole it followed similar trends as that of

biomass accumulation on unit area basis.

In a similar woodlot trial with ®ve tropical taxa in

Puerto Rico (two taxa being common with the present

trial), the highest above-ground biomass of

199 Mg haÿ1 was for 5.5 year-old Casuarina trees

(Wang et al., 1991). Acacia biomass estimated for the

present woodlot trial was close to this (comparison on

same age basis). Casuarina yields in the present study

were, however, much lower (96, 34 and 36 Mg haÿ1 at

8.8, 7 and 5 years of age; Table 1). Wittwer and

Stringer (1985) reported still inferior biomass values

(8.2±51.2 Mg haÿ1) for 5-year-old seedling stands of

®ve temperate hardwood species. Differences in age,

148 B.M. Kumar et al. / Forest Ecology and Management 112 (1998) 145±163

stocking, species, stage of stand development and site

generally account for such differences. In addition,

Sharma and Ambasht (1991) mentioned that varia-

tions in forest biomass productivity between sites are

probable, owing to differences in the length of grow-

ing season with negligible water de®cit, availability of

freshly weathered soils with moderately high base

saturation and cool nights and low respiration losses

during the growing and/or dormant season.

A noteworthy feature of the present results is the

tremendous productivity of Acacia in the woodlot

protocol. Converting biomass accumulation into an

annual basis yields MAI values (mean annual incre-

ment) between 2.6 and 37 Mg haÿ1 yearÿ1 (Table 1).

Lugo et al. (1988) found that above ground net

primary productivity for tropical species ranged from

16 to 29.8 Mg haÿ1 yearÿ1 of dry matter. We observed

that MAI was consistently highest for Acacia and

lowest for either Leucaena or Ailanthus. Further,

the above ground net primary productivity (NPP)

for all species except Acacia was lower than the

base-line ®gures for natural vegetation under the

corresponding climate of humid tropics with short

dry spells (23 Mg haÿ1 yearÿ1 of dry matter; Leith,

1976). Nonetheless Paraserianthes recorded a value

(21 Mg haÿ1 yearÿ1) close to the Leith's (Leith, 1976)

reported values for above-ground net primary produc-

tivity. All other species, regardless of whether indi-

genous or exotic, have fallen well below this range.

Factors such as intrinsic genetic variability of species

may explain the interspeci®c differences in biomass

productivity and MAI. The high biomass productivity

of Acacia observed in the present study can be attrib-

uted to its lower transpirational loss of water (Kallar-

ackal and Soman, 1992), wider adaptability and

nitrogen ®xing ability. Acacia also recorded the high-

est leaf area (Table 3) and foliar biomass compared

to other species (Tables 1 and 2), implying its higher

Table 1

Mean biomass accumulation (Mg haÿ1) in multipurpose trees of three age sequences in Kerala, India

Species/age Bole Branch Foliage Roots Total above-ground

Biomass MAI n

Wood lot (8.8 year of age)*Acacia auriculiformis 274.93a 42.55a 8.95a 17.73a 326.43a 37.09 31

Ailanthus triphysa 28.78bc 7.68b 4.08b 7.40a 40.54bc 4.61 30

Artocarpus heterophyllus 54.38bc 19.85b 7.78ab 10.13a 82.01b 9.32 32

Artocarpus hirsutus 32.15bc 14.83b 11.95d 11.15a 58.93bc 6.70 28*Casuarina equisetifolia 73.25b 16.63b 5.70b 5.60a 95.58b 10.86 26

Emblica officinalis 46.20bc 18.23b 4.43b 12.63a 68.86bc 7.83 17*Leucaena leucocephala 15.28c 6.25b 1.28c 3.23a 22.81c 2.59 18*Paraserianthes falcataria 141.18d 37.25a 5.05b 13.78a 183.48d 20.85 19

Pterocarpus marsupium 52.60bc 10.08b 3.43b 7.3a 66.11bc 7.51 30

Silvopasture (7 year of age)

Acacia auriculiformis 133.19a 31.17a 19.18a nd 183.54a 26.22 113

Ailanthus triphysa 15.79b 1.54b 2.05b nd 19.38b 2.77 120

Casuarina equisetifolia 27.21b 4.72b 1.75b nd 33.68b 4.81 86

Leucaena leucocephala 51.91b 10.49b 1.11b nd 63.51b 9.07 109

Silvopasture (5 year of age)

Acacia auriculiformis 111.8a 17.5a 11.1a 16.3a 140.5a 28.1 21

Ailanthus triphysa 16.8c 1.2b 1.8b 4.2a 19.8bc 3.96 20

Casuarina equisetifolia 28.2b 4.3b 3.4b 3.4a 35.9b 7.18 15

Leucaena leucocephala 51.7b 10.0c 4.1b 12.0a 65.8b 13.16 20

MAI: Mean annual increment (Mg haÿ1 yearÿ1).

Values followed by the same superscript do not differ significantly (age classes were analysed separately).* Exotics.

Nd: Not determined.

n: Number of trees sampled.

B.M. Kumar et al. / Forest Ecology and Management 112 (1998) 145±163 149

C-sequestration potential. Height and radial growth of

Acacia were also the highest (Table 3).

Tree management practices presumably exerted a

potent in¯uence on NPP. Planting geometry

(2 m�2 m in the woodlot vs. 49�1 m in the silvo-

pasture experiment), inter-cultivation, application of

chemical fertilisers, resultant soil fertility changes

(explained later) and/or lopping associated with the

cultivation of forage crops (see: Mathew et al., 1992;

George et al., 1996 for details George and Kumar,

1998) are the key determinants in this respect. Such

in¯uences are, however, species-dependent. For

instance, in the silvopastoral experiment, Leucaena

tallied the second highest biomass productivity,

although it recorded much lower values in the woodlot

routine. Acacia showing an MAI of

37 Mg haÿ1 yearÿ1 in the woodlot trial ®gured sub-

stantially lower values in the silvopastoral experiment.

Lopping branches to facilitate light in®ltration into the

understorey and/or possible interspeci®c competition

with the associated forage grasses especially during

the early stages of stand establishment may have

adversely affected Acacia growth and NPP. Fertilising

the associated understorey crop also did not change

the situation substantially in terms of Acacia growth.

Tree management practices, however, favoured

Leucaena growth and NPP (Tables 1±3).

A comparison of the biomass yield and MAI values

in respect of Ailanthus, Casuarina and Leucaena in

the silvopasture experiment at 7 years of age vs. 5

years of age (Tables 1 and 2) reveals moderately lower

values for the higher age class. Presumably growth and

productivity of these quick growing trees in the silvo-

pastoral system have plateaued out at about 5 years.

Table 2

Mean biomass accumulation (kg treeÿ1) in multipurpose trees of three age sequences in Kerala, India

Species/age Bole Branch Foliage Roots Total above

ground biomass

Grand total

Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD

Woodlot (8.8 year of age)*Acacia auriculiformis 109.97a 74.06 17.02a 16.50 3.58a 1.85 7.09a 3.54 130.57a 84.10 137.66a 85.49

Ailanthus triphysa 11.51bc 7.4 3.07b 2.91 1.63b 1.40 2.96a 0.28 16.21bc 10.92 19.17bc 11.07

Artocarpus heterophyllus 21.75bc 14.74 7.94b 7.75 3.11ab 2.54 4.05a 2.86 32.77b 23.20 36.82b 23.57

Artocarpus hirsutus 12.86bc 12.31 5.93b 6.33 4.78d 4.36 4.46a 1.04 23.57bc 21.91 28.03bc 22.32*Casuarina equisetifolia 29.30b 34.51 6.65b 10.35 2.28b 2.76 2.24a 0.64 38.23b 45.53 40.47b 46.43

Emblica officinalis 18.48bc 14.23 7.29b 8.15 1.77b 1.82 5.05a 5.80 27.54bc 22.93 32.59bc 23.63*Leucaena leucocephala 6.11c 5.14 2.50b 2.81 0.51c 0.37 1.29a 0.85 9.12c 8.03 10.41c 8.13*Paraserianthes falcataria 56.47d 44.65 14.90a 18.95 2.02b 1.44 5.51a 3.84 73.39d 61.18 78.90d 61.25

Pterocarpus marsupium 21.04bc 17.23 4.03b 4.85 1.37b 1.23 2.92a 2.91 26.44bc 22.12 29.36bc 22.50

Silvopasture (7 year of age)

Acacia auriculiformis 53.28a 32.36 12.47a 13.24 7.69a 3.18 Nd 73.42a 46.86 Ð

Ailanthus triphysa 6.32b 5.74 0.62b 0.55 0.82b 0.75 Nd 7.75b 6.54 Ð

Casuarina equisetifolia 10.89b 8.72 1.89b 1.89 0.70b 0.61 Nd 13.47b 10.82 Ð

Leucaena leucocephala 20.76b 19.33 4.20b 5.91 0.45b 0.57 Nd 25.40b 24.33 Ð

Silvopasture (5 year of age)

Acacia auriculiformis 44.70a 31.77 7.0a 5.28 4.43a 3.05 6.50a 8.3 56.13a 37.57 62.68a 38.5

Ailanthus triphysa 6.70c 4.22 0.46b 0.24 0.71b 0.49 1.69a 1.20 7.87bc 4.68 9.57bc 4.78

Casuarina equisetifolia 11.26b 0.03 1.71b 2.29 1.34b 1.19 1.34a 1.1 14.31b 3.29 15.65b 3.39

Leucaena leucocephala 20.67b 17.70 3.99c 3.46 1.62b 1.23 4.79a 6.2 26.28b 21.36 31.04b 21.35

MAI: Mean annual increment (Mg haÿ1 yearÿ1).

Values followed by the same superscript do not differ significantly (age classes were analysed separately).* Exotics.

Nd: Not determined.

SD: Standard deviation.

n, same as in Table 1.

150 B.M. Kumar et al. / Forest Ecology and Management 112 (1998) 145±163

Therefore, from the wood production point of view, it

is better to fell these trees when grown under similar

management systems, at about 5 years of age. How-

ever, caution should be exercised in extrapolating the

data to other sites and land management systems

involving these species, as site characteristics and/or

tree management practices can alter the pattern of

biomass accumulation.

Regarding component contribution to stand bio-

mass, clearly, the most important component of bio-

mass yield in all species is the bole. Bole accounted for

about 45% of the total biomass in A. hirsutus and 80%

in Acacia at 8.8 years of age. The corresponding

®gures for 7-year old stands are 73% in Acacia and

82% in Leucaena. In the 5-year old stand it varied

from 67% in Leucaena to 72% in Casuarina. Con-

tribution of branches ¯uctuated from 12.4% (Acacia)

to 24% (Leucaena) at 8.8 years, 8% (Ailanthus) to

17% (Leucaena) at 7 years and 5% (Ailanthus) to 13%

(Leucaena) at 5 years. Percentage contribution of

coarse roots was generally low (5.2±15.9% at 8.8

years and 9±17% at 5 years). Foliage invariably had

the least biomass yield (2±17%). Maghembe et al.

(1986) reported values ranging from 14.8% (foliage)

to 50.4% (bole) in Leucaena. Biomass allocation

pattern of different tree species showed considerable

variability in the present study. Stand age is another

cardinal determinant in this respect. Partitioning of dry

matter between different components namely, leaf,

reproductive parts, bole, branch wood and root is

probably important in agroforestry, as some of these

components are harvested periodically or at a stretch,

and some others are returned to the systems.

3.2. Tree allometry

Allometric relationships attempted in the present

study linking above ground tree biomass with DBH

and/or total height of the trees gave reasonably good

predictions. Table 4 contains the equations having

Table 3

Mean growth characteristics of the destructively sampled trees

Species/age Height (m) DBH (cm) Leaf aread (m2 treeÿ1)

Mean SD Mean SD Mean SD

Wood lot (8.8 year-old)

Acacia auriculiformis 17.84a 4.24 13.63a 4.26 99.63a 51.42

Ailanthus triphysa 5.00c 1.24 8.42b 2.89 30.90d 26.47

Artocarpus heterophyllus 8.73c 1.76 9.24b 3.70 63.94b 51.69

Artocarpus hirsutus 6.48c 1.90 8.12b 2.58 78.51b 71.66

Casuarina equisetifolia 12.13b 5.51 7.50b 3.47 45.87b 55.73

Emblica officinalis 7.38c 1.43 7.32b 2.63 43.23b 44.02

Leucaena leucocephala 6.30c 1.88 4.88b 1.52 17.75c 13.91

Paraserianthes falcataria 14.57ab 4.26 13.29a 5.16 59.44b 41.82

Pterocarpus marsupium 8.76c 2.97 8.85b 3.43 40.76b 36.91

Silvopasture (7 year-old)

Acacia auriculiformis 12.45a 2.54 11.64a 3.44 72.71a 50.33

Ailanthus triphysa 5.11c 1.83 6.68b 2.21 5.64b 5.05

Casuarina equisetifolia 9.43b 3.45 5.69bc 2.05 3.68b 3.25

Leucaena leucocephala 10.15b 2.76 7.66c 3.01 1.98b 2.70

Silvopasture (5 year-old)

Acacia auriculiformis 10.91a 6.08 9.28a 3.94 58.08a 32.2

Ailanthus triphysa 4.18c 0.93 5.64b 1.23 4.23b 2.60

Casuarina equisetifolia 8.24b 2.78 5.54b 2.10 0.19b 0.02

Leucaena leucocephala 9.05b 2.79 6.70b 3.02 7.08b 4.23

Values followed by the same superscript do not differ significantly (age classes were analysed separately).

SD: Standard deviation.

n, same as in Table 1.d Leaf area refers to one side area only.

B.M. Kumar et al. / Forest Ecology and Management 112 (1998) 145±163 151

Table 4

Allometric relationships linking oven dry above ground tree biomass (kg treeÿ1) with DBH (cm) and/or total tree height (H) in m for fast

growing multipurpose belonging to three age-series in Kerala, India (best fitting 3±4 equations per sepcies were selected based on r2 and

graphical examination of the residuals)

Species/age n Model# a b c d e f SEE R2

Wood lot (8.8 year-old)

Acacia auriculiformis

31 1 ÿ2.08235 0.839616 0.175 0.95

2 ÿ1.29248 2.305227 0.187 0.95

3 ÿ2.02754 1.726791 0.777652 0.178 0.95

4 47.01997 0.497737 ÿ9.57545

ÿ0.008992

008992 0.445589 ÿ0.00039 33.0 0.88

Ailanthus triphysa

30 1 ÿ1.522490 0.711523 0.332 0.79

3 ÿ1.66023 0.549792 1.946846 0.296 0.84

4 12.30338 0.455293 ÿ8.23808 ÿ0.13460 1.594640 0.010210 3.84 0.90

5 5.042591 0.025101 5.18 0.79

Artocarpus heterophyllus

32 1 ÿ2.90076 0.932870 0.353 0.92

2 ÿ1.71891 2.251298 0.363 0.91

3 ÿ2.72572 1.926456 0.791133 0.358 0.92

Artocarpus hirsutus

28 1 ÿ3.70899 1.068206 0.451 0.90

2 ÿ3.06934 2.793477 0.441 0.91

3 ÿ3.30879 2.576144 0.368640 0.445 0.91

4 ÿ9.69228 0.099484 2.708826 0.080171 ÿ0.23993 ÿ0.00618 6.55 0.93

Casuarina equisitifolia

26 1 ÿ2.69972 0.904278 0.146 0.99

2 ÿ2.26266 2.714223 0.142 0.99

3 ÿ2.49409 2.285804 0.438090 0.118 0.99

4 ÿ0.36550 0.032595 0.361268 0.042624 ÿ0.05887 ÿ0.00026 3.79 0.99

5 0.610691 0.033551 4.05 0.99

6 0 0.033773 4.00 0.99

Emblica officinalis

17 1 ÿ2.70511 0.969805 0.281 0.91

3 ÿ2.75315 1.917561 1.015588 0.291 0.91

4 15.37871 1.013115 ÿ8.35051 ÿ0.12287 0.812205 0.006643 6.99 0.94

5 1.415040 0.053909 6.46 0.93

6 0 0.055610 6.32 0.93

Leucaena leucocephala

18 1 ÿ3.70726 1.18746 0.320 0.92

3 ÿ3.64346 2.421473 0.925547 0.328 0.92

4 15.29280 ÿ1.25319 ÿ4.28088 0.387817 0.264011 ÿ0.02141 2.75 0.92

5 ÿ0.64396 0.052569 2.49 0.91

6 0 0.050398 2.45 0.91

Paraserianthes falcataria

19 1 ÿ3.76022 0.988626 0.180 0.98

2 ÿ2.92071 2.681800 0.179 0.98

3 ÿ3.33176 2.349211 0.472297 0.178 0.98

4 17.07716 0.295556 ÿ3.65340 0.025564 0.036064 ÿ0.00076 18.62 0.93

Pterocarpus marsupium

30 1 ÿ3.27136 0.955606 0.242 0.97

2 ÿ3.19198 2.828679 0.242 0.97

152 B.M. Kumar et al. / Forest Ecology and Management 112 (1998) 145±163

Table 4 (Continued )

Species/age n Model# a b c d e f SEE R2

3 ÿ3.24778 2.370139 0.485348 0.235 0.97

4 0.811538 ÿ0.44774 0.738908 0.120812 ÿ0.11031 ÿ0.00437 4.40 0.97

Silvopasture (7 year-old)

Acacia auriculiformis

113 1 ÿ1.83409 0.801471 0.445 0.71

3 ÿ2.36197 1.257008 1.344083 0.436 0.72

4 ÿ43.3570 ÿ0.67327 12.86643 0.095869 ÿ0.54247 ÿ0.00172 27.81 0.66

Ailanthus triphysa

120 1 ÿ1.79857 0.664972 0.417 0.76

2 ÿ2.16498 2.096065 0.326 0.85

3 ÿ2.19151 2.010111 0.119512 0.323 0.85

4 ÿ4.35547 0.410428 0.861704 ÿ0.08676 0.037309 0.006016 3.79 0.68

Casuarina equisetifolia

86 4 16.13236 ÿ0.63480 ÿ0.57654 0.169405 0.189591 ÿ0.00689 4.55 0.83

5 2.161506 0.028892 4.83 0.80

6 0 0.032087 4.99 0.79

Leucaena leucocephala

109 1 ÿ2.12777 0.800692 0.461 0.84

2 ÿ1.38435 2.157088 0.450 0.85

3 ÿ1.59567 2.018086 0.211554 0.450 0.85

Silvopasture (5 year-old)

Acacia auriculiformis

21 1 ÿ2.43061 0.916268 0.289 0.90

2 ÿ1.57926 2.436945 0.296 0.90

3 ÿ2.244 1.907 0.772 0.297 0.90

4 ÿ55.9908 7.716566 1.109856 ÿ1.16245 0.553252 0.048311 13.77 0.90

Ailanthus triphysa

20 2 ÿ7.895 2.623 2.508 0.67

4 ÿ97.5383 1.228182 46.72112 ÿ0.52595 ÿ5.38405 0.065601 2.88 0.69

5 2.228631 0.043332 2.87 0.61

Casuarina equisetifolia

15 3 ÿ2.943 0.837 1.794 0.368 0.92

4 ÿ0.92304 0.358393 0.528595 ÿ0.08138 ÿ0.03360 0.005182 1.45 0.89

5 ÿ0.57244 0.011877 1.66 0.79

6 0 0.010818 1.63 0.78

Leucaena leucocephala

20 3 ÿ4.236 1.014 2.318 0.342 0.95

4 ÿ2.73260 0.250769 1.100244 0.032018 ÿ0.11916 ÿ0.00033 5.12 0.96

5 1.239605 0.043575 4.70 0.96

6 0 0.044848 4.64 0.95

Generalised equations

Acacia auriculiformis

165 1 ÿ1.97414 0.827379 0.357 0.83

2 ÿ1.22540 2.221316 0.397 0.79

3 ÿ2.14951 1.438573 1.099639 0.355 0.83

4 ÿ33.7573 0.239033 7.126017 ÿ0.98841 ÿ0.10836 0.000597 27.44 0.80

Ailanthus triphysa

170 1 ÿ2.22227 0.775753 0.410 0.78

2 ÿ2.06622 2.120555 0.418 0.78

B.M. Kumar et al. / Forest Ecology and Management 112 (1998) 145±163 153

relatively high R2 and low propensity for bias. Bio-

mass equations were previously non-existent for

majority of the MPTs presently studied. However,

allometric equations for estimating biomass or volume

of other tropical fast growing trees have been devel-

oped elsewhere. Such species include Acacia man-

gium (Halenda, 1989), Eucalyptus saligna (Whitesell

et al., 1988; Dudley and Fownes, 1992), E. grandis,

E. robusta and E. urophylla (Schubert et al., 1988;

Dudley and Fownes, 1992), Leucaena leucocephala

(MacDicken and Brewbaker, 1988; Dudley and

Fownes, 1992), A. mearnsii and Casuarina equiseti-

folia (Dudley and Fownes, 1992).

Biomass estimation equations, generally vary with

species, age, bole shape and/or bole wood density.

Variations in these characteristics result from one or

more of the following causes, genetic differences

between populations, environmental variability

among sites, or crowding for trees that affect tree

shapes (Campbell et al., 1985). Therefore, biomass

regression equations, generalised for a geographic

region rather than a single age-class population, have

been developed to minimise errors in estimated bio-

mass that result from such variability in sampled trees

(Pastor et al., 1983/1984). Johnstone and Peterson

(1980), however, caution that such `regional' equa-

tions depict only the mean relationship in a region and

do not ensure that the equation is appropriate for a

speci®c population and that large over- and under-

estimates are likely.

In the present study we adopted a two-pronged

strategy for evolving biomass equations. To develop

species-speci®c equations for a speci®c age±class and

management regime and to evolve generalised bio-

mass equations that are independent of tree age,

location or management regime. The latter approach

was adopted for four species, for which data from

three age sequences were available. The data were

pooled (species-wise) and generalised equations

developed. However, as expected R2 values in respect

of the generalised equations were lower. For estimat-

ing tree and stand biomass, generalised equations for

the species and region can be used and if the popula-

tion is near the average for the region, according to

Campbell et al. (1985). Furthermore, these authors

suggested that in stands that differ from the regional

average, matching the characteristics of the trees to be

measured with those characteristics of trees for which

a ready-made regression is already available, would

provide more accurate predictions.

Table 4 (Continued )

Species/age n Model# a b c d e f SEE R2

3 ÿ2.21165 1.803968 0.469634 0.405 0.79

4 ÿ5.81961 0.165761 3.294793 ÿ1.08909 ÿ0.24001 0.000991 4.67 0.68

Casuarina equisetifolia

127 4 2.011005 0.311051 ÿ0.17876 ÿ1.23107 0.080123 0.000831 5.87 0.95

5 ÿ0.37767 0.032996 5.73 0.95

6 0 0.032752 5.72 0.95

Leucaena leucocephala

147 1 ÿ2.25737 0.827843 0.438 0.86

2 ÿ1.54321 2.247891 0.436 0.87

3 ÿ1.89270 1.984041 0.383154 0.432 0.87

4 26.51393 ÿ0.17273 ÿ10.7914 9.990701 0.028310 0.001193 13.45 0.67

Model 1: ln B�a�b ln (DBH2�H) (Campbell et al., 1985).

Model 2: ln B�a�b ln DBH (Campbell et al., 1985).

Model 3: ln B�a�b ln DBH�c ln H (Dudley and Fownes, 1992)

Model 4: B�a�bDBH2�cH�d (DBH2�H)�eH2�f(DBH2�H2) (Philip, 1994)

Model 5: B�a�b (DBH2�H) (Lavinge, 1982).

Model 6: B�b (DBH2�H) (Alemdag and Horton, 1981).

B: Above ground biomass, DBH:Diameter at breast height (cm), H�Total height (m).

n: Number of trees sampled (constant for a set).

SEE: Standard error of estimates.

154 B.M. Kumar et al. / Forest Ecology and Management 112 (1998) 145±163

Generalised equations developed in the present

study may have use for sites having similar eco-

climatic conditions. According to Pastor et al.

(1983/1984), there is justi®cation for using biomass

regressions developed elsewhere when regressions

cannot be developed on site. Further, if the age±class

of trees to be measured matches with that of the trees

for which a ready-made regression exists, then age±

class speci®c regressions could be more reliable.

Equations presented in Table 4 indicate that inclu-

sion of tree height in the models (models 1, 3, 4, 5 and

6; Table 4) generally improved predictability over the

diameter-based equation (model 2). This, however,

differs from the observations of Dudley and Fownes

(1992) that the time spent in ®eld measurements could

be greatly reduced by eliminating height measure-

ments in stands that are relatively homogenous.

3.3. Nutrient concentrations in tissue types and

removal at harvest

Nutrient removal at harvest from the site depends on

both nutrient concentration of different tissue fractions

and biomass yield. Nutrient concentrations were

found to vary markedly among the species, age classes

and tissue types studied (Table 5). In general, mineral

element concentration of tissue types decreased in the

order: foliage>branches�roots>bole. Although no

species has clearly higher or lower nutrient concen-

trations for all tissue types, generally N2 ®xing legu-

minous trees had markedly higher foliar N levels. For

instance, Leucaena registered the highest foliar N

concentration followed by Paraserianthes and Pter-

ocarpus. Surprisingly Casuarina, an actinorhizal tree

and Acacia, a mimosoid legume, showed relatively

lower foliar N concentrations in all age-series. Unlike

N, Leucaena recorded the lowest foliar P concentra-

tion. Pterocarpus and A. hirsutus recorded the two

highest foliar P levels. Foliar K concentration fol-

lowed an almost similar pattern as that of P. As tree age

increased, elemental concentrations in the bole gen-

erally declined. The observed variations in nutrient

concentrations are normally in the range of other

studies of these and similar species. Previously

reported values (Wang et al., 1991) of foliar N con-

centration for Leucaena (3.25%) and Casuarina

(1.56%) especially, were very close to that of the

present study, although site and soil conditions may

have a strong in¯uence on tissue nutrient concentra-

tions. Deviations in nutrient concentrations of tissue

fractions are, therefore, not extraordinary.

Owing to the wide variations in elemental concen-

trations among species and among tissue types, nutri-

ent accumulation did not follow a one-to-one

correspondence with biomass yield. The relative pro-

portion of nutrients tied up in various tissue fractions,

are signi®cantly different among the MPTs. Obviously

taxa with the highest nutrient concentrations did not

have the greatest nutrient accumulation rates. Age-

series and/or tree management practices also exerted a

profound in¯uence on this. Acacia had the highest N

accumulation (952 kg haÿ1 at 8.8 years; Table 6),

despite having relatively low levels of N in various

tissue fractions. It however, showed a dramatically

higher accumulation rate of 1539 kg N, 113 kg P and

623 kg K at 7 years of age and 998 kg N, 49 kg P and

478 kg K haÿ1 at 5 years of age, when grown in

association with forage grasses. Data presented in

Tables 1 and 2 show that the relative proportion of

Acacia foliage is highest at 7 years. Foliar nutrient

concentrations were obviously higher (Table 5).

Implicit in this is the role of tree management prac-

tices in deciding the relative proportion of different

tissue types in multipurpose trees. Differing nutrient

concentrations among types of harvested tissues

(leaves, stem etc.) and the high variability in the

relative abundance of tissue types in a species might

explain such diverse nutrient removal rates at harvest.

Nutrient accumulation and export from the site have

become an important consideration in short-rotation,

high-yield plantation systems (Hopman et al., 1993),

where nutrients removed through frequent harvests

may exceed the natural rates of nutrient inputs such as

mineral weathering, atmospheric inputs and biological

®xation. Heavy nutrient drain may have an adverse

impact on the long term site quality and sustained

production also. Small additional biomass yields are

usually accompanied by a many-fold increase in

nutrient removal (Wang et al., 1991). Needless to

mention that fast growing exotic trees such as Acacia

and Paraserianthes resulted in marked loss of nutri-

ents from the site especially when whole tree harvest-

ing is resorted to. As much as 46% of the total above

ground N, however, is tied up in Acacia bole wood,

another 30% in branches and 23% in the foliage at 8.8

years of age (Table 6). In Paraserianthes, about 53%

B.M. Kumar et al. / Forest Ecology and Management 112 (1998) 145±163 155

Table 5

Mean N, P and K concentration (%) of fast growing multi-purpose tree species in a three age sequence in Kerala, India

Species/age series Mineral nutrient element Biomass components

Bole Branch Root Foliage

Woodlot (8.8 year-old)

Acacia auriculiformis N 0.163 0.677 0.537 2.473

P 0.007 0.013 0.007 0.077

K 0.083 0.217 0.200 0.725

Ailanthus triphysa N 0.327 0.653 0.513 2.847

P 0.027 0.040 0.032 0.125

K 0.142 0.208 0.342 0.683

Artocarpus heterophyllus N 0.140 0.373 0.350 2.147

P 0.008 0.022 0.038 0.110

K 0.233 0.333 0.392 1.258

Artocarpus hirsutus N 0.210 0.233 0.467 1.727

P 0.013 0.068 0.057 0.132

K 0.283 0.875 0.583 1.683

Casuarina equisetifolia N 0.140 0.303 0.280 1.587

P 0.005 0.012 0.012 0.067

K 0.050 0.075 0.580 0.458

Emblica officinalis N 0.187 0.233 0.210 2.403

P 0.017 0.020 0.042 0.128

K 0.208 0.383 0.233 0.817

Leucaena leucocephala N 0.233 0.350 0.513 4.737

P 0.013 0.015 0.018 0.060

K 0.100 0.208 0.158 0.408

Paraserianthes falcataria N 0.233 0.373 0.233 3.057

P 0.005 0.012 0.007 0.092

K 0.117 0.192 0.083 0.858

Pterocarpus marsupium N 0.280 0.583 0.350 2.893

P 0.005 0.017 0.017 0.138

K 0.233 0.458 0.500 2.433

Nitrogen p <0.01 <0.01 <0.01 <0.01

SEM (�) 0.018 0.026 0.018 0.037

LSD (0.05) 0.054 0.077 0.054 0.109

Phosphorus p <0.01 <0.01 <0.01 <0.01

SEM (�) 0.001 0.002 0.007 0.003

LSD (0.05) 0.004 0.005 0.021 0.008

Potassium p <0.01 <0.01 <0.01 <0.01

SEM (�) 0.009 0.009 0.010 0.011

LSD (0.05) 0.026 0.026 0.029 0.031

Silvopasture (7 year-old)

Acacia auriculiformis N 0.572 0.849 nd 2.722

P 0.058 0.052 nd 0.114

K 0.175 0.311 nd 1.363

Ailanthus triphysa N 0.775 1.017 nd 2.845

P 0.109 0.142 nd 0.166

K 0.586 0.851 nd 1.215

Casuarina equisitifolia N 0.426 0.551 nd 2.254

P 0.014 0.028 nd 0.095

K 0.161 0.176 nd 0.891

Leucaena leucocephala N 0.597 0.784 nd 4.009

P 0.076 0.116 nd 0.189

K 0.223 0.404 nd 1.092

156 B.M. Kumar et al. / Forest Ecology and Management 112 (1998) 145±163

of N is tied up in the bole fraction. Therefore, during

the harvest operation, if the branches and bole alone

are removed, leaving the foliage and roots at the site,

nutrient export from the site could be substantially

reduced.

3.4. Nutrient use efficiency

Sustainable production without adversely affecting

site quality is a key design criteria in all short rotation

intensive cultural systems. Such systems are, however,

characterised by frequent removal of parts in pruning,

lopping etc. or whole tree harvest, which in turn, may

have the potential for high nutrient depletion.

Repeated biomass harvests also lead to high rates of

nutrient export from the site. In this context, nutrient

use ef®ciency (biomass to nutrient ratio) provides a

good measure to evaluate large differences in nutrient

`costs' of biomass production (Wang et al., 1991).

Species selection that considers nutrient use ef®-

ciency, therefore, is a potential tool available to the

forester to alter the `nutrient costs' associated with

such systems. They further suggested that a `better'

tree should (a) achieve rapid growth, (b) remove few

nutrients from site at each rotation and (c) be better

suited to poor sites where growth may be limited by

Table 5 (Continued )

Species/age series Mineral nutrient element Biomass components

Bole Branch Root Foliage

Nitrogen p 0.05 <0.01 ± <0.01

SEM (�) 0.027 0.05 ± 0.13

LSD (0.05) 0.079 0.167 ± 0.46

Phosphorus p <0.05 <0.01 ± <0.01

SEM (�) 0.018 0.010 ± 0.007

LSD 0.063 0.036 ± 0.025

Potassium p <0.01 <NS ± NS

SEM (�) 0.066 0.106 ± 0.017

LSD 0.228 ± ± ±

Silvopasture (5 year-old)

Acacia auriculiformis N 0.518 0.931 1.143 2.319

P 0.031 0.035 0.045 0.081

K 0.264 0.384 0.253 1.082

Ailanthus triphysa N 0.338 0.505 0.549 2.760

P 0.076 0.125 0.110 0.123

K 0.162 0.376 0.163 0.477

Casuarina equisitifolia N 0.441 0.764 1.288 1.866

P 0.043 0.123 0.108 0.153

K 0.053 0.119 0.128 0.470

Leucaena leucocephala N 0.594 1.139 0.592 4.051

P 0.057 0.086 0.085 0.171

K 0.134 0.348 0.178 1.392

Nitrogen p <0.05 <0.01 <0.01 <0.01

SEM (�) 0.02 0.04 0.10 0.22

LSD (0.05) 0.134 0.067 0.334 0.734

Phosphorus p N.S. <0.01 <0.01 <0.01

SEM (�) 0.01 0.01 0.01 0.01

LSD 0.033 0.033 0.033 0.033

Potassium p <0.01 <0.05 <0.01 <0.01

SEM (�) 0.03 0.06 0.04 0.07

LSD 0.100 0.200 0.134 0.234

Nd: Not determined.

Number of samples per category (n)�3.

B.M. Kumar et al. / Forest Ecology and Management 112 (1998) 145±163 157

Tab

le6

N,

Pan

dK

accu

mu

lati

on

(kg

haÿ

1)

inan

age

sequen

ceof

mult

ipurp

ose

tree

sin

Ker

ala,

India

Sp

ecie

s/ag

eB

ole

wo

od

Foli

age

Bra

nch

wood

Root

Tota

lab

ove

gro

und

NP

KN

PK

NP

KN

PK

NP

K

Wo

od

lot

(8.8

yea

r-old

)

Aca

cia

au

ricu

lifo

rmis

44

3.1

18

.3229.1

221.4

6.8

864.9

287.9

5.7

592.2

95.1

1.1

835.5

958.3

30.9

386.2

Ail

anth

us

trip

hys

a9

4.0

7.7

40.8

116.0

5.1

27.9

50.2

3.0

816.0

38.0

2.3

524.3

260.2

15.8

84.6

Art

oca

rpu

sh

eter

op

hyl

lus

76

.14

.5126.9

166.9

7.7

897.8

74.1

4.3

069.9

35.4

3.8

839.7

317.2

16.6

290.9

Art

oca

rpu

sh

irsu

tus

67

.52

4.3

91.3

206.3

15.7

3201.2

34.6

10.1

3129.7

52.0

6.3

365.1

308.5

30.2

422.0

Casu

ari

na

equ

iset

ifo

lia

10

2.6

3.7

36.6

90.5

3.8

26.1

50.4

1.9

512.5

15.7

0.6

53.3

243.4

9.4

75.2

Em

bli

cao

ffic

ina

lis

56

.37

.796.3

106.4

5.6

836.2

42.5

5.1

869.9

26.5

5.2

529.5

235.1

18.6

152.3

Leu

caen

ale

uco

cep

ha

la3

5.7

2.0

15.3

60.4

0.7

85.2

21.9

0.9

513.0

16.6

0.6

05.1

117.7

2.7

33.5

Pa

rase

ria

nth

esfa

lca

tari

a3

29

.47

.1164.7

154.4

4.6

343.3

139.1

4.3

571.4

32.2

0.7

511.5

622.8

16.2

279.5

Pte

roca

rpu

sm

ars

upiu

m1

47

.32

.6122.7

94.1

4.7

583.4

58.8

1.6

846.2

25.6

1.2

336.6

305.2

9.1

252.3

p<

0.0

1<

0.0

1<

0.0

1<

0.0

1<

0.0

1<

0.0

1<

0.0

1<

0.0

1<

0.0

1<

0.0

1<

0.0

1<

0.0

1<

0.0

1<

0.0

1<

0.0

1

SE

M(�

)2

4.4

41

.60

9.1

41.8

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158 B.M. Kumar et al. / Forest Ecology and Management 112 (1998) 145±163

the rate at which nutrients are made available. Within a

species, a further alteration in nutrient rates at harvest

can be achieved by adjusting the types of tissues

removed from the site.

Variations in nutrient use ef®ciency of the MPTs

studied (Table 7) did not follow a consistent pattern

for all nutrients. Cultural systems and/or stand age

were also found to in¯uence this parameter. Fertilisa-

tion and inter-cultivation generally depressed nutrient

use ef®ciency. Casuarina was, however, the most

ef®cient MPT for N at 8.8 years and Ailanthus, the

least. Most ef®cient species for P and K were Para-

serianthes and Casuarina, respectively. A. hirsutus

was the least ef®cient in respect of both these nutri-

ents. According to Wang et al. (1991), since the

amount of symbiotically ®xed N and soil N pool

are not partitioned, it is dif®cult to make species

selection solely based in N use ef®ciency. If P and

K use ef®ciency are used as the criteria, Acacia,

Casuarina and Paraserianthes (at 8.8 years) are better

options. However, when nutrient use ef®ciency and

biomass production are simultaneously considered,

Casuarina clearly emerges as the ideal choice for

short rotation agroforestry systems at this site (rela-

tively higher ef®ciency for all major nutrients and

biomass production next was only to Acacia and

Paraserianthes).

No clear pattern of N accumulation by leguminous

and non-leguminous trees was discernible in the pre-

sent study, except that the N use for leguminous

foliage was higher than that of non-legumes. Wang

et al. (1991) observed that such a comparison among

species for N use ef®ciency may not be completely

meaningful as symbiotic N ®xing might have involved

in deciding the N to biomass ratio.

3.5. Soil properties under MPTS

Trees in managed land use systems frequently cause

favourable changes in soil physico-chemical proper-

ties. In the present study, treeless plots (Table 8;

silvopasture) showed consistently lower values for

all soil parameters evaluated. According to Mac-

Dicken and Vergara (1990), micro-site enrichment

through improvement in the soil organic matter and

mineral nutrient pools form an important attribute of

woody perennials. Furthermore, marked variations

between MPTs in the soil chemical properties have

been noticed, implying their differential potential for

site improvement. Species differences in soil organic

C, N, P and K levels were statistically signi®cant

(Table 8). Leucaena and Acacia recorded the highest

organic C levels in the woodlot and silvopastoral

experiments respectively. Soil N also followed a simi-

lar trend, except in the 5-year age series. Nitrogen

®xing species, in general, logged more soil N, pre-

sumably due to litter dynamics (see: Jamaludheen and

Kumar, 1998) and/or biological N ®xing ability.

Such effects were, however, more pronounced in

the tree±grass systems (Table 8). The high organic

mater and nitrogen status of soil under 5- and 7-year-

old silvopastoralism is similar to what is documented

in the literature (Skerman and Riveros, 1990). Soil pH

was modestly higher in `tree plots'. No consistent

pattern, however, was discernible with respect to

species differences in soil pH. Available P levels were

the highest in the Casuarina plots while available K

was highest in A. inleucainebic plots. Although fast

growing trees in general remove large quantities of

nutrients at harvest, woody perennials may enrich

soils through nutrient cycling, nutrient pumping and

so on. Detailed and long term studies are perhaps

necessary to characterise such changes in soil proper-

ties on account of MPT growth. The present results in

this respect are only indicative.

4. Conclusions

Although many of our ®ndings are site-speci®c, we

feel that the concepts considered have general applic-

ability to the management of tropical plantation forest

ecosystems. In planning sustainable short-rotation,

intensive cultural systems, biomass productivity

and/or site nutrient removal must be considered. Tro-

pical MPTs show considerable variability in this

respect. In our experiments, total biomass accumula-

tion decreased in the order Acacia>Paraserianthes>-

Casuarina>A. heterophyllus>Emblica>Pterocar-

pus>A. hirsutus>Ailanthus>Leucaena. Assuming

that a given quantity of biomass of any species has

equivalent utilisation values, Acacia and Paraser-

ianthes (having an MAI>20 Mg haÿ1 yearÿ1) are pre-

ferred species on this site. However, in the

silvopastoral experiment Leucaena recorded higher

productivity, presumably due to fertilisation and other

B.M. Kumar et al. / Forest Ecology and Management 112 (1998) 145±163 159

Table 7

Nutrient use efficiency of multipurpose tree species grown under three age-series in Kerala, India

Species/age Bole Branch Foliage Roots Total

N use efficiency (Mg biomass/kg of N)

Woodlot (8.8 year of age)

Acacia auriculiformis 0.6205 0.1478 0.0404 0.1864 0.3592

Ailanthus triphysa 0.3062 0.1530 0.0352 0.1947 0.1841

Artocarpus heterophyllus 0.7146 0.2679 0.0466 0.2862 0.2904

Artocarpus hirsutus 0.4762 0.4286 0.0579 0.2144 0.2271

Casuarina equisetifolia 0.7139 0.3300 0.0630 0.3567 0.4157

Emblica officinalis 0.8206 0.4289 0.0416 0.4766 0.3466

Leucaena leucocephala 0.4280 0.2854 0.0212 0.1946 0.2212

Paraserianthes falcataria 0.4286 0.2678 0.0327 0.4280 0.3167

Pterocarpus marsupium 0.3571 0.1714 0.0365 0.2852 0.2405

Silvopasture (7 year of age)

Acacia auriculiformis 0.1754 0.1221 0.0366 Nd 0.1193

Ailanthus triphysa 0.1356 0.0985 0.0361 Nd 0.1026

Casuarina equisetifolia 0.2341 0.1815 0.0450 Nd 0.1859

Leucaena leucocephala 0.1689 0.1286 0.0245 Nd 0.1463

Silvopasture (5 year of age)

Acacia auriculiformis 0.1936 0.1072 0.0432 0.0880 0.1408

Ailanthus triphysa 0.2979 0.2069 0.0367 0.1803 0.1772

Casuarina equisetifolia 0.2276 0.1311 0.0543 0.0787 0.1633

Leucaena leucocephala 0.1686 0.0882 0.0250 0.1688 0.1123

P use efficiency (Mg biomass/kg of P)

Woodlot (8.8 year of age)

Acacia auriculiformis 15.023 7.400 1.301 15.025 1.139

Ailanthus triphysa 3.738 2.494 0.800 3.149 3.032

Artocarpus heterophyllus 12.084 4.616 1.000 2.611 5.550

Artocarpus hirsutus 7.477 1.464 0.760 1.761 2.320

Casuarina equisetifolia 19.797 8.528 1.500 8.615 10.764

Emblica officinalis 6.000 3.519 0.780 2.406 4.381

Leucaena leucocephala 7.640 6.579 1.661 5.383 9.641

Paraserianthes falcataria 19.885 8.563 1.091 18.373 12.175

Pterocarpus marsupium 20.231 6.000 0.722 5.935 8.066

Silvopasture (7 year of age)

Acacia auriculiformis 1.774 2.011 0.870 Nd 1.692

Ailanthus triphysa 0.991 0.691 0.621 Nd 0.904

Casuarina equisetifolia 7.068 3.631 1.074 Nd 4.968

Leucaena leucocephala 1.451 0.867 0.521 Nd 1.270

Silvopasture (5 year of age)

Acacia auriculiformis 3.337 2.500 1.247 2.296 2.844

Ailanthus triphysa 1.254 0.800 0.857 0.894 1.159

Casuarina equisetifolia 2.496 0.843 0.680 0.944 1.673

Leucaena leucocephala 1.668 1.205 0.594 1.200 1.420

K use efficiency (Mg biomass/kg of K)

Woodlot (8.8 year of age)

Acacia auriculiformis 1.200 0.461 0.138 0.499 0.891

Ailanthus triphysa 0.705 0.480 0.146 0.305 0.566

Artocarpus heterophyllus 0.429 0.284 0.080 0.255 0.317

Artocarpus hirsutus 0.352 0.114 0.059 0.171 0.166

Casuarina equisetifolia 2.001 1.330 0.218 1.697 1.345

Emblica officinalis 0.480 0.261 0.122 0.428 0.535

160 B.M. Kumar et al. / Forest Ecology and Management 112 (1998) 145±163

Table 7 (Continued )

Species/age Bole Branch Foliage Roots Total

Leucaena leucocephala 0.999 0.481 0.246 0.633 0.777

Paraserianthes falcataria 0.857 0.522 0.117 1.198 0.706

Pterocarpus marsupium 0.429 0.218 0.041 0.199 0.291

Silvopasture (7 year of age)

Acacia auriculiformis 0.532 0.311 0.070 Nd 0.295

Ailanthus triphysa 0.156 0.108 0.079 Nd 0.137

Casuarina equisetifolia 0.634 0.584 0.120 Nd 0.513

Leucaena leucocephala 0.460 0.250 0.096 Nd 0.382

Silvopasture (5 year of age)

Acacia auriculiformis 0.382 0.258 0.093 0.118 0.294

Ailanthus triphysa 0.627 0.273 0.214 0.609 0.496

Casuarina equisetifolia 1.679 0.860 0.214 0.791 0.952

Leucaena leucocephala 0.732 0.289 0.073 0.556 0.406

Nd: Not determined.

Table 8

Mean soil chemical properties (0±15 cm soil layer; n�4) in an age sequence of multi-purpose trees in Kerala, India

Species/stand age OC (%) N (%) P (mg lÿ1) K (mg lÿ1) pH

Woodlot (8.8 year-old)

Acacia auriculiformis 1.677 0.154 11.07 53.08 6.7

Ailanthus triphysa 1.526 0.117 9.93 23.83 6.7

Artocarpus hirsutus 1.400 0.103 8.67 45.93 6.7

Artocarpus heterophyllus 1.412 0.093 9.33 23.83 6.7

Casuarina equisetifolia 1.148 0.112 12.93 23.83 6.8

Emblica officinalis 1.463 0.117 12.73 19.07 6.7

Leucaena leucocephala 1.866 0.168 8.07 21.45 6.7

Paraseriathes falcataria 1.387 0.126 10.47 48.32 6.6

Pterocarpus marsupium 1.337 0.121 12.00 19.07 6.6

p <0.01 <0.01 <0.01 <0.01 NS

SEM (�) 0.006 0.007 0.855 4.700 0.055

LSD (0.05) 0.018 0.022 2.540 13.962 ±

Silvopasture (7 year-old)

Acacia auriculiformis 4.512 0.293 23.92 65.42 4.7

Ailanthus triphysa 3.784 0.252 19.81 62.50 4.8

Casuarina equisetifolia 3.654 0.277 24.33 58.54 4.7

Leucaena leucocephala 3.961 0.273 22.10 75.00 4.9

Tree-less control 3.279 0.237 10.08 53.13 4.6

p <0.01 <0.01 <0.01 <0.01 <0.01

SEM (�) 0.152 0.008 2.440 3.230 0.037

LSD (0.05) 0.435 0.022 6.985 9.248 0.105

Silvopasture (5 year-old)

Acacia auriculiformis 4.226 0.224 16.93 68.43 4.9

Ailanthus triphysa 2.097 0.190 13.69 47.40 5.1

Casuarina equisetifolia 3.062 0.212 20.04 57.33 5.2

Leucaena leucocephala 3.447 0.262 17.31 59.80 5.1

Tree-less control 1.956 0.154 11.25 36.66 5.1

p <0.01 <0.01 <0.01 <0.01 <0.01

SEM (�) 0.096 0.014 0.894 1.924 0.028

LSD (0.05) 0.274 0.039 1.803 3.882 0.079

B.M. Kumar et al. / Forest Ecology and Management 112 (1998) 145±163 161

tree management practices adopted therein. Tree bio-

mass productivity and nutrient export from the site are

strongly in¯uenced by species, stand age and the tree

management practices adopted. Bole fraction, in gen-

eral accounted for about 50% of the total nutrient

export. A slight reduction in the tree parts removed

from the site would de®nitely alter the rate of nutrient

export. Therefore, returning leaves and small twigs to

the site at the time of harvest may be a worthwhile

option to restrain nutrient export from the site.

Acknowledgements

Authors are grateful to the Associate Dean, College

of Forestry, Kerala Agricultural University, Vellanik-

kara, the Assistant Director General (Agroforestry),

Indian Council of Agricultural Research, New Delhi

and the Professor, Livestock Research Station, Thir-

uvazhamkunnu for the facilities provided. Dr. N.K.

Sasidharan, Dr. K.V. Suresh Babu, Mr. Thomas

Mathew and Mr. K. Umamaheshwaran, who were

involved in the early maintenance of the trial plots

are also gratefully acknowledged. Mr. K.K. Varghese

helped in data compilation. Dr. James Raich of Iowa

State University provided useful comments on a pre-

vious version of the manuscript which was presented

at the Seminar on `The Ecology of Moist forests in

southern India', organised by the USEFI at Madurai

Kamaraj University, Madurai, TN, India from 23 to 26

April, 1997.

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