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BIOTROPIA Vol. 27 No. 2, 2020: 104 - 114 DOI: 10.11598/btb.2020.27.2.1172

SITE INDICATOR SPECIES FOR PREDICTING THE
PRODUCTIVITY OF TEAK PLANTATIONS IN PHRAE

PROVINCE, THAILAND**

NARINTHORN JUMWONG1, CHONGRAIN WACHRINRAT2*, SARAWOOD SUNGKAEW3

AND ATCHARA TEERAWATANANON4

1Faculty of Forestry, Kasetsart University, Bangkok 10900, Thailand
2Department of Silviculture, Faculty of Forestry, Kasetsart University, Bangkok 10900, Thailand

department of Forest Biology, Faculty of Forestry, Kasetsart University, Bangkok 10900, Thailand
4Natural History Museum, Pathum Thani 12120, Thailand

Received 17 December 2018 / Accepted 25 April 2019

ABSTRACT

Site quality assessment is critically important in any tree planting activity as it may serve a range of
management functions such as, optimizing productivity estimates of forest plantations. This study aimed to
evaluate the site quality, using plant indicators species, for three teak plantations located in Northern Thailand
belonging to the Forest Industry Organization (FIO). Twenty-four sample plots were chosen to cover all the
growth classes within the age range of 6-39 years. The site index of teak was established by using the anamorphic
technique which is based on dominant height and age at a base age of 30 years, divided into 3 site index classes as
24, 21, and 18, as good, moderate, and poor site quality, respectively. Associated species, the native species that
are tree and shrub habits, were surveyed in the 24 plots and indicator species were classified using the Indicator
Species Analysis (ISA) and Two Way Indicator Species Analysis (TWINSPAN). The relationship between
indicator species and environmental factors was analyzed by the Generalized Linear Model (GLM). The
associated species was classified into 76 species with 21 families. The results of ISA indicated the significant
indicator species under the good site class were Strehlus ilicifolius, Tagerstroemia floribunda, Dalbergia cana and
Tagerstroemia calyculata\ while Schleichera oleosa and Dalbergia nigrescens were presented under poor site class,
respectively. The results from TWINSPAN supported Streblus ilicifolius, Tagerstroemia floribunda and Schleichera oleosa
were obvious indicators. Each indicator species distribution influenced by various relationships with
environmental factors, which soil pH and N were the main factors to distribute all indicator species to 3
relationships. First, the indicator species positively associated with soil pH and negatively associated with N were
Streblus ilicifolius and Dalbergia nigrescens. Second, the indicator species positively associated with soil pH and N
were Tagerstroemia floribunda and Schileichera oleosa. Third, the indicator species negatively associated with soil pH
and positively associated N were Dalbergia cana and Tagerstroemia calyculata. The GLM analysis revealed P, Ca and
elevation influenced indicator species distribution. As of writing, this is the first study on species indicators for
suitable sites of teak in Thailand. Meanwhile, in the absence of confirmatory studies, these indicators can be used
as guide for farmers interested in planting teak. In bare lands, the farmer can apply these indicator species to
determine the site quality based on the species’ past appearance.

Keywords: productivity, site indicator species, site quality, Teak plantation, Thailand

INTRODUCTION

Teak (Tectona grandis L.f.) plantations were
established 112 years ago by the Royal Forest
Department (RFD) and more than 50 years ago
““ Corresponding author, e-mail: fforcrw@ku.ac.th
**This paper was presented at the 3rd International
Conference on Tropical Biology 2018, 20-21 September
2018, Bogor, West Java, Indonesia

by the Forest Industry Organization (FIO) in
order to replenish the timber resources in
Thailand (Kijkar 2000). Initially, the teak
plantations were grown naturally in the natural
forest, especially in the northern part of
Thailand; however, with technology
improvements, these plantations were expanded
externally (Thueksathit 2006).

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Site indicator species for predicting the productivity of Teak plantations in Thailand — Jumwong et al

Since timber yield strongly depends on forest
site quality, determination of site quality is one
primary step in the intensive management of
forest land (Davis 1987; Skovsgaard & Vanclay
2008). Based on site and yield information, a
forest manager can estimate the future wood
supplies and make realistic decisions about
future costs and benefits of intensive
management, land acquisition and industrial
investment (Carmean 1977; Clutter et al. 1983).

For over 50 years, Thailand has performed
site quality assessments using the site index (SI)
(Boonthawee 1968; Chanpaisang 1977; Papata
2001; Prempanichnukul 2001; Srisuksai 2001). It
is determined using a direct method defining the
actual growth as an average of the heights of the
dominant and co-dominant trees at a given base
age in a single-species and evenly-aged stand
(Ford-Robertson 1971). The same site can
produce different site indices, as may be
influenced by the environmental factors.
However, the indirect or soil-site measurement
uses the soil, topography and climatic factors in
an area to correlate with the site index, growth,
or yield, estimated from the trees in each plot
(Sahunalu 1970; Srisuksai 2001).

Site quality assessments of Teak plantations
are based both on site index and soil survey
methods. The site index method, however,
needs records of teak growth in each site. It is
difficult to evaluate the site quality and
productivity of teak sites that lack teak growth
record and of those newly established teak
plantations. As tree heights and many other site
properties are difficult to measure, the plant
indicator species is determined based on the
measurement of indicative variables such as the
appearance or composition of ground vegetation
(Vanclay 1992). This study attempts to develop a
practical site productivity indicator by using
plant indicator species to evaluate the site quality
and describe the effects of all environmental
factors.

MATERIALS AND METHODS

Studied Sites and Sampling Plots

The study was conducted in year 2013 on
those teak plantations which apply similar
management techniques and are maintained by

the Forest Industry Organization (FIO) in the
Phrae Province, Northern Thailand. The planted
areas in all plantations were divided according to
the year of planting. The three plantations
selected from a total of 12 teak plantations
managed by FIO, included the Wang Chin
(WC), Khun Mae Kham Mee (KM) and Mae Sa-

Roy (MS) plantations (Fig. 1). These plantations
covered a wide range of growth rates, tree age
sizes, age classes and were classified as 6-10, 11-

15, 16-20, 21-25, 26-30 and > 30-years old
(Table 1). The elevation of the study areas
ranged from 100-700 m above the mean sea
level. The topography varied among sites with
undulating area from flat to hilly. The soil
texture is either sandy clay loam or clay type
derived from a parent rock consisting of
limestone (Table 2).

Using a dominant height growth covering 5
site index classes, 24 temporary sample plots
were randomly established in the selected study
sites managed by the Forestry Research Center
in 1997 (Forestry Research Center 1997) and
distributed into 6 age classes. All plots were
studied for their soil properties during the year
2000 (Sakurai et al. 2002).

Data Collection

Data were collected during the rainy season
(August-November 2013), in which the highest
density of associated species was observed.
Twenty-four temporary sample plots of 40 x 40
m were established and then divided into sub¬

plots of 10 x 10 m where bamboos were
measured. Inside the plots, the heights of 16
dominant and co-dominant trees were measured
using a haga altimeter. The diameters at breast
height (DBH) of all the trees were measured by
a diameter tape. Five subplots of 4 x 4 m were
set up for saplings observation at the corners
and in the middle of the 40 x 40 sample plot
(Fig. 2). The frequency and density of each
species’ sapling plant was also estimated.

Site Index Analysis
The site index for teak was determined using the
anamorphic site index method (Prasomsin
1991). The method defines an average height for
a given age, which is commonly taken as 30
years for teak rotation. The tree selection was
done based on the dominant height, as this

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BIOTROPIA Vol. 27 No. 2, 2020

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1N

A
ru i i I KM
0 5 10 15 20

r :
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A

1Legend

i* Plantation

District boundary

| Phrac Province

Province boundary 1:650,000
540000 560000 580000 600000 620000 640000 660000 -

Figure 1 Location of the three study areas, Khun Mae Kham Mee (KM) plantation, Wang Chin (WC) plantation and
Mae Sa-Roy (MS) plantation as indicated by circles

Table 1 Age classes of Teaks in the twenty-four sample plots selected from Khun Mae Kham Mee (KM), Wang Chin
(WC) and Mae Sa-Roy (MS) plantations

Age class
(y r)

Site indexa
Total8 11 14 17 20

6-10 i (i) i (i) 2 (2) 4 (4)
11-15 i (i ) i (i) 2 (2)
16-20 1 (1) 1 (1)
21-25 2 (2) 1 (2) 2 (2) 5 (6)
26-30 i (i) 3 (5) 3 (4) 7 (10)
> 30 0 (3) 2 (8) 2 (5) 1 (4) 5 (20)

Total i (i ) 5 (10) 7 (14) 5 (9) 6 (9) 24 (43)
Notes: a as reported by the Forestry Research Center (1997); the highlighted numbers indicate the sample plots and the

number in brackets are the existing plots.

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Site indicator species for predicting the productivity of Teak plantations in Thailand — Jumwong et al.

Table 2 The environmental conditions (topography and soil properties at 0 and 20 cm soil depth) at the 24 sample plots
from Khun Mae Kham Mee plantation (KM), Mae Saroy plantation (MS) and Wang Chin plantation (WC)

Topography Soil Soil properties
No Plot Slope

(%)
Elevation

(m)
depth
(cm) pH N

(%)
P

(mg P/kg)
Ca K Mg

— cmol(+)/kg
Na

1 KM75 50 498.20 0 5.24 1.10 3.86 4.99 0.21 1.04 0.30
20 5.66 2.20 2.28 7.56 0.26 3.33 0.23

2 KM81 20 348.00 0 6.04 1.20 3.37 9.99 0.21 1.90 0.26
20 5.79 1.00 1.07 9.03 0.10 1.43 0.28

3 KM85 45 550.00 0 6.11 1.70 18.86 7.00 0.34 1.29 0.27
20 5.89 1.10 1.48 4.27 0.14 1.03 0.28

4 KM83 0 432.30 0 6.53 2.10 12.47 14.85 0.41 3.27 0.32
20 6.21 1.40 0.73 10.64 0.14 2.31 0.35

5 KM78 35 426.10 0 6.08 2.20 2.84 13.64 0.28 4.82 0.35
20 5.59 1.60 0.85 6.72 0.11 3.73 0.25

6 KM05 0 441.00 0 5.93 1.80 4.28 9.07 0.37 3.55 0.11
20 5.51 1.20 0.79 4.92 0.13 2.86 0.32

7 KM02 0 432.30 0 5.93 1.80 4.28 9.07 0.37 3.55 0.11
20 5.51 1.20 0.79 4.92 0.13 2.86 0.32

8 KM04 5 453.70 0 5.93 1.80 3.55 9.38 0.30 4.23 0.32
20 5.60 0.60 0.70 6.36 0.13 2.58 0.29

9 KM01 10 458.20 0 5.93 1.80 3.55 9.38 0.30 4.23 0.32
20 5.60 0.60 0.70 6.36 0.13 2.58 0.29

10 MS87 5 164.00 0 5.89 1.50 7.25 5.20 0.31 3.18 0.21
20 5.44 0.90 1.70 2.87 0.08 2.11 0.28

11 MS83 2 136.20 0 5.22 1.30 3.58 2.13 0.21 1.46 0.27
20 4.91 1.00 1.04 1.20 0.12 0.62 0.29

12 MS80 5 147.40 0 5.39 1.20 3.07 3.54 0.19 1.79 0.28
20 5.36 0.80 1.80 1.87 0.11 2.39 0.32

13 MS86 35 175.80 0 5.93 1.80 7.54 8.08 0.44 2.21 0.30
20 5.06 1.90 1.56 4.85 0.25 1.56 0.29

14 MS82 20 185.30 0 5.69 1.10 2.33 2.99 0.20 2.13 0.26
20 5.23 0.90 1.97 1.77 0.22 0.80 0.29

15 MS84 30 135.70 0 5.90 1.10 13.29 3.88 0.21 1.72 0.23
20 5.24 0.80 1.64 1.90 0.14 1.00 0.32

16 WC06 2 142.60 0 5.39 1.20 3.07 3.54 0.19 1.79 0.28
20 5.36 0.80 1.80 1.87 0.11 2.39 0.32

17 WC83 30 125.90 0 5.22 1.30 3.58 2.13 0.21 1.46 0.27
20 4.91 1.00 1.04 1.20 0.12 0.62 0.29

18 WC82 15 128.20 0 5.69 1.10 2.33 2.99 0.20 2.13 0.26
20 5.32 0.80 0.86 1.40 0.14 2.07 0.27

19 WC79 3 177.20 0 6.26 0.90 3.34 7.19 0.30 3.08 0.20
20 5.60 0.80 0.65 5.09 0.16 4.02 0.30

20 WC89 0 142.00 0 5.74 1.30 5.36 4.01 0.16 2.05 0.20
20 5.06 0.80 1.40 1.08 0.10 1.03 0.27

21 WC90 3 178.90 0 5.31 1.40 4.37 7.61 0.17 4.75 0.32
20 5.14 0.90 1.23 2.56 0.09 3.91 0.28

22 WC07 0 155.20 0 5.39 1.20 3.07 3.54 0.19 1.79 0.28
20 5.36 0.80 1.80 1.87 0.11 2.39 0.32

23 WC92 35 139.90 0 5.52 1.10 6.90 3.09 0.19 1.17 0.26
20 5.27 0.50 4.14 0.47 0.14 0.45 0.26

24 WC93 30 118.80 0 5.91 1.60 13.16 5.11 0.47 2.65 0.34
20 5.19 0.90 1.17 2.52 0.17 1.28 0.11

Notes: Numbers after the plantation’s abbreviation indicate the planted year (19XX/20XX), for examples: WC92 is a
sample plot in Wang Chin plantation that was planted in year 1992; WC06 is a sample plot in Wang Chin
plantation that was planted in year 2006;
EC = electrical conductivity, N = total nitrogen, C = organic carbon, P = available phosphorus, Ca =
exchangeable calcium, K = exchangeable potassium, Mg = exchangeable magnesium, Na = exchangeable
sodium.

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BIOTROPIA Vol. 27 No. 2, 2020

10 m

40 m

1 4x4 m
1

11 [

f |

10 m

|— j teak growth data
collection

under story data
collection

G Bamboo
frequency

Figure 2 The experimental design for data collection

measure is relatively stable and robust over a
large range of managed stand densities (Steve
2001; Herrera-Fernandez et al. 2004). Many
stands had a dominant height and base age of
30-years at the time which the experiment was
conducted. A scatter plot between heights and
ages was fitted with a best-fit curve, along with
higher and lower envelope curves with a shape
similar to the guiding curves (Donald 1971) and
classified into 3 classes as having a good,
moderate, or poor site quality.

Classification of the Associated Species
Characteristics

The 24 sample plots or stands were analyzed
to describe the associated species life in the teak
plantation. In each stand, all the associated
species in the five sub-plots (4 x 4 cm each)
were identified based on Smitinand (2014) and
recorded, including its life form. The analysis of
associated species characteristics was important
value index (IVI).

Analysis of Plant Indicator Species
Indicator species was determined using

Indicator Species Analysis (ISA): an analysis of
the relationship between important index values
(IVI), which refer to species occurrence and
their abundance, from a set of sampled sites
which were site quality classes (good, moderate
and poor). The significant associated species
with p < 0.05 were indicator species of the site.
Two Way Indicator Species Analysis
(TWINSPAN) used to confirm the obvious
indicator species. Available in PC-ORD version

6.08 developed for windows (McCune &
Mefford 2011).

Relationship between Indicator Species and
Environmental Factors

A Generalized linear model (GLM) technique
was applied to determine the relationships of
indicator species distribution with
environmental factors (Table 2). The GLM
expands the general linear model so that the
dependent variable (number of each indicator
species) is linearly related to the covariates
(environmental factors) via a specified link
function which was natural log in this study.

RESULTS AND DISCUSSION

Site Index of Teak

Site index of teak was divided into 3 site
classes, with 24, 21 and 18, indicating a good,
moderate, and poor site quality, respectively
(Fig. 3 and Table 3). The number of plots that
were related to good, moderate, and poor site
quality was 9, 8 and 7, respectively.

The dominant height of teak trees, aged 30-

years, represented in the poor, moderate and
good quality sites, was 18, 21 and 24 m,
respectively. In a teak plantation in northern
Thailand, the site quality had influenced the 30-

year old teak height, 10 m (poor), 20 m
(moderate), and 30 m (good) (Kaosa-Ard 1991).
This study results indicated that the site quality
for teak plantation in Phrae Province was
relatively higher than the overall values reported

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Site indicator species for predicting the productivity of Teak plantations in Thailand — Jumwong et al.

in the northern Thailand, particular, for the poor
and moderate site quality. On the other hand,
the tree height for the good site class was lower
than that previously reported. These results
substantiated that of Chanpaisang (1997) where
the teak height at a base age of 30-years, were
classified it into 5 site qualities, 14 m (very
poor), 17 m (poor), 20 m (moderate), 23 m
(good) and 26 m (very good). The variability in
the average DBH, average dominant height, and
merchantable volume of teak was relatively high

for each of the site index classes (Table 1). In
sample plots with poor site quality, such as
MS83, it was observed that the average DBH
was higher than in those plots with good site
quality (WC83). This was a direct result of
silvicultural management, in which selective
thinning was done at ages 15 and 22 years, to
promote optimum growth of the remaining
trees. Thus, it is important to select a good site
with intensive management to grow teak.

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MS82

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C93*

MS87•
M01

wco;

10 15 20

age
25 30 35 40

Figure 3 Site index classes for teak in the three plantations located in Phrae Province, Thailand
Notes: KM = Khun Mae Kham Mee plantation; MS = Mae Saroy plantation; WC = Wang Chin plantation;

Numbers 24, 21, and 18 = site quality classes.

Table 3 Site index (SI), site quality (SQ) classes and related growth characteristics of Teak plantations at Phrae Province,
Thailand

SI No Plot Age Tree/ha H DBH Mean Annual Increment (MAI)
(SQ) (yr) (m) (cm) H (m) DBH (cm)
24 1 KM05 8 612 15.95 12.66 1.99 1.58

(good) 2 KM02 11 687 15.60 15.92 1.42 1.45
3 MS84 22 331 22.30 17.61 1.01 0.80
4 WC90 23 650 21.00 16.86 0.91 0.73
5 WC89 24 806 20.60 16.51 0.86 0.69
6 WC83 30 343 22.50 17.20 0.75 0.58
7 MS82 31 306 23.80 20.49 0.77 0.66
8 WC79 34 300 23.90 26.32 0.70 0.77
9 KM78 36 137 27.40 29.49 0.76 0.82

21 1 WC07 6 450 9.44 10.91 1.57 1.82
(moderate) 2 WC06 7 487 12.70 10.74 1.81 1.53

3 KM04 9 475 14.21 16.51 1.58 1.83
4 WC93 20 481 18.00 15.62 0.90 0.78
5 WC92 21 543 19.22 17.96 0.92 0.86
6 MS86 27 281 19.00 27.66 0.70 1.02
7 WC82 31 175 20.50 23.27 0.66 0.75
8 MS80 33 393 22.80 13.50 0.69 0.41

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BIOTROPIA Vol. 27 No. 2, 2020

Table 3 (Continued)
18 1 KM01 12 762 12.70 12.82 1.06 1.07

(poor) 2 MS87 26 837 16.05 15.60 0.62 0.60
3 KM85 28 581 17.99 19.59 0.64 0.70
4 KM83 30 262 17.49 22.79 0.60 0.64
5 MS83 30 312 18.10 19.19 0.58 0.76
6 KM81 32 293 18.50 23.95 0.58 0.75
7 KM75 39 137 19.60 18.51 0.50 0.47

Notes: Numbers indicate the planted year (19XX/20XX);
KM = Khun Mae Kham Mee plantation; MS = Mae Saroy plantation; WC = Wang Chin plantation.

Associated Species Characteristics
In this study, the associated species is native

species with only tree and shrub. From the
exploration of three Teak plantations in Phare
Province, it was found that all associated species
in 24 sample plots comprised of 76 species
belonging to 21 families. All the sample
unit was found in seedling and sapling stages.
Most of the associated species comprised of
trees (51 species). The dominant family was
Fabaceae (previously Leguminosae), with a total

of 15 species, followed by Malvaceae (6 species)
and Phyllanthaceae (6 species).

IVI was calculated by summing up the
relative density and relative frequency. The
top five with the highest IVI were
Cratoxylum formosum (20.86), Clerodendrum
chinense (13.24), Depisanthes rubiginosa (11.15),
Oroxylum indicum (10.25) and Dalbergia
lanceolaria (9.4). The species composition
and IVI of associated species are shown in
Table 3.

Table 3 Relative density (RD), relative frequency (RF) and important value index (IVI) of associated species

No Scientific name Family RD (%) RF (%) IVI
1 Cratoxylum formosum Hypericaceae 13.43 7.43 20.86
2 Clerodendrum chinense Lamiaceae 10.59 2.65 13.24
3 Fepisanthes rubiginosa Sapindaceae 3.71 7.43 11.15
4 Oroxylum indicum Bignoniaceae 3.53 6.73 10.25
5 Dalbergia lanceolaria Fabaceae 6.51 2.83 9.34
6 Vitex canescens Lamiaceae 4.95 4.07 9.02
7 Bridelia ovata Phyllanthaceae 6.00 2.12 8.13
8 Ficus hispida Moraceae 4.35 3.36 7.72
9 Croton stellatopilosus Euphorbiaceae 3.62 3.72 7.34

10 Barringtonia acutangula Lecythidaceae 2.84 3.72 6.56
11 Millettia brandisiana Fabaceae 3.62 2.48 6.10
12 Pterocarpus macrocarpus Fabaceae 3.67 2.30 5.97
13 Mitragyna rotundifolia Rubiaceae 1.92 3.19 5.11
14 Streblus ilicifolius Moraceae 3.25 1.24 4.49
15 Fernandoa adenophylla Bignoniaceae 1.10 2.83 3.93
16 Hymenodictyon orixense Rubiaceae 1.24 2.65 3.89
17 Greivia eriocarpa Malvaceae 1.47 2.12 3.59
18 Xylia xylocarpa Fabaceae 1.28 2.30 3.58
19 Dalbergia cultrata Fabaceae 1.37 1.95 3.32
20 Sterculia guttata Malvaceae 1.79 1.24 3.03
21 Fagerstroemia floribunda Lythraceae 1.65 1.24 2.89
22 Smilax sp. Smilacaceae 1.97 0.88 2.86
23 Diospyros malabarica Ebenaceae 0.73 1.59 2.33
24 Millettia leucantha Fabaceae 1.24 1.06 2.30
25 Bauhinia saccocalyx Fabaceae 1.05 1.24 2.29
26 Markhamia stipulate Bignoniaceae 0.64 1.42 2.06
27 Ferminalia nigrovenulosa Combretaceae 0.69 1.24 1.93
28 Fagerstroemia calyculata Lythraceae 0.50 1.42 1.92
29 Schleichera oleosa Sapindaceae 0.64 1.24 1.88
30 Artocarpus sp. Moraceae 0.55 1.06 1.61
31 AIbiyia odoratissima Fabaceae 0.37 1.24 1.61
32 Dalbergia nigrescens Fabaceae 0.50 1.06 1.57
33 Dalbergia cana Fabaceae 0.50 1.06 1.57
34 Albiyia lucidior Fabaceae 0.60 0.88 1.48
35 Casearia gremifolia Salicaceae 0.46 0.88 1.34

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Site indicator species for predicting the productivity of Teak plantations in Thailand — Jumwong et al.

Table 3 (Continued)
36 Bombax anceps Malvaceae 0.27 1.06 1.34
37 Streblus asper Moraceae 0.60 0.71 1.30
38 Cassia fistula Fabaceae 0.60 0.71 1.30
39 Vitex peduncularis Lamiaceae 0.41 0.88 1.30
40 Helicteres isora Malvaceae 0.23 1.06 1.29
41 Wrightia arborea Apocynaceae 0.27 0.88 1.16
42 Antidesma ghaesembilla Phyllanthaceae 0.41 0.71 1.12
43 Anogeissus acuminata Combretaceae 0.41 0.53 0.94
44 Microcos paniculata Malvaceae 0.41 0.53 0.94
45 Croton poilanei Euphorbiaceae 0.23 0.53 0.76
46 Broussonetia papyrifera Moraceae 0.32 0.35 0.67
47 Morinda tomentosa Rubiaceae 0.14 0.53 0.67
48 Irvingia malayana Irvingiaceae 0.27 0.35 0.63
49 Clausena harmandiana Rutaceae 0.09 0.53 0.62
50 Ardisia polycephala Primulaceae 0.23 0.35 0.58
51 Holarrhena pubescens Apocynaceae 0.05 0.53 0.58
52 Diospyros castanea Ebenaceae 0.37 0.18 0.54
53 Vitex pinnata Lamiaceae 0.32 0.18 0.50
54 Terminalia glaucifolia Combretaceae 0.14 0.35 0.49
55 Alstonia scholaris Apocynaceae 0.14 0.35 0.49
56 Catunaregam sp. Rubiaceae 0.14 0.35 0.49
57 I Jtsea glutinosa Lauraceae 0.14 0.35 0.49
58 Quercus kerrii Fabaceae 0.09 0.35 0.45
59 Homalium tomentosum Salicaceae 0.09 0.35 0.45
60 Siphonodon celastrineus Celastraceae 0.09 0.35 0.45
61 Antidesma bunius Phyllanthaceae 0.09 0.35 0.45
62 Cratoxylum cochinchinense Hypericaceae 0.23 0.18 0.41
63 Dalbergia ovata Fabaceae 0.09 0.18 0.27
64 Dalbergia oliveri Fabaceae 0.09 0.18 0.27
65 Terminalia pierrei Combretaceae 0.09 0.18 0.27
66 Adenanthera microsperma Fabaceae 0.09 0.18 0.27
67 Knema globularia Myristicaceae 0.09 0.18 0.27
68 Millingtonia hortensis Bignoniaceae 0.05 0.18 0.22
69 Glochidion assamicum Phyllanthaceae 0.05 0.18 0.22
70 Pterospermum semisagittatum Malvaceae 0.05 0.18 0.22
71 Tagerstroemia duperreana Lythraceae 0.05 0.18 0.22
72 Sterculia sp. Malvaceae 0.05 0.18 0.22
73 Canarium subulatum Burseraceae 0.05 0.18 0.22
74 Diospyros mollis Ebenaceae 0.05 0.18 0.22
75 Glochidion sphaerogynum Phyllanthaceae 0.05 0.18 0.22
76 Flueggea virosa Phyllanthaceae 0.05 0.18 0.22

Total 100.00 100.00 200.00

Plant Indicator Species
The results from the ISA significantly

indicated indicator species (p < 0.05) that were
Streblus ilicifolius, Dalbergia cana and Dagerstroemia
floribunda for good site. For poor site, the
indicator species were Schleichera oleosa and
Dalbergia nigrescens (Table 4). ISA could not
indicate indicator species for moderate site.

The results of TWINSPAN supported the
results of ISA which three indicator species were
found to define site quality of teak. Streblus
ilicifolius and Dagerstroemia floribunda were strong
indicator species for good site in KM. Schleichera
oleosa was strong indicator species for poor site
in KM (Fig. 4).

In Thailand, this is the first study of indicator
species and site quality of teak. There was no
information to compare the results with specific
site quality from previous works, therefore
discussion considered following the important
value of these indicator species from previous
works. The results of indicator species analysis
both of ISA and TWINSPAN were in
correspondence with Boonsri (2016) who found
Dalbergia nigrescens and Schleichera oleosa were
dominant species at KM. Forest Industry
Organization (2016) reported Schleichera oleosa
was dominant species in Mae Moh Forest
Plantation, Lampang.

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BIOTROPIA Vol. 27 No. 2, 2020

Table 4 The significant plant indicator species from ISA

Significance level
Site class Indicator SPP p-Value Bonferroni Sequential False Discovery

correction Bonferroni Rates
3 plantations
Good site Streblus ilicifolius * 0.00089 0.00089 0.00089
Good site l^agerstroemia floribunda * 0.00089 0.00091 0.00179
Good site Dalbergia cana * 0.00089 0.00093 0.00268
Poor site Schleichera oleosa * 0.00089 0.00094 0.00357
Poor site Dalbergia nigrescens * 0.00089 0.00096 0.00446
Khun Mae Kham Mee Plantation (KM)
Good site Lagerstroemia caljccdata * 0.00128 0.00128 0.00128
Good site Dalbergia cana * 0.00128 0.00132 0.00256
Wang Chin Plantation (WC)
Good site Streblus ilicifolius * 0.00054 0.00227 0.00227
Mae Saroy Plantation (MS); No indicator species

Note: * p < 0.05.

Dalbergia cultrata ( + )

00

0 Clerodendrum chinense { ~ )

01 Mitragyna rotundifolia (-)
Clerodendrum chinense {+ ) 10

010

0100 Diospyros malabarica (-)
Pterocorpus macrocarpus (- )
Streblus ilicifolius ( + )
Lagerstroemia floribunda (+)
Bridelia ovate ( + )

Mitragyna rotundifolia ( + ) Oil

0101

01000

KM04 MS80
KM01 MS87
KM82 WC82

01001

010010

Irvingia malayana (+)

010011

MS84 WC89
WC79
WC90
WC93

MS86
WC92
WC83

MS83
WC06
WC07

100

KM 78
KM05
KM02
KM83

1

Cassia fistula (+)

101

Vitex canescens (-)
Schleichera oleosa ( + )

11

KM85 KM75
KM81

Figure 4 The indicator species for each division from TWINSPAN
Notes: For the sample plot red alphabets indicate a good site, blue indicates a moderate site and black indicates

a poor site; 0 = negative group; 1 = positive group; (+) = right hand sub-group; (-) = leaf hand sub¬

groups.

Table 5 Generalized linear model (GLM) analysis of the relationships between indicator species distribution and
environmental factors

Indicator species Plantation
Site

quality pH N P Ca Elevation

Streblus ilicifolius KM/WC Good 3.38** -39.43* 26.53** 3.64
Dalbergia cana KM/WC Good -96.12 14.52 -0.13
Lagerstroemia caljcidata KM/WC Good -112.00 25.53 0.21
Lagerstroemia floribunda MS/WC Good 10.23** 20.42* 4.60**
Schileichera oleosa KM Poor 1.50 0.16
Dalbergia nigrescens KM Poor 2.56 -0.96 -3.24

Notes: * p < 0.05; ** p < 0.01;
The values in the various columns are model regression coefficient.

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Site indicator species for predicting the productivity of Teak plantations in Thailand — Jumwong et at

Relationship between Indicator Species and
Environmental Factors

Soil pH and N were the main factors to
distribute all indicator species to 3 relationships.
First, the indicator species positively associated
with soil pH and negatively associated with N
were Streblus ilicifolius and Dalbergia nigrescens.
Second, the indicator species positively
associated with soil pH and N were Lagerstroemia
floribunda and Schileichera oleosa. Third, the
indicator species negatively associated with soil
pH and positively associated N were Dalbergia
cana and _Lagerstroemia calyculata. The GLM
analysis revealed P, Ca and elevation influenced
indicator species distribution (Table 5).

Streblus ilicifolius was indicator species of good
site which the result of ISA computed from data
sets of three plantations: KM, MS and WC.
From the survey found that Streblus ilicifolius was
found in KM and WC. The distribution of
Streblus ilicifolius was statistically significant
positively associated with soil pH and P and
negatively associated with N. Furthermore, tend
to find Streblus ilicifolius in areas with high
calcium content.

Dalbergia cana and Dagerstroemia calyculata were
indicator species of good site which found in
KM and WC. The spatial distribution was not
statistically significant with environmental
factors (p > 0.05). The distribution was
negatively associated with soil pH and positively
associated with N. By the time, Dalbergia cana
was negatively associated with elevation but
Dagerstroemia calyculata was positively associated
with elevation.

Dagerstroemia floribunda was indicator species
of good site which found in MS and WC. The
distribution was statistically significant positively
associated with soil pH, N and P.

Schileichera oleosa and Dalbergia nigrescens were
indicator species of poor site in KM. The spatial
distributions were not statistically significant
with environmental factors (p > 0.05). The
distribution of Schileichera oleosa was positively
associated with soil pH and N. The distribution
of Dalbergia nigrescens was positively associated
with soil pH and negatively associated with N
and P.

CONCLUSION

Based on the anamorphic site index method,
Indicator Species Analysis (ISA) and Two Way
Indicator Species Analysis (TWINSPAN) of the
three Teak plantations in Phrae province,
Thailand, the site indices at base age 30 year old
teak trees could be divided into 3 classes,
namely; 24 for good, 21 for moderate, and 18
for poor site quality. The significant indicator
species in the 3 site index classes derived from
ISA (p < 0.05) are Streblus ilicifolius, Dalbergia
cana, Dagerstroemia floribunda and Dagerstroemia
calyculata for good site. For poor site, the
indicator species were Schleichera oleosa and
Dalbergia nigrescens. The results of TWINSPAN
supported the results of ISA which three
indicator species are obvious indicator species
i.e., Streblus ilicifolius and Dagerstroemia floribunda
and Schleichera oleosa for poor site, especially in
KM. Finally, since this study is the first of its
kind, it is recommended that the site indicator
species analysis be done in other teak areas to
substantiate this study results. Meanwhile, in the
absence of confirmatory studies, the farmers can
apply this current finding and determine the site
quality based on the past or present appearance
of the indicator species.

ACKNOWLEDGEMENTS

This research was funded by the Center for
Advanced Studies in Tropical Natural
Resources, Institute of Advanced Studies,
Kasetsart University (CASTNaR, NRU-KU),
Thailand.

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