PROCEEDINGS OF THE ADVANCED FIELDCOURSE IN ECOLOGY …€¦ · 15:30 L29: Forest restoration Tang Yong 16:30 L28: amphibians and birds Vivian Fu 18:00 Dinner 29 Nov 9:00 L16: Soil

PROCEEDINGS OF THE

ADVANCED FIELDCOURSE IN ECOLOGY AND

CONSERVATION – XTBG 2010

XISHUANGBANNA TROPICAL BOTANICAL GARDEN, YUNNAN, CHINA 20 NOV – 18 DEC 2010

EDITED BY LAN QIE, YALOU LIU AND RHETT HARRISON

Preface

i

Preface

The AFEC-X Field Biology Course is an annual, graduate-level field course in tropical forest biology run by the Program for Field Studies in Tropical Asia (PFS-TropAsia; www.pfs-tropasia.org), Xishuangbanna Tropical Botanical Garden, Chinese Academy of Science, in collaboration with institutional partners in the region. The course is held at Xishuangbanna Tropical Botanical Garden in Yunnan, China and at field sites in Xishunagbanna. AFEC-X 2010 Field Biology Course was held from from 20 November to 18 December, and was the second such course to be organised by PFS-TropAsia after launching the course in 2009. The aim of these courses is to provide high-level training in the biology and conservation of forests in tropical Asia. The courses are aimed at entry-level graduate students from the region, who are at the start of their thesis research or professional careers in forest biology. During the course topics in forest biology are taught by a wide range of experts in tropical forest science. There is also a strong emphasis on the development of independent research projects. Students are exposed to different ecosystem types through course excursions. The AFEC-X 2010 Field Biology Course was attended by 20 students from 10 countries (China, Thailand, Indonesia, India, Sri Lanka, Cambodia, Cameroon, Benin, Argentina and DPR Korea) and a total of 15 resource staff from a variety of national and international institutions gave lectures and practical instruction. Twelve participants received fellowships, including travel awards, to attend the field course. The course was run by Professor Ferry Slik (Laboratory of Plant Geography, XTBG), Dr. Lan Qie (PFS-TropAsia, XTBG), and Professor Chuck Cannon (Laboratory of Ecological Evolution, XTBG). Due to their efforts the course proved to be a huge success. The following report illustrates the hard work of the organizers and the enthusiasm and commitment of the students. Rhett D. Harrison

Director, Program for Field Studies in Tropical Asia

Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences

Acknowledgement

ii

Acknowledgement

The AFEC-X China 2010 organizers wish to thank all resource staff listed at the end of this proceedings, who generously gave their time to teach the field course, especially Dr. Doug Schaefer, Dr Jacob Wickham, Ms. Shi Lingling and Ms. Vivian Fu, who invested enormous amount of time into the course. A field course like this will not be possible without the commitment and support from these researchers. We thank Professor Ding Wenjun, the vice dean of the School Life Sciences, Chinese Academy of Sciences and Director Chen Jin of Xishuangbanna Tropical Botanical Garden (XTBG) for attending the Opening Ceremony of AFEC-X China 2010 and giving guest lectures to the participants. We give our sincere thanks to our Program Coordinator Liu Yalou (Allen) whose role in this course was absolutely indispensable. We would like to thank the supporting staff from the XTBG Personnel and Education Office: Mr. Chen Zhiyun and Ms. Liu Zhiqiu, from the Project Management Office: Mr. Yang Qing and Ms. Fang Chunyan, for their wonderful help to make sure the administration and logistics of this course went smoothly. We are very grateful for the kind help from the XTBG Student Union in taking care of the international participants upon their arrival and in putting on a wonder performance at the course farewell party. The organizers acknowledge the support and assistance of the Xishuangbanna Nature Reserve management, in particular Mr. Ai Jiao and Mr. Li Zhonghua, who accompanied the class during our field trip at Mengsong. We give out special thanks to the local Hani people at Mengsong, the Village Head Mr. He Yongneng, San Tu, and Ah Dong. Their great hospitality made all the international participants feel just at home. The wonderful and authentic Hani dinner we had at He’s house was one of the most memorable experiences during the field course. AFEC-X China 2010 was funded by XTBG and the Key Lab of Tropical Forest Ecology. Thanks to all.

Ferry Slik

Professor, Plant Geography Lab


Lan Qie

Scientific Coordinator, Program for Field Studies in Tropical Asia


CONTENT

iii

CONTENT

Preface................................................................................................................................... i

Acknowledgement ................................................................................................................ ii

CONTENT........................................................................................................................... iii

AFEC-X 2010 Schedule........................................................................................................ 1

Group Reports....................................................................................................................... 1

The Effect of Distance from Stream Edge on Insect Diversity in a Mengsong Meadow......... 1

Relationship between Soil Macrofauna and Soil Respiration in Two Different Vegetation

Types .................................................................................................................................... 7

Soil Respiration Responses to Forest Density and Elevation Gradients in the Rainforests of

Mengsong ........................................................................................................................... 14

Do Environmental Factors Influence the Density of Invasive Species? ................................ 21

The Distribution Patterns of Birds in Tropical Riparian Forest of Mengsong ....................... 29

Changes in Plant Community Trait Composition of Understory Trees: Mengsong Seasonal

Tropical Rainforests, Yunnan, China:.................................................................................. 35

Participants ......................................................................................................................... 50

People ................................................................................................................................. 55

Resource Staff..................................................................................................................... 55

Teaching Assistants............................................................................................................. 58

AFEC 2010 Schedule

1

AFEC-X 2010 Schedule

Day Month Time Activity Lecturer

20 Nov Arrival Participants

21 Nov 9:00 Registration (Kunming XTBG office)

10:00 L1: Course introduction Chuck Cannon

11:00 L2: Introduction to the tropics Chuck Cannon

12:00 Lunch

13:00 L3: Mutualisms Doug Yu

14:00 L4: Amerindians and conservation Doug Yu

15:00 Student introductions

18:00 Dinner

22 Nov 8:00 Bus trip to XTBG

23 Nov 8:30 CAS delegation of graduate school

9:30 L5: Conservation crisis in Asia and new developments

Ferry Slik

10:00 L6: Conservation Chuck Cannon

11:00 L7: DNA developments Chuck Cannon

12:00 Lunch

13:30 L8: Ecophysiology Cao Kunfang

14:30 L9: Seed dispersal Chen Jin

15:30 L14: Invasive plants Feng Yulong

18:00 Dinner

19:30 Student introductions

24 Nov 9:00 L17: Statistics day Rhett Harrison

12:00 Lunch

13:30 L17: Statistics day Rhett Harrison

18:00 Dinner

19:30 L12: Plant animal interactions Rhett Harrison

20:30 L23: Getting published Rhett Harrison

25 Nov 9:00 L11: Biodiversity Ferry Slik

10:00 L30: Biogeography Ferry Slik

11:00 L13: Wood ring research Fan Zexin

12:00 Lunch

13:30 L32: Modeling and climate change Ferry Slik

14:30 L15: Soil litter fauna Yang Xiaodong

15:30 L31: Introduction to Mengsong Ferry Slik

16:30 L27: Project design / Devide students in groups Chuck Cannon

18:00 Dinner

26 Nov 9:00 L10: Plant taxonomy Ferry Slik

10:00 Move to rainforest site (plant collecting) Ferry Slik

AFEC 2010 Schedule

14:00 Identify plants in lecture hall Ferry Slik

16:00 Introduce short term projects / Devide students in groups

Ferry Slik, Qie Lan

18:00 Dinner

27 Nov 9:00 Visit to CTFS 20 ha plot Ferry Slik, Qie Lan

18:00 Dinner

28 Nov 9:00 L18: DNA Applications Shi Lingling

10:00 L19: Molecular Ecology Shi Lingling

11:00 L31: Community ecology Ferry Slik

12:00 Lunch

13:30 L21: Insects Jacob Wickham

14:30 L22: Insects Jacob Wickham

15:30 L29: Forest restoration Tang Yong

16:30 L28: amphibians and birds Vivian Fu

18:00 Dinner

29 Nov 9:00 L16: Soil Ecology Douglas Scheaffer

10:00 Visit to forest restoration site Tang Yong

30 Nov 8:00 Move to Mengsong

13:00 Round trip through Mengsong Ferry Slik, Qie Lan

1 Dec Mensong field survey: Students start thinking about projects

Ferry Slik, Qie Lan

2 Dec Morning: preparation of proposals; Afternoon: presentation of proposals

Ferry Slik, Qie Lan

3 Dec Field projects Ferry Slik, Qie Lan








11 Dec 8:00 Return to XTBG

12:00 Lunch + free afternoon

12 Dec 9:00 Data analysis

13 Dec 9:00 L24: Energy plants Zeng-Fu Xu

10:00 Data analysis rest of day

14 Dec 9:00 Presentation try-outs (rest of day)

15 Dec 9:00 Prepare final presentation

16 Dec 9:00 Whole day symposium

18:00 Goodbye dinner in bamboo restaurant

17 Dec 8:00 Back to Kunming

18 Dec Everybody leaves for home

Group Reports

1

Group Reports

The Effect of Distance from Stream Edge on Insect Diversity in a Mengsong Meadow

Eka A.P. Iskandar

1, Duan Qiong

2 and Sophany Phauk

3

1Cibodas Botanical Garden, Indonesian Institute of Sciences, Cibodas, Cianjur, Indonesia 43253. 2Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Menglun, Mengla, Yunnan 666303, China 3 Department of Biology, Faculty of Sciences, Royal University of Phnom Penh, Phnom Penh 12000. Cambodia

Abstract

This study examined the effect of stream edge on diversity of insects in a meadow in Mengsong, Yunnan Province, China. The meadow was located between a stream and a forest. Insect sampling was conducted over the course of ten days at five distances from the stream: 0 m, 6.25 m, 12.5 m, 18.75 m and 25 m (at the forest edge). Insects were captured using pitfall traps and a sweep net, and identified to order and morph species. Vegetation analyses were performed using point transects. Diversity index for insect and plant were counted using shanon-Weaver index. The results showed that the insect diversity was not affected by distance from the stream, but insect abundance was affected. Plant diversity was correlated with distance from stream edge. However there was no correlation between insect diversity and plant diversity. And there was no correlation between plant diversity and insect abundance. Keywords: edge effect, insect diversity, insect abundance, meadow, pitfall, plant diversity

INTRODUCTION

In tropical dry forests, water resources

have the potential to influence local insect

diversity, abundance, and composition

(Janzen, 1967).Edge effects result from the

interplay between two spatially contiguous

ecosystems (Murcia, 1995). Edge effect

hypothesis states that diversity is higher in

ecotones than in adjacentassemblages

(Odum 1971), which influences

invertebrate assemblage patterns (Majer et

al.1997). Insect assemblages are very

important components of biodiversity

because they accumulate considerable

biomass and show high species richness

(Erwin, 1991). Insect plays a very

important role in the food web of

ecosystem. For these reasons, insects are

valuable ecological indicators of edge

effects in natural landscapes (Pinheiro et al.

2010).

A meadow in Mengsong was

chosen to investigate whether there was a


significant change in insect diversity and

abundance at increasing distances from the

stream. Our hypothesis was that the

walking insect diversity would decrease

with distance from the stream because of

the moisture, and the jumping and flying

insect diversity would increase with

distance from the stream because of the

insect resource from forest.

METHODS

STUDY AREA. –An even meadow in

Mengsong, Yunnan, China adjacent to a

stream and a forest was chosen for this

study (100o24’48”-100o40’25”E;

21o56’54” - 22o16’56” N; 1640 m a.s.l.). It

was formed due to the drying process of

the dam downstream earlier (c.a. one year

ago).The grass vegetation of the meadow

was almost the same, dominated by

grasses of knee height. There were some

herbs by the stream edge which can reach

until 75 cm height. The maximum distance

from the edge of the secondary forest to

the edge of the stream was approximately

30 m.

INSECT SAMPLING. –The study was

conducted from December 4th to 10th, 2010.

Five parallel line transects, one located at

the stream edge (line A), three on the

grassland (line B, C and D), and one at the

forest edge (line E), separated by at least 5

m were laid out. Five pitfalls were placed

along each line at 5m distance from each

other, to capture ground-favoring insects.

Each pitfall trap consisted of a white

plastic glass, buried to its rim in soil and

partly filled with a 30:70 ethylene glycol:

water mixture. Each trap was covered with

a small plastic sheet roof supported with a

stick to prevent either desiccation or

flooding, but left the sides open so that

insects could enter the pitfall unhindered.

Traps were inspected and collected every

48 hours over two periods. Trapped insects

were separated, identified to

morphospecies, and counted. Species

richness and abundance of taxa at each

pitfall was recorded by counting species.

Additionally, a sweep net method was

used in line A, C, and E, to capture more

mobile, none ground-favoring insects.

Because of the vegetation of the meadow

was almost grass, we used the point

transect method. Using a stick, we pointed

along the one meter line at 20 cm distance

on each side of the pitfall, where pitfalls

acted as its center. Plant species that

touches the stick was recorded and

identified to as specific as possible taxa or

to morphospecies if it was unidentified.

DATA ANALYSIS. –Diversity was

characterised by the Shannon-Weaver

Index. Statistical estimation of species

richness was performed using the Estimate

S 8.0.0 program [reference]. Chao 2was

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3

used to estimate species richness in the

study area. Statistical analyses were

performed using the statistics program R

2.12.0 (R Development Core Team 2010).

The effect of distance category (Line A-E)

from the stream on insect species richness

was analyzed using one-wayANOVA. The

effects of distance and plant diversity on

the insect diversity and abundance were

analyzed using linear regressions, with

some modifications, and the pitfall and

sweep netting result were analyzed

separately.

RESULTS

We collected 68 and 53 morphospecies

from the pitfalls and sweep netting, with

82% and 72% completeness, respectively

based on the Chao2. Vegetation was

dominated by Ageratina adenophora,

Poaceae sp.1, and Polygonum sp.2 for

stream edge, meadow center, and forest

edge, respectively. According to a

one-way ANOVA test, distance had a

significant effect on themean total number

of plantmorphospecies per line (DF-4, 20,

F=5.07, P=0.0055).

For both pitfalls and sweep net,

insect diversity was not correlated with

distance from the stream, and insect

diversity was also not correlated with plant

diversity. However, plant diversity

showed a quadratic relationship with

distance from the stream (r2=

0.54,p<0.0001 (fig.1), and a linear

relationship for sweep net: r2= 0.78, p =

0.02 (fig.2)). A quadratic relationship also

exists between insect abundance and

distance from the stream (r2= 0.20, p =

0.002 (fig.3)).


0 5 10 15 20 25

0.0

0.5

1.0

1.5

2.0

pitfall$distance.stream

Fig.1. Linear and quadratic regression of plant diversity with distance from the stream (pitfall).

0 5 10 15 20 25

0.6

0.8

1.0

1.2

1.4

1.6

sweep$distance.stream

Fig.2. Linear and regression of plant diversity with distance from the stream (sweep net).

R2=0.54, p<0.0001

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5

0 5 10 15 20 25

10

20

30

40

50

pitfall$distance.stream

Fig.3. Quadratic regression of insect abundance with distance from the stream (pitfall)

DISCUSSION

Our study showed that the insect diversity

was not correlated with distance from the

stream. This was probably due to the study

area that may have been too small to detect

the effects of distance. The period of

study was also short, and was in dry

whether where most insects were less

active. This result supports Bruneau &

Lee (2003) who found that distance has no

significant effect on insect diversity. Their

study was conducted on the dry tropical

forest dominated by low growing

vegetation near the water and grasses on

further distance from the water.

We found that plant diversity was

correlated with distance from the stream,

where both edges had higher diversity in

comparison with the center of the meadow.

By the stream, the moisture is a very

important effect factor; by the forest, the

insect resource may be the effect factor.

This is clearly supported Odum’s

hypothesis (1971). Higher plant diversity

on the edges would influence the

invertebrate assemblages’ patterns (Majer

et al.1997). Because a diversity of

resources should support a diversity of

consumers, most models predict that

increasing plant diversity increases animal

diversity. Analyses of relations among


plants and arthropod trophic groups

indicated that herbivore diversity was

influenced by plant(Stein et al. 2010).In

general, trees have richer insect faunas

than herbs(Whipple et al. 2010)

ACKNOWLEDGEMENTS

We would like to thank to our sponsor and

organizer, the Xishuangbanna Tropical

Botanical Garden (XTBG) for hosting this

AFEC 2010. Special thanks to Dr. Ferry

Slik, Dr. Charles Cannon, Dr. Jacob D.

Wickham, Dr. Rhett D. Harrison, Dr.

Doug Schaefer, Qie Lan, Liu Yalou and

all the staff in XTBG for great warm

welcome and facilitation. Thanks to all our

friends in the course with sharing

knowledge, culture and happiness.

LITERATURE CITED

BRUNEAU, L. & M. Lee. 2003. The affects of distance from water holes on insect diversity in tropical dry forests in Deinert, E., K. Gastreich, M. Sasa, A.C. Villegas (eds.) Undergraduate Semester Abroad Program. Organization of Tropical Studies.

ERWIN, T.L.1991.How many species are there?Revisited.Conserv.Biol.5:330-333.

JANZEN, D.H., T.W. Schoener. 1967. Differences in insect abundance anddiversity between wetter and drier sites during a tropical dry season. Ecology 49: 96-110.

MAJER,J.D., J.H.C. Delabie , N.L. McKenzie. 1997. Ant litter fauna of forest, forest edges and adjacent grassland in the Atlantic rainforest region of Bahia, Brazil. Insect Soc. 44:255-266.

MURCIA, C. 1995. Edge effects in fragmented forests: implications for conservation. TREE 10:58-62.

ODUM, E.P.1971.Fundamentals of

Ecology. Saunders, London.

PINHEIRO, R.S., L.S. Duarte, E. Diehl, S.M. Hartz. 2010. Edge effects on epigeic ant assemblages in a grassland forest mosaic in southern Brazil. Acta

Oecologica36:365-371.

R Development Core Team (2010). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org/.

STEIN, C., S. Unsicker, A. Kahmen, M. Wagner, V. Audorff, H. Auge, D. Prati, and W. Weisser. 2010. Impact of invertebrate herbivory in grasslands depends on plant species diversity. Ecology91:1639-1650.

WHIPPLE, S., M. Brust, W. Hoback, and K. Farnsworth-Hoback. 2010. Sweep Sampling Capture Rates for Rangeland Grasshoppers (Orthoptera: Acrididae) Vary During Morning Hours. Journal

of Orthoptera Research19:75-80.

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7

Relationship between Soil Macrofauna and Soil Respiration in Two Different

Vegetation Types

Iogna Patricia A.1, Liu Xiamo

2, Jo Won Ju

3

1GEBEF (Ecophysiological and Biophysical Research Group), Natural Sciences Faculty, National University of Patagonia San Juan Bosco (UNPSJB). National Council on Scientifics and Technical research (CONICET). Ciudad Universitaria Km4, Comodoro Rivadavia, 9005, Argentina. 2Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Menglun, Mengla, Yunnan 666303, China. 3Geographical Information Group, Land Use Planning Institute under the Ministry of Land Environment Protection (MoLEP). Abstract

There is an extremely high diversity of organisms living in the soil that contribute in returning the carbon fixed in photosynthesis to the atmosphere. This study compares the CO2 release, and macrofauna from the soil in secondary forest and adjacent tea plantation of Mengsong Nature Reserve, Yunnan, China. Soil CO2 measurements were made on soil samples taken from each site. Soil macrofauna were classified into 130 morphospecies and the number of individuals counted for each soil sample. While CO2 release was not significantly different between the two vegetation types, we found 30% higher species richness, and more than twice abundance, of soil macrofauna, in the secondary forest compared to tea plantation. Key words: carbon dioxide, decomposition, secondary forest, soil fauna, tea plantation. DECOMPOSITION OF DEAD PLANT

material is an important process by which

carbon fixed during photosynthesis is

returned to the atmosphere and is critical

for nutrient cycling (Swift et al. 1979).

This process is driven by interacting

physical factors, such as climate, substrate,

soil organisms, and physical and chemical

properties of soils (Dyer et al. 1990;

Pausas et al. 2004).

Soils host an extremely high

diversity of organisms. In one hectare of

temperate forest, several hundred species

of soil invertebrates may coexist (Schaefer

and Schauerman, 1990). This soil fauna

can be classified into microfauna,

mesofauna and macrofauna. Macrofauna

include organisms between 2 and 20 mm

(e.g., millipedes, woodlice, fly larvae,

beetles, snails and earthworms). They have

body sizes large enough to disrupt the

physical structure of the soil through their

feeding and/or burrowing activities.

These organisms contribute to litter

decomposition by digestion of substrates,

increase of surface area through

fragmentation, and acceleration of

microbial inoculation to materials (Swift et

Relationship between Soil Macrofauna and Soil Respiration in Two Different Vegetation Types

al.1979; Coleman and Crossley, 1996).

Soil microarthropods, as prevalent

components of the soil fauna, have been

shown to increase the rates of litter

decomposition, nutrient cycling and

primary productivity in forest ecosystems

(Seastedt,1984) through digestion and

breakdown of the litter, stimulation of

microbial activity and transport of fungal

and bacterial propagules (Moore et al.

1988; Read and Perez-Moreno, 2003). Soil

fauna can also influence microbial species

composition or biomass (Visser, 1985;

Groffman et al. 2004), thus altering

decomposition rates and nutrient cycles

(Moore et al. 1988; Lavelle, 2002).

Moreover, litter fragmentation and passage

through the guts of microarthropods such

as millipedes and isopods favor the

establishment of soil microbial populations

(Griffiths and Bardgett, 1997).

This soil macrofauna can be affected

by land use. Most land use practices

reduce the abundance or diversity of soil

macroinvertebrate communities by

disturbing their physical environment and

reducing the diversity and abundance of

organic inputs that they normally use for

feeding (Curry, 1987; Decaëns et al.

1994).

The objective of this study was to

compare the CO2 release from the soil

between secondary forest and adjacent tea

plantation macrofauna of Mengsong

Nature Reserve, Yunnan, China. Our

hypothesis was that soil macrofauna

diversity and abundance would be higher

in the secondary forest than in the tea

plantation for the human disturbance of the

site, and that these differences in soil

macrofauna will be reflected in a higher

CO2 release by the secondary forest soil.

In this study, we asked whether

forest type affect soil fauna richness and

abundance. If secondary forest and rubber

plantation have different physical and

chemical soil properties. It may have

altered CO2 production and different soil

fauna diversity.

METHODS

STUDY SITE AND SAMPLES. –The

study was carried out in Mengsong,

Xishuangbanna, Yunnan province, China.

Soil samples were extracted from

secondary forest and adjacent tea

plantation.

The study site has a typical monsoon

climate with three distinct seasons

distributed throughout the year as follows:

1. A humid hot rainy season that runs from

May to October,

2. A foggy cool-dry season from

November to February, and

3. A hot-dry season from March to April.

Mean annual temperature ranges

between 15.1°C and 21.7°C, and

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9

precipitation between 1200 and 2500 mm.

Rainfall during the wet season between

May and October accounts for over 80

percent of total annual precipitation. Water

deposition from fog accounts for over

one-third of total water input during the

dry season in the forests, suggesting an

important role that fog may play in

pushing up the northern limit of tropical

rain forest in Southeast Asia (Cao et al.

2006). The soil is classified as latosol (pH

4.5 5.5) developed from purple sandstone.

In the secondary forest, 4 plots of

20x20 m were selected with 100 m

intervals. In the tea plantation, due to the

limited size of the area, 4 plots of 10x10 m

were selected with 50 m intervals. In each

plot 4 soil samples of 15 cm diameter and

6 - 8 cm depth were extracted from each

corner of the plot. Soil extraction was done

inside a metal cylinder pushed into the

ground to prevent the soil fauna from

escaping during sampling. Soil mass of

each sample was measured in the

laboratory.

Tea plantation

Secondary forest

SOIL CO2 MEASUREMENTS. – Soil CO2 release was measured from each soil sample with a LI-820 (Licor, Licoln, NEUSA) in the laboratory.

SOIL MACROFAUNA - Winkler bags

were used to extract the soil macrofauna of

the soil samples. This fauna extraction

method works through the desiccation of

the soil samples inside the bag, which

makes the macrofauna to move out of the

soil sample, after which they end up in a

cup at the bottom of the bag. The cup was

partially filled with soapy water with salt

to drown and preserve the insects that fell

in the cup. Soil samples were first passed

through a 1 cm sieve to remove big


material present in the soil and then placed

in the winkler bag. After 24 hrs the soil

sample was taken out and remixed to

enhance desiccation, and placed back in

the winkler bag. After 48 hrs the water in

the cup was passed through a 2 mm mesh

to remove the micro- and mesofauna. The

remaining macrofauna were then sorted.

Soil macrofauna was classified in

morphospecies under a microscope and the

number of individuals counted for each

soil sample.

DATA ANALYSES – R software (R

Development Core Team 2010) was used

for data analyses. One-way analyses of

variances (ANOVA) were used to test the

significance of difference in CO2

production, abundance, richness and forest

type. Analysis of covariance (ANCOVA)

were used to test the significance of

difference between abundance, richness

and forest type was consistent CO2

production.

RESULTS

For all samples combined we identified

130 macrofauna morphospecies, of which

94 were found in the secondary forest and

64 in the tea plantation. The total number

of individuals found in the secondary

forest was 495, more than twice the

number in the tea plantation (202

individuals).

1. CO2 production rate was not

significantly different between

secondary forest and tea plantation

(Fig. 1; one factor ANOVA, p-value =

0.7508, adjusted R-squared = 0.02981).

The reason maybe that the secondary

forest site is not far away from the tea

plantation, and the tea plantation has

low management intensity.

secondary tea

10

00

30

00

50

00

forest.type

Fig. 1 One factor ANOVA showing that

CO2 production (μmoles/h-1) is not

significantly different between secondary

forest and tea plantation.

2. Abundance was not significantly

different between the two forest types

(Fig. 2; p-value = 0.7508 adjusted

R-squared = 0.03087)

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secondary tea

51

01

52

02

53

0

forest type

Fig. 2 One factor ANOVA showing

abundance of soil macrofauna is not

significantly different between secondary

forest and tea plantation.

secondary tea

10

20

30

40

forest type

richness

Fig. 3 One factor ANOVA showing that

the richness of insect is significantly

higher in secondary forest than in tea

plantation.

3.Richness was found to differ

significantly between different vegetation

types. (p-value = 0.001182, adjusted

R-squared = 0.2933)

DISCUSSION

Our study investigated whether forest type

affects soil fauna richness and abundance

and CO2 production. We found that CO2

production rate is not significantly

different between secondary forest and tea

plantation. We also found that Abundance

and richness is higher in secondary forest

than tea plantation. However this may

have to do with the fact that the tea

plantation is in the vicinity of the

secondary forest. Our data collection was

also limited to a single season of the year,

while ideally CO2 production needs to be

measured at different times of the year to

be able to detect its variability.

There may be many other factors

affecting CO2 production, such as root

respiration, surface-litter respiration and

soil organic matter. CO2 production from

soil surface is approximately equal to the

soil respiration. Which part of CO2

production comes from soil fauna is

difficult to measure, however, CO2

production from soil surface is

approximately equal to the soil respiration.

Because of limited time we did not

consider the associations between soil

fauna and litter quantity and quality. Soil


fauna represent a sensitive link between

plant detritus and plant-available nutrients.

Changes in litter quality could affect the

abundance of some faunal species either

directly or indirectly through their food

supply. In secondary forest, both litter

quality and quantity are expected to be

higher than in tea plantation.

Also, land use change may affect

soil fauna through modified environmental

conditions, such as soil temperature,

moisture, nutrients, heat and light, thereby

triggering changes in plant competitive

interactions, community composition and

disturbance regimes. Future studies should

take these environmental factors into

consideration.

ACKNOWLEDGEMENTS

We would like to thanks Lainie (Qie lan),

Douglas Schaefer, Chuck Cannon, Ferry

Slik, Rhett Harrison, Jacob Wickham,

Vivian Fu, Shi Lingling, Allen (Liu

Yalou) and the AFEC-2010 Group.

LITERATURED CITED

COLEMAN, D.C., CROSSLEY, D.A. (1996). Fundamentals of Soil Ecology. Academic Press,San Diego, California, USA.

CURRY, J.P. (1987). The invertebrate

fauna of grassland and its influence on productivity. 1. The composition of the fauna. Grass For Sci 42: 103–120.

DECAËNS, T., LAVELLE, P., JIMENEZ JAEN, J.J., ESCOBAR, G. & RIPSTEIN, G. (1994). Impact of land management on soil macrofauna in the Oriental Llanos of Colombia. Eur J Soil Biol 30(4): 157–168.

DYER, M.L., MEENTEMEYER, V., BERG, B., (1990). Apparent controls of mass loss rate of leaf litter on a regional scale: litter quality vs. climate. Scandinavian Journal of Forest Research 5, 311–323.

GRIFFITHS, B.S., BARDGETT, R.D. (1997). Modern Soil Microbiology: Interactions Between Microbe-feeding Invertebrate and Soil Microorganisms. Marvel Dekker lnc., New York, pp. 165–182.

GROFFMAN, P.M., BOHLEN, P.J., FISK,

M.C., FAHEY, T.J. (2004). Exotic earthworm invasion and microbial biomass in temperate forest soils. Ecosystems 7, 45–54.

LAVELLE, P. (2002). Functional domains

in soils. Ecology Resource 17, 441–450.

MOORE, J.C., WALTER, D.E., HUNT,

H.W. (1988). Arthropod regulation of micro- and mesobiota in below-ground detrital food webs. Annual Review of Entomology 33, 419–439.

PAUSAS, J.G., CASALS, P., ROMANYA,

J. (2004). Litter decomposition and faunal activity in Mediterranean forest soils: effects of N content and the moss layer. Soil Biology and

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Biochemistry 36, 989–997. READ, D.J., PEREZ-MORENO, J. (2003).

Mycorrhizas and nutrient cycling in ecosystems– a journey towards relevance? New Phytologist 157, 475–492.

SCHAEFER, M. AND SCHAUERMANN,

J. (1990). The soil fauna of beech forests: comparison between a mull and a moder soil. Pedobiologia 34(5), 299-314.

SEASTEDT, T.R. (1984). The role of

microarthropods in the decomposition and mineralization of

N. Annual Review of Ecology and Systematics 29, 25–46.

SWIFT, M.J., HEAL, O.W., ANDERSON,

J.M. (1979). Decomposition in Terrestrial Ecosystems. Blackwell Science, Oxford, UK.

VISSER, S. (1985). Role of the soil

invertebrates in determining the composition of soil microbial communities. In: Fitter, A.H., Atkinson, D., Read, D.J., Usher, M.B. (Eds.), Ecological Interactions in Soil. Blackwells, Oxford, pp. 297–317.

Soil Respiration Responses to Forest Density and Elevation Gradients in the Rainforests of Mengsong

Soil Respiration Responses to Forest Density and Elevation Gradients in the Rainforests

of Mengsong

Orou Augustin1, Chemboli Sreenivasan Dhanya

2, Liu Yanjie

3, Ri Kum Ran

4

1Hokkaido University, Japan 2M S Swaminathan Research Foundation, India 3Graduate University of Chinese Academy of Science, China 4Environment and Development Centre, DPR Korea

Abstract

A study was carried out looking at the effect of basal area and topography (elevation and slope) on CO2 production in the litter zone of the rain forests of Mengsong, Yunnan Province, China. Basal area was calculated from the dbh measured in 20 x 20 m quadrats at both upper and lower parts of the mountain, and CO2 production was measured in the field using a Co2 gas analyzer (Li-820). It was found that Soil respiration increased with increasing basal area and elevation, and basal area increased with increasing elevation. Slope didn’t affect either soil respiration or basal area in the Mengsong forest.

Key words: basal area, CO2 production, elevation, slope, tropical forest, Yunnan

INTRODUCTION

ESTIMATION OF CARBON STOCK IN

tropical forests and the factors influencing

the production of CO2 is a widely

discussed topic in the current era of

climate change. The past century has

witnessed a marked increase in

atmospheric carbon dioxide concentrations

and a concomitant ‘greenhouse warming’

that has drawn scientific attention to the

link between global carbon stocks and

climate change (Cox et al. 2000). And

there has been increasing interest in the

quantification of the biomass of forest

ecosystems and its potential carbon

fixation (Chave et al. 2005, Fearnside,

1996, Schulp et al. 2008 and Sierra et al.

2007).

Soil organic matter is an important

component that represents a carbon (C)

pool three times larger than that of the

atmosphere (GCTE 1996). The litter from

trees is one of the major factors that

contribute to the CO2 production in the soil

surface of tropical forests. Contribution to

soil respiration of different factors that are

related to plants, especially the Above

Ground Biomass (Kanowski, 2010), root

(Matamala, 2000) soil and litter

(Phillipson, 1975, Witkamp, 1961), have

caught the attention of many researchers.

Carbon stocks of forest trees are

well studied in terms of carbon

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sequestration (Brown S., Lugo A.E. 1982,

Clark D.A. et al. 2001, Dixon R.K.,

Houghton R.A., 1994, Huet S. et al. 2004,

Kraenzel M. et al. 2003, Le Goff N. et al.

2004, Wu Z.M. et al. 1998). Also there

have been efforts to determine the accurate

characterization of tree carbon (TC), forest

floor carbon (FFC) and soil organic carbon

(SOC) in tropical forests so as to estimate

their contribution to global carbon stocks

(Juan Carlos et al 2010). But the factors

that affect the soil carbon production in

natural forests and the relationship

between different factors such as

topography, species diversity and plant

density, remain little studied.

Hence the present study was carried

out to examine the correlation between

CO2 production in the litter and (1) the

basal area of trees, and (2) the topography

(elevation and slope) in the tropical rain

forest of Mengsong, Yunnan, China. We

hypothesized that he basal area of tropical

forest trees increases the CO2 production

in the litter zone.

MATERIALS and METHODS

STUDY AREA. –The study was

conducted at the forests of Mengsong,

which is a part of Xishuangbanna

Administrative region in Southern Yunnan,

China (fig. 1). The study site is located at

21.510 N, 100.510 E at an altitude that

ranges from 1600m to 1780m above sea

level. The region has tropical rainforest

vegetation comprising both primary and

secondary forest elements and has a

typical monsoon climate (fig. 2).

Fig. 1 Map showing the study site

Fig. 2 Forest site at Mengsong

METHODS.–A total of 6 sites were

selected, of which 4 sites were at the east

side and 2 sites at the west part of the

Mengsong forest. In each site, 2 quadrats

(20x20m each) were set up, one in the

upper part of the mountain and the second

in the lower part of the mountain, close to

the river, keeping an inter-distance of 50m.

The distance between sites was kept at

Xishuangbanna


100m along a trail that followed the same

elevation along the mountain side (fig. 3).

The twelve quadrats were surveyed over a

seven-day period.

Fig. 3 The plot design.

BASAL AREA. –All trees with

dbh>10cm were measured in each 20 X

20m quadrat. The basal area of each

quadrat was calculated by summing up the

basal area of the individual trees (BA of a

tree = 3.14 x (DBH/2)2) and dividing it by

0.04 to get the value per ha. For

multi-stemmed trees, the bole diameter

was measured separately, and then

summed and the basal area was calculated.

MEASUREMENT OF CO2

PRODUCTION IN THE LITTER

ZONE.–The rate of CO2 production in the

litter zone of the forest floor was measured

at five points in each quadrat using a CO2

Gas Analyser (Li-820) with a static

ventilated chamber. The temperature of the

litter zone was also recorded at each

sample point using a digital soil

thermometer. Then the rate of CO2

production was calculated from the slope

of the regression curve, as

micromoles/hr/m2.

SLOPE AND ALTITUDE.–The

slope of each quadrat was measured by

calculating the angle of inclination using a

stick of 1m length (Trigonometry).

Elevation of all the quadrats was also

recorded using a GPS.

STATISTICAL

ANALYSIS.–ANOVA and linear

regression have been adopted for

analyzing the data using R (Version 2.12.0)

software (R Development Core Team

2010). The factorial design was done, to

accommodate the errors.

RESULTS

VARIATION OF NUMBER OF TREES

AND BASAL AREA PER PLOT.–We

measured 352 trees in 12 quadrats

covering both the east and west parts of

Mensong Forest. The upper plots had a

significantly higher number of trees than

the lower plots (Fig. 4A). The basal area

was also higher in the upper plots

compared with the lower plots (Fig.4B).

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Fig. 4 A. Number of trees per quadrat

Fig. 4 B. Basal area per quadrat

VARIATION IN CO2 PRODUCTION

AMONG SITES.–CO2 production was

significantly higher for upper plots than

lower plots (Fig. 5) (Factorial

AnovaP<0.001). The highest CO2

production was ~400 micromoles/hr/m2

(site 2, Fig. 6) while the lowest was 180

micromoles/hr/m2 (site 1).

Fig. 5. CO2 production along elevation.


Fig. 6. CO2 production among sites in Mensong forest.

Fig. 7 Correlation between BA and CO2 production

SLOPE EFFECT ON C02 PRODUCTION

AND BASAL AREA.–Slope didn’t show

a significant correlation between either soil

respiration or basal area in Mengsong

forest.

DISCUSSION

Our results show a very clear positive

relationship between CO2 production and

basal area. When the gradient factor was

considered, there still exist a positive

correlation between CO2 production and

basal area (Prevost-Boure et al. 2009).

Potential causative factor behind this could

be the occurrence of higher basal area and

more number of trees in the upper plots.

The more amount of organic matter

produced in the upper part can cause an

increase in the CO2 production in the litter

zone.

The reason for occurrence of more

number of trees and higher basal area in

the upper part could be attributed to the

history of the forest, as the lower part is

always vulnerable to disturbance.

Another possibility is that there could be

more light available in the upper part than

the lower that could promote better tree

growth. Hence, further research

concerning trees and soil respiration, in the

Mensong forest could consider the effects

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of light and litter depth on soil respiration,

which were not measured in the present

study.

ACKNOWLEDGEMENTS

We would like to place on record our

sincere gratitude to Dr Chen Jin, Director,

XTBG, for providing us the opportunity to

do this study. We thank Dr Chuck Cannon,

Dr Ferry Slik and Dr Rhett Harrison for

their support and comments on our project.

We are deeply indebted to Dr Douglas

Schaefer for his lessons, continuous

encouragement and support during the

field work as well as analysis and

interpretation. We are grateful to Ms Qie

Lan for her advice, comments, critics and

wholehearted support that helped us to

complete this work.

LITERITURE CITED

Brown S., Lugo A.E., The storage and production of organic matter in tropical forests and their role in the global carbon cycle, Biotropica 14 (1982) 161–87. Chave et al. 2005 J. Chave, C. Andalo, S. Brown, M. Cairns, J. Chambers, D. Eamus, H. Fölster, F. Fromard, N. Higuchi and T. Kira, Tree allometry and improved estimation of carbon stocks and balance in tropical forests, Oecologia 145 (2005), pp. 87–99. Clark D.A., Brown S., Kicklighter D.W., Chambers J.Q., Thomlinson J.R., Ni J., Holland E.A., Net primary production in tropical forests: an evaluation and synthesis of existing field data, Ecol. Appl. 11 (2001) 371–384. Cox, P.M., Betts, R.A., Jones, C.D., Spall, S.A., Totterdell, I.J., 2000. Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model. Nature 408, 184–187.

Dixon R.K., Houghton R.A., Carbon pools and flux of global forest ecosystems, Science 263 (1994) 185–190. Fearnside, 1996 P. Fearnside, Amazonian deforestation and global warming: carbon

stocks in vegetation replacing Brazil's Amazon forest, Forest Ecology and Management 80 (1996), pp. 21–34. GCTE (1996) Effects of Global Change on

Soils: Implementation Plan. Activity 3.3, Report no. 12. GCTE Huet S., Forgeard F., Nys C., Above- and belowground distribution of dry matter and carbon biomass of Atlantic beech (Fagus

sylvatica L.) in a time sequence, Ann. For. Sci. 61 (2004) 683–694. Juan Carlos Loaiza Usugaa, Jorge Andrés Rodríguez Torob, Mailing Vanessa Ramírez Alzateb, Álvaro de Jesús Lema Tapiasc, Estimation of biomass and carbon stocks in plants, soil and forest floor in different tropical forests, Forest Ecology and Management 260 (2010) 1906-1913. Kanowski, J & Catterall P., 2010. Carbon stocks in above-ground biomass monoculture plantations, mixed species plantations and environmental restoration plantings in north-east Australia. Research Report 1442, 119-125. Kraenzel M., Castillo A., Moore T., Potvin C., Carbon storage of harvest-age teak (Tectona grandis) plantations, Panama, For. Ecol. Manage. 173 (2003) 213–225. Le Goff N., Granier A., Ottorini J., Peiffer


M., Biomass increment and carbon balance of ash (Fraxinus excelsior) trees in an experimental stand in northeastern France, Ann. For. Sci. 61 (2004) 577– 588. Matamala, R. & Schlesinger, W., 2001. Effects of elevated atmospheric On root production and activity in an intact temperate forest ecosystem. Global Change Biology 6, 967-979. Phillipson, J. ,Putman,J. & Woodell R. J., 1975. Litter input, litter decomposition and the evolution of carbon dioxide in a beech woodland-wythman woods. Oecologia 20, 203-217. Prevost-Boure C. N., Soudania, K., Damesina, C., Lata J.C.& Dufresne E, 2009. Increase in aboveground fresh litter quantity over-stimulates soil respiration in a temperate deciduous forest. Applied of Soil Ecology 46, 26-34. Schulp et al. 2008 C. Schulp, G. Nabuurs,

P. Verburg and R. de Waal, Effect of tree species on carbon stocks in forest floor and mineral soil and implications for soil carbon inventories, Forest Ecology and Management 256 (2008), pp. 482–490. Sierra et al. 2007 C. Sierra, J. del Valle, S. Orrego, F. Moreno, M. Harmon, M. Zapata, G. Colorado, M. Herrera, W. Lara and D. Restrepo, Total carbon stocks in a tropical forest landscape of the Porce region, Colombia, Forest Ecology and Management 243 (2007), pp. 299–309. Witkamp,M. & Van der Drift, J.,1961. Breakdown of forest litter in relation to environmental factors. Institute for Biological Research 4, 295-311. Wu Z.M., Li Y.D., Zeng Q.B., Zhou G.Y., Chen B.F., Du Z.H., Lin M.X., Carbon pool of tropical mountain rain forests in Jianfengling and effect of clear-cutting on it, Chinese J. Appl. Ecol. 9 (1998) 341–344.

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Do Environmental Factors Influence the Density of Invasive Species?

Yayan Wahyu C Kusuma1, Luo Yahuang

2, Choe Kumchol

3

1Bogor Botanic Garden, Jl. Ir. H. Juanda No. 13, Bogor, West Java, Indonesia 2 Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Menglun, Mengla, Yunnan 666303, China 3 Kunming Institute of Botany,

Abstract

China is especially vulnerable to the establishment of invasive species of foreign origin due to its increasing international trade that facilitate the weed dispersal. Rapid expansion of invasive plants in agricultural land and natural ecosystems is threatening biodiversity, productivity, and ecosystem health. The objective of this study is to determine which environmental factors influence the density of invasive plant species. Single factor ANOVA, and Linear Model Regression were employed to analyze the relationship between invasive and native plant density and environmental factors, as well as possible competition between invasive and native plants. We did this study in Bulong Nature Reserve, in the forest and stream area. The results show that canopy cover plays an important role in determining A.

adenophora density in two different habitat types. Competition among plants did not significantly affect the density of A. adenophora. However, other environmental factors such as precipitation and moisture might be important and should be considered in further research. Keywords: Ageratina adenopohora, canopy cover, forest edge, Mengsong, soil compaction

INTRODUCTION

CHINA CURRENTLY UNDERGOES A

rapid economic development and

increasing international trade, which may

lead to the spread of weeds and invasive

species. Such activities include the

construction of new roads and railways,

increased disturbance, nonecological

construction had increased (intentional)

species introduction (Liu et al.2003;

Lo´pez-Pujol et al. 2006). With a wide

range of habitats and environmental

conditions, China is especially vulnerable

to the establishment of invasive species of

foreign origin (Xie et al. 2000). Rapid

expansion of invasive plants in agricultural

land and natural ecosystems is threatening

biodiversity, productivity, and ecosystem

health.

In China, a total of 108 plant species

have been identified as alien weeds, of

which 15 are distributed throughout most

regions or the whole country (Qiang and

Cao 2000). One of the most notable

invasive plants is crofton weed (Ageratina

adenophora Spreng (King & Robinson), a

perennial herb native to Mexico, Central

Do Environmental factors Influence the Density of Invasive Species

America. It naturally spread into southern

Yunnan province of China from Myanmar

around the 1940s (Xie et al. 2001). An

extremely rapidly growing perennial shrub,

A. adenophora survives and proliferates

under harsh conditions. When it invades a

new habitat it can cause degeneration of

native plant communities in the new

habitat, changing it into an A. adenophora

mono-culture (Wang, 2005). Another

noxious weed is Ageratum conyzoides L.,

an invasive species that also originate from

South America. This harmful species not

only have bad impact in China but also in

Shivalik Hills, India. It has been reported

that A. conyzoides invasion had reduced

plant diversity significantly (Dogra et al.

2009). However, it still becomes a

question why those invasive species can

spread widely and invade many different

areas. With this research we aimed to

determine which environmental factors

influence the density of this highly

invasive plant species.

METHOD

This study was conducted in a stream and

forest area of Mengsong (21o 29’N, 100o

29’E: 1620 m asl.), which is located in

Bulong Nature Reserve, Yunnan Province,

China. Within the study area three

different habitats were chosen: (1) river

bank (high disturbance level), forest edge

(intermediate disturbance level) and forest

interior (low disturbance level). This river

bank was recently established as new

habitat due to the dam construction in the

downstream. Thus, it can also be called

human induced disturbances. Most of its

species consist of pioneer, grass and

invasive species. A line transect was

established for each disturbance level.

Transect in the river bank followed the

flow of the river. Transect in the forest

edge also followed the shape of the edge.

And transect in the forest was located 20

m from the forest edge transect. At each

transect, points were established in every

100 m distance. Thus, for each transect we

selected 34 points, 100 m from each other.

Plant surveys were carried out using point

centered quarter method.

Densities of the invasive alien plants

Ageratina adenophora Spreng (King &

Robinson) and Ageratum conyzoides L and

that of native plants and grasses were

measured at each sampling point using the

point centered quarter method. At each

point, four quadrants were specified using

a compass, and in each quadrant, the

distance from the mid-point to the nearest

individual of each plant category (native

plant, grasses and invasive plant) was

measured. At each point, environmental

variables (canopy cover, soil toughness,

and soil moisture) were also measured

with four replicates (Fig. 1). Each replicate

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located in each quadrant (there were 4

quadrants at each point).

Density was estimated using this

formula:

where, D = Density

A = specified area (i.e. 1 m2)

d = average distance the plant

from point center (m)

Fig. 1. Transect and plot layout for vegetation sampling.

Canopy cover was estimated using an

improvised aluminum can with 9 holes in

its bottom. The observer held the can

straight up and counted the number of

shaded holes as an estimate of the canopy

cover. Soil toughness was estimated using

a soil penetrometer. The one-kilogram

metal weight was dropped three times and

the depth of penetration was recorded,

which is inversely correlated with the soil

toughness.

Soil moisture was measured by

collecting a (approximately 20 g.) soil

sample from each point. Fresh and dry

weight of the soil sample was measured

using an electric balance. Water content

(soil moisture) was calculated using the

following formula: Water content = (Fresh

weight – Dry weight)/Fresh weight.

DATA ANALYSES

Single factor ANOVA was employed to

compare the density of plants (A.

adenophora, A. conyzoides, native plant,

and grasses) between habitats. The same

analysis was also applied for the

environmental factors. A quasi-Poisson

GLMs was used to detect the correlation

among variables due to non normal

distribution and overdispersion, especially

between plant densities and environmental

factors and between different plant

densities. Model selection was done in


backward selection using Akaike’s

Information Criterion (AIC). Started with

the most complex model and reduce the

most insignificant variable, and at last

compare the whole model based on AIC.

Then, Nonmetric Multi Dimensional

Scaling (NMDS) was also employed to

explore the dissimilarities among sites,

based on plant community composition

and environmental factors in order to

support and explain the GLMs model in

ordination.

All analyses were conducted in R

software version 2.12.0 (R Development

Core Team 2010).

RESULT

Densities of all plant types were

significantly different among habitats

except for A. conyzoides (Table 1). Native

plants had the highest density in all habitat

sites. Most of these native plants were

represented by pioneer species, such as

Sida sp, Polygonum spp, and other

creeping herbs. Both invasive plant

species had highest densities in the forest

edge, while A.conyzoides did especially

bad in the forested area.

Table 1. Comparison of mean density and standard error of all plants in each site.

Sites

A.

adenophora***

A.

conyzoides

Native

plant** Grasses**

Bank 0.34±0.09a 0.88±0.28ns 58.90±18.39b 2.86±0.47a

Edge 6.35±1.33b 2.50±1.26ns 12.18±2.73a 2.15±0.27a

Forest 0.40±0.24a 0.04±0.03ns 13.79±2.01a 0.67±0.12b

* p<0.05, ** p<0.01, ***p<0.001

The result of a quasi-Poisson GLMs

showed that environmental factors had

significant effect on the invasive plant

density. Density of A. adenophorum was

significantly affected by canopy cover and

interaction between canopy cover and soil

toughness (Table 2). Whilst, A. conyzoides

only significantly affected by soil

toughness (Table 3). Density correlation

among plants that correspond to

competition was not detected.

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Table 2. GLM with a quasi Poisson distribution of the effect of canopy cover, soil moisture, soil toughness, and interaction between them on Density of A. adenophorum.

GLM Model selection Predictor variable

t df P

intercept 1.771 101 0.07968

Can_cov (CC) 3.273 101 0.00147

So_moi (SM) 0.061 101 0.952

So_tou (ST) -0.750 101 0.4554

CC x SM -1.323 101 0.18889

SM x ST 0.330 101 0.7418

CC x ST -3.220 101 0.00173

SM x CC x ST 0.655 101 0.51416

Variables included in the final model are in bold. Significant P-values are in italic

Table 3. GLM with a quasi Poisson distribution of the effect of canopy cover, soil moisture, soil toughness, and interaction between them on Density of A. conyzoides.

GLM Model selection Source

t df P

intercept 2.419 101 0.0174

Can_cov (CC) -1.342 101 0.1826

So_moi (SM) -1.400 101 0.16478

So_tou (ST) -2.163 101 0.0329

CC x SM -1.273 101 0.2059

SM x ST 0.409 101 0.6835

CC x ST 1.013 101 0.3138

SM x CC x ST -0.523 101 0.602

Variables included in the final model are in bold. Significant P-values are in italic

For NMDS analysis forest data were

excluded due a lot of zero which caused by

inconsistent condition of the forest itself.

Most of the area inside the forest was

already converted into tea plantation with

varying environmental conditions. The

result showed that density of all plant

types were difference indicated by clearly

separated cluster for each plant type. Each

plant types also had different preference

on environmental factors. The density of A.

adenophora was influenced by canopy

cover and interaction between canopy

cover and soil toughness as suggested by

quasi Poisson GLMs. While, density of A.

conyzoides was only influenced by soil

toughness (Fig. 1). This was also in line

with the result of quasi poisson GLMs.


Fig. 1. NMDS of plant density and environmental factors in bank and edge

DISCUSSION

The study by Wang et al. (1994) suggested

that light stimulates germination of A.

adenophora seeds, thus it is highly

effective in invading heavily disturbed

areas such as river banks and forest edges.

However, Lu et al. (2006) found that in the

invaded regions A. adenophora seeds

preferred to germinate under relatively

cool conditions. Our study confirmed that

A. adenophora is most abundance in the

forest edge area, which is considerably

cooler and more shaded than in the river

bank (open) area. Nevertheless, once

established A. adenopohora will also grow

well in shaded areas (Sang et al. 2010).

This also confirms what Fang Hao et al

(2010) found, that A. adenophora is highly

adaptable to environmental extremes such

as (low) temperatures and drought.

Competition did not seem to be a

significant factor for the distribution of A.

adenophora. Hao (2010) and Yang (2008)

found that A. adenophora is allelopathic.

Its allochemicals can inhibit the growth

and development of the native plants. It

can thus effectively neutralize the

competition by other plant species.

However, the abundance and

distribution of invasive plant species such

as A. adenophora or A. conyzoides are not

only affected by light intensity, other

environmental factors such as precipitation

and moisture (Zhu et al. 2007, Sang, 2010)

may also play a role. Moreover, our result

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confirmed previous research that

environmental factors have influence on

the density of invasive plant which

improve their ability to spread and invade

many parts of the world. Nevertheless,

more precise measurement and more

environmental variable are needed in

future research to better explain which and

how environmental factor affect the

density and distribution of invasive plant.

ACKNOWLEDGEMENT

We are greatly indebted to Prof. Chen Jin

(Director of XTBG) for providing us the

great opportunity to attend the AFEC 2010

course. A big bunch of thanks to Prof.

Chuck, Prof. Ferry, Dr. Doug, also Lainie,

and Allen for giving us a lot of help and

suggestion during this project. We also

want to thankful to Dr. Rhett, Dr. Jacob,

and Professors in XTBG for all the

lectures. To all of AFEC 2010 students,

thanks so much for the joyful moment that

we shared during the course.

LITERATURE CITED

Dogra, K.S, R. K. Kohli, S. K. Sood, & P. K. Dobhal. 2009. Impact of Ageratum conyzoides L. on the diversity and composition of vegetation in the Shivalik hills of Himachal Pradesh (Northwestern Himalaya), India. International Journal of Biodiversity and Conservation Vol. 1(4) pp. 135-145

Fang Hao, W., L. Wan Xue, G. Jian Ying, Q. Sheng, L. Bao Ping, W. Jin Jun, Y. Guo Qing, N. Hong Bang, G. Fu Rong, H. Wen Kun, J. Zhi Lin, W. Wen Qi. (2010). Invasive mechanism and control strategy of Ageratina adenophora (Sprengel). Sci China Life Sci (53)11: 1291-1298.

Lo´pez-Pujol J, Zhang FM, Ge S (2006) Plant biodiversity inChina: richly varied, endangered, and in need of conservation. Biodivers Conserv 15:3983–4026

Lu P, Sang W, Ma K (2006) Effects of environmental factors on germination and emergence of Crofton weed (Eupatorium

adenophorum). Weed Sci 54:452–457

Qiang, S., X. Y Cao. 2000. Survey and analysis of exotic weeds in China. J Plant Resour Environ 9:34–38

Qing Yang, Q., F. Hao Wan, W Xue Liu, J Guo. 2008. Influence of two allelochemicals from Ageratina

adenophora Sprengel on ABA, IAA and ZR contents in roots of upland rice seedlings. Allelopathy journal 21 (2):253-262.

R Development Core Team (2010). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org.

Ren, D. R. 2000. Atlas of China. China Cartographic Publishing House, Beijing

Sang, W., L. Zhu, J. C. Axmacher. 2010. Invasion pattern of Eupatorium

adenophorum Spreng in southern China. Biol Invasions (12).1721-1730

Wang HJ, He P, Ma JL (1994) An investigation and research report on the dissemination of Ageratina

adenophora on rangeland areas in Liangshan District of


Sichuan Province. Grassland China 1:62–64

Wang, J.J. 2005. Ageratina adenophora (Spreng.). In: Wan FH, Zheng XB, Guo JY (eds) Biology and management of invasive alien species in agriculture and forestry. Science Press, Beijing, pp 651–661

Xie, Y., Y.Z. Li, W. P. Gregg, D. M.

Li.2001. Invasive species in China - an overview. Biodivers Conser 10:1317–1341

Zhu, L., O. J. Sun, W. Sang, Z. Li, K. Ma. 2007. Predicting the spatial distribution of an invasive plant species (Eupatorium

adenophorum) in China. Landscape Ecol (22): 22=1143-1154

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The Distribution Patterns of Birds in Tropical Riparian Forest of Mengsong

Liu Xiaohu 1, Peabotuwage Indika umara 2, O InYong 3 1Kumming Institute of Zoology, Chinese Academy of Sciences, Kunming, China 2 The Open University of Srilanka 3 Central Forest Design and Technical Institute. DPR Korea Abstract

In this study we conducted a preliminary survey on birds in one primary and one secondary forest sites in Mengsong, Yunnan province, China. To test for the effect of distance from river on the bird abundance, point transects of 200 m were set up from the river to the forest. At each point, we also recorded the number of flowering and fruiting trees, basal area, and canopy cover as covariates. Results suggest that bird abundance decreased with increasing distance from river. Although limited by sample size, our study suggests that the forest riparian zone is of particular importance for bird conservation.

Keywords: Avian diversity, Frugivory, Hunting, Point count, Riparian habitat

INTRODUCTION

The study was conducted in the forest

area of Mengsong, Yunnan province

(From 6th December to 10th December).

The annual rainfall is 1600-1800 mm

and the annual temperature is 18-19°C

(Z.Wang & C.Chris, 1998). Natural

vegetation types are tropical evergreen

rain forest, Mountain rain forest and

secondary forest. In Mengsong, the

indigenous people living in close

vicinity of the forest are Hani people,

and most of them live from agricultural

activities. They are combing with the

Mengsong forest from many years ago

and it has a long history.

Tropical forest forms a main

resource for the conservation of

biodiversity. Especially, tropical

riparian areas are often important

habitats for birds, particularly in

semi-arid of seasonally dry

environments (Woinarski et al. 2000).

So far, many studies have usually

focused on large streams or rivers over

broad geographical scales, where

riparian zones are often associated with


distinctive vegetation (Lock& Naiman

1998,Woinarski et al.2000, Harvey et

al.2006). However, riparian zones

along small streams within a tropical

forest matrix may also be important

habitats for birds (Naiman et al.2005,

Ballinger & Lake 2006).

Through this research, we

compared and analyzed the diversity of

birds in riparian areas of primary forest

& secondary forest, Mensong in

Yunnan Province.

METHOD

STUDY AREA. –The study was

conducted in the tropical rain forest

area of Mengsong, Yunnan province

china, From 6th December to 10th

December 2010

(100°28’26.5”-100°28’38.1”E,

21°30’35.8”-21°30’59.7”N). This

mountain range is a part of the

Indo-Burma biodiversity hotspot and is

recognized as a high priority area for

biodiversity conservation.

Sampling plot was situated in the

primary and secondary forest in

Mengsong. (Fig. 1).

Fig. 1

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Fig. 2

BIRD SURVEY. –We set up four

point transects each within primary and

secondary forest. Each transect was

200 m long, approximately

perpendicular to the stream, consisting

of five points, 50 m apart (Fig. 2). At

each point, birds seen and heard within

25 m from the observers were recorded

for 10 min duration. Bird species and

number of individuals were recorded.

We also recorded all flowering and

fruiting trees with 25 m from each

point. Birds were surveyed every day

between 9 am and 12 am for five days.

All point transects were surveyed on

each day following a random order.

For each point, we also measured

distance from river, basal area, canopy

cover, elevation and Geographical

position.

Data analyzed using R software 2.6.0

(R Development core team 2005).

RESULT

We recorded nine bird genera in the

primary forest and 13 genera in the

secondary forest. There were 17

common bird species with more than

10 individuals recorded, including

mainly barbets (Megalima spp.) and

bubuls (Hypsipetes spp.).

We tested the effects of canopy

openness, basal area, distance from

fruiting and flowering trees, number of

fruiting and flowering trees on number

of bird species at survey points, but

found no significant patterns. The

distance from stream was the most

significant factor and bird abundance

decreased with increasing distance

from river (Fig. 3), and effect of the


distance is not affected by forest type.

The distance from the stream was also

correlated to the number of flowering

and fruiting trees.

Fig. 3

DISCUSSION

Riparian zones are frequently

characterized as ecologically

significant corridors that contribute to

the maintenance of high biodiversity in

landscapes (e.g., Gregory et al. 1991,

Naiman et al. 2005). Fruit and nectar

feeding birds are dominant species in

the study area in winter. We found that

fruiting and flowering trees were

distributed in higher abundance closer

to the riparian zone in Mengsong.

Resource availability is likely to be a

significant factor affecting the

diversity and abundance of birds in

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primary and secondary forest. Our

results suggest the importance of

riparian zone as important area for the

conservation of forest birds.

Local peoples in Mengsong still

hunt birds in this area and three species.

Great Barbet (Megalaima virens),

Blue-throated Barbet (Megalaima

asiatica ), and Black Bulbul

(Hypsipetes leucocephalus) and among

the most hunted species. Populations

of these species are believed to be

stable at present; however, their

numbers may decrease in the future.

This study was limited by time

and sample size. More extensive

studies should be conducted to

determine the value of other riparian

habitats for forest birds, in which the

effect of hunting should be taken into

consideration.

ACKNOWLEDGEMENT

We wish to thanks Prof: Chen Jin

(Director XTBG), Prof: Ferry Slik

(AFEC-X organizer), Prof. Chuck

Cannon, Prof. Rhet Harrison, Prof.

Douglas Schaefer and Dr Jacob

Wiekham for gave this opportunity.

We also thank to Dr Qie Lan, Mr. Liu

Yalou, Ms Vivian Fu, Ms Shi Lingling,

in AFEC-X organizing committee

2010. Finally, we thank Mr Ai Jiao for

his kind help (forest manager in

mongsong).

LITERITURE CITED

W.Zhijun and C. Carpenter.1999., Forest landscape and bird diversity in mountain region, Xishuangbanna, Yunnan, Chinese geographical science, Vol: 09, No: 02, pp 172-176.

E.K.W. Chan, Y.T. Yu, Y. Zhang and

D. Dudgeon, 2008., Distribution patterns of birds and insect prey in a tropical riparian forest., Boitropica., pp1-7.

D.M.S. Karunarathna, A.A.T. Amarasinghe, P.I.K. Peabotuwage and A.A.D.A.Udayakumara., 2007. A study of the non-captive Avifaunal diversity in the National Zoological Gardens, Dehiwala, Sri Lanka. Siyoth. Vol 2 2 pp25-29.

M.Pliosungnoen. 2007., Lantana fruit

removal by birds in Xishuangbanna Tropical Botanical Garden, China., CTFC . AA International Field Biology Course. XTBG.,


pp106-111. L. Boonsong and R.D. Phillip., A guide to the birds of Thailand.

J. Mackinnon & K. Phillipps., 2000.A field guide to the birds of China.

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Changes in Plant Community Trait Composition of Understory Trees:

Mengsong Seasonal Tropical Rainforests, Yunnan, China.

Beng Kingsly Chuo 1, Ryom Song Hwan 2, Wu Junjie3 , Amornrat Pitakpong4 1Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Menglun, Mengla, Yunnan 666303, China 2Central Forest Design and Technical Institute. DPR Korea, 3Kumming Institute of Botany, Chinese Academy of Sciences, Kunming, China 4School of Biology, Institute of Science, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand. Abstract Tropical forests serve as biodiversity storehouses, providers of ecosystem services and sequestration of carbon among other functions. To fully understand the roles played by plant communities in these forests, knowledge about plant traits at the species, individual, population and community levels is required. These traits have been proven to vary with changes in environmental conditions. Understanding how and why they vary is important because they represent the fundamental basis of species survival and reproduction. Changes in plant community trait composition remain an interesting research topic despite many years of intensive research. Although trait variation has been widely studied, with different researchers working at different scales and focusing on different components of variation in different environmental conditions, much still needs to be done on this field. To address this problem, we studied changes in average tree height, dbh, leaf length, width, thickness, fresh weight, petiole length, margin, tip and base across 20 plots in the east and west tropical rainforests of Mengsong, Yunnan, China. In each forest, we established 10 plots on both sides along a small forest trail (topographic gradient). Each plot had a 20m transect perpendicular to the trail (east forest) and parallel to the dam (west) in a 20X10m area (disturbance gradient/edge effect). 20 plants were sampled along (20m) and within 1m on both sides of the transect. Two leaves were collected from the 3rd node of 2 separate branches for each tree. We measured light intensity (canopy opening), soil litter thickness and elevation in the field. From our correlation results using SPSS 17.0, leaf length, fresh weight and basal area correlated negatively with light; leaf width, fresh weight and basal area had a positive correlation with length; while DBH and tree height were positively correlated. These findings suggest that plant communities reduce their leaf sizes at high light intensities and increase leaf sizes at low light intensities. Keywords: functional traits, leaf length, light, plant community, tropical forest,

Changes in Plant Community Trait Composition of Understory Trees: Mengsong Seasonal Tropical Rainforest, Yunnan, China

understory trees

INTRODUCTION

Leaves are above-ground plant organs

specialized for the process of

photosynthesis. As such, they are very

essential for plant growth,

development and survival in different

habitats. However, they occur in

various shapes and sizes. This wide

variety of morphological features

equally accounts for the world’s plant

diversity. Plant functional traits are

features that determine the adaptations

and survivor of plants in various

environments and to different

conditions. Leaf traits on the other

hand are characteristics that assist in

the proper functioning of leaves and

include; area, length, width, thickness,

fresh weight, dry weight, petiole length,

margin, base, tip, venation etc. Many

studies have proven that plants alter

their leaf shape and sizes as a result of

changes in their environmental

conditions (e.g. Deschamp & Cooke,

1985; Emery et al 1994). Meanwhile

Givnish (1987) reported variation in

leaf morphology with changing light

intensity between species; Winn &

Evans (1991) also proved that light

availability is an essential

environmental condition that varies

both within and between populations;

and Winn (1999) reported the ability of

individual plants to appropriately

modify their morphological traits

under different moisture conditions.

Understanding how and why

these traits vary across plant

communities is as important as their

role in plant productivity and ecology.

Therefore, we must link the different

components of trait variation with

variation across communities so as to

bridge the gap between other aspects

of trait variation and changes in plant

community variation. This will give us

a common and wider scope of

knowledge on this subject. As a step

towards addressing this issue, we

studied changes in plant community

trait composition for some selected

traits across 20 plots in the east and

west tropical rainforests of Mengsong,

Xishuangbanna, Yunnan, Southwest

China.

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37

QUESTIONS. –How do light intensity,

topography, elevation and litter

thickness affect leaf functional traits of

understory plant communities? Does

low light intensity account for

decreased leaf thickness in understory

trees? What relationship exists

between leaf dimensions and light

intensity in understory plants?

OBJECTIVES . –To investigate the

effect of light intensity, topography,

elevation and litter thickness on

understory community leaf trait

variability.

HYPOTHESIS . –Variation in canopy

cover and subtle changes in light

availability in the forest understory

affect leaf traits and we hypothesize

that smaller-leaved species turn to

occur in higher-light environments.

EXPERIMENTAL DESIGN

STUDY SITES . –Mengsong is located

in Menghai county, Xishuanbanna,

Yunnan province, Southwest China.

This area borders Myanmar, Laos and

Vietnam with a subtropical climate

influenced by the Indian monsoon. The

annual mean temperature is about

18°C while the annual mean rainfall is

between 1600–1800 mm, 80% of

which occurs between May–October

(Xu et al 2009). The three main forest

types in this area include; (1)

South-subtropical evergreen broadleaf

forest, (2) Tropical-montane rainforest

and (3) Tropical-seasonal rainforest

(Zhang and Cao 1995). The Mengsong

forest area lies at elevations between

approximately 1500 and 1800m with

an undulating topography. Several tea

plantation patches occur around and

within the forest stands while a large

dam is situated near the west forest.

This dam is normally full of water

(almost same level as the forest flow)

flowing from the Mekong river but

was opened last year to release the

water for reconstruction. This has

created a huge edge effect at the forest

edge. However, a small quantity of the

water was retained in the dam during

the reconstruction period. This created

a disturbance gradient along the forest

and a kind of new habitat for plant

species now growing in and around the


dam.

PLOT SAMPLING . –We selected two

forest stands in the Mengsong seasonal

rainforest, one in the east and another

in the west (near the dam) to determine

the influence of disturbance gradient

on leaf traits. In each forest, we

established 10 plots on both sides

(left=top and right=valley/ridge) of a

small forest trail to investigate the

effects of topography on leaf traits.

Each plot had a 20m transect

perpendicular to the trail (in the east

forest) and parallel to the dam (in the

west forest) and a 20X10m area. For

each transect, we sampled the first 20

understory trees within 1m on either

sides from the transect line and with

dhb 5cm and height 5m. In each

20X10m area, we measured the

diameter of all trees with dbh 10cm to

estimate the basal area for that plot.

The distance between the plots and the

trail was at least 5m while the distance

between 2 plots was at least 100m.

Provincial capital

Mengsong, Xishuangbanna

Provincial and International boundaries

Mekong River

Dam

Tropical forest

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TRAIL

dbh 10cm tree

understory tree

transect

Dam

Island (area of land surrounded by water.

Small plants (grasses, herbs, shrubs)

Small stream/ water flow

SAMPLE COLLECTION . –We

collected 2 leaves (photosynthetic units)

each from the 3rd node of 2 separate

branches on the same tree and measured

their length, width, fresh weight, thickness,

petiole, etc immediately after field

collection.

20m 20m

10m

2m

100m T

RA

IL

LEFT

TOP

RIGHT

VALLEY/RIDGE

• Water

Island

FOREST

EDGE

N


MEASUREMENTS AND

EQUIPMENT . –Tape/ruler: leaf

length, width, petiole length, tree

height, litter thickness and GBH

1. Digital caliper: DBH, leaf

thickness

2. Precision scale: fresh weight

3. GPS: elevation (single)

4. Beer can: We completely cut out

one end of the can and used a nail

to bore 10 small holes on the other

end. Each small hole therefore

represented 10%. During

observation, we used transparent

tissue paper to cover the open end,

then look directly into the canopy

using a single eye repeatedly at

different points along the transect.

We counted the number of holes

open (not blocked by the canopy)

for each point and calculated the

average per plot.

DATA ANALYSIS

For each leaf trait, an arithmetic

average was calculated per tree from

Alternate Compound Opposite Whorled

Tape/ruler

DBH Beer can

Digital

caliper

Precision

scale

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two sampled leaves and then the final

arithmetic average was computed per

plot. A correlation analysis was

performed between the leaf traits and

environmental variables based on

overall plant community changes,

disturbance and topographic gradients

using the SPSS 17.0 statistical

software. We used a dendrogram

according to Minitab 16.0 statistical

software to visually represent our

correlation data. The individual plots

and variables are arranged along the

bottom of the dendrogram according to

their level of correlation. Highly

correlated variable clusters had a

correlation value close to 1 and thus

D=1-C was close to zero

(D=correlation distance and

C=correlation coefficient/value). As

such, highly correlated clusters are

nearer the bottom of the dendrogram.

Variable clusters that are not correlated

had a correlation value close to zero

and a corresponding distance value

close to 1. We did Principal

Component Analysis tests for all the

leaf traits, all the environmental

variables and for both traits and

environmental factors combined.

RESULTS

Variations in leaf length were

correlated with light, basal area, leaf

width and fresh weight (Pearson

correlation, p 0.005) when overall

plant community changes were

considered. Fresh weight equally

correlated with light and the relative

distance between the plants along the 20m

transect (Table 1).

Though light intensity is

significantly negatively correlated with

leaf length and fresh weight, it might

not be the only factor affecting these

traits. It was therefore necessary to

further investigate the level of

disturbance (disturbance gradient) and

the type of habitat (topographic

gradient) occupied by these plant

communities. According to our results

and with respect to the history of

disturbance in the east and west forests,

neither leaf length nor fresh weight

correlated with light intensity in the

east forest plant communities.

However, in the west forest, leaf length

correlated with light and basal area,

fresh weight and leaf width correlated


with soil litter thickness while

elevation correlated with DBH (Table

2).

With respect to their habitats,

plant communities did not show any

significant changes in traits with light

intensity or basal area in the top

topography but elevation was rather

correlated with leaf length, tree height

and light intensity. Meanwhile a more

usual pattern was observed in the

ridge/valley plant communities where

leaf length correlated with light and

basal area, and petiole length

correlated with soil litter thickness and

leaf width (Table 3).

Table 1 Combined east and west forests plant community changes

Variables Pearson correlation Sig. (2-tailed) Width .675** .001 Fresh weight .711** .000 Light -.605** .005

Length

Basal area .689** .001 Width .791** .000 Light -.460* .041

Fresh weight

Trans-X .533* .015

Height DBH .812** .000

Basal area Light -.636** .003 **Correlation is significant at the 0.01 level (2-tailed)

*Correlation is significant at the 0.05 level (2-tailed)

Trans-X is the relative distance between the plants along the 20m transect (X-axis)

Table 2 East forest plant community variations

Variables Pearson correlation Sig. (2-tailed) Width .947** .000 Length

Fresh weight .732** .016 Width .860** .001

Petiole length -.683* .029

Fresh weight

Trans-X .660* .038 Height DBH .770** .009

West forest plant community variations

Light -.650* .042 Length Basal area .724* .018

Width .703* .023 Fresh weight

Litter thickness -.797** .006

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Trans-Y .702* .024 Width Litter thickness -.647* .043

Height .882** .001

-.707* .022

DBH

Elevation

Trans-Y is the relative distance between the plants within 1m on both sides of the 20m transect.

Table 3 Top topography plant community trait variation

Variables Pearson correlation Sig. (2-tailed) Width .958** .000 Fresh weight .755* .019 Height .672* .048

Length

Elevation .721* .029 Width .784* .012 DBH .833** .005

Height

Elevation .690* .040 Fresh weight .676* .045 Trans-X

Petiole length -.718* .030

Light -.756* .018 Elevation

Trans-Y -.825** .006 Trans-Y Fresh weight -783* .013

Ridge/valley plant community trait variation

Fresh weight .615* .044

Light -.786** .004

Length

Basal area .748** .008 Fresh weight .837** .001 Width

Petiole length .683* .021

Petiole length Litter thickness -.709* .015

Height DBH .918** .000

Basal area Light -.667* .025

PLANT COMMUNTY TRAITS AND

LIGHT INTENSITY . –Plant

community traits and light

environment had a large effect on leaf

morphology. All leaf traits differed

strongly among communities (P <

0.001), and light had a significant

effect on 2 of 5 leaf traits. It appears

there was a significant basal area and

light as well as fresh weight and light

interactive effects for 3 of 5 leaf traits.

Light did not have a significant direct


or interactive effect on leaf thickness

and petiole length; tree height and

DBH. This indicates that these traits

had similar responses to light in the

different plant communities (Fig. 1).

Fig. 1: Cluster diagram showing the correlation patterns between plant traits and

environmental factors.

Apart from the correlations obtained between plant traits and environmental factors, there were also significant

correlations among the traits (Fig. 2) and among the environmental factors (Fig. 3).

Variables

Deg

ree

of

corr

ela

tio

n

Complete Linkage, Absolute Correlation Coefficient Distance

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Fig. 2: Cluster diagram showing correlations among plant traits

Fig. 3: Cluster diagram showing the correlation pattern among environmental conditions.

Plant traits

Deg

ree

of

corr

ela

tio

n


Environmental factors

Deg

ree

of

corr

ela

tio

n



It was equally important to know how

these plant communities vary or have

similar/common patterns across all the

plots despite their disturbance history

and habitat differences (Fig. 4).

Fig. 4: Cluster diagram show the degree of similarity among the 20 plots studied.

DISCUSSION

Leaf trait variation was mainly related

to differences in light availability.

According to Whitmore (1996), light is

considered to be the most limiting

resource for tree growth and survival

in tropical wet forests and a major axis

of differentiation for tropical tree

species (Lars Markesteijn et al 2007).

Our results showed a clear pattern of

decreasing leaf length with increasing

light intensity. Since light is a limiting

factor for growth in shaded understory

plant communities, trees growing in

these shaded areas enhance their light

interception by producing relatively

large leaves (Evans & Poorter, 2001).

Plant communities studied equally

demonstrated increasing fresh weight

Plots

Deg

ree

of

sim

ila

rity

Complete Linkage, Pearson Distance

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and basal area values with decreasing

light intensity. Chazdon and Kaufmann

(1993) reported that light acclimation

may be mediated by distinct processes

that involve structural, physiological

and biochemical changes.Though plant

communities may show variation in

leaf traits, these changes may be

important ecological adaptations

relative to environmental conditions

(Andrea et al 2000).

All the leaf traits examined did not

significantly vary with elevation but

when we used a classification matrix

based on variables, top and

ridge/valley communities, leaf length,

tree height and light correlated

positively with elevation. This might

be partly due to the fact that the

elevational gradients (1500-1800m)

were not high enough to influence

these traits. Velázquez-Rosas et al

(2002) analyzed the variation in leaf traits

of dominant tree species in six montane

rain forest communities along an

elevational gradient ranging from 1220 to

2560 m within a single basin at La

Chinantla, Oaxaca, México and found that

leaf area was the only variable that

significantly decreased with elevation.

CONCLUSIONS

Leaf trait variations in plant

communities of seasonal tropical

forests reveal important information

about the complex interactions

between abiotic factors and survival

mechanisms of trees in response to

mechanical stress and increased

resource acquisition. Changes in plant

community traits may not necessarily

be an advantage or a setback. These

might be structurally, biologically or

chemically initiated by the plants to

stabilize their ecosystem and maximize

the resources available.


LITERITURE CITED

C. Li, X. Zhang, X. Liu, O. Luukkanen and F. Berninger, Leaf morphological and physiological responses of Quercus aquifolioides along an altitudinal gradient, Silva

Fenn 40 (2006), pp. 5–13.

Chazdon R. L. Fetcher N.. 1984. Light environments of tropical forests. In E. Medina, H. A. Mooney, C. Vasquez-Yanes, [eds.], Physiological ecology

of plants in the wet tropics, 27-36. W. Junk, The Hague, Netherlands.

Chazdon R. L. Kaufmann S.. 1993.

Plasticity in leaf anatomy of two rainforest scrubs in relation to photosynthetic light acclimation. Functional

Ecology 7: 385-394..[CrossRef]

Deschamp, P.A., and Cooke, T.J.

(1985). Leaf dimorphism in the aquatic angiosperm Callitriche heterophylla. Am. J. Bot. 72, 1377-1387.

Emery RJN, Chinnappa CC,

Chmielewski JG (1994) Specialization, plant strategies, and phenotypic plasticity in populations of Stellaria

longipes along an elevation gradient.

Evans J. R. Poorter H.. 2001.

Photosynthetic acclimation of

plants to growth irradiance: the relative importance of specific leaf area and nitrogen partitioning in maximizing carbon gain. Plant, Cell and

Environment 24: 755-767..[CrossRef]

Fonseca CR, Overton JC, Collins B,

Westoby M (2000) Shifts in trait-combinations along rainfall and phosphorus gradients. J Ecol 88:964-977. dio:10.1046/j

Givnish, T.J. (1979) On the adaptive

significance of leaf form. Topics in Plant Population Biology (eds O.T. Solbrig, S. Jain, G.B. Johnson & P.H. Raven), pp. 375¨C407. Columbia University Press, NewYork.

Knight CA, Ackerly DD (2003)

Evolution and plasticity of photosynthetic thermal tolerance, leaf specific area and leaf size: congeneric species from desert and coastal environments.

Poorter L.. 1999. Growth responses of

fifteen rain forest tree species to a light gradient: the relative importance of morphological and physiological traits. Functional Ecology 13: 396-410.[CrossRef]

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Whitmore T. C.. 1996. A review of some aspects of tropical rain forest seedling ecology with suggestions for further enquiry. In M. D. Swaine, [ed.], The ecology of tropical

forest tree seedlings, 3-39. Programme on Man and the Biosphere, UNESCO series, vol. 17. Parthenon, Paris, France

Velázquez-Rosas, J. Meave and S.

Vázquez-Santana, Elevation variation of leaf traits of montane rain forest tree species at La Chinantla, Southern México, Biotropica 24 (2002), pp. 534–546.

Xu, J., L. Lebel, and J. Sturgeon. 2009.

Functional links between biodiversity, livelihoods, and culture in a Hani swidden landscape in southwest China. Ecology and Society 14(2): 20. [online] URL: http://www.ecologyandsociety.org/vol14/iss2/art20/

Zhang, J. H., and M. Cao. 1995. Tropical forest vegetation of Xishuangbanna, S.W. China and its secondary changes, with special reference to some problems in local nature conservation. Biological

Conservation 73(3):229–

Patticipants

Participants

Miss Amornrat Pitakpong Thailand

Suranaree University of Technology 829 Dech-udom Road, Naimuang, Muang, Nakhon Ratchasima, Thailand. 30000 Email: [email protected] [email protected]

OROU MATILO TIMOTHEE BIO Augustin Benin

Hokkaido University 001-0020, Kitaku-Kita 20, Nishi7-101, Sapporo, Japan. Email: [email protected]

Chemboli Sreenivasan Dhanya India

M S Swaminathan Research Foundation, Community Agrobiodiversity Centre, Puthoorvayal Post office, Kalpetta, Wayanad District, 673121, Kerala, India Email: [email protected]

Eka Aditya Putri Iskandar Indonesia

Indonesian Institute of Sciences, Cibodas Botanic Garden Jl. Kebun Raya Cibodas, Cipanas, Cianjur 43253, Indonesia Email: [email protected]

Participants

51

Peabotuwage Indika Kumara Sri Lanka

The Open University of Sri Lanka NO 143, Hettipola RD, Piduma, Pansal Watta, Kuliyapitiya, Sri Lanka Email: [email protected] / [email protected]

Ryom SongHwan Democratic People's Republic of Korea

Central Forest Design and Technical Institute, Pyongyang, DPRK Email: [email protected]

O InYong Democratic People's Republic of Korea

Central Forest Design and Technical Institute, Pyongyang, DPRK Email: [email protected]

Ri KumRan Democratic People's Republic of Korea

Environment and Development Center, Pyongyang, DPRK Email:[email protected]

Participants

Jo WonJu Democratic People's Republic of Korea

Land Use Planning Institute, Pyongyang, DPRK Email: [email protected]

Choe KumChol Democratic People's Republic of Korea

Land Use Planning Institute, Pyongyang, DPRK Email: [email protected]

Sophany Phauk Cambodia

Royal University of Phnom Penh 63EoD Street 118, Sangkat Tuk Laak I, Khan Toul Kok, Phnom Penh, 12000, Cambodia Email: [email protected]

Luo Yahuang China

Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences , Menglun, Mengla, Yunnan, 666303,China Email: [email protected]

Participants

53

Liu Xiamo China

Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences , Menglun, Mengla, Yunnan, 666303,China Email:[email protected]

Wu Junjie China Kunming Institute of

Botany, Chinese Academy of Sciences 132# Lanhei Road, Heilongtan, Kunming 650204, Yunnan, China Email: [email protected]

Kingsly Chuo Beng Cameroon


Duan Qiong China

Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences , Menglun, Mengla, Yunnan, 666303,China Email:[email protected]

Participants

Iogna Patricia Araceli Argentina U.N.P.S.J.B. –

CONICET Gral Roca 3094/B - B° San Martin Eete KM3 - CP 9005 - Comodoro Rivadavia - Chubut – Argentina Email: [email protected]

Liu Yanjie China

Graduate University of Chinese Academy of Sciences, No.19(A), Yuquan Road, Shijingshan District, Beijing100049 Email:[email protected]

Liu Xiaohu China

Kunming Institute of Zoology, Chinese Aademy of Sciences, NO.32, Jiao Chang east road, Wu Hua district, Kunming, Yunnan province, China Email:[email protected]

Yayan Wahyu Candra Kusuma Indonesia

Bogor Botanic Garden, Indonesian Institute of Sciences (LIPI) Jl. Ir. H. Juanda No. 13 PO BOX 309 Bogor 16003, Indonesia Email: [email protected]

People

55

People

Resource Staff

Rhett D HARRISON (PhD)


Lan QIE a.k.a. Lainie (PhD)


Liu Yalou (MSc) Xishuangbanna

Tropical Botanical Garden, Chinese Academy of Sciences , Menglun, Mengla, Yunnan, 666303,China Email: [email protected]

Chuck CANNON (PhD)


Resource Staff

Kunfang CAO (PhD)


Jin CHEN (PhD)


Ze-Xin FAN (PhD)


Yulong FENG (PhD)


People

57

Douglas SCHAEFER (PhD)

Associate Professor of Soil Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Menglun, Mengla, Yunnan, 666303, China Email: [email protected]

Ferry SLIK (PhD)


Jacob D. WICKHAM (PhD)

NSF International Research Fellow (USA), Institute of Chemistry, Chinese Academy of Sciences, Beijing, China Email: [email protected]

Douglas YU (PhD)

Researcher, Principal Investigator of Ecology, Conservation, & Environment Center (ECEC), Kunming Institute of Zoology, Chinese Academy of Sciences Email: [email protected]

Resource Staff

TANG Yong (PhD)


Teaching Assistants

FU Wing Kan, Vivian (MPhil)

China Programme Officer, The Hong Kong Bird Watching Society/BirdLife International Email: [email protected]

SHI Lingling (PhD candidate)

Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences , Menglun, Mengla, Yunnan, 666303,China Email: [email protected]

Documents

PROCEEDINGS OF THE ADVANCED FIELDCOURSE IN ECOLOGY …€¦ · 15:30 L29: Forest restoration Tang Yong 16:30 L28: amphibians and birds Vivian Fu 18:00 Dinner 29 Nov 9:00 L16: Soil