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博 士 学 位 論 文

Changes in Tree Nutrient Stocks and Soil Fertility

Characteristics under Smallholder Rubber Cultivation

in a West Sumatran Lowland of Indonesia

近畿大学大学院

農学研究科 環境管理学専攻

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博 士 学 位 論 文

Changes in Tree Nutrient Stocks and Soil Fertility

Characteristics under Smallholder Rubber Cultivation

in a West Sumatran Lowland of Indonesia

インドネシア国西スマトラ州低地の小規模農家栽培ゴム

園における樹木養分ストックと土壌肥沃度特性の変化

平成 31 月 3 月

近畿大学大学院

農学研究科 環境管理学専攻

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ACKNOWLEDGEMENTS

Firstly, I would like to express my sincere and genuine gratitude to my academic advisor, Dr. Shin Abe, for the tireless supervision and guidance with which he provided me during the PhD course at the Graduate School of Agriculture, Kindai University, Nara, Japan. From him, I have learnt to keep persistent motivation for the research, support to acquire knowledge on the ethics of the scientific world and scientific writing.

Besides my academic advisor, I am profoundly grateful to my official supervisor, Prof. Mitsuo Matsumoto and the members of the reviewing committee on my dissertation, Prof. T. Kawasaki (Chair) and Prof. M. Ijima, for their guidance and insightful comments to complete this dissertation. My special thanks also go to Mr. Robert Sheridan for his linguistic help to write up this dissertation.

I gratefully acknowledge the financial support for my PhD course at Kindai University from the Ministry of Education, Culture, Sports, Science and Technology of Japan (MEXT Scholarship No. 152256). The field work in Indonesia during this study would not be possible without the financial assistance from the Japan Society for the Promotion of Science (JSPS Kakenhi Grant Nos. JA16K18669 and JA18H02316).

I am very deeply indebted to Prof. Hermansah (Vice Rector, Andalas University) who helped me have a great opportunity to study in Japan. My sincere thanks also goes to Prof. Ardi, Prof. Reni Mayerni, Dr. Munzir Busniah and Dr. Yaherwandi (Faculty of Agriculture, Andalas University) for their permission and generous support to pursue my study in Japan, as well as my colleagues in Department of Agroecotechnology (Mrs. Dewi Reski, Mr. Siska Effendi, Mrs. Wulan Kumala Sari) for their help in administration during my leave from Andalas University and assistance during my field survey in Indonesia.

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None of this work could have been completed without the supports from the students at Andalas University (Maulana I Kamil, Fisrtka Delyanandra, Nanda Y Syafitri, Japius S, Amanah Siregar, Ridho Wahid, Haikal and Rahmat Fauzi) and many smallholder farmers in Dharmasraya, Indonesia, who allowed me to use their rubber gardens for this study. I thank my fellow labmates in Eco-Tech Lab (Khairunisa Kamarudin, Kenta Ashida, Mayu Tomita, Syunsuke Nakayama, Kanami Tsujimoto, Yuka Kohara, Eika Yamashita, Satoka Niwa, and Hiroaki Kato), for the time we were working together and for all the fun we have had in the last 3 years.

Last but not least, the most importantly, I would like to thank my family in Padang, Indonesia (my father, my mother, my sister and brother) for supporting me spiritually throughout my study and life in Japan.

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ABSTRACT

Rubber tree (Hevea brasiliensis) is an industrial crop with high economic value because of its nature to produce milky latex as the primary source of natural rubber. Currently, Indonesia produces annually 3 million tons of natural rubber from 3.6 million ha of rubber gardens, most (85%) of which are cultivated by smallholder farmers, and has more than 2 million households enjoying the rubber-derived income. To successfully estimate the capacity of ecosystems services provided by rubber plantation and sustainably enhance the productivity of rubber farming, the impact of rubber cultivation on environments needs to be assessed in this county. Although the study on the impacts of land use change from natural forests or jungle rubber agroforests to monoculture rubber plantation on the stocks of nutrients (inc. carbon [C]) and soil fertility has been certainly accumulated, much less is available how the nutrient stocks and soil fertility parameters change during rubber plantations, especially those managed by smallholder farmers with limited use of external resources such as fertilizers and agrochemicals. Therefore, the aim of the present study was to examine changes in tree nutrient stocks and soil fertility characteristics under smallholder rubber farming during an economic life time of rubber tree (ca. 25 years) in a low land area of West Sumatra, Indonesia.

Twenty-five rubber gardens with different ages of rubber trees (3 to 27-year-old) managed by different smallholder farmers were selected for this study. In the center of each rubber garden, soil samples were taken from freshly exposed soil profile at 0.1 m interval up to 0.8 m in depth. General soil fertility parameters of the collected soil samples {pH, EC, total C and N, available [Bray 2] P, exchangeable Ca, Mg, K, and acidityin addition to available [Mehlich 3] micronutrients (Fe, Mn, Cu and Zn)} were done following the routine methods of the laboratory analysis. Above- and belowground tree biomasses were sampled in 12 rubber gardens, which were selected from the above given 25 gardens to cover the rubber’s economic lifespan, by the logging and trenching method, respectively. Aboveground biomass was further separated into three components; stem, branches and foliage (leaves and twigs). Undergrowth (weed) biomass, and land-surface litter were also

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sampled. The contents of selected nutrients (C, N, P, K, Ca, Mg, Fe, Mn, Cu and Zn) of each tree component were determined by the digestion method.

The increasing patterns of both biomass and C stock in the rubber tree at the study site were mostly fitted well by the Gompertz model. The diameter at breast height (D) was identified as a fairly good estimator, which is easily measurable and can predict accurately both biomass and C stock in the rubber tree based on the linear regression model. These models were also adoptable to many of the other nutrients with slight modifications. With these tree growth and C accumulation patterns, this study revealed that C stock in both above- and belowground tree biomasses increased consecutively, but those in the other pools (i.e., soil organic matter, undergrowth biomass and land surface litter) remained on a relatively constant level during the economic life time of the rubber tree. The major contributors to the C stock in the rubber gardens were soil (52.2±18.0%) and aboveground tree biomass (42.8±16.9%), and belowground biomasses (4.9±1.3%) contributed to a much less extent. Undergrowth (0.10±0.03%) and land surface litter (0.05±0.02%) accounted for only the negligible portion (<0.2% in total). These results imply that rubber tree cultivation have a potential role in improving the regional C sequestration due to C assimilation by the rubber tree.

On the other hand, there are no clear trends of soil fertility decline during the economic life cycle of rubber tree, regardless of no- or .low-input practice of the smallholder rubber farmers This result suggests that the amounts of macronutrients taken up by the rubber tree are not large enough to overbalance the removal of these nutrients from the soil and/or natural replenishment mechanisms of soil nutrients, e.g., nutrient-rich deposit left after flash flood, may exist in the study site. In contrast, soil micronutrients, especially Cu and Zn, exhibited decreasing trends of their availability in the same period, suggesting significant mining of soil micronutrients though the rubber cultivation at the study site. Although the current level of these macronutrient availability is still high enough to support the rubber cultivation because of the inherently high availability of the micronutrients due to the low pH and high level of organic matter in the studied soils but the future risk of Cu and Zn deficiencies remains in the study site, In this regard, soil organic matter is considered the key

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component of sustainable soil management in this site because most of the examined soil nutrients were positively correlated with soil organic C.

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TABLE OF CONTENTS

ACKNOWLEDGEMENTS ... ii

ABSTRACT ... iv

TABLE OF CONTENTS ... vii

CHAPTER I: Introduction ... 1

1. General Backgrounds ... 1

2. Objectives ... 6

References ... 8

CHAPTER II: Measuring Biomass and Carbon Stock in Smallholder-managed in Lowland Area of West Sumatra ... 15

1. Introduction ... 15

2. Materials and Methods ... 17

3. Results ... 21

4. Discussion ... 26

5. Conclusion ... 29

References ... 30

CHAPTER III: Changes in Nutrient Stocks of Rubber Trees under Smallholder-managed Rubber Garden in a West Sumatran Lowland ... 34

1. Introduction ... 34

2. Materials and Methods ... 35

3. Results ... 40

4. Discussion ... 44

5. Conclusion ... 45

References ... 46

CHAPTER IV: Changes in Carbon Stock in Five Different Pools in Smallholder-managed Rubber Garden of a West Sumatran Lowland ... 50

1. Introduction ... 50

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3. Results ... 56

4. Discussion ... 60

5. Conclusion ... 62

References ... 63

CHAPTER V: Changes in Soil Fertility Parameters under a Smallholder-managed Rubber Garden in a West Sumatran Lowland ... 68

1. Introduction ... 68

2. Materials and Methods ... 70

3. Results ... 73

4. Discussion ... 78

5. Conclusion ... 81

References ... 81

CHAPTER VI: Changes in Soil Micronutrients Status in Samllholder-managed Rubber Garden in a West Sumatran Lowland ... 86

1. Introduction ... 86

2. Materials and Methods ... 88

3. Results ... 91

4. Discussion ... 95

5. Conclusion ... 98

References ... 98

CHAPTER VII: Summary and Further Challenges ... 104

1. Summary ... 104

2. Further challenges... 107

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CHAPTER I

INTRODUCTION

1. General Backgrounds

1.1. Accelerated Deforestation and Expansion of Industrial Crop Plantations

Rubber tree (Hevea brasiliensis) is an industrial crop with high economic value because of its nature to produce milky latex as the primary source of natural rubber. This latex consists of polymers of the organic compound isoprene (Rose & Steinbuchel 2005) along with non-rubber components (ca. 6%, w/w) such as proteins, phospholipids and ash (Kawahara & Tanaka 2009). Recently, an additional value of the rubber tree was raised recently due to the technical advancement to manufacture engineered woods for the production of furniture and plywood (Lokmal et al. 2008). This deciduous tree is originally from Amazon basin forest in South America and thus can grow up well in other areas under a tropical humid climate. Currently, the world top producers of natural rubber, e.g., Thailand, Indonesia and Malaysia (share: 83%), are all situated in Southeast Asia (FAO 2014), where rubber tree was successfully introduced as a cash crop at the turn of the twentieth century and its cultivation area has been expanding rapidly (FAO 2001; de Jong 2001).

On the other hand, Insular Southeast Asia has experienced the highest level of deforestation among all humid tropical regions of the world since the 1990s (FAO 2016), largely due to the conversion of natural forests to plantations of industrial crops such as oil palm (Elaeis guineensis) and rubber tree (Hevea brasiliensis) (Miettinen et al. 2011, Margono et al. 2014), making this region have the world’s largest cultivation area of these industrial crops at present (FAO 2018). Indonesia is known as the world’s second largest producer of natural rubber which annually produces 3 million tons of natural rubber from 3.6 million ha of rubber (FAO 2018). Rubber seeds were firstly introduced to Sumatra (Indonesia) from Malaysia by migrant plantation workers and tradesman in the late 19th

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century (Joshi et al. 2002) and as of the moment it plays a vital role in economic growth in this country by increasing the country’s cash income.

Sumatra and Kalimantan Island are the hotspot areas of rubber plantation in Indonesia (Warren-Thomas et al. 2015). These island account for about 95 % of the national rubber production (DGEC 2017). Historically, forests in these regions were converted into agroforestry rubber systems (Pye-Smith 2011; Guillaume et al. 2015), where rubber trees were planted within the natural forest landscape (Gouyon et al. 1993), whereas this form of rubber farming subsequently converted into a monoculture plantation (Fitzherbert et al. 2008). The land use conversion to industrial crop plantation (mostly oil palm and rubber tree) is the main cause of the loss of original land cover, i.e., natural forest (Margono et al. 2014). In the recent years, Sumatra Island has been displaying the highest deforestation rate in the world and thus lost almost half of its forest cover for the period of 1985–2007 (Laumonier et al. 2010). Similarly, the deforestation and subsequent land conversion to the plantations have been seen in Kalimantan where only 50% of natural land cover remained in 2012 (Miettinen et al. 2011). In particular, massive deforestation was seen in lowland area of Sumatra, where only 9% of natural land cover was left by 2012 (Margono et al. 2014). These changes in the land use: from natural or semi-natural systems to artificial or agricultural lands inevitably brought about a variety of environmental degradations such as enhanced carbon emission and loss of biodiversity (Danielsen et al. 2009), accelerated soil erosion and exploitation of soil fertility (Dechert et al. 2004), and deterioration of water quality (Klinge et al. 2004), and these environmental issues have been seriously concerned worldwide as well as in Indonesia.

1.2. Rubber Cultivation and Smallholder Farming Systems in Sumatra Island

The rubber plantation in Indonesia is predominantly managed by smallholder farmers who own less than 25 ha of land (Fox & Castella 2013), and this country has more than 2 million households enjoying the rubber-derived income (DGEC 2017). Under the policy formulation and financial supports from the government, the land area under the smallholder rubber farming increased by 65% over the past 30 years, and it currently accounts for 85% of the total rubber plantation area in Indonesia (IMOA 2016). In case of Sumatra Island,

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which has one of the largest areas of rubber garden in Indonesia, the rubber cultivation was encouraged by the subsidy from the government-led projects such as Smallholder Rubber Development Project (SRDP) and later Tree Crop Smallholder Development Project (TCSDP) (Penot et al. 2017). These projects allowed farmers to acquire productive clones and contributed to significant improvement of latex yields in the region (Penot et al. 2017). As a result, these projects accelerated expansion of rubber gardens, improved rubber production and supported a rapid economic development in the Sumatra region (DGEC 2017).

The general characteristics of the rubber farming methods by smallholders in West Sumatra are similar to those described for other small-scale tree crop farmings. Smallholders are often defined based on the size of operating land and in the present study referred to as those who operate less than 25 ha of land (Fox & Castella 2013). Smallholders often produce relatively small volumes depending largely on family labors (ETI 2005). Moreover, in agronomic aspects, smallholders cultivate rubber trees at high densities, take less care of plants even in the immature tree (over the first 5 years) period, tap trees intensively and use no or minimal amounts of fertilizers and other agrochemicals (Goldthorpe 1987). Furthermore, smallholders are often facing the lack of facilities to process latex to crude rubber and the difficulty in marketing their products. It is also said that labor is less productive in the smallholder gardens than in estate plantations (Barlow & Jayasuriya 1984). These characteristics represent the contrasting situations with the estate plantations managed by the commercial companies, e.g., lower tree densities, well managed trees individually during the immature period, intensive use of fertilizers and agrochemicals, and latex harvest by advanced tapping methods. As a result, the estate plantations often enjoy the larger production at harvest (Goldthorpe, 1987).

1.3. The Impacts of Smallholder Farming Method on Carbon and Nutrient Stocks in Rubber Gardens

Carbon sequestration is one of the ecosystem services that rubber plantation can support (Wauters et al. 2008; Moreira et al. 2009; Orjuela et al. 2014; Blagodatsky et al. 2016). Rubber tree has its economic life cycle of approximately 25 years, which is

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sufficiently long enough to sequester carbon from the atmosphere (Petsri et al. 2013). In southeast Asia, total ecosystem C stock in the rubber plantation (93–376 Mg ha-1) is a land use type ranked among the top contributors, following native forest (119–3737 Mg ha-1), logged forest (101–474 Mg ha-1) and orchards (82–462 Mg ha-1) (Ziegler et al. 2012). According to the comprehensive review of literature by Blagodatsky et al. (2016), C stocks in rubber plantations are highly variable and depend largely on the tree factors: i) plantation age, ii) plantation management, and iii) environmental and edaphic conditions regulated by the local climate and topography. Consequently, information on the biomass content in specific ecosystems, regions and countries is limited worldwide including Southeast Asian landscapes (Yuen et al. 2013, 2016). Furthermore, carbon stock assessment in the context of afforestation and reforestation under a global agenda (Penman et al. 2003) requires the simultaneously estimation of five different carbon pools: i) aboveground tree biomass, ii) belowground tree biomass, iii) undergrowth biomass, iv) litter (including woody debris), and v) soil organic matter. However, the assessment that determines the complete set of carbon pools is still lacking.

On the other hand, considering the management strategy of smallholder farmers with no- or minimal inputs, understanding nutrient uptake by trees and cycles of nutrients help better management in rubber gardens. Essential nutrients (macro and micronutrients) such as nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), iron (Fe), manganese (Mn), cooper (Cu), and zinc (Zn) on which we focus in the present study, play essential roles in tree growth (Tripathi et al. 2014). It helps to increase the yield, growth, and quality of various crops (Morgan and Connolly 2013). On the other hand, micronutrients are required by plants in small amounts but are important in determining plant growth and crop yield and long-term sustainability of agricultural production (Brady & Weil 2007).

Measuring the amount of those nutrients uptake (accumulation in tree biomass) also help estimating nutrient stocks and is a crucial step in the development of sustainable land use systems, especially on low-fertility soils of the humid tropics (Smaling et al. 1999; Schroth et al., 2001), because stock size of the nutrients depends on the amount of biomass and fertility status of the soil (Hartemink 2005). Information concerning total nutrients

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content of a plant at different age within its growth cycle is a basic requirement for the assessment of nutritional problem. However, it has so far been rare available for rubber tree (Shorrocks 1965). Such information leads to considerable insight that regulate is nutrient cycling and put to provide nutrient balances information that could make for environmental policies and help to guide system management decisions of future research (Haertemink 2006).

1.4.The Impact of Smallholder Farming Methods on Soil Fertility Characteristics in Rubber Gardens

Soil fertility management is considered a key cultural practice for the sustainable improvement of latex yield in the rubber garden, in spite that the relationship between soil fertility and latex yield is still a matter under discussion (Chambon et al. 2017). This key agricultural practice is in particular concerned with respect to the smallholder rubber farming system because little or no use of fertilizer in a commonly accepted management practice (Goldthorpe, 1987) implies the exploitation of nutrients from the rubber garden soils through the latex collection (Tanaka et al. 2009). In fact, many of the previous studies reported that land use change from natural or secondary forests to rubber plantation resulted on soil gradation such as the depletion of soil organic matter and mineral nutrients (e.g., Li et al. 2012; de Blécourt et al. 2013; Kotowska et al. 2015; 2016; Allen et al. 2015) and such degradation can be further accelerated during the rubber cultivation (e.g., Aweto 1987, 2001; Cheng et al. 2007), unless otherwise natural mechanisms of nutrient replenishment such as organic matter mineralization, biological fixation, and mineral weathering can make up for the loss of soil nutrients (Hartemink 2005).

On the other hand, some other reports documented inconsistent results: soil fertility status under the rubber farming was seen to a similar extent as that those under the primary and secondary forest (e.g., Tanaka et al. 2009; Moreira et al. 2013), and little loss or even enhanced contents of organic matter and some nutrients in the soil were investigated during the rubber cultivation (Guillaume et al. 2016; N’dri et al. 2018; Peerawat et al. 2018). These inconsistent findings warrant further research needs on how soil fertility status change under

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the rubber cultivation. Nevertheless, the study on changes in soil fertility during the rubber cultivation, in particular those under the smallholder farming scheme, has been attracting much less attention, compared to the study focuses on those induced by the land use change from forest to rubber plantation which have been accumulated significantly (e.g., Li et al. 2012; de Blécourt et al. 2013; Allen et al. 2015, Kotowska et al. 2015, 2016).

In addition to the macronutrients such as nitrogen (P), phosphorus (P), potassium (K), calcium (Ca) and magnesium (Mg), the micronutrients such as iron (Fe), manganese (Mn), copper (Cu) and zinc (Zn) are increasingly recognized as being essential for achieving higher yields (Fageria, 2002) as improving the micronutrient supply to crops can have seedlings more vigorous growth and higher resistance to diseases and possibly to drought (Frossard et al., 2000). Micronutrients in the plant originate largely on those in the soil, and thus micronutrient content and availability in the soils are of interest in the research (Nubé and Voortman, 2011). In general, soil micronutrient contents (status and behaviors of micronutrients in the soil) in natural ecosystems vary depending on the nature of the parent material and the pedogenic processes (Harmsen and Vlek, 1985) but those in agricultural lands are also influenced by the management practices such as the application of fertilizers (Harsmen and Vlek, 1985) and animal manures (Ortiz Escobar and Hue, 2008). To develop a sustainable strategy of soil management in rubber plantation of the region, it is crucial to assess the impact of the current farming practices on soil resources (Abe et al., 2016) and long-term assessment is preferential to evaluate the sustainability of the farming system. Nonetheless, the study on soil micronutrient availability in the rubber garden is found in scarcity, and particularly little information is available on changes in soil micronutrient availability during the economic lifetime of the rubber tree.

2. Objectives

Most of recent studies addressed the impact of land use change with a focus on the conversion from natural or secondary forest to perennial crops including rubber trees on carbon sequestration (de Blecourt et al. 2013, Kotowska et al. 2015, Guillaume et al. 2015,

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Van Straaten et al. 2015), lead to soil degradation (Guillaume et al. 2016) changes in soil nutrients and its dynamic (Moreira et al. 2013, Allen et al. 2015, Kotowska et al. 2016, Maranguit et al. 2017) and alteration in biodiversity (Krashevska et al. 2015). Nonetheless, study considering rubber plantations alone after the long term of land use change led by rubber cultivation is rare and still limited. Only few previous studies that were focusing on rubber cultivation, such as changes in soil properties (Aweto 1987) and carbon sequestration (Cheng et al. 2007) but did not consider the comprehensive study about rubber tree nutrient stocks and soil fertility characteristics within a chronosequence of rubber’s economic life time (e.g. 25 years), especially under smallholder-managed rubber farms.

The study was taking place in the largest area of rubber cultivation in West Sumatra Province. At present, West Sumatra Province has a rubber plantation area of >170,000 ha as a frontier of agricultural expansion, out of which 41,260 ha (≈24%) are situated in Dharmasraya (BPS-PSB 2015). Study plots are located in Pulau Punjung, a district capital of Dharmasraya (Figure 1.1). The study was conducted in lowland area (97 to 110 m a.s.l). To capture economic lifetime of rubber tree (i.e. 25 years), all plots of the present study were established in 25 different rubber gardens with ranging from 3 to 27 years of stand age which lies on 0° 55.976' - 0° 57.665' S and 101° 28.557' - 101° 32.590' E, about 190 km southeastern of province capital. The site information is described in more detail in the following chapter.

Therefore, in this present study, we were focusing to address how tree nutrient stocks and soil fertility characteristics changes over the economic life time, where monoculture rubber gardens have been rapidly expanding since last few decades in Indonesia which is typically no- or low external input (fertilization). Specifically, we firstly narrow the focus on changes of tree biomass and nutrient measurement, aimed to quantify the changes and the rate of biomass accumulation-associated macronutrients stock (Chapter II, Chapter III), second, we nail down on the assessment of carbon stock in complete set of C pools (Chapter IV) to assess carbon stock under the smallholder rubber farming with special focus on five different carbon pools, to the end how each C pools contributed to total carbon stock in rubber ecosystem. Third, we forward on soil fertility assessment, aimed to address how soil fertility

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status and soil micronutrients status changes during rubber cultivation under common management with no- or minimal inputs of external resources (Chapter V, Chapter VI).

Figure 1.1 Map of the study location

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Kongsager, R., Napier, J., Mertz, O. (2013): The carbon sequestration of tree crop plantations. Mitig. Adapt. Strat. GL. 18, 1197–1213.

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Kotowska, M. M., Leuschner, C., Tridiati, T., Hertel, D. (2016): Conversion of tropical lowland forest reduces nutrient return through litterfall and alters nutrient use efficiency and seasonality of net primary production. Oecologia 180, 601–618. Krashevska, V., Klarner, B., Widyastuti, R., Maraun, M., Scheu1, S. (2015): Impact of

tropical lowland rainforest conversion into rubber and oil palm plantations on soil microbial communities. Biol. Fertil. Soils 51, 697-705.

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Laumonier, Y. L., Uryu, Y., Stüwe, M., Budiman, A., Setiabudi, B., Hadian, O. (2010): Eco-floristic sectors and deforestation threats in Sumatra: identifying new conservation area network priorities for ecosystem-based land use planning. Biodivers. Conserv. 19, 1153–1174.

Li, H., Ma, Y., Liu, W., Liu, W. (2012): Soil changes induced by rubber and tea plantation establishment: comparison with tropical rain forest soil in Xishuangbanna SW China. Environ. Manage. 50, 837–848.

Liu, C., Pang, J., Jepsen, M. R., Lü, X., Tang, J. (2017): Carbon Stocks across a Fifty Year Chronosequence of Rubber Plantations in Tropical China. Forests 8, 209

Lokmal, N., Zaki, A., Fazwa, M., Suhaimi, W., Azmy, Y., Zakaria, I., Tan, H., Khoo, S. K., Wan-Akil, A. T. (2008): Growth of several rubber clones for timber production. J. Trop. For. Sci., 20, 175-180.

Maranguit, D., Guillaume, T., Kuzyakov, Y. (2017): Land-use change affects phosphorus fractions in highly weathered tropical soils. Catena 149, 385-393.

Margono, B. A., Potapov P. V., Turubanova S., Stolle F., Hansen M. C. (2014): Primary forest cover loss in Indonesia over 2000–2012. Nat. Clim. Change 4,730–735. Miettinen, J., Shi C., Liew S. C. (2011): Deforestation rates in insular Southeast Asia between

2000 and 2010. Global Change Biol. 17, 2261–2270.

Moreira A., Moraes, L. A. C., Fageria, N. K. (2009): Potential of rubber plantations for environmental conservation in Amazon region. Biorem. Biodiv. Bioavail. 3, 1-5 Moreira, A., Moraes, L. A. C., Zaninetti, R. A., Canizella, B. T. (2013): Phosphorus dynamics

in the conversion of a secondary forest into a rubber tree plantation in the Amazon rainforest. Soil Sci. 178, 618–625.

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Orjuela, C. J. A., Andrade C. H. J., Vergas V. Y. (2014): Potential of carbon storage of rubber (Hevea brasiliensis Mull.Arg) plantations in monoculture and agroforestry systems in the Colombian Amazon. Trop. Subtrop. Agroecosyst. 17, 231-240.

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CHAPTER II

MEASURING BIOMASS AND CARBON STOCK IN SMALLHOLDER-MANAGED RUBBER TREES IN A LOWLAND AREA OF WEST SUMATRA

1. Introduction

Indonesia has experienced the highest level of deforestation among all humid tropical regions of the world since the 1990s (FAO 2016), largely due to the conversion of natural forests to plantations of industrial crops such as oil palm (Elaeis guineensis) and rubber tree (Hevea brasiliensis) (Miettinen et al. 2011; Margono et al. 2014), making this region have the world’s largest cultivation area of these industrial crops at present (FAO 2017). Both Sumatra and Kalimantan islands are the hotspots of deforestation and expansion of plantations (Miettinen et al. 2011; Margono et al. 2012). The conversion of natural forests to oil palm and rubber plantations results in the loss of ≈80% of total tree biomass in Sumatran rainforest area (Kotowska et al. 2015), representing severe impacts of deforestation due to land use change on regional carbon budget (Ziegler et al. 2012). In contrast, development of plantation of industrial trees including rubber tree and oil palm in degraded regions may contribute to carbon sequestration (Wauters et al. 2008). Whichever case be considered, it highlights the importance of the assessment on the changes in biomass and carbon stock after the establishment of plantations, which has been underrepresented in the literature (Ziegler et al. 2012; Yuen et al. 2013, 2016) regardless of the potential of carbon sequestration in the plantations (Kongsager et al. 2013; Khasanah et al. 2015).

The use of allometric equations has been a common approach to estimate tree biomass due to the difficulty of direct sampling of tree components, especially of tree roots. However, applying existing allometric equations without considering differences in local environmental settings and without first verifying their applicability in the target site is potentially a key source of uncertainty (Yuen et al. 2016). The recent review (Krisnawati et al. 2012) revealed that limited number of equations have been prepared in limited

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geographical areas, and thus limited coverage with focus on rubber tree in Southeast Asia: only eight equations exist for aboveground biomass estimation of which two are from Indonesia. The situation becomes further worse for belowground biomass estimation because only two equations are so far available (Templeton 1968) despite its significant contribution (approximately 10–30%) to whole tree biomass (Yuen et al. 2013).

In the present study, we focus on smallholder rubber farming in a lowland region of West Sumatra, Indonesia, currently known as the region ranked among the highest rates of deforestation (higher than 5% per annum) in the world. In Sumatra, approximately 550,000 ha of forests have been lost over the past 30 years, the majority of which occurred due to conversion to other land uses and forest fires (Miettinen et al. 2011; Margono et al. 2012). Historically, forests in Sumatra were converted into agroforestry rubber systems, where rubber trees were planted within the natural forest landscape (Gouyon et al. 1993), whereas this form of agriculture subsequently converted into a monoculture plantation of rubber tree (Fitzherbert et al. 2008). Currently, most of rubber gardens in Sumatra have been managed by smallholder farmers; rubber plantations have significantly contributed to economic growth in this region under the financial and policy supports from the Indonesian Government (Penot and Budiman 2001).

In the present study, we aimed to assess the changes in tree biomass and associated carbon stock under smallholder rubber farming over an economic life of rubber in a lowland region of West Sumatra, where monoculture rubber gardens have been rapidly expanding for the last few decades. More specifically, the objectives of this study were threefold: i) to measure quantitatively below and above ground stocks of biomass and carbon, ii) to model the rate of biomass accumulation and the associated carbon stock in rubber trees, and iii) to identify a simple estimator of biomass and carbon stock in rubber tree under smallholder farmings in the study region.

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2. Materials and Methods

2.1. Study site

The present study was carried out in Dharmasraya District, West Sumatra Province, Indonesia (0º55’s–0º56’s; 101º28’e–101º32’e; 120–150 m above sea level) (Figure 2.1). This district was established in 2004, currently known as a developing district due to the immigration from the densely populated Java under decentralization policy of Indonesian Government. The rubber farming was firstly introduced to West Sumatra Province in the early 1910s (Gouyon et al. 1993), and its subsequent expansion (in terms of latex production) contributed to economic development in the province (Penot and Budiman 2001). At present, rubber farming in this

Figure 2.1. Map of the study site (Dharmasraya District, West Sumatra Province,

Indonesia). The open circles in the figure indicate the locations of the investigated plots (n=12).

province covers an area of more than 170,000 ha out of which 41,260 ha (24.2%) is situated in Dharmasraya District (BPS-PSB 2015).

Dharmasraya District is situated under a tropical rain forest climate, classified as Af in the Koppen-Geiger classification system, having an annual daily temperature of 27oc and

101o6’ E 101o24’ E 101o42’ E 102o0’ E 0o54’ S 1o12’ S 1o48’ S 0 5 20 km Dharmasraya District Malaysia INDONESIA Singapore 1o30’ S West Sumatra Province

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an annual precipitation of 2418 mm over the past 30 years (1981–2010) (BMKG 2017). Soils of alluvium origin classified as Aquic Dystrudepts in the U.S. Soil Taxonomy widely cover the study site. These soils at the land surface (0–10 cm) had low pH values (4.6±0.4), moderate contents of organic C (37.1±8.7 g kg-1) and total N (3.0±0.6 g kg-1), large amounts of exchangeable acidity (5.5±1.5 cmolc kg-1) with low base saturation (15.0±19.1%), and low

status of available (Bray II) phosphorus (13.8±18.4 mg kg-1) and exchangeable bases (Ca,

0.45±0.84 cmolc kg-1; Mg, 0.24±0.21 cmolc kg-1; K, 0.20±0.15 cmolc kg-1) (see Chapter V).

The field survey was conducted in the study site from July to August 2016. Twelve rubber trees with different ages planted in different gardens managed by different owner farmers (up to 2-ha landholders) were selected for the field measurement and the sampling of plant tissues. Herein rubber trees were selected to widely cover their economic life of 25 years following the identification of tree ages (i.e., 3 to 27 years old; equivalent to the establishment ages of rubber gardens) by the interviews with the owner farmers. In all the rubber gardens investigated in this study, rubber trees were planted in space interval of 3 m x 5 m (667 trees ha-1) or 4 m x 5 m (500 trees ha-1). Our interview with the owner farmers revealed that these rubber gardens were established due to the direct conversion from either of natural forests or jungle rubber agroforestry systems. In general, these rubber gardens had been taken care without the application of fertilizers throughout the cultivation period. The names of the rubber clones planted in their lands are unknown because owner farmers could not specify the clone names. However, based on a local association of rubber farmers, all rubber trees planted in Dharmasraya District are most-likely the productive clones such as GT1, PB260, IRR112, and BPM24. The collection of latex yield information also encountered the great difficulty. For this reason, the present study does not take the latex production into consideration.

2.2. Field measurement and sampling

For each of rubber trees studied, diameter at breast height (D) and tree height (H) were measured: D was measured at 1.3 m off the ground, whereas H was determined using a measuring tape after hewing down the target tree. A logged (aboveground) tree was separated

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into three components: i) stem, ii) branches and iii) foliage (including twigs). In addition, iv) tree roots (including stump) was also collected as the fourth component by the trenching method. Fresh biomass was weighed for each tree component using a spring balance, while subsamples taken as a composite of several parts within each component were used to measure its moisture content and carbon concentration. Hereafter, aboveground component was referred to as the stem, branches and foliage combined, while belowground component indicates the roots.

2.3. Laboratory analysis

Tree tissue (fresh biomass) samples were dried in an oven at 80ºc for 72 hours to

measure their moisture contents and to determine the dried biomass at each tree component; stem (Bstem), branches (Bbranch), foliage (Bfoliage) and roots (Broot). After drying, each sample

was ground using a blade mill and then ball-milled to prepare homogenized fine powder samples. Carbon concentrations in the powder samples were determined by the dry combustion method using a NC analyzer (Sumigraph NC-22A, Sumika Chem. Anal. Serv. Ltd., Tokyo). Carbon stocks in the four different tree components, i.e., stem (Cstem), branches

(Cbranch), foliage (Cfoliage) and roots (Croot), were calculated through multiplication of their

biomass amounts by the corresponding carbon concentrations, respectively. At the end, Bstem,

Bbranch, and Bfoliage were summed up to obtain the aboveground biomass (Bshoot) and its

associated carbon stock (Cshoot) was calculated due to the summation of Cstem, Cbranch, and

Cfoliage, while biomass (Btotal) and its carbon stock (Ctotal) in a whole tree is obtained due to

the summation of aboveground and belowground (root) biomasses and carbon stocks, respectively.

2.4. Statistical analysis

Multiple comparison was done by the Tukey test (with assumption of Gaussian distribution and homoscedasticity of parent populations) to differentiate means in carbon concentration among the tree components at the probability of less than 5% (P < 0.05). Following the generally accepted theory (e.g., Wauters et al. 2008; Sone et al. 2014), the

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well-known growth model of Gompertz was applied to a series of data points in order to analyze the trends of rubber tree growth parameters, i.e., H, D, and biomass in each tree component (i.e., foliage, branches, stem and roots), aboveground tree total and whole tree total, and their associated carbon stocks:

𝑌 = 𝑎 × exp⁡[− exp(𝑐 − 𝑡𝑟𝑒𝑒⁡𝑎𝑔𝑒)/𝑏]

Where Y is the dependent variable “H, D, B or C” in response to the independent variable “tree age”, and a, b, and c are coefficients of each of the regression curves: a is an asymptotic value, b is the width of the transition, and c is the tree age at 50% of the function’s amplitude. The difference between the maximum and minimum of H, D, B or C was used to estimate a, the difference between the tree age at 75% and 25% of the amplitude was used to estimate b, and the tree age at 50% of the amplitude was used to estimate c. The other theoretical nonlinear regression models such as exponential, logarithmic and power models were also tested for the goodness of fit based on the standard error of the estimate (σest):

𝜎Est = ⁡ √

∑(𝑦 − 𝑦′)2

𝑁

Where y is an actual score, y' is a predicted score, and N is the number of pairs of scores. The coefficient of determination (R2) is given together with σest but R2 is referenced to a lesser

extent than σest as R2 is not a reliable indicator of the model fitting in the case of the

non-linear models (Spiess and Neumeyer 2010).

On the other hand, to identify the best estimator of rubber tree biomass and associated carbon stock, candidate variables, i.e., H and D, and their combinations such as “H‧D” and “H‧D2”, were tested and the best estimator in the linear model was selected based

on both R2 and σest. All statistical analyses in this study were performed using sigmaplot ver.

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3. Results

Tree height (H) and D of the rubber tree at the study site increased from 7.8 and 0.14 m of the 3-year-old tree to 22.1 and 0.42 m of the 27-year-old one, respectively (Figure 2.2). The increasing pattern of H was fitted well by the Gompertz model, while D was not because of non-constant variance indicated by unstable model coefficients during the iteration process. Instead, the non-growth models such as the exponential model earned a better result (R2 = 0.82, σest = 0.039, P < 0.001; the non-growth model curves are not shown in Figure 2.2).

Figure 2.2 Changes in the height (H) and diameter at breast height (D) of Hevea brasiliensis

in relation to their ages at the study site. Height = 19.7 × exp[–exp(2.2 – tree age) / 3.0] (R2 = 0.89, σest = 1.38, P < 0.001).

Biomasses in aboveground and belowground parts of the rubber tree at the study site increased from 49.7 and 14.3 kg tree-1 of 3-year-old tree to 825.4 and 101.1 kg tree-1 of 27-year-old tree, respectively (Figure 2.3). As a result, Btotal increased from 64.0 kg tree-1 at

3-year-old tree to 926.5 kg tree-1 at 27-year-old. All these increasing patterns were fitted well by the Gompertz model (see Figure 2.3). Regarding the increasing patterns of biomass in

T

ree height

(m

)

Rubber tree age (year)

Diam eter at breast height (m ) 0 10 20 30 0 10 20 30 0.0 0.2 0.4 0.6 0 10 20 30

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each tree component, the Gompertz model fitted well to biomass in stem and foliage, while it did not fit to Bbranch, due to non-constant variance indicated as mentioned for D.

Looking at the contribution of each tree component to the whole tree biomass, Bstem

accounted for more than one half of the total biomass (ave. 53.5±8.9%), and it was relatively constant (coefficient of variation (CV) = 16.6%) compared to the other components (CV: Bbranch = 32.7%; Bfoliage = 33.8%; Broot = 25.1%). The second largest contribution was made

by Bbranch (22.5±7.4%), followed by Broot (12.9±3.2%) and Bfoliage (11.1±3.8%). Although the

shoot to root (S/R) ratio for the biomass was relatively constant (S/R ratio = 7.1±1.4; CV = 20.0%) over the studied tree ages, except for the 3-year-old tree which had a very low S/R ratio (3.5).

Figure 2.3 Changes in biomass at four different components in foliage (Bfoliage), branches

(Bbranch), stem (Bstem) and roots (Broot), aboveground total (Bshoot) and whole tree

total (Btotal) of Hevea brasiliensis in relation to their ages at the study site. Rubber tree age (year)

0 10 20 30 B io m a s s ( k g t re e -1) 0 200 600 1000 Shoot trend Root trend Total trend Total Shoot Root 0 10 20 30 B io m a s s ( k g t re e -1) 0 200 400 600 Stem Branches Foliage Stem trend Foliage trend 400 800

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Figure 2.4 Comparison of carbon concentration between tree components of Hevea

brasiliensis at the study site. Different letters on the shoulders of the symbols indicate a statistically significant at the probability of <0.05.

Figure 2.5 Changes in carbon stock in foliage (Cfoliage), branches (Cbranch), stem (Cstem) and

roots (Croot), aboveground total (Cshoot) and whole tree total (Ctotal) of Hevea

brasiliensis in relation to their ages at the study site.

Rubber tree components

Stem Branch Foliage Root

C a rb o n c o n c e n tr a ti o n ( g k g -1) 400 450 500 550 a b b c

Rubber tree age (year)

0 10 20 30 C a rb o n s to c k ( k g t re e -1) 0 100 300 500 Shoot trend Total Shoot Root trend Root Total trend 0 10 20 30 C a rb o n s to c k (k g t re e -1) 0 100 200 300 Stem trend Stem Branch Foliage Foliage trend 200 400

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Table 2.1 Changes in biomass and carbon stock at different components in rubber tree.

Carbon concentration in each component of rubber tree varied to a minor extent in relation to its age, as indicated by low values of CV (<10%) (Figure 2.4). Compared between four different tree components (stem, branches, foliage and roots) in the rubber tree, the highest C concentration was found in foliage (514.5±9.5 g kg-1; CV = 1.8%); with significant

differences (P < 0.05) from those in the other components. There was no significant difference in C concentration between branches (471.7±11.9 g kg-1; CV = 2.5%) and stem

(464.7±13.2 g kg-1; CV = 2.8%) but significantly lower C concentration (P < 0.05) was seen in roots (395.3±37.6 g kg-1; CV = 9.5%). Carbon stock in Bshoot and Broot of the rubber tree at

the study site increased from 22.5 and 5.8 kg tree-1 of the 3-year-old tree to 376.3 and 45.5 kg tree-1 m of the 27-year-old one, respectively (Figure 2.5). All these increasing patterns were fitted well by the Gompertz model (i.e., Cshoot: R2 = 0.75; σest = 65.2; P < 0.01; Croot: R2

= 0.79; σest = 6.5; P < 0.001; Ctotal: R2 = 0.75; σest = 71.4; P < 0.01).

Carbon stock in the roots accounted for 11.1±3.1% of Ctotal. Stem accounted for the

major portion (ave. 53.7±9.4%) of total carbon stock in a rubber tree, followed by branches (ave. 23.0±7.4%), foliage (ave. 12.3±4.0%) and roots (ave. 11.1±3.1%). There was a very strong, positive, significant linear correlation between D and Bshoot, between D and Broot as

well as between D and Btotal (Figure 2.6). Also, such intercorrelations were observed between

D and Cshoot, D and Croot, and D and Ctotal. On the other hand, regarding the synthesized factors,

Parameter Tree component a b c R2 SEE P

Biomass Foliage 69.11 2.91 5.62 0.54 23.3 0.030 Branches 1463.46 27.60 42.53 0.74 48.5 0.002 Stem 456.80 7.53 8.67 0.63 108.9 0.011 Aboveground 1109.57 13.80 13.79 0.75 141.0 0.002 Belowground 147.33 16.31 13.73 0.74 16.3 0.002 Total 1256.16 14.05 13.78 0.75 156.9 0.002

Carbon stock Foliage 34.86 2.87 5.64 0.54 11.7 0.029

Branches 565.02 26.00 38.87 0.75 22.5 0.002

Stem 202.42 6.93 8.37 0.62 50.5 0.012

Aboveground 458.75 11.95 11.97 0.75 65.2 0.002

Belowground 70.92 16.99 14.18 0.74 7.6 0.002

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H‧D and H‧D2, which have been frequently used in the previous study (e.g., Petsri et al. 2013; Sone et al. 2014), H‧D earned slightly better correlations of linear regression (Bshoot: R2 = 0.94,

σest = 67.2, P < 0.001; Broot: R2 = 0.94, σest = 7.4, P < 0.001; Btotal: R2 = 0.94, σest = 73.8, P <

0.001) than D alone, while H‧D2 showed less correlations (Bshoot: R2 = 0.87, σest = 97.2, P <

0.001; Broot: R2 = 0.88, σest = 10.8, P < 0.001; Btotal: R2 = 0.87, σest = 107.4, P < 0.001)

compared to D alone.

Table 2.2 Relationship of diameter at breast height with biomass and carbon stock in

different components of rubber tree.

Figure 2.6 Relationship of diameter at breast height (D) with aboveground, belowground

and total biomasses (Bshoot, Broot and Btotal) and associated carbon stocks (Cshoot,

Croot and Ctotal) of Hevea brasiliensis in relation to their ages at the study site.

Parameter Tree component a b R2 SEE P

Biomass Aboveground 68.07 5.25 0.91 80.4 <0.0001

Belowground 11.19 4.66 0.93 8.2 <0.0001

Total 79.00 5.18 0.91 87.7 <0.0001

Carbon stock Aboveground 32.84 5.16 0.90 38.8 <0.0001

Belowground 3.47 5.33 0.97 2.5 <0.0001

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4. Discussion

Compared with H (21.9 m) and D (0.26 m) for the 20 year-old tree (based on the Gompertz models) reported in North Sumatra Province (Sone et al. 2014), a neighboring region of our study site, a lower H (19.6±0.8 m: the mean of 19, 20 and 21 year-old trees (n = 3)) but a higher D (0.31±0.05 m) were found in the present study. Apart from H which does not always reflect tree biomass, in most cases D shows strongly positive correlation with tree biomass (e.g., Schroth et al. 2002; Wauters et al. 2008; Sone et al. 2014; Yuen et al. 2016). Such intercorrelation was also observed in this study (Btotal = 3094.8 × D – 322.9; R2 = 0.93,

P < 0.001), which will be discussed in detail below. Therefore, the higher D suggests the higher biomass production. In fact, the 20-year-old tree in our study site contained 714.3±125.1 kg tree-1 as B

total, which was almost twice as high biomass as that (350.3 kg tree -1) in the neighboring North Sumatra site reported by Sone et al. (2014), and the mean biomass

production rate (29.7 kg tree-1 year-1) calculated based on the Gompertz equation (Btotal =

1256.2 × exp[–exp(13. 8 – tree age) / 14.1]) prepared in the present study was 1.8 times higher in the former than 16.7 kg tree-1 year-1 in the latter. Because these two sites are situated in the geographically same region and thus have very similar environmental settings, such a large difference in the rubber tree biomass production rate between these two sites can be attributed to the different management systems: small-scale rubber gardens (mean area=1.1±0.4 ha) investigated in the present study were thoroughly managed by smallholder farmers, but, in contrast, large-scale rubber plantation (18,000 ha) in North Sumatra was managed by a rubber estate (Sone et al. 2014).

On the other hand, the mean biomass production rate in the rubber tree obtained in the present study (29.7 kg tree-1 year-1) was also higher than those previously reported in some other countries such as Thailand (13.2 kg tree-1 year-1, based on the 20 year-old tree:

Saengruksawong et al. 2012) and probably China (Mendez et al. 2012), Ghana and Brazil (Wauters et al. 2008), as mentioned by Sone et al. (2014) but lower than that in Malaysia (45.7 kg tree-1 year-1, based on the 24 year-old tree: Shorrocks et al. 1965). It is suggested

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inherently better soil fertility of alluvial origin as indicated by the relatively high content of total N (3.0±0.6 g kg-1) (see Chapter V) and sufficient water supply from the rainfall without any dry spell and from shallow-depth groundwater in the lowland region.

More than half of Btotal was consisted of Bstem, and Bfoliage and Broot occupied a similar

portion (Bfoliage = 11.1±3.8%; Broot = 12.9±3.2%).It is generally said that the proportions of

the total tree composed of leaves and roots decreases with increasing tree size (or age) (Sone et al. 2014). In this study, the proportion composed of roots was found at the highest (22.3%, S/R = 3.5) in the 3-year-old tree and its contribution subsequently got to a relatively constant level (ave. 12.0±1.3%, CV = 11.2; S/R = 7.4±0.9, CV = 12.1; n = 11). The same trend, i.e., the declination of the root proportion has been reported elsewhere, although the root biomass proportion and its degree of decrease with the increase in the tree age in the present study is relatively lower than those reported by the previous studies, i.e., 36% to 15% in Malaysia (Shorrocks et al. 1965), 55% to 15% in Brazil and 40% to 10% in Ghana (Wauters et al. 2008) in contrast to the similar pattern (i.e., 23 to 12%) in North Sumatra (Sone et al. 2014). The shallower groundwater table in the study site located in the lowland area as well as super wet climate without remarkable dry spell might limit the elongation of rubber tree roots. However, the lack of information on tree root biomass highlights the need for the further research in this regard.

Such a variation in carbon concentration over the rubber tree components has been reported elsewhere (e.g., Sone et al. 2014). These results indicate that, the estimating methods of carbon stock in woody plants simply as half of the woody biomass irrespective of tree species and components, as often adopted in the previous studies (e.g., Gower et al. 2001; Hector et al. 2011; Sone et al. 2014), are over-simplified (Blagodatsky et al. 2016) and thus are not recommended to apply for the carbon stock assessment in the rubber tree. In the study site, C concentration in the rubber tree biomass varied from 341.9 g kg-1 in the minimum

concentration in the roots to 525.7 g kg-1 in the maximum concentration in the foliage, depending on tree components (i.e., foliage, branches, stems and roots) and tree age (i.e., 3 to 27 years old). The possible misestimation of Croot is more concerned due to much lower

range of its C concentration (341.9–460.0 g kg-1) in B

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study, the simplified method shown above resulted in 6.8%–14.2% (ave. 9.5±2.2%) overestimation of Ctotal.

The similar trend of the rubber tree biomass partitioning was seen for its associated carbon stock: Cstem accounted more than half of Ctotal (ave. 53.7±9.4%). Although Broot (ave.

12.9±3.2%) was larger than Bfoliage (ave. 11.1±3.8%), carbon stock gave an opposite trend:

Croot (11.1±3.1%) became smaller than Cfoliage (ave. 12.3±4.0%) because of the lower C

concentration (ave. 395.3±37.6 g kg-1) in Broot than that in Bfoliage (ave. 514.5±9.5 g kg-1).

However, these results indicate that the rubber tree roots contain a comparable carbon amount to that in its foliage and carbon associated with the roots are not negligible in spite that the sampling of the tree roots demands much of labor and time (Yuen et al. 2013).

The use of allometric estimation of the rubber tree biomass and associated carbon stock is a key to promote the assessment on the capacities of the rubber tree plantation on biomass production and carbon sequestration. Based on the results obtained in the present study, we conclude that D is the reliable (in terms of accuracy) estimator of both biomass and carbon stock in the whole rubber tree as well as in its aboveground and belowground components at the study site (Figure 2.6). In this regard, Sone et al. (2014) and other researchers (e.g., Schroth et al. 2002; Wauters et al. 2008) also identified D as a good estimator of the rubber tree biomass. Although the synthesized parameter such as H‧D2 earned a slightly better result in this study and so in the previous studies (e.g., Sone et al. 2014), considering the tediousness and difficulty of acute measurement of H, the use of D alone in the allometric equation suits the objective and feasibility in the future study. In particular, considering the difficulty and tediousness of measuring root biomass and thus less documented in the literature (Yuen et al. 2013), the establishment of an allometric equation using D stresses the value because it can exempt from labor-demanding and time-consuming work for the sampling of tree roots without undermining the accuracy of the measurement. Although many of the previous studies applied the exponential model in the allometric estimation of the rubber tree biomass (Schroth et al. 2002; Wauters et al. 2008; Sone et al. 2014; Yuen et al. 2016), we chose the linear model in this study because of its easiness to

Figure 1.1 Map of the study location
Figure 2.1. Map of the study site (Dharmasraya District, West Sumatra Province,  Indonesia)
Figure 2.2 Changes in the height (H) and diameter at breast height (D) of Hevea brasiliensis  in  relation  to  their ages  at  the study site
Figure 2.3 Changes  in  biomass  at  four different  components  in  foliage (B foliage ), branches  (B branch ), stem (B stem ) and roots (B root ), aboveground total (B shoot ) and whole tree  total (B total ) of Hevea brasiliensis in relation to their a
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