Significance of the phosphorus-use strategies of trees for the Title cycling of phosphorus in Bornean tropical rainforest ecosystems( Dissertation_全文 )
Author(s) Tsujii, Yuki
Citation 京都大学
Issue Date 2018-03-26
URL https://doi.org/10.14989/doctor.k21147
学位規則第9条第2項により要約公開; 許諾条件により本文 Right は2020-07-02に公開; 許諾条件により要約は2019-03-20に 公開
Type Thesis or Dissertation
Textversion ETD
Kyoto University Significance of the phosphorus-use strategies of trees for the cycling of phosphorus in Bornean tropical rainforest ecosystems
Yuki Tsujii 2018 Contents
Acknowledgements p 1
Chapter 1. General introduction p 3
Chapter 2. Significance of the localization of phosphorus among tissues on a cross- section of leaf lamina of Bornean tree species for phosphorus-use efficiency
p 33
Chapter 3. Phosphorus and nitrogen resorption from different chemical fractions in senescing leaves of tropical tree species on Mount Kinabalu, Borneo p 44
Chapter 4. Relationships of phosphorus concentration in reproductive organs with soil phosphorus availability for tropical rainforest tree species on Mount Kinabalu,
Borneo p 78
Chapter 5. Significance of phosphorus allocation among tree organs for the residence time of phosphorus in tropical rainforest biomass p 103
Chapter 6. General discussion p 132
References p 142
Acknowledgements
First and foremost, I express my sincere gratitude to my supervisor Prof. K.
Kitayama for his guidance, patience and encouragement throughout my study. He gave me the precious opportunity to conduct an ecosystem ecological study on
Mount Kinabalu, Borneo. The complex and diverse ecosystems on the mountain always stir my curiosity. Additionally, I thank my committee member Prof. Y.
Honda, Prof. Y. Kosugi, and Prof. K. Kitajima for their comments and discussions.
I thank Dr. Jamili Nais, Ms. Rimi Repin, Mr. Fred Tuh, Mr. Alim Biun, and all stuff of Sabah parks for giving me opportunities to study the ecosystems of
Mount Kinabalu, and their kind support. I also thank Assoc. Prof. S. Aiba, Assist.
Prof. Y. Onoda and Dr. A. Hidaka for their fruitful advice on field work and chemical analyses. Dr. M. Oikawa helped me examine a Micro-PIXE analysis with the staff members of NIRS, Japan. I would like to express my gratitude to the following persons: Assoc. Prof. N. Osawa, Prof. Y. Isagi, Prof. M. Takyu, Prof. J.
Yanai, Assoc. Prof. N. Okada, Assist. Prof. M. Yamasaki, Dr. R. Wagai, Dr. K.
Miyamoto, Assoc. Prof. T. Seino, Assoc. Prof. N. Imai, Dr. H. Samejima, Assist.
Prof. A. Nakao, Ms. Luiza Majuakim, Dr. K. Fujii, Dr. M. Ushio, Dr. K. Okada, Dr.
T. Mori, Dr. R. Aoyagi, Dr. H. Iidzuka, Dr. S. Fujiki, and Dr. R. Spake. Their comments helped me to improve my thesis.
Ms. Rosnah Binti Molidin, Mr. Therence Richie Kimpong, Mr. Daniel
James, Dr. A. Izuno, Dr. K. Ioki, Ms. L.J. Sun, Mr. S. Ando, Ms. C. Ikeda, Ms. Y.
Ichitsuka, Mr. S. Nishio, Mr. K. Nakashima, Mr. Y. Nomura, Mr. D. Yokoyama, Ms.
M. Mukai, Ms. M. Okano, Mr. T. Genroku, Ms. H. Nagano, Mr. T. Takehara, Ms. S.
Yanou, Mr. M. Nakano, Mr. H. Taga, and Ms. K. Ohira assisted me in field work
1 and chemical analyses. Members in the laboratory of forest ecology, Kyoto
University, commented to my work. I thank Ms. T. Norimoto, Ms. R. Fujiwara, and
Ms. K. Taneda for their daily support.
I would like to send my special thanks to all my Kadazan and Dusun friends.
Had it not been for their help, I could not do this work.
Finally, I thank my parents Mr. Sadahiko Tsujii and Ms. Etsuko Tsujii, my brothers Mr. Koki Tsujii and Mr. Haruki Tsujii, and my grandmother Ms. Matsue
Shimodaira.
This study was supported by JSPS KAKENHI Grant numbers JP16J11435 to Y. Tsujii, and JP22255002 to Prof. K. Kitayama, and ‘the MEXT Project for
Creation of Research Platforms and Sharing of Advanced Research Infrastructure’.
2
Chapter 1. General introduction
Phosphorus (P) is an essential element for all living organisms, and is used to build the molecules for genes (DNA and RNA), energy carriers (ATP and ADP), cellular membranes (phospholipids), and others (Westheimer 1987; Campbell & Farrell
2006; Alberts et al. 2013). Plants require P particularly for photosynthesis, because the substrates for binding carbon dioxides consist of P-containing compounds (i.e. sugar-phosphate) (Malkin & Niyogi 2000; Raven et al. 2005; Hawkesford et al.
2012). Therefore, P availability can be a selective pressure for plants by affecting photosynthesis (Shane et al. 2004; Thomas et al. 2006; Denton et al. 2007; Hidaka
& Kitayama 2009, 2013), productivity (Vitousek 1984; Wardle et al. 2004; Elser et al. 2007; Cleveland et al. 2011; Harpole et al. 2011), reproduction (Lambers et al.
2010; Wright et al. 2011; Fujita et al. 2014; Kitayama et al. 2015; DiManno &
Ostertag 2016), and others.
P in terrestrial ecosystems is derived mostly from rock weathering (Walker
& Syers 1976). Bioavailable P (i.e. inorganic P and labile organic P) in soils decreases with increasing soil age by leaching and/or the conversion to unavailable forms (e.g. P adsorption by soils), and consequently P is impoverished in old soils
(Fig. 1-1) (Walker & Syers 1976; Lajtha & Schlesinger 1988; Crews et al. 1995;
Richardson et al. 2004; Vitousek 2004; Turner et al. 2007; Laliberté et al. 2012).
Wardle et al. (2004) examined the change of tree basal area per area (a surrogate of tree biomass) in relation to the nitrogen (N):P ratios of fresh litter and humus, which increase with increasing P deficiency (Redfield 1958) along the following six pedogenesis chronosequences: the Cooloola dune sequence in eastern Australia, the
Arjeplog lake island sequence in Sweden, the Glacier Bay sequence in Alaska, the
3 chronosequence of the Hawaiian Archipelagos, and the Franz Josef and Waitutu sequences in New Zealand. The tree basal area increased in the earlier stage, and then decreased in the later stage of pedogenesis across the sequences. The decline of the tree basal area was linked with the increases of the N:P ratios of fresh litter and humus at the final stage of pedogenesis. Therefore, Wardle et al. (2004) suggested that forest retrogression occurred due to P deficiency in the end of pedogenesis across biomes.
Contrary to this hypothesis, Kitayama (2005) demonstrated that the biomass of Bornean tropical rainforests was maintained even on P-poor soils. He analyzed the relationship of tree aboveground biomass with the N:P ratio of fresh litter for Bornean tropical rainforests, and found that the biomass did not dramatically decline with the increase of the N:P ratio of leaf litter, which varied more widely than that in Wardle et al. (2004). Kitayama (2005, 2012) pointed out the extreme high species diversity in Bornean tropical rainforests compared with that in Wardle et al. (2004), and suggested that the high species diversity maintained forest biomass on P-poor soils by the increase of P-use efficient species in abundance with increasing P deficiency.
1.1. The questions, objectives and logical structure of this thesis
Soils in the tropics are often highly weathered and contain little bioavailable P
(Crews et al. 1995; Kitayama et al. 2000; Yang et al. 2014; Fujii et al. 2017).
Bornean tropical rainforests on such soils are gigantic and highly productive
(Kitayama 2005). This is thought to be because Bornean rainforest trees on P-poor soils have high P-use efficiency (PUE; net primary productivity per unit P absorbed from soils; Vitousek 1982) (Kitayama et al. 2000; Kitayama & Aiba 2002) with
4 adaptive mechanisms to P deficiency (Paoli et al. 2005; Hidaka & Kitayama 2011,
2013) (see section 1.2.). Previous studies have explored the underlying mechanism of high PUE by focusing on leaf, which is the primary photosynthetic organ of trees and requires a large amount of P, and have elucidated several mechanisms for high photosynthetic P-use efficiency and a long residence time of P in leaves (e.g. Paoli et al. 2005; Hidaka 2011; Hidaka & Kitayama 2009, 2011, 2013) (see section 1.3.).
On the other hand, a substantial amount of P is allocated to other functions, such as P storage (Ichie & Nakagawa 2013; Sardans & Peñuelas 2013; Zavišić &
Polle 2017), mechanical supporting (Tanner 1985; Meerts 2002; Chave et al. 2009;
Imai et al. 2010; Sardans & Peñuelas 2013; Heineman et al. 2016), P acquisition
(i.e. fine roots, Gordon & Jackson 2000; Yuan & Chen 2010; Yuan et al. 2011;
Wurzburger & Wright 2015; Okada et al. 2017), and especially reproduction
(Lambers et al. 2010; Ichie & Nakagawa 2013; Tully et al. 2013; Kitayama et al.
2015; Dimanno & Ostertag 2016). Reproduction requires much P for genes (DNA and RNA) and the investment for progenies (i.e. P storage in seeds) (Fenner et al.
1986; Lott et al. 2000; Fenner & Thompson 2005; Lambers et al. 2010) (see section
1.4). The investment of P to reproduction, which competes with that to photosynthesis and others (Obeso 2002), may influence PUE by affecting forest productivity. Therefore, the knowledge on the reproductive strategy of trees is required for understanding the maintenance of the biomass of forests on P-poor soils. However, the relationship of P with the reproduction of Bornean rainforest trees remains mostly unknown. This is because the reproduction is not easily observed due to the episodic occurrence of flowering/fruiting events, known as general flowering/fruiting (Ashton et al. 1988; Sakai 2002; Cannon et al. 2007).
A continuous monitoring is required for the observation of the reproduction
5 of Bornean rainforest trees. Therefore, I aimed to answer my research questions by conducting a continuous monitoring of the forests. In this chapter, I explain the novelty and importance of this thesis by reviewing previous studies addressing the
P-use strategies in production and reproduction for Bornean rainforest trees on P- poor soils. First, I introduce P-use efficiency (PUE), which is an essential concept to understand the P-use strategies of trees. Second, I focus on the relationship of the P-use strategies in production with PUE. I review the studies on the mechanism of trees to use P efficiently in production, and point out unresolved research questions for Bornean rainforest trees. Next, I review previous studies on the reproductive strategy of trees on P-poor soils. I propose the reproductive mechanisms of Bornean rainforest trees to use P efficiently based on the knowledge from the previous studies. Finally, I focus on the allocation of P among tree organs, such as leaves, wood, reproductive organs, and others, to understand the influence of the P-use strategies in production and reproduction on the dynamics of P in
Bornean tropical rainforest ecosystems. My working hypotheses are summarized in section 1.6..
1.2. Phosphorus-use efficiency
P-use efficiency (PUE), defined as net primary productivity per unit P absorbed from soils (Hirose 1971; Vitousek 1982), is an important concept to understand the relationship of the P-use strategies of plants with P availability, because plants on
P-poor soils theoretically and empirically exhibit greater PUE than those on P-rich soils (Loveless 1962; Vitousek 1984; Vitousek & Sanford 1986; Kitayama et al.
2000) (but see Chapin 1980). Chapin (1980) showed an exception that slow growing plants from infertile environments often exhibited lower PUE than rapid growing
6 plants from fertile soils when grown under similar environmental conditions (e.g.
Clarkson 1967; White 1972).
There are various procedures to calculate PUE at an individual leaf to a forest stand level (Hidaka 2011). In this chapter, I define the PUE at an individual leaf level, a whole plant level (including plant community level), and a forest stand level as the inverse of P concentration in leaf litterfall (Aerts & Chapin 1999), the inverse of P concentration in standing biomass (in the case of annual plants) (Chapin
1980), and the inverse of P concentration in fine litterfall including leaves, twigs, reproductive organs, and others (Vitousek 1982), respectively.
In the case of annual plants, the PUE at a plant community level can be calculated as the inverse of P concentration in standing biomass (Chapin 1980), because the P in standing biomass is equivalent to the uptake of P from soils in a year. However, this methodology cannot be simply applied to forest ecosystems, because it is technically difficult to estimate tree belowground biomass, belowground productivity, and annual P uptake from soils (Vitousek 1982). Instead,
Vitousek (1982) approximated the PUE at a forest stand level as the inverse of P concentration in fine litterfall, including leaves, twigs, reproductive organs, and others, for mature forests at a dynamic equilibrium, where the return of elements in litterfall may be equivalent with the uptake of elements.
Vitousek (1984) estimated the PUE at a forest stand level for 62 tropical forests, and showed that many of the forests exhibited a quite high PUE compared with temperate forests, where productivity is often limited by N (Vitousek &
Sanford 1986; Martinelli et al. 1999; Cleveland et al. 2011). This reflects that the productivity of tropical forests is often limited by P availability (Vitousek 1984).
PUE was estimated also across Bornean tropical rainforests, and negative
7 correlations of the PUE at a forest level with soil P availability were shown
(Kitayama et al. 2000; Paoli et al. 2005). Such a high PUE at forest stand level is considered to be associated with the adaptive mechanisms of trees to P deficiency, such as a low P concentration in tissues and P resorption from tissues during abscission (Vitousek 1984), a process by which plants resorb P from senescing tissues and recycle P in their bodies (Stoddart & Thomas 1982; Killingbeck 2004).
The PUE at a whole plant level is expressed as the product of P productivity
(productivity per P in tree biomass) and the residence time of P in tree biomass
(Berendse & Aerts 1987; see equation 1.1).
PUE = annual net productivity / annual uptake of P from soils
P productivity = annual net productivity / P bound in tree biomass
P residence time = P bound in tree biomass / annual return of P in litterfall†
PUE = P productivity * P residence time (equation 1.1)
† Annual return of P in litterfall is equivalent with annual uptake of P from soils under a dynamic equilibrium.
Hidaka (2011) applied this concept to the P dynamics in canopies. He estimated P productivity (i.e. annual net productivity per P bound in canopy) and the residence time of P in canopies for 37 Bornean tropical rainforests that differed in soil P availability. He found that the P productivity was invariant and the residence time of P increased with increasing PUE at a forest stand level. The same pattern was found also when the analysis was performed including the data of Paoli et al. (2005) which showed a negative correlation between the P productivity and the residence
8 time of P in canopy. This trend was in line with the results from the studies in other ecosystems (Hawaii, Vitousek 2004; Australian tropical rainforests, Gleason et al.
2009). Therefore, Hidaka (2011) concluded that high P productivity and a long residence time of P in canopy related to high PUE at a forest stand level.
1.3. Physiological mechanisms underlying high PUE
Photosynthesis is a key function to govern plant productivity, because the carbon
(C) fixed in photosynthesis accounts for ca. 40% of plant dry mass (Lambers et al.
2008b). Photosynthesis requires much P for substrates to bind carbon dioxide (i.e. sugar-phosphate) and energy carriers (i.e. ADP and ATP) (Malkin & Niyogi 2000;
Raven et al. 2005; Hawkesford et al. 2012). Therefore, the physiological mechanism of high PUE has been explored by focusing on leaf, which is the primary photosynthetic organ of trees.
The PUE at an individual leaf level is calculated as the inverse of P concentration in leaf litterfall (Aerts & Chapin 1999), and can be expressed as the product of photosynthetic productivity per unit leaf P (photosynthetic P-use efficiency; PPUE) (i.e. leaf-level P productivity) and the mean residence time of P in leaf biomass (MRT) (Berendse & Aerts 1987). These variables are thought to increase with increasing PUE at a forest stand level based on Hidaka (2011) (see section 1.2.). Indeed, high PPUE was found in Bornean rainforest trees on P-poor soils (Hidaka & Kitayama 2009, 2013). The efficient resorption of P from senescing leaves, which potentially increases MRT (Kazakou et al. 2007), was reported in
Bornean rainforest trees on P-poor soils (Hidaka & Kitayama 2011).
Bornean rainforest trees on P-poor soils exhibit high PPUE by maintaining rapid photosynthetic rates despite low P concentration in leaves (Hidaka &
9
Kitayama 2009, 2013). The mechanisms to maintain photosynthetic rates remain largely unknown for Bornean rainforest trees, whereas mechanisms underlying high
PPUE have been elucidated in Australian Proteaceae (see the following mechanisms; reviewed by Lambers et al. 2015a, b).
• Mechanism 1. A reduced investment of P to ribosomal RNA with ‘normal’ levels
of phosphorylated intermediates as the substrates for photosynthesis (Sulpice
et al. 2014): plants on P-poor soils have a relatively smaller investment of P to
ribosomal RNA in return with a slow protein synthesis, including Calvin–
Benson cycle enzymes. These plants maintain ‘normal’ levels of the
phosphorylated intermediates, which maximizes photosynthetic rates under a
relatively smaller amount of Calvin–Benson cycle enzymes.
• Mechanism 2. The replacement of phospholipids with galactolipids/sulfolipids
in membranes (Lambers et al. 2012): plants on P-poor soils have a relatively
smaller investment of P to cell membranes through the substitution of
phospholipids with non-phospholipids.
• Mechanism 3. The accumulation of P in photosynthetic mesophyll cells (Shane
et al. 2004): plants on P-poor soils have a large relative allocation of P to
photosynthesis by the accumulation of P in photosynthetic mesophyll cells.
The first and second mechanisms are associated with the composition of P containing compounds in leaves, and have been examined for Bornean rainforest trees (Hidaka & Kitayama 2011; 2013). Hidaka & Kitayama (2011) fractionated P containing compounds in the leaves of 21 Bornean rainforest tree species, from three sites with different soil P availabilities, into the following four fractions:
10 metabolic P (including inorganic P, ATP and sugar phosphates), nucleic acid P
(including DNA and RNA), lipid P (including cell membranes), and residual P using a series of extracting solutions (Bieleski 1968a, b; Chapin & Bieleski 1982; Chapin
& Kedrowski 1983; Hidaka & Kitayama 2011, 2013). They found that trees on P- poor soils had a lower P concentration in all fractions, including the nucleic acid and lipid fraction, than those on P-rich soils. This supports the mechanism 1 and 2; i.e. a low investment of P to nucleic acids, including RNA (the mechanism 1,
Sulpice et al. 2014), and to lipid, associated with the substitution of phospholipids with other lipids (the mechanism 2, Lambers et al. 2012). Furthermore, Hidaka &
Kitayama (2013) found a significant positive interspecific correlation of PPUE with the ratio of the metabolic P to the lipid P for 10 species from two of the same sites, indicating the importance of a large relative investment of P to metabolic functions in high PPUE. Therefore, Bornean rainforest trees on P-poor soils are thought to exhibit high PPUE by a large relative allocation of P to the P-containing compounds used for metabolic activities in exchange with the reduced investment to nucleic acids and lipids.
On the other hand, the anatomical mechanism of high PPUE (i.e. the mechanism 3) has not been examined for Bornean rainforest trees. The anatomical mechanism is related to the spatial heterogeneity of P among leaf tissues. Leaf tissues are classified to photosynthetic tissues (e.g. palisade and spongy mesophyll, and vascular bundles), and non-photosynthetic tissues (e.g. cuticle, epidermis, hypodermis, xylem, and phloem) (Fahn 1982; Evert 2006). Shane et al. (2004) showed that Australian Hakea prostrata (Proteaceae), which naturally inhabited P- poor environments and exhibited high PPUE, accumulated P in photosynthetic mesophyll cells (i.e. palisade mesophyll) in response to P fertilization; this was in
11 contrast with the general pattern that eudicots accumulate P in non-photosynthetic cells (i.e. epidermis cells) (Conn & Gilliham 2010). The localization of P to photosynthetic mesophyll cells means an increased allocation of P to photosynthesis, which may lead to high PPUE (Lambers et al. 2015a). The same phenomenon is possible for Bornean rainforest trees on P-poor soils, because the trees showed a large relative allocation of P to P containing compounds for metabolic activities such as ATP and sugar-phosphates (Hidaka & Kitayama 2009, 2013) (hypothesis 1).
Another component of the PUE at an individual leaf level is the mean residence time of P in leaves (MRT; Berendse & Aerts 1987). MRT can be elongated by longer leaf life span (LLS) and the efficient resorption of P from senescing leaves
(Escudero et al. 1992; Aerts & Chapin 1999; Paoli et al. 2005; Kazakou et al. 2007;
Hidaka 2011). Hidaka (2011) calculated LLS and P resorption efficiency (PRE), defined as the percentage of P resorbed from leaves prior to abscission (Killingbeck
1996, 2004), for the canopies of 37 Bornean tropical rainforests with different PUEs.
He found a weak positive correlation of LLS with the PUE and a significant positive correlation of PRE with the PUE. This suggests that both LLS and PRE contribute to increasing MRT in Bornean rainforest trees.
The long LLS of trees on P-poor soils may be associated with a large leaf dry mass per unit area (LMA). Hidaka & Kitayama (2011) compared LMA among
Bornean rainforest trees from three different P availability sites, and found that mean LMA of trees on P-poor soils was significantly greater than that on P-rich soils. The greater LMA may result from a thick epidermis, cuticle, and abundant sclerenchyma (Cunningham et al. 1999; Poorter et al. 2009; Lambers et al. 2015a), which leads to a longer LLS by higher leaf physical strength (Onoda et al. 2011)
(hypothesis 2). However, the anatomical structure of the leaves of Bornean
12 rainforest trees has not been studied well.
Bornean rainforest trees on P-poor soils exhibit an extremely high PRE
(>80%; Hidaka & Kitayama 2011), while the global average of PRE is around 50–
60% in evergreen angiosperms (Yuan & Chen 2009a; Vergutz et al. 2012). There are three possible mechanisms underlying the high PRE: 1) high transportation rates
(Zhang et al. 2015), 2) a great ratio of labile to recalcitrant P in leaves (Mao et al.
2015), and 3) a high degradation capacity of recalcitrant compounds (implied by
Hidaka & Kitayama 2011). The first mechanism was examined for
Dipterocarpaceae species, which predominate Southeast Asia including Borneo.
Zhang et al. (2015) examined the relationships of N and P resorption efficiency with leaf vein density for 17 Dipterocarpaceae species in a common garden. They found
N resorption efficiency was positively correlated with leaf vein density, and suggested that a greater phloem transport capacity led to a greater N resorption efficiency (Zhang et al. 2015). In contrast, PRE was not correlated with leaf vein density (Zhang et al. 2015). This result implies the importance of the other factors in the variation in PRE. For the second mechanism, Mao et al. (2015) explored the relationship of PRE with the ratio of inorganic to organic P in plant organs in the freshwater marsh of Northeast China, and showed that PRE increased with an increasing ratio of inorganic to organic P in plant organs. However, contrary to Mao et al. (2015), Hidaka & Kitayama (2011) showed that the PRE of Bornean rainforest trees in P-poorer sites was greater than those in P-rich sites, despite a constant allocation ratio of P to labile fraction in leaves. This suggests that the high PRE of
Bornean rainforest trees did not necessarily depend on the ratio of labile to recalcitrant P in leaves. Therefore, the high degradation capacity of recalcitrant compounds may be important in high PRE (hypothesis 3). However, this hypothesis
13 has not been investigated yet.
1.4.1. The reproductive strategy of trees on P-poor soils
Reproduction requires much P for genes (DNA and RNA) and progenies (e.g. phytic acids in seeds) (Fenner et al. 1986; Kitajima & Fenner 2000; Lott et a. 2000; Fenner
& Thompson 2005; Lambers et al. 2010). The allocation ratio of P to reproduction was ca. 10–15% of the total P flux through an internal P cycle as litterfall in Bornean rainforests on P-poor soils (Fig. 1-2, Kitayama et al. 2015). Such a large allocation of P to reproduction was found also in other species (e.g. Ichie et al. 2005; Lambers et al. 2010). In the case of Banksia hookeriana (Proteaceae), which naturally grows on P-poor soils in Australia, the P in seeds accounted for more than 48% of the P bound in aboveground biomass (Witkowski & Lamont 1996). These suggest that the reproductive strategy of trees has a large influence on the dynamics of P in forest ecosystems.
Plants on P-poor soils are known to use P efficiently in reproduction by at least the following three mechanisms: 1) P resorption from inflorescences during abscission (Ashman 1994a), 2) the relative accumulation of P in seeds (e.g.
Atkinson & Davison 1971; Witkowski 1990; Groom & Lamont 2010; DiManno &
Ostertag 2016), and 3) the storage of P in stems (Sala et al. 2012; Ichie & Nakagawa
2013). First, Ashman (1994a) showed that P was resorbed from calyx, corolla complex, and ovary in inflorescences during abscission. The resorbed P may be translocated to fruits, and may help their developments. Second, plants on P-poor soils may show rapid seedling growth under P limitation by a large storage of P in seeds (e.g. Atkinson & Davison 1971; Witkowski 1990; Thomson & Bolger 1993;
Groom & Lamont, 2010; DiManno & Ostertag 2016; Vandamme et al. 2016).
14
Groom & Lamont (2010) showed that Proteaceae from southwestern Australia
(stronger P deficiency) had more than two-fold greater P concentration in seeds than those from the Cape of Africa (weaker P deficiency). Similarly DiManno & Ostertag
(2016) demonstrated that Hawaiian Metrosideros polymorpha (Myrtaceae) at P- limited sites (i.e. more P-poor sites) had a greater P concentration in seeds than that at P-richer sites. The storage of P in seeds was verified to support rapid seedling growth on P-poor soils (Thomson & Bolger 1993; Groom & Lamont, 2010;
Vandamme et al. 2016). Finally, the storage of P in stem may be important in flowering/fruiting on P-poor soils. Ichie & Nakagawa (2013) monitored P concentration in the stems of Dryobalanops aromatica (Dipterocarpaceae) in a masting period in Bornean lowland rainforests, and found that P concentration in the stem significantly decreased during reproduction. The P stored in a tree, mainly in the stem, accounted for 67.7% of the total P used in reproduction.
1.4.2. The reproductive strategy of Bornean rainforest trees
Tropical rainforests in Southeast Asia demonstrated an episodic reprodution, known as general flowering/fruiting (Medway 1972; Appanah 1985, 1993; Ashton et al.
1988; Sakai et al. 1999; Brearley et al. 2007; Cannon et al. 2007). Many ultimate and proximate factors are known to regulate this epidodic reporodution (van Schaik et al. 1993; Kelly 1994; Kely & Sork 2002; Pearse et al. 2016): e.g. ultimate factors, including predator satiation hypothesis (Janzen 1971, 1974; Curran et al. 1999) and the promotion of pollination by interspecific synchronization (Sakai et al. 1999), and proximate factors including weather cues, such as a low minimum air temperature and droughts associated with El Nino southern oscillation (Ashton et al. 1988; Curran et al. 1999; Yasuda et al. 1999; Numata et al. 2003; Sakai et al.
15
2006; Chen et al. 2017a; Kurten et al. in press; Yeoh et al. 2017) and others (van
Schaik et al. 1993; Wright & van Schaik 1994), and the storage of resources in a tree (Isagi et al. 1997; Satake & Iwasa 2000; Ichie & Nakagawa 2013). This episodic flowering/fruiting may be considered as an adaptation to P deficiency, beacuse the trees on P-poor soils may require accumlated P for the flowering/fruiting (Ichie et al. 2005; Ichie & Nakagawa 2013).
A long-term monitoring is required for the observation of the reproduction of tropical rainforest trees in Southeast Asia. Kitayama et al. (2015) conducted a
10-year continuous monitoring of litterfall in eight tropical rainforests that differed in soil P availability on Mount Kinabalu, Borneo. They calculated the allocation ratios of C, N, and P to reproductive-organ litter per total litterfall, and found that these ratios were invariant across the forests. This suggests that Bornean rainforest trees maintain reproductive activities even under a strong P deficiency. This was in contrast with European herbaceous vegetation (Fujita et al. 2014), where plants on
P-poorer soils showed a less investment of resource in sexual reproduction.
Why Bornean rainforest trees can maintain P-expensive reproductive activities on P-poorer soils? One possibility is that the trees on P-poor soils exhibit a low P concentration in reproductive organs (Kitayama et al. 2015). Kitayama et al. (2015) showed a significant negative correlation of P concentration in reproductive-organ litter with the PUE at a forest stand level (Fig. 1-3), and raised the following two hypotheses: 1) the dilution of P in flowers/fruits with increasing
PUE, and 2) the increase of species with capsulate fruits in abundance with increasing PUE (see chapter 4 for the detail of these hypothesis). The first hypothesis points to different P demands among reproductive organs, including inflorescence, seed, pericarp, and pedicle etc. P demand may be different among
16 these components depending on their roles. For instance, seeds may require much
P for germination, and seedling growth on P-poor soils (Milberg & Lamont 1997;
Lamont & Groom 2002; White & Veneklaas, 2012; Vandamme et al., 2016), while pericarps and pedicles may not require P for the growth of progenies. If so, trees on
P-poor soils would have a lower P concentration in pericarps but not in seeds
(hypothesis 4). Indeed, plants adapted to P deficiency is known to preferentially allocate P to seeds compared with pericarps (DiManno & Ostertag 2016). The second hypothesis focused on different P concentration among fruit types.
Capsulate fruits are expected to show lower P concentration than fleshy fruits, because dry woody pericarps may contain a lesser amount of P compared with fleshy pericarps. The relative abundance of tree species with capsulate fruits may increase with increasing P deficiency. If so, the shift of species composition will reduce mean concentration of P per site in reproductive organs (hypothesis 5). To test these hypothesis is required for understanding the reproductive strategy of
Bornean rainforest trees on P-poor soils.
1.5. Significance of the P-use strategies of trees for the P dynamics in forest ecosystems
How strongly the P-use strategies of trees influence the P dynamics in forest ecosystems? Previous studies explored this question by focusing on the residence time of P in tree biomass, defined as the P bound in tree biomass divided by the annual loss of P via litterfall (Kazakou et al. 2007; Hidaka 2011). Kazakou et al.
(2007) simulated mathematically the contributions of leaf life span (LLS) and P resorption efficiency (PRE) to the mean residence time of P in leaves (MRT). MRT is expressed as LLS divided by (1 – PRE) (see equation 1.2). Therefore, the
17 contribution of LLS to MRT is in direct proportion to MRT for a given value of PRE
(i.e. the increase of 10% in LLS yields the increase of 10% in MRT) (see equation
1.3), while the contribution of PRE to MRT exponentially increases with increasing
PRE (see equation 1.4). For instance, the change of 10% in LLS yields the change of 10% in MRT when PRE equals 50%, while the change of 10% in PRE yields the change of 40% in MRT when PRE equals 80%.
MRT = LLS / (1 - PRE) (equation 1.2)
δMRT / δLLS = 1 / (1 - PRE)
δMRT / δPRE = LLS / (1 - PRE)2
The elasticity of the contribution of LLS on MRT = LLS / MRT * δMRT / δLLS
= 1 (equation 1.3)
The elasticity of the contribution of PRE on MRT = PRE / MRT * δMRT / δPRE
= PRE / (1 - PRE)
(equation 1.4)
Hidaka (2011) evaluated empirically the contribution of PRE to the residence time of P in canopy by subtracting LLS from the residence time of P in canopy for 37
Bornean tropical rainforests. He showed that the contribution of PRE to the residence time of P in canopy increased with increasing PUE, which became greater than that of LLS when PRE was greater than 50%. This is in line with Kazakou et al. (2007). Bornean rainforest trees on P-poor soils are known to exhibit an
18 extremely high PRE (>80%; Hidaka & Kitayama 2011). Thus, the residence time of
P in tree biomass may be influenced on P-poor soils especially by PRE.
However, the results from these studies could not represent the contribution of PRE to the residence time of P in whole tree biomass. The exact contribution should be smaller than would be expected from the previous studies, because the P bound in leaf biomass accounts for <50% of the total P in tree biomass (Tanner et al. 1982; Jonson et al. 2001; Feldpasch et al. 2004; Imai et al. 2010; Sardans &
Peñuelas 2013, 2015). More than 50% of the P bound in tree biomass is often contained in wood biomass (Tanner et al. 1985; Jonson et al. 2001; Feldpasch et al.
2004; Imai et al. 2010; Sardans & Peñuelas 2013, 2015), and hence the P bound in wood biomass may have a large influence on the residence time of P in tree biomass.
Therefore, the contribution of PRE to the residence time of P in tree biomass should be evaluated in light of the P bound in wood biomass.
P allocation among tree organs is a key factor to determine the contribution of PRE to the residence time of P in tree biomass, when taking the P bound in wood biomass into account. For instance, a greater allocation ratio of P to leaves may lead to a greater contribution of PRE to the residence time of P in tree biomass for given values of the other parameters. The allocation ratio of P to leaves may increase with increasing P deficiency (Gleason et al. 2009; Aoyagi & Kitayama 2016). Aoyagi &
Kitayama (2016) investigated P allocation among tree organs (leaves, stems, and roots) in relation to “realized” P availability, expressed as P concentration in whole plant (total P mass per total biomass), for the saplings of 13 Bornean tree species, and found a significant increase of the allocation ratio of P to leaves with decreasing realized P availability. The similar trend was found also for mature trees (Gleason et al. 2009). Gleason et al. (2009) analyzed P concentration in leaves (leaf [P]) and
19 wood (wood [P]) for both schist specialists (the specialists on P-poor soils) and generalists occurring both on basalt (P-rich soils) and schist soils (P-poor soils) for mature trees in Australian rainforests. They showed that the schist specialists had
27% greater leaf [P]:wood [P] ratio than generalists occurring on schist soils, and suggested that specialists on P-poor soils allocated more P to leaves relative to wood than generalists. In addition, the contribution of PRE to the residence time of P in canopy may exponentially increase with increasing P deficiency (Hidaka 2011).
Therefore, the contribution of PRE to the residence time of P in tree biomass is expected to increase with increasing P deficiency (hypothesis 6).
1.6. Synthesis and outline of this thesis
As reviewed above, previous studies have focused on productivity only to explain the maintenance of the biomass of Bornean tropical rainforests on P-poor soils
(section 1.3). On the other hand, Kitayama et al. (2015) showed a lower P concentration in reproductive-organ litter on P-poor soils, which may influence the maintenance of forests on P-poor soils (section 1.4). Therefore, I hypothesized that trees on P-poor soils used P efficiently in reproduction as well as in production, both of which related to the maintenance of Bornean tropical rainforests on P-poor soils. To test this hypothesis, this thesis addressed the following three questions: 1) how do Bornean rainforest trees use P efficiently in production, 2) how do the trees use P efficiently in reproduction, and 3) how do these P-use strategies affect the P dynamics in forest ecosystems?
In Chapter 2 and 3, I investigated the strategies of Bornean rainforest trees to maintain productivity on P-poor soils (the first question). Although many studies examined the P-use strategies in production for Bornean rainforest trees, there
20 remained the following three untested hypotheses: 1) Bornean rainforest trees on P- poor soils allocate a relatively large fraction of P to photosynthesis by investing P to photosynthetic cells, which helps maintain rapid photosynthetic rates under P limitation, 2) the trees on P-poor soils produce long-lived leaves with tough anatomical structures, including developed epidermis with thick cuticles, which elongate the residence time of P in leaves, and 3) the trees on P-poor soils resorb more P from senescing leaves by degrading recalcitrant compounds compared with those on P-rich soils (section 1.3). In Chapter 2, I tested the hypotheses 1 and 2
(anatomical mechanisms) by examining the spatial distribution of P on the cross- section of leaf lamina using a micro-PIXE technique (particle-induced X-ray emission analysis with a focused ion beam). Micro-PIXE provides a semi- quantitative elemental map by detecting the gradient of characteristic X-ray emissions from the sample surface (Mesjasz-Przybyłowicz & Przybyłowicz 2002;
Oikawa et al. 2015). I compared P concentration among tissues on the cross-section of leaf lamina for Bornean tree species growing on P-poor soils (the hypothesis 1).
The anatomical structures of leaves were examined using a florescence microscope
(the hypothesis 2). In Chapter 3, the biochemical mechanism of high PRE was examined by fractionating P containing compounds in leaves into chemical fractions. I calculated the P resorption rate in each of the chemical fractions and compared P resorption rate among the fractions during senescence (the hypothesis
3).
In Chapter 4, I addressed the reproductive strategy of Bornean rainforest trees on P-poor soils (the second question). Based on Kitayama et al. (2015), I raised the following two hypotheses: 1) trees on P-poorer soils have a lower P concentration in reproductive organs by reducing P concetration in pericarps but
21 not in inflorescences and seeds (hypothesis 4), and 2) capsulate species increase in abundance with increasing P deficiency, which dilutes overall P concentration in reproductive organs per site (hypothesis 5). I conducted a 5-year continuous monitoring of Bornean tropical rainforests, analyzed P concentration in reproductive organs (inflorescences, seeds, and pericarps), and examined the hypotheses.
In Chapter 5, I quantitatively estimated the contribution of PRE to the residence time of P in tree biomass. I focused on the residence time of P in tree aboveground biomass (AGB; including leaves and wood), because the allocation ratio of P to belowground biomass (i.e. roots) was not substantial in my study sites
(ca. 10–40% of total P mass allocated to belowground, Fig. 1-4; Tsujii, Aiba &
Kitayama unpublished data) and technically could not estimate the annual loss of P via root litterfall. I estimated the residence time of P in AGB for eight tropical rainforests on Mount Kinabalu, Borneo, and discussed the contribution of PRE on the P dynamics in forest ecosystems.
I addressed the following hypotheses.
• Hypothesis 1. Bornean rainforest trees on P-poorer soils exhibit high PPUE by
a large relative allocation of P to photosynthesis through the accumulation of P
in photosynthetic mesophyll (Chapter 2).
• Hypothesis 2. Bornean rainforest trees on P-poorer soils have tough leaf
anatomical structures, including thick cuticles, epidermis, and hypodermis
(Chapter 2).
• Hypothesis 3. Bornean rainforest trees on P-poorer soils exhibit high PRE by
degrading more recalcitrant compounds (Chapter 3).
22
• Hypothesis 4. Bornean rainforest trees on P-poorer soils have a lower P
concentration in reproductive organs by reducing P concetration in pericarps
but not in inflorescences and seeds (Chapter 4)
• Hypothesis 5. Capsulate species increase in abundance with increasing P
deficiency, which dilutes the overall P concentration in reproductive organs per
site (Chapter 4)
• Hypothesis 6. The contribution of PRE on the residence time of AGB increaeses
with incraesing P deficiency (Chapter 5)
1.7. Study sites: Mount Kinabalu, Borneo
Mount Kinabalu, Borneo (6°05′ N, 116°33′ E, 4096 m a.s.l.), is the highest mountain between the Himalayas and Irian Jaya in New Guinea (Harison 1996). Mount
Kinabalu is a non-volcanic mountain, and consists of granitic rock above 3000 m and of Tertiary sedimentary rocks below 3000 m (Collenette 1964; Choi 1996;
Burton-Johnson et al. 2017). Ultrabasic rocks occur among the granite and sedimentary substrates as mosaic. The soils derived from ultramafic rocks often contain less bioavailable P compared with those from granite and sedimentary substrates (Proctor 2003). Mount Kinabalu with its surrounding area is designated as Sabah state park and is managed by the Sabah Parks (ca. 75000 ha, from ca. 150–
4100 m above sea level) (Liew 1996; Ismail & Ali 1996).
Mount Kinabalu is one of the most species rich areas in the world (Merckx et al. 2015), where more than 5000 taxa of vascular plants are recorded (Beaman et al. 2001; Beaman 2005). The park area was designated as a World Heritage Site by
UNESCO in 2000, because of the diverse biota and high endemism, associated with high environmental variations, such as the wide gradients of altitude, climate,
23 topography, and geology (UNESCO 2000). The high species diversity on Mount
Kinabalu is thought to be associated with the following reasons: 1) a large climatic variation along an altitudinal gradient, from a lowland zone near sea level to an alpine zone (Stapf 1894; Hotta 1974; Kobayashi & Hotta 1978; Kitayama 1992), 2) an effective genetic differentiation underpinned by a precipitous topography
(Beaman 1996; Repin 1998; van der Ent et al. 2014, 2016, 2018), 3) a large topographical variation, including sedimentary, granitic, and ultrabasic substrates
(Collenette 1964; Beaman & Beaman 1990; Choi 1996; Kitayama & Aiba 2002;
Aiba et al. 2015), 4) geological history of the Malay Archipelago of several tectonic plates (van Steenis 1964; Barkman & Simpson 2001; Merckx et al. 2015), 5) temporal climatic variation linked with El Nino Southern Oscillation (ENSO) (Lee
& Lowry 1980; Kudo & Kitayama 1999; Aiba & Kitayama 2002; Kitayama et al.
2014; Sawada et al. 2015), 6) environmental instability resulting from landslips, droughts, flooding, and glaciation (Beaman et al. 2001), and 7) other factors (e.g. plant-soil feedback, Ushio et al. 2017).
Nine tropical rainforests were selected on the southern slope of Mount
Kinabalu by earlier workers (Aiba & Kitayama 1999; Aiba et al. 2002; Kitayama &
Aiba 2002). Eight of the nine forests were placed as a matrix manner consisting of four elevations (ca. 700, 1700, 2700, and 3100 m) and two substrates (P-rich sedimentary and P-poor ultrabasic rocks), which were established to explore the effect of the interaction of P availability and altitude on ecosystem properties (Aiba
& Kityama 1999; Kitayama & Aiba 2002). The 3100-m “sedimentary” site is actually underlain by granite rock. Another forest on Quaternary colluvial sedimentary rock deposits at 1700 m was also selected (Takyu et al. 2002a, b, 2003).
These nine forests have been continuously monitored for population turnover, wood
24 increment, litterfall, and others from 1996 by a Japanese research team in collaboration with Sabah Parks (Aiba & Kitayama 1999; Kitayama & Aiba 2002;
Kitayama et al. 2015).
The climate of these sites is aseasonal humid tropical. Mean annual air temperature is 24.3°C at 550 m and declines with a lapse rate of 0.55°C per 100 m
(Kitayama 1992), from ca. 23.9°C at the 700-m sedimentary site to ca. 10.6°C at the 3100-m sedimentary site. The pool size of soil P was different among the sites depending on geological substrates and weathering intensity in relation to altitude
(Wagai et al. 2008). The pool size of total and soluble soil P (extracted with 0.03N
NH4F/0.1N HCl solution) was greater in the sedimentary sites than in the ultrabasic sites at the same altitude (Kitayama et al. 2000). Among the three sites at 1700 m, the pool size of total and soluble soil P was greatest in the Quaternary sedimentary site, moderate in the Tertiary sedimentary site, and lowest in the ultrabasic site
(Kitayama et al. 2004). Detailed information on these sites is provided in Table 1.
Tree species composition
The composition of tree species dramatically changes along an altitudinal gradient and across soil substrates (Kitayama 1992; Aiba & Kitayama 1999; Aiba et al. 2002;
Takyu et al. 2002a) (see the sample list in table 6–S1). The two lowest sites (700- m sites) are classified as lowland dipterocarp forest. The lowland ultrabasic site is dominated by Shorea (Dipterocarpaceae), Agathis (Araucariaceae) with Myrtacea,
Sapotaceae, Fagacea, Lauraceae and others, whereas the lowland sedimentary site is dominated by primarily Shorea (Dipterocarpaceae) with Myrtaceae, Sapotaceae,
Fagaceae, Lauraceae and others.
The three 1700-m sites are classified as lower montane forest. The
25
Quaternary sedimentary site (most P-rich soils) is dominated by Magnolia
(Magnoliaceae), Ternstroemia (Theaceae), Lithocarpus (Fagaceae), Syzygium
(Myrtaceae), Madhuca (Sapotaceae) and others. The Tertiary-sedimentary site (P- intermediate soils) is dominated by some conifers, such as Dacrycarpus and
Dacrydium (Podocarpaceae), and angiosperms such as Tristaniopsis, Syzygium
(Myrtaceae), Lithocarpus (Fagaceae), Sapotaceae, Clusiaceae, and others. The ultrabasic site (most P-poor soils) is dominated primarily by Tristaniopsis
(Myrtaceae), and some conifers including Agathis (Araucariaceae), Podocarpus and
Dacrydium (Podocarpaceae), and angiosperms such as Weinmannia (Cunoniaceae),
Lithocarpus (Fagaceae), Syzygium (Myrtaceae), and others.
The 2700 and 3100-m sites are classified as upper montane or subalpine forest. The 2700-m sedimentary site is classified as montane cloud forest, where canopy is dominated by Magnolia (Magnoliaceae), Syzygium (Myrtaceae), Ilex
(Aquifoliaceae), Olea (Oleaceae), and others with understory covered with
Racemobambos gibbsiae (Poaceae). The 2700-m ultrabasic site is dominated by conifers, such as Dacrycarpus and Dacrydium (Podocarpaceae), and angiosperms such as Leptospermum (Myrtaceae), Syzygium (Myrtaceae) and Schima (Theaceae).
The 3100-m sedimentary site (actually granite rocks) is dominated by Dacrycarpus
(Podocarpaceae), Syzygium and Leptospermum (Myrtaceae), Ilex (Aquifoliaceae),
Polyospma (Escalloniaceae), and etc. In contrast, the 3100-m ultrabasic site is dominated mostly (>80%) by a single species Leptospermum recurvum (Myrtaceae).
26
Table 1-1. Description of the eight study sites on Mount Kinabalu, Borneo. Canopy height represents the maximum height of a tree at the site (cited from Kitayama & Aiba 2002). Total soil P represents the mean content of total soil P per site (30 cm depth in a topsoil) (cited from Kitayama et al. 2000). Soluble soil P represents the mean concentration per site of soluble soil P that was extracted with hydrochloric-ammonium fluoride solution (15 cm depth in a topsoil) (cited from Kitayama & Aiba 2002 and Takyu et al. 2002b). P-use efficiency (PUE) is calculated as the inverse of the P concentration in litter that was collected during the 10 years from 1996 to 2006 (cited from Kitayama et al. 2015).
Site name 700S 1700S 2700S 3100S 700U 1700U 2700U 3100U 1700Q Altitude (m) 650 1560 2590 3080 700 1860 2700 3050 1860 Slope (°) 19 17 20 27 11 24 22 19 15 Canopy height (m) 46.8 30 20.6 15 65.4 22.6 14.2 6.1 32.1 ANPP (g m-2 yr-1) 1913 1110 780 816 1715 813 725 199 1230
Mean annual air temperature (°C) 23.8 18.7 13.1 10.4 23.5 17.1 12.5 10.6 17.1
Mean annual precipitation (mm yr-1) 2509 2714 2085 3285 2509 2714 2085 3285 2714
27
Table 1-1. (Continued)
Site name 700S 1700S 2700S 3100S 700U 1700U 2700U 3100U 1700Q Soil properties Quaternary Substrate Sedimentray Sedimentary Sedimentary Granite Ultrabasic Ultrabasic Ultrabasic Ultrabasic sedimentary
pH (H2O) 4.1 4.0 3.4 4.9 4.5 5.4 5.1 5.3 4.1 Total soil P (g m-2) 61.36 34.87 72.57 37.15 29.19 8.97 21.47 12.02 60.82 Soluble soil P (g m-2) 0.18 0.14 0.36 0.35 0.14 0.04 0.09 0.07 0.19 Total N (%) 0.21 0.32 0.92 0.60 0.21 0.28 0.35 0.26 0.56 -1 NH4-N (μg g ) 3.9 23 29.9 4.80 8.9 26.6 7.3 5.2 19.3 -1 NO3-N (μg g ) 10.2 1.8 2.9 8.40 7.2 0.8 0.8 NA 11.5 PUE (g g-1) 2195 3025 2230 2478 2266 5159 4785 6326 1964 Hill Lower Upper Hill Lower Upper Lower Subalpine Subalpine Forest type dipterocarp montane montane dipterocarp montane montane montane forest forest forest forest forest forest forest forest rain forest
28
Figure 1-1. Changes in the profiles of P in terrestrial ecosystems along a long-term soil development. This figure was illustrated based on Walker & Syers (1976).
29
Figure 1-2. Relationship between the relative allocation ratio of P to reproductive- organ litter and P-use efficiency (PUE) at forest stand level for eight tropical rainforests on Mount Kinabalu, Borneo. A dotted line denotes a non-significant correlation (P = 0.23). PUE is calculated as the inverse of the P concentration in litter that was collected during the 10 years from 1996 to 2006 (cited from Kitayama et al. 2015). This figure was illustrated based on the data from Kitayama et al.
(2015).
30
Figure 1-3. Relationship between P concentration in reproductive-organ litter and
P-use efficiency (PUE) at forest stand level for eight tropical rainforests on Mount
Kinabalu, Borneo. PUE is calculated as the inverse of the P concentration in litter that was collected during the 10 years from 1996 to 2006 (cited from Kitayama et al. 2015). A solid line denotes a significant correlation (P < 0.05). This figure was illustrated based on the data Kitayama et al. (2015).
31
Figure 1-4. P mass by tree organs (a and b) and their relative allocation (c and d) for the aboveground biomass of eight tropical rainforests on Mount Kinabalu,
Borneo. P mass in wood on panels (a) and (c) represent the upper bound values estimated on the assumption that P concentration in wood was constant from the sapwood to heartwood area across a stem section. In contrast, P mass in wood on panels (b) and (d) represent the lower bound values estimated on the assumption that P was contained only in sapwood. P mass in leaves and wood were estimated in the chapter 5. P mass in fine roots were cited from Okada et al. (2017). The detailed methods are shown in Chapter 5.
32
Chapter 2. Significance of the localization of phosphorus among tissues on a cross-section of leaf lamina of Bornean tree species for phosphorus-use efficiency
Abstract
A greater relative allocation of phosphorus (P) to photosynthetically active cells functions to maintain a rapid photosynthesis under P limitation, and may be a key mechanism of plants to use P efficiently. This mechanism has not been studied in tropical trees despite the productivity of tropical forests being often limited by P. In this study, the spatial distribution of P among tissues on a cross-section of leaf lamina was analyzed for 13 tree species from P-limited sites on Mount Kinabalu, Borneo.
Most species showed greater P concentration in palisade mesophyll than in spongy mesophyll and epidermal tissues, suggesting that tropical trees under P limitation localize leaf P to photosynthetic palisade mesophyll cells.
Key words: anatomical structure, foliar-element distribution, micro-PIXE, phosphorus deficiency, phosphorus-use efficiency, photosynthesis, tropical forest
33
2.1. Introduction
Understanding the adaptive mechanisms of trees to phosphorus (P) limitation is a major topic in tropical ecology, because the productivity of tropical forests is often limited by P (Vitousek 1984; Cleveland et al. 2011). Trees under P limitation typically have low concentrations of total foliar P (total foliar [P]) (Hidaka &
Kitayama 2009; Ordoñez et al. 2009; Lambers et al. 2012). They show fast photosynthetic rates per unit mass despite the low total foliar [P], consequently exhibiting high photosynthetic P-use efficiency (PPUE; photosynthetic rate per unit foliar P) (Hidaka & Kitayama 2009). The high PPUE contributes to a high carbon acquisition per unit P absorbed (P-use efficiency) at a plant individual level
(Berendse & Aerts 1987), which may be adaptive to P limitation. Thus, elucidating the mechanisms underlying the high PPUE is essential to understanding the adaptation of trees to P limitation.
One explanation of the high PPUE is a greater relative allocation of P to photosynthesis via the localization of foliar P in photosynthetic cells (Shane et al.
2004). Shane et al. (2004) showed that Hakea prostrata (Proteaceae) adapted to P- limitation accumulates P in palisade mesophyll at high P supplies, which contrasts to the general pattern that eudicots accumulate P in the epidermis (Conn & Gilliham
2010). The accumulation of P in mesophyll was found also in other Proteaceae species (Hawkins et al. 2008; Lambers et al. 2015), but has not been studied in tropical trees.
2.2. Materials and methods
I studied the localization of P within a leaf for tropical rainforest trees. This study was performed in three forests on the southern slope of Mount Kinabalu, Borneo
34
(6°05′N, 116°33′E, 4096 m asl). These sites are different in soil P availability due to different geological substrates consisting of ultramafic rocks (P-poor), Tertiary sedimentary rocks (intermediate P) and Quaternary colluvial sedimentary rock deposits (P-rich) (Kitayama & Aiba 2002; Takyu et al. 2002b). Mean concentration of soluble soil P, which is extracted with hydrochloric-ammonium fluoride solution, is 0.44, 2.32 and 3.31 mg kg-1 dry weight in topsoils (15 cm depth) at the P-poor, P- intermediate, and P-rich sites (caluculated from the data of Takyu et al. 2002b), respectively. These sites were located at ca. 1700 m asl and close to each other
(within 10 km). The mean annual temperature was ca. 18°C and mean annual precipitation was ca. 2800 mm at the P-intermediate site (Kitayama 1992).
Four to five dominant canopy tree species, belonging to widespread genera or families across all the sites (see Table 2-1), were selected in each forest. Fully expanded sun leaves were sampled from three canopy individuals per species using a catapult. Sampled leaves were freeze-dried (under 20 Pa for 24 h) after having been frozen at -30°C. Portion of these samples was powdered and used for determining total foliar [P]. Freeze-dried leaves of one or two individuals per species were used for examining the spatial distribution of P within a leaf.
Total foliar [P] was determined by the following procedure. A powdered sample (ca. 200 mg) was digested in 5 mL of concentrated H2SO4 and 2 mL of 30%
(v/v) H2O2 at 380°C for 5 h. P concentration in the digest was determined using inductively coupled plasma atomic emission spectrometer (ICPS-7510, Shimadzu,
Japan).
The spatial distribution of P within a leaf was examined using a Micro-PIXE technique (particle-induced X-ray emission analysis with a focused ion beam)
(Mesjasz-Przybyłowicz & Przybyłowicz 2002) (Fig. 2-1). Micro-PIXE provides a
35 semi-quantitative elemental map by detecting the gradient of characteristic X-ray emissions among pixels. A freeze-dried sample was dissected into a cross-section
(thickness ca. 250 μm) using a sliding microtome (TU-213, Yamato Koki, Japan). An elemental map on the cross-section was captured using the nuclear microprobe at
National Institute of Radiological Sciences (NIRS), Japan. A proton beam with the energy of 3.0 MeV from the tandem type electrostatic accelerator was used for the micro-PIXE analysis system installed at NIRS-electrostatic accelerator facility
(Oikawa et al. 2015). The beam spot was approximately 1 μm in diameter. A scanning area for the micro-PIXE analysis system was adjusted according to the size of a cross- section (250–1000 × 250–1000 μm). After the micro-PIXE analysis, the cross-section was examined under a fluorescence microscope, and its image was captured using a microscope camera (DS-Vi1, NIKON, Japan; Fig. 2-1a). The following five tissue categories were demarcated on a fluorescence image; i.e. the upper epidermal tissues
(cuticle + epidermis + hypodermis), palisade mesophyll, spongy mesophyll and lower epidermal tissues (cuticle + epidermis) and vascular bundles. Boundaries among the tissue categories were visually demarcated as vector data, which were subsequently superimposed on the corresponding elemental map. The sample analyzed by a micro-
PIXE was partially discoloured by the ion beam, and the discoloured part was used as a marker to superimpose these two images.
Mean relative P concentration per tissue category on a cross-section was estimated as mean X-ray emission per pixel within the regions of each tissue category on an image. Mean X-ray emission per pixel represented the amount of P per pixel, because the strength of X-ray emission correlated with the amount of P. However, X- ray emission per P varied depending on the thickness of cross-section because I could not prepare cross-sections with a uniform thickness. Thus, X-ray emission per pixel
36 was not comparable among cross-sections and I here compared the relative P concentration among tissue categories on a given cross-section only. Mean X-ray emission per pixel in each tissue category was calculated using an image analysis software (Image J, http://rsb.info.nih.gov./ij/). Paired t-tests were performed to test differences in mean relative P concentration between tissue categories. Nineteen cross-sections were used as units of replication in this analysis.
An among-site difference in total foliar [P] was evaluated based on the means of the four or five dominant species per site by ANOVA. The 13 species were used as units of replication in this analysis. Statistical analyses were performed with R version 3.0.1.
2.3. Results and Discussion
Mean total foliar [P] per species ranged from 0.25–0.68 mg g-1 dry weight (Table 2-
1), which was much less than the average of terrestrial plants (over 1 mg g-1) (Han et al. 2005). This suggests that these species are under P limitation. The extracted data from the elemental maps suggested that most species had higher P concentration in palisade mesophyll than in the other tissues when compared on a single cross-section.
Scattergrams in Figure 2-2 show the relationships of the relative P concentration of the palisade mesophyll (Y axis) to that of the other tissues on the same cross-section
(X axis). Most points were located above the 1:1 line across the scattergrams (Figs.
2-2a–d). When all samples were pooled, mean differences between the Y values (the relative P concentration of the palisade mesophyll) and the paired X values (that of the other tissue on the same cross-section) were significantly greater than 0 across the scattergrams (paired t-test, t = 3.13–4.16, n = 18–19, P < 0.01; Figs. 2-2a–c), except for the vascular bundles (Fig. 2-2d). This indicates greater P concentration in
37 the palisade mesophyll than in the spongy mesophyll and epidermal tissues on a given cross-section. This greater P concentration in the palisade mesophyll is possibly associated with one or more of the following three possibilities: (1) the accumulation of P in mesophyll cells (Shane et al. 2004), (2) the dilution of P in the epidermal tissues by thick cell walls, and (3) very little P stored in the vacuoles of epidermis cells.
In contrast to the localization of P across most species, mean total foliar [P] per site based on dominant species was significantly lower at the P-poor site than the other sites (ANOVA, P < 0.01; Table 2-1). This low total foliar [P] may reflect the following three mechanisms; (1) the substitution of phospholipids with non- phospholipids, (2) a slower protein synthesis, and (3) a tougher leaf structure. First, trees may have low P concentrations in all cells through the substitution of phospholipids with non-phospholipids in membranes. Lambers et al. (2012) suggested that the Proteaceae species adapted to P limitation substitute phospholipids with galactolipids and sulfolipids. Second, the low total foliar [P] may be linked with a slower protein synthesis (Sulpice et al. 2014). Hidaka & Kitayama (2011) showed that low total foliar [P] was correlated with low concentrations of nucleic acid P. The low nucleic acid P may be linked with low concentrations of ribosomal-RNA, leading to a slower protein synthesis (Sulpice et al. 2014). Third, trees may have a tougher leaf structure including a thick cuticle and abundant sclerenchyma (Choong et al.
1992, Onoda et al. 2012). This leaf structure contributes to a high P-use efficiency by prolonged leaf longevity (Escudero et al. 1992), which may be adaptive to P- deficiency. Mean ± SE upper cuticle thickness per site based on dominant species was significantly greater at the P-poor site (9.0 ± 1.3 μm) than at the P-intermediate, and P-rich sites (4.9 ± 0.9, and 4.7 ± 0.2 μm, respectively) (Fig. 2-S1, ANOVA, P <
38
0.05). Sclerenchymatic cells, which have a greater specific density (Poorter et al.
2009), might be more abundant in the leaves of the P-poor site, because leaf mass per area (LMA) of the species at the P-poor site was greater (Hidaka & Kitayama 2011).
Sclerenchymatic cells contain a greater portion of cell walls, which are devoid of P
(Lambers et al. 2015).
39
Table 2-1. Species mean ± SE in total foliar [P] for 13 species from three forests on Mount Kinabalu, Borneo. Site mean, and P-value from an ANOVA test among sites in the site means were also reported. The site mean was calculated as the average of species means per site. † The numbers in parentheses represent the sample sizes taken for micro-PIXE experiments per species.
Species Total foliar [P] (mg g-1) P-poor N† Mean ± SE Lithocarpus rigidus (Fagaceae) 3(2) 0.32 ± 0.04 Syzygium subdecussata (Myrtaceae) 3(2) 0.30 ± 0.02 Tristaniopsis kinabaluensis (Myrtaceae) 3(1) 0.30 ± 0.01 Schima brevifolia (Theaceae) 3(1) 0.23 ± 0.01 P-intermediate Lithocarpus clementianus (Fagaceae) 3(2) 0.41 ± 0.03 Syzygium chrysanthum (Myrtaceae) 3(2) 0.64 ± 0.02 Tristaniopsis clementis (Myrtaceae) 3(1) 0.49 ± 0.03 Schima wallichii (Theaceae) 3(1) 0.36 ± 0.06 Payena microphylla (Sapotaceae) 3(1) 0.63 ± 0.01 P-rich Lithocarpus lampadalius (Fagaceae) 3(2) 0.66 ± 0.03 Syzygium pachysepalum (Myrtaceae) 3(2) 0.51 ± 0.01 Schima wallichii (Theaceae) 3(1) 0.42 ± 0.06 Madhuca endertii (Sapotaceae) 3(1) 0.68 ± 0.06
P-poor 4 0.29 ± 0.02 P-intermediate 5 0.51 ± 0.07 P-rich 4 0.57 ± 0.07 ANOVA 13 P < 0.01
40
Figure 2-1. Anatomical structures (a) and P-distributions (b) on a leaf cross-section for Schima brevifolia from the P-poor site. The colour scale is in X-ray count per pixel. UE, Upper epidermal tissues; LE, Lower epidermal tissues; PM; Palisade mesophyll; SM; Spongy mesophyll; VB, Vascular bundles. Bars, 100 μm
41
Figure 2-2. Relationships of relative P concentration of palisade mesophyll (Y axis) with that of the other tissues (X axis) for 19 leaf cross-sections of 13 species from three forests on Mount Kinabalu, Borneo. The X axis represents relative P concentration of upper epidermal tissues, spongy mesophyll, lower epidermal tissues, and vascular bundles on panel a, b, c, and d, respectivel y. The relative P concentration of palisade mesophyll was estimated as mean X-ray emission per pixel within the regions of palisade mesophyll on a single cross-section and compared with that of the other tissues on the same cross-section. Black dotted lines indicate a 1:1 line. Crosses, circles, and triangles represent the P-poor, P-intermediate and P-rich sites, respectively. Paired t-tests were performed between Y values and the paired X values in each panel.
42
Figure 2-S1. Thickness of upper cuticle layer on cross-sections of leaf laminas for 13 trees species from three montane tropical rain forests on Mount Kinabalu, Borneo. Each point represents mean value per species. Black circle, red triangle, green squared, blue diamond and light blue triangle symbols indicate Lithocarpus, Tristaniopsis, Syzygium, Sapotaceae and Schima, respectively. P-value is shown for testing a difference among sites (paired-sample ANOVA).
43
Chapter 3. Phosphorus and nitrogen resorption from different chemical fractions in senescing leaves of tropical tree species on Mount Kinabalu, Borneo
Abstract
Nutrient resorption, a process by which plants degrade organic compounds and resorb their nutrients from senescing tissues, is a crucial plant function to increase growth and fitness in nutrient-poor environments. Tropical trees on phosphorus (P)-poor soils are particularly known to have high P resorption efficiency (PRE, the percentage of P resorbed from senescing leaves before abscission per total P in green leaves).
However, the biochemical mechanisms underlying this greater PRE remain unclear.
In this study, I determined the P concentration in easily-soluble, nucleic acid, lipid and residual fractions for green and senescent leaves of 22 tree species from three sites, which differed in P availability, on the lower flanks of Mt. Kinabalu, Borneo.
PRE varied from 24 to 93% and was higher in species from the P-poor site. P resorption rate was greatest from the lipid fraction, the nucleic acid fraction, and lowest in the easily-soluble fraction and the residual fraction when all the species were pooled. For species with higher PRE, P resorption rate of the residual fraction was relatively high and was comparable in magnitude to that of other labile fractions.
This suggests that tree species inhabiting P-poor environments increased PRE by improving the degradation of recalcitrant compounds. This study suggests that plants selectively degrade organic compounds depending on environmental conditions, which is a key mechanism underlying the variation of PRE.
Key words: foliar phosphorus fractionation, nutrient resorption, nutrient-use efficiency, phosphorus deficiency, tropical forest
44
3.1. Introduction
Phosphorus (P) is a major macro-nutrient that limits plant activities such as photosynthesis (Thomas et al. 2006; Denton et al. 2007; Hidaka & Kitayama 2009), productivity (Vitousek 1984; Kitayama & Aiba 2002; Wardle et al. 2004; Elser et al.
2007; Cleveland et al. 2011) and reproduction (Lambers et al. 2010; Fujita et al. 2014;
Kitayama et al. 2015). Plants have developed mechanisms to use P efficiently (e.g.
Lambers et al. 2008b, 2015) and elucidating these mechanisms has been a central issue in ecosystem ecology (Vitousek 1984; Laliberté et al. 2015; Lambers et al.
2015).
Tropical soils are often highly weathered, and bioavailable P is impoverished in such soils (Walker & Syers 1976; Vitousek 1984; Vitousek & Sanford 1986; Crews et al. 1995; Yang et al. 2014). On P-poor soils, tropical trees demonstrate high P-use efficiency thereby increasing carbon (C) acquisition for a given amount of foliar P, which helps maintain high productivity atop P-poor soils (Vitousek 1982, 1984;
Silver 1994; Kitayama & Aiba 2002). One mechanism to increase nutrient-use efficiency is nutrient resorption from senescing leaves (Aerts 1990; Aerts & Chapin
1999; Franklin & Ågren 2002). Nutrient resorption is a process by which plants degrade organic compounds and resorb their nutrient elements from senescing tissues
(Stoddart & Thomas 1982; Shane et al. 2014).
Nutrient-resorption efficiency is defined as the percentage of a nutrient element resorbed from senescing leaves before abscission per the element in green leaves (Killingbeck 1996, 2004). Nutrient-resorption efficiency is often higher when soil nutrients are limited (Hidaka & Kitayama 2011; Reed et al. 2012; Yuan & Chen
2015). The global average of P resorption efficiency (PRE) is around 50–60% in evergreen angiosperms (Yuan & Chen 2009a; Vergutz et al. 2012), while PRE can
45 exceed 80% in plants under P deficiency (Denton et al. 2007; Hidaka & Kitayama
2011; Lambers et al. 2015). This suggests that the degradation of P compounds is an energetically expensive process and plants inhabiting P deficient environments have a high PRE probably by expending more energy to degrade P compounds in senescing tissues. However, little is known about the biochemical mechanisms underlying this greater PRE.
Foliar P is contained in multiple biochemical compounds, including inorganic phosphates, sugar phosphates, nucleic acids, and cell membrane lipids
(Bieleski 1968a, b; Chapin & Bieleski 1982; Chapin & Kedrowski 1983; Hidaka &
Kitayama 2011, 2013). These compounds differ in their degradability and therefore the energy expenditure required to resorb P from these compounds. For example, soluble forms of P such as inorganic phosphates can be easily resorbed, while lipid P such as P bound to cell membranes requires a greater energy for degradation (Ostertag
2010; Hidaka & Kitayama 2011). Consequently, plants may preferentially resorb P from more easily degraded compounds to minimize the cost of P resorption. Mao et al. (2015) found that PRE increased with an increasing ratio of inorganic P to organic
P in mature plant organs. This suggests that plants preferentially resorb P from more easily degraded fractions. On the other hand, PRE sometimes exceeds the proportion of easily-soluble P fraction in total P especially in plants growing in soils with low P availability (Hidaka & Kitayama 2011), suggesting that plants can degrade more recalcitrant compounds and resorb P from them when P availability is limited.
However, it remains unclear which P compounds are actually degraded and resorbed from senescing tissues across plant species with different PRE.
P compounds in foliar tissues can be divided into several fractions by using different extractants. Chapin & Kedrowski (1983) and Hidaka & Kitayama (2011,
46
2013) fractionated P compounds in the leaves of wild plants to the following four fractions: an easily-soluble fraction (including inorganic P, ATP and sugar phosphates), a nucleic acid fraction (including DNA and RNA), a lipid fraction
(including cell membranes), and a residual fraction using a series of extracting solutions. The residual fraction includes chemically recalcitrant compounds that cannot be extracted with the extracting solutions. Thus, P resorption from the residual fraction may be lower than those from the other fractions. Among the other fractions,
P resorption from the lipid fraction may be lower than those from the easily-soluble and nucleic acid fractions because phospholipids form cell membranes which would be less degradable. Therefore, I hypothesize that plants most preferentially resorb P from the easily-soluble and nucleic acid fractions and less preferentially the lipid and residual fractions (Hypothesis 1). In addition, it is expected that plant species under greater P limitation will have higher PRE by degrading more recalcitrant compounds i.e. the lipid and residual fractions (Hypothesis 2).
To investigate the above two hypotheses, I analyzed green and senescent leaves for 22 major tree species at three different sites that differ in soil P fertility on
Mount Kinabalu, Borneo. I determined the above-mentioned four P fractions in green and corresponding senescent leaves, estimated P resorption rate of each fraction, and examined the relationships between P resorption rates per fraction and PRE (per whole leaf). This fractionation method was originally developed for foliar P fractions, but it can be applied for nitrogen (N) fractions. By this method, I can quantify N fractions in low molecular weight compounds (e.g. NH3 and amino acids), nucleic acids (DNA and RNA), lipids and residuals including proteins and other recalcitrant compounds. Since the information regarding foliar N fractions is scarce (Onoda et al.
2017), I also report these N fractions in parallel with P fractions.
47
3.2. Materials and Methods
Study sites
Mount Kinabalu, Borneo (6°05′ N, 116°33′ E, 4096 m a.s.l.), is one of the most species-rich mountains in the world (Merckx et al. 2015), where tree species composition dramatically shifts across a soil P gradient and thereby community-level
P-use efficiency (Kitayama & Aiba 2002). I selected three tropical rain forest sites that differ in soil P status due to different geological substrates consisting of ultrabasic rocks (P-poor site), Tertiary sedimentary rocks (P-intermediate site) and
Quaternary colluvial sedimentary rock deposits (P-rich site). These sites correspond to the lower-slope sites on ultrabasic rocks, Tertiary sedimentary rocks and
Quaternary sedimentary rocks, described in Takyu et al. (2002b). Inclinations were
24, 17, and 15° at the P-poor, P-intermediate, and P-rich sites, respectively (Takyu et al. 2002b). The mean content of soluble soil P (extracted with 0.03N NH4F/0.1N HCl solution) was 0.02, 0.12, and 0.19 g m-2 in topsoils, and the mean content of soil inorganic N (NO3 + NH4-N) (extracted with 1.5 N KCl solution) was 1.29, 1.56, and
1.77 g m-2 at the P-poor, P-intermediate, and P-rich sites, respectively (Takyu et al.
2002b). These three sites were located within 10 km of each other at around 1700 m a.s.l. on the southern slope of Mount Kinabalu, limiting variation in climatic variables amongst sites. Mean annual temperature and precipitation, as measured at the intermediate-P site is ca. 18°C and precipitation is ca. 2800 mm yr-1, respectively
(Kitayama 1992). The species composition was markedly differentiated along the soil
P availability with almost no overlap in dominant tree species (Table S1; Kitayama
& Aiba 2002).
48
Leaf sampling
Fully expanded top canopy sun leaves were sampled from seven or eight dominant broadleaved evergreen tree species in each forest using a slingshot. These species represented 50.3, 31.9, and 43.3% of the basal area at the P-poor, P-intermediate, and
P-rich sites, respectively (see Table S1). For each species, three or four canopy individuals were sampled.
Fresh senescent leaves of the same species were also sampled in each forest by shaking trees. When trees were too large to shake, we collected fresh senescent leaves using litter traps at two-day intervals. To ensure that selected leaves were fresh,
I visually examined whether the abscission layers of petioles were still fresh to distinguish fresh ones from old senescent leaves. Sampling methods did not affect foliar element concentrations; mean (±SE) P concentrations of senescent leaves were
0.08 (0.02) (n=7) and 0.10 (0.02) (n=7; Hidaka & Kitayama 2011) mg g-1 obtained from tree shaking and litter traps, respectively at the P-poor site.
Sampled green leaves and senescent leaves were immediately put into a cool box in the field to suppress enzyme activities in leaf tissues and brought back to the laboratory located on the middle slope of Mount Kinabalu. The samples were freeze- dried and powdered by a vibration mill (TI-200, Advantec, Tokyo, Japan) prior to chemical analysis.
Foliar P and N fractions
P- and N-containing compounds both in green and senescent leaves were divided into the following four chemical fractions by the sequential extraction method (Chapin &
Kedrowski 1983; Hidaka & Kitayama 2011, 2013); namely an easily-soluble fraction
(including inorganic P, ATP and sugar phosphates/ inorganic N and amino acids), a
49 nucleic acid fraction (including DNA and RNA), a lipid fraction (including cell membranes, chlorophyll and some lipoproteins), and a residual fraction (including proteins and unidentified residue that cannot be extracted with the extracting solutions).
A known amount of each powdered sample (ca. 300–500 mg) was extracted twice by chloroform-methanol-formic acid (12:6:1 v/v/v, 8+7 mL in total) for two minutes each, and subsequently extracted twice by chloroform-methanol-water
(1:2:0.8 v/v/v, 10+9 mL in total) for two minutes each. For each extraction process, the sample was homogenized using a Polytron homogenizer (Multipro Model 395,
Dremel Co., Racine, WI, USA; Generator shaft 10u, SMT Co., Tokyo, Japan). After this process, the sample was added to 9.5 mL deionized water (total volume 43.5 mL) to separate into a lipid-rich organic bottom layer and an aqueous upper layer. This lipid-rich organic layer was transferred to a new tube (called lipid extract) after centrifugation (1000 g for 10 min). To complete the lipid extraction, the sample was further extracted with 5 mL chloroform several times (by shaking on a shaker for 30 s; MS1 Minishaker, IKA). These chloroform extracts were combined with the initial lipid extract, and used for lipid-P and N determination (hereafter defined as a lipid fraction). 5 mL of 85% methanol was added to the remaining sample, following lipid extraction, to separate precipitates from the aqueous phase, and the aqueous phase was transferred to a new tube. Both the aqueous phase and the precipitates were separately placed under vacuum for 48 hours to remove the dissolved chloroform and methanol. After this process, the aqueous phase and the precipitates were recombined and trichloroacetic acid (TCA) was added to make to 5% TCA solution (total volume
30 mL) at 4°C. This cold-TCA extraction was made for 1 h with shaking at 10-min intervals and the supernatants were transferred to a new tube. This procedure was
50 repeated with 10 mL cold-TCA (5% w⁄v) and the supernatants were combined. The supernatant (i.e. cold-TCA solution) contained easily-soluble small molecules, and defined as "easily-soluble fraction". The precipitates after the cold-TCA extraction were extracted twice with hot-TCA (2.5% w⁄v) at 95°C (20+15 mL) for one hour each
(Hot-TCA extraction). The hot-TCA solution is supposed to represent a “nucleic acid fraction” (Chapin & Kedrowski 1983). The residue remaining after hot-TCA extraction was defined as "residual fraction" in this study representing cell wall materials and precipitated proteins. Temperature during all processes was kept at
20°C unless otherwise mentioned. All liquid-solid separations were accomplished by decantation following centrifugation at 1000 g for 10 min.
N fractions were determined based on the same chemical fractions as P
(Chapin & Kedrowski 1983). In the case of N fractionation, a greater portion of foliar
N occurs in proteins, which were categorized as the residual fraction in this procedure because proteins are insoluble in TCA. Because proteins are biologically active (i.e. degradable and its degradation products are highly mobile) (Chapin & Kedrowski
1983; Yasumura et al. 2006), the fractionation method used for foliar P may not be ideal to distinguish N compounds to elucidate the chemical recalcitrancy. However, information for the amount of lower molecular-weight N compounds such as inorganic N, nucleic acids and lipids in leaves should be valuable and therefore reported in a parallel manner to the P fractions. Recovery rates (mean ±SD) were 93
±7% and 91 ±7% for P and N, respectively, throughout the sequential extraction processes.
P and N concentrations in the four fractions, and total P, N and Ca (see below for the reason of Ca measurement) concentrations in green and senescent leaves were determined by the following procedure. Solid samples (i.e. powdered leaves, dried
51 lipid fraction and residual fraction) were digested with 5 mL of concentrated H 2SO4 and 2 mL of 30% H2O2 at 380°C for 5 hour. In the case of liquid samples (i.e. easily- soluble fraction and nucleic acid fraction), each sample was digested with 5 mL
H2SO4 for 5 hour. During this digestion, H2O in the samples was evaporated by gradual increase in temperature up to 200°C. Then 2 mL 30% H2O2 was added to this sample to complete the digestion at 380°C. P and Ca concentrations in the digests were determined using an inductively coupled plasma atomic emission spectrometer
(ICPS-7510, Shimadzu Co., Kyoto, Japan). N concentrations in the digests were determined colourimetrically as NH4-N by indophenol blue absorptiometry according to Sims et al. (1995). P, N and Ca concentrations in the samples were calculated on a dry mass basis.
Calculation of P and N resorption efficiency
I calculated P resorption efficiency (PRE) and N resorption efficiency (NRE) as the percentage of reduction in foliar P and N concentration from green to senescent leaves (Killingbeck 1996) in each species. In this procedure, I corrected for the underestimate of PRE and NRE due to mass loss during senescence by taking the difference of Ca concentration between the green and the senescent leaves into account (see equation 3.1) because foliar Ca is little resorbed from senescing leaves in evergreen angiosperms (Vergutz et al. 2012), serving as a standard to correct for mass loss associated with senescence (Vitousek & Sanford 1986).
Nu(G) Nu(S) Nu(G) NuRE = ( − )/ ∗ 100 (%) (equation 3.1) Ca(G) Ca(S) Ca(G)
where Nu stands for nutrients either P or N (i.e. NuRE denotes either PRE or NRE),
52 and G and S stand for green and senesced leaves respectively. The mean ratio of Ca concentration in green leaves to that in senescent leaves was 0.80 (SD=0.26), meaning that resorption rates may be underestimated by ca. 20% if mass transfer was not properly considered. P and N resorption rates of each fraction were calculated in the same manner.
The magnitude of elements resorbed from senescing leaves were calculated as the difference in element concentrations between green leaves and senescent leaves.
Statistical analysis
Throughout the statistical analyses, the 22 species were used as units of replication.
Among-site differences were evaluated based on the means of the 7–8 dominant species per site by ANOVA for the following response variables: i) total foliar P and
N concentrations, ii) the concentrations and relative proportions of each P and N fraction for green and/or senescent leaves, and iii) the magnitudes of P and N resorbed from senescing leaves. I also evaluated differences among sites by calculating community weighted mean (CWM). The CWM was defined as the average of species- mean values weighted by relative basal area of each species sampled in a site. The
CWMs showed quite similar trends with arithmetic site means (i.e. the arithmetic means of the 7–8 dominant species for each site) across all response variables (see
Table 3-1, 3-S2 and 3-S3, Figs 3-S1, 3-S2b, 3-S3 and 3-S4c and d). Therefore, I focus on arithmetic site means only in the following results and discussion.
Paired-sample ANOVA was used to evaluate the differences between green leaves and senescent leaves, for total foliar P and N concentrations and the concentrations and relative proportions of each P and N fraction. Regression analyses
53 were performed for the pooled 22 species data to examine the relationships between
P or N resorption rates of each fraction and PRE or NRE. Standardized major axis slope (Warton et al. 2012) was used to fit bivariate relationships.
I evaluated the contribution of phylogeny on the interspecific variations in
PRE and NRE using a variance partitioning technique (Borcard et al. 1992). This analysis was performed for the following response variables; i) total foliar P and N concentrations, ii) the concentrations of each P and N fraction for green and senescent leaves, and iii) PRE and NRE, and P and N resorption rates of each fraction. Ordinary least squares models were developed using the procedure of previous studies (Asner
& Martin 2011; Tsujii et al. 2016) with a slight modification (see supplementary R code), to partition the variance in a response variable into a phylogenetic and a site factor. The variance was divided into the following four categories; the unique contribution of genus, the unique contribution of site, the shared contribution of genus and site, and residuals. The unique contribution of genus represents the effect of genus independent of site, and vice versa. The shared contribution of genus and site represents an inter-correlation between genus and site, thus reflecting the effect of the turnover in genus composition among sites.
All statistical analyses were done in R version 3.0.1 (R Development Core
Team 2013). NRE of Lithocarpus confertus and N fractions of Magnolia candolii and
Syzygium pachysepalum in senescent leaves were not reported due to insufficient replication. Across all statistical analyses, the response variables were not transformed because the data had typically Gaussian distribution (Shapiro-test, P >
0.05).
54
3.3. Results
Foliar P and N, and their resorption efficiency
P concentration ranged from 0.25 to 1.03 mg g-1 in green leaves and from 0.04 to
0.46 mg g-1 in senescent leaves across all 22 species. Similarly, N concentration ranged from 6.8 to 21.7 mg g-1 in green leaves and from 3.7 to 14.6 mg g-1 in senescent leaves. The site mean P concentration (i.e. the mean of 7–8 dominant species for each site) was significantly lower in the P-poor than in the P-rich site both in green leaves and senescent leaves (Table 1) in line with a previous study (Hidaka
& Kitayama 2011). In particular, the site mean senescent leaf P (mean ±SE) was quite low in the P-poor site (0.08 ±0.02 mg g-1) compared with the average of tropical forest plants (0.4 ±0.0 mg g-1; Yuan & Chen 2009b). On the other hand, the site mean green-leaf N was not significantly different among the sites, whereas senescent-leaf
N was significantly lower in the P-poor and P-intermediate sites than the P-rich site
(Table S2).
P resorption efficiency (PRE) varied from 24 to 93%, while N resorption efficiency (NRE) varied from 17 to 89% across all species (Fig. 3-1). ANOVA revealed that the site mean PRE was significantly higher in the P-poor site than in the P-rich site (Fig. 3-1). In contrast, the site mean NRE was not significantly different among the sites (Fig. 3-S2a).
Foliar P and N fractions
The site mean P concentration in each fraction was significantly lower in the P-poor site both in green leaves and senescent leaves except for the residual P in green leaves
(Table 1; Fig. 3-2a). The site mean N concentration in each fraction in green leaves was not significantly different among the sites, except for the nucleic acid N fraction
55 which was significantly lower in infertile sites (Table 3-S2; Fig. 3-S4a). In senescent leaves, the site mean N concentration of the residual fraction was significantly lower in the P-poor and P-intermediate sites than in the P-rich site, and that of the nucleic acid fraction was significantly lower in the P-intermediate site (Table 3-S2; Fig. 3-
S4a).
The allocation patterns among the four fractions were different between P and N (Figs. 3-2b and 3-S4b). Foliar P was allocated more or less equally among all fractions: the relative proportion of each fraction was 20.0–43.0, 28.3–41.5, 19.7–
30.5 and 7.0–18.3% for the easily-soluble, nucleic acid, lipid and residual fractions, respectively in green leaves (Table 3-S3; Fig. 3-2b). This result is in accord with the previous observation by Hidaka & Kitayama (2011). The site mean of the relative proportions was not significantly different among sites across all P fractions (Fig. 3-
2b). On the other hand, green-leaf N was allocated mainly to the residual fraction, which includes proteins, in accord with the tendency in taiga tree species in Chapin
& Kedrowski (1983); i.e. the relative proportion of each fraction per species in green- leaf N is 5.5–16.8%, 7.1–11.3%, 4.1–9.3% and 67.4–81.3% for the easily-soluble, nucleic acid, lipid and residual fractions, respectively (Table 3-S3; Fig. 3-S4b). The site mean of the relative proportions was not significantly different among sites across all N fractions, except for the residual N (Fig. 3-S4b).
The senescent leaves were different from green leaves in the relative proportions of the P and N fractions (Table 3-S3; Figs. 3-2b and 3-S4b). Senescent leaves had significantly lower relative proportion of the lipid P but higher proportion of the residual P than green leaves across all sites. The relative proportion of the easily-soluble P was slightly but significantly higher in senescent leaves than green leaves except for the most P-rich site, and the relative proportion of the nucleic acid
56
P was not different between green and senescent leaves. For N, while the relative proportion of the easily-soluble N was significantly higher in senescent leaves than green leaves (Table 3-S2; Fig. 3-S4b), the relative proportion of other compounds differed only slightly between senescent and green leaves.
Resorption rates of each fraction
When all species were pooled, P or N resorption rates of the four fractions were all significantly positively correlated with PRE or NRE, respectively (Table 3-S2; Figs
3-3a–d and 3-S5a–d). The relationship between P resorption rate of the residual fraction and PRE was lower than the 1:1 line but the slope was significantly greater than 1 and closer to the 1:1 line when PRE was high (Fig. 3-3d, P < 0.05). This suggests that the P resorption rate of the residual fraction was typically lower than the other fractions, but comparable to the other fractions when PRE was high. Similar pattern was found for the easily-soluble P fraction (Fig. 3-3a). The regression line was above the 1:1 line and its slope was significantly less than 1 (Fig. 3-3c, P < 0.05) for P resorption from the lipid fraction. This suggests that that tree species with low
PRE may preferentially degrade lipid P. For P resorption rate of the nucleic acid fraction, the relationship was not significantly different from the 1:1 line (Fig. 3-3b).
In contrast to P resorption, the relationship between N resorption rate of the residual fraction and NRE was not significantly different from the 1:1 line (Fig. 3-
S5d). Regression lines for the N resorption rates of the nucleic acid fraction and lipid fraction were higher than that of the residual fraction and the latter was significantly higher than the 1:1 line (Figs. 3-S5b and c). The regression line for the easily-soluble fraction was significantly lower than the 1:1 line (Fig. 3-S5a).
The mean P resorption rate of fraction was highest in the lipid fraction,
57 second highest in the nucleic acid fraction and lowest in the easily-soluble fraction and the residual fraction (Fig. 3-3e, paired sample t-test with Bonferroni correction,
P < 0.05). In contrast, the mean N resorption rates were highest in the lipid fraction and the nucleic acid fraction, secondary in the residual fraction, and lowest in the easily-soluble fraction (Fig. 3-S5e, paired sample t-test with Bonferroni correction,
P < 0.05). N resorption rate of the easily-soluble fraction was slightly negative in one species despite that those of the other fractions were all positive, indicating that the concentration of the easily-soluble N increased in the senescent leaves.
Mean magnitude of P resorption per fraction was not significantly different among the sites for all fractions (Fig 3-2a). Also, the magnitude of N resorption per fraction was not significantly different among the sites for all fractions (Fig 3-S4a).
Phylogenetic patterns
The interspecific variance in PRE was correlated with both phylogeny (i.e. genus) and soil P availability (i.e. site) (Fig. 3-4). The variances in PRE and P resorption rates of each fraction were in part explained by the unique contributions of genus
(25–43%) and site (20–37%), and the shared contribution of genus and site (6–24%).
Similar trends were found in green and senescent leaf P, but there were some differences between them; the variances in green leaf P and its fractions were explained primarily by genus (30–51%) rather than site (8–26%), while the variances in senescent leaf P and its fractions were explained primarily by site (27–37%) rather than genus (15–30%). The variances of the N data were explained mostly by genus
(37–74%, Fig. 3-S6). In total, 59–93% of the variances in these nutrient characteristics were explained by the combinations of genus and site.
58
3.4. Discussion
Phosphorus resorption
In the three study sites, the tree species composition was clearly differentiated across a soil fertility gradient within relatively short distance, and the site mean PRE was higher in the P-poor site (82%) than the P-intermediate and P-rich sites (62% and
78%, respectively; Fig. 3-1). This suggests that P-poor environments favor tree species with higher PRE. I analyzed the mechanisms of the greater PRE and demonstrated that greater PRE in tree species was not necessarily dependent on the quotient of low molecular weight P to other organic P (but see Mao et al. 2015). This is because the relative proportions of the foliar P fractions were independent of soil
P-availability (Fig. 3-2b, Hidaka & Kitayama 2011). Instead, the magnitude of PRE seemed to depend on the capacity of trees to degrade P compounds.
Species with lower PRE degraded the lipid P most preferentially, followed by the nucleic acid P and the residual P in senescing tissues (Fig. 3-3e). This was contrary to my hypothesis. I expected that lipids would be less degraded compared to nucleic acids, because lipids primarily represent cell membranes (Somerville et al.
2000). However, the greater P resorption rate of the lipid fraction implies that cell membranes are relatively easily degradable.
Despite that the easily-soluble P was expected to have a high resorption rate due to its high mobility, its resorption rate was smaller than those of the nucleic acid fraction and the lipid fraction (Fig. 3-3e). However, this does not mean that the easily- soluble fraction was less resorbed from senescing tissues. The amount of easily- soluble P can increase as a transient form during the degradation of organic P in senescent tissues (Stoddart & Thomas 1982; Chapin & Kedrowski 1983). Therefore, such transient degradation products may result in the lower net resorption rate of the
59 easily-soluble fraction. In addition, a luxury consumption of P (e.g. Cordell et al.
2001) may be involved in the relatively lower resorption rate of the easily-soluble P in the P-rich site. Because trees on P-rich soils may store excessive P as easily-soluble
P in leaves (e.g. Ostertag 2010), the excessive P may remain in senescent leaves.
The P resorption rate of the residual fraction was significantly smaller than those of the nucleic acid fraction and the lipid fraction (Fig. 3-3e; Chapin et al. 1986) presumably due to chemically recalcitrant compounds in this fraction. Nevertheless, species with greater PRE demonstrated a high P resorption rate of the residual fraction, which was comparable in magnitude to that of the other labile fractions (Fig.
3-3d). This supports my hypothesis that species with greater PRE can degrade more recalcitrant compounds in senescing tissues. Probably, tree species adapted to P deficiency expend greater energy to degrade recalcitrant compounds to increase PRE.
Conversely, tree species on P-rich soils may not need to degrade recalcitrant compounds to meet their P requirements.
An intriguing question was how phylogeny was related to the PRE. I estimated that 20–37% of the variances in PRE and P resorption rates of each fraction were explained by the unique contribution of site while 25–43% by the unique contributions of genus. The former suggested that PRE converged into a high value under a severe P limitation across genera, while the latter suggested a fixed effect of genus on the variation in PRE. These two effects were inter-correlated (i.e. the shared contribution of genus and site), also suggesting the importance of the changes in species composition across the soil P availability (see Table 3-S1).
Nitrogen resorption
Most foliar N was associated with the residual fraction (67.4–81.3%) by the present
60 method (Fig. 3-S4b) because cytosolic proteins were precipitated by the organic solvents and TCA solution. These proteins are known to be easily degradable
(Pugnaire & Chapin 1993; Yasumura et al. 2006), and thus the residual N does not necessarily mean recalcitrant N. However, it should be noted that the residual N also contained real recalcitrant N such as structural proteins that were tightly cross-linked in cell wall matrix (Lamport 1965; Carpita & MaCann 2000). Cell wall N may account for 5–30% of leaf N (Onoda et al. 2004, 2017) and is considered to remain in senescent leaves. Therefore, cell wall N may determine the upper threshold of NRE
(Yasumura et al. 2006).
I quantified the fractions of N in low molecular weight compounds (e.g. NH3 and amino acids), nucleic acids (DNA and RNA) and lipids. N fractions within leaves have been studied mostly for photosynthetic proteins such as Rubisco (e.g. Evans
1989; Poorter & Evans 1998), and knowledge for other non-protein N has been very limited (Onoda et al. 2017). Therefore this study provides valuable information on N resorption from those non-protein N factions. Among the four N fractions, the nucleic acid and the lipid fraction had higher resorption rates, suggesting that these compounds were easily degradable and resorbed from senescing tissues, which is consistent with the case of P (Fig. 3-S5e). Furthermore, species with high NRE degraded the lipid fraction more efficiently as indicated by the regression slope steeper than 1 (Fig. 3-S5c). The easily-soluble fraction showed the lowest N resorption rate among all fractions (Fig. 3-S5a). As is in P, the easily-soluble fraction may contain transient mobile degradation products of N compounds masking the real
N resorption rate of this fraction. The reduction of the apparent resorption rate from this fraction was somewhat more pronounced in N compared to P.
61
3.5. Concluding remarks
My study showed that plants selectively degraded organic compounds depending on soil nutrient availability, leading to the variation in nutrient-resorption efficiency.
The higher PRE in plants grown on P-poor soils was possible because they degraded more chemically recalcitrant compounds during leaf senescence rather than because they had greater fraction of the P that could be easily degraded. My study also implied significant ecosystem consequences of different rates of resorption among P (N) fractions. The different rates of resorption among fractions change leaf chemical compositions during leaf senescence, which may influence the decomposition of leaf litters and the activity of other organisms that rely on leaf tissues. I conclude that degradation capacity as well as chemical composition are the major factors to govern nutrient-resorption efficiency, influencing plant nutrient-use strategy and biogeochemical cycling in forest ecosystems.
62
Table 3-1. Site mean (±SD) and community-weighted mean (CWM) total P concentrations and P concentrations of chemical fractions in green and senescent leaves, in three tropical rain forests on Mount Kinabalu, Borneo. Pairwise significant diffe rences at P <0.05 among the sites in the site means are shown with different letters (Tukey HSD).
P-poor, n=7 P-intermediate, n=7 P-rich, n=8 Mean ±SD CWM Mean ±SD CWM Mean ±SD CWM ANOVA Green leaves Total P (mg g-1) 0.354 ±0.113a 0.339 0.496 ±0.102ab 0.499 0.700 ±0.214b 0.677 P < 0.01 Easily-soluble P (mg g-1) 0.086 ±0.019a 0.098 0.113 ±0.024ab 0.116 0.183 ±0.099b 0.161 P < 0.05 Nucleic acid P (mg g-1) 0.124 ±0.040a 0.146 0.163 ±0.037ab 0.167 0.213 ±0.059b 0.201 P <0.01 Lipid P (mg g-1) 0.080 ±0.027a 0.089 0.115 ±0.018ab 0.113 0.148 ±0.045b 0.126 P < 0.01 Residual P (mg g-1) 0.048 ±0.012 0.055 0.069 ±0.026 0.071 0.078 ±0.033 0.087 n.s. Senescent leaves Total P (mg g-1) 0.076 ±0.040a 0.07 0.153 ±0.025a 0.152 0.302 ±0.106b 0.297 P < 0.01 Easily-soluble P (mg g-1) 0.022 ±0.010a 0.02 0.042 ±0.011a 0.042 0.088 ±0.039b 0.085 P < 0.01 Nucleic acid P (mg g-1) 0.026 ±0.019a 0.02 0.045 ±0.010a 0.045 0.094 ±0.038b 0.092 P < 0.01 Lipid P (mg g-1) 0.011 ±0.006a 0.009 0.023 ±0.005a 0.022 0.052 ±0.021b 0.05 P < 0.01 Residual P (mg g-1) 0.014 ±0.005a 0.01 0.030 ±0.013a 0.029 0.053 ±0.022b 0.054 P < 0.01
63
Figure 3-1. Boxplots showing P resorption efficiency (PRE) for 22 trees species from three tropical rain forests on Mount Kinabalu, Borneo. Pairwise significant differences among sites in site mean PRE are shown as different letters (Tukey HSD, P < 0.05). The central box in each box plot shows the inter quartile range and median; the whiskers extend 1.5 times the inter quartile range or to the most extreme value. The number of species per site is indicated at the bottom of the graph.
64
Figure 3-2. Site mean P concentrations of chemical fractions in green and senescent leaves and site mean magnitude of the P resorbed from senescing leaves (a) and site mean relative proportions of the P contained in the chemical fractions (b) in three tropical rain forests on Mount Kinabalu, Borneo (mean ±SD). The magnitude of elements resorbed from senescing leaves was calculated as the difference in P concentrations between green leaves and senescent leaves.
65
Figure 3-3. Relationships between P resorption rates of chemical fractions and PRE (P resorption efficiency) (a–d), and boxplots showing P resorption rates of the chemical fractions (e), for 22 tree species on Mount Kinabalu, Borneo. The Y axis represents P resorption rate of the easily-soluble, nucleic acid, lipid, and residual fraction in diagram a, b, c, and d, respectively. In diagrams a to d; grey colored broken lines indicate a 1 : 1 line, black solid lines represent type II Regression lines (Warton et al. 2012) for each fraction, and circle, diamond and triangle symbols represent the mean values per species in the P-poor, P-intermediate and P-rich sites, respectively. In diagram e, pairwise significant differences at P < 0.05 among fractions in P resorption rates are shown with different letters (paired sample t-test with Bonferroni correction), the central box in each box plot shows the inter quartile range and median, and the whiskers extend 1.5 times the inter quartile range or to the most extreme value.
66
Figure 3-4. Proportion of variance explained (R2) by genus, site, and residue. Sums of squares (R2) were calculated by comparing R2 across different models. We calculated the unique contributions of genus and site and the shared contributions, because genus and site were inter-correlated.
67
Table 3-S1. Sampled species; RBA shows the relative basal area (%) of each species in each forest.
P-poor site P-intermediate site P-rich site
Family Species RBA Family Species RBA Family Species RBA
Myrtaceae Tristaniopsis kinabaluensis 31.4 Myrtaceae Tristaniopsis clementis 6.9 Fagaceae Lithocarpus confertus 7.8
Polygalaceae Xanthophylum fenue 6.9 Myrtaceae Syzygium pachysepalum 5 Theaceae Ternstroemia magnifica 6.7
Cunoniaceae Weinmannia cf. blumei 3.9 Fagaceae Lithocarpus clementianus 4.6 Myrtaceae Syzygium cf castaneum 6.2
Fagaceae Lithocarpus rigidus 2.3 Sapotaceae Payena microphylla 4.6 Sapotaceae Maduca endertii 6.1
Myrtaceae Syzygium castaneum 2.1 Myrtaceae Tristaniopsis sp2 4.3 Fagaceae Lithocarpus lampadalius 5.3
Myrtaceae Syzygium subdecussata 2.1 Myrtaceae Syzygium napiforme 3.4 Myrtaceae Syzygium pachysepalum 5
Aquifoliaceae Ilex oppositifolia 1.6 Myrtaceae Syzygium chrysanthum 3.1 Magnoliaceae Magnolia carsonii 4.2
Magnoliaceae Magnolia candolii 2
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Table 3-S2. Site mean (±SD) and community-weighted mean (CWM) total N concentrations and N concentrations of chemical fraction in green and senescent leaves, in the three tropical rain forests on Mount Kinabalu, Borneo. Pairwise significant di fferences at P <0.05 among the sites in the site means are shown in different letters (Tukey HSD).
P-poor, n=7 Intermediate, n=7 P-rich, n=8 Mean ±SD CWM Mean ±SD CWM Mean ±SD CWM ANOVA Green leaves Total N (mg g-1) 10.07 ±4.84 9.65 10.3 ±0.96 10.3 13.55 ±4.66 13.36 n.s. Easily-soluble N (mg g-1) 1.08 ±0.96 1.01 0.69 ±0.12 0.67 1.25 ±0.72 1.16 n.s. Nucleic acid N (mg g-1) 0.80 ±0.28 0.82 0.81 ±0.13 0.83 1.13 ±0.31 1.1 P < 0.05 Lipid N (mg g-1) 0.56 ±0.27 0.5 0.54 ±0.12 0.53 0.84 ±0.32 0.81 P=0.05 Residual N (mg g-1) 6.72 ±3.12 6.37 7.28 ±1.03 7.45 8.99 ±2.62 8.85 n.s. Senescent leaves Total N (mg g-1) 5.45 ±2.53 5.01 5.80 ±1.72 5.97 8.82 ±3.43 9.62 P < 0.05 Easily-soluble N (mg g-1) 0.82 ±0.60 0.79 0.67 ±0.04 0.68 1.13 ±0.47 1.06 n.s. Nucleic acid N (mg g-1) 0.41 ±0.29 0.38 0.35 ±0.17 0.35 0.68 ±0.20 0.67 P < 0.05 Lipid N (mg g-1) 0.27 ±0.14 0.24 0.24 ±0.07 0.24 0.38 ±0.09 0.38 P = 0.08 Residual N (mg g-1) 3.65 ±1.45a 3.22 4.03 ±1.27a 4.19 6.94 ±2.56b 6.88 P < 0.01
69
Table 3-S3. Site mean (±SD) and community weighted mean (CWM) relative proportions of P or N fraction in green and senescent leaves, in three tropical rainforests on Mount Kinabalu, Borneo. P-values are shown for testing differences in the site mean proportions of P or N fraction between green leaves and senescent leaves (paired-sample t-test). Green leaves Senescent leaves P-poor Mean ±SD CWM Mean ±SD CWM P-values Easily-soluble P (%) 25.7 ±2.2 25.4 30.9 ±5.2 35.1 0.1 Nucleic acid P (%) 36.6 ±1.9 37.5 32.9 ±7.0 32.7 n.s. Lipid P (%) 23.5 1.8 ±22.9 14.9 2.1 ±14.6 <0.01 Residual P (%) 14.2 2.1 ±14.2 21.3 6.8 ±17.7 <0.05 Easily-soluble N (%) 10.6 ±3.0 10.4 15.2 ±4.3 16.3 <0.01 Nucleic acid N (%) 9.2 ±1.6 10.0 7.4 ±1.9 7.8 0.1 Lipid N (%) 6.1 0.7 ±5.7 5.1 0.3 ±5.0 <0.05 Residual N (%) 74.1 1.9 ±73.9 72.3 4.7 ±70.9 n.s. P-intermediate Easily-soluble P (%) 24.7 ±3.6 24.8 29.8 ±6.6 30.3 <0.05 Nucleic acid P (%) 35.3 ±2.8 35.7 32.2 ±4.0 32.4 0.1 Lipid P (%) 25.3 3.6 ±24.6 16.9 3.3 ±16.3 <0.01 Residual P (%) 14.7 3.0 ±14.8 21.1 7.1 ±21.0 <0.05 Easily-soluble N (%) 7.6 ±1.7 7.2 13.3 ±3.1 13.0 <0.01 Nucleic acid N (%) 8.7 ±1.0 8.7 6.4 ±1.4 6.3 <0.01 Lipid N (%) 5.8 1.6 ±5.6 4.8 2.0 ±4.6 n.s. Residual N (%) 77.9 3.2 ±78.4 75.5 4.2 ±76.1 0.1 P-rich Easily-soluble P (%) 28.4 ±7.2 28.2 30.2 ±3.7 30.2 n.s. Nucleic acid P (%) 34.7 ±4.0 34.9 32.6 ±4.4 32.5 n.s. Lipid P (%) 24.2 3.9 ±23.7 18.5 3.2 ±18.1 <0.01 Residual P (%) 12.7 4.3 ±13.2 18.7 4.6 ±19.2 <0.01 Easily-soluble N (%) 9.9 ±2.9 9.5 12.6 ±3.6 12.1 <0.05 Nucleic acid N (%) 9.5 ±1.1 9.4 8.0 ±3.1 8.1 n.s. Lipid N (%) 7.0 1.4 ±6.9 4.4 0.8 ±4.4 <0.05 Residual N (%) 73.7 4.2 ±74.1 75.0 5.4 ±75.4 n.s.
70
Figure 3-S1. Community-weighted mean (CWM) P resorption efficiency (PRE) in three tropical rain forests on Mount Kinabalu, Borneo. The CWM was calculated as the average of species-mean values weighted by relative basal area of each species sampled in a site.
71
Figure 3-S2. Boxplots showing N resorption efficiency (NRE) for 22 trees species from three tropical rain forests on Mount Kinabalu, Borneo (a), and community- weighted mean (CWM) NRE in the three forests (b). In diagram a, the central box in each box plot shows the inter quartile range and median; the whiskers extend 1.5 times the inter quartile range or to the most extreme value. The number of species per site is indicated at the bottom of the graph. n.s. indicates insignificant differences among sites in site mean NRE (ANOVA, P > 0.05).
72
Figure 3-S3. Community-weighted mean (CWM) P concentrations of chemical fractions in green and senescent leaves and CWM magnitude of the P resorbed from senescing leaves (a) and CWM relative proportions of the P contained in the chemical fractio ns (b) in three tropical rain forests on Mount Kinabalu, Borneo. The magnitude of elements resorbed from senescing leaves was calculated as the difference in element concentrations between green leaves and senescent leaves.
73
Figure 3-S4. Site mean N concentrations of chemical fractions in green and senescent leaves and site mean magnitude of the N resorbed from senescing leaves (a), and site mean relative proportions of the N contained in the chemical fractions (b) in th ree tropical rain forests on Mount Kinabalu, Borneo (mean ± SD). Community-weighted mean (CWM) values of the N data are shown in panel c and d.
74
Figure 3-S5. Relationships between N resorption rates of chemical fractions and NRE (N resorption efficiency) (a–d), and boxplots showing N resorption rates of the chemical fractions (e), for 22 tree species on Mount Kinabalu, Borneo. The Y axis represents N resorption rate of the easily-soluble, nucleic acid, lipid, and residual fraction in diagram a, b, c, and d, respectively. In diagrams a to d; grey colored broken lines indicate a 1 : 1 line, black solid lines represent type II Regression lines (Warton et al. 2012) for each fraction, and circle, diamond and triangle symbols represent the mean values per species in the P-poor, P-intermediate and P-rich sites, respectively. In diagram e, pairwise significant differences at P < 0.05 among fractions in P resorption rates are shown with different letters (paired sample t-test with Bonferroni correction), the central box in each box plot shows the inter quartile range and median, and the whiskers extend 1.5 times the inter quartile range or to the most extreme value.
75
Figure 3-S6. Proportion of variance explained (R2) by genus, site, and residue. Sums of squares (R2) were calculated by comparing R2 across different models. We calculated the unique contributions of genus and site and the shared contributions, because genus and site were inter-correlated.
76
Supplementary R code
The R code used in the variance portioning analysis
#I developed the following anova models; y ~ genus (model1), y ~ site (model2), and y ~ genus + site (model 3). model1=lm(y ~ Genus) model2=lm(y ~ Site) model3=lm(y ~ Genus + Site)
# The variances of these models were divided into the following four categories; the unique contribution of genus (R2_Genus), the unique contribution of site (R2_Site), the shared contribution of genus and site (R2_Genus+Site), and residuals (R2_residue). In the R code, summary(model)$r.squared represents an R2 value of the model. The detail method to partition variance is described in Borcard et al. (1992).
R2_Genus = summary(model3)$r.squared - summary(model2)$r.squared R2_Site = summary(model3)$r.squared - summary(model1)$r.squared R2_Genus+Site = summary(model1)$r.squared + summary(model2)$r.squared - summary(model3)$r.squared R2_Residue = 1 - summary(model3)$r.squared
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Chapter 4. Relationships of phosphorus concentration in reproductive organs with soil phosphorus availability for tropical rainforest tree species on Mount
Kinabalu, Borneo
Abstract
An earlier study of 10-year continuous monitoring of litterfall in eight tropical rainforests with different soil phosphorus (P) availabilities found that P concentration in reproductive-organ litter decreased with decreasing soil P availability. Yet, the underlying mechanism and ecological significance of the decrease of the P concentration in reproductive organs remain unclear. P concentration in fresh inflorescences, seeds, and pericarps was analyzed for 46 tree species (21 genera) from the same eight forests as the previous study. Mean P concentration per site in the above three reproductive organs was determined, and regressed against soil P availability for each genus to allow for the difference of fruit types among genera. The composition of fruit types was determined based on the relative abundance of each genus and fruit type by genus at a given site from literature data, to examine the linkage of the composition of fruit types with mean
P concentration per site in reproductive organs. Mean P concentration per site by genus in inflorescences was significantly positively correlated with soil P availability, while that in seeds and pericarps was not significantly correlated. This trend was found across many genera. The relative proportion of capsulate fruits increased with decreasing soil P availability, while those of the other fruit types decreased. This shift in the composition of fruit types may dilute mean P concentration per site in reproductive organs, because mean P concentration of pericarps was significantly lower in capsulate fruits than in the other fruit types
78 when all species were pooled. By contrast, mean P concentration of seeds was significantly greater in capsulate fruits than in the other fruit types. In summary,
Bornean rainforest trees maintain P in seeds on P-poor soils in exchange with the dilution of P in inflorescences. Community composition shifts to the dominance of capsulate-fruit type, which requires less P in pericarps. These may be adaptive to maintain reproductive activities under P deficiency.
Key words: general flowering/fruiting, phosphorus deficiency, masting, nutrient allocation, soil nutrient, adaptation
79
4.1. Introduction
Phosphorus (P) is an essential element for plants (Veneklaas et al. 2012; Rennenberg
& Herschbach 2013; Lambers et al. 2015), but its deficiency occurs across natural ecosystems (Elser et al. 2007; Vitousek 2010; Cleveland et al. 2011). Tropical rainforests on highly weathered soils are particularly known for P deficiency, because highly weathered soils in the tropics contain little bioavailable P (Vitousek
1984; Crews et al. 1995; Yang et al. 2014; Fujii et al. 2017). Tropical tree species on P-poor soils have developed mechanisms to use P efficiently (Vitousek 1984;
Hidaka & Kitayama 2011; Kitayama et al. 2015; Heineman et al. 2016).
Reproduction is a crucial process in a tree life history (Willson 1983;
Fenner 2012), and requires a disproportionately greater amount of P than other elements (Witkowski & Lamont 1996; Kitayama et al. 2015). Bornean rainforest trees allocate a large amount of P to reproduction; ca. 10–15% of the total P that flowed through an internal nutrient cycle as litterfall was allocated to reproduction in Bornean tropical rainforests on P-poor soils (Kitayama et al. 2015). The trees in the same forests allocated a lesser ratio of carbon (C) and nitrogen (N) (ca. 2–10% in the C or N) to reproduction (Kitayama et al. 2015). Therefore, the reproductive strategy of Bornean rainforest trees may be more critically selected by P availability.
For instance, an episodic reproduction of tropical trees in Southeast Asia (i.e. known as general flowering/fruiting) (Medway 1972; Appanah 1985, 1993; Ashton et al. 1988; Sakai et al. 1999; Brearley et al. 2007; Cannon et al. 2007) may be an adaptation to P deficiency, because the trees may require accumlated P for the episodic flowering/fruiting (Ichie et al. 2005; Ichie & Nakagawa 2013). However, the study on the reproduction of Bornean rainforest trees is scarce, and how Bornean rainforest trees on P-poor soils maintain reproductive activities remains mostly
80 unknown.
Kitayama et al. (2015) investigated P concentration in reproductive-organ
(flower and fruits combined and bulked) litter collected for ten years from eight
Bornean tropical rainforests, which differed in soil P availability, and found that P concentration in the reproductive-organ litter was negatively correlated with the P- use efficiency of net primary production (PUE; net primary production per unit P absorbed, Vitousek 1982). This suggests that P concentration in reproductive organs is lower on P-poorer soils, because PUE is negatively correlated with soil P availability (Kitayama et al. 2000). This result is not intuitively understandable, because the dilution of the P in reproductive organs may reduce reproductive success; the progenies on P-poorer soils, which may require a greater amount of P inherited from maternal trees (Thomson & Bolger 1993; Fenner & Thompson 2005;
White & Veneklaas 2012), will increasingly suffer from P deficiency.
Kitayama et al. (2015) proposed the following two possiblities for the decline of the P cocnentartion in the bulked litter of flowers/fruits with increasing
P deficiency: 1) P concentration in flowers/fruits is more diluted with increasing P deficiency, and 2) species with capsulate fruits increase in abundance with increasing P deficiency. The first possibility points that the proportion of P-diluted tissues within a reproductive organ increases with increasing P deficiency
(hypothesis 1). The reproductive organ of trees consists of inflorescence, seed, pericarp, pedicle, and etc. These components may have different P demands depending on the roles in reproduction. Seeds may require much P for germination and seedling growth (Thomson & Bolger 1993; Milberg & Lamont 1997; Lamont
& Groom 2002; White & Veneklaas 2012; Vandamme et al. 2016). Inflorescences may also require much P in pollen and embryo (Ashman 1994a, b). In contrast,
81 pericarps may not necessarily require P for the growth of progenies, and the P concentration may be diluted on P-poor soils.
The second possibility reflects the shift in the composition of tree species along the gradient of P availability. The relative proportion of tree species with capsulate fruits varied greatly among the forest communities on Mt. Kinabalu (Aiba
& Kitayama 1999). Capsulate fruits are expected to contain less P than fleshy fruits, because dry woody pericarps may contain a lesser amount of P compared with fleshy pericarps. Conversely, the fruits with fleshy pulps may contain more P to reward seed dispersers. Therefore, I hypothesize that the abundance of capsulate species increases with increasing P deficiency, which reduces mean P concentration per site in reproductive organs (hypothesis 2).
I aimed to examine the above two hypotheses in this study. I determined P concentration in fresh inflorescences, seeds, and pericarps for 46 tree species (21 genera) from eight tropical rainforests, which differed in soil P availability, on
Mount Kinabalu, Borneo. Mean P concentration per site in the above three reproductive organs was calculated and regressed against soil P availability for each genus, separately, in the light of the difference in flower/fruit types among genera.
To examine the linkage of the composition of fruit types with mean P concentration per site in reproductive organs, I estimated the composition of fruit types based on the relative abundances of genus and fruit types by genus in a given site using data in published works (see materials and methods). These results were discussed in association with different seed dispersal strategies among fruit types.
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4.2. Materials and methods
Study sites
Mount Kinabalu, Borneo (6°05′ N, 116°33′ E, 4096 m a.s.l.), is one of the most species-rich mountains in the world (Merckx et al. 2015), where tree species composition dramatically changes among soil substrates and altitudes (Kitayama &
Aiba 2002). Mount Kinabalu is a non-volcanic mountain, and consists of a granitic rock above 3000 m and of Tertiary sedimentary rocks below 3000 m (Collenette
1964; Choi 1996; Burton-Johnson et al. 2017). Ultrabasic rocks occur among the granite and sedimentary substrates as mosaic. Eight tropical rainforests were selected in a matrix manner consisting of four elevations (ca. 700, 1700, 2700, and
3100 m) and two substrates (sedimentary and ultrabasic rocks) on the southern slope of Mount Kinabalu by earlier workers (Aiba & Kitayama 1999). The 3100-m
“sedimentary” site is actually underlain by granite rock. In addition, one forest on
Quaternary colluvial sedimentary rock deposits at 1700 m was selected. These nine forests have been continuously monitored for the growth, biomass, and litterfall from 1996 (Aiba & Kitayama, 1999; Kitayama & Aiba 2002; Kitayama et al. 2015).
Eight out of the nine forests were investigated in this study. The 700-m site on ultrabasic rock was not studied here due to insufficient replication in the samples of flowers/fruits.
The climate in these sites is aseasonal humid tropical. Mean annual air temperature is 24.3°C at 550 m and predictably declines with a lapse rate of 0.55°C per 100 m (Kitayama 1992). The pool size of soil P was different among the sites depending on geological substrates and weathering in relation to altitude (Wagai et al. 2008). The pool size of total and soluble soil P was greater in the sedimentary sites than in the ultrabasic sites at the same altitude (Kitayama et al. 2000). Among
83 the three sites at 1700 m, the pool size of total and soluble soil P was greatest in the
Quaternary sedimentary, moderate in the Tertiary sedimentary substrates, and lowest on the ultrabasic substrate (Kitayama et al. 2004). Mean concentration per site in total and soluble soil P (extracted with 0.03N NH4F/0.1N HCl solution) was provided in Table 1.
Sampling of reproductive organs
Fully expanded inflorescences and mature fruits were sampled from a total of 46 dominant tree species (21 genera) from the eight sites (see Table S1), using a 15-m telescopic pruning pole and a catapult. The dominant species were selected based on basal area. An entire inflorescence was sampled from a shoot in the case of species with hermaphrodite flowers. In the case of Lithocarpus species, which had unisexual flowers, entire inflorescences were also collected because the inflorescence included both male and female flowers. In the case of Agathis and
Phyllocladus species (species with unisexual flowers), only male inflorescences were sampled due to the lack of enough female inflorescences. Inflorescences and fruits were collected from more than one canopy individual per species as much as possible (see Table S1). The sampled inflorescences and fruits were dried at 60°C for more than one week to a constant dry weight. After being dried, the fruits were divided to seeds (including embryo, cotyledon and seed coat) and pericarps (i.e. the pericarp with a pedicel for angiosperm, and the cone with a pedicel for gymnosperm). The seeds of drupes actually included woody endocarps (i.e. stone), because the stones could not be removed. Only viable seeds (i.e. containing embryos) were analyzed across the species, except for Tristaniopsis species. The seeds of Tristaniopsis species were analyzed as a mixture of viable and non-viable
84 seeds, because their seeds were too minute to separate non-viable from viable seeds.
Dried inflorescences, seeds, and pericarps were powdered by a vibration mill (TI-
200, Advantec, Tokyo, Japan) prior to chemical analysis.
Measurements of P concentration in reproductive organs
P concentration in the powdered samples was determined by the following procedure. The samples (ca. 200 mg) were digested with 5 mL of concentrated
H2SO4 and 2 mL of 30% H2O2 at 380°C for 5 hours. P concentration in the digests was determined using an inductively coupled plasma atomic emission spectrometer
(ICPS-7510, Shimadzu Co., Kyoto, Japan). P concentration in the sample was calculated on a dry mass basis.
The composition of fruit types
The composition of fruit types at each site was estimated based on the relative abundances of genera and fruit types by genus using the list of the species composition documented by Aiba et al. (2002). I targeted all the species with >
0.1% relative basal area. I categorized the fruit types of the listed species to the following categories; capsule, berry or drupe, nut, gymnosperm, the others, and unknown. The fruit type of each species/genus was determined according to the description in the following literatures: Sleumer (1955), Keng (1978),
Soepadmo & Wong (1995), Soepadmo, Wong & Saw (1996), Soepadmo, Saw &
Chung (2002, 2004), Elser (1997), Schot (2004), LaFrankie (2010), Soepadmo
& Saw (2000), and Soepadmo, Saw, Chung & Kiew (2007, 2011, 2014). I categorized fruit type as unknown when the information regarding fruit type was not obtained from these literatures.
85
The calculation of mean P concentration per site in reproductive organs
Mean P concentration per site in inflorescences, seeds, and pericarps was calculated for each genus, separately. When there were several species in a given genus, mean
P concentration was calculated for each species and the species-mean values were used as units of replication in a site.
Statistics
Ordinary least squares (OLS) regression was performed to fit the relationships of the following response variables against soil P availability or PUE: the mean P concentration per site by genus (i.e. mean P concentration per site calculated for each genus, separately) in inflorescences, seeds, and pericarps. Soluble soil P concentration at each site was used as an explanatory variable of soil P availability
(Table 1). PUE (the inverse of P concentration in litter) at each site was used as an index of P deficiency, because PUE commonly increases with the decline in P availability (Vitousek 1982; Silver 1994; Kitayama et al. 2000). Soluble soil P concentration and PUE at each site were cited from Kitayama & Aiba (2002) and
Kitayama et al. (2015). OLS models were fitted to each of the data sets by genus, separately. This approach is legitimate, because common species across sites are very few on this mountain due to high species turnover (Aiba & Kitayama 1999) and because flower/fruit traits are usually conservative within a given genus.
Significance was assessed at P = 0.1 due to the small sample size per genus (n = 3–
8) in this regression analysis. Following the OLS regression analysis, sign tests were performed to examine whether the OLS models by genus had a common sign in the Pearson`s correlation coefficients (i.e. plus or minus) across genera or not.
When one or more genera have the counter sign to the majority, significance is not
86 achieved with sample sizes of 6–7 or 8–9 genera.
A logistic regression with binomial error distribution was performed to model the relationship between the composition of fruit types and soil P availability or PUE. I also calculated community-weighted mean (CWM) to explore the linkage of the composition of fruit types with mean P concentration per site in reproductive organs. The CWM was defined as the average of species-mean P concentration weighted by the relative basal area of each species sampled in a site. In the estimation of the CWM, the species-mean values were calculated at each site, respectively. The relationships of the following response variables against soluble soil P concentration or PUE were examined by OLS regressions: the mean P concentration per site by genus in inflorescences, seeds, and pericarps.
The differences among fruit types were tested by ANOVAs for P concentration in seeds and pericarps. This analysis was performed using mean values per site by species. The pooled data of the 46 species were used in this analysis.
There was a large variation in altitude among sites (i.e. ca. 700–3100 m), which was possibly correlated with P concentration in reproductive organs.
Therefore, the same analyses were conducted to test significant relationships of the following response variables with altitude: the mean P concentration per site by genus in inflorescences, seeds, and pericarps, and the CWM P concentration in the same tissues. There was no significant correlation between the mean P concentration per site by genus and altitude across all the genera (Figs. 4-1g–i), and also between the CWM P concentration and altitude (Figs. 4-3g–i), for all the reproductive organs. Therefore, I focused only on the relationships of P concentration in reproductive organs with soil P availability or PUE in the following
87 results and discussion.
4.3. Results
P concentration in reproductive organs
Mean P concentration per site by genus was 0.32–1.54, 0.17–4.36, and 0.08–1.49 mg g-1 in inflorescences, seeds, and pericarps, respectively (Fig. 4-1). The mean P concentration per site by genus in inflorescences was significantly positively correlated with soluble soil P concentration (or negatively with PUE) for many genera (Figs. 4-1a and d, P < 0.10). These patterns in inflorescences were significant majorities across genera (sign test, P < 0.05); i.e. 7 of 8 genera shared the same sign in the Pearson`s correlation coefficient of the OLS models by genus
(see Table 2). In contrast, the mean P concentration per site by genus in seeds and pericarps was not significantly correlated with both soluble soil P concentration and
PUE (P > 0.10), except for the seeds of Syzygium and Ternstroemia species (Figs.
4-1b, c, e, and f). The mean P concentration per site by genus in seeds was significantly positively correlated with soluble soil P concentration (or negatively with PUE) in the case of Syzygium species (Figs. 4-1b and d, P < 0.10). The mean
P concentration per site by genus in seeds was significantly negatively correlated with soluble soil P concentration in the case of Ternstroemia species (Fig. 4-1d, P
< 0.10). Significant majorities across genera were not found in the signs in the
Pearson`s correlation coefficients of the OLS models by genus, both for seeds and pericarps (Table 2).
Mean P concentration in seeds and pericarps was significantly different among fruit types (ANOVA, P < 0.05; Fig. 4-2), when all species were pooled.
Mean P concentration in seeds by fruit type was significantly higher in capsulate
88 fruits than in acorns and drupes (Tukey HSD, P < 0.05; Fig. 4-2a). Mean P concentration in pericarps by fruit type was significantly lower in capsulate fruits than in drupes (Tukey HSD, P < 0.05; Fig. 4-2b).
Community weighted mean (CWM) P concentration
The CWM P concentration varied from 0.61–1.32, 0.42–1.42, and 0.29–1.01 mg g-
1 in inflorescences, seeds, and pericarps, respectively (Fig. 4-3). The CWMs showed quite similar trends with the mean values per site by genus across all the response variables (Fig. 4-3). The CWM P concentration in inflorescences was significantly positively correlated with soluble soil P concentration (or negatively with PUE)
(Figs. 4-3a and d, P < 0.05). The CWM P concentration in seeds and pericarps was not significantly correlated both with soluble soil P concentration and PUE (Figs.
4-3b, c, e, and f, P > 0.05).
The composition of fruit types
The relative proportion of species with capsulate fruits increased with the decline in soluble soil P concentration or the increase of PUE, from 4.3% in the most P-rich site (i.e. the site of the Quaternary colluvial sedimentary rock deposits at 1700 m asl) up to 89.5% in the most P-poor site (i.e. the site of the ultrabasic rock at 3100 m asl) (Figs. 4-4a and b). In contrast, the relative proportions of species with the other fruit types decreased with the decline in soluble soil P concentration or the increase of PUE, except for gymnosperm. The relative proportion of gymnosperm was invariant across the sites with different PUEs. The relative proportion of capsulate fruits increased along an altitudinal gradient, while those of the other fruit types decreased (Fig. 4-4c).
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4.4. Discussion
The aim of this study is to elucidate the underlying mechanism and ecological significance of the dilution of P in reproductive organs with increasing P deficiency.
The results from this study showed that the dilution of P in reproductive organs was both due to 1) low P concentration in inflorescences but not in fruits (Figs. 4-1a–f, and 4-3a–f), and 2) the dominance of capsulate species (Figs. 4-4a and b). The former suggests that the allocation of P among reproductive organs is critically selected by P availability. The latter implies that community assemblage influences the dynamics of P in a forest via fruit type.
P concentration in reproductive organs
The mean P concentration per site by genus in inflorescences significantly decreased with decreasing P availability (Figs. 4-1a, and d, P < 0.10), which was a common trend across most genera (Table 4-2). This is in contrast with my hypothesis. I expected that P concentration in inflorescences was maintained even on P-poorer soils, because ample P in pollen and embryos is required for pollination success. However, P-poor environments favored tree species with low P concentration in inflorescences across lineages.
This low P concentration in inflorescences may be associated with the following two mechanisms: 1) P resorption from inflorescences during abscission, and/or 2) low P concentration in fresh inflorescences. Ashman (1994a) showed that
P was resorbed from non-dispersive reproductive components (i.e. calyx, and corolla complex) but not from dispersive reproductive components (i.e. pollen and seeds) during abscission. The P resorbed from inflorescences may be reallocated to developing fruits and/or other parts. However, this possibility is unlikely in this
90 study, because I sampled only fresh inflorescences before abscission. Therefore, the second mechanism is more likely. A fresh inflorescence may include the non- dispersive reproductive components with lower P concentration. If so, P concentration in fresh inflorescences may be diluted without the reduction of P concentration in pollen and embryos.
In contrast to inflorescences, P concentration in seeds was maintained even on P-poor soils (Figs. 4-1b and e). This may be because tree species on P-poor soils accumulate P in seeds (e.g. Witkowski 1990; DiManno & Ostertag 2016). The accumulation of P in seeds was often found in species naturally growing on P-poor soils (Atkinson & Davison 1971; Witkowski 1990; Groom & Lamont 2010;
DiManno & Ostertag 2016). For instance, DiManno & Ostertag (2016) conducted
P or nitrogen (N) fertilization experiments at two sites with contrasting soil fertility
(P-limited sites vs. N-limited sites) in the Hawaiian Archipelago, and found that
Metrosideros polymorpha (Myrtaceae) at the P-limited sites accumulated P in seeds in response to P fertilization while that at the N-limited sites did not. They also showed that Metrosideros polymorapha had a greater P concentration in seeds at the P-limited sites than at the N-limited sites under natural conditions (DiManno &
Ostertag 2016). Similarly, Witkowski (1990) showed that Australian Proteaceae inhabiting P-poor soils accumulated P in seeds in response to P fertilization. Groom
& Lamont (2010) showed that Proteaceae from southwestern Australia (stronger P deficiency) had on average two-fold greater P concentration in seeds than those from the Cape of Africa (weaker P deficiency). The accumulation of P in seeds is considered to be an adaptive mechanism to P deficiency (Lambers et al. 2015b;
DiManno & Ostertag 2016), because the storage of P in seeds contributes to rapid
91 seedling growth on P-poor soils (e.g. Thomson & Bolger 1993; Groom & Lamont,
2010; Vandamme et al. 2016).
I hypothesized that P concentration in pericarps decreased with increasing
P deficiency. However, contrary to this hypothesis, P concentration in pericarps was invariant across the sites with different P availability; i.e. the mean P concentration per site by genus in pericarps was not significantly correlated with soil P availability or PUE across genera (Figs. 4-1c and f, P > 0.10). Therefore, my hypothesis was not accepted. Rather, P concentration in pericarps was in association with fruit type.
Mean P concentration in pericarps was significantly different among fruit types when all species were pooled (ANOVA, P < 0.05). P concentration in pericarps may be related to seed-dispersal syndromes. For instance, the seeds of berries and drupes are typically dispersed by animals; such fruits have a high P concentration to reward seed dispersers even on P-poorer soils. Indeed, high P concentration in the pericarps of berries and drupes (e.g. Syzygium, Ternstroemia, and Prunus) (0.26–1.21 mg g-
1) was found across sites (Figs. 4-1b and e, and 2b). In contrast, the fruits with wind- dispersed seeds may require less P in pericarps (e.g. capsules). P concentration in capsules was low (0.08–0.57 mg g-1) across all sites for Leptospermum,
Tristaniopsis, and Schima species (Figs. 4-1b and e, and 4-2b).
The shift in the composition of fruit types along a soil P gradient
In present study sites, the relative proportion of capsulate fruits increased with increasing P deficiency, while that of drupes or berries decreased (Figs. 4-4a and b).
The abundance of capsulate species may explain the mean concentration of P in reproductive organs, because capsulate fruits had significantly lower P concentration in pericarps than the other fruit types (ANOVA, P < 0.05; Fig. 4-2b).
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The reason why capsulate species dominated with greater abundance on P-poorer soils is an intriguing question. One possibility is that seed dispersal by wind is adaptive to P deficiency. Capsulate species are predominantly wind-dispersed, and the pericarps may require less P to reward seed dispersers (Fig. 4-2b). Capsulate species require a smaller amount of P per fruit, and hence could maintain the production of massive fruits even under P deficiency. Furthermore, mean P concentration in seeds was significantly greater in capsulate species than in the other fruit types (Fig. 4-2a, P < 0.05). This greater P concentration in seeds may help seedling growth on infertile soils (Thomson & Bolger 1993; Vandamme et al.
2016), assuring a competitive advantage on P-poor soils.
Further study is required to understand the relationship between fruit types and P availability, because the dominance of capsulate species may be linked with many other factors such as phenology, air temperature, precipitation, and fruit- frugivore interactions (Almeida-neto et al. 2008; Fenner 2012; Correa et al. 2015;
Chen et al. 2017a). For instance, the dominance of the species with dry pericarps including capsulate species may be associated with the decline in air temperature along an altitudinal gradient (Chen et al. 2017a) (see Fig. 4-4c). In addition, the lack (or reduction) of frugivore mammals at higher elevations (Nor 2001) may also explain the dominance of capsulate species, which are dispersed by winds.
4.5. Conclusion
There are two mechanisms to explain the P-use efficiency in reproduction in
Bornean rainforest trees. Firstly, the dilution of P concentration in inflorescences maintains the production of unit reproductive organ with a lesser amount of P.
However, such species with diluted P in inflorescences still maintained the P
93 concentration in seeds, implying that these species maintain P investment to progenies in exchange with reduced P in inflorescences. Secondly, the community shift to capsulate species, whose pericarps contain less P than those of the other fruits types, maintains the reproduction with a smaller P investment at an individual or a stand level. These mechanisms may increase the productivity of reproductive organs per unit P and maintain reproductive activities under P limitation.
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Table 4-1. Description of the eight study sites on Mount Kinabalu, Borneo. Canopy height represents the maximum height of a tree at the site (cited from Kitayama & Aiba 2002). Total soil P represents the mean content of total soil P per site (30 cm depth in a topsoil) (cited from Kitayama et al. 2000). Soluble soil P represents the mean concentration per site of soluble soil P that was extracted with hydrochloric-ammonium fluoride solution (15 cm depth in a topsoil) (cited from Kitayama & Aiba 2002 and Takyu et al. 2002b). P-use efficiency (PUE) is calculated as the inverse of the P concentration in litter that was collected during the 10 years from 1996 to 2006 (cited from Kitayama et al. 2015).
Site name Altitude (m) Canopy height (m) Total soil P (g m-2) Soluble soil P (g m-2) PUE (g g-1) Forest type Sedimentary sites 700S 650 46.8 61.36 0.18 2195 Hill dipterocarp forest 1700S 1560 30 34.87 0.14 3025 Lower montane forest 2700S 2590 20.6 72.57 0.36 2230 Upper montane forest
A granite site 3100S 3080 15 37.15 0.35 2478 Subalpine forest
Ultrabasic sites 1700U 1860 22.6 8.97 0.04 5159 Lower montane forest 2700U 2700 14.2 21.47 0.09 4785 Upper montane forest 3100U 3050 6.1 12.02 0.07 6326 Subalpine shrub
A quaternary sedimentary site 1700Q 1860 32.1 60.82 0.19 1964 Lower montane rain forest
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Table 4-2. The signs of the Pearson`s correlation coefficients of the following response variables against soluble soil P concentration, P-use efficiency (PUE), and altitude at each site on Mount Kinabalu, Borneo; mean P concentration per site in inflorescences, seeds, and pericarps. The mean P concentration per site was calculated for each genus, separately. The sign of the Pearson`s correlation coefficients were calculated for each genus (7–9 tree genera), respectively. The number of genera sharing the same sign in the Pearson`s correlation coefficients was documented in the table. Significant majorities in the signs of the Pearson`s correlation coefficients were examined by sign-tests.
Soluble soil P (g m-2) PUE (g g-1) Altitude (m) Response variables - + Sign-test - + Sign-test - + Sign-test Inflorescence P (mg g-1) 1 7 P < 0.05 7 1 P < 0.05 4 4 n.s. Seed P (mg g-1) 2 5 n.s. 6 1 n.s. 3 4 n.s. Pericarp P (mg g-1) 2 7 n.s. 5 4 n.s. 2 7 n.s.
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Figure 4-1. Relationships of mean P concentration per site in reproductive organs with soluble soil P concentration (a–c), P-use efficiency (PUE) (d–f), or altitude at each site (g–i), for 21 tree genera on Mount Kinabalu, Borneo. The mean P concentration per site was calculated for each genus, respectively. OLS models were fitted to each of the data sets by genus, separately. Solid, and dotted lines denote significant (P < 0.1), and non-significant correlation, respectively. Significance was assessed at P = 0.1 due to the small sample size per genus (n = 3–8). Different colored and/or shaped symbols represent different genera (see the legend in the figure).
97
Figure 4-2. Boxplots showing mean P concentration by species in seeds (a) and pericarps (b) for six fruit types from eight forests on Mount Kinabalu, Borneo. Mean P concentration by species were calculated at each site and used to demonstrate the data distributions, because P concentrations in reproductive organs were significantly different among sites within a species. The central box in each box plot shows the inter quartile range and median; the whiskers extend 1.5 times the inter quartile range or to the most extreme value. Pairwise significant differences among sites are shown as different letters (Tukey HSD, P < 0.05).
98
Figure 4-3. Relationships of community weighted-mean (CWM) P concentration in reproductive organs with mean concentration per site in soluble soil P (a–c), mean P-use efficiency (PUE) per site (d–f), and altitude (g–i) for eight forests on Mount Kinabalu, Borneo. Solid, and dotted lines denote significant (P < 0.05), and non-significant correlation, respectively.
99
Figure 4-4. Relationships of the relative proportion of fruit types with soluble soil P concentration (a), P-use efficiency (PUE)
(b), or altitude (c) for eight forests on Mount Kinabalu, Borneo. Black, red, brown, blue, orange, and green colored symbols/ lines represent capsule, berry or drupe, nut, gymnosperm, the others, and unknown, respectively.
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Table 4-S1. The list of the species sampled at each forest. Numbers represent the replication of individuals in a species.
Site Species Inflorescences Seeds Pericarps
1700U Agathis kinabaluensis 1 1 2 Leptospermum flavescens 3 Lithocarpus rigidus 3 1 2 Phyllocladus hypophyllus 1 1 Prunus sp17U 1 1 Schima brevifolia 4 2 Syzygium havilandii 1 1 1 Syzygium petrophyllum 1 1 1 Tetractomia sp17U 1 Timonius sp17U 2 Tristaniopsis kinabaluensis 1 Weiinmania cf brumei 3 2700U Ilex zygophylla 3 Leptospermum flavescens 1 Leptospermum recurvum 4 2 Phyllocladus hypophyllus 1 2 2 Prunus arborea 1 1 Schima wallichii 3 1 1 Symplocos sp27U 1 Syzygium steenisii 1 1 1 Ternstroemia lowii 1 1 1 Tristaniopsis sp27U 3 3100U Leptospermum recurvum 4 Phyllocladus hypophyllus 5 4 4 700S Lithocarpus sp07S 1 1 Syzygium sp07S 1 1 1700S Agathis bornensis 3 Elaeocarpus sp17S 1 1 Lithocarpus clementianus 1 1 Lithocarpus havilandii 3 Lithocarpus revoluta 1
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Lithocarpus sp17S1 2 Lithocarpus sp17S3 1 1 Quercus psedoverticellata 1 1 Schima wallichii 1 1 1 Syzygium cf castaneum 1 1 1 Syzygium chrysanthum 2 Syzygium pachrysepalum 2 2 Syzygium sp17S 1 Tristaniopsis clementianus 1 2700S Ilex zygophylla 1 Leptospermum flavescens 3 2 Lithocarpus sp27S 2 Lithocarpus turbinatus 3 2 3 Magnolia carsonii 1 1 1 Olea decussata 2 2 Phyllocladus hypophyllus 1 1 Syzygium sp27S 1 Tristaniopsis sp27S 1 1 3100S Leptospermum recurvum 3 3 Phyllocladus hypophyllus 4 4 Polyosma hooklly 1 1 Syzygium houttuynii 3 3 3 Ternstroemia lowii 1 1 1700Q Lithocarpus havilandii 1 Lithocarpus lampadalius 2 2 Magnolia sp17Q 1 1 Schima wallichii 1 Ternstroemia magnifica 3 2 2
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Chapter 5. Significance of phosphorus allocation among tree organs for the residence time of phosphorus in tropical rainforest biomass
Abstract
Trees under phosphorus (P) limitation have developed P conservation mechanisms
(e.g. P resorption from senescing tissues), which may lead to a long residence time of P in tree biomass. How the conservation of P contributes to the residence time of
P in tree biomass has not been quantitatively examined in tropical rainforests, where productivity is often limited by P. I estimated P mass in tree aboveground biomass
(AGB; including leaves and wood) and the annual loss of P via litterfall, and quantified the residence time of P in AGB (P mass in AGB/annual P loss via litterfall) for eight tropical rainforests, which differed in P availability, on Mount
Kinabalu, Borneo. The residence time of P in AGB (2.2–10.3 yr) was five-fold shorter than the turnover time of AGB per se (AGB/annual litterfall mass; 16.9–
39.5 yr). This was due to a disproportionately greater allocation ratio of P to leaves
(9.5–48.0%), which had a small fraction of biomass (1.0–4.6%) but a much faster turnover. Therefore, the rate of P loss via litterfall was faster than would be expected from that of biomass per se. The allocation ratio of P to leaves increased with the decrease in the concentration of soluble soil P, and hence a shorter residence time of P in AGB was expected under severer P deficiency. However, the residence time of P in AGB was invariant across forests with different P availabilities; this was due to greater resorption of P from senescing leaves with the decrease in the concentration of soluble soil P, which reduced up to 66% of the annual loss of P via litterfall. This study demonstrates the importance of P allocation among tree organs in the cycling of P in forest ecosystems.
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Key words: ecosystem functioning, nutrient allocation, nutrient cycling, nutrient- use efficiency, nutrient resorption, phosphorus deficiency
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5.1. Introduction
Understanding the mechanisms and processes underlying nutrient cycling is a central topic in ecosystem ecology (Vitousek 1982; Costanza et al. 1997; Vanni
2002; Vitousek 2004; Chapin et al. 2011). Biological, geological, and other factors influence the cycling of nutrients in terrestrial ecosystems (Hättenschwiler &
Vitousek 2000; Vanni 2002; Vitousek 2004; Vergutz et al. 2012). The rate of nutrient cycling is strongly controlled by the pool size of the nutrient in and flux rate of the nutrient to/from plant biomass in an ecosystem. Therefore, such plant activities as nutrient allocation, translocation, and acquisition will influence the rate of nutrient cycling (Jackson et al. 1997; Poorter et al. 2012; Vergutz et al. 2012; Bardgett et al.
2014; Hobbie 2015).
Phosphorus (P) is an essential nutrient for plants (Malkin & Niyogi 2000;
Marschner 2005; Raven et al. 2005), and often limits the productivity of plant communities (Wardle et al. 2004; Elser et al. 2007; Vitousek 2010), especially in tropical rainforests (Vitousek 1984; Cleveland et al. 2011; Laliberté et al. 2015;
Fujii et al. 2017). Soils in the tropics are often highly weathered and contain little bioavailable P (Crews et al. 1995; Yang et al. 2014; Fujii et al. 2017). Despite the low availability of P in soils, tropical rainforests are highly productive and gigantic
(Kitayama et al. 2000; Kitayama 2005). This is because tropical rainforest trees have high P-use efficiency (PUE; net primary productivity per unit P absorbed from soils; Vitousek 1982) with adaptive mechanisms to P deficiency (Vitousek 1984;
Paoli et al. 2005; Hidaka 2011; Hidaka & Kitayama 2011, 2013).
The residence time of P in tree biomass, defined as P mass in tree biomass divided by the annual loss of P via litterfall, is a consequence of the plant adaptive traits to increase/decrease PUE (Berendse & Aerts 1987). Elongating the residence
105 time of P in canopy increases PUE, because PUE is the product of P productivity
(annual productivity per P mass in canopy) and the residence time of P (Berendse
& Aerts 1987). Previous studies estimated the residence time of P in the canopy of
Bornean tropical rainforests that differed in soil P availability, and found a negative correlation between the residence time and soil P availability (Paoli et al. 2005;
Hidaka 2011). They suggested that the long residence time of P in the canopy was adaptive to P deficiency, and contributed to enhancing PUE on P-poor soils (Paoli et al. 2005; Hidaka 2011). However, these studies did not show the exact residence time of P in tree biomass because they focused on canopy leaves only.
Wood accounts for a substantial percentage of tree biomass (Tanner 1982;
Jonson et al. 2001; Feldpausch et al. 2004; Imai et al. 2010; Sardans & Peñuelas
2013), and the P bound in wood biomass may have a large influence on the residence time of P in tree biomass as a whole. However, the residence time of P in the entire tree biomass has not been estimated. P concentration in wood is lower than that in leaves (Jonson et al. 2001; Imai et al. 2010; Sardans & Peñuelas 2013). Therefore, a much smaller fraction of P may be allocated to wood than expected from wood biomass per se (Jonson et al. 2001; Imai et al. 2010; Sardans & Peñuelas 2013). By contrast, a disproportionately greater amount of P may be allocated to leaves, which have a smaller fraction of biomass. This large allocation ratio of P to leaves may lead to a fast rate of P loss via litterfall, because the residence time of leaves is shorter than that of whole tree biomass. If so, the residence time of P in tree biomass would be shorter than the residence time of tree biomass per se (i.e. the inverse of the turnover rate of tree biomass) against the long-standing hypothesis that P has a prolonged residence time in vegetation (e.g. Hidaka 2011). This points to the importance of P allocation among tree organs to influence the residence time of P.
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P allocation among tree organs may be influenced by P availability
(Gleason et al. 2009; Aoyagi & Kitayama 2016). Aoyagi & Kitayama (2016) investigated P allocation among tree organs (leaves, stems, and roots) in relation to
P availability for the saplings of 13 Bornean tree species. They found a significant increase of the allocation ratio of P to leaves with decreasing P availability, and suggested that the greater allocation ratio of P to leaves (i.e. photosynthesis) helped maintain tree productivity on P-poor soils (Aoyagi & Kitayama 2016). The same trend was found also for mature trees in Australian tropical rainforests (Gleason et al. 2009). Therefore, increased P allocation to leaves with P deficiency is a common trend across biomes to enhance instantaneous photosynthetic rate per tree; however, this potentially sacrifices another adaptation mechanism to P deficiency, i.e. a long residence time of P in tree biomass. How trees resolve this apparent dilemma?
Resorption provides a solution for this dilemma. Resorption of P is a process by which plants degrade P-containing compounds and resorb P from senescing leaves
(Killingbeck 2004). Tropical trees on P-poor soils exhibit an extremely high P resorption efficiency (PRE, the percentage of the P resorbed from senescing leaves before abscission per P in green leaves) (Hidaka & Kitayama 2011; Tsujii et al.
2017b). Therefore, increased PRE with increasing P deficiency can elongate the residence time of P in tree biomass to offset the effects of P allocation to leaves
(process 2).
I aimed to examine the relationships between P allocation to leaves and P resorption from leaves in this study, and their influences on P residence time. I calculated P mass in tree aboveground biomass (AGB; including leaves and wood) and the annual flux of P via litterfall, and quantified the residence time of P in AGB
(P mass in AGB/annual P flux via litterfall) for eight tropical rainforests that
107 differed in soil P availability, on Mount Kinabalu, Borneo. The contribution of P resorption from senescing leaves to the residence time of P was evaluated by comparing with and without P resorption. The turnover time of AGB was estimated as AGB divided by annual litterfall mass, and was compared with the residence time of P in AGB to examine the difference between the turnover rates of P and biomass in a forest.
5.2. Materials and methods
Study sites
This study was carried out in eight sites of tropical rainforests on Mount Kinabalu,
Borneo (6°05′ N, 116°33′ E, 4096 m a.s.l.) (Table 5-1). These sites consist of four altitudes (ca. 700, 1700, 2700, and 3100 m) on each of the two substrates (P-rich sedimentary and P-poor ultrabasic rocks), which were established to explore the effects of the interaction of P availability and altitude on the forest dynamics by earlier workers (Aiba & Kityama 1999; Kitayama & Aiba 2002). The 3100-m
“sedimentary” site is actually underlain by granite rock. These forests have been continuously monitored for biomass, productivity, and litterfall from 1996 (Aiba &
Kitayama 1999; Kitayama & Aiba 2002; Kitayama et al. 2015). Climate is aseasonal humid tropical. Mean annual air temperature is 24.3°C at 550 m and declines with a lapse rate of 0.0055°C m-1 (Kitayama 1992). Mean annual precipitation is >2000 mm yr-1 across the sites. The pool size of soil P was different among the sites depending on rock substrates and weathering in relation to altitude (Wagai et al.
2008). The concentration of total and soluble soil P was greater in the sedimentary than the ultrabasic sites at the same altitudes (Kitayama & Aiba 2002). The detailed information on these sites is described in Table 5-1.
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Analysis of P concentration in leaves and wood
Fully expanded top canopy sun leaves were sampled from more than five dominant tree species in each forest, using a 15-m telescopic pruning pole, a catapult, and tree climbing techniques. Wood cores (5.2 mm in diameter and 5 cm in length) were sampled from more than three dominant tree species in each forest at 1.4 m height from the ground. Leaves and wood cores were collected from more than three canopy individuals per species per site. More than one leaves and one or two wood cores were sampled per individual. The sum of the relative basal area (RBA) of the sampled species attained 32.8–99.9% per site (see Table 5-S1). P concentration in the samples was determined by the following procedure. Dried leaves and wood cores (ca. 200–400 mg) were digested with 5 mL of concentrated H2SO4 and 2 mL of 30% H2O2 at 380°C for 5 hours. P concentration in the digests was determined by an inductively coupled plasma atomic emission spectrometer (ICPS-7510,
Shimadzu Co., Kyoto, Japan). P concentration in the samples was calculated on a dry mass basis.
I calculated community-weighted mean (CWM) P concentration in leaves and wood to estimate their mean P concentration at a forest level. The CWM was defined as the average of species-mean P concentration weighted by the relative basal area of each species sampled per site. The CWM P concentration was used in the calculation of the mass and residence time of P in AGB. Mean P concentrations in green leaves per species at the 1700-m sedimentary and ultrabasic sites were cited from Tsujii et al. (2017a and b).
The estimation of AGB
All trees ≥10 cm diameter at breast height (dbh) within each plot were measured in
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2011 (Aiba et al. unpublished data). The heights of trees were estimated by a hyperbolic allometric equation (Ogawa 1969, equation 5.1):
1/H = 1/AD +1/H* (equation 5.1)
where A and H∗ are regression constants. The data on A and H* at each site were cited from Kitayama & Aiba (2002). D and H represent the dbh and height of trees, respectively.
AGB was estimated using the following allometric equations obtained from a lowland dipterocarp forest in West Kalimantan (Yamakura et al. 1986, equation 5.2).
Ws = 0.02903 (D2 H)0.9813 (equation 5.2)
Wb = 0.1192 Ws1.059, and Wl = 0.09146 (Ws + Wb)0.7266
where Ws, Wb and Wl (kg) represent the dry mass of the stems, branches, and leaves of trees, respectively. D and H represent the dbh and height of trees, respectively.
Earlier works suggested that these equations reasonably well estimated the AGB of forests from lowland to alpine on Mount Kinabalu (Kitayama & Aiba 2002). Wood biomass was calculated as the sum of Ws and Wb.
P mass in AGB
P mass in AGB was estimated as the sum of leaf and wood biomass multiplied by leaf and wood CWM P concentration, respectively (equation 5.4). P concentration
110 in wood decreases from the outer sapwood to the inner heartwood area across a stem section (Meerts 2002; Heineman et al. 2016). However, it is not practical to measure the P concentration across the diameter of each tree, because destructive sampling is inevitably involved in such a measurement. Instead, I took an approach to estimate the upper bound and lower bound of the P mass in wood. The upper bound was estimated as wood biomass multiplied by the CWM P concentration in outer (5-cm depth) wood. The derived P mass in wood may be overestimated, because outer wood is mainly comprised of sapwood, which has a greater P concentration than heartwood (Meerts 2002; Heineman et al. 2016). The lower bound was estimated as sapwood biomass multiplied by the CWM P concentration of outer wood. Therefore the lower bound does not account for the P in heartwood.
Sapwood here was defined as the wood within 5-cm depth from bark, and its mass was estimated as stem biomass minus “heartwood” biomass. “Heartwood” here was defined as the wood deeper than 5 cm from the circumference and its diameter (cm) was given by the measured diameter (cm) minus 10 cm. Branch biomass (which is predominantly sapwood) was not included in this calculation, and hence sapwood biomass would be underestimated. Derived sapwood biomass accounted for 32–
84% of that of whole wood.
Wh = 0.02903 (Dh2 Hh)0.9813 (equation 5.3)
Dh = D – 10 cm
1/Hh = 1/ADh +1/H∗
Wss = Ws – Wh
where Wh, Wss, and Ws (kg) represent the dry mass of the heartwood, sapwood,
111 and stem wood of trees, respectively. D, Dh and Hh represent the dbh of trees, and the dbh and height of heartwood, respectively.
P mass in each organ was estimated as follows:
P mass in leaves ＝ Leaf biomass * Leaf [P] (equation 5.4)
P mass in wood ＝ Wood biomass * Wood [P]
P mass in sapwood ＝ Sapwood biomass * Wood [P]
where leaf [P], and wood [P] (mg g-1) represent the CWM P concentration in leaves and wood, respectively. Again, P mass in wood represents the upper bound of P in wood, and P mass in sapwood represents the lower bound of P in wood in my study.
The residence time of P in AGB
The residence time of P in AGB was estimated as P mass in AGB divided by the annual flux of P via litterfall. P mass in AGB was calculated as the sum of P mass in leaves and wood. There is logically a positive correlation between the allocation ratio of P to wood and the residence time of P in AGB (see introduction). Therefore, the upper bound and lower bound of the residence time of P in AGB were estimated using the upper bound and lower bound of P mass in wood, respectively. The annual flux of P via litterfall was calculated as the sum fluxes of P in fine litter (including leaves, reproductive organs, and branches/bark) and coarse litter (stem wood). The
P fluxes via fine-litterfall were cited from the data set obtained by a 10-year continuous collection of litterfall on the study sites (Kitayama et al. 2015). Coarse litter is supplied primarily as fallen stem wood. In addition, my study sites were mature forests, where the growth and the mortality (production of fallen stem wood)
112 can be considered at a dynamic equilibrium. Therefore, the annual flux of P via coarse litterfall (i.e. fallen stem wood as fresh wood) could be estimated as annual wood increment multiplied by P concentration in fresh wood. P mass in fallen stem wood was estimated in the same way as the P mass in standing wood either assuming a constant (sapwood) P concentration from sap to heartwood (upper bound), or zero
P concentration in heartwood (lower bound).
Overall, the residence time of P in AGB was estimated as follows for an upper and a lower bound value (equation 5.5):
The residence time of P in AGB (upper bound) (equation 5.5)
= {P mass in leaves + P mass in wood (upper bound)} / {Annual P flux via fine
litterfall + Annual P flux via coarse litterfall (upper bound)}
The residence time of P in AGB (lower bound)
= {P mass in leaves + P mass in wood (lower bound)} / {Annual P flux via fine
litterfall + Annual P flux via coarse litterfall (lower bound)}
Annual P flux via coarse litterfall (upper bound) = Annual wood increment * Wood
[P]
Annual P flux via coarse litterfall (lower bound) = Annual mass of fallen stem
sapwood * Wood [P]
Annual mass of fallen stem sapwood = Annual wood increment * Sapwood biomass
/ Wood biomass
where wood [P] (mg g-1) represents the actually measured CWM P concentration in wood using outer 5-cm cores. The following data were cited from Kitayama et al.
(2015): the annual flux of P via the litterfall of leaves, reproductive organs, and
113 branches/bark. Annual wood increment was cited from Kitayama & Aiba (2002).
The turnover time of AGB
The turnover time of AGB was estimated as AGB divided by annual litterfall mass.
Annual litterfall mass was calculated as the sum of the annual mass of fine litter
(including leaves, reproductive organs, and branches/bark) and coarse litter (stem wood). The annual mass of the coarse litter was similarly estimated as annual wood increment as above. AGB, the annual mass of fine litter, and annual wood increment were cited from Kitayama & Aiba (2002). The turnover time of AGB was compared with the residence time of P in AGB.
The effect of P resorption from senescing leaves on the residence time of P in AGB
I evaluated the effect of P resorption from senescing leaves on the residence time of P by comparing with and without P resorption. The residence time of P in AGB without P resorption was estimated by assuming that P concentration in leaf litter was equal to the CWM P concentration in fresh leaves; the annual flux of P via leaf litterfall without P resorption was estimated as the annual mass of leaf litterfall multiplied by the CWM P concentration in fresh leaves.
Data analysis
Ordinary least square regressions were performed to examine the relationships of the following response variables with altitude or the concentration of soluble soil
P: 1) the CWM P concentration in leaves or wood, and 2) the turnover time of AGB.
Altitude was selected as an explanatory variable, because the allocation ratio of biomass to leaves increased and the turnover time of AGB largely varied along an
114 altitudinal gradient (Kitayama & Aiba 2002), which potentially influences the residence time of P in AGB. Altitude and the concentration of soluble soil P at each site were cited from Kitayama & Aiba (2002) and Kitayama et al. (2015).
5.3. Results
Community weighted mean (CWM) P concentration
The CWM P concentration in leaves (0.21–0.75 mg g-1) was seven-fold or more greater than that in wood (0.01–0.10 mg g-1). The CWM P concentration in leaves was lower in the ultrabasic (P-poor soils) than in the sedimentary sites (P-rich soils) at the same altitudes (Fig. 5-1a), in line with previous observation (Kitayama &
Aiba 2002). The CWM P concentration in leaves was significantly negatively correlated with altitude (Fig. 5-1a, P < 0.05), while that was not significantly correlated with the concentration of soluble soil P (Fig. 5-1c, P > 0.05). The CWM
P concentrations in wood was smaller in the ultrabasic (P-poor soils) than the sedimentary sites (P-rich soils) at the same altitudes (Fig. 5-1b). The CWM P concentration in wood was not significantly correlated with altitude (Fig. 5-1b, P >
0.05), while that was significantly positively correlated with the concentration of soluble soil P (Fig. 5-1d, P < 0.05).
P mass in tree organs
The greater P concentration in leaves than in wood resulted in a disproportionately greater allocation ratio of P to leaves (16.2–48.0%) compared to leaf-biomass allocation per se (1.0–4.6%). P mass was 0.04–0.37, 0.12–2.79, and 0.10–1.22 g m-
2 for leaves, wood (upper bound), and wood (lower bound), respectively (Figs. 5-
2a and c). The relative allocation of P was 9.5–36.4, and 63.6–90.5% for leaves,
115 and wood, respectively (Fig. 5-2b), when P mass in wood was estimated on the assumption that P concentration in wood was constant from the sapwood to heartwood area across a stem section (i.e. upper bound). The relative allocation of
P was 16.2–48.0, and 52.0–83.8% for leaves, and wood, respectively (Fig. 5-2d), when P mass in wood was estimated on the assumption that P was contained only in sapwood (i.e. lower bound).
The relative allocation of P to leaves tended to be greater in the ultrabasic
(P-poor soils) than in the sedimentary sites (P-rich soils) at the same altitudes (Fig.
5-3a), whereas that to wood tended to be smaller in the ultrabasic sites (Fig. 5-3b).
There was no correlation of the relative allocation of P with altitude for both leaves and wood (Figs. 5-3a and b). On the other hand, the relative allocation of P to leaves increased with the decline in the concentration of soluble soil P (Fig. 5-3c), while that of P to wood decreased (Fig. 5-3d).
The annual flux of P via litterfall
The annual flux of P via litterfall was 0.016–0.253, 0.003–0.141, 0.005–0.067,
0.001–0.057, and 0.001–0.019 g m-2 yr-1, for leaves, reproductive organs, branches/bark, woody stem (upper bound) and wood (lower bound), respectively
(Figs. 5-4a and c). The P flux tended to be smaller at higher altitudes, and also smaller in the ultrabasic (P-poor soils) than in sedimentary sites (P-rich soils) at the same altitudes (Figs. 5-4a and c). Their fractions were 45.5–71.3, 10.9–34.0, 12.2–
33.3, and 2.9–12.8%, for leaves, reproductive organs, branches/bark, and woody stem, respectively, based on the assumption that P concentration in wood was constant from the sapwood to heartwood area across a stem section (i.e. upper bound) (Fig. 5-4b). Their fractions were 46.8–72.4, 11.2–35.0, 12.4–33.7, and 1.3–
116
4.6%, for leaves, reproductive organs, branches/bark, and woody stem, respectively, based on the assumption that P was contained only in sapwood (i.e. lower bound).
(Fig. 5-4d).
The residence time of P in AGB
The residence time of P in AGB ranged from 2.2–10.3 yr (Figs. 5-5a and d). The residence time of P in AGB did not significantly correlate with altitude (Fig. 5-5a) or the concentration of soluble soil P (Fig. 5-5d).
The residence time of P in AGB was 1.4–7.9 yr when P was not assumed to be resorbed from senescing leaves (Figs. 5-5b and e). The P residence time (without
P resorption) tended to be shorter on the ultrabasic (P-poor soils) than the sedimentary sites (P-rich soils) at the same altitudes. There was no correlation between the P residence time (without P resorption) and altitude (Fig. 5-5b) or the concentration of soluble soil P (Fig. 5-5e).
The actual P residence time was 1.2–2.0 times longer than the P residence time without P resorption (Figs. 5-5c and f). The effect of P resorption was greater in the ultrabasic (P-poor soils) than in the sedimentary sites (P-rich soils) at the same altitudes (Fig. 5-5c), and tended to increase with the decrease of the concentration of soluble soil P (Fig. 5-5f). There was no correlation between the effect of P resorption and altitude (Fig. 5-5c).
The turnover time of AGB
The turnover time of AGB ranged from 16.9–39.5 yr (Table 5-1). These values were four-fold or more greater than the residence time of P in AGB. The turnover time of AGB was not significantly correlated with altitude or the concentration of soluble
117 soil P (P > 0.05, data not shown).
5.4. Discussion
The residence time of P in AGB was much shorter (2.2–10.3 yr) than the turnover time of AGB (16.9–39.5 yr; Kitayama & Aiba 2002) and did not monotonously increase with decreasing soil P availability. This suggests that the residence time of
P is influenced by P allocation among tree organs. As I expected, the relative allocation of P to leaves (9.5–48.0%) was seven-fold greater than the ratio of leaf biomass to total biomass (1.0–4.6%; Kitayama & Aiba 2002), which led to a large annual loss of P via leaf litterfall (Figs. 5-4 a and c) in association with short leaf- life spans (ca. 1.0 yr, Aiba unpublished data). Such a greater allocation ratio of P to leaves compared with biomass ratio was found across many forest biomes; e.g.
Amazonian tropical rainforests (Johnson et al. 2001; Feldpausch et al. 2004),
Catalan forests including semi-arid Mediterranean, wet Mediterranean, Atlantic temperate, and alpine forests (Sardans & Peñuelas 2013), and a lowland Bornean tropical rainforest (Imai et al. 2010).
The relative allocation of P to leaves increased with decreasing soil P availability (Fig. 5-2c), in line with previous studies (Gleason et al. 2009; Aoyagi
& Kitayama 2016). The increased P allocation to leaves potentially shortens the residence time of P in AGB and sacrifices PUE (productivity per unit P absorbed).
This is contradictory to the suggestion that a rather longer P residence enhances
PUE under P deficiency (Hidaka 2011). However, the actual residence time of P in
AGB did not become shorter with decreasing soil P availability (Figs. 5-4a). The actual residence time was increased by P resorption by ca. 20 to 100%, and the effect of P resorption increased with decreasing soil P availability (Fig. 5-5g); this
118 is because PRE significantly increased with decreasing soil P availability (Fig. 5-
S1). Therefore, my hypothesis was accepted. In contrast, the effect of P resorption on the P residence time was not significantly correlated with altitude (Fig. 5-5c).
Therefore, the residence time of P in AGB was linked with P availability rather than altitude.
Why does P resorption from senescing leaves have such a strong effect on the residence time of P in AGB? This is due to the large annual flux of P via leaf litter, which accounted for >50% of the total P flux (Figs. 5-4b and d). 25–60% of the P in fresh leaves was resorbed before leaf abscission, which reduced total annual
P by 26–66% (data not shown). P deficiency is expected to increase tree mortality and, if so, P deficiency must have been evolutionarily a selection factor. Fine-tuning between P allocation to and P resorption from leaves, which I demonstrated among tropical trees, must be a consequence of evolutional adaptation to P deficiency.
Further studies are required for understanding the residence time of P in tropical rainforest biomass, because it may be influenced by many other factors, such as herbivory, P allocation to belowground biomass, and other environmental factors (Suzuki et al. 2012; Metcalfe et al. 2014; Poorter et al. 2012). The annual loss of P via herbivory may account for >10% of the annual flux of P via leaf litterfall (Metcalfe et al. 2014). Furthermore, up to 5.0–39.6% of P mass in the entire tree biomass can be allocated to fine roots (Tsujii, Aiba, Okada, and Kitayama unpublished data), which may influence the residence time of P in whole tree biomass.
5.5. Conclusion
This study highlighted the significance of the P allocation to and the resorption from
119 leaves to determine the residence time of P in tree biomass, and their influences on
P cycling in forest ecosystems. Allocation ratio of P to leaves increased with increasing P deficiency, which must be adaptive to enhance instantaneous photosynthetic rate per tree under P deficiency. However, increased allocation to leaves shortened the residence time of P in tree biomass through a faster rate of P loss via litterfall. Against this effect, trees under severer P deficiency resorbed more
P from senescing leaves, and this effect increased the residence time by ca. 20 to
100%. These results suggest that the residence time of P in tree biomass is evolutionarily determined as the balance of P allocation and P resorption, which ultimately governs the cycling rate of P in tropical rainforest ecosystems.
120
Table 5-1. Description of eight study sites on Mount Kinabalu, Borneo. Canopy height represents the maximum height of a tree at the site (cited from Kitayama & Aiba 2002). Total soil P represents mean content of total soil P per site (30 cm depth in a topsoil) (cited from Kitayama et al. 2000). Soluble soil P represents mean concentration per site of soluble soil P, extracted with hydrochloric-ammonium fluoride solution (15 cm depth in a topsoil) (cited from Kitayama & Aiba 2002). P-use efficiency (PUE) is calculated as the inverse of P concentration in litter collected during 10 years from 1996 to 2006 (cited from Kitayama et al. 2015). Mean annual air temperature and precipitation were cited from Kitayama & Aiba (2002). The turnover time of tree aboveground biomass (AGB) was calculated using the data in Kitayama & Aiba (2002).
Site name 700S 1700S 2700S 3100S 700U 1700U 2700U 3100U Rock substrate Sedimentary Sedimentary Sedimentary Granite Ultrabasic Ultrabasic Ultrabasic Ultrabasic Altitude (m) 650 1560 2590 3080 700 1860 2700 3050 Canopy height (m) 46.8 30 20.6 15 65.4 22.6 14.2 6.1 Mean annual air temperature (°C) 23.8 18.7 13.1 10.4 23.5 17.1 12.5 10.6 Mean annual precipitation (mm yr-1) 2509 2714 2085 3285 2509 2714 2085 3285 Total soil P (g m-2) 61.36 34.87 72.57 37.15 29.19 8.97 21.47 12.02 Soluble soil P (g m-2) 0.18 0.14 0.36 0.35 0.14 0.04 0.09 0.07 PUE (g g-1) 2195 3025 2230 2478 2266 5159 4785 6326 The turnover time of AGB (yr) 22.8 24.1 39.5 26.3 32.3 29.3 16.8 18.6 Hill Lower Upper Hill Lower Upper Subalpine Subalpine Forest type dipterocarp montane montane dipterocarp montane montane forest forest forest forest forest forest forest forest
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Figure 5-1. Relationships of community-weighted mean (CWM) P concentration in leaves or wood with altitude (a and b) or the concentration of soluble soil P (c and d), for eight tropical rainforests on Mount Kinabalu, Borneo. Filled and open circles represent sedimentary and ultrabasic sites, respectively. A solid line denotes a significant correlation (P < 0.05).
122
Figure 5-2. P mass in leaves and wood (a and c) and their relative allocation (b and d) for the aboveground biomass of eight tropical rainforests on Mount Kinabalu,
Borneo. P mass in wood on panels (a) and (b) represent the upper bound values estimated on the assumption that P concentration in wood was constant from the sapwood to heartwood area across a stem section. In contrast, P mass in wood on panels (c) and (d) represent the lower bound values estimated on the assumption that P was contained only in sapwood.
123
Figure 5-3. Relationships of the relative allocation of P to leaves or wood with altitude (a and b) or the concentration of soluble soil P (c and d), for eight tropical rainforests on Mount Kinabalu, Borneo. Bars represent the intervals between the upper and lower bound values at each site. The upper bound of the relative allocation of P to leaves (or the lower bound of that to wood) was estimated on the assumption that P was contained only in sapwood. The lower bound of the relative allocation of P to leaves (or the lower bound of that to wood) was estimated on the assumption that P concentration in wood was constant from the sapwood to heartwood area across a stem section. Black and grey bars represent sedimentary and ultrabasic sites, respectively.
124
Figure 5-4. The annual flux of P (a and c) by litter component, and their relative proportion (b and d) for eight tropical rainforests on Mount Kinabalu, Borneo. The annual flux of P via coarse litterfall (i.e. fallen stem wood) on panels (a) and (b) represent the upper bound values estimated on the assumption that P concentration in wood was constant from the sapwood to heartwood area across a stem section.
The annual flux of P via coarse litterfall on panels (c) and (d) represent the lower bound values estimated on the assumption that the P in wood was contained only in sapwood.
125
Figure 5-5. Relationships of the residence time of P in tree aboveground biomass with altitude (a and b) or the concentration of soluble soil P (d and e). The residence time of P was estimated in two ways, one with and the other without P resorption. The relationships of the magnitude of the effect of P resorption from senescing leaves on the residence time of P with altitude (c) or the concentration of soluble soil P (f) for eight tropical rainforests on Mount Kinabalu, Borneo. The magnitude of the effect of P resorption from senescing leaves was evaluated as the actual P residence time divided by the P residence time without P resorption. Bars represent the intervals between the upper and lower bound values at a site. The upper bound values were estimated on the assumption that P concentration in wood was constant from the sapwood to heartwood area across a stem section. The lower bound values were estimated on the assumption that P was contained only in sapwood. Black and grey bars represent sedimentary and ultrabasic sites, respectively.
126
Table 5-S1. The list of sampled species. RBA represents relative basal area of each species at a site. The sample size of leaves and wood was represented in the columns named leaf and wood, respectively. The RBA was cited from Aiba et al. (2002).
Site Species RBA (%) Leaf Wood
700S Castanopsis javanica 4.3 3 3
Cinnamomum parthenoxylon 2.4 3 3
Dialium indum 1.8 3 3
Ixonanthes reticulata 8 3 3
Litsea cf. brachystachya 2.8 3 3
Magnolia dolichogyne 2.2 3 3
Norrisia major 3.5 3 3
Payena microphylla 6.7 3 3
Sandoricum koetjape 3.1 3 3
Shorea argentifolia 6.4 3 3
Shorea hopeifolia 4.4 3 3
Shorea leprosula 7.3 3 3
Shorea parvistipulata 4.5 3 3
Syzygium fastigiatum 2 3 3
Tristaniopsis sp07S 3 3 3
Total RBA 62.4 62.4 32.8
700U Agathis borneensis 3.5 3 3
Aquillaria malaccensis 3.4 3 3
127
Coelostigia griffithii 2.9 3 3
Cyathocalyx magnificus 1.5 3 3
Dacryodes costata 4.2 3 3
Dysoxylum excelsum 2 3 3
Heritiera simplifolia 2.6 3 3
Koompassia malaccensis 2.2 3 3
Palaquium herveyi 2.3 3 3
Scaphium macropodum 2.5 3 3
Shorea gibbosa 1.9 3 3
Shorea laevis 30.5 3 3
Shorea parvistipulata 3.1 3 3
Syzygium cf. tawahense 1.9 3 3
Trigoniastrum hypoleum 1.3 3 3
Total RBA 65.8 65.8 43.2
1700S Dacrycarpus imbricatus 5.7 3 3
Dacrydium pectinatum 5.9 3 3
Lithocarpus clementianus 4.6 3 3
Payena microphylla 6.2 3 3
Phyllocladus hypophyllus 1.8 3 3
Schima wallichii 0.5 3 3
Syzygium chrysanthum 3.1 3 3
Syzygium napiforme 3.4 3 3
Syzygium pachysepalum 5 3 3
Tristaniopsis clementis 6.9 3 3
128
Tristaniopsis sp17S 4.3 3 3
Total RBA 60.3 40 45.1
1700U Agathis kinabaluensis 19.2 3 3
Syzygium subdecussata 2.1 3 3
Ilex oppositifolia 1.6 3 3
Lithocarpus rigidus 2.3 3 3
Podocarpus gibbsii 6.8 3 3
Quercus lowii 3.3 3 3
Schima brevifolia 1.2 3 3
Syzygium castaneum 2.1 3 3
Tristaniopsis kinabaluensis 31.4 3 3
Weinmania cf. blumei 3.9 3 3
Xanthophyllum tenue 6.9 3 3
Total RBA 84.8 80.8 80.8
2700S Syzygium punctilimba 40.7 3 3
Ilex zygophylla 8.2 3 3
Lithocarpus havilandii 8.2 3 3
Magnolia carsonii 18.3 3 3
Olea decussata 9.1 3 3
Phyllocladus hypophyllus 7.9 3 3
Total RBA 92.4 92.4 92.4
2700U Dacrycarpus kinabaluensis 19.1 3 3
129
Dacrydium gibbsiae 32.5 3 3
Eugenia steenisii 4.6 3 3
Ilex zygophylla 0.5 3 3
Leptospermum recurvum 21.6 3 3
Polyosma hookeri 2.8 3 3
Schima brevifolia 7.2 3 3
Tristaniopsis sp27U 6.8 3 3
Total RBA 94.6 85.5
3100S Dacrycarpus kinabaluensis 36.3 3 3
Eugenia houttuynii 10.4 3 3
Eugenia kinabaluensis 6.8 3 3
Ilex zygophylla 5.9 3 3
Leptospermum recurvum 6.9 3 3
Schima brevifolia 10 3 3
Total RBA 76.3 76.3 76.3
3100U Dacrycarpus kinabaluensis 7.5 3 3
Dacrydium gibbsiae 1.7 3 3
Leptospermum recurvum 89.4 3 3
Phyllocladus hypophyllus 1.3 3 3
Total RBA 99.9 99.9 99.9
130
Figure 5-S1. The relationship of P resorption efficiency (PRE, the percentage of P resorbed from senescing leaves before abscission per total P in green leaves) with the concentration of soluble soil P, for eight tropical rainforests on Mount Kinabalu,
Borneo. Filled and open circles represent sedimentary and ultrabasic sites, respectively. A chain line denotes a significant correlation (P < 0.05). PRE was calculated as the following equation: PRE (%) = {1 – (P concentration in leaf litter/P concentration in green leaves)} * 100 (%).
131
Chapter 6. General discussion
Forest retrogression often occurs at the terminal stage with highly weathered soils during a long soil chronosequence across the boreal, temperate, and subtropical zones; the retrogression (the decline of biomass) is hypothesized to occur due to phosphorus (P) deficiency (Wardle et al. 2004; Peltzer et al. 2010). However, contrary to this hypothesis, Bornean tropical rainforests maintain large biomass on highly weathered soils that contain little bioavailable P (Kitayama et al. 2000;
Kitayama 2005). The maintenance mechanism of biomass on such weathered soils with little bioavailable P is an enigma in ecosystem ecology. This enigma was investigated from viewpoints of the productivity and reproduction of trees.
The novelty of this thesis is the focus on the reproduction of trees. The reproductive strategy of trees may have large influences on the dynamics of P in
Bornean tropical rainforests, where trees allocate a substantial amount of P to reproduction (Ichie et al. 2005; Ichie & Nakagawa 2013; Kitayama et al. 2015).
Nevertheless, the influences of the reproduction of Bornean rainforest trees on the
P dynamics have not been studied well, because the reproduction is often episodic, known as general flowering/fruiting (Ashton et al. 1988; Sakai 2002; Cannon et al.
2007) and not easily observed. I conducted a continuous monitoring of tropical rainforests on Mount Kinabalu, Borneo, and addressed the following three questions: 1) how Bornean rainforest trees use P efficiently in production (Chapters
2 and 3), 2) how the trees use P efficiently in reproduction (Chapter 4), and 3) how these P-use strategies affect the dynamics of P in forest ecosystems (Chapter 5).
132
6.1. P-use strategies in production
To address the first question, I studied how Bornean rainforest trees on P-poor soils used P in production. Bornean rainforest trees on P-poor soils exhibit high P-use efficiency (PUE; net primary productivity per unit P absorbed from soils, Vitousek
1982), which is adaptive to maintain forest productivity under P deficiency
(Kitayama & Aiba 2002; Paoli et al. 2007; Hidaka 2011). The mechanisms underlying the high PUE were focused in Chapters 2 and 3. Although many studies had investigated the mechanism underlying the productivity of Bornean rainforest trees, there remained the following three untested hypotheses: 1) Bornean rainforest trees on P-poor soils allocate a relatively large fraction of P to photosynthesis by investing P to photosynthetic cells, which helps maintain rapid photosynthetic rates under P limitation (Shane et al. 2004; Lambers et al. 2015), 2) the trees on P-poor soils produce long-lived leaves with tough anatomical structures, including thick cuticles and epidermis (Cunningham et al. 1999), which elongate the residence time of P in leaves (Escudero et al. 1992), and 3) the trees on P-poor soils resorb more P from senescing leaves by degrading recalcitrant compounds compared with those on P-rich soils (implied by Hidaka & Kitayama 2011).
The first and second hypotheses were related to anatomical mechanisms and examined in Chapter 2. Bornean rainforest trees on P-poor soils were known to allocate a relatively greater fraction of leaf P to the compounds related to photosynthetic activities, such as ATP and sugar-phosphates (Hidaka & Kitayama
2011, 2013). If so, leaf P may be localized to photosynthetic cells in occurrence on a leaf cross section (Shane et al. 2004; Lambers et al. 2015) (the first hypothesis).
The spatial distribution of P on the cross-section of leaf lamina was examined for
13 Bornean rainforest tree species on P-poor soils, and the localization of P to
133 photosynthetic palisade mesophyll cells was found across most of the species.
Therefore, the first hypothesis was accepted. The localization of P to photosynthetic cells may contribute to high PUE by enhancing photosynthetic rate per unit leaf P
(Shane et al. 2004; Lambers et al. 2015). Indeed, the leaves of the studied species exhibited relatively rapid photosynthetic rates (Hidaka & Kitayama 2013) despite their lower P concentration than those of global average (Reich & Oleksyn 2004;
Wright et al. 2004). Furthermore, the leaves of those species demonstrated developed epidermal structures, including thick and/or multi-layered epidermis with thick cuticles. The leaf physical strength (force to punch; the maximum punch force divided by the circumference of the punch rod, Onoda et al. 2011) of the species was on average greater than that of global average (Onoda et al. 2011)
(Tsujii, Onoda & Kitayama unpublished data). These results suggested that the studied species had high leaf physical strength with developed epidermal structures.
This high leaf physical strength may support a longer leaf life span (Onoda et al.
2011, 2012, 2015; Wright et al. 2002) and consequently greater PUE (Escudero et al. 1992). My results supported the second hypothesis
In relation to the third hypothesis, Bornean rainforest trees on P-poor soils were known to exhibit an extremely high P resorption efficiency (PRE, the percentage of P resorbed from senescing leaves before abscission per total P in green leaves) (Hidaka & Kitayama 2011). This high PRE in effect elongates the residence time of P in tree biomass, which may closely relate to high PUE (Paoli et al. 2005; Kazakou et al. 2007; Hidaka 2011). The biochemical mechanism underlying the high PRE was investigated by focusing on different degradability among P-containing compounds in leaves in Chapter 3. P concentration in easily soluble, nucleic acid, lipid and residual fractions was determined for the green and
134 senescent leaves of 22 Bornean rainforest tree species from three sites with different
P availability, and the rate of P resorption from each of the P fractions was determined. The species with a low PRE resorbed more P from the lipid and nucleic acid fractions and less from the residual fraction that contained chemically recalcitrant compounds. In contrast, those with high PRE resorbed much P from the residual fraction as well as the lipid and nucleic acid fractions. Bornean rainforest trees with a high PRE on P-poor soils exhibited a high degradation capacity of the recalcitrant compounds. Therefore, the hypothesis 3 was accepted.
Several mechanisms underlying high PUE were elucidated for Bornean rainforest trees in this thesis and previous studies (Hidaka & Kitayama 2011, 2013).
These mechanisms are found also in the tree species of other regions, such as
Australian and African Proteaceae (Shane et al. 2004, 2014; Hawkins et al. 2008;
Lambers et al. 2015), Hawaiian Metrosideros polymorpha (Myrtaceae) (Cordell et al. 2002; Vitousek 2004; Ostertag 2010), and others (e.g. Cunningham et al. 1999;
Wright & Westoby 2003; Mayor et al. 2014; Mao et al. 2015; Zalamea et al. 2016).
This suggests the evolutionary convergence of the leaf traits of trees to P deficiency or similar physiological responses to P deficiency among evolutionally unrelated lineages.
6.2. P-use strategies in reproduction
In Chapter 4, I explored the second question: how do Bornean rainforest trees use
P efficiently in reproduction? Bornean rainforest trees maintain reproductive activities, which require a large amount of P, even on P-poor soils (Kitayama et al.
2015). One possible mechanism for the maintenance of massive (but episodic) reproduction was the dilution of P concentration in some of the reproductive organs
135 with increasing P deficiency (Kitayama et al. 2015). Based on Kitayama et al.
(2015), I raised the following two hypotheses: 4) Bornean rainforest trees on P- poorer soils exhibit a decreased P investment to reproduction by the dilution of P concetration in such reproductive organs as pericarps, where reduced P may not cause a decline in fitness, and 5) species with capsulate fruits, which have a relatively low P concentration, increase in abundance with increasing P deficiency and this community response would reduce the overall P invested to reproductive organs per site. In relation to the hypothesis 4, P concentration in inflorescences and seeds would be maintained even on P-poor soils because reducing P in such organs would cause a lower fitness. These hypotheses were examined in eight tropical rainforests that differed in P availability on Mount Kinabalu, Borneo.
The former hypothesis (the hypothesis 4) pointed to different P demands among reproductive organs (i.e. inflorescences, seeds, and pericarps). Seeds may require much P for germination and seedling growth (Brookes et al. 1980; Milberg
& Lamont 1997; Lamont & Groom 2002; White & Veneklaas, 2012; Vandamme et al., 2016), while pericarps may not require P for progenies. Inflorescences may require much P for pollen and embryos (Ashman 1994b). Therefore, I hypothesized that Bornean rainforest trees on P-poorer soils would exhibit a lower P concentration in pericarps but not in inflorescences and seeds. However, contrary to this hypothesis, a greater number of trees showed a lower P concentration in inflorescences but not in pericarps. This suggested that the low concentration of P in inflorescences was adaptive to P deficiency. How Bornean rainforest trees maintain pollination and fertilization in the inflorescences that contain less P remains unclear.
The increase of capsulate species in abundance may reduce the overall
136 investment of P to reproduction per site, because the pericarps of capsulate fruits may contain less P than those of other fruit types, such as drupes and berries (the hypothesis 5). As I expected, the relative abundance of capsulate species (based on relative basal area per plot) increased with increasing P deficiency. Mean P concentration in the pericarp of capsulate fruits was significantly lower than that of other fruit types, such as drupes, and follicles. Therefore, the hypothesis 5 was accepted. I suggest that this phenomenon is unique to Bornean tropical rainforests, where β diversity of tree species is much higher than other regions (Kitayama 2012).
In contrast, in Hawaiian forest systems, a single species Metrosideros polymorpha predominates forests across sites with different P availabilities (Vitousek et al. 1988,
1992; Kitayama & Mueller-Dombois 1995; Kitayama et al. 1995; Cordell et al.
1998; Cornwell et al. 2007). This species produces capsulate fruits only, and the shift in the composition of fruit types does not occur.
6.3. The consequence of P-use strategies in production and reproduction in the
P dynamics in forest ecosystems
The third question was related to the consequences of PUE in ecosystem processes, i.e. how the increased P-use efficiencies in productivity and reproduction influenced the dynamics of P in forest ecosystems. I explored this question by focusing on the relationship between PRE and the residence time of P in tree aboveground biomass (AGB; including leaves and wood). The P bound in canopy leaves accounted for 9.5–48.0% of the whole P in tree biomass (i.e. leaves and wood) across my study forests (Chapter 5). Therefore, increased PRE in tree canopies will straightforwardly result in a longer P residence time.
The partition of P between leaves and wood is a key factor to determine the
137 residence time of P. A greater allocation ratio of P to leaves combined with a greater
PRE from the leaves will contribute to increasing the residence time of P when other parameters are constant. Interestingly, the allocation ratio of P to leaves may increase with increasing P deficiency (Gleason et al. 2009; Aoyagi & Kitayama
2016), because it is adaptive to P deficiency and helps maintain tree productivity on P-poor soils (Aoyagi & Kitayama 2016). Furthermore, PRE of Bornean rainforest trees is greater on P-poorer soils (Hidaka & Kitayama 2011). Therefore, the relative contribution of PRE to the residence time of P would increase with increasing P deficiency (hypothesis 6). This hypothesis was examined in eight tropical rainforests that differed in P availability on Mount Kinabalu, Borneo. P mass in AGB and the annual loss of P via litterfall (the sum of the litterfall of leaves, twigs, reproductive organs and woody stem) were estimated, and the residence time of P in AGB (P mass in AGB/annual P loss via litterfall) was calculated for the eight forests. The contribution of P resorption from senescing leaves to the residence time of P in AGB was evaluated by comparing with and without P resorption.
The residence time of P in AGB (2.2–10.3 yr) was six-fold shorter than the turnover time of AGB (19.7–60.2 yr, AGB/annual litterfall mass). This was due to a greater allocation ratio of P to leaves (9.5–48.0%), which had a small fraction of biomass (1.0–4.6%) and a fast turnover. Therefore, the rate of P loss via litterfall was faster than would be expected from that of biomass per se. The residence time of P in AGB was elongated by P resorption by 20–100%, and the magnitude of the elongation increased with increasing PUE. Both greater P resorption per se and greater P allocation to leaves are involved in the higher PRE under severer P deficiency. Therefore, my hypothesis was accepted. Why P resorption from senescing leaves had a strong effect on the P residence time is an intriguing question.
138
This was presumably due to the large annual flux of P via leaf litterfall, which accounted for >50% of the total annual P flux including wood. Similarly, the P in reproductive-organ litter accounted for a considerable percentage of the total annual
P flux. These results suggested a large influence of the P-use strategies of trees in productivity and reproduction on the dynamics of P in Bornean tropical rainforest ecosystems.
6.4. Implication into P cycling in terrestrial ecosystems
This thesis provides two important implications into the cycling of P in terrestrial ecosystems. The first is for the asymmetry of the turnover rates of P and biomass in vegetation. The residence time of P in AGB (2.2–10.3 yr, P mass in AGB/annual P loss via litterfall) was six-fold shorter than the turnover time of AGB per se (16.9–
39.5 yr, AGB/annual litterfall mass) for Bornean rainforest trees (Chapter 5). In contrast, in herbaceous vegetation, the P residence time may be longer than the turnover time of biomass. Hirose (1971) estimated the turnover rate of nitrogen (N)
(the inverse of the residence time of N) in plant biomass for Solidago altissima
(Asteraceae), which is a perennial herbaceous species on the flood plain in Japan.
In the Solidago altissima vegetation, the residence time of N was longer that the turnover time of biomass (ca. 0.49–1.08 and 0.18–0.85 yr, for N and biomass, respectively; calculated using the data in Hirose 1971). N was resorbed from standing biomass before abscission and stored in roots during winter while biomass was lost as standing litter (Hirose 1971). The same pattern must apply to the case of P in herbaceous species. However, P had a shorter residence time than biomass in tropical rainforests; the longer P residence time than biomass is characterized by the allocation of P between short-lived leaves and long-standing woody organs.
139
Another implication is for the chemical composition of P in plant tissues.
This thesis showed that the chemical composition of P in leaves changed during senescence through P resorption processes (Chapter 3). This change may influence the cycling of P in forest ecosystems by affecting the subsequent P-acquisition strategies of plants and microbes (e.g. Turner 2008; Ceulemans et al. 2017; Nasto et al. 2017; Yokoyama et al. 2017). However, most studies so far have focused on the concentration of bulk P in plant tissues only, and hence the influence of the chemical composition of P on the cycling of P in ecosystems remains unknown. The investigation on the ecosystem consequences of the changes of chemical composition in litter is required for better understanding of the cycling of P in terrestrial ecosystems.
6.5. Conclusion
Bornean tropical rainforests maintain large biomass even on P-poor soils (Kitayama et al. 2000; Kitayama 2005), whereas forest retrogression occurs during a long soil chronosequences due to P deficiency on highly weathered soils across the boreal, temperate, and subtropical zones (Wardle et al. 2004; Peltzer et al. 2010). I demonstrated that the maintenance of Bornean tropical rainforests on P-poor soils could be explained by high P-use efficiencies in both productivity and reproduction.
These mechanisms were closely linked with the shift in the composition of tree species along the gradient of P availability, thus suggesting the importance of high tree species diversity in the maintenance of Bornean tropical rainforests. Most importantly, this thesis quantitatively showed that P resorption from senescing leaves exerted disproportionately large influences on the residence time of P in tree biomass. These results suggest that the P-use strategies in production and
140 reproduction are key factors to govern biochemical cycling in Bornean tropical rainforest ecosystems.
141
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