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\begin{document}

\title{Phenology of tropical lower montane forests in southern highlands of
Vietnam: leafing is associated with precipitation but flowering is not}



\author[1]{Ai Nagahama}%
\author[2]{Shuichiro Tagane}%
\author[3]{Nguyen Ngoc}%
\author[3]{Hoang Binh}%
\author[4]{Truong Cuong}%
\author[5]{Kojin Tsuchiya}%
\author[6]{Meng Zhang}%
\author[6]{Etsuko Moritsuka}%
\author[7]{Hironori Toyama}%
\author[8]{Hidetoshi Nagamasu}%
\author[9]{Akiyo Naiki}%
\author[10]{Shumpei Kitamura}%
\author[6]{Tetsukazu Yahara}%
\affil[1]{National Museum of Nature and Science}%
\affil[2]{Kagoshima University}%
\affil[3]{University of DaLat}%
\affil[4]{Bidoup-Nui Ba National Park}%
\affil[5]{The University of Tokyo}%
\affil[6]{Kyushu University}%
\affil[7]{National Institute for Environmental Studies}%
\affil[8]{Kyoto University}%
\affil[9]{University of the Ryukyus}%
\affil[10]{Ishikawa Prefectural University}%


\vspace{-1em}



  
  \date{June 17, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
The premise of the study Though phenological studies in montane forests
are important, particularly in tropical Asia where primitive angiosperms
are found, the phenology in these forests is still poorly understood. To
characterize the phenological patterns and reveal the relationships
between meteorological factors and phenology, we observed the leafing,
flowering, and fruiting phenology in the tropical montane forests of
Vietnam. Methods We observed the leafing, flowering, and fruiting
phenology of 91 species every three months in five plots (elev.
1460--1920 m) in Bidoup-Nui Ba National Park, Vietnam, and analyzed how
the number of species that were leafing, flowering, or fruiting varied
in relation to precipitation, temperature, or daylength. Key results The
leafing phenology showed a peak at the beginning of the wet season
(April) and was significantly influenced by all of day length,
precipitation, and temperature. The flowering phenology did not show any
distinct peaks and was influenced by day length and precipitation. The
fruiting phenology showed a low peak from the wet season (July) to the
beginning of the dry season (December) and was not significantly
influenced by any of the meteorological factors. Main conclusion The
community-wide phenological patterns of leafing, flowering, and fruiting
in the tropical montane forest of Bidoup-Nui Ba are unique among the
tropical forests of East and Southeast Asia. In particular, our
observation suggests that masting in tropical montane forests may be an
ancestral state of both general flowering in tropical rainforests and
masting found in temperate forests in East and Southeast Asia.%
\end{abstract}%



\sloppy


\textbf{The article category} : Original Article

\textbf{Title:} Phenology of tropical lower montane forests in southern
highlands of Vietnam: leafing is associated with precipitation but
flowering is not.

\textbf{Authors:} Ai Nagahama\textsuperscript{1, *}, Shuichiro
Tagane\textsuperscript{2}, Nguyen Van Ngoc\textsuperscript{3}, Hoang Thi
Binh\textsuperscript{3}, Truong Quang Cuong\textsuperscript{4}, Kojin
Tsuchiya\textsuperscript{5}, Meng Zhang\textsuperscript{6}, Etsuko
Moritsuka\textsuperscript{7}, Hironori Toyama\textsuperscript{8},
Hidetoshi Nagamasu\textsuperscript{9}, Akiyo Naiki\textsuperscript{10},
Shumpei Kitamura\textsuperscript{11}, Tetsukazu
Yahara\textsuperscript{6, 12}.

\textsuperscript{1}Department of Botany, National Museum of Nature and
Science, 4--1--1 Amakubo, Tsukuba, Ibaraki 305--0005, Japan.

\textsuperscript{2}The Kagoshima University Museum, Kagoshima
University, 1-21-30 Korimoto, Kagoshima, 890-0065, Japan.

\textsuperscript{3}Dalat University, 01 Phu Dong Thien Vuong, Dalat
City, Lam Dong, Vietnam. \textsuperscript{4}Bidoup-Nui Ba National Park,
Lam Dong, Vietnam.

\textsuperscript{5}Atmosphere and Ocean Research Institute, The
University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8564, Japan.

\textsuperscript{6}Department of Biology, Kyushu University. 744
Motooka, Fukuoka, 819- 0395, Japan.

\textsuperscript{7}Department of Environmental Changes, Faculty of
Social and Cultural Studies, Kyushu University. 744 Motooka, Fukuoka,
819- 0395, Japan.

\textsuperscript{8}Biodiversity Division, National Institute for
Environmental Studies, Tsukuba, Ibaraki 305-8506, Japan.

\textsuperscript{9}The Kyoto University Museum, Kyoto University,
Yoshida Honmachi, Sakyo-Ku, Kyoto, 606-8501, Japan.

\textsuperscript{10}Iriomote Station, Tropical Biosphere Research
Center, University of the Ryukyus, 870 Uehara, Taketomi-Cho,
Yaeyama-gun, Okinawa, 907-1541, Japan.

\textsuperscript{11} Ishikawa Prefectural University, 1-308, Suematsu,
Nonoichi, Ishikawa, 921-8836, Japan.

\textsuperscript{12} Kyushu Open University, 744 Motooka, Fukuoka, 819-
0395, Japan.

*Corresponding author: anagahama@kahaku.go.jp

\emph{The premise of the study}

Though phenological studies in montane forests are important,
particularly in tropical Asia where primitive angiosperms are found, the
phenology in these forests is still poorly understood. To characterize
the phenological patterns and reveal the relationships between
meteorological factors and phenology, we observed the leafing,
flowering, and fruiting phenology in the tropical lower montane forests
of Vietnam.

\emph{Methods}

We observed the leafing, flowering, and fruiting phenology of 91 species
every three months in five plots (elev. 1460--1920 m) in Bidoup-Nui Ba
National Park, Vietnam, and analyzed how the number of species that were
leafing, flowering, or fruiting varied in relation to precipitation,
temperature, or daylength.

\emph{Key results}

The leafing phenology showed a peak at the beginning of the wet season
(April) and was significantly influenced by all of day length,
precipitation, and temperature. The flowering phenology did not show any
distinct peaks and was influenced by day length and precipitation. The
fruiting phenology showed a low peak from the wet season (July) to the
beginning of the dry season (December) and was not significantly
influenced by any of the meteorological factors.

\emph{Main conclusion}

The community-wide phenological patterns of leafing, flowering, and
fruiting in the tropical lower montane forest of Bidoup-Nui Ba are
unique among the tropical forests of East and Southeast Asia. In
particular, our observation suggests that masting in tropical lower
montane forests may be an ancestral state of both general flowering in
tropical rainforests and masting found in temperate forests in East and
Southeast Asia.

\textbf{Keywords} (up to 5)\textbf{:}

Bidoup-Nui Ba National Park, community-wide phenology, fruiting
phenology, precipitation, Southeast Asia.

\emph{}

\textbf{Introduction}

In East and Southeast Asia, lowland and montane vegetation consist of
various forest types. Lowland vegetation includes temperate forests,
tropical seasonal forests, and tropical rain forests, among others.
Montane vegetation, on the other hand, is comprised of tropical lower
montane forests, higher montane forests, subalpine forests, and alpine
forests (Corlett, 2007). Each of these forests displays specific
phenological patterns (Kira, 1991). In temperate forests, environmental
factors such as day length, temperature, and precipitation change
predictably throughout the year, providing reliable signals for plants
to sense seasonal progress (Borchert et al., 2005; Lechowicz, 1984;
Rathcke \& Lacey, 1985; Sakai \& Kitajima, 2019). As a result, plants in
temperate forests typically grow new leaves in spring, flower from
spring to summer, and produce fruit mainly in autumn (Zhang et al.,
2007; Edwards et al., 2017; Nagahama \& Yahara, 2019). In a similar
manner, tropical seasonal forests experience predictable changes in
precipitation throughout the year, resulting in wet and dry seasons.
Plants are able to monitor these changes in water availability to
determine the progression of the seasons (Rathcke \& Lacey, 1985).
Consequently, in tropical seasonal forests, many plants have a peak of
leafing in either wet or dry season depending on the accessibility to
deeper water (Wright \& van Schaik, 1994), a peak of flowering at the
end of the dry season, and a peak of fruiting early in the wet season
(Kurten et al., 2018). In contrast, in tropical rain forests, annual
fluctuations in temperature and precipitation are much lower and more
unpredictable than in temperate or tropical seasonal forests.
Consequently, species in the tropical rainforests have low intensity
blooms throughout the year or experience high intensity blooms only in
years with exceptionally low rainfall and low temperatures (Sakai et
al., 1999; Ichie et al., 2004; Nakagawa et al., 2019). This phenomenon
is referred to as supra-annual flowering or general flowering (Sakai,
2002). Notably, species common to the tropical seasonal and rain forests
usually bloom every year in the former but every few years in the latter
(Kurten et al., 2018).

These generalizations about the phenology of tropical forests are based
on observations made in lowland forests, which have been the focus of
most previous studies. The phenology of tropical montane forests, found
at elevations above 1000 m and having a different species composition
from lowland forests (Kira, 1991), remains poorly understood in Asia.
Although the transition from lowland to lower montane forest in
Southeast Asia has a width of around 750--1200 m and altitude varies
depending on the location (Ashton, 2014), phenological studies of
tropical montane forests are of particular importance in Asia. Many
primitive angiosperms can be found in these forests (Axelrod, 1966;
Morley, 2001, 2018; Ohtani et al., 2021), and understanding their
phenological patterns may provide insight into the ancestral
phenological states of Asian forests.

According to Axelrod (1966), angiosperms evolved in tropical mountains
during the Cretaceous period. As they expanded their distribution after
the Cretaceous, deciduousness evolved as an adaptation to dry climates
in the northern hemisphere, while evergreenness was maintained as an
adaptation to climates without dry season in the southern hemisphere.
Based on this hypothesis, the phenology of species growing in Southeast
Asian tropical montane forests is considered ancestral in angiosperms.
Thus, understanding the relationship between phenology and
meteorological factors in these will help reconstruct the history of
phenological divergence from tropical montane forests to tropical
lowland and temperate forests.

The relationship between phenology and meteorological factors in the
tropical montane forests of Southeast Asia has been well-studied in Mt.
Kinabalu, Malaysia, with observations limited to eight species
of\emph{Medinilla} (Melastomataceae) by Nomura et al. (2003) for leafing
and Kimura et al. (2009) for flowering and fruiting phenology. The
average annual temperature at 1560 m in Mt. Kinabalu is 18.9 \selectlanguage{ngerman}ºC, and the
average annual precipitation is 2714 mm. However, the precipitation
decreases significantly during El Niño events. The average monthly
temperature ranges from 16.5 ºC (January) to 19.5 ºC (September), and
the average monthly precipitation changes from 100 mm (June) to 550 mm
(November). Precipitation changes have a negative correlation with solar
radiation.

The study of leafing phenology by Nomura et al. (2003) showed that tree
species in lower mountain forests (elev. 1560 m) developed new leaves
after the El Niño -caused dry period, while those in upper mountain
forests (elev. 2590 m) developed new leaves during and after the dry
period. However, tree species in the subalpine zone (elev. 3081 m) had
continuous leaf development. This indicates that meteorological factors
affecting leaf phenology varied with elevation. The other study of
flowering and fruiting phenology by Kimura et al. (2009) at elevations
1600--1800 m showed that flowering occurred twice a year in June (when
temperature rises) and January (when temperature fall) and was
correlated only with temperature. Fruiting, however, occurred once a
year for most species and was correlated with both temperature and solar
radiation. It remains uncertain whether these patterns are prevalent
among other native plant groups to Mt. Kinabalu.

Although Nomura et al. (2003) and Kimura et al. (2009) provide valuable
data on the phenology of Asian tropical mountain forests, it is
challenging to generalize their findings to all Southeast Asian montane
forests. This is due to the varying climate conditions in Southeast
Asia. For example, precipitation, which is often used as a cue for
phenological changes, shows distinct annual changes in Mainland
Southeast Asia, but indistinct changes in Mt. Kinabalu, resulting in
different relationships between meteorological factors and phenology
(Kumagai et al., 2005). Thus, the relationship between meteorological
factors and phenology in Southeast Asian mainland lower montane forests
may differ from that in Mt. Kinabalu.

In this study, we observed the phenology of leafing, flowering, and
fruiting every three months in five plots located in the lower montane
forests (1460--920 m) of Bidoup-Nui Ba National Park, Vietnam, in
Mainland Southeast Asia. The monthly average temperature in Bidoup-Nui
Ba National Park changes by only 3.6°C per year, with an average annual
temperature of 18.7ºC. However, the average monthly precipitation varies
from 10 mm in January to 281 mm in September, with an average annual
precipitation of 1678 mm (Fick \& Hijmans, 2017). This results in a
distinction between the dry season from December to March and the rainy
season from April to November. The forest of Bidoup-Nui Ba National Park
is primarily composed of broad-leaved evergreen trees from families such
as Fagaceae and Lauraceae, with some deciduous tree species, such as
Acer spp. (Sapindaceae), also commonly found (Nagahama et al., 2019).

Our study aimed to answer the following three questions:

(1) What are the patterns of leafing, flowering, and fruiting in the
lower montane forests of Bidoup-Nui Ba National Park, Vietnam?

(2) Which meteorological factors are correlated with the patterns of
leafing, flowering, and fruiting patterns in lower montane forests
there?

(3) What are the differences in the patterns of leafing, flowering, and
fruiting between the lower mountain forests of Bidoup-Nui Ba National
Park and other parts of the Southeast Asian tropics?

\textbf{Methods}

\emph{Study site}

Leafing, flowering and fruiting phenology was observed in five plots
located along an elevation gradient from 1460 m to 1920 m in Bidoup-Nui
Ba National Park, located in Lam Dong Province, Central Highland of
Vietnam (Table 1; Fig. 1a). The monthly average temperature in this area
ranges from 16.7°C in January to 20.3°C in May (a difference of 3.6°C),
and monthly precipitation varies from 10 mm in January to 281 mm in
September (a difference of 271 mm; Fick \& Hijmans, 2017; Fig. 1c--e).
The wet season in this area occurrs from April to November, and the dry
season occurs from December to March.

\emph{Field observations}

Five plots for phenological observations were located at Giang Ly (GL),
Hon Giao (HG), Dung Iar Reing (DIG), Cong Troi (CT), and Langbian (LB;
Table 1; Fig. 1b). The size of plots varied from 1000
m\textsuperscript{2} (10 m x 100 m; HG) to 2500 m\textsuperscript{2} (50
m x 50 m; DIG). The distance between the westernmost plot (CT) and the
easternmost plot (HG) was 45 km. The elevations of five plots ranged
from 1460 m (GL) to 1920 m (LB). In June 2018, we recorded girth and
height for all trees and vine individuals 4 m or taller in each plot and
attached a number tag to the trunk of each individual. We distinguished
species in the field and collected a voucher specimen of each species
for identification and small pieces of leaves for DNA analysis. We
identified species based on morphology using taxonomic literature and
type specimen images (Nagahama et al., 2019). For Fagaceae and
Lauraceae, which have many similar species that are difficult to
distinguish in the fields, we collected a specimen for each tree. Based
on the number of individuals of each species, we selected around 20
dominant tree species in each plot, and for each of the selected
dominant species, we selected five individuals with larger girth for
phenological observations. Of the 100 species for which we recorded
phenological states, some species had only one or two individuals due to
misidentification in the first census in June 2018. We removed these
seven species from the following analysis.

We recorded phenological states as binary values: presence/absence of
new leaves, flowers, and fruits, and used these values as species
phenological states when at least one individual had them. We recorded
leafing, flowering, and fruiting events in a total of 91 species (17
spp. in CT, 18 spp. in DIG and HG plot, 19 spp. in LB and GL plots) in
the plots in June, September, and December of 2018, April, July, and
October of 2019, and January 2020 (only one individual was observed for
each species in June 2018). In some species, flowers and fruits were
rare and often found only in very large trees. For those species, we
also searched for flowering and fruiting trees around the plots and
recorded any observed flowering and fruiting events, which were then
included in our subsequent analyses.

\emph{Meteorological data collection}

Data of precipitation and temperature were obtained from the weather
database WorldClim (Fick \& Hijmans, 2017). Data of day length was
obtained the function 'daylength' from the R package 'geosphere'
(Hijmans et al., 2017).

\emph{Categorizing phenological patterns}

Considering sample size, data from five plots was pooled for the
following analyses. The proportions of leafing, flowering, and fruiting
species were calculated for 91 species observed in five plots using
Excel for Mac (16.16.12). Phenological variation of 91 species was
summarized by principal component analysis (PCA) and classified into by
clustering analysis, with presence/absence data of new leaves, flowers,
or fruits in seven observations. PCA was performed using the ``prcomp''
function in R (3.4.3; R core Team, 2017). Phenological similarity among
species was calculated through squared Euclidean distance using the
``dist'' function in R (3.4.3) and dendrograms were constructed using
the UPGMA method. Before performing PCA and clustering analysis, the
presence of large multicollinearity between the explanatory variables
was confirmed using the Variance Inflation Factor (VIF).

To verify the reliability of the UPGMA clustering results,
non-hierarchical clustering was performed to the same data set using the
Kmeans++ method. By comparing the results of UPGMA and Kmeans++, the
number of clusters was determined for leafing, flowering, and fruiting
phenology, respectively.

To assess whether the resulting clusters were unbiased towards any
particular phylogenetic groups, we examined the distribution of top five
families, Fagaceae (10 spp.), Symplocaceae (10 spp.), Lauraceae (9
spp.), Rosaceae (8 spp.), and Rubiaceae (8 spp.), on the dendrogram.

\emph{Relationship between phenology and meteorological factors}

We used Generalized Linear Models (GLMs) with logit link function and
binomial distribution of errors to investigate how the number of species
that have leafing, flowering, or fruiting aried with precipitation,
temperature, or daylength. The three meteorological factors were
strongly correlated with each other (Appendix S1). Therefore, we used
the following methods to summarize these correlated variations. First,
we performed PCA for six variables, including temperatures,
precipitations, and daylengths of current and previous months. We then
tested the relationship between phenology and meteorological factors
using GLMs with PC1 and PC2 as explanatory variables. Second, we
performed two regression analyses: one between day length and
precipitation, and another between day length and temperature. We
calculated residuals for each regression and tested the relationship
using GLMs with day length, residual precipitation, and residual
temperature as explanatory variables. All calculations were performed
using R (3.4.3).

\emph{Comparison of phenological patterns among forests in East and
Southeast Asia}

Based on previous studies, we compared phenological patterns of leafing,
flowering, and fruiting among nine well-studied locations of tropics,
seasonal tropics, subtropics, and temperate (Table 2). We conducted a
search for phenological studies in East and Southeast Asia using the
keywords ''leafing phenology'', ''flowering phenology'', and ''fruiting
phenology''. We selected areas where the visual observation of leafing,
flowering, and fruiting phenology was conducted in the field for at
least one year as well-studied areas for inclusion in our analysis. If
the monthly phenological intensity, such as the number or proportion of
flowering species, was not reported, the study was excluded from our
analysis. We averaged each phenological record into a twelve-months
record and calculated the proportions of leafing, flowering, and
fruiting species for each month (Appendix S2). To determine phenological
similarity between locations, we used the ``dist'' function in R (3.4.3)
to calculate squared Euclidean distance and constructed dendrograms
using the UPGMA method.

For the phenological data of Bidoup-Nui Ba, however, the observational
records were only available for seven months (excluding February, March,
May, August, and November). Thus, we constructed dendrograms: (1) using
21 proportion variables (3 phenological categories x 7 months) for nine
areas including Bidoup-Nui Ba, and (2) using 36 proportion variables (3
categories x 12 months) for eight areas excluding Bidoup-Nui Ba. We then
compared the topologies of those dendrograms. For the first data set, we
performed PCA to summarize 21 variables into fewer principal components,
and illustrated a biplot of PC1 and PC2 to interpret the result of the
above clustering.

In addition, we calculated meteorological similarity between locations
using monthly averages of day length (hours), temperature (ºC), and
precipitation (mm) for nine locations, and constructed a dendrogram
using the UPGMA method with squared Euclidean distance.

\textbf{Results}

\emph{Species composition}

In five plots, we recorded a total of 3,965 tree individuals belonging
to 60 families (Fig. 2). Fagaceae was the most abundant family (461
individuals; 11.6\%) followed by Lauraceae with 422 individuals
(10.6\%), Rubiaceae with 368 individuals (9.3\%), Symplocaceae with 325
individuals (8.2\%), and Rosaceae with 197 individuals (5.0\%). The
remaining 2,193 individuals (55.3 \%) belonged to the other 65 families
or unknown families. Fifteen families were represented by only one
individual.

Among the 19 dominant tree species in the LB plot (Appendix
S3),\emph{Claoxylon langbiangense} A.Nagah. \& Tagane (Euphorbiaceae;
Nagahama et al., 2021) was the most common (45 individuals; 11.3\%)
almost twice as abundant as the second most common species, \emph{Prunus
wallichii} Steud. (Rosaceae; 36 individuals; 9.0\%). In the CT
plot,\emph{Quercus bidoupensis} H.T.Binh \& Ngoc (Binh et al., 2018) was
the most common species (61 individuals; 10.4\%) nearly three times as
frequent as the second most common species, \emph{Melicope
pteleifolia}(Champ. ex Benth.) T. Hart. (Rutaceae; 22 individuals;
3.8\%). In the HG plot, two species of Rubiaceae, \emph{Diplospora} sp.
(121 individuals; 7.8\%) and \emph{Urophyllum bidoupense} Yooprasert,
Culham \& Utteridge (Yooprasert et al., 2022; 109 individuals; 7.1\%),
had over 100 individuals within a plot. In the DIG plot, \emph{Quercus}
sp. (Fagaceae) was the most common species (63 individuals; 7.6\%)
followed by \emph{Symplocos acuminata} (Blume) Miq. (Symplocaceae; 55
individuals; 6.6\%) and \emph{Litsea} sp. (Lauraceae; 41 individuals;
4.9\%). In GL plot, \emph{Adinandra donnaiensis} Gagnep. ex Kobuski
(Pentaphylacaceae) was the most common species (48 individuals; 7.9\%)
followed by \emph{Melicope pteleifolia} (Rutaceae; 46 individuals;
7.6\%) and \emph{Symplocos hayatae} K. Mori (Symplocaceae; 34
individuals; 5.6\%). Among monitored tree species, only four species
were deciduous species: \emph{Meliosma pinnata} (Roxb.) Maxim.
(Sabiaceae) in GL plot, and \emph{Acer erythranthum} Gagnep., \emph{A.
campbellii} subsp. \emph{flabellatum} (Rehder) A.E.Murray (Sapindaceae)
and \emph{Engelhardia serrata} Blume (Juglandaceae) in LB plot. The rest
were evergreen species.

\emph{Phenological pattern}

Among 91 monitored species, leafing, flowering, and fruiting events were
recorded for 91 spp. (100.0 \%), 65 spp. (71.4\%), and 54 spp. (59.3
\%), respectively. The number of leafing species varied seasonally by a
factor of 4.6, ranging from 20 spp. (22.0\%) in June to 91 spp. (100\%)
in April (Fig. 3a). The number of flowering species varied seasonally by
a factor of 2.2, ranging from 15 spp. (16.5\%) in September to 33 spp.
(36.3\%) in December (Fig. 3b). The number of fruiting species varied
seasonally by a factor of 2.3, from 12 spp. (13.2\%) in January to 27
spp. (29.7\%) in July (Fig. 3c).

The phenological variations of leafing, flowering, and fruiting events
were summarized into four principal components (Table 3; PC1 to PC4),
which explained 77.6\%, 77.8\%, and 80.2\% of the total variance of
leafing, flowering, and fruiting events, respectively. In leafing,
flowering, and fruiting data, all of the presence records in seven
observation months positively impacted PC1. However, presence records
had both positive and negative contributions to PC2, PC3, and PC4 (Table
3).

\emph{Leafing phenology}

In leafing phenology, the \selectlanguage{english}first, second, third, and fourth principal
components accounted for 27.5\%, 19.8\%, 16.3\%, and 14.0\% of the total
variance, respectively (Table 3). Eight species that had new leaves only
in January and April had the highest PC1 scores (Appendix S4).
Conversely, \emph{Maesa perlaria} (Lour.) Merr., \emph{Urophyllum
bidoupense} , and \emph{Saurauia napaulensis} DC. had new leaves in all
seven times and had the lowest PC1 scores.

By a clustering analysis using the UPGMA method, 91 species can be
classified into three groups, designated as Group 1--4 in Fig. 4.
Species of Group 1 showed low frequency of new leaf growth and expanded
new leaves in January and April but rarely in June, September, and
October. This group included two deciduous species (\emph{Acer
erythranthum} and \emph{Meliosma pinnata} ) and 29 evergreen species.
Species of Group 2 also showed low frequency of new leaf growth and
expanded new leaves in January and April but not in December. This group
included two deciduous species (\emph{Acer flabellatum}
and\emph{Engelhaldia serrata} ) and 18 evergreen species. Species of
Group 3 showed high frequency of new leaf growth and expanded new leaves
in most observed months. This group included 37 evergreen species.
Species of Group 4 showed low frequency of new leaf growth, usually
expanded new leaves usually in April and June, not in July, October, and
September, and included only three evergreen species.

By conducting another clustering analysis using the Kmeans++ method, the
clustering did not converge when K=4 (the number of clusters in UPGMA).
When K=3, the result of clustering was agreed with the UPGMA clustering
results for 83 species of the 91 total. However, Group 4 of the UPGMA
clustering was not present.

Based on these two clustering results, the 91 species can be classified
into three groups, designated as Group A--C (Fig. 4). Group A consisted
of 31 species that showed new leaves at low frequency, and rarely
expanded new leaves in September, October, and December. Group B
consisted of 24 species that showed new leaves at high frequency and
expanded new leaves in most observed months except October. Group C
consisted of 37 species that showed new leaves at high frequency and
expanded new leaves in October.

The top five families were scattered among Groups A, B and C, with the
exception of Rubiaceae (2 spp. in Group B and 4 spp. in Group C; Table
4). For Fagaceae, 6 out of 10 spp. were included in Group A and the
others were scattered in Group B and C. Similarly, for Lauraceae, 5 out
of 9 spp. were included in Group A and the others were scattered in
Group B and C.

\emph{Flowering phenology}

In flowering phenology, the \selectlanguage{english}first, second, third, and fourth principal
components accounted for 32.0\%, 19.2\%, 15.5\%, and 11.0\% of the total
variance, respectively (Table 3). The 26 species had no flowering events
and low PC1 scores, while three species (\emph{Melicope pteleifolia}
,\emph{Diplospora} sp., and \emph{Maesa} sp. in GL) flowered five or six
times and had high PC1 scores (Appendix S4).

By a clustering analysis using the UPGMA method, 91 species can be
classified into three groups designated as Group 1--3 in Fig. 5. Species
of Group 1 bloomed at the beginning of the wet season (April, June, and
July), and rarely in October, and December. This group included 12
evergreen species. Species of Group 2 flowered at low frequency or did
not bloom in our observation periods. This group included four deciduous
species and 59 evergreen species. Species of Group 3 bloomed from the
late wet season (October) to the dry season (December). This group
included seven evergreen species.

By conducting another clustering analysis using the Kmeans++ method, the
clustering did not converge when K=3. When K=2, Group A included 12
species of Group 1 and 17 species of Group 3 of the UPGMA clustering.
All the rest 62 species of Group B were included in Group 2 species of
the UPGMA clustering (Fig. 5).

Based on these two clustering results, 91 species can be classified into
two groups, designated as Group A and B (Fig. 5). Twenty-eight species
of Group A bloomed at high frequency and showed flowers at the beginning
of the wet season (April, June, and July) and at the beginning of the
dry season (November, and December). Sixty-three species of Group B
bloomed at low frequency (31 spp.) or did not bloom (32 spp.). In this
dendrogram, the top five families were scattered in Group A and B (Table
4). For Fagaceae and Symplocaceae, however, most species (9 out of 10
species in each) were included in Group B.

\emph{Fruiting phenology}

In fruiting phenology, the \selectlanguage{english}first, second, third, and fourth principal
components accounted for 42.2\%, 16.4\%, 11.8\%, and 9.9\% of the total
variance, respectively (Table 3). The 37 species showed no fruiting
events and had the highest PC1 score. Conversely, \emph{Maesa}
sp.,\emph{Illicium} sp., and \emph{Litsea} sp. set fruits all
observation months except January and had high PC1 scores (Appendix S4).

By a clustering analysis using the UPGMA method, 91 species can be
classified into two groups designated as Group 1 and 2 in Fig. 6.
Species of Group 1 set fruits at high frequency, including 15 evergreen
species. Species of Group 2 set fruits at low frequency or did not
fruit, including four deciduous species.

By conducting another clustering analysis using the Kmeans++ method, the
computation when K = 2 converged to the clustering of Group A and B:
Group A included 15 species of UPGMA Group 1, and Group B included 9 and
67 species of UPGMA Group 1 and 2, respectively.

Based on these two clustering results, 91 species can be classified into
two groups, designated as Group A and B (Fig. 6). Fifteen species of
Group A set fruits at high frequency. On the other hand, 76 species of
Group B set fruits at low frequency (39 spp.) or did not set (37 spp.).
In this dendrogram, all species of Fagaceae and Rosaceae were included
in Group B, 8 out of 9 spp. of Lauraceae were included in Group B, and
species of Rubiaceae and Symplocaceae are more evenly distributed in
Group A and Group B

\emph{Relationship between phenology and meteorological factors}

Both temperature and precipitation were highly correlated with day
length (Appendix S5); correlation coefficients between temperature vs.
daylength and precipitation vs. daylength were 0.89 and 0.83,
respectively. Notably, the correlation between temperatures of current
and previous months was weaker (0.78) and similarly, the correlation
between the precipitations of current and previous months was 0.74.
These values were lower than the correlation between the day lengths of
current and previous months (0.87). Summary statistics of these six
meteorological factors were obtained through a principal component
analysis, and PC1 and PC2 accounted for 81.5\% and 11.8\% of the total
variance, respectively. PC1 reflected whether six correlated variables
showed higher or lower scores and was positive in the wet season and
negative in the dry season (Fig. 7a). The high-PC1 season, from May to
September, and the low-PC1 season, from December to March, corresponded
to ''summer'' and ''winter'' in temperate forests of the northern
hemisphere, respectively. PC2 reflected a ratio of current month's
temperature and previous month's precipitation and was the lowest in
April, a turning point from dry to the wet season, and the highest from
October to November, a turning point from wet to dry season. All
variables increased in the former turning point and decreased in the
latter (Fig. 7b). The former turning-point season (April) and the latter
turning-point season (October and November) corresponded to ''spring''
and ''autumn'' in temperate forests of the northern hemisphere,
respectively. The annual change in the residual precipitation of the
previous month relative to the day length of that month was similar to
the annual change in PC2 (Fig. 7c). Results of statistical tests using
GLM with PC1 and PC2 as explanatory variables showed that the number of
leafing species showed a significant negative correlation with both PC1
and PC2 (\emph{p} \textless{} 0.001 for both PC1, and PC2), the number
of flowering species showed significant negative correlation with PC1
(\emph{p} \textless{} 0.001 for PC1, \emph{p} = 0.231 for PC2), and the
number of fruiting species showed significant correlation with either
PC1 (\emph{p} = 0.373) or PC2 (\emph{p} = 0.097).

Based on the results of the statistical tests using GLM with daylength,
residual precipitation, and residual temperature as explanatory
variables, the number of leafing species showed a significant negative
correlation with day length and residual precipitation and a significant
positive correlation with residual temperature (\emph{p} \textless{}
0.001 for daylength and residual precipitation, and \emph{p} \textless{}
0.01 for residual temperature). The number of flowering species showed a
significant negative correlation with daylength and residual
precipitation, but did not show a significant correlation with residual
temperature (\emph{p} \textless{} 0.01 for daylength,
\emph{p}\textless{} 0.05 for residual precipitation, \emph{p} = 0.586
for residual temperature). The number of fruiting species did not show a
significant correlation with any explanatory variables (\emph{p} =
0.918, 0.165, 0.504 for day length, residual precipitation, and residual
temperature, respectively).

\emph{Comparison of phenological patterns among forests in East and
Southeast Asia}

In the nine-location phenological similarity dendrogram, which was
constructed using the proportions of leafing, flowering, and fruiting
species in seven months (Fig. 8a, left side), Bidoup-Nui Ba was
positioned at the outermost part, while Mt. Kinabalu was placed between
Bidoup-Nui Ba and other seven areas. Among the seven areas, Fushan in
Taiwan was positioned on the outermost part. In the inner part of
Fushan, there were two clusters: a cluster consisting of two locations
in Malaysia (Lambir and Pasoh) and two locations in Japan (Kanto and
Kyushu), and another cluster consisting of Xishuangbanna in China and
Khao Yai in Thailand. The eight-location phenological similarity
dendrogram, which used data from twelve months (Fig. 8a, right side),
showed a similar topology, with the exception that the two locations in
Japan were now now grouped together.

A principal component analysis was performed for the 21 variables (3
phenology categories x 7 months), resulting PC1 and PC2, which explained
for 48.8\% and 19.1\% of the total variance, respectively. PC1 was
primarily influenced by the proportions of leafing species in January,
April, July, September, October, and December (Appendix S6). PC2 was
primarily influenced by the proportion of leafing species in April, that
of flowering species in September, October, and December, and the
proportion of fruiting species in January, April, June, and December.

The meteorological similarity dendrogram of nine locations was
constructed using monthly averages of day length, precipitation, and
temperature. It was separated into two groups: Group 1 included six
locations in China, Japan, Taiwan, Thailand, and Vietnam, and Group 2
included three locations in Malaysia and located at the base (Fig. 8b).
Group 1 showed large, unimodal annual changes of day length,
temperature, and precipitation, while Group 2 had high annual constancy
of day length and temperature, and smaller, irregular annual change of
precipitation.

\textbf{Discussion}

\emph{Key findings}

In terms of species composition, the lower montane forest in Bidoup-Nui
Ba National Park was similar to forests in Xishuangbanna, China, with
Fagaceae being the most common family, followed by Lauraceae and
Symplocaceae (Table 2). In terms of meteorological data, Bidoup-Nui Ba
National Park was similar to Xishuangbanna, China and Khao Yai, Thailand
(Fig. 8b). Seasons in Bidoup-Nui Ba were classified into the dry season,
the wet season, and two transition stages including dry to wet
transition around April and wet to dry transition around October. These
two transition stages corresponded to ``spring'' and ``autumn'' in the
temperate Northern Hemisphere climate. Under this pronounced
seasonality, 91 monitored species showed high variabilities in leafing,
flowering, and fruiting behaviors. They expanded new leaves at least
once a year, while leafing frequency largely varied between species.
Twenty four of the 37 species with high new leaf development frequency
expanded new leaves in all observed months except October, while the
other species expanded new leaves in October, the transition stage from
wet to dry season. Flowering frequency also varied among 91 species that
were classified into the high frequency group (28 spp.) and the low
frequency group (63 spp.). In the former, 12 species had flowers at the
beginning of the wet season (April, June, and July) and other species
had flowers at the beginning of the dry season (November, and December).
Notably, 32 out of 91 species (35.2\%) did not flower during the
observation period. For fruiting phenology, 91 species were also
classified into high frequency and low frequency groups, containing 15
spp. and 76 spp. (including non-fruiting 37 species), respectively.

In the following discussion, we will first characterize the phenological
patterns in Bidoup-Nui Ba by comparing them with patterns in mainland SE
Asia, China, Taiwan, and Japan. Second, we consider why the two
clustering results based on the phenological patterns (Fig. 8a) and the
meteorological data (Fig. 8b) were inconsistent. Finally, based on these
considerations, we infer how different phenological patterns diverged in
tropical montane forests, tropical lowland forests, and seasonal
forests.

\emph{Phenological characteristic in Bidoup-Nui Ba}

By summarizing the above-mentioned variability, the overall phenological
patterns in the tropical lower montane forest of Bidoup-Nui Ba, Vietnam
were characterized as follows. First, leafing phenology had a low peak
at the beginning of the wet season (April), and was significantly
associated with day length, precipitation, and temperature. This
observation is consistent with previous observations in tropical
seasonal forests where many plants have a peak of leafing in either wet
or dry season (Wright \& van Schaik, 1994). Second, flowering phenology
did not show any distinct peak, although it was associated with day
length and precipitation. This phenological pattern was different from a
previous observation study in the tropical lowland forest showing a peak
of flowering at the end of the dry season (Kitamura \emph{et al.} ,
unpublished). Third, 32 out of 91 species (35.2\%) did not flower during
the observation period, suggesting that those species have masting
habit. Among these non-flowering species, Lithocarpus and Quercus
(Fagaceae) are of the same genera as species known to exhibit musting in
temperate forests (Shibata et al., 2019; Wang et al., 2022). This is the
first report suggesting the occurrence of masting species in tropical
montane forests of Southeast Asia, although masting species have been
observed in montane forests of South India (Mohandass et al., 2016) and
tropical seasonal lowland forest in Thailand (Kurten et al., 2018).
However, there is a possibility that some species did not flower due to
their immaturity, as we observed that some species such
as\emph{Calophyllum rugosum} P.F.Stevens (Calophyllaceae), \emph{Platea
latifolia} Blume (Metteniusaceae), \emph{Beilschmiedia
bidoupensis}Komada, Tagane \& Yahara (Komada et al., 2022), and
\emph{Acer campbellii} subsp. \emph{flabellatum} in the plots did not
flower even though the taller trees outside of the plots were in
flowering or fruiting. Further studies, including tree size and maturity
data for each species, are needed to conclude that some tree species of
lower montane forest in Bidoup-Nui Ba show masting habits. Fourth,
fruiting phenology showed a low peak from the mid-wet season (July) to
the early dry season (December) and was not significantly associated
with any meteorological factor. Again, this observation was different
from a previous study in the tropical lowland forest showing a peak of
fruiting early in the wet season (Kurten et al., 2018). In summary, tree
species in the lower montane forests of Bidoup-Nui Ba are highly
variable in leafing, flowering, and fruiting behaviors, and the
phenological patterns observed there were different from previous
observations in tropical lowland forests with dry season in spite that
the climate in Bidoup-Nui Ba shows a pronounced seasonality in
precipitation.

These phenological patterns in the lower montane forests of Bidoup-Nui
Ba were similar to those of Mt. Kinabalu with high intensities of
flowering and fruiting events throughout the year (Fig. 8a). Here, we
define the term ``intensity'' to describe the proportion of species
active in leafing, flowering, or fruiting in a particular observation
month. Unlike Bidoup-Nui Ba and Mt. Kinabalu, the phenological patterns
in the other areas showed more pronounced seasonality in the intensities
of flowering and fruiting events, with some low-intensity months. These
differences in phenological intensity may be the one of the key factors
characterizing forest phenology and are not necessarily consistent with
the meteorological differences among forests (Fig. 8).

\emph{Comparison between the phonological similarities and the
meteorological similarities}

The discrepancies between the clustering results based on the
phenological patterns (Fig. 8a) and the meteorological data (Fig. 8b)
suggested that not only day length, temperature, and precipitation
included in this study's analyses, but also some other meteorological
factors affected forest phenology. If the three meteorological factors
are sufficient to explain forest phenology, the phenological patterns in
Bidoup-Nui Ba are expected to be similar to those in Xishuangbanna,
where three meteorological factors show similar seasonal patterns. In
reality, however, the phenological patterns differed between Bidoup-Nui
Ba, with a high intensity of leafing and flowering throughout the year,
and Xishuangbanna, with distinct peaks of leafing and flowering within
the year. Moreover, if the three meteorological factors are sufficient
to explain forest phenology, its patterns are expected to differ between
Bidoup-Nui Ba and Mt. Kinabalu, due to meteorological differences
between them, especially in precipitation (Kumagai et al., 2005). In
reality, however, the phenological patterns of two montane forests were
similar in high intensities of flowering and fruiting events throughout
the year.

Compared to lowlands, there are more days when clouds cover tropical
mountains (Karger et al., 2021). Though the number of cloudy days was
not monitored in our observations in Bidoup-Nui Ba National Park, tree
trunks in the HG plot were covered by mosses, suggesting that the forest
was often covered with clouds. Previous study (Sklenar et al., 2008)
summarized the effects from the occurrence of clouds to the ecology of
mountain ecosystems as follows: (i) considerable quantities of water can
be provided indirectly through cloud or fog water deposition, (ii)
reduced evapotranspiration during the day prevents development of water
stress in the plants, (iii) reduced temperature oscillations minimize
the risk of night frosts, and (iv) low temperatures affect metabolic
rates of plants (Hedberg, 1964; Sarmiento, 1986; Breckle, 2002; Sklenar
et al., 2008). Due to those effects, many plants in tropical mountains
may grow or reproduce without the resting season and show high-intensity
phenology in leafing, flowering, and fruiting throughout the year, as in
the lower montane forests of Bidoup-Nui Ba and Mt. Kinabalu.

\emph{Diversification of phenological patterns among forests in East and
Southeast Asia}

Given the above similarities and differences of phenological patterns
found in representative forest types, here we propose a framework for
the process of phenological diversification in forests of East and
Southeast Asia. This framework explains how and why various phenological
patterns evolved as a result of the adaptive evolution of angiosperms in
East and Southeast Asia.

According to the paleobotanical (Axelrod, 1966; Morley, 2001, 2018) and
molecular-ecological studies (Ohtani et al., 2021), angiosperms in
tropical and temperate regions of Asia occurred in low-latitude regions
in the early Cretaceous and extended their distribution to northern and
southern regions. It is also suggested that, before the entry of
angiosperms into the lowland Cretaceous record, they evolved chiefly in
moist tropical to warm temperate upland regions (Axelrod, 1966).
Therefore, when inferring how phenological patterns diverged between
various forest types, we can assume that tropical lower montane forests
have ancestral states of leafing, flowering, and fruiting phenology
(Fig. 9). This assumption does not preclude reverse changes, but rather
helps in considering reverse changes.

First, during the process of distribution expansion from tropical lower
montane forest to tropical lowland forest (process 1 of Fig. 9), some
plants weakened their seasonal patterns as a result of adaptation to
lowland climates, resulting in reduced intensities of leafing,
flowering, and fruiting through a year. In contrast, other plants,
including masting species in tropical lower montane forests, retained
their abilities to respond to changes in temperature and precipitation,
resulting in supra-annual flowering events occurring after irregular
drought and low temperature, known as general flowering.

Second, during the process of distribution expansion from tropical lower
montane forests to tropical seasonal forests (process 2 of Fig. 9),
plants reduced phenological intensities as a result of adaption to
severe drought in lowland climates, resulting in annual patterns of
leafing and flowering in the dry season, and fruiting in the wet season.
In this process, some plants evolved deciduousness for adaptation to
severe drought (Axelrod, 1966).

Third, phenological changes similar to the process 2 are considered to
have occurred during the processes of geographical migration from
tropical rain forest areas to tropical seasonal forest areas (process 3
of Fig. 9), resulting in annual patterns of leafing and flowering in the
dry season, and fruiting in the wet season. In this process, some plants
evolved deciduousness for adaptation to severe drought (Axelrod, 1966).

Fourth, during the processes of geographical migration from the tropical
seasonal forest areas to subtropical seasonal forest areas (process 4 of
Fig. 9), plants adapted to the lower temperature, where annual patterns
of leafing and flowering in spring, and fruiting in autumn emerged.

Fifth, during the processes of geographical migration from the
subtropical forest areas to warm-temperate forest areas (process 5 of
Fig. 9), plants adapted to the cooler temperature in winter, resulting
in high-peaked annual patterns of leafing and flowering in spring, and
fruiting in autumn. In this process, only some groups, including
Fagaceae, are considered to retain masting habits.

This hypothetical framework explains that high-intensity patterns of
leafing and flowering phenology are found in montane forests, longer and
scattered patterns of leafing and flowering phenology are found in
low-latitude areas, and shorter and concentrated patterns of leafing and
flowering phenology are found in high-latitude areas (Fig. 8a). Based on
this framework, we suggest that phenological traits may change in future
by sensitively responding to climate changes. However, it should be
noted that the framework of Figure 9 is a simplification of the
complicated changes in tree phenology observed in various forest types.
To develop a more realistic framework, we need to describe and compare
community-wide phenological patterns in various forests in more
locations in East and Southeast Asia.

\emph{Conclusion}

In conclusion, the community-wide phenological patterns of leafing,
flowering, and fruiting in the tropical lower montane forest of
Bidoup-Nui Ba are unique among tropical forests of East and Southeast
Asia. Particularly, our observation suggests that masting of tropical
lower montane forest can be an ancestral trait to both general flowering
in tropical rain forests and masting found in temperate forests in East
and Southeast Asia. These considerations are derived from the first
quantitative observations of the leafing, flowering, and fruiting
phenology in the tropical lower montane forest of continental Asia, and
comparisons of community-wide phenological patterns among various forest
types observed in East and Southeast Asia.

This study also suggested that not only day length, temperature, and
precipitation, but also some other meteorological factors, such as cloud
cover days may have affected forest phenology. Cloud forests in the
tropics are known as terrestrial ecosystems that are rich in species and
endemics (Karger et al., 2021). Further studies on the influence of
cloud cover days on phenology are needed using meteorological data
including the data of near-global, fine-grain monthly cloud frequencies
from 15 year of Moderate Resolution Imaging Spectroradiometer (MODIS)
satellite images (Wilson \& Jetz, 2016).

Further quantitative studies describing community-wide phenological
patterns are also needed to determine whether similar patterns are
observed in plant communities under similar climatic conditions or not.
Also, we need to consider the phylogenetic constraint among species for
more precise comparison. In recent years, community-level phenological
shifts have been reported in several areas (e.g. CaraDonna et al., 2014;
Chen et al., 2017), suggesting that significant change will occur in
synchronized ecosystems in response to future climate change. To deepen
our understanding of phenological responses to climate change, we need
additional detailed studies of phenology throughout Asia.

\textbf{Acknowledgments:}

The authors are grateful to the managers and staff of the Bidoup-Nui Ba
National Park for supporting our botanical inventories in the protected
area. We also thank Hiromi Murakami (Kyushu University) for her kind
help with office administration, and the curators and staff of the
following herbaria: BKF, DLU, FOF, FU, KAG, KYO, MAK, NHL, PNH, TI, TNS,
and VNM for allowing us to examine their collections. This study was
partly supported by the Environment Research and Technology Development
Fund (4--1601) of the Ministry of the Environment, Japan, and JSPS
KAKENHI (JP18H04011, JP20J10047, JP22K20671).

\textbf{Contributions:}

AN (Nagahama) and TY lead the study and significantly contributed to
data analysis and interpretation. AN (Nagahama), ST, NVN, HTB, TQC, NTN,
KT, MZ, HT, HN, AN (Naiki), and TY contributed to field surveys in
Vietnam and collecting phenological data. AN (Nagahama), ST, NVN, HTB,
TQC, EM, HT, HN, AN (Naiki), and TY contributed to species
identifications. SK contributed to field surveys in Thailand and
collecting phenological data. All authors reviewed the manuscript draft
and revised it critically on intellectual content. All authors approved
the final version of the manuscript to be published.

\textbf{References}

Ashton, P. (2014). \emph{On the Forests of Tropical Asia: Lest the
Memory Fade} . London: Royal Botanic Gardens Kew.

Axelrod, D. I. (1966). Origin of deciduous and evergreen habits in
temperate forests. \emph{Evolution} , 20, 1--15. doi:10.2307/2406145

Binh, H.T., Ngoc, N. V., Tagane, S., Toyama, H., Mase, K., Mitsuyuki,
C., Strijk, J. S., Suyama, Y., \& Yahara., T. (2018). A taxonomic study
of \emph{Quercus langbianensis} complex based on morphology and DNA
barcodes of classic and next generation sequences. \emph{PhytoKeys} ,
95, 37--70. doi: 10.3897/phytokeys.95.21126

Borchert, R., Robertson, K., Schwartz, M. D., \& Williams-Linera, G.
(2005). Phenology of temperate trees in tropical
climates.\emph{International Journal of Biometeorology} , 50, 57--65.
doi:10.1007/s00484-005-0261-7

Breckle, S.-W. (2002). \emph{Walter's vegetation of the Earth. The
ecological systems of the geo-biosphere (Fourth edition)} . Berlin:
Springer.

CaraDonna, P. J., Iler, A. M., \& Inouye, D. W. (2014). Shifts in
flowering phenology reshape a subalpine plant
community.\emph{Proceedings of the National Academy of Sciences} ,
111(13), 4916--4921. doi:10.1073/pnas.1323073111

Chang\selectlanguage{english}-Yang, C. H., Lu, C. L., Sun, I. F., \& Hsieh, C. F. (2013).
Flowering and fruiting patterns in a subtropical rain forest,
Taiwan.\emph{Biotropica} , 45(2), 165--174.
doi:10.1111/j.1744-7429.2012.00911.x

Cheablam, O., Tanakanjana, N., Vejaboonsakorn, S., \& Sangtongpraow, S.
(2004). Plant community analysis for nature interpretation designing in
the nature trails at Khao Yai National Park. \emph{Thai Journal of
Forestry} , 23(1), 60--73. thaijo:index.php/tjf/article/view/255967

Chen, X., Wang, L., \& Inouye, D. (2017). Delayed response of spring
phenology to global warming in subtropics and tropics.\emph{Agricultural
and Forest Meteorology} , 234, 222--235.

Corlett, R. T. (2009). \emph{The Ecology of Tropical East Asia (Third
Edition)} . Oxford: Oxford University Press.

Edwards, E. J., Chatelet, D. S., Chen, B. C., Ong, J. Y., Tagane, S.,
Kanemitsu, H., Tagawa, K., Teramoto, K., Park, B., Chung, K. F., Hu, J.
M., Yahara, T., \& Donoghue, M. J. (2017). Convergence, consilience, and
the evolution of temperate deciduous forests. \emph{The American
Naturalist} , 190(S1), S87--S104. doi:10.5061/dryad.k505s

Fick, S. E., \& Hijmans, R. J. (2017). Worldclim 2: new 1-km spatial
resolution climate surfaces for global land areas. \emph{International
Journal of Climatology} . 37(12), 4302-4315. doi:10.1002/joc.5086

Hedberg, O. (1964). \emph{Features of afroalpine plant ecology.} Sweden:
Swedish Science Press.

Hijmans, R. J., Williams, E., Vennes, C., \& Hijmans, M. R. J. (2017).
Package `geosphere'. \emph{Spherical trigonometry} , 1(7), 1--45.

Ichie, T., Hiromi, T., Yoneda, R., Kamiya, K., Kohira, M., Ninomiya, I.,
\& Ogino, K. (2004). Short-term drought causes synchronous leaf shedding
and flushing in a lowland mixed dipterocarp forest, Sarawak,
Malaysia.\emph{Journal of Tropical Ecology} , 20(6), 697--700.
doi:10.1017/S0266467404001713

Intachat, J., Holloway, J. D., \& Staines, H. (2001). Effects of weather
and phenology on the abundance and diversity of geometroid moths in a
natural Malaysian tropical rain forest. \emph{Journal of Tropical
Ecology} , 17(3), 411--429. doi:10.1017/S0266467401001286

Karger, D. N., Kessler, M., Lehnert, M., \& Jetz, W. (2021). Limited
protection and ongoing loss of tropical cloud forest biodiversity and
ecosystems worldwide. \emph{Nature Ecology \& Evolution} , 5(6),
854--862. doi:10.1038/s41559-021-01450-y

Kimura, K., Yumoto, T., Kikuzawa, K., \& Kitayama, K. (2009). Flowering
and fruiting seasonality of eight species of
\emph{Medinilla}(Melastomataceae) in a tropical montane forest of Mount
Kinabalu, Borneo. \emph{Tropics} , 18, 35--44. doi:10.3759/tropics.18.35

Kira, T. (1991). Forest ecosystems of east and southeast Asia in a
global perspective. \emph{Ecological Research} , 6, 185--200.
doi:10.1007/BF02347161

Kumagai, T., Saitoh, T. M., Sato, Y., Takahashi, H., Manfroi, O. J.,
Morooka, T., Kuraji, K., Suzuki, M., Yasunari, T., \& Komatsu, H.
(2005). Annual water balance and seasonality of evapotranspiration in a
Bornean tropical rainforest. \emph{Agricultural and Forest Meteorology}
, 128 (1-2), 81--92. doi:10.1016/j.agrformet.2004.08.006

Kurten, E. L., Bunyavejchewin, S., \& Davies, S. J. (2018). Phenology of
a dipterocarp forest with seasonal drought: Insights into the origin of
general flowering. \emph{Journal of Ecology} , 106(1), 126--136.
doi:10.1111/1365-2745.12858

Lechowicz, M. J. (1984). Why do temperate deciduous trees leaf out at
different times? Adaptation and ecology of forest communities. \emph{The
American Naturalist} , 124(6), 821--842. doi:10.1086/284319

Mohandass, D., Campbell, M. J., Chen, X. S., \& Li, Q. J. (2018).
Flowering and fruiting phenology of woody trees in the tropical-seasonal
rainforest, Southwestern China. \emph{Current science} , 2313--2322.
jstor:stable/26495797

Morley, R. J. (2001). Why are there so many primitive angiosperms on the
rain firests of Asia-Australasia. \emph{In:} I. Metcalfe, J. M. B.
Smith, M. Morwood, I. Davidson (eds) \emph{Faunal and Floral Migration
and Evolution in SE Asia-Australasia} . Lisse: A. A. Balkema Publishers.

Morley, R. J. (2018). Assembly and division of the South and South-East
Asian flora in relation to tectonics and climate change. \emph{Journal
of Tropical Ecology} , 34(4), 209--234. doi: 10.1017/S0266467418000202

Nagahama, A., Tagane, S., Zhang, M., Ngoc, N. V., Binh, H. T., Cuong, T.
Q., Nagamasu, H. Toyama, H., Tsuchiya, K.,\& Yahara., T.
(2021).\emph{Claoxylon langbiangense} (Euphorbiaceae), a new species
from, Southern Vietnam. \emph{Acta Phytotaxonomica et Geobotanica} ,
72(3), 275--280. doi:10.18942/apg.202016

Nagahama, A., Tagane, S., Ngoc, N. V., Binh, H. T., Cuong, T. Q.,
Toyama, H., Nagamasu, H., Tsuchiya, K., Zhang, M., Suyama, Y.,
Moritsuka, E., Thu, N. T. A., Thinh, N. C., Matsuo, A., Hirota, S. K.,
Naiki, A., Son, L. V., Nhan, P. H., \& Yahara, T. (2019). \emph{A
picture guide for the flora of Bidoup-Nui Ba National Park I: Mt.
Langbian} . Fukuoka: Center for Asian Conservation Ecology, Kyushu
University.

Nagahama, A., \& Yahara, T. (2019). Quantitative comparison of flowering
phenology traits among trees, perennial herbs, and annuals in a
temperate plant community. \emph{American Journal of Botany} , 106(12),
1545--1557. doi:10.1002/ajb2.1387

Nakagawa, M., Ushio, M., Kume, T., \& Nakashizuka, T. (2019). Seasonal
and long-term patterns in litterfall in a Bornean tropical
rainforest.\emph{Ecological Research} , 34(1), 31--39.
doi:10.1111/1440-1703.1003

Nitta, I., \& Ohsawa, M. (1997). Leaf dynamics and shoot phenology of
eleven warm-temperate evergreen broad-leaved trees near their northern
limit in central Japan. \emph{Plant Ecology} , 130: 71--88.
doi:10.1023/A:1009735709258

Nomura, N., Kikuzawa, K., \& Kitayama, K. (2003). Leaf flushing
phenology of tropical montane rain forests: relationship to soil
moisture and nutrients. \emph{Tropics} , 12(4), 261--276.
doi:10.3759/tropics.12.261

Ohtani, M., Tani, N., Ueno, S., Uchiyama, K., Kondo, T., Lee, S. L., Ng,
K. K. S., Muhammad, N., Finkeldey, R., Gailing, O., Na'iem, M.,
Indrioko, S., Widiyatno, Siregar, I. Z., Kamiya, K., Harada, K., Diway,
B., \& Tsumura, Y. (2021). Genetic structure of an important widely
distributed tropical forest tree, \emph{Shorea parvifolia} , in
Southeast Asia. \emph{Tree Genetics \& Genomes} , 17, 1--13.
doi:10.1007/s11295-021-01525-8

R Core Team. (2017). R: A language and environment for statistical
computing. https:// www.R-project.org/

Rathcke, B., \& Lacey, E. P. (1985). Phenological patterns of
terrestrial plants. \emph{Annual review of ecology and systematics} ,
16, 179--214.

Sakai, S. (2002). General flowering in lowland mixed dipterocarp forests
of South-east Asia. \emph{Biological Journal of the Linnean Society} ,
75(2), 233--247. doi:10.1046/j.1095-8312.2002.00016.x

Sakai, S., \& Kitajima, K. (2019) Tropical phenology: recent advances
and perspectives. \emph{Ecological Research} , 34: 50--54.
doi:10.1111/1440-1703.1131

Sakai, S., Momose, K., Yumoto, T., Nagamitsu, T., Nagamasu, H., Hamid,
A. A., \& Nakashizuka, T. (1999). Plant reproductive phenology over four
years including an episode of general flowering in a lowland dipterocarp
forest, Sarawak, Malaysia. American journal of botany, 86(10),
1414--1436. doi:10.2307/2656924

Sarmiento, G. (1986). Ecological features of climate in high tropical
mountains. \emph{High altitude tropical biogeography} , 11, 45.

Sklenar, P., Bendix, J. \& Balslev, H. (2008). Cloud frequency
correlates to plant species composition in the high Andes of
Ecuador.\emph{Basic and Applied Ecology} , 9(5), 504--513.
doi:10.1016/j.baae.2007.09.007

Shibata, M., Masaki, T., Yagihashi, T., Shimada, T., \& Saitoh, T.
(2020). Decadal changes in masting behaviour of oak trees with rising
temperature. Journal of Ecology, 108(3), 1088--1100.
doi:10.1111/1365-2745.13337

Takanose, Y., \& Kamitani, T. (2003) Fruiting of fleshy-fruited plants
and abundance of frugivorous birds: phenological correspondence in a
temperate forest in central Japan. \emph{Ornithological Science} , 2(1),
25--32. doi:10.2326/osj.2.25

Ushio, M., Osada, Y., Kumagai, T. O., Kume, T., Pungga, R. A. S.,
Nakashizuka, T., \ldots{} \& Sakai, S. (2020). Dynamic and synergistic
influences of air temperature and rainfall on general flowering in a
Bornean lowland tropical forest. \emph{Ecological Research} , 35(1),
17--29. doi:10.1111/1440-1703.12057

Wang, Y., Han, Q., Kitajima, K., Kurokawa, H., Shimada, T., Yamaryo, T.,
Kabeya, D., Kawasaki, T., \& Satake, A. (2022). Resource allocation
strategies in the reproductive organs of Fagaceae
species.\emph{Ecological Research} , 1--11. doi:10.1111/1440-1703.12350

Wilson, A. M., \& Jetz, W. (2016). Remotely sensed high-resolution
global cloud dynamics for predicting ecosystem and biodiversity
distributions. \emph{PLoS biology} , 14(3), e1002415.
doi:10.1371/journal.pbio.1002415

Wright, S. J., \& Van Schaik, C. P. (1994). Light and the phenology of
tropical trees. \emph{The American Naturalist} , 143(1), 192--199.
doi:10.1086/285600

Yooprasert, S., Culham, A., Tagane, S., Yahara, T., Nguyen, K. S., \&
Utteridge, T. M. (2022). New species and new status of
\emph{Urophyllum}Wall.(Rubiaceae) from Cambodia and Vietnam.
\emph{Adansonia} , 44(11), 91--114. doi:10.5252/adansonia2022v44a11

Zhang, J.-L., Zhu, J.-J., \& Cao, K.-F. (2007). Seasonal variation in
photosynthesis in six woody species with different leaf phenology in a
valley savanna in southwestern China. \emph{Trees} , 21: 631--643.
doi:10.1007/s00468-007-0156-9

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