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ALTITUDINAL VARIATION OF FERN COMMUNITY IN YAKUSHIMA ISLAND
Genki Yumoto1, Hiroya Takiyama2,3, Renata Schmitt4, Sho Murakami5, Wanyi Lee2 and Yusuke Fuke5
1Center for Ecological Research, Kyoto University, Japan 2Primate Research Institute, Kyoto University, Japan 3The Leading Graduate Program in Primatology and Wildlife Science, Japan 4Amazon National Research Institute (INPA), Brazil 5Graduate School of Science, Kyoto University, Japan
Abstract
Yakushima Island harbors a great diversity of ferns with rich micro-habitats and high
precipitation. Mountainous geology and steep altitudinal gradient allow co-existence of distinct
climatic zones from warm to cool temperate. Survey on fern community was conducted to
explore the altitudinal gradient of sporophyte and gametophyte distribution in Yakushima Island.
We identified sporophytes by morphology and gametophyte by determining rbcL sequences.
Overall, we identified 17 genera of gametophytes and 30 genera of sporophytes. Of all the
genera found, Dryopteris were present in all three altitudinal levels. In addition to fern
distribution, present study recorded gametophyte samples possibly to be the new record of
Histopteris fern on Yakushima and possibly a new species in the genus Histopteris.
Introduction
Biogeographical research concerns about the relationships between distribution patterns
of organisms and environments and their changes along with evolutionary history. Many
researches have focused on the latitudinal gradients in species richness along environmental
gradients, such as those of temperature and humidity. Similar to research of latitudinal richness,
studies on altitudinal or elevational gradients on species richness were carried out to explore the
species community transition from warm to cold habitats (Barrington, 1993; Kessler, 2010;
Kessler et al., 2011). Latitudinal and elevational gradient is different in that elevational gradients
are more spatially compressed. Compared with latitudinal gradient, environment in altitudinal
gradient, especially in temperature, changes more rapidly than that in latitude gradient.
Therefore, altitudinal studies may provide us insight on how other abiotic factors, in addition to
temperature, may have influence on biodiversity. For example, UV radiation and diurnal
fluctuations in temperature increases more rapidly with elevation, incurring negative effect on
growth of some plants (Halbritter et al., 2013; Siefert et al., 2015).
Ferns made interesting study subject of biogeographical studies with distinctive
generations, i.e., sporophytic and gametophytic generations. The distributions of ferns have been
considered to be determined primarily by abiotic environmental factors (Barrington, 1993;
Kessler, 2010). However, most biogeographical studies on ferns are done on sporophytes due to
the fact that gametophytes are typically smaller in size and less distinguishable by morphology.
Previous studies reported that distributions of gametophytes can be different from those of
sporophytes (Ebihara et al., 2008; Ebihara et al., 2013). Despite the essential role they played in
dispersal of ferns, gametophytes distributions are therefore less studied and require more
attention (Dassler & Farrar, 2001; Pinson et al., 2017; Schneider & Schuettpelz, 2006).
Lately, DNA sequencing technique provides an opportunity for accurate identification of
gametophyte species (Li et al., 2010). In plants, ribulose-bisphosphate carboxylase (rbcL) region
on the chloroplast genome have been used for DNA barcoding analyses. As an essential protein
in photosynthesis, a subunit of rubisco, the protein rbcL codes for, has relatively high
conservativeness. The use of this gene is advantageous for inference of phylogenetic relationship
at higher taxonomic levels. In the case of ferns, their nucleotide sequences are often used for
identification of genera (Hasebe et al., 1994).
Here in our study, we aimed to investigate and compare the species compositions of fern
gametophytes and sporophytes at different altitudes in Yakushima Island. By using combination
of sporophyte identification by morphology and gametophyte by molecular information, we
determined altitudinal gradient of two distinct generations of ferns in Yakushima.
Methodology
Study site
Yakushima Island is situated at the southern-most region of Kyushu, Japan (30° N, 130°
E). The island is about 500 km2 in area, lying on the biogeographic boundary of the northern
limit of the subtropical zone and southern limit of the temperate zone. Precipitation in
Yakushima Island is high, estimated to be over 4,000 mm in the low-land areas and 10,000 mm
in the high-altitudinal areas (Tokumaru, 2003). The island is mountainous, with the highest peak
Mt. Miyanoura-dake at 1,935 m above sea level (a.s.l.). As a result of steep altitudinal gradient,
climatic zones that corresponds to warm to cool temperate are present on the island. Vegetation
on the island serves as miniature representative of vegetation in Japanese Archipelago, ranging
from evergreen broadleaf forest in the warm temperate zone below 700-800 a.s.l. to
cool-temperate coniferous forests and scrub forests of dwarf bamboo above 1,200 a.s.l. (Okano
& Matsuda, 2013; Tokumaru, 2003). Diversity in micro-habitats and rich precipitation give rise
to astonishingly high variety of fern community, including about 300 species (Ministry of the
Environment, 2013; Okano & Matsuda, 2013).
Sample Collection
Study sites were categorized into three altitudinal levels, 1) low altitude, less than 300 m,
2) mid altitude, between 300–1,000 m and 3) high altitude, higher than 1,000 m. We sampled
two sites for each altitudinal level. To equalize sampling efforts across altitudes, each sampling
session lasted for about 30 minutes. For sporophytes, we collected one sample for one species to
get the distribution information at each altitude level. For gametophytes, samples were collected
using tweezers. Sporophyte samples were preserved as pressed specimens using newspapers
immediately after returning to the field station. We also examined the proportion of sporophyte
samples with spores. For species that we were able to get more than two samples in one altitude
level, we include it as “with spore” when at least one sample had spores. Gametophyte samples
were carefully washed using a stereomicroscope, were cut into half for molecular analysis and
for preservation as voucher specimens, and both of them were preserved in ethanol 100%.
Sporophytes were identified by examining morphological characteristics (e.g. leaf
arrangement, spore appearance and root morphology). Gametophyte were identified by DNA
sequencing of rbcL region.
DNA Isolation and Amplification by PCR (Polymerase Chain Reaction)
We performed tissue-direct PCR for 192 out of 349 gametophyte samples using ca. 1
mm2 of gametophytes tissue preserved in 100% Ethanol. The tissue samples were cut with
razors, placed in 0.2 ml tubes and mixed with 10 µl of PCR mix for a nested PCR technique that
combines two distinct reactions. For the first PCR, we used a 10 µL reaction mixture containing
1X PCR buffer (Takara Bio), 0.2 mM dNTPs (Takara Bio), 5 pmol of both forward and reverse
primers, and 0.5 units of Taq DNA polymerase (Takara Bio) using TaKaRa PCR Thermal Cycler
Dice TP650 (Takara Bio) or 2720 Thermal Cycler (Applied Biosystems). The cycling parameters
for the first PCR were; 94°C for 5 min (heat shock), 35 cycles each of 30 sec at 94°C
(denaturing), 30 sec at 50°C (annealing), and 72°C for 60 sec (extension), 7 min at 72°C (final
extension), followed by 10°C (storage). For the second PCR reaction, we used 0.5 µl of the first
PCR as template and the same conditions as the first one. In both PCR reactions, the chloroplast
fragment of the large-subunit of rbcL region was amplified using the following pair of primers
aF (5’- ATG TCA CCA CAA ACA GAG ACT AAA GC – 3’ ) and bR (5’ – CGT TCG CCT
TCC AAT TTG CCC ACT ACA GT – 3’) (Hasebe et al., 1994).
PCR products were electrophoresed in a 1% agarose gel in 1X TAE buffer with 1 µl of
loading solution (BFB) and 0.6 µl of Safety-dye (Natural Immunity) (diluted to 20 times) to
confirm PCR amplification for 10 min at 100V using Mupid-exU (Mupid). The PCR products
were purified using ExoSAP-IT (Affymetrix) according to manufacturer's instructions before the
DNA sequencing by Sanger method using an automated sequencer (ABI 3130) with only a single
strand, primer aF.
Molecular Analyses
The sequences obtained were confirmed and edited in MEGA 7.0.20 (Kumar et al., 2016)
and then “blasted” in BLAST nucleotide (Basic Local Assignment Search Tool -
https://blast.ncbi.nlm.nih.gov/Blast.cgi) to infer the gametophytes genera, based on the hit with
the highest similarity percentage. After, the rbcL sequences were aligned using the multiple
sequence alignment program Clustal W (Thompson et al., 1994). The resulting alignment was
subject to the Neighbour-Joining (NJ) method using MEGA 7. The confidence of the internal
branches from the resulting tree was tested by bootstrap analysis with 500 replications.
We also performed Maximum likelihood analyses for the genus Histiopteris. The
alignments of nucleotide sequences were done by Clustal W implemented in MEGA 7. To find
the best model that fits our data set we also performed a search in MEGA 7. The branch support
was assessed using 500 bootstrap replicates.
Results
Species identification of Sporophyte
In total, 93 samples of sporophytes were collected; 40 from low, 50 from mid and 3 from
high altitudes. The species were from 30 different genera. Dryopteris was found distributing in
all three altitude levels (Table 1, Figure 1). Different altitudinal levels generally have limited
sharing genus, although some genera were found in both low and high altitudes. There were 20
genera of sporophyte that exclusively present in only one altitude (Table 1, Figure 1 and 2). In
every altitude level, the proportion of sporophyte species with spores was less than 60% (Table
2).
Molecular Data of Gametophyte
We obtained part of rbcL gene sequences from 62 out of 192 samples, that resulted in a
final alignment with 700 bp. Using nucleotide BLAST, 57 samples were identified as
gametophyte ferns (used as ingroup in our NJ analysis) and five as moss (used as outgroup in the
NJ analysis) (Figure 1). For the ferns, we found seventeen genera belonging to 11 families. The
most abundant genus was Dryopteris, occurring in all three altitudes (Table 1, Figure 1). There
were thirteen gametophyte genera exclusively presented in only one altitude (Table 1, Figure 1
and 2). Between the altitude levels, there were few genera overlapping for gametophytes (Figure
2).
For the Neighbor Joining (NJ) analysis, we included 25 sequences downloaded from
GenBank for comparisons with our own sequences (Figure 1). The analysis recovered 17 genera
identified in our BLAST search, and for some of the genera (the colored boxes in the
cladogram), it might be possible that we have more than one species (e.g. Dryopteris,
Arachniodes).
Furthermore, we found a new record for distribution to Japan for the genus Histiopteris,
or even a new species not yet described for the genus. The genus Histiopteris has seven nominal
species. BLAST results for Histiopteris showed that our samples are more closely related with a
sequence of H. incisa (a worldwide distributed species) from New Zealand (KT983822.1) than
those ones found in the mainland of Japan. These result is corroborated by ML analysis,
recovering Histiopteris as a monophyletic group (Figure 3).
Table 1. Genus list of fern sporophytes and gametophyte
Altitude level high, middle, low represented by “H”, “M”, “L” respectively. “o” means the genera is present.
Table 2. Percentage of sporophyte with spore
Figure 1. Neighbor-Joining (NJ) tree for gametophytes. The
optimal tree with the sum of branch length = 1.24 is shown.
The percentage of replicate trees in which the associated
taxa clustered together in the bootstrap test (500 replicates)
are shown next to the branches – only values over 70%. The
tree is drawn to scale, with branch lengths in the same units
as those of the evolutionary distances used to infer the
phylogenetic tree. The evolutionary distances were
computed using the p-distance method and are in the units
of the number of base differences per site. The analysis
involved 87 nucleotide sequences. All ambiguous positions
were removed for each sequence pair. There were a total of
700 positions in the final dataset. Evolutionary analyses
were conducted in MEGA7. The color boxes represents the
genera and the dots besides each sample represent the
altitude (yellow = high, blue = middle, red = low).
Figure 2. Genus distribution of gametophyte (left) and sporophyte (right) across altitude. Color
presents the altitude level (yellow = high, blue = middle, red = low)
Figure 3. Phylogeny of Histiopteris by Maximum Likelihood method (ML) based on partial rbcL
sequence data (689 bp). Number on each nodes is bootstrap values in 500 replicates. Red dots
represent the samples collected in this study.
Discussion
Phenology of ferns
Two possibilities are assumed from the fact that only about 50% of the sporophyte
samples collected in this study germinate spores. Firstly, we can confirm that seasonality exists
in fern sporophyte and gametophyte reproduction. In our sampling, which was conducted within
a relatively short span of time, we could still found about half of the sporophyte samples with
spores. The ratio of the sporophyte samples that have spores in the low and middle altitude level
were 40% and 59%, respectively. Previous study revealed that fern spores can maintain
dormancy until the environment becomes more suitable for germination (Inoue, 2003). And
humidity, precipitation, temperature and sunlight hour, which change seasonally, could influence
the length of dormancy. Accordingly, there may be difference between season of spore dispersal
and that of germination.
Secondly, the result may be affected by our sample size. In high altitude, we got only
three sporophyte samples, which may not reveal the actual reproductive state of the fern
community. Since the sampling of present study only lasts for few days, it is highly possible that
we underestimate the diversity of fern gametophytes. We recommend conducting study in
different seasons so as to resolve the problem of underestimation. To further confirm the
seasonality in fern reproduction, close observation in phenology of sporophyte individuals and
its relationship with environmental factors like humidity, precipitation is also recommended.
Overlapping genus
In gametophyte, only one genus was found to be distributed in all three altitude levels.
In sporophyte, overlapping genus between high and low altitude was similar result with
gametophyte. However, overlapping between mid and low altitude was different, which had 8
genera overlapping between mid and low altitude. Regarding this, we propose two possible
reasons, firstly the sampling method and secondly the effect of climate.
During sampling, different strategies were implemented when sporophytes and
gametophytes were collected. For sporophytes, we collected samples on the way to sampling site
for gametophytes. Whereas for gametophyte, we collected samples in smaller areas at the
sampling sites. Therefore, sampling range for sporophytes was larger than that of gametophytes.
There is thus a possibility of underestimate the overlapping gametophyte genus since we may not
be able to cover all ecotones in elevation. Other than that, there were differences in sampling
efforts that may underestimate the distribution of sporophytes in high altitude and overestimate
the overlapping genera found in both mid and low altitude.
Scientists have consensus on the importance of climatic condition on distribution and
species richness (Kessler, 2010). In Yakushima, 750 m a.s.l. is temperature transition zone, and
above this altitude, diurnal and annual ranges of temperature fluctuation tend to increase
considerably (Kawarai, 2009). Above 1,000 m a.s.l., snow accumulates during winter (Osawa,
2006). The ferns in high altitude may be specific to be able to survive under low temperature and
snow accumulation conditions, so there may be few genera found overlapping between high and
mid altitude, or between high and low altitude. However, it is not the case for gametophytes. We
think it is due to the aforementioned bias in sampling and the possibility of underestimation for
overlapping of gametophyte genera.
The genus Dryopteris
In this study, Dryopteris was collected in all altitude levels in Yakushima. So far in
Yakushima, species from Dryopteris genus is most abundant around our research sites (Nature
Conservation Bureau of the Environment Agency, 1993). However, if we identify the samples to
lower taxonomic level i.e. to species level, it is possible that the degree of overlapping will
decrease.
Putative new Histopteris spp.
Two of the gametophyte samples we collected (Middle-23 and Middle-40) were from the
genus Histopteris. By BLAST, they are genetically different from H. incisa, a species widely
distributed in temperate and tropical areas including Japan. Almost all H. incisa including that
reported in Wakayama (Ebihara et al., 2010) made one clade, but our samples and H. incisa
reported in New Zealand (Perrie et al., 2015) made different clade (Figure 3). Hence, we suggest
that our samples are not H. incisa.
In total, there are seven species in the genus Histopteris. However, we can only obtain
rbcL DNA sequence of two species i.e. H. incisa and H. sinuate from GenBank. Therefore, our
samples could either be undescribed species or described species whose DNA sequence of rbcL
are not available in GenBank. In any case, these two samples are the first report of Histopteris
spp. other than H. incisa in Japan, because. H. incisa was the only one Histopteris reported in
Japan.
Sporophyte samples from Histopteris were also collected in this study. With reference to
morphological characteristics and distribution information, it was identified as H. incisa.
However, no molecular analysis was done on that sporophyte sample. Therefore, by the limited
information, we could not eliminate the possibility that our sporophyte sample is from a species
that is reported in Japan. For further study, we recommend molecular analysis on the sporophyte
sample and compare it with our gametophyte sample. Moreover, comparison of genetic and
morphological information with other species from Histopteris including the five lacking from
GenBank is highly recommended.
Acknowledgement
This course was supported by PWS. Our sincere thanks go to Ms. Sakai and Ms.
Akiyama, staff of the PWS office. We would like to express our deep gratitude to Prof. Wataru
Shinohara, Prof. Hiroshi Kudoh and the other lecturers for precious knowledge they shared. We
would also like to acknowledge Prof. Shizuka Fuse and staffs of laboratory of Plant Physiology,
who advised on DNA analysis.
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