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Seasonal yield and composition of an inland artisanal fishery in a humic floodplain ecosystem of Central Kalimantan, Indonesia
SULMIN GUMIRI1,7,, ARDIANOR1,7, SYAHRINUDIN2,7, GUSTI Z. ANSHARI3,7, YUKIO KOMAI4, KAZUO TAKI6, HARUKUNI TACHIBANA6
1Department of Aquatic Resources Management, Faculty of Agriculture, Universitas Palangka Raya. Jl. Yos Sudaro, Kampus UPR, Palangka Raya 73111, Central Kalimantan, Indonesia. Tel./fax: +62-536-3229092, email: [email protected]
2Department of Soil Science and Forest Nutrition, Universitas Mulawarman. Samarinda 75116, East Kalimantan, Indonesia
3Department of Soil Science, Magister of Environmental Science, Universitas Tanjungpura. Pontianak 78124, West Kalimantan, Indonesia
4Department of Environmental Engineering, Osaka Institute of Technology. 5-16-1 Ohmiya, Asahi-ku, Osaka, 535-8585, Japan
5Department of Environmental Engineering, Chiba Institute of Technology. 94-99, Ohwada-shinden, Yachio-shi, Chiba-ken, 276-0046, Japan
6Research Institute of Water Environment Hydrosphere Environmental Science, 1-3-6 Fukui Nishi-ku, Sapporo, Hokkaido, 063-0012, Japan
7Consortium of Tropical Peat Sciences, Kalimantan Universities Consortium. C/q. Universitas Tanjungpura. Pontianak 78124, West Kalimantan, Indonesia
Manuscript received: 15 November 2017. Revision accepted: 1 June 2018.
Abstract. Gumiri S, Ardianor, Syahrinudin, Anshari GZ, KomaiY, TakiK, Tachibana H. 2018. Seasonal yield and composition of an inland artisanal fishery in a humic floodplain ecosystem of Central Kalimantan, Indonesia. Biodiversitas 19: 1181-1185. Seasonal yield of an inland artisanal fishery was studied in 2015 in the Takapan Floodplain Lake located along the Rungan River of Central Kalimantan Province-Indonesia. Record on daily fish catch consisting weight data and species composition was made in situ along with a one-year rainfall data that was collected from the nearest Meteorological Station located in Palangka Raya City airport. Results showed that throughout the year, total annual yield of captured fishes reached 4.8 tons comprised of 34 commercial freshwater fish species. Seasonal yield varied considerably in which fish capture was higher during the rainy season than on the dry season. The transition period from rainy to dry season was found to be the peak period of fish capture in the floodplain. Of the 34 fish species, the most abundant species was Channa striata that accounted to almost 50% of total annual fish yield. The two most abundant fishes, Channa striata, and Kryptopterus palembangensis were a top predatory blackfish and an omnivorous surface water whitefish, respectively. This result indicated that the studied floodplain habitat was still in good condition, however, conservation is needed to maintain the sustainability of freshwater fish resource in the future.
Keywords: Artisanal, fishery, floodplain, yield, sustainability
INTRODUCTION
Palangka Raya City is the capital city of Central Kalimantan Province, Indonesia. The city covers an area of 2,678.51 km2 inhabited by only 244,500 people or with the population density is only 91 people/km2. Although it is a provincial capital, the city often said to have three faces:
the city face, the village face and the forest. About 93% of its area is still considered as the forested area (Anon 2014a).
The city is flowed by two big rivers namely the Kahayan River, 550 km long, and the Rungan River, 750 km long (Anon 2014b). Along these rivers, 104 oxbow lakes were found with their size ranging from less than one hectare up to several hectares. These lakes were surrounded by tropical peat swamp forest. The rivers, lakes and this tropical peat swamp forest were interlinked forming a floodplain ecosystem. During rainy season, the rise of water level caused the oxbow lakes to expand and the peat swamp area was inundated and then dried up during the dry season (Gumiri and Iwakuma 2005).
These seasonal hydrological dynamics was the major determinant of the seasonal dynamics of water quality of this floodplain ecosystem. Ardianor et al. (2014) reported
that values of physicochemical parameters both in the river and its adjacent lakes varied greatly between dry season and wet season periods. During dry season, the water from both of the adjacent lakes and the Rungan River exhibited very low pH values. This low pH is probably due to the decrease of water discharge from upstream and the water bodies are then filled with the water released from the acidic groundwater from the surrounding peatland. On the other hand, during rainy season the increase of water discharge from upstream, the pH values will increase due to the dilution. However, the turbidity values were higher during dry season and lower during rainy season. The concentrations of dissolved oxygen were also higher during dry season than during rainy season.
The floodplain ecosystem of Palangka Raya was also characterized by relatively low concentrations of anions and cations. The anion concentrations tended to increase significantly during the transition period between dry and rainy season, whereas the cation concentrations were relatively stable throughout the year. The periodic fluctuation of cation concentrations during this transition period is presumably due to the sudden increase of water discharge that might be bringing more organic inputs to the system.
Despite the fact that this humic floodplain ecosystem of Palangka Raya is physicochemically poor in nutrient content (Tachibana et al. 2003), it supports high diversity and production of inland fisheries. There were more than 300 freshwater fish species had been recorded in Central Kalimantan Province (Anon 2010). It has been reported that even a single lake with less than 3 ha in size could harbor more than 100 species of freshwater fish (Buchar et al. 2007). The annual yield of inland captured fisheries in Palangka Raya City in 2013 was 1,340.5 tons (Anon 2014a). This high production of inland fisheries is probably partly due to the existence of riparian forest that provides fishes with natural food during rainy season (Gumiri et al.
2009).
The inland fishery catch in Southeast Asia was mostly under-reported including in Indonesia the official figures reported may not be based properly on recorded data (Coates 2002). In the present study, we attempt to provide a more accurate information of the inland fishery yield and species composition from the floodplain ecosystem of Central Kalimantan Province, Indonesia.
MATERIALS AND METHODS Study area
The study was conducted in floodplain ecosystem surround Takapan Lake, a 53 ha humic floodplain oxbow lake located at the Rungan River, Sub-district of Pahandut, Palangka Raya City, Central Kalimantan, Indonesia (02 9’
2.86” S; 113 55’ 1.17 E) (Figure 1).
The lake area was inhabited by a small number of subsistent local fishermen families in which they relied on their income solely from catching fish from the forested floodplain ecosystem of Rungan River watershed either
from the river, lake or the swamp forest area around the lake. Data collection was made for one year period from January until December 2015. Fish record was made by treating a local fisherman household operated in the lake as a defined unit effort as suggested by Coates (2002). This was possible because the fisherman was the only one buyer of all landed fishes in the lake. This daily bulk of catches was then usually sold to local market in Palangka Raya City. The fisherman was asked to record the daily fish catch consisting of number of fish types or local fish name and their weight. The fisherman’s record was then collected every month by visiting the lake. Naming the scientific names of the caught fished based on local names was made according to Kotellat et al. (1993) and Roberts (1989). Along with the fish record, rainfall data were also collected from the Airport Meteorological Station located in Palangka Raya City, located c.a 20 km from the study site. The fish data were then tabulated and presented in the form of tables and graphs.
RESULTS AND DISCUSSION Results
Throughout the year the daily fish yield fluctuated considerably (Figure 2). In most cases, the daily fish catch was less than 25 kg per day, but during high yield period, the catch could reach more than 75 kg per day. More fish was captured between December and July, whereas between August and November were the months with the lowest catch. This trend somewhat coincided with the rainy events in the region. High rainfall periods occurred between February and May, and between October and December. It seemed that the high fish yield periods were preceded by those of high rainfall periods.
Figure 1. Study site in Takapan Lake, Palangka Raya City, Central Kalimantan, Indonesia. Arrow indicates the fish landing point where fish record was made
Takapan Lake
Rungan River
Kahayan River
Palangkaraya
Although the fish catch quiet high in certain periods (Figure 3.A), the number of fish species was relatively low (Figure 3.B). During high yield days, the number of fish species was mostly less than 5, and even during the two highest yields periods on mid of May and mid of July, the species caught consisted of only one species. This indicated that some particular species were abundant only during particular periods of the year.
Throughout the year, the number of commercial fishes caught in the lake was 34 species with the total yield reached 4.8 tons (Table 1). The most abundant and common species caught was Channa striata that contributed to almost 50% of the total catch and captured in 198 days out of 365 days. The second high fish catch was Kryptopterus palembangensis with the total yield over 1 ton, and caught in 89 days per year. Mystus nemurus, Trichogaster trichopterus, Osteochilus melanopleura and Mystus nigriceps were the next abundant fish caught respectively.
Throughout the year, trends of monthly catch of the top five most abundant species varied (Figure 4). The yield of Channa striata peaked during May and June. The variation of its catch was very similar with the trend of the rainfall events but it seemed that the high yields happened just after the heavy rainfall period or during the transition period between the rainy and the dry season. The highest season of Kryptopterus palembangensis and Mystus nemurus were of January and February, respectively. Their yield variations somewhat coincided with the seasonal variation of rainfall events in the region. On the other hand, other two abundant species: Trichogaster trichopterus and Osteochilus melanopleura yield did not seem to have any correlation to the rainfall events.
Discussion
In the current study, the data were based on a whole one year period of inland artisanal fishery yield record. Since the study was conducted in a floodplain ecosystem where this type of inland fishery usually covers full spectrum of gears, the bulk of catches was difficult to see and monitor (Coates 2002). However, since all of the captured fishes were usually landed and sold to a local fisherman who then resells them on daily basis to Palangka Raya City, so we claim that our record represents the bulk catches of fish in this floodplain ecosystem.
The total number of species found during the present study was 34 species. Although the species richness was similar, the species composition differed considerably with fish species found in other studied tropical inland water ecosystems in Kalimantan and Sumatera (Utomo and Prasetyo 2005; Kartamiharja et al. 2011; Kasim et al. 2015;
Rupawan and Rais 2016). This difference supports the common scientific view that high diversity of freshwater fish species occurs mostly in the equatorial countries including Indonesia (Ng et al. 2017).
Similar to fish caught in other tropical floodplain ecosystems (de Merona 1990; Baran 2005; Freitas et al.
2002), fish yield in the studied floodplain ecosystem fluctuated considerably throughout the year. We found that
high yields occurred during the rainy season and during the transitional period, from rainy to the dry season. This yield pattern could be attributed to fish migration behaviors in this typical ecosystem (Junk et al. 1989; Coates 2002). It has been well documented that adults of many tropical freshwater species migrate up tributaries and on to flooded plains to spawn, lake dwelling species move into tributary streams and other riverine species migrated upriver to headwater regions in anticipation of seasonal rains (Helfman et al. 2009). In this type of inland fishery, local fishermen have adapted to apply more appropriate and efficient fishing gears to capture more fishes as floodwater recede (Coates 2002).
0 10 20 30 40 50 60 70 80 90
Fish catch (kg)
0 20 40 60 80 100 120 140 160
Rainfall (mm)
Fish Catch Rainfall
Dry season
Figure 2. Seasonal variation in fish yield during the period from January until December 2015
Figure 3. A. Daily number of fish yield, B. The number fish species caught
A B C D E
Figure 4. Trends of yield of five most abundant species: A. Channa striata, B. Kryptopterus palembangensis, C. Mystus nemurus, D.
Trichogaster trichopterus, and E. Osteochilus melanopleura. Units of Y-axis were kg for fish catch and mm for rainfall
Table 1. List of commercial captured fish species, their yields and catching days during the period from January until December 2015
Local name Scientific name
Annual catch (kg)
Catch- ing days
Haruan Channa striata 2,289.5 198
Lais baji Kryptopterus palembangensis 1,056 89
Baung Mystus nemurus 242 30
Sapat Trichogaster trichopterus 155.1 30
Tauman Channa micropletes 116 22
Biawan Helostoma temminckii 128 19
Kapar Belontia hasselti 61.7 15
Puyau Osteothilus hasselti 54.4 14
Kalabau Osteochilus melanopleura 149.9 12
Pantikan Mystus nigriceps 144.7 12
Karandang Channa pleurophthalma 28 12
Udang Macrobrachium sp 11.7 12
Saluang Rasbora oxygastroides 39.5 10 Tauman alas Channa micropeltes 28.6 8 Lili Mastacembelus nothopthalmus 22.5 8
Papuyu Anabas testudineus 12.8 7
Puhing Cyclocheilichthys apogon 26.3 5 Lais tabirin Belodontichthys dinema 25.3 5
Mihau Channa melasoma 16.4 5
Tauman karamba Ophiocephalus micropeltres 47.6 4
Manangin Elops machnata 30.3 4
Kalui Osphronemus goramy 11.2 4
Pipih Chitala lopis 7.7 4
Patin Pangasius djambal 11.1 3
Lawang Pangasius polyuranodon 6.5 3
Pentet Clarias batrachus 3.3 3
Lais besar Kryptopterus parvanalis 13.5 2
Tapah Wallago leeri 6.3 2
Jelawat Leptobarbus hoeveni 2.4 2
Lais bamban Kryptopterus cry 1.9 2
Lais bantut Ompok hypophthalmus 17.5 1
Darap Mystus olyroides 8 1
Sanggi Mystus sp 2.5 1
Kakap Lates calcarifer 1 1
Total annual catch 4,779.2
Of the almost 4.8 tons of total annual fish yield, 48% of the catch composed of snakehead (Channa striata). This species is considered as a native freshwater fish species of Borneo (Roberts 1989). The very high production of this top predatory fish can be an indicator that this floodplain ecosystem is still healthy because these predatory fishes depend largely on the production in floodplain (Junk et al.
1989).
The variation in time of peak yields of the five most abundant species could be attributed to the reproductive adaptations of these species to the seasonal dynamics of the ecosystem. The study area was a typical floodplain freshwater ecosystem consisted of river, lake, and floodplain to form a so-called river-floodplain system (Junk et al. 1989). This system is interconnected during rainy season and disconnected at dry season (Gumiri and Iwakuma 2005). During the rise of river water, these expanded interconnected ecosystems become a common spawning and nursery grounds for many riverine fishes.
These fishes have reproductive cycles that coincide with seasonal inundation of gallery forest and swamps, perhaps cued by rainfall or rising water levels (Helfman et al.
2009). This high recruitment of riverine fishes could be due to the fact that food supply in fertile floodplains during the flood phase can be so abundant (Junk et al. 1989). The importance of peat swamp forest ecosystem as habitat of freshwater fish community in the region was reported by Thornton (2017) in which of the 55 fish species found in Sebangau floodplain ecosystem, 29 species of them were captured in the forest.
The dominance of predatory species Channa striata could be attributed to the abundance of juvenile of other fishes during the rainy season. It has been well documented that worldwide predatory fish species often spawn earlier than their prey, thus assuring a food source for young predators (Helfman et al. 2009). The coincident trend of Kryptopterus palembangensis catches with the rainfall events in this study perhaps due to its both migration and reproductive strategies which utilised the expanded floodplain habitat, since members of this Siluridae was
found as an omnivorous surface water fish that feed mostly on terrestrial insects falling from the swamp forest or riparian vegetation (Handayani et al. 2009; Minggawati 2009).
To conclude, the present study has attempted to provide a more reliable data on bulk catches of inland artisanal fishery in a humic tropical floodplain ecosystem. In this complex system, the rainfall events tended to govern the high seasonality of fish yield and composition. The dominance of Channa striata and Kryptopterus palembangensis as a top predatory blackfish and an omnivorous surface water whitefish respectively, indicate that their habitats are still in good condition to maintain the sustainability of freshwater fish resource in the studied floodplain ecosystem.
ACKNOWLEDGEMENTS
We would like to express our sincere thanks to The Resona Foundation for Asia and Oceania of Japan for their financial support during the study. Our thanks are due also to Mahrani, a local fisherman in Takapan Lake for his great assistance in data collection and record throughout the study.
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Kartamiharja ES, Purnomo K, Fahmi Z. 2011. Struktur komunitas dan biomassa stok ikan di Danau Sembuluh dan Papudak, Kalimantan Tengah. J Lit Perikan Ind 17 (4): 285-291. [Indonesian]
Kasim K, Prianto E, Umar C. 2015. The impact of water level fluctuation to the catch at the Mahakam Hulu floodplain East Kalimantan. J Lit Perikan Ind 21 (4): 229-236. [Indonesian]
Kottelat M, Whitten AJ, Kartikasari SN, Wirjoatmodjo S. 1993:
Freshwater Fishes of Western Indonesia and Sulawesi. Periplus Editions Limited, Singapore.
Minggawati I. 2009. Studi kebiasaan makan dan jenis makanan ikan Lais Bantut (Ompok hypophthalmus) di Danau Dapur Kota Palangka Raya.
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Pages: 1186-1193 DOI: 10.13057/biodiv/d190402
Molecular phylogeny of trees species in Tripa Peat Swamp Forest, Aceh, Indonesia inferred by 5.8S nuclear gen
ZAIRIN THOMY1, ARDHANA YULISMA2,♥, ESSY HARNELLY1 , ARIDA SUSILOWATI3
Program in Magister Biology, Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala. Jl. Tgk Chik Pante Kulu No. 5, Kopelma Darussalam, Syiah Kuala, Banda Aceh 23111, Aceh, Indonesia. Tel.: +62-651-8012505, ♥email: [email protected]
Faculty of Forestry, Universitas Sumatera Utara. Jl. Tridharma Ujung No. 1, Kampus USU, Padang Bulan, Medan 20155, North Sumatra, Indonesia
Manuscript received: 25 January 2018. Revision accepted: 1 June 2018.
Abstract. Authors. 2018. Molecular phylogeny of trees species in Tripa Peat Swamp Forest, Aceh, Indonesia inferred by 5.8S nuclear gen. Biodiversitas 19: 1186-1193. Tripa peat swamp forest is protected areas that have high biodiversity. Nevertheless, in some areas, the damage occurred due to conversions of land function to oil palm plantations. The impact of conversions of peat swamp forest to oil palm plantations has led to biodiversity decreased. Hence, it is important to identify the remain tree species in Tripa peat swamp forest.
This study aimed to determine of trees species diversity in Tripa peat swamp forest by using of 5.8S rRNA nuclear gene. Research was conducted at Forest Genetics and Molecular Forestry Laboratory, Faculty of Forestry, IPB from September 2015 to August 2016.
Molecular identification consisted of DNA extraction, PCR analysis, and sequencing. The data were analyzed using Bioedit, MEGA 6, BLAST, and ITS2 database. Molecular identification using ITS 1 and ITS 4 primer successfully amplified (the ITS region ITS1-5.8S- ITS2) of 16 trees species from 9 families. BLAST analysis results indicate the presence of 16 species has similar bases sequence with the GeneBank DNA database. The plant species are Branckenridgea palustris (Ochnaceae), Gonystylus sp. (Thymelaeaceae), Tristaniopsis whiteana (Myrtaceae), Syzygium sp.1 (Myrtaceae), Macaranga triloba (Euphorbiaceae), Syzygium garciniifolium (Myrtaceae), Knema intermedia (Myristicaceae), Palaquium ridleyi (Sapotaceae), Palaquium sp. (Sapotaceae), Dyera lowii (Apocynaceae), Elaeocarpus petiolatus (Elaeocarpaceae), Ficus sp. (Moraceae), Syzygium leptostemon (Myrtaceae), Chilocarpus suaveolens (Apocynaceae), Alstonia pneumatophora (Apocynaceae), and Alstonia sp. (Apocynaceae). Phylogeny tree reconstruction using the Neighbor-Joining Method (NJ) showed that 5.8S rRNA nuclear gene was successful as marker for 16 trees species from 9 different families. In addition, the 5.8S also successful for resolving phylogenetic relationships at genus level i.e. Alstonia, Palaquium, Syzygium, Tristaniopsis, Macaranga, Elaeocarpus, and Ficus.
Keywords: Tripa peat swamp forests identification, phylogenetic relationships, tree species, 5.8S rRNA nuclear gene
INTRODUCTION
Tripa peat swamp forest is a protected peat swamp forest area of ± 63.228 hectares and part of the Leuser Ecosystem. It locates in Aceh Barat Daya District to Nagan Raya District, Aceh Province, Indonesia. The Tripa peat swamp forest is one of megadiversity center and also the largest carbon storage site in Aceh (YLI-AFEP 2008).
Peatland has extremely poor soils which are acidic and lower minerals as well as nutrients content. The unique and specific conditions of peatland created unique species diversity compared to another forest. According to Thomy et al. (2016) there were 17 families of trees species that can be found in Tripa peat swamp forest, i.e., Myrtaceae, Apocynaceae, Sapotaceae, Anacardiaceae, Sterculiaceae, Moraceae, Euphorbiaceae, Rubiaceae, Stemonuraceae, Thymelaeaceae, Ochnaceae, Rhizophoraceae, Annonaceae, Dipterocarpaceae, Myristicaceae, Elaeocarpaceae, and Arecaceae. WWF and LIPI (2007) reported that the endemic species in peat swamp ecosystem are Dyera lowii (Apocynaceae), Gonystylus bancanus (Thymelaeaceae), Kompassia malaccensis (Fabaceae), Alstonia pneumatophora (Apocynaceae), Campnosperma spp. (Anacardiaceae), Callophylum spp. (Calophyllaceae), Palaquium spp.
(Sapotaceae), and Lagerstroemia speciosa (Lythraceae).
Moreover, Djufri et al. (2016) reported that there were 41 species of herbs, seven species of shrubs and 24 species of trees in deforested peat-swamp forest of Tripa.
Tripa was mostly covered by forest as many as 67.000 hectares or 65% of the area, of which most was peat swamp forest. In the most recent year of observation, forest cover was 19.000 hectare (18% of the area). The largest forest conversion took place from 2005 to 2009, with the loss of approximately 4.000 hectares per year. Historical analyses can be used to support efforts to protect the remaining peat swamp forest in Tripa. In addition, forest degradation, conversion of forest area into oil palm plantations, illegal logging, forest fire, reduced Tripa peat swamp forest area as well as biodiversity, especially tree species. Hence, it is important to identify trees species that still found in the remain forest area. Database about the trees species will support the restorations program in the future (Widayati et al. 2012).
The 5.8S nuclear rRNA gene lies between Internal Transcribed Spacer 1 (ITS1) and Internal Transcribed Spacer 2 (ITS2). The 5.8 S rDNA sequences contain three conserved motives in their nucleotide sequences that are essential for the correct folding of secondary structure (Harpke and Peterson 2008a,b). According to Gomes et al.
(2002) and; O'Brien et al. (2005) the 5.8S rRNA gene has a
very high conserved level and commonly used as a marker for plant identification. Hribova et al. (2011) also reported that the 5.8S rDNA sequence region had a conserved length of 155 bp or 154 bp, its GC content varied from 49.68 to 57.48% and it can be used for molecular phylogeny.
Alvarez and Wendel (2003) also reported that 5.8S sequence region is one of the most popular loci used in molecular phylogenetic studies. Therefore this study was conducted to identify peat swamp trees species in Tripa swamp forest using of 5.8S rRNA nuclear gene for conserving and restoring effort in the future.
MATERIALS AND METHODS Study area
The research was conducted in Tripa peat swamp forest, Darul Makmur Sub-district of Nagan Raya District, Aceh, Indonesia and Laboratory of Forest Genetics and Molecular Forestry, Faculty of Forestry, Bogor Agricultural University, Bogor, West Java, Indonesia. The research was begun from September 2015 to August 2016.
Procedures Sample collection
This research used purposive sampling method. The total area for sampling site is 18.000 ha. Species sample
was taken as much as 2% per plot in the three locations, i.e., primary, secondary, and tertiary forest. Forty-five plots were designed in the study area and each location was divided into fifteen plots. The plot size was 20 m x 20 m for tree sampling (tree diameter > 20 cm and tree height
> 10 m).
DNA extraction, amplification, and sequencing
Total genomic DNA from each 16 trees species was extracted from young leaves using the Qiagen DNeasy Plant Mini kit (Qiagen, Hilden, Germany) following the manufacturer's instructions. The concentration and quality of DNA were checked by 2% agarose gel electrophoresis and visualized by UV transilluminator after red gel staining.
Amplification segments of DNA were conducted using 20 µL Polymerase Chain Reaction (PCR) reactions (Kapa Taq PCR MasterMix). All of the components consists of 10 µL (1X Kapa Taq), 1 µL forward primer, 1 µL reverse primer, 3 µL DNA template, and 5 µL nuclease-free water.
The temperature for PCR condition start to initial denaturation at 94˚C for 3 minutes, 30 cycles of denaturation (at 94˚C for 30 s), annealing (at 58˚C for 30 s), and extension (at 72˚C for 1 minutes), and ends with an elongation stage at 72˚C for 10 minutes. The primer used in this study was ITS 1 and ITS 4 (Table 1).
Figure 1. The forest cover map in The Leuser Ecosystem in the area of Tripa peat swamp forest, Aceh, Indonesia
Figure 2. Location of sample collection in Tripa peat swamp forest, Aceh, Indonesia
Table 1. Bases sequence of ITS 1 and ITS 4 primers
Genom DNA region Primer name Bases Sequence (5’-3’) Reference
Nuclear ITS1
5.8S rRNA ITS2
ITS 1 ITS 4
TCCGTAGGTGAACCTGCGG TCCTCCGCTTATTGATATGC
White et al. (1990) White et al. (1990)
Sequencing process is conducted after amplicon was checked by 2% agarose gel electrophoresis. The amplicons were sequenced based on the selective incorporation of chain-terminating dideoxynucleotides method according to the manufacturer’s instructions and run on an ABI-3100 automatic sequencer (Applied Biosystems) (Sanger and Coulson 1997). DNA strands were fully sequenced.
Editing and sequence alignment
The data was analyzed using BioEdit, BLAST and MEGA 6. Manual data review was performed by using BioEdit version 7.0.5.2 (Hall 1999). The Basic Local Alignment Search Tool (BLAST) from the NCBI homepage (http://www.ncbi.nlm.nih.gov/blast/blast.cgi) was then used to compare these sequences with in-house sequences and GenBank database sequences. The software of Molecular Evolutionary Genetics Analysis (MEGA) version 6.0 (Tamura et al. 2013) was used to predict phylogenetic relationships among trees species in Tripa
peat swamp forest. The reconstructing of phylogenetic tree using Neighbor-Joining method (NJ) bootstrap 1000x (Saitou and Nei 1987).
RESULTS AND DISCUSSION
The 5.8S motifs for the identifications of peat swamp tree The ITS2 database gives information about the sequence, structure, and taxonomic classification in GenBank. ITS2 region was delimited in the database http://its2.bioapps.biozentrum.uni-wuerzburg.de/cgibin/
index.pl?annotator. The ITS2 database also looked for several motifs in Internal Transcribed Spacer (ITS), i.e., 5.8S, ITS2, and 28S (Keller et al. 2009). The presence of all these motifs suggests that all ITS sequences obtained in this study are functional. An example of annotating result
of a complete sequence of the ITS region in Palaquim ridleyi is presented in Figure 4.
In the following years, the ITS2 database was further expanded from a data repository to a rather full-featured interactive workbench (Selig et al. 2008; Koetschan et al.
2010, 2012; Wolf et al. 2014). This figure also explained that one of species originated from Tripa peat swamp forest has a complete sequence. But in the several cases, not all species have a complete sequence. This research focused on the 5.8S rRNA as the functional part of the ITS region as marker for revolving phylogenetic relationships at the genus/species level. Generally, the region of 5.8S motifs has a length of 24 base pair (bp). However, the length of base pair (bp) could vary in other species. The 5.8S rRNA nuclear gene is the short sequence which is often used to identify and predict phylogenetic in plants and fungi. The 5.8S motifs for tree species identification in Table 2.
In tree phylogenetic, ITS1 and ITS2 can be used for distantly related species whereas 5.8S gene can be used for closely related species include plants and fungi. Conserved motifs for the 5.8S gene are poorly described in fungi.
However, three motifs of the 5.8S gene are conserved for
angiosperms M1 (5'-CGAUGAAGAACGUAGC-3'), M2
(5'-GAAUUGCAGAAUCC-3') and M3 (5'-
UUUGAACGCA-3') (Harpke et al. 2008). The 5.8S ribosomal RNA (5.8S rRNA) is a non-coding RNA component of the large subunit of the eukaryotic ribosome and plays an important role in protein translation. Thus, the 5.8S locus can serve as a critical alignment-free anchor point for search algorithms that make sequence comparisons for both phylogenetic and barcoding purposes.
Basic Local Alignment Search Tool (BLAST)
BLAST analysis was conducted to compare the DNA sequence of the peat swamp tree and the DNA sequence in GenBank DNA database. BLAST analysis also finds the similarity regions between biological sequences. Hence, it is assisting for reconstruction of the phylogenetic tree.
Furthermore, it could explain the position of the species in taxonomy. The BLAST analysis result of the 16 trees species from 9 families in Tripa peat swamp forest is presented in Table 3.
Figure 4. The annotated of 5.8S motifs in Palaquim ridleyi
Table 2. The 5.8S motifs of the tree species in Tripa peat swamp forest, Aceh, Indonesia
Name of species Locus Sequences Length (bp)
Palaquium ridleyi 5.8 S CGAGGGCACGCCTGCCTGGGCGTCT 25
Palaquium sp. 5.8 S CGAGGGCACGCCTGCCTGGGCGTCT 25
Alstonia sp. 5.8 S CGAGGGCACGTCTGCCTGGGCGTCA 25
Alstonia pneumatophora 5.8 S CGAGGGCACGTCTGCCTGGGCGTCA 25
Chilocarpus suaveolens 5.8 S CGAGGGCACGTCTGCCTGGGCGTCA 25
Dyera lowii 5.8 S GGAGGGCGCGTCTGCCTTGGGGGTCA 26
Elaeocarpus petiolatus 5.8 S CGAGGGCACGTCTGCCTGGGGTCA 24
Ficus sp. 5.8 S CGAGGGCACGTCTGCCTGGGCGTCA 25
Syzygium sp. 5.8 S CGAGGGCACGTTTGCCTGGGTGTCA 25
S. leptostemon 5.8 S TGAGGGCACGTTTGCCTGGGTGTCA 25
S. garciniifolium 5.8 S TTAGGGCACGTTTGCCTGGGTGTCA 25
Tristaniopsis whiteana 5.8 S AGAGGGCACGCTTGCCTGGGTGTCA 25
Macaranga triloba 5.8 S CAAGGGCACGTCTGCCTGGGTGTCA 25
Branckenridgea palustris 5.8 S CGAGGGCACGCCTGCCTGGGCGTCA 25
Knema intermedia 5.8 S TGAGGGCACGTCTGCCTGGGCGTCA 25
Gonystylus sp. 5.8 S CGAGGGCACGCCTGCCTGGGTGTCA 25
region target
Table 3. BLAST analysis of the 16 trees species from Tripa peat swamp forest, Aceh, Indonesia based on 5.8S rRNA nuclear gene
Species name Families Process ID Quary cover Ident E-value
Palaquium ridleyi Sapotaceae >KF686291.1 P. xanthochymum 100% 100% 3e-08
Palaquium sp. Sapotaceae >KF686291.1 P. xanthochymum 100% 100% 3e-08
Alstonia sp. Apocynaceae >KC960438.1 Alstoniascholaris 100% 100% 2e-07
Alstonia. pneumatophora Apocynaceae >KC960438.1 Alstoniascholaris 100% 100% 2e-07 Chilocarpus. suaveolens Apocynaceae >KC960438.1 Alstoniascholaris 100% 100% 2e-07
Dyera lowii Apocynaceae >JX856398.1 Alstonia macrophylla 96% 92% 0.014
Elaeocarpus petiolatus Elaeocarpaceae >KX365744.1E. floribundus 83% 100% 9e-06
Ficus sp. Moraceae >KX572966.1 F. carica 100% 100% 4e-07
Syzygium sp. Myrtaceae >KR532633.1 Syzygium oblatum 100% 100% 1e-06
S. leptostemon Myrtaceae >KX079334.1 Syzygium cumini 100% 100% 1e-06
S. garciniifolium Myrtaceae >JF682809.1 S. aqueum 100% 100% 1e-06
Tristaniopsis whiteana Myrtaceae >KM064872.1 T. laurina 100% 100% 1e-06
Macaranga triloba Euphorbiaceae >AF361166.1 M. bancana 100% 100% 3e-06
Branckenridgea palustris Ochnaceae >KF263225.1 B. zanguebarica 100% 100% 1e-08
Knema intermedia Myristicaceae >KR532228.1 K.globularia 100% 100% 5e-09
Gonystylus sp. Thymelaeaceae >GQ205178.1 Pimelea williamsonii 100% 100% 3e-08
All of the trees species from Tripa peat swamp forest has a similarity at the genus level with the sequences from GenBank DNA database. The Query Cover for 16 trees species has values in the range of 83% to 100%. It has a high degree of alignment to BLAST sequences. The E- value of 0.0 indicates the number of alignments with scores equivalent to or greater than that is expected to occur in a database by chance. Therefore the lower the E-value the more significant the score is and a better quality of the alignment BLAST search. The E-value was high in this study due to the locus sequence as the marker is very short.
In this study, the 5.8S nuclear gene has a length of about 24-26 bp. Hence, searching for similarity to a query sequence limited. According to Claverie and Notredame (2003), the DNA sequence has a high similarity if the Query Cover value is close to 100% and the E-value is close to 0.0.
Phylogenetic relationships based on 5.8S rRNA nuclear gene
The reconstructions of the phylogenetic tree (Figure 5) explained about phylogenetic relationships within the 9 families of the plants, i.e., Apocynaceae, Sapotaceae, Myrtaceae, Euphorbiaceae, Elaeocarpaceae, Moraceae, Ochnaceae, Thymelaeaceae, and Myristicaceae. In our study, from 16 different species, the 5.8S nuclear gene were clearly differentiated species from genus Alstonia (Figure 5.A), Palaquium (Figure 5.B), Syzygium (Figure 5.C), Tristaniopsis (Figure 5.C), Macaranga (Figure 5.D), Elaeocarpus (Figure 5.E), and Ficus (Figure 5.F). This marker is attractive because it has been used in previous barcoding studies of the eukaryotic with success (Nguyen and Seifert 2008; Schoch et al. 2012). However, the 5.8S as marker was not successful to resolve phylogenetic relationships in genus Chilocarpus (Figure 5.A), Dyera (Figure 5.A), Branckenridgea (Figure 5.G), Gonystylus (Figure 5.H), and Knema (Figure 5.I). According to Stern
et al. (2012) ITS region is one of the difficult markers technically because it is present in multiple distinct copies.
ITS region also has the high level of intra and intergenomic variability in species that can make alignment difficult.
The 5.8S is the small and large subunit ribosomal RNA genes are separated by the Internal Transcribed Spacer (ITS) units 1 and 2 as well as-as a marker using a wide variety of the tree species from peat swamp forest. The molecular phylogeny studies about plants in the peat swamp forest are very limited. It is therefore important to develop of molecular phylogenetic to determine the best of DNA barcode markers for the identification. The best performance of 5.8S occurred in Figure 5.A, whereby the 5.8S was successful grouped genus Alstonia (TPSF) with Alstonia from GenBank while there are four genera there.
(Burge et al. 2013) reported that the complete sequence of ITS (ITS1, 5.8S, ITS2) was used to predict molecular phylogeny of the plant within genus Pachypodium (Apocynaceae).
The most dominant species in Tripa peat swamp forests belong to Myrtaceae. According to Manshor and Manshor (2014), most species in peat swamp forests belong to the Myrtaceae and Dipterocarpaceae. Among all phylogenetic trees, the 5.8S was very successful for resolving phylogenetic relationships within families Myrtaceae.
Caused all member of families Myrtaceae (Figure 5.C) grouped clades based on the same genus i.e. Syzygium (TPSF) with Syzygium (GenBank) as well as Tristaniopsis (TPSF) with Tristaniopsis (GenBank). Even though 5.8S is highly conserved within plants, but this marker can be used to differentiate among species within families Myrtaceae.
The 5.8S was used for reconstructing phylogenetic relationships among species of Myrceugenia (Myrtaceae) (José Murillo-A et al. 2012). Furthermore, the 5.8S nuclear gene is recommended as universal barcodes for plants, especially within families Myrtaceae.
Alstonia pneumatophora (TPSF) Alstonia sp. (TPSF) KX277720.1 Hemidesmus indicus LN901557.1 Cynanchum foetidum Chilocarpus suaveolens (TPSF) KX079330.1 Alstonia scholaris Dyera lowii (TPSF) JX856398.1 Alstonia macrophylla Cyrtostachys lakka (OG) 52
8 55
7 3 8
A
Palaquium ridleyi (TPSF) KF686284.1 Palaquium rufolanigerum Palaquium sp. (TPSF) KF686287.1 Palaquium sp.
KF686286.1 Palaquium sericeum KF686291.1 Palaquium xanthochymum KF686290.1 Palaquium walsurifolium Cyrtostachys lakka (OG) 12
10 8 2 11
B
Syzygium sp. (TPSF) KR532633.1 Syzygium oblatum Tristaniopsis whiteana (TPSF) KM064872.1 Tristaniopsis laurina Syzygium leptostemon (TPSF) KX079334.1 Syzygium cumini Syzygium garciniifolium (TPSF) JF682809.1 Syzygium aqueum Cyrtostachys lakka (OG) 87
30 28 29
17 47
C
Macaranga triloba (TPSF) AF361161.1 Macaranga tanarius AF361151.1 Macaranga pruinosa AF361142.1 Macaranga kingii AF361167.1 Macaranga winkleri Cyrtostachys lakka (OG) 16
13 16
D
Elaeocarpus petiolatus (TPSF) KJ675670.1 Elaeocarpus thelmae KX365744.1 Elaeocarpus floribundus KJ675665.1 Elaeocarpus stellaris KJ675681.1 Elaeocarpus largiflorens Cyrtostachys lakka (OG) 15
13 17
E
Ficus sp. (TPSF) KU365058.1 Ficus amplocarpa KX689296.1 Ficus rubra KU365054.1 Ficus anamalayana KP325598.1 Ficus semicordata KP325593.1 Ficus prostrata Cyrtostachys lakka (OG) 13
12 4 15
F
Branckenridgea palustris (TPSF) KF263204.1 Campylospermum umbricola KF263225.1 Brackenridgea zanguebarica KF263200.1 Campylospermum schoenleinianum KF263209.1 Campylospermum klainei Cyrtostachys lakka (OG) 16
15 15
G
Gonystylus sp.(TPSF) FJ572732.1 Pimelea decora AM162502.1 Thecanthes punicea GQ205178.1 Pimelea williamsonii Cyrtostachys lakka (OG) 23
23
H
Knema intermedia (TPSF) KR532219.1 Horsfieldia prainii KR532228.1 Knema globularia Cyrtostachys lakka (OG) 33
I
Figure 5. Phylogenetic tree based on 58s rRNA nuclear gene within families: A. Apocynaceae; B. Sapotaceae; C. Myrtaceae; D.
Euphorbiaceae; E. Elaeocarpaceae; F. Moraceae; G. Ochnaceae; H. Thymelaeaceae; I. Myristicaceae using Neighbor-Joining (NJ) method. The phylogenetic tree is the consensus result. The bootstrap value shows in every node. TPSF: Tripa Peat Swamp Forest, OG:
Out Group
Species endemic, which is discovered in Tripa peat swamp forest i.e. Palaquium, Palaquium ridleyi, Gonystylus sp., Dyera lowii, and Alstonia pneumatophora.
Generally, all the species are classified as timber forest products. According to (Yamada 1997) reported that the dominants of mixed swamp forest common both to Sumatra and Kalimantan are Alstonia pneumatophora, Campnosperma coriacea, Durio carinatus, Dyera lowii,
Gonystylus bancanus, Koompassis malaccensis, Lophopetalum multinervium, Mezzettia leptopoda, Palaquium burckii, Parastemon urophyllum, Shorea platycarpa, S. teysmanniana and S. uliginosa.The timber production in peat swamp forest is low when compared to the lowland or mix dipterocarp forests. Therefore, the problem faced by peat swamp forest is due to increased human activity on tropical peatlands has resulted in much Clade I
Clade II
Clade III
Clade I
Clade II
Clade I
Clade I Clade I
Clade II
Clade III
Clade I
Clade II
Clade I
Clade II
Clade III
Clade IV
Clade II Clade I
Clade I
Clade II
of the destruction of the peat swamp forest ecosystem. The remaining pristine peat swamp forests need to be protected and managed wisely to prevent further losses of valuable endemic species. We concluded that 5.8S is strongly supported within genus Palaquium (Figure 5.B). Prior to, there were several studies used the 5.8S for the identification within families Sapotaceae. Swenson et al.
(2007a) reported that the 5.8S as one of a marker was used to molecular phylogeny studies of Planchonella (Sapotaceae) as well as eight new species from New Caledonia. Bartish et al. (2005) also reported that the 5.8S is one of the sequences used for resolving phylogenetic relationships among New Caledonian Sapotaceae.
In addition, there are several species include as the compiler of peat swamp vegetation in Tripa peat swamp forest, i.e., Elaeocarpus petiolatus, Macaranga triloba, Ficus sp., Knema intermedia, and Branckenridgea palustris. According to Kuniyasu and Tetsuya (2002) reported that one of the species compositions of Sumatran peat swamp forests is Knema intermedia. There were approximately 40 species of Macaranga including both peat swamp and non-peat swamp environments (Siregar and Sambas 2000). Molecular identification using the 5.8S as a marker is not recommended for several of the compiler species such as Branckenridgea palustris (Figure 5.G) and Knema intermedia (Figure 5.I). Due to searching the similarity of the 5.8S rRNA belonging to the species B.
palustris and K. intermedia with the query sequence in NCBI limited. We concluded that the phylogenetic relationships among that species (Figure 5.G and 5.I) are not clear. Further, needed full sequences of ITS region for resolving the phylogenetic issue. According to Vivas et al.
(2014) for species discrimination, ITS region provided the best results, followed by matK, trnH-psbA, and rbcL.
Furthermore, the combined analysis of two, three or four markers did not result in higher rates of discrimination than with ITS alone. These results indicate that the ITS region is the best option for molecular identification of Sapotaceae species from the Atlantic Forest.
Conversely, the 5.8 is very recommended for species Elaeocarpus petiolatus (Elaeocarpaceae), Macaranga triloba (Euphorbiaceae), and Ficus sp. (Moraceae). The previous study reported that several molecular phylogenetic studies on the families Elaeocarpaceae, as well as the genus Elaeocarpus, have been undertaken. The molecular studies using full sequence data from the Internal Transcribed Spacer (ITS) of nuclear ribosomal DNA (Maynard 2008).
Zeng et al. (2005) reported that phylogenetic relationships within families Moraceae have also used the 5.8S rRNA to predict phylogenetic of intra-species and inter-species within genus Morus (Moraceae).
In conclusion, the 5.8S was successful to distinguish all species within 9 families i.e. Apocynaceae, Sapotaceae, Myrtaceae, Euphorbiaceae, Elaeocarpaceae, Moraceae, Ochnaceae, Thymelaeaceae, and Myristicaceae from Tripa peat swamp forest. In addition, the 5.8S also successful for resolving phylogenetic relationships at the genus level, especially in genus Alstonia, Palaquium, Syzygium, Tristaniopsis, Macaranga, Elaeocarpus, and Ficus.
ACKNOWLEDGEMENTS
This project was funded by Indonesia Directorate General of Higher Education (DIKTI), Ministry of Research, Technology and Higher Education, Indonesia through Fundamental Scheme. The authors are very grateful to Prof. Iskandar Z. Siregar for kindly providing the Laboratory of Forest Genetics and Molecular Forestry, Faculty of Forestry, Bogor Agricultural University, West Java, Indonesia for this research. Our high appreciation for our supporting team, i.e., Nurur Rahmy, Syafrina, and Samsul Muarrif. Special thanks to Istafan from Forum Konservasi Leuser (FKL) who assisted in the field.
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