Research Article |
Corresponding author: Badrul Munir Md-Zain ( abgbadd1966@yahoo.com ) Academic editor: Klaus Henle
© 2024 Millawati Gani, Frankie Thomas Sitam, Zubaidah Kamarudin, Siti Suzana Selamat, Nik Mohd Zamani Awang, Hani Nabilia Muhd-Sahimi, Michael Wong, Baharim Selat, Nur Fatin Khairunnisa Abdullah-Halim, Lim Shu Yong, Ling Fong Yoke, Salmah Yaakop, Abd Rahman Mohd-Ridwan, Badrul Munir Md-Zain.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Gani M, Sitam FT, Kamarudin Z, Selamat SS, Awang NMZ, Muhd-Sahimi HN, Wong M, Selat B, Abdullah-Halim NFK, Yong LS, Yoke LF, Yaakop S, Mohd-Ridwan AR, Md-Zain BM (2024) Unveiling prey preferences of endangered wild Malayan tiger, Panthera tigris jacksoni, in Peninsular Malaysia through scat analysis via COI DNA metabarcoding. Nature Conservation 55: 249-268. https://doi.org/10.3897/natureconservation.55.114211
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Understanding the prey preference of Malayan tiger (Panthera tigris jacksoni) in Malaysia is important to guide conservation planning initiatives. The utilisation of DNA metabarcoding provides valuable insights, particularly in the field of carnivora diet research. This technique has been proven to be effective for identifying various species within complex mixtures such as scat materials, where visual identification is challenging. The Cytochrome c oxidase subunit I (COI) locus has been selected as it is a widely used as an effective non-invasive approach for diet studies. Hence, given this advance approach, Malayan tiger scats were collected on the basis of existing records of their presence in two types of habitats, namely, protected areas (PA) and human–tiger conflict (HTC) areas. This study aimed to identify prey species in Peninsular Malaysia, based on Malayan tiger scat samples using DNA metabarcoding. Based on the partial mitochondrial COI region, DNA metabarcoding led to the taxonomic resolution of prey DNA remnants in scats and the identification of prey species consumed by Malayan tiger, which were predominately small-to-medium-sized prey, including livestock. The dominant DNA prey detected belongs to the family Canidae, followed by Bovidae, Vespertilionidae, Homonidae, Felidae, Phasianidae and Muridae. A significant difference (p < 0.05) was observed in alpha and beta diversity using the Shannon index and PERMANOVA with regard to prey richness and evenness in two different habitat groups, namely, PA and HTC. Our finding provides insights into Malayan tiger dietary requirements, which can be used to develop conservation plans and strategies for Malayan tiger, particularly for habitat priorities.
Diet, faecal, mitochondrial DNA, next-generation sequencing, tiger
The Malayan tiger (Panthera tigris jacksoni) is a prominent apex predator, which has received considerable attention in Malaysia. Peninsular Malaysia constituted approximately 6% of the land areas in Malaysia and is designated as totally protected, which comprises national parks and wildlife reserves managed by the Department of Wildlife and National Parks (PERHILITAN), as well as state parks under the supervision of state governments (
Predators play a crucial role in shaping the structure of food webs within ecosystems (
Determining the real-time prey selection by Malayan tiger is necessary to recognise the essential conservation needs of this endangered species in the future. Studies on prey selection of predators have been conducted in different ways, such as direct observation and scat analysis through undigested prey items remains in scats, such as hair, fur, bone and nails by using microscopic morphological analysis (
Both approaches have limitation in our study, such as safety during direct observation and the lack of a reference library database for hair, fur and other parts of wildlife. The database remains to be developed by forensic morphology teams at the National Wildlife Forensic Laboratory (PERHILITAN). Apart from scat analysis for undigested prey items to detect a tiger’s diet, recent advances on molecular genetics using high-throughput next-generation sequencing (NGS) employing DNA metabarcoding have shown great application potential in determining the current Malayan tiger prey selection. At present, the molecular identification of prey items in scats is used to complement morphological analysis. In recent years, DNA metabarcoding has been widely used to determine various animal taxa diets. A molecular approach to detect prey items from scats is a time- and cost-effective tool (
The research trend of faecal analysis using DNA metabarcoding in Malaysia has been conducted to various species, such as primate, elephant, bats, birds and insect (
A total of 33 scat samples were collected from areas known to be inhabited by the Malayan tiger between the years 2021 and 2022. Fig.
Sampling locations of Malayan tiger scats. (1: Royal Belum State Park, Perak; 2: Felda Kerteh, Kemaman, Terengganu; 3: Taman Negara Terengganu; 4: Pos Bihai Gua Musang, Kelantan; 5: Hutan Simpan Kekal Perias, Kelantan. Map on the left side: green, forest coverage; brown, oil palm plantation; purple, human settlement).
All scat samples were extracted using the QIAmp FAST Stool Kit (Qiagen, Germany) and QIAmp DNA Blood and Tissue Kit (Qiagen, Germany). A slight modification was performed during lysis by incorporating DTT to effectively lyse harder components, such as hair and nails present in the scats. In ensuring the absence of cross-contamination, negative controls were included in all DNA extraction procedures and in polymerase chain reactions (PCR). The extracted genomic DNA was visualised using 1% agarose gel electrophoresis and the DNA concentration was determined using Nanodrop ND-1000 (Nanodrop, Wilmington, DE, USA).
Scat samples were amplified using the partial control region (Dloop): MGCR560F (5′-GTGTACCTCTTCGCTCCG-3′) and MGCR873R (5′-TGTTGTACGTGGAACCCC-3′) for species identification. Of the 33 samples, 13 were successfully amplified and identified as Malayan tiger scats. Given the low concentration of obtained DNA, only 10 Malayan tiger samples were subjected for DNA metabarcoding analysis. Fig.
No. | Individuals/Sample ID | Locations tag on map | Habitat type | Habitat type |
---|---|---|---|---|
1. | Syamilla Mek Bihai | 4 | Kampung Orang Asli | HTC |
2. | Sau Bihai | 4 | Kampung Orang Asli | HTC |
3. | PT-BH01 | 4 | Kampung Orang Asli | HTC |
4. | Awang Rasau | 2 | Oil palm plantation | HTC |
5. | Atan Kerteh | 2 | Oil palm plantation | HTC |
6. | PSC01 | 2 | Oil palm plantation | HTC |
7. | PSC12 | 3 | National Park | PA |
8. | PSC13 | 3 | National Park | PA |
9. | HSKP-21-13 | 5 | Forest Reserve | PA |
10. | SgKejar | 1 | Forest Reserve | PA |
A total of 10 samples were proceeded with amplicon sequencing as these samples passed the quality control (QC) with the minimum concentration of 10 ng/μl. A two-stage PCR was used to amplify and prepare sequencing libraries. The PCR amplification using the COI primer pairs m1COIintF and dgHCO2198 (
The second round of amplification was performed to incorporate Illumina i5 and i7 adapters and 8-bp barcodes. The PCR mixture was performed in a 10-μl reaction containing 5 μl of KAPA HiFi HotStart Ready Mix, 1 μl of each primer index (i7 and i5) and 3 μl of PCR products from the first PCR. The second PCR conditions were as follows: initial denaturation at 95 °C for 3 min, followed by 8 cycles of denaturation at 95 °C for 30 s, annealing at 55 °C for 30 s, extension at 72 °C for 30 s and a final extension at 72 °C for 1 min. The libraries were purified using 0.7X AMPure XP beads and quantified using a Qubit 2.0 fluorometer (Life Technologies). The size distribution of the libraries was assessed using TapeStation 2200 (Agilent). All libraries were pooled and loaded on to an Illumina Miseq 2 × 250 bp flow cell at 11 pM. All NGS laboratory works were conducted in
Monash University Malaysia Genomics Platform (
Fastq-formatted reads were imported into Geneious Prime® 2022.1.1. The assembly of raw reads of COI sequences was run using Geneious Prime® 2022.1.1. Raw sequencing data were trimmed using BBDuk in the Geneious Prime platform to remove any remaining Illumina adapters, bases below the average quality and reads that are less than 150 bp after end-trimming. Then, the trimmed sequences were merged by using the BBMerge tool in the Geneious Prime platform to create a single consensus sequence for each pair. Chimeric sequences were checked and eliminated on the basis of UCHIME (https://drive5.com/uchime/uchime_download.html) and “Gold” database (https://drive5.com/uchime/gold.fa).
Reads were clustered into operational taxonomic units (OTU) using a de novo assembler. Then, the sequences were assigned with a minimum overlap identity of no less than 97%. The taxonomy database was created by blasting the OTUs against a COI database from the National Center for Biotechnology Information (NCBI) nucleotide database with some entrez filters targeting on Eukaryote sequences and excluding environmental, uncultured and unclassified sequences. After creating a sequence classifier database from BLAST hits, the full amplicon dataset was classified using the Sequence Classifier in Geneious Prime 2022.1.1. Then, the filtered reads were analysed using R version 2022.07.2. All analyses, including the determination of relative read abundance (RRA), as well as alpha and beta diversity analyses, were performed to evaluate within and between sample habitat types by using the phyloseq (
Raw sequence reads have been archived on the NCBI Sequence Read Archive (SRA) with project number PRJNA954969, Biosamples submission numbers SAMN34161777, SAMN34161791, SAMN34161871, SAMN34162214, SAMN34162338, SAMN34162396, SAMN34163286, SAMN34163462, SAMN34163485 and SAMN34163613.
Of the 33 felid scats collected during field sampling, only 13 were confirmed to be Malayan tigers. However, only 10 gDNA products of Malayan tiger scats were proceeded to NGS because of low DNA concentration. DNA metabarcoding analysis was run in Illumina Miseq platform and a total of 2,132,729 raw reads were generated after filtering. Then, low-quality sequences, primer adapter and chimeric reads were removed and 440,272 reads remained. The remaining metabarcoding COI data were blasted against the NCBI nucleotide database. The rarefaction curve with 13,885 reads (Fig.
Sample ID | Habitat type | OTU numbers | Raw sequence reads | Non-chimeric reads |
---|---|---|---|---|
Syamilla Mek Bihai | HTC | 81 | 187,410 | 80,100 |
Sau Bihai | HTC | 73 | 146,716 | 43,777 |
PT-BH01 | HTC | 116 | 159,839 | 59,362 |
Awang Rasau | HTC | 71 | 176,472 | 55,069 |
Atan Kerteh | HTC | 110 | 203,531 | 26,232 |
PSC01 | HTC | 26 | 247,962 | 32,600 |
PSC12 | PA | 73 | 249,590 | 35,862 |
PSC13 | PA | 131 | 246,986 | 13,885 |
HSKP-21-13 | PA | 120 | 182,621 | 51,093 |
SgKejar | PA | 219 | 331,602 | 42,382 |
A total of 10 Malayan tiger scat samples indicated the presence of 416 OTUs and yielded 17 phyla in the kingdom of eukaryotes (Fig.
Scat composition of 10 Malayan tigers A relative read abundance (RRA) of scat composition at phylum level, based on 416 OTUs and B RRA of scat composition from two habitat groups of Malayan tigers at order level, based on 3.56% Chordata phyla identified.
Considering the habitat type, Malayan tigers at PA preyed most on the family Canidae (66.21%), followed by Vespertilionidae (5.66%), Bovidae (1.75%) and Rhinolophidae (0.01%). Meanwhile, the dominant prey DNA was identified in Malayan tiger scats that are living in areas categorised as HTC mostly from the family Bovidae (20.74%), Homonidae (0.34%), Felidae (Felinae, 0.06%), Muridae (0.044%) and Phasianidae (0.038%, Fig.
Prey taxa composition in scat samples of Malayan tigers, based on 21 OTUs A relative read abundance (RRA) of prey taxa at family level in Malayan tiger scats and B venn diagram from two habitat groups of Malayan tigers.
Species richness in each sample was assessed for alpha diversity analysis using the Chao1 and Shannon indices. The Shannon index showed a significant difference in prey selection by Malayan tigers at two different habitat groups (p < 0.05), whereas the Chao1 index showed no significant difference (p > 0.05). The high value of the Shannon index indicates the high diversity in richness and evenness. Meanwhile, the Chao1 index is a non-parametric method for estimating the number of species in a community. Table
Samples ID | Chao1 index | Shannon index |
---|---|---|
Syamilla Mek Bihai | 88.5 | 1.47674 |
Sau Bihai | 106.0 | 0.67834 |
PT-BH01 | 129.6 | 2.38472 |
Atan Kerteh | 141.6 | 2.37876 |
Awang Rasau | 76.6 | 0.97147 |
PSC01 | 32.0 | 0.78397 |
PSC12 | 82.2 | 2.03072 |
PSC13 | 143.4 | 2.88448 |
HSKP-21-13 | 130.1 | 3.13198 |
SGKejar | 235.1 | 3.38908 |
Diversity of prey taxa in Malayan tiger scat samples A alpha diversity, based on Chao1 and Shannon indices. B beta diversity displayed in the PCoA plot, based on the Bray–Curtis distance.
Beta diversity was displayed using a PCoA plot of COI-rarefied RRA data of prey DNA in Malayan tiger scats in different habitat types (Fig.
Malayan tiger is an apex predator that plays a vital role in the ecosystem in Malaysia. The abundance and occurrence of prey species in tiger’s habitat are associated with the predator–prey interaction, including survival, behaviour and their movement areas. In this study, scat sample collection was conducted in the wild habitat of Malayan tiger to understand the selection of prey by Malayan tiger in Peninsular Malaysia. Fig.
Collected Malayan tiger faecal samples A Syamilla Mek Bihai B Sau Bihai C PT-BH01 D Atan Kerteh E Awang Rasau F PSC01 G PSC12 H PSC13 I HSKP-21-13 J SgKejar.
This study found that the scat composition of the Malayan tiger in the selected areas of Peninsular Malaysia was dominated by medium prey (67.9%), livestock (20.8%) and small prey (5.7%, Fig.
Scat composition analysis of Malayan tigers inhabiting PA areas detected the presence of dogs DNA in HSKP-21-13 sample, serow’s DNA from PSC12 and PSC13; meanwhile bats, rodent and squamate DNA have been found in the scat sample named PSC12. Notably, the COI taxonomic classification analysis in this study did not detect any common prey by Malayan tiger as reported in previous studies (
In addition to the above, during field sampling, wild boar is found to be present in PA and HTC areas; however, no wild boar DNA were detected in tiger scats in our analysis.
Based on the findings of this study, the prey DNA in Malayan tiger scats may be influenced by other factors such as the scat sample quality, predation time, and selection of gene used. The detection of DNA prey depends on several factors, particularly the time when Malayan tigers consumed their prey species. Some DNA were degraded because of long exposure to the environment and the freshness of the scat sample affected the detection and identification of prey species (
Another factor influencing the result is the selection of gene or primers for prey DNA detection in scat samples. In this study, taxonomic classification analysis indicates that 2.42% of COI sequences generated could not be assigned to any taxonomic group (unknown/unclassified sequences). The partial COI gene (mlCOIintF and dgHCO2198R) can identify only 3.56% of the Chordata taxa in all samples and another 94.02% of the sequences generated largely identified other eukaryotes, such as fungi, amoebozoa, viridiplantae and another metazoan other than Chordata. The partial region of COI used in this study is an insufficient taxonomic coverage of COI barcoding primers.
This study was the first to investigate and describe the prey selection of Malayan tigers by DNA metabarcoding of scats. Despite the relatively small number of scats analysed in this study, the result demonstrated the overview of the current situation of prey selection by Malayan tigers in Peninsular Malaysia. In HTC and PA areas, Malayan tigers mostly consumed livestock and medium-to-small-sized prey species. Human expansion might be the major cause of the alteration of prey selection to livestock and medium-to-small-sized prey species. Prey selection by Malayan tigers is affected by human-induced alterations to the environment. Forest fragmentation causes the roaming areas of Malayan tiger to move towards the human areas, particularly oil palm plantation areas and human settlements. Usually, livestock owned by local people are often placed within their oil palm plantations area and most of the oil palm plantations in Peninsular Malaysia were near to the forest making the area a HTC area. When livestock is available, tigers will readily prey on them. Based on our results, future studies on tiger diet should consider using multi-locus DNA metabarcoding and conducting field sampling for a longer duration and should cover a wide area to understand the spatiotemporal variation in tiger diet. This approach will provide other opportunities to study their preference in the wild. Although this study cannot be used to quantify true abundance or proportion of prey species, it provides an important first step towards identifying prey taxa and spatial–temporal patterns in Malayan tiger diets. Less attention has been paid to medium and small prey than to large ones, leading to a shortfall in knowledge regarding their ecological roles. This limitation should be considered to help in planning strategies of conservation effort to Malayan tigers in Peninsular Malaysia. The data obtained in this study will improve dietary insight, which can be used to develop conservation plans and strategies for Malayan tigers, particularly for habitat priorities, protection and restoration in specific areas.
We wish to thank the Director General (YBhg. Dato’ Abdul Kadir bin Abu Hashim) and Director of the Ex-situ Conservation Division of PERHILITAN Peninsular Malaysia (Dr. Pazil Abdul Patah) for the support and permission to conduct this study (Permit No.: P06/10/2020). We are also thankful to the Universiti Kebangsaan Malaysia for the ethical permit approval in our research protocol (UKMAEC approval number: FST/2021/BADRUL MUNIR/22-SEPT./1198-OCT.-2021-OCT.-2023-NAR-CAT2). We would especially like to thank the MyTAG teams, staff of Ex-Situ Conservation Division, National Wildlife Rescue Centre (NWRC), Carnivore Unit Wildlife Conservation Division, PERHILITAN Terengganu, PERHILITAN Kelantan, PERHILITAN Perak, Royal Belum State Park, for their assistance in handling tigers during field sampling at HTC areas. Acknowledged also are the teams from SPARTA PERHILITAN, Primate Unit Wildlife Conservation Division PERHILITAN, Inventory Unit Wildlife Conservation Division PERHILITAN and Panthera Malaysia who helped with sample collections.
The authors have declared that no competing interests exist.
Wildlife Permit No.: P06/10/2020 -Ethical Permit: UKMAEC approval number: FST/2021/BADRUL MUNIR/22-SEPT./1198-OCT.-2021-OCT.-2023-NAR-CAT2).
The authors acknowledge the Fundamental Research Grant Scheme (FRGS), FRGS/1/2020/WAB11/UKM/01/1 funded by the Ministry of Higher Education (MOHE), Malaysia and the part for this research is supported by the Government of Malaysia under the 12th Malaysia Plan Project: Strengthening Wildlife Forensics, Ex-Situ Conservation and Biobanking-Phase 2 (Project Code: P23071000810008) and Geran Universiti Penyelidikan (GUP), grant number GUP-2022-043 Universiti Kebangsaan Malaysia.
MG, FTS, ZK, SSS, NMZA, HNMS, MW, BS and NFKAH conducted field sampling and collected samples. MG conducted DNA extraction and laboratory works. LSY and LFY performed library construction and sequencing. MG analysed all the data and collected information of the samples. MG drafted and edited the manuscript. ARMR, SY and BMMZ critically revised the intellectual content. All authors read and approved the final version of the manuscript.
Millawati Gani https://orcid.org/0000-0002-9508-7481
Lim Shu Yong https://orcid.org/0000-0003-2232-8261
Ling Fong Yoke https://orcid.org/0000-0002-1696-4969
Salmah Yaakop https://orcid.org/0000-0002-2998-8716
Abd Rahman Mohd-Ridwan https://orcid.org/0000-0003-0052-4149
Badrul Munir Md-Zain https://orcid.org/0000-0003-4037-8115
All of the data that support the findings of this study are available in the main text.