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Salis R, Sunde J, Gubonin N, Franzén M, Forsman A. Performance of DNA metabarcoding, standard barcoding and morphological approaches in the identification of insect biodiversity. Mol Ecol Resour 2024; 24:e14018. [PMID: 39285627 DOI: 10.1111/1755-0998.14018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 06/25/2024] [Accepted: 08/06/2024] [Indexed: 10/03/2024]
Abstract
For two decades, DNA barcoding and, more recently, DNA metabarcoding have been used for molecular species identification and estimating biodiversity. Despite their growing use, few studies have systematically evaluated these methods. This study aims to evaluate the efficacy of barcoding methods in identifying species and estimating biodiversity, by assessing their consistency with traditional morphological identification and evaluating how assignment consistency is influenced by taxonomic group, sequence similarity thresholds and geographic distance. We first analysed 951 insect specimens across three taxonomic groups: butterflies, bumblebees and parasitic wasps, using both morphological taxonomy and single-specimen COI DNA barcoding. An additional 25,047 butterfly specimens were identified by COI DNA metabarcoding. Finally, we performed a systematic review of 99 studies to assess average consistency between insect species identity assigned via morphology and COI barcoding and to examine the distribution of research effort. Species assignment consistency was influenced by taxonomic group, sequence similarity thresholds and geographic distance. An average assignment consistency of 49% was found across taxonomic groups, with parasitic wasps displaying lower consistency due to taxonomic impediment. The number of missing matches doubled with a 100% sequence similarity threshold and COI intraspecific variation increased with geographic distance. Metabarcoding results aligned well with morphological biodiversity estimates and a strong positive correlation between sequence reads and species abundance was found. The systematic review revealed an 89% average consistency and also indicated taxonomic and geographic biases in research effort. Together, our findings demonstrate that while problems persist, barcoding approaches offer robust alternatives to traditional taxonomy for biodiversity assessment.
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Affiliation(s)
- Romana Salis
- Department of Biology and Environmental Sciences, Linnaeus University, Kalmar, Sweden
| | - Johanna Sunde
- Department of Biology and Environmental Sciences, Linnaeus University, Kalmar, Sweden
| | - Nikolaj Gubonin
- Department of Biology and Environmental Sciences, Linnaeus University, Kalmar, Sweden
| | - Markus Franzén
- Department of Biology and Environmental Sciences, Linnaeus University, Kalmar, Sweden
| | - Anders Forsman
- Department of Biology and Environmental Sciences, Linnaeus University, Kalmar, Sweden
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Buchner D, Sinclair JS, Ayasse M, Beermann AJ, Buse J, Dziock F, Enss J, Frenzel M, Hörren T, Li Y, Monaghan MT, Morkel C, Müller J, Pauls SU, Richter R, Scharnweber T, Sorg M, Stoll S, Twietmeyer S, Weisser WW, Wiggering B, Wilmking M, Zotz G, Gessner MO, Haase P, Leese F. Upscaling biodiversity monitoring: Metabarcoding estimates 31,846 insect species from Malaise traps across Germany. Mol Ecol Resour 2024:e14023. [PMID: 39364584 DOI: 10.1111/1755-0998.14023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 09/05/2024] [Accepted: 09/12/2024] [Indexed: 10/05/2024]
Abstract
Mitigating ongoing losses of insects and their key functions (e.g. pollination) requires tracking large-scale and long-term community changes. However, doing so has been hindered by the high diversity of insect species that requires prohibitively high investments of time, funding and taxonomic expertise when addressed with conventional tools. Here, we show that these concerns can be addressed through a comprehensive, scalable and cost-efficient DNA metabarcoding workflow. We use 1815 samples from 75 Malaise traps across Germany from 2019 and 2020 to demonstrate how metabarcoding can be incorporated into large-scale insect monitoring networks for less than 50 € per sample, including supplies, labour and maintenance. We validated the detected species using two publicly available databases (GBOL and GBIF) and the judgement of taxonomic experts. With an average of 1.4 M sequence reads per sample we uncovered 10,803 validated insect species, of which 83.9% were represented by a single Operational Taxonomic Unit (OTU). We estimated another 21,043 plausible species, which we argue either lack a reference barcode or are undescribed. The total of 31,846 species is similar to the number of insect species known for Germany (~35,500). Because Malaise traps capture only a subset of insects, our approach identified many species likely unknown from Germany or new to science. Our reproducible workflow (~80% OTU-similarity among years) provides a blueprint for large-scale biodiversity monitoring of insects and other biodiversity components in near real time.
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Affiliation(s)
- Dominik Buchner
- Aquatic Ecosystem Research, University of Duisburg Essen, Essen, Germany
| | - James S Sinclair
- Senckenberg Research Institute and Natural History Museum Frankfurt, Gelnhausen, Germany
| | - Manfred Ayasse
- Institute of Evolutionary Ecology and Conservation Genomics, University of Ulm, Ulm, Germany
| | - Arne J Beermann
- Aquatic Ecosystem Research, University of Duisburg Essen, Essen, Germany
- Centre for Water and Environmental Research (ZWU), Essen, Germany
| | - Jörn Buse
- Black Forest National Park, Freudenstadt, Germany
| | - Frank Dziock
- University of Applied Sciences HTW Dresden, Dresden, Germany
| | - Julian Enss
- Centre for Water and Environmental Research (ZWU), Essen, Germany
- Entomological Society Krefeld, Krefeld, Germany
- Faculty of Biology, University of Duisburg Essen, Essen, Germany
| | - Mark Frenzel
- Helmholtz Centre for Environmental Research-UFZ, Department of Community Ecology, Halle, Germany
| | | | - Yuanheng Li
- Aquatic Ecosystem Research, University of Duisburg Essen, Essen, Germany
| | - Michael T Monaghan
- Department of Evolutionary and Integrative Ecology, Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Berlin, Germany
- Institute of Biology, Freie Universität Berlin, Berlin, Germany
| | - Carsten Morkel
- Kellerwald-Edersee National Park, Bad Wildungen, Germany
| | - Jörg Müller
- Field Station Fabrikschleichach, Department of Animal Ecology and Tropical Biology, Julius-Maximilians-Universität Würzburg, Würzburg, Germany
- Bavarian Forest National Park, Grafenau, Germany
| | - Steffen U Pauls
- Senckenberg Research Institute and Natural History Museum Frankfurt, Frankfurt am Main, Germany
- LOEWE Centre for Translational Biodiversity Genomics, Frankfurt am Main, Germany
- Institute for Insect Biotechnology, Justus-Liebig-University Gießen, Gießen, Germany
| | - Ronny Richter
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Systematic Botany and Functional Biodiversity, Institute for Biology, Leipzig University, Leipzig, Germany
| | - Tobias Scharnweber
- Institute for Botany and Landscape Ecology, Greifswald University, Greifswald, Germany
| | - Martin Sorg
- Entomological Society Krefeld, Krefeld, Germany
| | - Stefan Stoll
- Faculty of Biology, University of Duisburg Essen, Essen, Germany
- Environmental Campus Birkenfeld, University of Applied Sciences Trier, Hoppstädten-Weiersbach, Germany
| | | | - Wolfgang W Weisser
- Terrestrial Ecology Research Group, Department of Life Science Systems, School of Life Sciences, Technische Universität München, Freising-Weihenstephan, Germany
| | | | - Martin Wilmking
- Institute for Botany and Landscape Ecology, Greifswald University, Greifswald, Germany
| | - Gerhard Zotz
- Institute of Biology and Environmental Sciences, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany
| | - Mark O Gessner
- Department of Plankton and Microbial Ecology, Leibniz Institute of Freshwater Ecology & Inland Fisheries (IGB), Stechlin, Germany
- Department of Ecology, Berlin Institute of Technology (TU Berlin), Berlin, Germany
| | - Peter Haase
- Senckenberg Research Institute and Natural History Museum Frankfurt, Gelnhausen, Germany
- Centre for Water and Environmental Research (ZWU), Essen, Germany
- Faculty of Biology, University of Duisburg Essen, Essen, Germany
| | - Florian Leese
- Aquatic Ecosystem Research, University of Duisburg Essen, Essen, Germany
- Centre for Water and Environmental Research (ZWU), Essen, Germany
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Svenningsen CS, Schigel D. Sharing insect data through GBIF: novel monitoring methods, opportunities and standards. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230104. [PMID: 38705176 PMCID: PMC11070266 DOI: 10.1098/rstb.2023.0104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 03/12/2024] [Indexed: 05/07/2024] Open
Abstract
Technological advancements in biological monitoring have facilitated the study of insect communities at unprecedented spatial scales. The progress allows more comprehensive coverage of the diversity within a given area while minimizing disturbance and reducing the need for extensive human labour. Compared with traditional methods, these novel technologies offer the opportunity to examine biological patterns that were previously beyond our reach. However, to address the pressing scientific inquiries of the future, data must be easily accessible, interoperable and reusable for the global research community. Biodiversity information standards and platforms provide the necessary infrastructure to standardize and share biodiversity data. This paper explores the possibilities and prerequisites of publishing insect data obtained through novel monitoring methods through GBIF, the most comprehensive global biodiversity data infrastructure. We describe the essential components of metadata standards and existing data standards for occurrence data on insects, including data extensions. By addressing the current opportunities, limitations, and future development of GBIF's publishing framework, we hope to encourage researchers to both share data and contribute to the further development of biodiversity data standards and publishing models. Wider commitments to open data initiatives will promote data interoperability and support cross-disciplinary scientific research and key policy indicators. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.
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Affiliation(s)
- Cecilie S. Svenningsen
- Global Biodiversity Information Facility, Universitetsparken 15, 2100 København Ø, Denmark
| | - Dmitry Schigel
- Global Biodiversity Information Facility, Universitetsparken 15, 2100 København Ø, Denmark
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Cheng R, Luo A, Orr M, Ge D, Hou Z, Qu Y, Guo B, Zhang F, Sha Z, Zhao Z, Wang M, Shi X, Han H, Zhou Q, Li Y, Liu X, Shao C, Zhang A, Zhou X, Zhu C. Cryptic diversity begets challenges and opportunities in biodiversity research. Integr Zool 2024. [PMID: 38263700 DOI: 10.1111/1749-4877.12809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
Abstract
How many species of life are there on Earth? This is a question that we want to know but cannot yet answer. Some scholars speculate that the number of species may reach 2.2 billion when considering cryptic diversity and that each morphology-based insect species may contain an average of 3.1 cryptic species. With nearly two million described species, such high estimates of cryptic diversity would suggest that cryptic species are widespread. The development of molecular species delimitation has led to the discovery of a large number of cryptic species, and cryptic biodiversity has gradually entered our field of vision and attracted more attention. This paper introduces the concept of cryptic species, how they evolve, and methods by which they may be discovered and confirmed, and provides theoretical and methodological guidance for the study of hidden species. A workflow of how to confirm cryptic species is provided. In addition, the importance and reliability of multi-evidence-based integrated taxonomy are reaffirmed as a way to better standardize decision-making processes. Special focus on cryptic diversity and increased funding for taxonomy is needed to ensure that cryptic species in hyperdiverse groups are discoverable and described. An increased focus on cryptic species in the future will naturally arise as more difficult groups are studied, and thereby, we may finally better understand the rules governing the evolution and maintenance of cryptic biodiversity.
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Affiliation(s)
- Rui Cheng
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Arong Luo
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Michael Orr
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Entomologie, Staatliches Museum für Naturkunde Stuttgart, Stuttgart, Germany
| | - Deyan Ge
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Zhong'e Hou
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Yanhua Qu
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Baocheng Guo
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Feng Zhang
- College of Plant Protection, Nanjing Agricultural University, Nanjing, China
| | - Zhongli Sha
- Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China
| | - Zhe Zhao
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Mingqiang Wang
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Xiaoyu Shi
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Hongxiang Han
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Qingsong Zhou
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Yuanning Li
- Institute of Oceanography, Shandong University, Qingdao, China
| | - Xingyue Liu
- Department of Entomology, China Agricultural University, Beijing, China
| | - Chen Shao
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Aibing Zhang
- College of Life Science, Capital Normal University, Beijing, China
| | - Xin Zhou
- Department of Entomology, China Agricultural University, Beijing, China
| | - Chaodong Zhu
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Integrated Pest Management, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences/International College, University of Chinese Academy of Sciences, Beijing, China
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Li M, Lei T, Wang G, Zhang D, Liu H, Zhang Z. Monitoring insect biodiversity and comparison of sampling strategies using metabarcoding: A case study in the Yanshan Mountains, China. Ecol Evol 2023; 13:e10031. [PMID: 37091562 PMCID: PMC10121320 DOI: 10.1002/ece3.10031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 03/31/2023] [Accepted: 04/07/2023] [Indexed: 04/25/2023] Open
Abstract
Insects are the richest and most diverse group of animals and yet there remains a lack, not only of systematic research into their distribution across some key regions of the planet, but of standardized sampling strategies for their study. The Yanshan Mountains, being the boundary range between the Inner Mongolian Plateau and the North China Plain, present an indispensable piece of the insect biodiversity puzzle: both requiring systematic study and offering opportunities for the development of standardized methodologies. This is the first use of DNA metabarcoding to survey the insect biodiversity of the Yanshan Mountains. The study focuses on differences of community composition among samples collected via different methods and from different habitat types. In total, 74 bulk samples were collected from five habitat types (scrubland, woodland, wetland, farmland and grassland) using three collection methods (sweep netting, Malaise traps and light traps). After DNA extraction, PCR amplification, sequencing and diversity analysis were performed, a total of 7427 Operational Taxonomic Units (OTUs) at ≥97% sequence similarity level were delimited, of which 7083 OTUs were identified as belonging to Insecta. Orthoptera, Diptera, Coleoptera and Hemiptera were found to be the dominant orders according to community composition analysis. Nonmetric multidimensional scaling (NMDS) analysis based on Bray-Curtis distances revealed highly divergent estimates of insect community composition among samples differentiated by the collection method (R = .524802, p = .001), but nonsignificant difference among samples differentiated according to habitat (R = .051102, p = .078). The study therefore appears to indicate that the concurrent use of varied collection methods is essential to the accurate monitoring of insect biodiversity.
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Affiliation(s)
- Min Li
- College of Biological Science and TechnologyTaiyuan Normal UniversityJinzhongChina
| | - Ting Lei
- College of Biological Science and TechnologyTaiyuan Normal UniversityJinzhongChina
| | - Guobin Wang
- College of Biological Science and TechnologyTaiyuan Normal UniversityJinzhongChina
| | - Danli Zhang
- College of Biological Science and TechnologyTaiyuan Normal UniversityJinzhongChina
| | - Huaxi Liu
- Department of Life SciencesNatural History MuseumLondonUK
| | - Zhiwei Zhang
- College of Forestry, Shanxi Agricultural UniversityJinzhongChina
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Ouyang X, Fan Q, Chen A, Huang J. Effects of trunk injection with emamectin benzoate on arthropod diversity. PEST MANAGEMENT SCIENCE 2023; 79:935-946. [PMID: 36309931 DOI: 10.1002/ps.7264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 10/20/2022] [Accepted: 10/30/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Pine wood nematode is a major plant quarantine object in the world. Trunk injection is an effective method for controlling pests that cause disease. To evaluate the ecological safety of trunk injection with emamectin benzoates in forests of Pinus massoniana, the community diversity and community composition of soil arthropods and flying insects (Hymenoptera) were studied at different stages of trunk injection. RESULTS The dominant taxonomic groups of soil arthropods were Collembola (30.80%), Insecta (26.42%), and Arachnida (23.84%). The taxonomic groups of flying insects (Hymenoptera) were Ichneumonidae (48.94%), Formicidae (14.10%), and Braconidae (8.44%). Trunk injection with emamectin benzoate has no significant effect on the community diversity indices of total soil arthropods and flying insects (Hymenoptera). However, it has a significant effect on the community diversity indices of detritivores for soil arthropods. It changed the community composition of soil arthropods but did not impact the community composition of flying insects (Hymenoptera). Redundancy analysis of arthropod community structure and environmental variables showed that total potassium, residual of green leaf, and residual of litter leaf have a significant impact on the community structure of soil arthropods, and total phosphorus, total nitrogen, water content, organic matter, and total potassium have a significant impact on the community structure of flying insects (Hymenoptera). CONCLUSION Trunk injection with emamectin benzoate is safe for the ecological environment. This study provides a new insight into the field for the prevention and control of pine wood nematode disease, which is of great significance to forest management and pest control. © 2022 Society of Chemical Industry.
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Affiliation(s)
- Xianheng Ouyang
- School of Forestry and Biotechnology, Zhejiang A&F University, Hangzhou, China
| | - Qingbin Fan
- Key Laboratory of Desert and Desertification, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Anliang Chen
- School of Forestry and Biotechnology, Zhejiang A&F University, Hangzhou, China
| | - Junhao Huang
- School of Forestry and Biotechnology, Zhejiang A&F University, Hangzhou, China
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Liu C, Ashfaq M, Yin Y, Zhu Y, Wang Z, Cheng H, Hebert P. Using DNA metabarcoding to assess insect diversity in citrus orchards. PeerJ 2023; 11:e15338. [PMID: 37168534 PMCID: PMC10166080 DOI: 10.7717/peerj.15338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 04/11/2023] [Indexed: 05/13/2023] Open
Abstract
Background DNA metabarcoding is rapidly emerging as a cost-effective approach for large-scale biodiversity assessment and pest monitoring. The current study employed metabarcoding to assess insect diversity in citrus orchards in Ganzhou City, Jiangxi, China in both 2018 and 2019. Insects were sampled using Malaise traps deployed in three citrus orchards producing a total of 43 pooled monthly samples. Methods The Malaise trap samples were sequenced following DNA metabarcoding workflow. Generated sequences were curated and analyzed using two cloud databases and analytical platforms, the barcode of life data system (BOLD) and multiplex barcode research and visualization environment (mBRAVE). Results These platforms assigned the sequences to 2,141 barcode index numbers (BINs), a species proxy. Most (63%) of the BINs were shared among the three sampling sites while BIN sharing between any two sites did not exceed 71%. Shannon diversity index (H') showed a similar pattern of BIN assortment at the three sampling sites. Beta diversity analysis by Jaccard similarity coefficient (J) and Bray-Curtis distance matrix (BC) revealed a high level of BIN similarity among the three sites (J = 0.67-0.68; BC = 0.19-0.20). Comparison of BIN records against all those on BOLD made it possible to identify 40% of the BINs to a species, 57% to a genus, 97% to a family and 99% to an order. BINs which received a species match on BOLD were placed in one of four categories based on this assignment: pest, parasitoid, predator, or pollinator. As this study provides the first baseline data on insect biodiversity in Chinese citrus plantations, it is a valuable resource for research in a broad range of areas such as pest management and monitoring beneficial insects in citrus gardens.
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Affiliation(s)
- Chenxi Liu
- Sino-American Biological Control Laboratory, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Muhammad Ashfaq
- Centre for Biodiversity Genomics and Department of Integrative Biology, University of Guelph, Guelph, Ontario, Canada
| | - Yanfang Yin
- Sino-American Biological Control Laboratory, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yanjuan Zhu
- Sino-American Biological Control Laboratory, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhen Wang
- Sino-American Biological Control Laboratory, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Hongmei Cheng
- Sino-American Biological Control Laboratory, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Paul Hebert
- Centre for Biodiversity Genomics and Department of Integrative Biology, University of Guelph, Guelph, Ontario, Canada
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Ottati S, Eberle J, Rulik B, Köhler F, Ahrens D. From DNA barcodes to ecology: Meta-analysis of central European beetles reveal link with species ecology but also to data pattern and gaps. Ecol Evol 2022; 12:e9650. [PMID: 36568864 PMCID: PMC9771709 DOI: 10.1002/ece3.9650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 11/23/2022] [Accepted: 12/02/2022] [Indexed: 12/24/2022] Open
Abstract
DNA barcoding has been used worldwide to identify biological specimens and to delimit species. It represents a cost-effective, fast, and efficient way to assess biodiversity with help of the public Barcode of Life Database (BOLD) accounting for more than 236,000 animal species and more than 10 million barcode sequences. Here, we performed a meta-analysis of available barcode data of central European Coleoptera to detect intraspecific genetic patterns among ecological groups in relation to geographic distance with the aim to investigate a possible link between infraspecific variation and species ecology. We collected information regarding feeding style, body size, as well as habitat and biotope preferences. Mantel tests and two variants of Procrustes analysis, both involving the Principal Coordinates Neighborhood Matrices (PCNM) approach, were applied on genetic and geographic distance matrices. However, significance levels were too low to further use the outcome for further trait investigation: these were in mean for all ecological guilds only 7.5, 9.4, or 15.6% for PCNM + PCA, NMDS + PCA, and Mantel test, respectively, or at best 28% for a single guild. Our study confirmed that certain ecological traits were associated with higher species diversity and foster stronger genetic differentiation. Results suggest that increased numbers of species, sampling localities, and specimens for a chosen area of interest may give new insights to explore barcode data and species ecology for the scope of conservation on a larger scale. We performed a meta-analysis of available barcode data of central European beetles to detect intraspecific genetic patterns among ecological groups in relation to geographic distance, regarding feeding style, body size, as well as habitat and biotope preferences. Our study confirmed that certain ecological traits were associated with higher species diversity and foster stronger genetic differentiation. However, significance levels were too low to further use the outcome for further trait investigation.
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Affiliation(s)
- Sara Ottati
- Zoologisches Forschungsmuseum A. Koenig (LIB)BonnGermany
- Department of Agricultural, Forest and Food Sciences (DISAFA)University of TorinoTurinItaly
| | - Jonas Eberle
- Zoologisches Forschungsmuseum A. Koenig (LIB)BonnGermany
- Department of Environment & BiodiversityUniversity of SalzburgSalzburgAustria
| | - Björn Rulik
- Department of Agricultural, Forest and Food Sciences (DISAFA)University of TorinoTurinItaly
| | - Frank Köhler
- Coleopterological Research OfficeBornheimGermany
| | - Dirk Ahrens
- Zoologisches Forschungsmuseum A. Koenig (LIB)BonnGermany
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