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Bell KL, Turo KJ, Lowe A, Nota K, Keller A, Encinas‐Viso F, Parducci L, Richardson RT, Leggett RM, Brosi BJ, Burgess KS, Suyama Y, de Vere N. Plants, pollinators and their interactions under global ecological change: The role of pollen DNA metabarcoding. Mol Ecol 2023; 32:6345-6362. [PMID: 36086900 PMCID: PMC10947134 DOI: 10.1111/mec.16689] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 08/18/2022] [Accepted: 08/30/2022] [Indexed: 11/28/2022]
Abstract
Anthropogenic activities are triggering global changes in the environment, causing entire communities of plants, pollinators and their interactions to restructure, and ultimately leading to species declines. To understand the mechanisms behind community shifts and declines, as well as monitoring and managing impacts, a global effort must be made to characterize plant-pollinator communities in detail, across different habitat types, latitudes, elevations, and levels and types of disturbances. Generating data of this scale will only be feasible with rapid, high-throughput methods. Pollen DNA metabarcoding provides advantages in throughput, efficiency and taxonomic resolution over traditional methods, such as microscopic pollen identification and visual observation of plant-pollinator interactions. This makes it ideal for understanding complex ecological networks and their responses to change. Pollen DNA metabarcoding is currently being applied to assess plant-pollinator interactions, survey ecosystem change and model the spatiotemporal distribution of allergenic pollen. Where samples are available from past collections, pollen DNA metabarcoding has been used to compare contemporary and past ecosystems. New avenues of research are possible with the expansion of pollen DNA metabarcoding to intraspecific identification, analysis of DNA in ancient pollen samples, and increased use of museum and herbarium specimens. Ongoing developments in sequencing technologies can accelerate progress towards these goals. Global ecological change is happening rapidly, and we anticipate that high-throughput methods such as pollen DNA metabarcoding are critical for understanding the evolutionary and ecological processes that support biodiversity, and predicting and responding to the impacts of change.
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Affiliation(s)
- Karen L. Bell
- CSIRO Health & Biosecurity and CSIRO Land & WaterFloreatWAAustralia
- School of Biological SciencesUniversity of Western AustraliaCrawleyWAAustralia
| | - Katherine J. Turo
- Department of Ecology, Evolution, and Natural ResourcesRutgers UniversityNew BrunswickNew JerseyUSA
| | | | - Kevin Nota
- Department of Ecology and GeneticsEvolutionary Biology Centre, Uppsala UniversityUppsalaSweden
| | - Alexander Keller
- Organismic and Cellular Networks, Faculty of BiologyBiocenter, Ludwig‐Maximilians‐Universität MünchenPlaneggGermany
| | - Francisco Encinas‐Viso
- Centre for Australian National Biodiversity ResearchCSIROBlack MountainAustralian Capital TerritoryAustralia
| | - Laura Parducci
- Department of Ecology and GeneticsEvolutionary Biology Centre, Uppsala UniversityUppsalaSweden
- Department of Environmental BiologySapienza University of RomeRomeItaly
| | - Rodney T. Richardson
- Appalachian LaboratoryUniversity of Maryland Center for Environmental ScienceFrostburgMarylandUSA
| | | | - Berry J. Brosi
- Department of BiologyUniversity of WashingtonSeattleWashingtonUSA
| | - Kevin S. Burgess
- Department of BiologyCollege of Letters and Sciences, Columbus State University, University System of GeorgiaAtlantaGeorgiaUSA
| | - Yoshihisa Suyama
- Field Science CenterGraduate School of Agricultural Science, Tohoku UniversityOsakiMiyagiJapan
| | - Natasha de Vere
- Natural History Museum of DenmarkUniversity of CopenhagenCopenhagenDenmark
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Pansu J, Hutchinson MC, Anderson TM, Te Beest M, Begg CM, Begg KS, Bonin A, Chama L, Chamaillé-Jammes S, Coissac E, Cromsigt JPGM, Demmel MY, Donaldson JE, Guyton JA, Hansen CB, Imakando CI, Iqbal A, Kalima DF, Kerley GIH, Kurukura S, Landman M, Long RA, Munuo IN, Nutter CM, Parr CL, Potter AB, Siachoono S, Taberlet P, Waiti E, Kartzinel TR, Pringle RM. The generality of cryptic dietary niche differences in diverse large-herbivore assemblages. Proc Natl Acad Sci U S A 2022; 119:e2204400119. [PMID: 35994662 DOI: 10.1073/pnas.2204400119] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Ecological niche differences are necessary for stable species coexistence but are often difficult to discern. Models of dietary niche differentiation in large mammalian herbivores invoke the quality, quantity, and spatiotemporal distribution of plant tissues and growth forms but are agnostic toward food plant species identity. Empirical support for these models is variable, suggesting that additional mechanisms of resource partitioning may be important in sustaining large-herbivore diversity in African savannas. We used DNA metabarcoding to conduct a taxonomically explicit analysis of large-herbivore diets across southeastern Africa, analyzing ∼4,000 fecal samples of 30 species from 10 sites in seven countries over 6 y. We detected 893 food plant taxa from 124 families, but just two families-grasses and legumes-accounted for the majority of herbivore diets. Nonetheless, herbivore species almost invariably partitioned food plant taxa; diet composition differed significantly in 97% of pairwise comparisons between sympatric species, and dissimilarity was pronounced even between the strictest grazers (grass eaters), strictest browsers (nongrass eaters), and closest relatives at each site. Niche differentiation was weakest in an ecosystem recovering from catastrophic defaunation, indicating that food plant partitioning is driven by species interactions, and was stronger at low rainfall, as expected if interspecific competition is a predominant driver. Diets differed more between browsers than grazers, which predictably shaped community organization: Grazer-dominated trophic networks had higher nestedness and lower modularity. That dietary differentiation is structured along taxonomic lines complements prior work on how herbivores partition plant parts and patches and suggests that common mechanisms govern herbivore coexistence and community assembly in savannas.
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Cuff JP, Kitson JJN, Hemprich-Bennett D, Tercel MPTG, Browett SS, Evans DM. The predator problem and PCR primers in molecular dietary analysis: swamped or silenced; depth or breadth? Mol Ecol Resour 2022; 23:41-51. [PMID: 36017818 PMCID: PMC10087656 DOI: 10.1111/1755-0998.13705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 08/11/2022] [Accepted: 08/24/2022] [Indexed: 11/28/2022]
Abstract
Dietary metabarcoding has vastly improved our ability to analyse the diets of animals, but it is hampered by a plethora of technical limitations including potentially reduced data output due to the disproportionate amplification of the DNA of the focal predator, here termed 'the predator problem'. We review the various methods commonly used to overcome this problem, from deeper sequencing to exclusion of predator DNA during PCR, and how they may interfere with increasingly common multi-predator-taxon studies. We suggest that multi-primer approaches with an emphasis on achieving both depth and breadth of prey detections may overcome the issue to some extent, although multi-taxon studies require further consideration, as highlighted by an empirical example. We also review several alternative methods for reducing the prevalence of predator DNA that are conceptually promising but require additional empirical examination. The predator problem is a key constraint on molecular dietary analyses but, through this synthesis, we hope to guide researchers in overcoming this in an effective and pragmatic way.
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Affiliation(s)
- Jordan P Cuff
- School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - James J N Kitson
- School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, UK
| | | | - Maximillian P T G Tercel
- School of Biosciences, Cardiff University, Cardiff, UK.,Durrell Wildlife Conservation Trust, Les Augrès Manor, La Profonde Rue, Trinity, Jersey, JE3 5BP, Channel Islands
| | - Samuel S Browett
- Ecosystems and Environment Research Centre, School of Science, Engineering and Environment, University of Salford, Salford, UK
| | - Darren M Evans
- School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, UK
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4
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van Klink R, August T, Bas Y, Bodesheim P, Bonn A, Fossøy F, Høye TT, Jongejans E, Menz MHM, Miraldo A, Roslin T, Roy HE, Ruczyński I, Schigel D, Schäffler L, Sheard JK, Svenningsen C, Tschan GF, Wäldchen J, Zizka VMA, Åström J, Bowler DE. Emerging technologies revolutionise insect ecology and monitoring. Trends Ecol Evol 2022; 37:872-885. [PMID: 35811172 DOI: 10.1016/j.tree.2022.06.001] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 05/26/2022] [Accepted: 06/07/2022] [Indexed: 12/30/2022]
Abstract
Insects are the most diverse group of animals on Earth, but their small size and high diversity have always made them challenging to study. Recent technological advances have the potential to revolutionise insect ecology and monitoring. We describe the state of the art of four technologies (computer vision, acoustic monitoring, radar, and molecular methods), and assess their advantages, current limitations, and future potential. We discuss how these technologies can adhere to modern standards of data curation and transparency, their implications for citizen science, and their potential for integration among different monitoring programmes and technologies. We argue that they provide unprecedented possibilities for insect ecology and monitoring, but it will be important to foster international standards via collaboration.
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Affiliation(s)
- Roel van Klink
- German Centre for Integrative Biodiversity Research (iDiv) Halle Jena Leipzig, Puschstrasse 4, 04103, Leipzig, Germany; Martin Luther University-Halle Wittenberg, Department of Computer Science, 06099, Halle (Saale), Germany.
| | - Tom August
- UK Centre for Ecology & Hydrology, Benson Lane, Wallingford, OX10 8BB, UK
| | - Yves Bas
- Centre d'Écologie et des Sciences de la Conservation, Muséum National d'Histoire Naturelle, Paris, France; CEFE, Université Montpellier, CNRS, EPHE, IRD, Montpellier, France
| | - Paul Bodesheim
- Friedrich Schiller University Jena, Computer Vision Group, Ernst-Abbe-Platz 2, 07743, Jena, Germany
| | - Aletta Bonn
- German Centre for Integrative Biodiversity Research (iDiv) Halle Jena Leipzig, Puschstrasse 4, 04103, Leipzig, Germany; Helmholtz - Centre for Environmental Research - UFZ, Permoserstrasse 15, 04318, Leipzig, Germany; Friedrich Schiller University Jena, Institute of Biodiversity, Dornburger Strasse 159, 07743, Jena, Germany
| | - Frode Fossøy
- Norwegian Institute for Nature Research, P.O. Box 5685 Torgarden, 7485, Trondheim, Norway
| | - Toke T Høye
- Aarhus University, Department of Ecoscience and Arctic Research Centre, C.F. Møllers Allé 8, 8000, Aarhus, Denmark
| | - Eelke Jongejans
- Radboud University, Animal Ecology and Physiology, Heyendaalseweg 135, 6525, AJ, Nijmegen, The Netherlands; Netherlands Institute of Ecology, Animal Ecology, Droevendaalsesteeg 10, 6708 PB, Wageningen, The Netherlands
| | - Myles H M Menz
- Max Planck Institute for Animal Behaviour, Department of Migration, Am Obstberg 1, 78315, Radolfzell, Germany; College of Science and Engineering, James Cook University, Townsville, Qld, Australia
| | - Andreia Miraldo
- Swedish Museum of Natural Sciences, Department of Bioinformatics and Genetics, Frescativägen 40, 114 18, Stockholm, Sweden
| | - Tomas Roslin
- Swedish University of Agricultural Sciences (SLU), Department of Ecology, Ulls väg 18B, 75651, Uppsala, Sweden
| | - Helen E Roy
- UK Centre for Ecology & Hydrology, Benson Lane, Wallingford, OX10 8BB, UK
| | - Ireneusz Ruczyński
- Mammal Research Institute, Polish Academy of Sciences, Stoczek 1, 17-230, Białowieża, Poland
| | - Dmitry Schigel
- Global Biodiversity Information Facility (GBIF), Universitetsparken 15, 2100, Copenhagen, Denmark
| | - Livia Schäffler
- Leibniz Institute for the Analysis of Biodiversity Change, Museum Koenig Bonn, Adenauerallee 127, 53113, Bonn, Germany
| | - Julie K Sheard
- German Centre for Integrative Biodiversity Research (iDiv) Halle Jena Leipzig, Puschstrasse 4, 04103, Leipzig, Germany; Helmholtz - Centre for Environmental Research - UFZ, Permoserstrasse 15, 04318, Leipzig, Germany; Friedrich Schiller University Jena, Institute of Biodiversity, Dornburger Strasse 159, 07743, Jena, Germany; University of Copenhagen, Centre for Macroecology, Evolution and Climate, Globe Institute, Universitetsparken 15, bld. 3, 2100, Copenhagen, Denmark
| | - Cecilie Svenningsen
- University of Copenhagen, Natural History Museum of Denmark, Øster Voldgade 5-7, 1350, Copenhagen, Denmark
| | - Georg F Tschan
- Leibniz Institute for the Analysis of Biodiversity Change, Museum Koenig Bonn, Adenauerallee 127, 53113, Bonn, Germany
| | - Jana Wäldchen
- German Centre for Integrative Biodiversity Research (iDiv) Halle Jena Leipzig, Puschstrasse 4, 04103, Leipzig, Germany; Max Planck Institute for Biogeochemistry, Department of Biogeochemical Integration, Hans-Knoell-Str. 10, 07745, Jena, Germany
| | - Vera M A Zizka
- Leibniz Institute for the Analysis of Biodiversity Change, Museum Koenig Bonn, Adenauerallee 127, 53113, Bonn, Germany
| | - Jens Åström
- Norwegian Institute for Nature Research, P.O. Box 5685 Torgarden, 7485, Trondheim, Norway
| | - Diana E Bowler
- German Centre for Integrative Biodiversity Research (iDiv) Halle Jena Leipzig, Puschstrasse 4, 04103, Leipzig, Germany; UK Centre for Ecology & Hydrology, Benson Lane, Wallingford, OX10 8BB, UK; Helmholtz - Centre for Environmental Research - UFZ, Permoserstrasse 15, 04318, Leipzig, Germany; Friedrich Schiller University Jena, Institute of Biodiversity, Dornburger Strasse 159, 07743, Jena, Germany
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Fernandes Magalhães de Oliveira H, Pinheiro RBP, Varassin IG, Rodríguez-Herrera B, Kuzmina M, Rossiter SJ, Clare EL. The structure of tropical bat-plant interaction networks during an extreme El Niño-Southern Oscillation event. Mol Ecol 2022; 31:1892-1906. [PMID: 35064726 PMCID: PMC9305221 DOI: 10.1111/mec.16363] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Revised: 01/06/2022] [Accepted: 01/14/2022] [Indexed: 11/28/2022]
Abstract
Interaction network structure reflects the ecological mechanisms acting within biological communities, which are affected by environmental conditions. In tropical forests, higher precipitation usually increases fruit production, which may lead frugivores to increase specialization, resulting in more modular and less nested animal–plant networks. In these ecosystems, El Niño is a major driver of precipitation, but we still lack knowledge of how species interactions change under this influence. To understand bat–plant network structure during an extreme El Niño‐Southern Oscillation event, we determined the links between plantivorous bat species and the plants they consume by DNA barcoding seeds and pulp in bat faeces. These interactions were recorded in the dry forest and rainforest of Costa Rica, during the dry and the wet seasons of an extreme El Niño year. From these we constructed seasonal and whole‐year bat–plant networks and analysed their structures and dissimilarities. In general, networks had low nestedness, had high modularity, and were dominated by one large compartment which included most species and interactions. Contrary to our expectations, networks were less nested and more modular in drier conditions, both in the comparison between forest types and between seasons. We suggest that increased competition, when resources are scarce during drier seasons and habitats, lead to higher resource partitioning among bats and thus higher modularity. Moreover, we have found similar network structures between dry and rainforests during El Niño and non‐El Niño years. Finally, most interaction dissimilarity among networks occurred due to interaction rewiring among species, potentially driven by seasonal changes in resource availability.
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Affiliation(s)
| | | | | | | | - Maria Kuzmina
- Centre for Biodiversity Genomics, Biodiversity Institute of Ontario, University of Guelph, Guelph, Canada
| | - Stephen James Rossiter
- School of Biological and Chemical Sciences, Queen Mary University of London, London, United Kingdom
| | - Elizabeth Lloyd Clare
- School of Biological and Chemical Sciences, Queen Mary University of London, London, United Kingdom.,Department of Biology, York University, Toronto, Ontario, Canada
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6
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Cuff JP, Windsor FM, Tercel MPTG, Kitson JJN, Evans DM. Overcoming the pitfalls of merging dietary metabarcoding into ecological networks. Methods Ecol Evol 2022. [DOI: 10.1111/2041-210x.13796] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Affiliation(s)
- Jordan P. Cuff
- School of Natural and Environmental Sciences Newcastle University Newcastle upon Tyne UK
| | - Fredric M. Windsor
- School of Natural and Environmental Sciences Newcastle University Newcastle upon Tyne UK
| | - Maximillian P. T. G. Tercel
- School of Biosciences Cardiff University Cardiff UK
- Durrell Wildlife Conservation Trust Jersey Channel Islands
| | - James J. N. Kitson
- School of Natural and Environmental Sciences Newcastle University Newcastle upon Tyne UK
| | - Darren M. Evans
- School of Natural and Environmental Sciences Newcastle University Newcastle upon Tyne UK
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7
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Mata VA, da Silva LP, Veríssimo J, Horta P, Raposeira H, McCracken GF, Rebelo H, Beja P. Combining DNA metabarcoding and ecological networks to inform conservation biocontrol by small vertebrate predators. Ecol Appl 2021; 31:e02457. [PMID: 34529299 PMCID: PMC9285058 DOI: 10.1002/eap.2457] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 04/22/2021] [Accepted: 05/20/2021] [Indexed: 06/04/2023]
Abstract
In multifunctional landscapes, diverse communities of flying vertebrate predators provide vital services of insect pest control. In such landscapes, conservation biocontrol should benefit service-providing species to enhance the flow, stability and resilience of pest control services supporting the production of food and fiber. However, this would require identifying key service providers, which may be challenging when multiple predators interact with multiple pests. Here we provide a framework to identify the functional role of individual species to pest control in multifunctional landscapes. First, we used DNA metabarcoding to provide detailed data on pest species predation by diverse predator communities. Then, these data were fed into an extensive network analysis, in which information relevant for conservation biocontrol is gained from parameters describing network structure (e.g., modularity) and species roles in such network (e.g., centrality, specialization). We applied our framework to a Mediterranean landscape, where 19 bat species were found to feed on 132 insect pest species. Metabarcoding data revealed potentially important bats that consumed insect pest species in high frequency and/or diversity. Network analysis showed a modular structure, indicating sets of bat species that are required to regulate specific sets of insect pests. A few generalist bats had particularly important roles, either at network or module levels. Extinction simulations highlighted six bats, including species of conservation concern, which were sufficient to ensure that over three-quarters of the pest species had at least one bat predator. Combining DNA metabarcoding and ecological network analysis provides a valuable framework to identify individual species within diverse predator communities that might have a disproportionate contribution to pest control services in multifunctional landscapes. These species can be regarded as candidate targets for conservation biocontrol, although additional information is needed to evaluate their actual effectiveness in pest regulation.
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Affiliation(s)
- Vanessa A. Mata
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório AssociadoCampus de Vairão, Universidade of PortoVairão4485‐661Portugal
- BIOPOLIS Program in Genomics, Biodiversity and Land PlanningCIBIO, Campus de VairãoVairão4485‐661Portugal
| | - Luis P. da Silva
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório AssociadoCampus de Vairão, Universidade of PortoVairão4485‐661Portugal
- BIOPOLIS Program in Genomics, Biodiversity and Land PlanningCIBIO, Campus de VairãoVairão4485‐661Portugal
| | - Joana Veríssimo
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório AssociadoCampus de Vairão, Universidade of PortoVairão4485‐661Portugal
- BIOPOLIS Program in Genomics, Biodiversity and Land PlanningCIBIO, Campus de VairãoVairão4485‐661Portugal
- Departamento de Biologia, Faculdade de CiênciasUniversidade do PortoPorto4099‐002Portugal
| | - Pedro Horta
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório AssociadoCampus de Vairão, Universidade of PortoVairão4485‐661Portugal
- BIOPOLIS Program in Genomics, Biodiversity and Land PlanningCIBIO, Campus de VairãoVairão4485‐661Portugal
- Departamento de Biologia, Faculdade de CiênciasUniversidade do PortoPorto4099‐002Portugal
| | - Helena Raposeira
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório AssociadoCampus de Vairão, Universidade of PortoVairão4485‐661Portugal
- BIOPOLIS Program in Genomics, Biodiversity and Land PlanningCIBIO, Campus de VairãoVairão4485‐661Portugal
- Departamento de Biologia, Faculdade de CiênciasUniversidade do PortoPorto4099‐002Portugal
| | - Gary F. McCracken
- Department of Ecology and Evolutionary BiologyUniversity of TennesseeKnoxvilleTennessee37996‐1610USA
| | - Hugo Rebelo
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório AssociadoCampus de Vairão, Universidade of PortoVairão4485‐661Portugal
- BIOPOLIS Program in Genomics, Biodiversity and Land PlanningCIBIO, Campus de VairãoVairão4485‐661Portugal
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório AssociadoInstituto Superior de Agronomia, Universidade de LisboaLisboa1349‐017Portugal
| | - Pedro Beja
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório AssociadoCampus de Vairão, Universidade of PortoVairão4485‐661Portugal
- BIOPOLIS Program in Genomics, Biodiversity and Land PlanningCIBIO, Campus de VairãoVairão4485‐661Portugal
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório AssociadoInstituto Superior de Agronomia, Universidade de LisboaLisboa1349‐017Portugal
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8
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Roslin T, Somervuo P, Pentinsaari M, Hebert PDN, Agda J, Ahlroth P, Anttonen P, Aspi J, Blagoev G, Blanco S, Chan D, Clayhills T, deWaard J, deWaard S, Elliot T, Elo R, Haapala S, Helve E, Ilmonen J, Hirvonen P, Ho C, Itämies J, Ivanov V, Jakovlev J, Juslén A, Jussila R, Kahanpää J, Kaila L, Jari-PekkaKaitila, Kakko A, Kakko I, Karhu A, Karjalainen S, Kjaerandsen J, Koskinen J, Laasonen EM, Laasonen L, Laine E, Lampila P, Levesque-Beaudin V, Lu L, Lähteenaro M, Majuri P, Malmberg S, Manjunath R, Martikainen P, Mattila J, McKeown J, Metsälä P, Miklasevskaja M, Miller M, Miskie R, Muinonen A, Veli-MattiMukkala, Naik S, Nikolova N, Nupponen K, Ovaskainen O, Österblad I, Paasivirta L, Pajunen T, Parkko P, Paukkunen J, Penttinen R, Perez K, Pohjoismäki J, Prosser S, Raekunnas M, Rahulan M, Rannisto M, Ratnasingham S, Raukko P, Rinne A, Rintala T, Miranda Romo S, Salmela J, Salokannel J, Savolainen R, Schulman L, Sihvonen P, Soliman D, Sones J, Steinke C, Ståhls G, Tabell J, Tiusanen M, Várkonyi G, Vesterinen EJ, Viitanen E, Vikberg V, Viitasaari M, Vilen J, Warne C, Wei C, Winqvist K, Zakharov E, Mutanen M. A molecular-based identification resource for the arthropods of Finland. Mol Ecol Resour 2021; 22:803-822. [PMID: 34562055 DOI: 10.1111/1755-0998.13510] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
To associate specimens identified by molecular characters to other biological knowledge, we need reference sequences annotated by Linnaean taxonomy. In this study, we (1) report the creation of a comprehensive reference library of DNA barcodes for the arthropods of an entire country (Finland), (2) publish this library, and (3) deliver a new identification tool for insects and spiders, as based on this resource. The reference library contains mtDNA COI barcodes for 11,275 (43%) of 26,437 arthropod species known from Finland, including 10,811 (45%) of 23,956 insect species. To quantify the improvement in identification accuracy enabled by the current reference library, we ran 1000 Finnish insect and spider species through the Barcode of Life Data system (BOLD) identification engine. Of these, 91% were correctly assigned to a unique species when compared to the new reference library alone, 85% were correctly identified when compared to BOLD with the new material included, and 75% with the new material excluded. To capitalize on this resource, we used the new reference material to train a probabilistic taxonomic assignment tool, FinPROTAX, scoring high success. For the full-length barcode region, the accuracy of taxonomic assignments at the level of classes, orders, families, subfamilies, tribes, genera, and species reached 99.9%, 99.9%, 99.8%, 99.7%, 99.4%, 96.8%, and 88.5%, respectively. The FinBOL arthropod reference library and FinPROTAX are available through the Finnish Biodiversity Information Facility (www.laji.fi) at https://laji.fi/en/theme/protax. Overall, the FinBOL investment represents a massive capacity-transfer from the taxonomic community of Finland to all sectors of society.
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Affiliation(s)
- Tomas Roslin
- Department of Ecology, Swedish University of Agricultural Sciences, Uppsala, Sweden.,Department of Agricultural Sciences, University of Helsinki, Helsinki, Finland
| | - Panu Somervuo
- Organismal and Evolutionary Biology Research Programme, University of Helsinki, Helsinki, Finland
| | - Mikko Pentinsaari
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | - Paul D N Hebert
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | - Jireh Agda
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | - Petri Ahlroth
- Finnish Environment Institute (SYKE), Helsinki, Finland
| | - Perttu Anttonen
- Institute of Biology/Geobotany and Botanical Garden, Martin Luther University Halle-Wittenberg, Halle, Germany.,German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
| | - Jouni Aspi
- Ecology and Genetics Research Unit, University of Oulu, Oulu, Finland
| | - Gergin Blagoev
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | - Santiago Blanco
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | - Dean Chan
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | | | - Jeremy deWaard
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | - Stephanie deWaard
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | - Tyler Elliot
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | - Riikka Elo
- Zoological Museum, Biodiversity Unit, University of Turku, Turku, Finland.,Zoology Unit, Finnish Museum of Natural History, University of Helsinki, Helsinki, Finland
| | | | | | - Jari Ilmonen
- Metsähallitus, Parks & Wildlife Finland, Vantaa, Finland
| | | | - Chris Ho
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | | | - Vladislav Ivanov
- Ecology and Genetics Research Unit, University of Oulu, Oulu, Finland
| | | | - Aino Juslén
- Finnish Museum of Natural History 'Luomus', University of Helsinki, Helsinki, Finland
| | | | - Jere Kahanpää
- Zoology Unit, Finnish Museum of Natural History, University of Helsinki, Helsinki, Finland
| | - Lauri Kaila
- Zoology Unit, Finnish Museum of Natural History, University of Helsinki, Helsinki, Finland
| | | | | | - Iiro Kakko
- Forssa Museum of Natural History, Forssa, Finland
| | | | | | - Jostein Kjaerandsen
- The Arctic University Museum of Norway, UiT -The Arctic University of Norway, Langnes, Tromsø, Norway
| | - Janne Koskinen
- Department of Agricultural Sciences, University of Helsinki, Helsinki, Finland.,Department of Environmental and Biological Sciences, University of Eastern Finland, Joensuu, Finland
| | | | | | | | | | | | - Liuqiong Lu
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | - Meri Lähteenaro
- Division of Systematics, Department of Zoology, Stockholm University, Stockholm, Sweden.,Department of Entomology, Swedish Museum of Natural History, Stockholm, Sweden
| | | | | | - Ramya Manjunath
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | | | | | - Jaclyn McKeown
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | | | | | - Meredith Miller
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | - Renee Miskie
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | | | | | - Suresh Naik
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | - Nadia Nikolova
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | | | - Otso Ovaskainen
- Organismal and Evolutionary Biology Research Programme, University of Helsinki, Helsinki, Finland.,Department of Biological and Environmental Science, University of Jyväskylä, Jyväskylä, Finland.,Department of Biology, Centre for Biodiversity Dynamics, Norwegian University of Science and Technology, Trondheim, Norway
| | | | | | - Timo Pajunen
- Finnish Museum of Natural History 'Luomus', University of Helsinki, Helsinki, Finland
| | | | - Juho Paukkunen
- Zoology Unit, Finnish Museum of Natural History, University of Helsinki, Helsinki, Finland
| | - Ritva Penttinen
- Zoological Museum, Biodiversity Unit, University of Turku, Turku, Finland.,Zoology Unit, Finnish Museum of Natural History, University of Helsinki, Helsinki, Finland
| | - Kate Perez
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | - Jaakko Pohjoismäki
- Department of Environmental and Biological Sciences, University of Eastern Finland, Joensuu, Finland
| | - Sean Prosser
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | | | - Miduna Rahulan
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | - Meeri Rannisto
- Finnish Museum of Natural History 'Luomus', University of Helsinki, Helsinki, Finland
| | | | | | | | | | | | - Jukka Salmela
- Regional Museum of Lapland, Arktikum, Rovaniemi, Finland.,Arctic Centre, University of Lapland, Rovaniemi, Finland
| | | | - Riitta Savolainen
- Organismal and Evolutionary Biology Research Programme, University of Helsinki, Helsinki, Finland
| | - Leif Schulman
- Finnish Environment Institute (SYKE), Helsinki, Finland.,Finnish Museum of Natural History 'Luomus', University of Helsinki, Helsinki, Finland
| | - Pasi Sihvonen
- Finnish Museum of Natural History 'Luomus', University of Helsinki, Helsinki, Finland
| | - Dina Soliman
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | - Jayme Sones
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | - Claudia Steinke
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | - Gunilla Ståhls
- Finnish Museum of Natural History 'Luomus', University of Helsinki, Helsinki, Finland
| | | | - Mikko Tiusanen
- Department of Agricultural Sciences, University of Helsinki, Helsinki, Finland
| | - Gergely Várkonyi
- Biodiversity Centre, Finnish Environment Institute SYKE, Kuhmo, Finland
| | - Eero J Vesterinen
- Department of Ecology, Swedish University of Agricultural Sciences, Uppsala, Sweden.,Department of Biology, University of Turku, Turku, Finland
| | | | | | | | | | - Connor Warne
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | - Catherine Wei
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | | | - Evgeny Zakharov
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | - Marko Mutanen
- Ecology and Genetics Research Unit, University of Oulu, Oulu, Finland
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9
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Runghen R, Poulin R, Monlleó-Borrull C, Llopis-Belenguer C. Network Analysis: Ten Years Shining Light on Host-Parasite Interactions. Trends Parasitol 2021; 37:445-455. [PMID: 33558197 DOI: 10.1016/j.pt.2021.01.005] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 01/15/2021] [Accepted: 01/16/2021] [Indexed: 12/24/2022]
Abstract
Biological interactions are key drivers of ecological and evolutionary processes. The complexity of such interactions hinders our understanding of ecological systems and our ability to make effective predictions in changing environments. However, network analysis allows us to better tackle the complexity of ecosystems because it extracts the properties of an ecological system according to the number and distribution of links among interacting entities. The number of studies using network analysis to solve ecological and evolutionary questions in parasitology has increased over the past decade. Here, we synthesise the contribution of network analysis toward disentangling host-parasite processes. Furthermore, we identify current trends in mainstream ecology and novel applications of network analysis that present opportunities for research on host-parasite interactions.
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Affiliation(s)
- Rogini Runghen
- Centre for Integrative Ecology, School of Biological Sciences, University of Canterbury, Private Bag 4800, 8140 Christchurch, New Zealand
| | - Robert Poulin
- Department of Zoology, University of Otago, 340 Great King Street, 9054 Dunedin, New Zealand
| | - Clara Monlleó-Borrull
- Cavanilles Institute of Biodiversity and Evolutionary Biology, University of Valencia, PO Box 22085, ES-46071, Valencia, Spain
| | - Cristina Llopis-Belenguer
- Cavanilles Institute of Biodiversity and Evolutionary Biology, University of Valencia, PO Box 22085, ES-46071, Valencia, Spain.
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10
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Bellekom B, Hackett TD, Lewis OT. A Network Perspective on the Vectoring of Human Disease. Trends Parasitol 2021; 37:391-400. [PMID: 33419670 DOI: 10.1016/j.pt.2020.12.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 11/25/2020] [Accepted: 12/01/2020] [Indexed: 12/25/2022]
Abstract
Blood-sucking insects are important vectors of disease, with biting Diptera (flies) alone transmitting diseases that cause an estimated 700 000 human deaths a year. Insect vectors also bite nonhuman hosts, linking them into host-biting networks. While the major vectors of prominent diseases, such as malaria, yellow fever, dengue, and Zika, are intensively studied, there has been limited focus on the wider interactions of biting insects with nonhuman hosts. Drawing on network analysis and visualisation approaches from food-web ecology, we discuss the value of a network perspective for understanding host-insect-disease interactions, with a focus on Diptera vectors. Potential applications include highlighting pathways of disease transmission, highlighting reservoirs of infection, and identifying emerging and previously unrecognised vectors.
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Affiliation(s)
- Ben Bellekom
- Department of Zoology, 11a Mansfield Road, Oxford OX1 3SZ, UK.
| | - Talya D Hackett
- Department of Zoology, 11a Mansfield Road, Oxford OX1 3SZ, UK
| | - Owen T Lewis
- Department of Zoology, 11a Mansfield Road, Oxford OX1 3SZ, UK
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11
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Meyer JM, Leempoel K, Losapio G, Hadly EA. Molecular Ecological Network Analyses: An Effective Conservation Tool for the Assessment of Biodiversity, Trophic Interactions, and Community Structure. Front Ecol Evol 2020. [DOI: 10.3389/fevo.2020.588430] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
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12
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Magalhães de Oliveira HF, Camargo NF, Hemprich-Bennett DR, Rodríguez-Herrera B, Rossiter SJ, Clare EL. Wing morphology predicts individual niche specialization in Pteronotus mesoamericanus (Mammalia: Chiroptera). PLoS One 2020; 15:e0232601. [PMID: 32392221 PMCID: PMC7213686 DOI: 10.1371/journal.pone.0232601] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 04/17/2020] [Indexed: 12/30/2022] Open
Abstract
Morphological variation between individuals can increase niche segregation and decrease intraspecific competition when heterogeneous individuals explore their environment in different ways. Among bat species, wing shape correlates with flight maneuverability and habitat use, with species that possess broader wings typically foraging in more cluttered habitats. However, few studies have investigated the role of morphological variation in bats for niche partitioning at the individual level. To determine the relationship between wing shape and diet, we studied a population of the insectivorous bat species Pteronotus mesoamericanus in the dry forest of Costa Rica. Individual diet was resolved using DNA metabarcoding, and bat wing shape was assessed using geometric morphometric analysis. Inter-individual variation in wing shape showed a significant relationship with both dietary dissimilarity based on Bray-Curtis estimates, and nestedness derived from an ecological network. Individual bats with broader and more rounded wings were found to feed on a greater diversity of arthropods (less nested) in comparison to individuals with triangular and pointed wings (more nested). We conclude that individual variation in bat wing morphology can impact foraging efficiency leading to the observed overall patterns of diet specialization and differentiation within the population.
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Affiliation(s)
- Hernani Fernandes Magalhães de Oliveira
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, Iowa, United States of America
- School of Biological and Chemical Sciences, Queen Mary University of London, London, England, United Kingdom
| | | | - David R. Hemprich-Bennett
- School of Biological and Chemical Sciences, Queen Mary University of London, London, England, United Kingdom
- Department of Zoology, University of Oxford, Oxford, England, United Kingdom
| | | | - Stephen J. Rossiter
- School of Biological and Chemical Sciences, Queen Mary University of London, London, England, United Kingdom
| | - Elizabeth L. Clare
- School of Biological and Chemical Sciences, Queen Mary University of London, London, England, United Kingdom
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13
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Rieseberg L, Geraldes A, Taberlet P. Editorial 2020. Mol Ecol 2020; 29:1-19. [DOI: 10.1111/mec.15328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Accepted: 12/06/2019] [Indexed: 11/27/2022]
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14
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Compson ZG, Monk WA, Hayden B, Bush A, O'Malley Z, Hajibabaei M, Porter TM, Wright MTG, Baker CJO, Al Manir MS, Curry RA, Baird DJ. Network-Based Biomonitoring: Exploring Freshwater Food Webs With Stable Isotope Analysis and DNA Metabarcoding. Front Ecol Evol 2019. [DOI: 10.3389/fevo.2019.00395] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
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15
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Roslin T, Traugott M, Jonsson M, Stone GN, Creer S, Symondson WOC. Introduction: Special issue on species interactions, ecological networks and community dynamics - Untangling the entangled bank using molecular techniques. Mol Ecol 2019; 28:157-164. [PMID: 30548494 DOI: 10.1111/mec.14974] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Revised: 11/23/2018] [Accepted: 12/05/2018] [Indexed: 02/06/2023]
Affiliation(s)
- Tomas Roslin
- Department of Ecology, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Michael Traugott
- Mountain Agriculture Research Unit, Institute of Ecology, University of Innsbruck, Innsbruck, Austria
| | - Mattias Jonsson
- Department of Ecology, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Graham N Stone
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Simon Creer
- Molecular Ecology and Fisheries Genetics Laboratory, School of Natural Sciences, Bangor University, Gwynedd, UK
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16
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Whitaker MRL, Baker CCM, Salzman SM, Martins DJ, Pierce NE. Combining stable isotope analysis with DNA metabarcoding improves inferences of trophic ecology. PLoS One 2019; 14:e0219070. [PMID: 31329604 DOI: 10.1371/journal.pone.0219070] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2018] [Accepted: 06/14/2019] [Indexed: 12/31/2022] Open
Abstract
Knowing what animals eat is fundamental to our ability to understand and manage biodiversity and ecosystems, but researchers often must rely on indirect methods to infer trophic position and food intake. Using an approach that combines evidence from stable isotope analysis and DNA metabarcoding, we assessed the diet and trophic position of Anthene usamba butterflies, for which there are no known direct observations of larval feeding. An earlier study that analyzed adults rather than caterpillars of A. usamba inferred that this butterfly was aphytophagous, but we found that the larval guts of A. usamba and two known herbivorous lycaenid species contain chloroplast 16S sequences. Moreover, chloroplast barcoding revealed high sequence similarity between chloroplasts found in A. usamba guts and the chloroplasts of the Vachellia drepanolobium trees on which the caterpillars live. Stable isotope analysis provided further evidence that A. usamba caterpillars feed on V. drepanolobium, and the possibilities of strict herbivory versus limited omnivory in this species are discussed. These results highlight the importance of combining multiple approaches and considering ontogeny when using stable isotopes to infer trophic ecology where direct observations are difficult or impossible.
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17
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Gordon R, Ivens S, Ammerman LK, Fenton MB, Littlefair JE, Ratcliffe JM, Clare EL. Molecular diet analysis finds an insectivorous desert bat community dominated by resource sharing despite diverse echolocation and foraging strategies. Ecol Evol 2019; 9:3117-3129. [PMID: 30962885 PMCID: PMC6434550 DOI: 10.1002/ece3.4896] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2018] [Revised: 12/12/2018] [Accepted: 12/13/2018] [Indexed: 01/05/2023] Open
Abstract
Interspecific differences in traits can alter the relative niche use of species within the same environment. Bats provide an excellent model to study niche use because they use a wide variety of behavioral, acoustic, and morphological traits that may lead to multi-species, functional groups. Predatory bats have been classified by their foraging location (edge, clutter, open space), ability to use aerial hawking or substrate gleaning and echolocation call design and flexibility, all of which may dictate their prey use. For example, high frequency, broadband calls do not travel far but offer high object resolution while high intensity, low frequency calls travel further but provide lower resolution. Because these behaviors can be flexible, four behavioral categories have been proposed: (a) gleaning, (b) behaviorally flexible (gleaning and hawking), (c) clutter-tolerant hawking, and (d) open space hawking. Many recent studies of diet in bats use molecular tools to identify prey but mainly focus on one or two species in isolation; few studies provide evidence for substantial differences in prey use despite the many behavioral, acoustic, and morphological differences. Here, we analyze the diet of 17 sympatric species in the Chihuahuan desert and test the hypothesis that peak echolocation frequency and behavioral categories are linked to differences in diet. We find no significant correlation between dietary richness and echolocation peak frequency though it spanned close to 100 kHz across species. Our data, however, suggest that bats which use both gleaning and hawking strategies have the broadest diets and are most differentiated from clutter-tolerant aerial hawking species.
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Affiliation(s)
- Rowena Gordon
- School of Biological and Chemical SciencesQueen Mary University of LondonLondonUK
| | - Sally Ivens
- School of Biological and Chemical SciencesQueen Mary University of LondonLondonUK
| | | | - M. Brock Fenton
- Department of BiologyUniversity of Western OntarioLondonOntarioCanada
| | - Joanne E. Littlefair
- School of Biological and Chemical SciencesQueen Mary University of LondonLondonUK
- Department of BiologyMcGill UniversityMontréalQuébecCanada
| | - John M. Ratcliffe
- Department of BiologyUniversity of Toronto MississaugaMississaugaOntarioCanada
| | - Elizabeth L. Clare
- School of Biological and Chemical SciencesQueen Mary University of LondonLondonUK
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