Literature DB >> 27987263

eDNA metabarcoding: a promising method for anuran surveys in highly diverse tropical forests.

Carla M Lopes1, Thais Sasso2, Alice Valentini3, Tony Dejean3, Marcio Martins2, Kelly R Zamudio4, Célio F B Haddad1.   

Abstract

Understanding the geographical distribution and community composition of species is crucial to monitor species persistence and define effective conservation strategies. Environmental DNA (eDNA) has emerged as a powerful noninvasive tool for species detection. However, most eDNA survey methods have been developed and applied in temperate zones. We tested the feasibility of using eDNA to survey anurans in tropical streams in the Brazilian Atlantic forest and compared the results with short-term visual and audio surveys. We detected all nine species known to inhabit our focal streams with one single visit for eDNA sampling. We found a higher proportion of sequence reads and larger number of positive PCR replicates for more common species and for those with life cycles closely associated with the streams, factors that may contribute to increased release of DNA in the water. However, less common species were also detected in eDNA samples, demonstrating the detection power of this method. Filtering larger volumes of water resulted in a higher probability of detection. Our data also show it is important to sample multiple sites along streams, particularly for detection of target species with lower population densities. For the three focal species in our study, the eDNA metabarcoding method had a greater capacity of detection per sampling event than our rapid field surveys, and thus, has the potential to circumvent some of the challenges associated with traditional approaches. Our results underscore the utility of eDNA metabarcoding as an efficient method to survey anuran species in tropical streams of the highly biodiverse Brazilian Atlantic forest.
© 2016 John Wiley & Sons Ltd.

Entities:  

Keywords:  12S mitochondrial gene; amphibians; biodiversity; monitoring methods; next-generation sequencing; site occupancy-detection modelling

Mesh:

Substances:

Year:  2017        PMID: 27987263     DOI: 10.1111/1755-0998.12643

Source DB:  PubMed          Journal:  Mol Ecol Resour        ISSN: 1755-098X            Impact factor:   7.090


  12 in total

1.  Applying convolutional neural networks to speed up environmental DNA annotation in a highly diverse ecosystem.

Authors:  Benjamin Flück; Laëtitia Mathon; Stéphanie Manel; Alice Valentini; Tony Dejean; Camille Albouy; David Mouillot; Wilfried Thuiller; Jérôme Murienne; Sébastien Brosse; Loïc Pellissier
Journal:  Sci Rep       Date:  2022-06-17       Impact factor: 4.996

2.  Got Glycogen?: Development and Multispecies Validation of the Novel Preserve, Precipitate, Lyse, Precipitate, Purify (PPLPP) Workflow for Environmental DNA Extraction from Longmire's Preserved Water Samples.

Authors:  Richard C Edmunds; Damien Burrows
Journal:  J Biomol Tech       Date:  2020-12

3.  Plant DNA metabarcoding of lake sediments: How does it represent the contemporary vegetation.

Authors:  Inger Greve Alsos; Youri Lammers; Nigel Giles Yoccoz; Tina Jørgensen; Per Sjögren; Ludovic Gielly; Mary E Edwards
Journal:  PLoS One       Date:  2018-04-17       Impact factor: 3.240

4.  Needle in a haystack? A comparison of eDNA metabarcoding and targeted qPCR for detection of the great crested newt (Triturus cristatus).

Authors:  Lynsey R Harper; Lori Lawson Handley; Christoph Hahn; Neil Boonham; Helen C Rees; Kevin C Gough; Erin Lewis; Ian P Adams; Peter Brotherton; Susanna Phillips; Bernd Hänfling
Journal:  Ecol Evol       Date:  2018-05-29       Impact factor: 2.912

5.  Using eDNA to biomonitor the fish community in a tropical oligotrophic lake.

Authors:  Martha Valdez-Moreno; Natalia V Ivanova; Manuel Elías-Gutiérrez; Stephanie L Pedersen; Kyrylo Bessonov; Paul D N Hebert
Journal:  PLoS One       Date:  2019-04-22       Impact factor: 3.240

6.  Meta-analysis shows that environmental DNA outperforms traditional surveys, but warrants better reporting standards.

Authors:  Julija Fediajevaite; Victoria Priestley; Richard Arnold; Vincent Savolainen
Journal:  Ecol Evol       Date:  2021-03-18       Impact factor: 2.912

7.  Evaluating sediment and water sampling methods for the estimation of deep-sea biodiversity using environmental DNA.

Authors:  Miriam I Brandt; Florence Pradillon; Blandine Trouche; Nicolas Henry; Cathy Liautard-Haag; Marie-Anne Cambon-Bonavita; Valérie Cueff-Gauchard; Patrick Wincker; Caroline Belser; Julie Poulain; Sophie Arnaud-Haond; Daniela Zeppilli
Journal:  Sci Rep       Date:  2021-04-12       Impact factor: 4.379

8.  Unveiling biogeographical patterns of the ichthyofauna in the Tuichi basin, a biodiversity hotspot in the Bolivian Amazon, using environmental DNA.

Authors:  Cédric Mariac; Fabrice Duponchelle; Guido Miranda; Camila Ramallo; Robert Wallace; Gabriel Tarifa; Carmen Garcia-Davila; Hernán Ortega; Julio Pinto; Jean-François Renno
Journal:  PLoS One       Date:  2022-01-04       Impact factor: 3.240

Review 9.  Noninvasive Genetic Assessment Is an Effective Wildlife Research Tool When Compared with Other Approaches.

Authors:  Miriam A Zemanova
Journal:  Genes (Basel)       Date:  2021-10-23       Impact factor: 4.096

10.  Comparing fish prey diversity for a critically endangered aquatic mammal in a reserve and the wild using eDNA metabarcoding.

Authors:  Chanjuan Qu; Kathryn A Stewart; Rute Clemente-Carvalho; Jinsong Zheng; Yuxiang Wang; Cheng Gong; Limin Ma; Jianfu Zhao; Stephen C Lougheed
Journal:  Sci Rep       Date:  2020-10-07       Impact factor: 4.379

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