Volume 17, Issue 1 p. 31-50

ORIGINAL ARTICLE

Can immature stages be ignored in studies of forest leaf litter arthropod diversity? A test using Oxford Nanopore DNA barcoding

Martin Fikáček,

Corresponding Author

Martin Fikáček

[email protected]

orcid.org/0000-0002-2078-6798

Department of Biological Sciences, National Sun Yat-sen University, Kaohsiung, Taiwan

Department of Entomology, National Museum, Prague, Czech Republic

Correspondence

Martin Fikáček, Department of Biological Sciences, National Sun Yat-sen University, No. 70, Lienhai Rd., Kaohsiung 80424, Taiwan.

Email: [email protected]

Contribution: Conceptualization, Methodology, Data curation, Investigation, Formal analysis, Supervision, Funding acquisition, Visualization, Project administration, Writing - original draft, Writing - review & editing

Search for more papers by this author

Fang-Shuo Hu,

Fang-Shuo Hu

orcid.org/0000-0003-1269-8904

Department of Biological Sciences, National Sun Yat-sen University, Kaohsiung, Taiwan

Contribution: Data curation, Investigation, Conceptualization, Writing - review & editing, Methodology, Formal analysis

Search for more papers by this author

My-Hanh Le,

My-Hanh Le

orcid.org/0000-0003-0286-1472

Biodiversity Research Center, Academia Sinica, Taipei, Taiwan

Contribution: Conceptualization, Methodology, Data curation, Investigation, Formal analysis, Resources, Writing - review & editing

Search for more papers by this author

Jen-Pan Huang,

Jen-Pan Huang

orcid.org/0000-0002-9329-8867

Biodiversity Research Center, Academia Sinica, Taipei, Taiwan

Contribution: Methodology, Investigation, Supervision, Resources, Writing - review & editing, Software, Project administration

Search for more papers by this author

Martin Fikáček,

Corresponding Author

Martin Fikáček

[email protected]

orcid.org/0000-0002-2078-6798

Department of Biological Sciences, National Sun Yat-sen University, Kaohsiung, Taiwan

Department of Entomology, National Museum, Prague, Czech Republic

Correspondence

Martin Fikáček, Department of Biological Sciences, National Sun Yat-sen University, No. 70, Lienhai Rd., Kaohsiung 80424, Taiwan.

Email: [email protected]

Search for more papers by this author

Fang-Shuo Hu,

Fang-Shuo Hu

orcid.org/0000-0003-1269-8904

Department of Biological Sciences, National Sun Yat-sen University, Kaohsiung, Taiwan

Contribution: Data curation, Investigation, Conceptualization, Writing - review & editing, Methodology, Formal analysis

Search for more papers by this author

My-Hanh Le,

My-Hanh Le

orcid.org/0000-0003-0286-1472

Biodiversity Research Center, Academia Sinica, Taipei, Taiwan

Contribution: Conceptualization, Methodology, Data curation, Investigation, Formal analysis, Resources, Writing - review & editing

Search for more papers by this author

Jen-Pan Huang,

Jen-Pan Huang

orcid.org/0000-0002-9329-8867

Biodiversity Research Center, Academia Sinica, Taipei, Taiwan

Contribution: Methodology, Investigation, Supervision, Resources, Writing - review & editing, Software, Project administration

Search for more papers by this author

First published: 21 November 2023

https://doi.org/10.1111/icad.12702

Citations: 2

Editor: Yves Basset and Associate Editor: Michelle DiLeo

Share a link

Email
Facebook
x
LinkedIn
Reddit
Wechat

Abstract

Forest soil and leaf litter support diverse arthropod mesofauna for which diversity dynamics is challenging to study due to the high number of species and specimens, small body size and limited taxonomic knowledge.
Immature stages (larvae) are even harder to identify than adults, as their morphology is largely unknown. Therefore, larvae are often ignored, even though they may form a substantial proportion of specimens collected, are less mobile than adults and their exclusion may provide an incomplete diversity profile.
Here, we use Oxford Nanopore DNA barcoding to investigate whether the inclusion of larvae provides a more complete taxonomic, phylogenetic and functional diversity profiles in leaf litter beetles (Coleoptera) from a subtropical forest in Taiwan.
Our results indicate that larvae represent up to 38% of beetle specimens per sample, but most of them belong to 2–3 common species. Larvae of most beetle species are rarely collected repeatedly or in multiple specimens, possibly due to special habitat requirements or high seasonality.
Taxonomic, phylogenetic and incidence-based functional diversity measures were not affected by the exclusion of larvae in the Staphylinidae dataset but were strongly biased in all-beetle dataset, especially when only common or abundant species were considered. Taxonomic beta diversity was not affected by the omission of larvae.
Our results indicate that immature stages may be omitted in ecological studies of arthropods in case both adults and larvae co-occur in the same habitat, and the sites are sampled repeatedly. Caution is needed (1) in groups in which larvae and adults do not inhabit the same environment or strongly differ in biology, (2) when rare species are omitted or (3) when functional diversity is calculated from abundance data.

CONFLICT OF INTEREST STATEMENT

The authors declare no conflicts of interest.

Open Research

DATA AVAILABILITY STATEMENT

All DNA barcodes used in this study have been published online in the BOLD database (Hu et al., 2023). The data used for all analyses in this study, including the incidence and abundance data, the morphological data used for functional diversity analyses, the alignments used to construct the tree for phylogenetic diversity analyses, the R scripts used for the data processing, and all results are available in Supporting Information S2–S8 and also from the Zenodo research archive under the following DOI: https://doi.org/10.5281/zenodo.8144203.

Supporting Information

Filename

Description

icad12702-sup-0001-Supinfo.docxWord 2007 document , 3 MB

Data S1: Supporting Information.

Table S1: Tagged primers used for ONT sequencing in this project.

Table S2: The ‘plate map’ with the reverse primers indicate the position of the sample in the 96-well plate.

Table S3: The pooling, clean-up and library preparation protocol used in this project.

Table S4: Summary of the differences between the results of the DNA-morphology manual species delimitation and the results of the ASAP species delimitations. OTU numbers are based on DNA-morphology clustering.

Table S5: Statistics of the ONTbarcoder performance on the example of Flongle flow cell #4, using 10–100 % of the data.

Table S6: Species alpha diversity based on all beetle data.

Table S7: Species alpha diversity based on Staphylinidae.

Table S8: Number of OTUs found in each sample when larvae are included or excluded.

Table S9: Complete results of the iNEXT3D analyses of taxonomic diversity based in incidence data.

Table S10: Complete results of the iNEXT3D analyses of taxonomic diversity based in abundance data.

Table S11: Observed and estimated phylogenetic diversity of Huisun leaf litter beetles. s.e. = standard error; LCL = lower 95% confidence limit, UCL = upper 95% confidence limit).

Table S12: Observed and estimates functional diversity based on incidence data and trait data with NA values. s.e. = standard error; LCL = lower 95% confidence limit, UCL = upper 95% confidence limit).

Table S13: Observed and estimates functional diversity based on incidence data with NA values replaced by most frequent value. s.e. = standard error; LCL = lower 95% confidence limit, UCL = upper 95% confidence limit).

Table S14: Observed and estimates functional diversity based on abundance data with NA values. s.e. = standard error; LCL = lower 95% confidence limit, UCL = upper 95% confidence limit).

Table S15: Results of the PERMANOVA analyses based on data for all beetles, testing the differences in comminity composition between the sampled localities in Huisun Forest Reserve. Cases with significant differences are marked by for *p<0.05, and **p<0.01.

Table S16: Results of the PERMANOVA analyses based on data for staphylinid beetles, testing the differences in community composition between the sampled localities in Huisun Forest Reserve. Cases with significant differences are marked by for *p<0.05, and **p<0.01.

Figure S1: Barcoding failure test. Real number of failures per family (blue line) versus expected number of failures in case the failure distribution is random (at 15.4 % failure rate, corresponding to 121 failed PCRs out of 788).

Figure S2: Summary of the ONT sequencing and consensus calling. A, number of consensus barcodes generated by ONTbarcoder as a function of total number of reads. B, number of reads per sample generated by ONT R9 Flongle cell. C, number of reads per sample used for the generation of the consensus sequenced by ONT barcoder. D, the quality of the consensus sequence as a function of reads used (samples with >100 reads omitted).

Figure S3: Taxonomic diversity as a function of number of samples (incidence data) or number of specimens (abundance data) for all three sites combined. q=0 corresponds to species richness, q=1 to Shannon diversity, q=2 to Simpson diversity.

Figure S4: Taxonomic diversity as a function of number of samples (incidence data) or number of specimens (abundance data) for the lowest and middle locality. q=0 corresponds to species richness, q=1 to Shannon diversity, q=2 to Simpson diversity.

Figure S5: Taxonomic diversity as a function of number of samples (incidence data) or number of specimens (abundance data) for the highest locality. q=0 corresponds to species richness, q=1 to Shannon diversity, q=2 to Simpson diversity.

Figure S6: Phylogenetic diversity as a function of the number of samples for each locality separately, and for all beetles and Staphylinidae. Increasing q values indicate decreasing effect of rare species on the phylogenetic diversity value.

Figure S7: Phylogenetic relationships of all OTUs recorded in Huisun and their presence on individual localities. Red mark indicates OTUs only found as larvae on the specific locality, blue mark indicates OTUs for which adults or adults + larvae were found on the specific locality.

Figure S8: Functional diversity as a function of the number of samples (incidence data) for all beetles and Staphylinidae. Increasing q values indicate decreasing effect of rare species on the phylogenetic diversity value. Curves and 95% confidence intervals are shown for original trait data with NAs and for adapted data in which NAs were replaced by the most probable value.

Figure S9: Functional diversity as a function of the number of specimens (abundance data) for all beetles and Staphylinidae. Increasing q values indicate decreasing effect of rare species on the phylogenetic diversity value. Curves and 95% confidence intervals are shown for original trait data with NAs and for adapted data in which NAs were replaced by the most probable value.

Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

REFERENCES

Anderson, R.S. & Ashe, J.S. (2000) Leaf litter inhabiting beetles as surrogates for establishing priorities for conservation of selected tropical montane cloud forests in Honduras, Central America (Coleoptera; Staphylinidae, Curculionidae). Biodiversity and Conservation, 9(5), 617–653. Available from: https://doi.org/10.1023/A:1008937017058
10.1023/A:1008937017058
Web of Science®Google Scholar
Archangelsky, M. (1999) Adaptations of immature stages of Sphaeridiinae (Staphyliniformia, Hydrophiloidea: Hydrophilidae) and state of knowledge of preimaginal Hydrophilidae. Coleopterist Bulletin, 53(1), 64–79.
Web of Science®Google Scholar
Arriaga-Varela, E., Seidel, M., Deler-Hernández, A., Senderov, V. & Fikáček, M. (2017) A review of the Cercyon Leach (Coleoptera, Hydrophilidae, Sphaeridiinae) of the Greater Antilles. ZooKeys, 681, 39–93. Available from: https://doi.org/10.3897/ZOOKEYS.681.12522
10.3897/zookeys.681.12522
Web of Science®Google Scholar
Arribas, P., Andújar, C., Salces-Castellano, A., Emerson, B.C. & Vogler, A.P. (2020) The limited spatial scale of dispersal in soil arthropods revealed with whole-community haplotype-level metabarcoding. Molecular Ecology, 30(1), 48–61. Available from: https://doi.org/10.1111/mec.15591
10.1111/mec.15591
PubMedWeb of Science®Google Scholar
Awadalla, H.S., Guedes, R.N.C. & Hashem, A.S. (2021) Feeding and egg-laying preferences of the sawtoothed grain beetle Oryzaephilus surinamensis: beyond cereals and cereal products. Journal of Stored Products Research, 93(101841), 1–8. Available from: https://doi.org/10.1016/j.jspr.2021.101841
10.1016/j.jspr.2021.101841
Google Scholar
Baig, F., Farnier, K., Piper, A.M., Speight, R. & Cunningham, J.P. (2020) Yeasts influence host selection and larval fitness in two frugivorous Carpophilus beetle species. Journal of Chemical Ecology, 46(8), 675–687. Available from: https://doi.org/10.1007/s10886-020-01167-5
10.1007/s10886-020-01167-5
CASPubMedWeb of Science®Google Scholar
Basset, Y., Novotny, V., Miller, S.E. & Pyle, R. (2000) Quantifying biodiversity: experience with parataxonomists and digital photography in Papua New Guinea and Guyana. Bioscience, 50(10), 899–908. Available from: https://doi.org/10.1641/0006-3568(2000)050[0899:QBEWPA]2.0.CO;2
10.1641/0006-3568(2000)050[0899:QBEWPA]2.0.CO;2
Web of Science®Google Scholar
Bong, L.-J., Neoh, K.-B., Jaal, Z. & Lee, C.-Y. (2012) Life table of Paederus fuscipes (Coleoptera: Staphylinidae). Journal of Medical Entomology, 49(3), 451–460. Available from: https://doi.org/10.1603/ME11163
10.1603/ME11163
PubMedWeb of Science®Google Scholar
Brunke, A.J., Bahlai, C.A., Sears, M.K. & Halleti, R.H. (2009) Generalist predators (Coleoptera: Carabidae, Staphylinidae) associated with millipede populations in sweet potato and carrot fields and implications for millipede management. Environmental Entomology, 38(4), 1106–1116. Available from: https://doi.org/10.1603/022.038.0418
10.1603/022.038.0418
PubMedWeb of Science®Google Scholar
Burgess, N.D., Ponder, K.L. & Goddard, J. (1999) Surface and leaf-litter arthropods in the coastal forests of Tanzania. Journal of Ecology, 37, 355–365.
10.1046/j.1365-2028.1999.00188.x
Web of Science®Google Scholar
Cadotte, M.W., Carscadden, K. & Mirotchnick, N. (2011) Beyond species: functional diversity and the maintenance of ecological processes and services. Journal of Applied Ecology, 48(5), 1079–1087. Available from: https://doi.org/10.1111/j.1365-2664.2011.02048.x
10.1111/j.1365-2664.2011.02048.x
Web of Science®Google Scholar
Camacho, C., Coulouris, G., Avagyan, V., Ma, N., Papadopoulos, J., Bealer, K. et al. (2009) BLAST+: architecture and applications. BMC Bioinformatics, 10, 1–9. Available from: https://doi.org/10.1186/1471-2105-10-421
10.1186/1471-2105-10-421
CASPubMedWeb of Science®Google Scholar
Caterino, M.S. & Langton-Myers, S.S. (2019) Intraspecific diversity and phylogeography in southern Appalachian Dasycerus carolinensis (Coleoptera: Staphylinidae: Dasycerinae). Insect Systematics and Diversity, 3(6), 8. Available from: https://doi.org/10.1093/isd/ixz022
10.1093/isd/ixz022
Web of Science®Google Scholar
Chao, A. (1984) Nonparametric estimation of the number of classes in a population. Scandinavian Journal of Statistics, 11(4), 265–270.
Web of Science®Google Scholar
Chao, A., Chiu, C.-H., Villéger, S., Sun, I.-F., Thorn, S., Lin, Y.-C. et al. (2019) An attribute-diversity approach to functional diversity, functional beta diversity, and related (dis)similarity measures. Ecological Monographs, 89(2), e01343. Available from: https://doi.org/10.1002/ecm.1343
10.1002/ecm.1343
Web of Science®Google Scholar
Chao, A., Henderson, P.A., Chiu, C.-H., Moyes, F., Hu, K.-H., Dornelas, M. et al. (2021) Measuring temporal change in alpha diversity: a framework integrating taxonomic, phylogenetic and functional diversity and the iNEXT.3D standardization. Methods in Ecology and Evolution, 12(10), 1926–1940. Available from: https://doi.org/10.1111/2041-210X.13682
10.1111/2041-210X.13682
Web of Science®Google Scholar
Chiou, C.R., Hsieh, C.F., Wang, J.C., Chen, M.Y., Liu, H.Y., Yeh, C.L. et al. (2009) The first national vegetation inventory in Taiwan. Taiwan Journal of Forest Science, 24(4), 295–302. Available from: https://doi.org/10.7075/TJFS.200912.0295
10.7075/TJFS.200912.0295
Google Scholar
Chung, A.Y.C., Eggleton, P., Speight, M.R., Hammond, P.M. & Chey, V.K. (2000) The diversity of beetle assemblages in different habitat types in Sabah, Malaysia. Bulletin of Entomological Research, 90(6), 475–496. Available from: https://doi.org/10.1017/s0007485300000602
10.1017/S0007485300000602
CASPubMedWeb of Science®Google Scholar
Didham, R.K., Hammond, P.M., Lawton, J.H., Eggleton, P. & Stork, N.E. (1998) Beetle species responses to tropical forest fragmentation. Ecological Monographs, 68(3), 295–323. Available from: https://doi.org/10.1890/0012-9615(1998)068[0295:BSRTTF]2.0.CO;2
10.1890/0012-9615(1998)068[0295:BSRTTF]2.0.CO;2
Web of Science®Google Scholar
Drag, L., Burner, R.C., Stephan, J.G., Birkemoe, T., Doerfler, I., Gossner, M.M. et al. (2023) High-resolution 3D forest structure explains ecomorphological trait variation in assemblages of saproxylic beetles. Functional Ecology, 37(1), 150–161. Available from: https://doi.org/10.1111/1365-2435.14188
10.1111/1365-2435.14188
CASPubMedWeb of Science®Google Scholar
Egli, L., LeVan, K.E. & Work, T.T. (2020) Taxonomic error rates affect interpretations of a national-scale ground beetle monitoring program at National Ecological Observatory Network. Ecosphere, 11(4), e03035. Available from: https://doi.org/10.1002/ecs2.3035
10.1002/ecs2.3035
Web of Science®Google Scholar
Fikáček, M. (2019) 20. Hydrophilidae Leach, 1815. In: A. Ślipiński & J.F. Lawrence (Eds.) Australian beetles. Volume 2, Archostemata, Myxophaga, Adephaga, Polyphaga (part). CSIRO Publishing, Clayton, Victoria, Australia pp. 271–337.
Google Scholar
Fikáček, M., Zhao, Q.-H., Kobe, I.N. & Grebennikov, V. (2020) Kruia rediscovered: phylogenetic implications, larval morphology, and biology of an enigmatic hydrophilid beetle from western Africa (Coleoptera: Hydrophilidae). Arthropod Systematics & Phylogemny, 78(3), 427–444. Available from: https://doi.org/10.26049/ASP78-3-2020-05
10.26049/ASP78-3-2020-05
Web of Science®Google Scholar
Folmer, O., Black, M., Hoeh, W., Lutz, R. & Vrijenhoek, R. (1994) DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Molecular Marine Biology and Biotechnology, 3(5), 294–299.
CASPubMedGoogle Scholar
Fountain-Jones, N.M., Jordan, G.J., Burridge, C.P., Wardlaw, T.J., Baker, T.P., Forster, L. et al. (2017) Trophic position determines functional and phylogenetic recovery after disturbance within a community. Functional Ecology, 31(7), 1441–1451. Available from: https://doi.org/10.1111/1365-2435.12845
10.1111/1365-2435.12845
Web of Science®Google Scholar
Frith, D. & Frith, C. (1990) Seasonality of litter invertebrate populations in an Australian upland tropical rain forest. Biotropica, 22(2), 181–190.
10.2307/2388411
Web of Science®Google Scholar
Fujisawa, T. & Barraclough, T.G. (2013) Delimiting species using single-locus data and the Generalized Mixed Yule Coalescent approach: a revised method and evaluation on simulated data sets. Systematic Biology, 62(5), 707–724. Available from: https://doi.org/10.1093/sysbio/syt033
10.1093/sysbio/syt033
PubMedWeb of Science®Google Scholar
Galford, J.R., Williams, R.N. & Beacom, M. (1991) Notes on the biology and hosts of Stelidota ferruginea (Coleoptera: Nitidulidae) (Northeastern Forest Experiment Station Research Paper, pp. 1–4). United States Department of Agriculture, Forest Service, Northeastern Forest Experimental Staton.
Google Scholar
Giller, P.S. (1996) The diversity of soil communities, the ‘poor man's tropical rainforest’. Biodiversity and Conservation, 5(2), 135–168. Available from: https://doi.org/10.1007/BF00055827
10.1007/BF00055827
Web of Science®Google Scholar
Gimmel, M.L. & Ferro, M.L. (2018) General overview of saproxylic coleoptera. In: M. Ulyshen (Ed.) Saproxylic insects. Zoological monographs, Vol. 1. Springer, New York, USA pp. 51–128. Available from: https://doi.org/10.1007/978-3-319-75937-1_2
10.1007/978-3-319-75937-1_2
Google Scholar
Goslee, S. & Urban, D. (2022) ecodist: dissimilarity-based functions for ecological analysis (2.0.9) [Computer software]. Available from: https://cran.r-project.org/web/packages/ecodist/index.html
Google Scholar
Gotelli, N.J. & Chao, A. (2013) Measuring and estimating species richness, species diversity, and biotic similarity from sampling data. In: Encyclopedia of biodiversity, 2nd edition. Elsevier Inc., Oxford, UK pp. 195–211. Available from: https://doi.org/10.1016/B978-0-12-384719-5.00424-X
10.1016/B978-0-12-384719-5.00424-X
Google Scholar
Gotelli, N.J. & Colwell, R.K. (2010) Estimating species richness. In: A.E. Magurran & B.J. McGill (Eds.) Biological diversity: Frontiers in measurement and assessment. Oxford University Press, Oxford, UK pp. 39–54.
Google Scholar
Grimbacher, P.S., Edwards, W., Liddell, M.J., Nelson, P.N., Nichols, C., Wardhaugh, C.W. et al. (2018) Temporal variation in abundance of leaf litter beetles and ants in an Australian lowland tropical rainforest is driven by climate and litter fall. Biodiversity and Conservation, 27(10), 2625–2640. Available from: https://doi.org/10.1007/s10531-018-1558-2
10.1007/s10531-018-1558-2
Web of Science®Google Scholar
Gullan, P.J. & Cranston, P.S. (2014) The insects. An outline of entomology. John Wiley & Sons, Ltd, Hoboken, New Jersey, USA.
Google Scholar
Hajibabaei, M., Janzen, D.H., Burns, J.M., Hallwachs, W. & Hebert, P.D.N. (2006) DNA barcodes distinguish species of tropical Lepidoptera. Proceedings of the National Academy of Sciences of the United States of America, 103(4), 968–971. Available from: https://doi.org/10.1073/pnas.0510466103
10.1073/pnas.0510466103
PubMedWeb of Science®Google Scholar
Hebert, P.D.N., Ratnasingham, S. & DeWaard, J.R. (2003) Barcoding animal life: cytochrome c oxidase subunit 1 divergences among closely related species. Proceedings of the Royal Society B: Biological Sciences, 270(Supplement 1), S96–S99. Available from: https://doi.org/10.1098/rsbl.2003.0025
10.1098/rsbl.2003.0025
CASPubMedGoogle Scholar
Hermans, S.M., Lear, G., Buckley, T.R. & Buckley, H.L. (2022) Environmental DNA sampling detects between-habitat variation in soil arthropod communities but is a poor indicator of fine-scale spatial and seasonal variation. Ecological Indicators, 140, 109040. Available from: https://doi.org/10.1016/j.ecolind.2022.109040
10.1016/j.ecolind.2022.109040
CASWeb of Science®Google Scholar
Hopp, P.W., Caron, E., Ottermanns, R. & Roß-Nickoll, M. (2011) Evaluating leaf litter beetle data sampled by Winkler extraction from Atlantic forest sites in southern Brazil. Revista Brasileira de Entomologia, 55(2), 253–266. Available from: https://doi.org/10.1590/S0085-56262011000200017
10.1590/S0085-56262011000200017
Web of Science®Google Scholar
Hopp, P.W., Ottermanns, R., Caron, E., Meyer, S. & Roß-Nickoll, M. (2010) Recovery of litter inhabiting beetle assemblages during forest regeneration in the Atlantic forest of Southern Brazil. Insect Conservation and Diversity, 3(2), 103–113. Available from: https://doi.org/10.1111/j.1752-4598.2010.00078.x
10.1111/j.1752-4598.2010.00078.x
Web of Science®Google Scholar
Hsieh, T.C., Ma, K.H. & Chao, A. (2016) iNEXT: an R package for rarefaction and extrapolation of species diversity (Hill numbers). Methods in Ecology and Evolution, 7(12), 1451–1456. Available from: https://doi.org/10.1111/2041-210X.12613
10.1111/2041-210X.12613
Web of Science®Google Scholar
Hsu, F.C., Tseng, S.P., Hsu, P.W., Lu, C.W., Yang, C.C.S. & Lin, C.C. (2022) Introduction of a non-native lineage is linked to the recent black cocoa ant, Dolichoderus thoracicus (Smith, 1860), outbreaks in Taiwan. Taiwania, 67(2), 271–279. Available from: https://doi.org/10.6165/tai.2022.67.271
10.6165/tai.2022.67.271
Web of Science®Google Scholar
Hu, F.S., Arriaga-Varela, E., Biffi, G., Bocák, L., Bulirsch, P., Damaška, A.F. et al. (2023) Forest leaf litter beetles of Taiwan: first DNA barcodes and first insight into the fauna. Deutsche Entomologische Zeitschrift submitted.
Google Scholar
Jałoszyński, P. & Olszanowski, Z. (2013) Specialized feeding of Euconnus pubicollis (Coleoptera: Staphylinidae: Scydmaeninae) on oribatid mites: prey preferences and hunting behaviour. European Journal of Entomology, 110(2), 339–353. Available from: https://doi.org/10.14411/eje.2013.047
10.14411/eje.2013.047
Web of Science®Google Scholar
Janzen, D.H. & Hallwachs, W. (2011) Joining inventory by parataxonomists with DNA barcoding of a large complex tropical conserved wildland in northwestern Costa Rica. PLoS One, 6(8), e18123. Available from: https://doi.org/10.1371/journal.pone.0018123
10.1371/journal.pone.0018123
CASPubMedWeb of Science®Google Scholar
Johansson, T., Gibb, H., Hjältén, J., Pettersson, R.B., Hilszczański, J., Alinvi, O. et al. (2007) The effects of substrate manipulations and forest management on predators of saproxylic beetles. Forest Ecology and Management, 242(2–3), 518–529. Available from: https://doi.org/10.1016/j.foreco.2007.01.064
10.1016/j.foreco.2007.01.064
Web of Science®Google Scholar
Jost, L., Chao, A. & Chazdon, R.L. (2011) Compositional similarity and β (beta) diversity. In: A.E. Magurran & B.J. McGill (Eds.) Biological diversity. Frontiers in measurement and assessment. Oxford University Press, Oxford, UK pp. 66–84.
Google Scholar
Kalyaanamoorthy, S., Minh, B.Q., Wong, T.K.F., Von Haeseler, A. & Jermiin, L.S. (2017) ModelFinder: fast model selection for accurate phylogenetic estimates. Nature Methods, 14(6), 587–589. Available from: https://doi.org/10.1038/nmeth.4285
10.1038/nmeth.4285
CASPubMedWeb of Science®Google Scholar
Kearse, M., et al. (2012) Geneious Basic: An Integrated and Extendable Desktop Software Platform for the Organization and Analysis of Sequence Data. Bioinformatics, 28, 1647–1649. https://doi.org/10.1093/bioinformatics/bts199
10.1093/bioinformatics/bts199
PubMedWeb of Science®Google Scholar
Köhler, J., Rulik, B., Eberle, J., Thormann, J., Köhler, F. & Ahrens, D. (2022) Does monitoring of saproxylic beetles benefit from inclusion of larvae? Insect Conservation and Diversity, 15(5), 555–571. Available from: https://doi.org/10.1111/ICAD.12573
10.1111/icad.12573
Web of Science®Google Scholar
Krell, F.T. (2004) Parataxonomy vs. taxonomy in biodiversity studies—pitfalls and applicability of ‘morphospecies’ sorting. Biodiversity and Conservation, 13(4), 795–812. Available from: https://doi.org/10.1023/B:BIOC.0000011727.53780.63
10.1023/B:BIOC.0000011727.53780.63
Web of Science®Google Scholar
Kumar, S., Stecher, G. & Tamura, K. (2016) MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Molecular Biology and Evolution, 33(7), 1870–1874. Available from: https://doi.org/10.1093/MOLBEV/MSW054
10.1093/molbev/msw054
CASPubMedWeb of Science®Google Scholar
Lagerlöf, J., Maribie, C. & Muturi John, J. (2017) Trophic interactions among soil arthropods in contrasting land-use systems in Kenya, studied with stable isotopes. European Journal of Soil Biology, 79, 31–39. Available from: https://doi.org/10.1016/j.ejsobi.2017.01.002
10.1016/j.ejsobi.2017.01.002
Web of Science®Google Scholar
Laliberté, E., Legendre, P. & Shipley, B. (2022) FD: measuring functional diversity (FD) from multiple traits, and other tools for functional ecology (1.0-12.1) [Computer software]. Available from: https://cran.r-project.org/web/packages/FD/index.html
Google Scholar
Lamarre, G.P.A., Hérault, B., Fine, P.V.A., Vedel, V., Lupoli, R., Mesones, I. et al. (2016) Taxonomic and functional composition of arthropod assemblages across contrasting Amazonian forests. Journal of Animal Ecology, 85(1), 227–239. Available from: https://doi.org/10.1111/1365-2656.12445
10.1111/1365-2656.12445
PubMedWeb of Science®Google Scholar
Landvik, M., Niemelä, P. & Roslin, T. (2016) Mother knows the best mould: an essential role for non-wood dietary components in the life cycle of a saproxylic scarab beetle. Oecologia, 182(1), 163–175. Available from: https://doi.org/10.1007/s00442-016-3661-y
10.1007/s00442-016-3661-y
PubMedWeb of Science®Google Scholar
Lavelle, P., Bignell, D., Lepage, M., Wolters, V., Roger, P., Ineson, P. et al. (1997) Soil function in a changing world: the role of invertebrate ecosystem engineers. European Journal of Soil Biology, 33(4), 159–193.
CASWeb of Science®Google Scholar
Lawrence, J.F. & Ślipiński, A. (2013) Australian beetles. Volume 1: morphology, classification and keys. CSIRO Publishing, Clayton, Victoria, Australia.
10.1071/9780643097292
Google Scholar
Li, C.F., Chytrý, M., Zelený, D., Chen, M.Y., Chen, T.Y., Chiou, C.R. et al. (2013) Classification of Taiwan forest vegetation. Applied Vegetation Science, 16(4), 698–719. Available from: https://doi.org/10.1111/avsc.12025
10.1111/avsc.12025
Web of Science®Google Scholar
Lövei, G.L. & Sunderland, K.D. (1996) Ecology and behavior of ground beetles (Coleoptera: Carabidae). Annual Review of Entomology, 41(1), 231–256. Available from: https://doi.org/10.1146/annurev.en.41.010196.001311
10.1146/annurev.en.41.010196.001311
CASPubMedWeb of Science®Google Scholar
Lü, L., Cai, C.-Y., Zhang, X., Newton, A.F., Thayer, M.K. & Zhou, H.-Z. (2020) Linking evolutionary mode to palaeoclimate change reveals rapid radiations of staphylinoid beetles in low-energy conditions. Current Zoology, 66(4), 435–444. Available from: https://doi.org/10.1093/cz/zoz053
10.1093/cz/zoz053
PubMedWeb of Science®Google Scholar
Luff, M.L. (1987) Biology of polyphagous ground beetles in agriculture. Agricultural Zoology Reviews, 2, 237–278.
Google Scholar
Martinez Arbizu, P. (2023) pairwiseAdonis [Computer software]. Availabe from: https://github.com/pmartinezarbizu/pairwiseAdonis.
Google Scholar
Mcgill, B., Enquist, B., Weiher, E. & Westoby, M. (2006) Rebuilding community ecology from functional traits. Trends in Ecology & Evolution, 21(4), 178–185. Available from: https://doi.org/10.1016/j.tree.2006.02.002
10.1016/j.tree.2006.02.002
PubMedWeb of Science®Google Scholar
McKenna, D.D., Wild, A.L., Kanda, K., Bellamy, C.L., Beutel, R.G., Caterino, M.S. et al. (2015) The beetle tree of life reveals that Coleoptera survived end-Permian mass extinction to diversify during the Cretaceous terrestrial revolution. Systematic Entomology, 40(4), 835–880. Available from: https://doi.org/10.1111/syen.12132
10.1111/syen.12132
Web of Science®Google Scholar
Meier, R., Wong, W., Srivathsan, A. & Foo, M. (2016) $1 DNA barcodes for reconstructing complex phenomes and finding rare species in specimen-rich samples. Cladistics, 32(1), 100–110. Available from: https://doi.org/10.1111/cla.12115
10.1111/cla.12115
PubMedWeb of Science®Google Scholar
Migge-Kleian, S., Woltmann, L., Anas, I., Schulz, W., Steingrebe, A. & Schaefer, M. (2007) Impact of forest disturbance and land use change on soil and litter arthropod assemblages in tropical rainforest margins. In: T. Tscharntke, C. Leuschner, M. Zeller, E. Guhardja & A. Bidin (Eds.) Stability of tropical rainforest margins: linking ecological, economic and social constraints of land use and conservation. Springer Verlag, New York City, USA. pp. 147–163. Available from: https://doi.org/10.1007/978-3-540-30290-2_8
10.1007/978-3-540-30290-2_8
Google Scholar
Minh, B.Q., Schmidt, H.A., Chernomor, O., Schrempf, D., Woodhams, M.D., Von Haeseler, A. et al. (2020) IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Molecular Biology and Evolution, 37(5), 1530–1534. Available from: https://doi.org/10.1093/MOLBEV/MSAA015
10.1093/molbev/msaa015
CASPubMedWeb of Science®Google Scholar
Minoshima, Y.N. (2018) Larval morphology of Armostus ohyamatensis Hoshina and Satô (Coleoptera: Hydrophilidae: Megasternini). Coleopterists Bulletin, 72(4), 767–778. Available from: https://doi.org/10.1649/0010-065X-72.4.767
10.1649/0010-065X-72.4.767
Web of Science®Google Scholar
Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M. et al. (2017) Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology, 31(3), 558–567. Available from: https://doi.org/10.1111/1365-2435.12776
10.1111/1365-2435.12776
Web of Science®Google Scholar
Nadkarni, N.M. & Longino, J.T. (1990) Invertebrates in canopy and ground organic matter in a neotropical montane forest, Costa Rica. Biotropica, 22(3), 286. Available from: https://doi.org/10.2307/2388539
10.2307/2388539
Web of Science®Google Scholar
Oksanen, J. (2022) Vegan: community ecology package. R package version 2.6-2. [Computer software]. Availabe from: https://github.com/vegandevs/vegan
Google Scholar
Olson, D.M. (1994) The distribution of leaf litter invertebrates along a Neotropical altitudinal gradient. Journal of Tropical Ecology, 10(2), 129–150. Available from: https://doi.org/10.1017/S0266467400007793
10.1017/S0266467400007793
Web of Science®Google Scholar
Owens, B.E. & Carlton, C.E. (2015) ‘Berlese vs. Winkler’: comparison of two forest litter Coleoptera extraction methods and the Ecoli (extraction of Coleoptera in litter) protocol. Coleopterists Bulletin, 69(4), 645–661. Available from: https://doi.org/10.1649/0010-065X-69.4.645
10.1649/0010-065X-69.4.645
Web of Science®Google Scholar
Papadopoulou, A., Anastasiou, I. & Vogler, A.P. (2010) Revisiting the insect mitochondrial molecular clock: the mid-Aegean trench calibration. Molecular Biology and Evolution, 27(7), 1659–1672. Available from: https://doi.org/10.1093/MOLBEV/MSQ051
10.1093/molbev/msq051
CASPubMedWeb of Science®Google Scholar
Parr, C.L., Dunn, R.R., Sanders, N.J., Weiser, M.D., Photakis, M., Bishop, T.R. et al. (2017) GlobalAnts: a new database on the geography of ant traits (Hymenoptera: Formicidae). Insect Conservation and Diversity, 10(1), 5–20. Available from: https://doi.org/10.1111/icad.12211
10.1111/icad.12211
Web of Science®Google Scholar
Pfingstl, T. & Schatz, H. (2021) A survey of lifespans in Oribatida excluding Astigmata (Acari). Zoosymposia, 20, 7–27. Available from: https://doi.org/10.11646/zoosymposia.20.1.4
10.11646/zoosymposia.20.1.4
Google Scholar
Piper, A.M., Batovska, J., Cogan, N.O.I., Weiss, J., Cunningham, J.P., Rodoni, B.C. et al. (2019) Prospects and challenges of implementing DNA metabarcoding for high-throughput insect surveillance. GigaScience, 8(8), 1–22. Available from: https://doi.org/10.1093/gigascience/giz092
10.1093/gigascience/giz092
Web of Science®Google Scholar
Pollierer, M.M., Klarner, B., Ott, D., Digel, C., Ehnes, R.B., Eitzinger, B. et al. (2021) Diversity and functional structure of soil animal communities suggest soil animal food webs to be buffered against changes in forest land use. Oecologia, 196(1), 195–209. Available from: https://doi.org/10.1007/s00442-021-04910-1
10.1007/s00442-021-04910-1
PubMedWeb of Science®Google Scholar
Puillandre, N., Brouillet, S. & Achaz, G. (2021) ASAP: assemble species by automatic partitioning. Molecular Ecology Resources, 21(2), 609–620. Available from: https://doi.org/10.1111/1755-0998.13281
10.1111/1755-0998.13281
PubMedWeb of Science®Google Scholar
R Core Team. (2021) R: a language and environment for statistical computing [Computer software]. R Foundation for Statistical Computing. Availabe from: https://www.R-project.org/
Google Scholar
Ratnasingham, S. & Hebert, P.D.N. (2007) BOLD: the barcode of life data system: barcoding. Molecular Ecology Notes, 7(3), 355–364. Available from: https://doi.org/10.1111/j.1471-8286.2007.01678.x
10.1111/j.1471-8286.2007.01678.x
CASPubMedWeb of Science®Google Scholar
Sakchoowong, W., Jaitrong, W., Ogata, K., Nomura, S. & Chanpaisaeng, J. (2008) Diversity of soil-litter insects: comparison of the pselaphine beetles (Coleoptera: Staphylinidae: Pselaphinae) and the ground ants (Hymenoptera: Formicidae). Thai Journal of Agriculture Science, 41, 11–18.
Google Scholar
Schloss, P.D., Westcott, S.L., Ryabin, T., Hall, J.R., Hartmann, M., Hollister, E.B. et al. (2009) Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Applied and Environmental Microbiology, 75(23), 7537–7541. Available from: https://doi.org/10.1128/AEM.01541-09/FORMAT/EPUB
10.1128/AEM.01541-09
CASPubMedWeb of Science®Google Scholar
Schroeder, P.J. & Jenkins, D.G. (2018) How robust are popular beta diversity indices to sampling error? Ecosphere, 9(2), e02100. Available from: https://doi.org/10.1002/ecs2.2100
10.1002/ecs2.2100
Web of Science®Google Scholar
Soares, D.M., Nascimento, A.R.T., da Silva, J.M.H. & de Oliveira, C.H.E. (2021) Litter arthropods community in multifunctional landscapes: spatial and temporal complementarity of Brazilian ecosystems. Pedobiologia, 84, 150707. Available from: https://doi.org/10.1016/j.pedobi.2021.150707
10.1016/j.pedobi.2021.150707
Web of Science®Google Scholar
Srivathsan, A., Lee, L., Katoh, K., Hartop, E., Kutty, S.N., Wong, J. et al. (2021) ONTbarcoder and MinION barcodes aid biodiversity discovery and identification by everyone, for everyone. BMC Biology, 19(1), 1–21. Available from: https://doi.org/10.1186/s12915-021-01141-x
10.1186/s12915-021-01141-x
PubMedWeb of Science®Google Scholar
Stork, N.E. & Grimbacher, P.S. (2006) Beetle assemblages from an Australian tropical rainforest show that the canopy and the ground strata contribute equally to biodiversity. Proceedings of the Royal Society B: Biological Sciences, 273(1596), 1969–1975. Available from: https://doi.org/10.1098/rspb.2006.3521
10.1098/rspb.2006.3521
PubMedWeb of Science®Google Scholar
Tayllon Serra, R., Santos, C.D., Rousseau, G.X., Triana, S.P., Muñoz Gutiérrez, J.A. & Burgos Guerrero, J.E. (2021) Fast recovery of soil macrofauna in regenerating forests of the Amazon. Journal of Animal Ecology, 90(9), 2094–2108. Available from: https://doi.org/10.1111/1365-2656.13506
10.1111/1365-2656.13506
PubMedWeb of Science®Google Scholar
Thayer, M.K. (2016) 14.7 Staphylinidae Latreille, 1802. In: R.G. Beutel & R.A.B. Leschen (Eds.) Coleoptera, beetles. Vol. 1: Morphology and systematics (Archostemata, Adephaga, Myxophaga, Polyphaga partim) (Issue March). Walter de Gruyter, Berlin, Germany.
Google Scholar
Truett, G.E., Heeger, P., Mynatt, R.L., Truett, A.A., Walker, J.A. & Warman, M.L. (2000) Preparation of PCR-quality mouse genomic DNA with hot sodium hydroxide and tris (HotSHOT). BioTechniques, 29(1), 52–54. Available from: https://doi.org/10.2144/00291bm09
10.2144/00291bm09
CASPubMedWeb of Science®Google Scholar
Vasconcelos, H.L. & Bruna, E.M. (2012) Arthropod responses to the experimental isolation of Amazonian forest fragments. Zoologia, 29(6), 515–530. Available from: https://doi.org/10.1590/S1984-46702012000600003
10.1590/S1984-46702012000600003
Web of Science®Google Scholar
Vellend, M., Cornwell, W.K., Magnuson-Ford, K. & Mooers, A.Ø. (2010) Measuring phylogenetic biodiversity. In: A.E. Magurran & B.J. McGill (Eds.) Biological diversity: Frontiers in measurement and assessment. OUP Oxford, Oxford, UK.
Google Scholar
Weiher, E. (2011) A primer of trait and functional diversity. In: A.E. Magurran & B.J. McGill (Eds.) Biological diversity: Frontiers in measurement and assessment. Oxford: Oxford University Press, pp. 175–193.
Google Scholar
Wickham, H. (2016) ggplot2: elegant graphics for data analysis [Computer software]. Available from: https://ggplot2.tidyverse.org
Google Scholar
Wong, M.K.L., Guénard, B. & Lewis, O.T. (2019) Trait-based ecology of terrestrial arthropods. Biological Reviews, 94(3), 999–1022. Available from: https://doi.org/10.1111/brv.12488
10.1111/brv.12488
PubMedWeb of Science®Google Scholar
Zhang, J., Kapli, P., Pavlidis, P. & Stamatakis, A. (2013) A general species delimitation method with applications to phylogenetic placements. Bioinformatics, 29(22), 2869–2876. Available from: https://doi.org/10.1093/bioinformatics/btt499
10.1093/bioinformatics/btt499
CASPubMedWeb of Science®Google Scholar
Zhang, S.-Q., Che, L.-H., Li, Y., Dan Liang, D., Pang, H., Ślipiński, A. et al. (2018) Evolutionary history of Coleoptera revealed by extensive sampling of genes and species. Nature Communications, 9(1), 205. Available from: https://doi.org/10.1038/s41467-017-02644-4
10.1038/s41467-017-02644-4
PubMedWeb of Science®Google Scholar

Citing Literature

Volume17, Issue1

January 2024

Pages 31-50

Can immature stages be ignored in studies of forest leaf litter arthropod diversity? A test using Oxford Nanopore DNA barcoding

Abstract

CONFLICT OF INTEREST STATEMENT

Open Research

DATA AVAILABILITY STATEMENT

Supporting Information

REFERENCES

Citing Literature

References

Information

About Wiley Online Library

Help & Support

Opportunities

Connect with Wiley

Can immature stages be ignored in studies of forest leaf litter arthropod diversity? A test using Oxford Nanopore DNA barcoding

Abstract

CONFLICT OF INTEREST STATEMENT

Open Research

DATA AVAILABILITY STATEMENT

Supporting Information

REFERENCES

Citing Literature

References

Related

Information