REFERENCES
[dataset] Derycke, S. e. a. (2020). Scripts and links to
sequence data from the paper ”Optimisation of metabarcoding for
monitoring marine macrobenthos: primer choice and morphological traits
determine species detection in bulkDNA and eDNA from the ethanol
preservative” .
Alberdi, A., Aizpurua, O., Gilbert, M. T. P., & Bohmann, K. (2018).
Scrutinizing key steps for reliable metabarcoding of environmental
samples. Methods in Ecology and Evolution, 9 (1), 134-147.
doi:10.1111/2041-210x.12849
Andujar, C., Arribas, P., Yu, D. W., Vogler, A. P., & Emerson, B. C.
(2018). Why the COI barcode should be the community DNA metabarcode for
the metazoa. Molecular Ecology, 27 (20), 3968-3975.
doi:10.1111/mec.14844
Appeltans, W., Ahyong, S. T., Anderson, G., Angel, M. V., Artois, T.,
Bailly, N., . . . Costello, M. J. (2012). The Magnitude of Global Marine
Species Diversity. Current Biology, 22 (23), 2189-2202.
doi:10.1016/j.cub.2012.09.036
Aylagas, E., Borja, A., Irigoien, X., & Rodriguez-Ezpeleta, N. (2016).
Benchmarking DNA Metabarcoding for Biodiversity-Based Monitoring and
Assessment. Frontiers in Marine Science, 3 .
doi:10.3389/fmars.2016.00096
Aylagas, E., Borja, A., Muxika, I., & Rodriguez-Ezpeleta, N. (2018).
Adapting metabarcoding-based benthic biomonitoring into routine marine
ecological status assessment networks. Ecological Indicators, 95 ,
194-202. doi:10.1016/j.ecolind.2018.07.044
Aylagas, E., Mendibil, I., Borja, A., & Rodriguez-Ezpeleta, N. (2016).
Marine Sediment Sample Pre-processing for Macroinvertebrates
Metabarcoding: Mechanical Enrichment and Homogenization. Frontiers
in Marine Science, 3 . doi:10.3389/fmars.2016.00203
Barbier, E. B. (2017). Marine ecosystem services. Current Biology,
27 (11), R507-R510. doi:10.1016/j.cub.2017.03.020
Bates, D., Maechler, M., Bolker, B. M., & Walker, S. C. (2015). Fitting
Linear Mixed-Effects Models Using lme4. Journal of Statistical
Software, 67 (1), 1-48. doi:10.18637/jss.v067.i01
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery
rate - A practical and powerful approach to multiple testingJournal of the Royal Statistical Society Series B-Methodological,
57 (1), 289-300.
Bolger, A. M., Lohse, M., & Usadel, B. (2014). Trimmomatic: a flexible
trimmer for Illumina sequence data. Bioinformatics, 30 (15),
2114-2120. doi:10.1093/bioinformatics/btu170
Borja, A., Elliott, M., Snelgrove, P. V. R., Austen, M. C., Berg, T.,
Cochrane, S., . . . Wilson, C. (2016). Bridging the Gap between Policy
and Science in Assessing the Health Status of Marine Ecosystems.Frontiers in Marine Science, 3 . doi:10.3389/fmars.2016.00175
Braukmann, T. W. A., Ivanova, N. V., Prosser, S. W. J., Elbrecht, V.,
Steinke, D., Ratnasingham, S., . . . Hebert, P. D. N. (2019).
Metabarcoding a diverse arthropod mock community. Molecular
Ecology resources, 19 (3), 711-727. doi:10.1111/1755-0998.13008
Breine, N. T., De Backer, A., Van Colen, C., Moens, T., Hostens, K., &
Van Hoey, G. (2018). Structural and functional diversity of soft-bottom
macrobenthic communities in the Southern North Sea. Estuarine
Coastal and Shelf Science, 214 , 173-184. doi:10.1016/j.ecss.2018.09.012
Brusca, R. C., & Brusca, G. J. (2002). Invertebrates (Second
edition ed.). USA: Sinauer Associated Inc.
Callahan, B. J., McMurdie, P. J., Rosen, M. J., Han, A. W., Johnson, A.
J. A., & Holmes, S. P. (2016). DADA2: High-resolution sample inference
from Illumina amplicon data. Nature Methods, 13 (7), 581-+.
doi:10.1038/nmeth.3869
Carr, C. (2012). Polychaete diversity and distribution patterns in
Canadian marine waters. Marine Biodiversity, 42 (2), 93-107.
doi:10.1007/s12526-011-0095-y
Conway, J. R., Lex, A., & Gehlenborg, N. (2017). UpSetR: an R package
for the visualization of intersecting sets and their properties.Bioinformatics, 33 (18), 2938-2940.
doi:10.1093/bioinformatics/btx364
Degraer, S., Verfaillie, E., Willems, W., Adriaens, E., Vincx, M., &
Van Lancker, V. (2008). Habitat suitability modelling as a mapping tool
for macrobenthic communities: An example from the Belgian part of the
North Sea. Continental Shelf Research, 28 (3), 369-379.
doi:10.1016/j.csr.2007.09.001
Dixon, P. (2003). VEGAN, a package of R functions for community ecology.Journal of Vegetation Science, 14 (6), 927-930.
doi:10.1111/j.1654-1103.2003.tb02228.x
Douvere, F., Maes, F., Vanhulle, A., & Schrijvers, J. (2007). The role
of marine spatial planning in sea use management: The Belgian case.Marine Policy, 31 (2), 182-191. doi:10.1016/j.marpol.2006.07.003
Duncan, C., Thompson, J. R., & Pettorelli, N. (2015). The quest for a
mechanistic understanding of biodiversity-ecosystem services
relationships. Proceedings of the Royal Society B-Biological
Sciences, 282 (1817). doi:10.1098/rspb.2015.1348
Elbrecht, V., & Leese, F. (2017). Validation and Development of COI
Metabarcoding Primers for Freshwater Macroinvertebrate Bioassessment.Frontiers in Environmental Science, 5 .
doi:10.3389/fenvs.2017.00011
Elbrecht, V., Peinert, B., & Leese, F. (2017). Sorting things out:
Assessing effects of unequal specimen biomass on DNA metabarcoding.Ecology and Evolution, 7 (17), 6918-6926. doi:10.1002/ece3.3192
Elbrecht, V., Vamos, E. E., Meissner, K., Aroviita, J., & Leese, F.
(2017). Assessing strengths and weaknesses of DNA metabarcoding-based
macroinvertebrate identification for routine stream monitoring.Methods in Ecology and Evolution, 8 (10), 1265-1275.
doi:10.1111/2041-210x.12789
Elliott, S. A. M., Guerin, L., Pesch, R., Schmitt, P., Meakins, B.,
Vina-Herbon, C., . . . Serrano, A. (2018). Integrating benthic habitat
indicators: Working towards an ecosystem approach. Marine Policy,
90 , 88-94. doi:10.1016/j.marpol.2018.01.003
Ewels, P., Magnusson, M., Lundin, S., & Kaller, M. (2016). MultiQC:
summarize analysis results for multiple tools and samples in a single
report. Bioinformatics, 32 (19), 3047-3048.
doi:10.1093/bioinformatics/btw354
Ficetola, G. F., Coissac, E., Zundel, S., Riaz, T., Shehzad, W.,
Bessiere, J., . . . Pompanon, F. (2010). An In silico approach for the
evaluation of DNA barcodes. BMC Genomics, 11 .
doi:10.1186/1471-2164-11-434
Folmer, O., Black, M., Hoeh, W., Lutz, R., & R, V. (1994). DNA primers
for amplification of mitochondrial cytochrome c oxidase subunit I from
diverse metazoan invertebrates. Molecular Marine Biology and
Biotechnology, 3 , 294-299.
Fox, J., & Weisberg, S. (2019). An {R} Companion to Applied
Regression . Thousand Oaks, CA: Sage.
Gauthier, M., Konecny-Dupre, L., Nguyen, A., Elbrecht, V., Datry, T.,
Douady, C., & Lefebure, T. (2020). Enhancing DNA metabarcoding
performance and applicability with bait capture enrichment and DNA from
conservative ethanol. Molecular Ecology resources, 20 (1), 79-96.
doi:10.1111/1755-0998.13088
Giebner, H., Langen, K., Bourlat, S. J., Kukowka, S., Mayer, C., Astrin,
J. J., . . . Fonseca, V. G. (2020). Comparing diversity levels in
environmental samples: DNA sequence capture and metabarcoding approaches
using 18S and COI genes. Molecular Ecology resources .
doi:10.1111/1755-0998.13201
Goodwin, K. D., Thompson, L. R., Duarte, B., Kahlke, T., Thompson, A.
R., Marques, J. C., & Cacador, I. (2017). DNA Sequencing as a Tool to
Monitor Marine Ecological Status. Frontiers in Marine Science, 4 .
doi:10.3389/fmars.2017.00107
Hajibabaei, M., Porter, T. M., Robinson, C. V., Baird, D. J., Shokralla,
S., & Wright, M. T. G. (2019). Watered-down biodiversity? A comparison
of metabarcoding results from DNA extracted from matched water and bulk
tissue biomonitoring samples. PLoS ONE, 14 (12).
doi:10.1371/journal.pone.0225409
Halpern, B. S., Longo, C., Lowndes, J. S. S., Best, B. D., Frazier, M.,
Katona, S. K., . . . Selig, E. R. (2015). Patterns and Emerging Trends
in Global Ocean Health. PLoS ONE, 10 (3).
doi:10.1371/journal.pone.0117863
Hollatz, C., Leite, B. R., Lobo, J., Froufe, H., Egas, C., & Costa, F.
O. (2017). Priming of a DNA metabarcoding approach for species
identification and inventory in marine macrobenthic communities.Genome, 60 (3), 260-271. doi:10.1139/gen-2015-0220
Kebschull, J. M., & Zador, A. M. (2015). Sources of PCR-induced
distortions in high-throughput sequencing data sets. Nucleic Acids
Research, 43 (21). doi:10.1093/nar/gkv717
Lenth, R. (2020). emmeans: Estimated Marginal Means, aka Least-Squares
Means. R package version 1.4.7.
Leray, M., & Knowlton, N. (2015). DNA barcoding and metabarcoding of
standardized samples reveal patterns of marine benthic diversity.Proceedings of the National Academy of Sciences of the United
States of America, 112 (7), 2076-2081. doi:10.1073/pnas.1424997112
Leray, M., Yang, J. Y., Meyer, C. P., Mills, S. C., Agudelo, N., Ranwez,
V., . . . Machida, R. J. (2013). A new versatile primer set targeting a
short fragment of the mitochondrial COI region for metabarcoding
metazoan diversity: application for characterizing coral reef fish gut
contents. Frontiers in Zoology, 10 . doi:10.1186/1742-9994-10-34
Lobo, J., Costa, P. M., Teixeira, M. A. L., Ferreira, M. S. G., Costa,
M. H., & Costa, F. O. (2013). Enhanced primers for amplification of DNA
barcodes from a broad range of marine metazoans. BMC Ecology, 13 .
doi:10.1186/1472-6785-13-34
Lobo, J., Shokralla, S., Costa, M. H., Hajibabaei, M., & Costa, F. O.
(2017). DNA metabarcoding for high-throughput monitoring of estuarine
macrobenthic communities. Sci Rep, 7 .
doi:10.1038/s41598-017-15823-6
Macheriotou, L., Guilini, K., Bezerra, T. N., Tytgat, B., Nguyen, D. T.,
Nguyen, T. X. P., . . . Derycke, S. (2019). Metabarcoding free-living
marine nematodes using curated 18S and CO1 reference sequence databases
for species-level taxonomic assignments. Ecology and Evolution,
9 (3), 1211-1226. doi:10.1002/ece3.4814
Machida, R. J., Leray, M., Ho, S. L., & Knowlton, N. (2017). Data
Descriptor: Metazoan mitochondrial gene sequence reference datasets for
taxonomic assignment of environmental samples. Scientific Data,
4 . doi:10.1038/sdata.2017.27
Marquina, D., Andersson, A. F., & Ronquist, F. (2019). New
mitochondrial primers for metabarcoding of insects, designed and
evaluated using in silico methods. Molecular Ecology resources,
19 (1), 90-104. doi:10.1111/1755-0998.12942
Marquina, D., Esparza-Salas, R., Roslin, T., & Ronquist, F. (2019).
Establishing arthropod community composition using metabarcoding:
Surprising inconsistencies between soil samples and preservative ethanol
and homogenate from Malaise trap catches. Molecular Ecology
resources, 19 (6), 1516-1530. doi:10.1111/1755-0998.13071
Martinez Arbizu, P. (2019). pairwiseAdonis: Pairwise multilevel
comparison using adonis. (Version R package version 0.3). Retrieved from
https://github.com/pmartinezarbizu/pairwiseAdonis
Martins, F. M. S., Galhardo, M., Filipe, A. F., Teixeira, A., Pinheiro,
P., Pauperio, J., . . . Beja, P. (2019). Have the cake and eat it:
Optimizing nondestructive DNA metabarcoding of macroinvertebrate samples
for freshwater biomonitoring. Molecular Ecology resources, 19 (4),
863-876. doi:10.1111/1755-0998.13012
Mora, C., Tittensor, D. P., Adl, S., Simpson, A. G. B., & Worm, B.
(2011). How Many Species Are There on Earth and in the Ocean? PLoS
Biology, 9 (8). doi:10.1371/journal.pbio.1001127
Motokawa, T. (1984). CONNECTIVE-TISSUE CATCH IN ECHINODERMS.Biological Reviews of the Cambridge Philosophical Society, 59 (2),
255-270. doi:10.1111/j.1469-185X.1984.tb00409.x
Pawlowski, J., Kelly-Quinn, M., Altermatt, F., Apotheloz-Perret-Gentil,
L., Beja, P., Boggero, A., . . . Kahlert, M. (2018). The future of
biotic indices in the ecogenomic era: Integrating (e) DNA metabarcoding
in biological assessment of aquatic ecosystems. Science of the
Total Environment, 637 , 1295-1310. doi:10.1016/j.scitotenv.2018.05.002
Porter, T. M., & Hajibabaei, M. (2018). Automated high throughput
animal CO1 metabarcode classification. Sci Rep, 8 .
doi:10.1038/s41598-018-22505-4
Quinn, G., & Keough, M. (2002). Experimental design and data
analysis for biologists . New York: Cambridge University Press.
Ritari, J., Salojarvi, J., Lahti, L., & de Vos, W. M. (2015). Improved
taxonomic assignment of human intestinal 16S rRNA sequences by a
dedicated reference database. BMC Genomics, 16 .
doi:10.1186/s12864-015-2265-y
Solan, M., Cardinale, B. J., Downing, A. L., Engelhardt, K. A. M.,
Ruesink, J. L., & Srivastava, D. S. (2004). Extinction and ecosystem
function in the marine benthos. Science, 306 (5699), 1177-1180.
doi:10.1126/science.1103960
Team, R. C. (2019). R: A language and environment for statistical
computing. Vienna, Austria: R Foundation for Statistical Computing.
Retrieved from http://www.R-project.org
Van Hoey, G., Degraer, S., & Vincx, M. (2004). Macrobenthic community
structure of soft-bottom sediments at the Belgian Continental Shelf.Estuarine Coastal and Shelf Science, 59 (4), 599-613.
doi:10.1016/j.ecss.2003.11.005
Van Hoey, G., Wischnewski, J., Craeymeersch, J., Dannheim, J., Enserink,
L., Guerin, L., . . . Birchenough, S. N. R. (2019). Methodological
elements for optimising the spatial monitoring design to support
regional benthic ecosystem assessments. Environmental Monitoring
and Assessment, 191 (7). doi:10.1007/s10661-019-7550-9
Wang, Q., Garrity, G. M., Tiedje, J. M., & Cole, J. R. (2007). Naive
Bayesian classifier for rapid assignment of rRNA sequences into the new
bacterial taxonomy. Applied and Environmental Microbiology,
73 (16), 5261-5267. doi:10.1128/aem.00062-07
Wangensteen, O. S., Palacin, C., Guardiola, M., & Turon, X. (2018). DNA
metabarcoding of littoral hard-bottom communities: high diversity and
database gaps revealed by two molecular markers. Peerj, 6 .
doi:10.7717/peerj.4705
Zenker, M. M., Specht, A., & Fonseca, V. G. (2020). Assessing insect
biodiversity with automatic light traps in Brazil: Pearls and pitfalls
of metabarcoding samples in preservative ethanol. Ecology and
Evolution, 10 (5), 2352-2366. doi:10.1002/ece3.6042
Zizka, V. M. A., Elbrecht, V., Macher, J. N., & Leese, F. (2019).
Assessing the influence of sample tagging and library preparation on DNA
metabarcoding. Molecular Ecology resources, 19 (4), 893-899.
doi:10.1111/1755-0998.13018
Zizka, V. M. A., Leese, F., Peinert, B., & Geiger, M. F. (2019). DNA
metabarcoding from sample fixative as a quick and voucher-preserving
biodiversity assessment method. Genome, 62 (3), 122-136.
doi:10.1139/gen-2018-0048