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The Tree of Life eDNA metabarcoding reveals a similar taxonomic richness but dissimilar evolutionary lineages between seaports and marine reserves (metazoa data)

This dataset is associated to the following publication: Macé, B., Mouillot, D., Dalongeville, A., Bruno, M., Deter, J., Varenne, A., Gudefin, A., Boissery, P., & Manel, S. (2024). The Tree of Life eDNA metabarcoding reveals a similar taxonomic richness but dissimilar evolutionary lineages between seaports and marine reserves. Molecular Ecology, e17373. <a href="https://doi.org/10.1111/mec.17373">https://doi.org/10.1111/mec.17373</a> It contains the data obtained with the metazoa marker: <ul> <li>fastq files are the raw NGS eDNA sequencing outputs</li> <li>dat file records the adapters names and oligos used for sequencing</li> </ul> Metadata associated to each eDNA sample are also provided.   Methods <blockquote> eDNA extractions were performed in a BSL-2 lab dedicated for eDNA samples following the protocol described in Polanco Fernández et al. (2021). Four PCR amplifications were conducted with different assays covering the whole tree of life. The teleo primer pair (Valentini et al., 2016) targets a 12S mitochondrial DNA marker from teleosts and elasmobranchs; the metazoa primer pair (Kelly et al., 2016) targets a 16S mitochondrial DNA marker from metazoans; the euka2 primer pair (Guardiola et al., 2015) targets a marker from eukaryotes located on the V7 region of the 18S ribosomal RNA; and the bact2 primer pair (Taberlet et al., 2018) targets a marker from prokaryotes located on the V4 region of the 16S ribosomal RNA. The idea of this experimental design is to give a holistic overview of communities, with a nested hierarchy euka2-metazoa-teleo to obtain a finer taxonomic resolution over animal communities, and particularly fish. Twelve PCR replicates per sample were run, with negative extractions and PCR positive and negative controls analyzed in parallel. Unique tags were used for each PCR replicate amplified with the teleo primers only, allowing to differentiate them in the bioinformatic analysis (see after). NGS library preparation and MiSeq paired-end sequencing (2 × 150 bp) were performed at DNA Gensee (Le Bourget-du-Lac, France). </blockquote>   References Guardiola, M., Uriz, M. J., Taberlet, P., Coissac, E., Wangensteen, O. S., & Turon, X. (2015). Deep-Sea, Deep-Sequencing: Metabarcoding Extracellular DNA from Sediments of Marine Canyons. PLOS ONE, 10(10), e0139633. https://doi.org/10.1371/journal.pone.0139633 Kelly, R. P., O’Donnell, J. L., Lowell, N. C., Shelton, A. O., Samhouri, J. F., Hennessey, S. M., Feist, B. E., & Williams, G. D. (2016). Genetic signatures of ecological diversity along an urbanization gradient. PeerJ, 4, e2444. https://doi.org/10.7717/peerj.2444 Polanco Fernández, A., Marques, V., Fopp, F., Juhel, J.-B., Borrero-Pérez, G. H., Cheutin, M.-C., Dejean, T., González Corredor, J. D., Acosta-Chaparro, A., Hocdé, R., Eme, D., Maire, E., Spescha, M., Valentini, A., Manel, S., Mouillot, D., Albouy, C., & Pellissier, L. (2021). Comparing environmental DNA metabarcoding and underwater visual census to monitor tropical reef fishes. Environmental DNA, 3(1), 142–156. https://doi.org/10.1002/edn3.140 Taberlet, P., Bonin, A., Zinger, L., & Coissac, E. (2018). Environmental DNA: For Biodiversity Research and Monitoring. Oxford University Press. Valentini, A., Taberlet, P., Miaud, C., Civade, R., Herder, J., Thomsen, P. F., Bellemain, E., Besnard, A., Coissac, E., Boyer, F., Gaboriaud, C., Jean, P., Poulet, N., Roset, N., Copp, G. H., Geniez, P., Pont, D., Argillier, C., Baudoin, J.-M., … Dejean, T. (2016). Next-generation monitoring of aquatic biodiversity using environmental DNA metabarcoding. Molecular Ecology, 25(4), 929–942. https://doi.org/10.1111/mec.13428

The Tree of Life eDNA metabarcoding reveals a similar taxonomic richness but dissimilar evolutionary lineages between seaports and marine reserves (bact2 data)

This dataset is associated to the following publication: Macé, B., Mouillot, D., Dalongeville, A., Bruno, M., Deter, J., Varenne, A., Gudefin, A., Boissery, P., & Manel, S. (2024). The Tree of Life eDNA metabarcoding reveals a similar taxonomic richness but dissimilar evolutionary lineages between seaports and marine reserves. Molecular Ecology, e17373. <a href="https://doi.org/10.1111/mec.17373">https://doi.org/10.1111/mec.17373</a> It contains the data obtained with the bact2 marker: <ul> <li>fastq files are the raw NGS eDNA sequencing outputs</li> <li>dat file records the adapters names and oligos used for sequencing</li> </ul> Metadata associated to each eDNA sample are also provided.   Methods <blockquote> eDNA extractions were performed in a BSL-2 lab dedicated for eDNA samples following the protocol described in Polanco Fernández et al. (2021). Four PCR amplifications were conducted with different assays covering the whole tree of life. The teleo primer pair (Valentini et al., 2016) targets a 12S mitochondrial DNA marker from teleosts and elasmobranchs; the metazoa primer pair (Kelly et al., 2016) targets a 16S mitochondrial DNA marker from metazoans; the euka2 primer pair (Guardiola et al., 2015) targets a marker from eukaryotes located on the V7 region of the 18S ribosomal RNA; and the bact2 primer pair (Taberlet et al., 2018) targets a marker from prokaryotes located on the V4 region of the 16S ribosomal RNA. The idea of this experimental design is to give a holistic overview of communities, with a nested hierarchy euka2-metazoa-teleo to obtain a finer taxonomic resolution over animal communities, and particularly fish. Twelve PCR replicates per sample were run, with negative extractions and PCR positive and negative controls analyzed in parallel. Unique tags were used for each PCR replicate amplified with the teleo primers only, allowing to differentiate them in the bioinformatic analysis (see after). NGS library preparation and MiSeq paired-end sequencing (2 × 150 bp) were performed at DNA Gensee (Le Bourget-du-Lac, France). </blockquote>   References Guardiola, M., Uriz, M. J., Taberlet, P., Coissac, E., Wangensteen, O. S., & Turon, X. (2015). Deep-Sea, Deep-Sequencing: Metabarcoding Extracellular DNA from Sediments of Marine Canyons. PLOS ONE, 10(10), e0139633. https://doi.org/10.1371/journal.pone.0139633 Kelly, R. P., O’Donnell, J. L., Lowell, N. C., Shelton, A. O., Samhouri, J. F., Hennessey, S. M., Feist, B. E., & Williams, G. D. (2016). Genetic signatures of ecological diversity along an urbanization gradient. PeerJ, 4, e2444. https://doi.org/10.7717/peerj.2444 Polanco Fernández, A., Marques, V., Fopp, F., Juhel, J.-B., Borrero-Pérez, G. H., Cheutin, M.-C., Dejean, T., González Corredor, J. D., Acosta-Chaparro, A., Hocdé, R., Eme, D., Maire, E., Spescha, M., Valentini, A., Manel, S., Mouillot, D., Albouy, C., & Pellissier, L. (2021). Comparing environmental DNA metabarcoding and underwater visual census to monitor tropical reef fishes. Environmental DNA, 3(1), 142–156. https://doi.org/10.1002/edn3.140 Taberlet, P., Bonin, A., Zinger, L., & Coissac, E. (2018). Environmental DNA: For Biodiversity Research and Monitoring. Oxford University Press. Valentini, A., Taberlet, P., Miaud, C., Civade, R., Herder, J., Thomsen, P. F., Bellemain, E., Besnard, A., Coissac, E., Boyer, F., Gaboriaud, C., Jean, P., Poulet, N., Roset, N., Copp, G. H., Geniez, P., Pont, D., Argillier, C., Baudoin, J.-M., … Dejean, T. (2016). Next-generation monitoring of aquatic biodiversity using environmental DNA metabarcoding. Molecular Ecology, 25(4), 929–942. https://doi.org/10.1111/mec.13428

The Tree of Life eDNA metabarcoding reveals a similar taxonomic richness but dissimilar evolutionary lineages between seaports and marine reserves (euka2 data)

This dataset is associated to the following publication: Macé, B., Mouillot, D., Dalongeville, A., Bruno, M., Deter, J., Varenne, A., Gudefin, A., Boissery, P., & Manel, S. (2024). The Tree of Life eDNA metabarcoding reveals a similar taxonomic richness but dissimilar evolutionary lineages between seaports and marine reserves. Molecular Ecology, e17373. <a href="https://doi.org/10.1111/mec.17373">https://doi.org/10.1111/mec.17373</a> It contains the data obtained with the euka2 marker: <ul> <li>fastq files are the raw NGS eDNA sequencing outputs</li> <li>dat file records the adapters names and oligos used for sequencing</li> </ul> Metadata associated to each eDNA sample are also provided.   Methods <blockquote> eDNA extractions were performed in a BSL-2 lab dedicated for eDNA samples following the protocol described in Polanco Fernández et al. (2021). Four PCR amplifications were conducted with different assays covering the whole tree of life. The teleo primer pair (Valentini et al., 2016) targets a 12S mitochondrial DNA marker from teleosts and elasmobranchs; the metazoa primer pair (Kelly et al., 2016) targets a 16S mitochondrial DNA marker from metazoans; the euka2 primer pair (Guardiola et al., 2015) targets a marker from eukaryotes located on the V7 region of the 18S ribosomal RNA; and the bact2 primer pair (Taberlet et al., 2018) targets a marker from prokaryotes located on the V4 region of the 16S ribosomal RNA. The idea of this experimental design is to give a holistic overview of communities, with a nested hierarchy euka2-metazoa-teleo to obtain a finer taxonomic resolution over animal communities, and particularly fish. Twelve PCR replicates per sample were run, with negative extractions and PCR positive and negative controls analyzed in parallel. Unique tags were used for each PCR replicate amplified with the teleo primers only, allowing to differentiate them in the bioinformatic analysis (see after). NGS library preparation and MiSeq paired-end sequencing (2 × 150 bp) were performed at DNA Gensee (Le Bourget-du-Lac, France). </blockquote>   References Guardiola, M., Uriz, M. J., Taberlet, P., Coissac, E., Wangensteen, O. S., & Turon, X. (2015). Deep-Sea, Deep-Sequencing: Metabarcoding Extracellular DNA from Sediments of Marine Canyons. PLOS ONE, 10(10), e0139633. https://doi.org/10.1371/journal.pone.0139633 Kelly, R. P., O’Donnell, J. L., Lowell, N. C., Shelton, A. O., Samhouri, J. F., Hennessey, S. M., Feist, B. E., & Williams, G. D. (2016). Genetic signatures of ecological diversity along an urbanization gradient. PeerJ, 4, e2444. https://doi.org/10.7717/peerj.2444 Polanco Fernández, A., Marques, V., Fopp, F., Juhel, J.-B., Borrero-Pérez, G. H., Cheutin, M.-C., Dejean, T., González Corredor, J. D., Acosta-Chaparro, A., Hocdé, R., Eme, D., Maire, E., Spescha, M., Valentini, A., Manel, S., Mouillot, D., Albouy, C., & Pellissier, L. (2021). Comparing environmental DNA metabarcoding and underwater visual census to monitor tropical reef fishes. Environmental DNA, 3(1), 142–156. https://doi.org/10.1002/edn3.140 Taberlet, P., Bonin, A., Zinger, L., & Coissac, E. (2018). Environmental DNA: For Biodiversity Research and Monitoring. Oxford University Press. Valentini, A., Taberlet, P., Miaud, C., Civade, R., Herder, J., Thomsen, P. F., Bellemain, E., Besnard, A., Coissac, E., Boyer, F., Gaboriaud, C., Jean, P., Poulet, N., Roset, N., Copp, G. H., Geniez, P., Pont, D., Argillier, C., Baudoin, J.-M., … Dejean, T. (2016). Next-generation monitoring of aquatic biodiversity using environmental DNA metabarcoding. Molecular Ecology, 25(4), 929–942. https://doi.org/10.1111/mec.13428

The Tree of Life eDNA metabarcoding reveals a similar taxonomic richness but dissimilar evolutionary lineages between seaports and marine reserves (teleo data)

This dataset is associated to the following publication: Macé, B., Mouillot, D., Dalongeville, A., Bruno, M., Deter, J., Varenne, A., Gudefin, A., Boissery, P., & Manel, S. (2024). The Tree of Life eDNA metabarcoding reveals a similar taxonomic richness but dissimilar evolutionary lineages between seaports and marine reserves. Molecular Ecology, e17373. <a href="https://doi.org/10.1111/mec.17373">https://doi.org/10.1111/mec.17373</a> It contains the data obtained with the teleo marker: <ul> <li>fastq files are the raw NGS eDNA sequencing outputs</li> <li>dat file records the adapters names and oligos used for sequencing</li> </ul> Metadata associated to each eDNA sample are also provided.   Methods <blockquote> eDNA extractions were performed in a BSL-2 lab dedicated for eDNA samples following the protocol described in Polanco Fernández et al. (2021). Four PCR amplifications were conducted with different assays covering the whole tree of life. The teleo primer pair (Valentini et al., 2016) targets a 12S mitochondrial DNA marker from teleosts and elasmobranchs; the metazoa primer pair (Kelly et al., 2016) targets a 16S mitochondrial DNA marker from metazoans; the euka2 primer pair (Guardiola et al., 2015) targets a marker from eukaryotes located on the V7 region of the 18S ribosomal RNA; and the bact2 primer pair (Taberlet et al., 2018) targets a marker from prokaryotes located on the V4 region of the 16S ribosomal RNA. The idea of this experimental design is to give a holistic overview of communities, with a nested hierarchy euka2-metazoa-teleo to obtain a finer taxonomic resolution over animal communities, and particularly fish. Twelve PCR replicates per sample were run, with negative extractions and PCR positive and negative controls analyzed in parallel. Unique tags were used for each PCR replicate amplified with the teleo primers only, allowing to differentiate them in the bioinformatic analysis (see after). NGS library preparation and MiSeq paired-end sequencing (2 × 150 bp) were performed at DNA Gensee (Le Bourget-du-Lac, France). </blockquote>   References Guardiola, M., Uriz, M. J., Taberlet, P., Coissac, E., Wangensteen, O. S., & Turon, X. (2015). Deep-Sea, Deep-Sequencing: Metabarcoding Extracellular DNA from Sediments of Marine Canyons. PLOS ONE, 10(10), e0139633. https://doi.org/10.1371/journal.pone.0139633 Kelly, R. P., O’Donnell, J. L., Lowell, N. C., Shelton, A. O., Samhouri, J. F., Hennessey, S. M., Feist, B. E., & Williams, G. D. (2016). Genetic signatures of ecological diversity along an urbanization gradient. PeerJ, 4, e2444. https://doi.org/10.7717/peerj.2444 Polanco Fernández, A., Marques, V., Fopp, F., Juhel, J.-B., Borrero-Pérez, G. H., Cheutin, M.-C., Dejean, T., González Corredor, J. D., Acosta-Chaparro, A., Hocdé, R., Eme, D., Maire, E., Spescha, M., Valentini, A., Manel, S., Mouillot, D., Albouy, C., & Pellissier, L. (2021). Comparing environmental DNA metabarcoding and underwater visual census to monitor tropical reef fishes. Environmental DNA, 3(1), 142–156. https://doi.org/10.1002/edn3.140 Taberlet, P., Bonin, A., Zinger, L., & Coissac, E. (2018). Environmental DNA: For Biodiversity Research and Monitoring. Oxford University Press. Valentini, A., Taberlet, P., Miaud, C., Civade, R., Herder, J., Thomsen, P. F., Bellemain, E., Besnard, A., Coissac, E., Boyer, F., Gaboriaud, C., Jean, P., Poulet, N., Roset, N., Copp, G. H., Geniez, P., Pont, D., Argillier, C., Baudoin, J.-M., … Dejean, T. (2016). Next-generation monitoring of aquatic biodiversity using environmental DNA metabarcoding. Molecular Ecology, 25(4), 929–942. https://doi.org/10.1111/mec.13428

opencc-zeroMay 2024View details →

Data from: Increased intake of tree forage by moose is associated with intake of crops rich in non-structural carbohydrates

Animals representing a wide range of taxonomic groups are known to select specific food combinations to achieve a nutritionally balanced diet. The nutrient balancing hypothesis suggests that, when given the opportunity, animals select foods to achieve a particular target nutrient balance, and that balancing occurs between meals and between days. For wild ruminants who inhabit landscapes dominated by human land use, nutritionally imbalanced diets can result from ingesting agricultural crops rich in starch and sugar (non-structural carbohydrates, NC), which can be provided to them by people as supplementary feeds. Here, we test the nutrient balancing hypothesis by assessing potential effects that the ingestion of such crops by Alces alces (moose) may have on forage intake. We predicted that moose compensate for an imbalanced intake of excess NC by selecting tree forage with macro-nutritional content better suited for their rumen microbiome during wintertime. We applied DNA metabarcoding to identify plants in faecal and rumen content from the same moose during winter in Sweden. We found that the concentration of NC-rich crops in faeces predicted the presence of Picea abies (Norway spruce) in rumen samples. The finding is consistent with the prediction that moose use tree forage as a nutritionally complementary resource to balance their intake of NC-rich foods, and that they ingested P. abies in particular (normally a forage rarely eaten by moose) because it was the most readily available tree. Our finding sheds new light on the foraging behaviour of a model species in herbivore ecology, and on how habitat alterations by humans may change the behaviour of wildlife.

opencc-by-4.0Aug 2021View details →

Tree species richness differentially affects the chemical composition of leaves, roots and root exudates in four subtropical tree species - Sampling Raw Data

Sampling Raw Data for the manuscript "Tree species richness differentially affects the chemical composition of leaves, roots and root exudates in four subtropical tree species "  R Code for producing the sunburst plots from the data obtained by classyFire

opencc-zeroSep 2023View details →

Data to: Remotely sensed tree height and density explain global gliding vertebrate richness

In vertebrates, gliding evolved as a mode of energy-efficient locomotion to move between trees. Gliding vertebrate richness is hypothesised to increase with tree height and decrease with tree density but empirical evidence for this is scarce, especially at a global scale. Here, we test the ability of tree height and density to explain species richness of gliding vertebrates globally compared to richness of all vertebrates, while controlling for biogeographical and climatic factors. We compiled a global database of 193 gliding amphibians, mammals and reptiles and created maps of species richness from extent-of-occurrence range maps. We paired species richness of gliding vertebrates with spatial estimates of global tree height and density and biogeographical regions as covariates to account for ecological differences among global regions. We used univariate linear and multivariate generalised linear mixed-effect models to evaluate relationships between species richness and tree height and density and the interaction between both. We found that richness of all gliding vertebrate species increased significantly with tree height, while results for richness of amphibians, mammals and reptiles alone indicated mixed responses, especially among different biogeographical regions. Mixed-effect models mirrored these results for richness of all species combined, while also revealing the mixed responses to tree height and density of richness of amphibians, mammals and reptiles. Richness of all vertebrate species – gliding and non-gliding – also increased with tree height and density but at a lesser rate than richness of gliding vertebrates indicating a greater influence of forest structure on richness patterns of gliding vertebrates. Our results support hypotheses stating that gliding in vertebrates globally evolved in tall forests as energy-efficient locomotion between trees and provide further evidence for the importance of forest structure to explain the distribution of gliding vertebrates.

opencc-zeroOct 2023View details →

Tree species richness around urban red maples reduces pest abundance but does not enhance biological control

Urban trees often host greater insect pest abundance than trees in rural forests. This may be due, in part, to differences in tree diversity and canopy cover between these settings. Urban trees are often planted in isolation or monoculture, which favors pest accumulation. The gloomy scale, Melanaspis tenebricosa Comstock, is a pest of urban red maples (Acer rubrum L.) that is abundant where impervious surfaces dominate the local landscape. Increasing tree diversity and canopy cover around urban red maples may reduce gloomy scale abundance by supporting natural enemy communities. We investigated the effect that surrounding tree species richness and tree canopy cover had on gloomy scale abundance, natural enemy abundance, and biological control in red maple trees in Raleigh, NC, USA. We collected scales and natural enemies from red maples that spanned a gradient of tree species richness, canopy cover, and impervious surface values. We also measured gloomy scale parasitism and predation of sentinel prey in red maple canopies. Greater tree species richness and canopy cover were associated with lower gloomy scale density. Red maples in diverse settings also hosted fewer scales per natural enemy. Parasitoids were less common in maples in diverse settings, but generalist predator abundance was unaffected by tree diversity. Finally, tree species richness and canopy cover did not increase biological control of scales or sentinel prey. Our findings suggest that higher tree diversity and greater canopy cover may reduce gloomy scale density, but this is not entirely explained by the effects of natural enemies and biological control.

opencc-by-sa-4.0Oct 2023View details →

Data from: Leaf trait variation within individuals mediates the relationship between tree species richness and productivity

This dataset contains tree biometry data and leaf trait data of the Kreinitz Tree Diversity Experiment. In winter 2013/14 and winter 2016/17, height and basal area were measured for all 2880 individuals of the Kreinitz experiment. Tree biometry data is available in the file Data_Kreinitz_Tree.xlsx. In summer 2017, leaf traits for 283 selected trees were measured via near-infrared spectroscopy. For each tree, samples were taken from approximately 3 levels in the trees' crown (total 843 levels). At each level, approximately 4 leaves were harvested (total 3656 leaves) and scanned in triplicates (total 10986 scans). Sampled leaves were scanned on the day of harvest. Leaf trait data is available in the file Data_Kreinitz_Leaf.xlsx.

publicOct 2023View details →

Tree species richness around urban red maples reduces pest abundance but does not enhance biological control

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publicMay 2024View details →

Data from: Increased intake of tree forage by moose is associated with intake of crops rich in non-structural carbohydrates

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publicSep 2023View details →

Data to: Remotely sensed tree height and density explain global gliding vertebrate richness

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publicSep 2024View details →

Tree species richness suppresses red imported fire ant invasion in a subtropical plantation forest

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publicApr 2024View details →

Differential effects of tree species identity on rhizospheric bacterial and fungal community richness and composition across multiple trace element-contaminated sites

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