The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
Meta‐analysis supports further refinement of eDNA for monitoring aquatic species‐specific abundance in nature
Open accessAbstract
The use of eDNA to detect the presence/absence of rare or invasive species is well documented and its use in biodiversity monitoring is expanding. Preliminary laboratory research has also shown a positive correlation between the concentration of species‐specific eDNA particles and the density/biomass of a species in a given environment. However, the extent to which these results can be extended to natural environments has yet to be formally quantified. We collated data from experiments that examined the correlation between eDNA and two metrics of abundance (biomass and density) and, using mixed‐effects meta‐analysis, quantified the strength of that correlation across laboratory and natural environments. We found that eDNA particle concentration was more strongly correlated with abundance in laboratory environments compared to natural environments, accounting for approximately 82% and 57% of the observed variation in abundance, respectively. We found some evidence of potential publication bias that may have impacted the estimation of the correlation in natural environments; after smaller studies were removed from the dataset, eDNA particle concentration accounted for approximately 50% of the observed variation in abundance in natural environments. No effect of abundance metric was found on the strength of correlation between eDNA particle concentration and abundance. Despite a weaker general correlation in natural environments, eDNA concentration often still explained substantial variation in abundance. eDNA research is still an emergent field of study; with only moderate improvements in technology or technique, it could represent a powerful new tool for quantifying abundance.
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Cites
Conducting Meta-Analyses in R with the metafor Package
Viechtbauer, W. (2010) · Journal of Statistical Software · doi:10.18637/jss.v036.i03 · Cited by 20,464
VII. Note on regression and inheritance in the case of two parents
Pearson, K. (1895) · Proceedings of the Royal Society of London · doi:10.1098/rspl.1895.0041 · Cited by 3,424
On the probable error of a coefficient of correlation deduced from a small sample
Fisher, R. A. (1921) · Adelaide Research & Scholarship (AR&S) (University of Adelaide) · Cited by 2,089
Monitoring endangered freshwater biodiversity using environmental DNA
THOMSEN, P. F., KIELGAST, J., IVERSEN, L. L., WIUF, C., RASMUSSEN, M., GILBERT, M. T. P., ORLANDO, L., & WILLERSLEV, E. (2012) · Molecular Ecology · doi:10.1111/j.1365-294x.2011.05418.x · Cited by 1,184
The ecology of environmental DNA and implications for conservation genetics
Barnes, M. A., & Turner, C. R. (2016) · Conservation Genetics · doi:10.1007/s10592-015-0775-4 · Cited by 1,139
Environmental Conditions Influence eDNA Persistence in Aquatic Systems
Barnes, M. A., Turner, C. R., Jerde, C. L., Renshaw, M. A., Chadderton, W. L., & Lodge, D. M. (2014) · Environmental Science & Technology · doi:10.1021/es404734p · Cited by 939
Quantifying effects of UV-B, temperature, and pH on eDNA degradation in aquatic microcosms
Strickler, K. M., Fremier, A. K., & Goldberg, C. S. (2015) · Biological Conservation · doi:10.1016/j.biocon.2014.11.038 · Cited by 901
Estimation of Fish Biomass Using Environmental DNA
Takahara, T., Minamoto, T., Yamanaka, H., Doi, H., & Kawabata, Z. (2012) · PLoS ONE · doi:10.1371/journal.pone.0035868 · Cited by 863
Bias in meta-analysis detected by a simple, graphical
Stuck, A. E., Rubenstein, L. Z., Wieland, D., Vandenbroucke, J. P., Irwig, L., Macaskill, P., Berry, G., Glasziou, P., Seagroatt, V., Stratton, I., et al. (1998) · BMJ · doi:10.1136/bmj.316.7129.469 · Cited by 699
Luikart, G., Ryman, N., Tallmon, D. A., Schwartz, M. K., & Allendorf, F. W. (2010) · Conservation Genetics · doi:10.1007/s10592-010-0050-7 · Cited by 656
Mitochondrial DNA molecules and virtual number of mitochondria per cell in mammalian cells
Robin, E. D., & Wong, R. (1988) · Journal of Cellular Physiology · doi:10.1002/jcp.1041360316 · Cited by 650
Pilliod, D. S., Goldberg, C. S., Arkle, R. S., & Waits, L. P. (2013) · Canadian Journal of Fisheries and Aquatic Sciences · doi:10.1139/cjfas-2013-0047 · Cited by 602
Robust Detection of Rare Species Using Environmental DNA: The Importance of Primer Specificity
Wilcox, T. M., McKelvey, K. S., Young, M. K., Jane, S. F., Lowe, W. H., Whiteley, A. R., & Schwartz, M. K. (2013) · PLoS ONE · doi:10.1371/journal.pone.0059520 · Cited by 589
Distance, flow and PCR inhibition: e DNA dynamics in two headwater streams
Jane, S. F., Wilcox, T. M., McKelvey, K. S., Young, M. K., Schwartz, M. K., Lowe, W. H., Letcher, B. H., & Whiteley, A. R. (2015) · Molecular Ecology Resources · doi:10.1111/1755-0998.12285 · Cited by 549
Factors influencing detection of eDNA from a stream‐dwelling amphibian
Pilliod, D. S., Goldberg, C. S., Arkle, R. S., & Waits, L. P. (2014) · Molecular Ecology Resources · doi:10.1111/1755-0998.12159 · Cited by 517
Klymus, K. E., Richter, C. A., Chapman, D. C., & Paukert, C. (2015) · Biological Conservation · doi:10.1016/j.biocon.2014.11.020 · Cited by 460
Quantification of mesocosm fish and amphibian species diversity via environmental DNA metabarcoding
Evans, N. T., Olds, B. P., Renshaw, M. A., Turner, C. R., Li, Y., Jerde, C. L., Mahon, A. R., Pfrender, M. E., Lamberti, G. A., & Lodge, D. M. (2016) · Molecular Ecology Resources · doi:10.1111/1755-0998.12433 · Cited by 408
Wilcox, T. M., McKelvey, K. S., Young, M. K., Sepulveda, A. J., Shepard, B. B., Jane, S. F., Whiteley, A. R., Lowe, W. H., & Schwartz, M. K. (2016) · Biological Conservation · doi:10.1016/j.biocon.2015.12.023 · Cited by 401
The Release Rate of Environmental DNA from Juvenile and Adult Fish
Maruyama, A., Nakamura, K., Yamanaka, H., Kondoh, M., & Minamoto, T. (2014) · PLoS ONE · doi:10.1371/journal.pone.0114639 · Cited by 391
Environmental DNA analysis for estimating the abundance and biomass of stream fish
Doi, H., Inui, R., Akamatsu, Y., Kanno, K., Yamanaka, H., Takahara, T., & Minamoto, T. (2017) · Freshwater Biology · doi:10.1111/fwb.12846 · Cited by 356
Quantifying relative fish abundance with eDNA: a promising tool for fisheries management
Lacoursière‐Roussel, A., Côté, G., Leclerc, V., & Bernatchez, L. (2016) · Journal of Applied Ecology · doi:10.1111/1365-2664.12598 · Cited by 337
Lacoursière‐Roussel, A., Rosabal, M., & Bernatchez, L. (2016) · Molecular Ecology Resources · doi:10.1111/1755-0998.12522 · Cited by 324
Methods to maximise recovery of environmental DNA from water samples
Hinlo, R., Gleeson, D., Lintermans, M., & Furlan, E. (2017) · PLOS ONE · doi:10.1371/journal.pone.0179251 · Cited by 324
Use of Droplet Digital PCR for Estimation of Fish Abundance and Biomass in Environmental DNA Surveys
Doi, H., Uchii, K., Takahara, T., Matsuhashi, S., Yamanaka, H., & Minamoto, T. (2015) · PLOS ONE · doi:10.1371/journal.pone.0122763 · Cited by 319
Moving environmental DNA methods from concept to practice for monitoring aquatic macroorganisms
Goldberg, C. S., Strickler, K. M., & Pilliod, D. S. (2015) · Biological Conservation · doi:10.1016/j.biocon.2014.11.040 · Cited by 272
Wolbachia variant that induces two distinct reproductive phenotypes in different hosts
Sasaki, T., Massaki, N., & Kubo, T. (2005) · Heredity · doi:10.1038/sj.hdy.6800737 · Cited by 256
Environmental DNA(eDNA) detects the invasive rusty crayfish Orconectes rusticus at low abundances
Dougherty, M. M., Larson, E. R., Renshaw, M. A., Gantz, C. A., Egan, S. P., Erickson, D. M., & Lodge, D. M. (2016) · Journal of Applied Ecology · doi:10.1111/1365-2664.12621 · Cited by 198
Vanni, M. J., & McIntyre, P. B. (2016) · Ecology · doi:10.1002/ecy.1582 · Cited by 164
Environmental DNA reflects spatial and temporal jellyfish distribution
Minamoto, T., Fukuda, M., Katsuhara, K. R., Fujiwara, A., Hidaka, S., Yamamoto, S., Takahashi, K., & Masuda, R. (2017) · PLoS ONE · doi:10.1371/journal.pone.0173073 · Cited by 152
Schmelzle, M. C., & Kinziger, A. P. (2015) · Molecular Ecology Resources · doi:10.1111/1755-0998.12501 · Cited by 147
The digitize Package: Extracting Numerical Data from Scatterplots
Poisot, T. (2011) · The R Journal · doi:10.32614/rj-2011-004 · Cited by 110
Larson, E. R., Renshaw, M. A., Gantz, C. A., Umek, J. W., Chandra, S., Lodge, D. M., & Egan, S. P. (2017) · Hydrobiologia · doi:10.1007/s10750-017-3210-7 · Cited by 108
Nevers, M. B., Byappanahalli, M. N., Morris, C. C., Shively, D. A., Przybyla-Kelly, K. J., Spoljaric, A. M., Dickey, J., & Roseman, E. F. (2018) · PLoS ONE · doi:10.1371/journal.pone.0191720 · Cited by 104
Testing correlated correlations.
Olkin, I., & Finn, J. D. (1990) · Psychological Bulletin · doi:10.1037/0033-2909.108.2.330 · Cited by 103
Detecting the movement and spawning activity of bigheaded carps with environmental DNA
Erickson, R. A., Rees, C. B., Coulter, A. A., Merkes, C. M., McCalla, S. G., Touzinsky, K., Walleser, L. R., Goforth, R. R., & Amberg, J. J. (2016) · Molecular Ecology Resources · doi:10.1111/1755-0998.12533 · Cited by 101
An analytical framework for estimating aquatic species density from environmental DNA
Chambert, T., Pilliod, D. S., Goldberg, C. S., Doi, H., & Takahara, T. (2018) · Ecology and Evolution · doi:10.1002/ece3.3764 · Cited by 69
Whiteley, A. R., Coombs, J. A., Cembrola, M. R., O’Donnell, M. J., Hudy, M., Nislow, K. H., & Letcher, B. H. (2015) · Molecular Ecology · doi:10.1111/mec.13273 · Cited by 51
Cited by
Rourke, M. L., Fowler, A. M., Hughes, J. M., Broadhurst, M. K., DiBattista, J. D., Fielder, S., Wilkes Walburn, J., & Furlan, E. M. (2022) · Environmental DNA · doi:10.1002/edn3.185 · Cited by 435
Keck, F., Blackman, R. C., Bossart, R., Brantschen, J., Couton, M., Hürlemann, S., Kirschner, D., Locher, N., Zhang, H., & Altermatt, F. (2022) · Molecular Ecology · doi:10.1111/mec.16364 · Cited by 259
Metadata
- Authors
- Yates, M. C., Fraser, D. J., & Derry, A. M.
- Venue
- Environmental DNA
- Publisher
- Wiley
- Published
- 2019-04-16
- Volume
- 1
- Issue
- 1
- Pages
- 5-13
- ISSN
- 2637-4943 (ISSN-L)
- OpenAlex
- W2937376009
- Cited by
- 284
- References
- 37
- FWCI
- 16.86
- Type
- journal article
- Language
- en
- Open access
- gold
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