The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Connecting Earth observation to high-throughput biodiversity data
Open accessAbstract
Understandably, given the fast pace of biodiversity loss, there is much interest in using Earth observation technology to track biodiversity, ecosystem functions and ecosystem services. However, because most biodiversity is invisible to Earth observation, indicators based on Earth observation could be misleading and reduce the effectiveness of nature conservation and even unintentionally decrease conservation effort. We describe an approach that combines automated recording devices, high-throughput DNA sequencing and modern ecological modelling to extract much more of the information available in Earth observation data. This approach is achievable now, offering efficient and near-real-time monitoring of management impacts on biodiversity and its functions and services. A new approach is outlined for capturing multiple facets of biodiversity in near real-time by combining the latest advances in automated Earth observation recording, high-throughput sequencing and ecological modelling.
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High-Resolution Global Maps of 21st-Century Forest Cover Change
Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S. A., Tyukavina, A., Thau, D., Stehman, S. V., Goetz, S. J., Loveland, T. R., et al. (2013) · Science · doi:10.1126/science.1244693 · Cited by 11,704
Biodiversity loss and its impact on humanity
Cardinale, B. J., Duffy, J. E., Gonzalez, A., Hooper, D. U., Perrings, C., Venail, P., Narwani, A., Mace, G. M., Tilman, D., Wardle, D. A., et al. (2012) · Nature · doi:10.1038/nature11148 · Cited by 7,457
Mash: fast genome and metagenome distance estimation using MinHash
Ondov, B. D., Treangen, T. J., Melsted, P., Mallonee, A. B., Bergman, N. H., Koren, S., & Phillippy, A. M. (2016) · Genome biology · doi:10.1186/s13059-016-0997-x · Cited by 3,373
A mid-term analysis of progress toward international biodiversity targets
Tittensor, D. P., Walpole, M., Hill, S. L. L., Boyce, D. G., Britten, G. L., Burgess, N. D., Butchart, S. H. M., Leadley, P. W., Regan, E. C., Alkemade, R., et al. (2014) · Science · doi:10.1126/science.1257484 · Cited by 1,227
The natural selection of bad science
Smaldino, P. E., & McElreath, R. (2016) · Royal Society Open Science · doi:10.1098/rsos.160384 · Cited by 860
Lidar: shedding new light on habitat characterization and modeling
Vierling, K. T., Vierling, L. A., Gould, W. A., Martinuzzi, S., & Clawges, R. M. (2008) · Frontiers in Ecology and the Environment · doi:10.1890/070001 · Cited by 527
Several scales of biodiversity affect ecosystem multifunctionality
Pasari, J. R., Levi, T., Zavaleta, E. S., & Tilman, D. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1220333110 · Cited by 289
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Emerging opportunities and challenges for passive acoustics in ecological assessment and monitoring
Gibb, R., Browning, E., Glover‐Kapfer, P., & Jones, K. E. (2019) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.13101 · Cited by 730
Scaling up: A guide to high‐throughput genomic approaches for biodiversity analysis
Porter, T. M., & Hajibabaei, M. (2018) · Molecular Ecology · doi:10.1111/mec.14478 · Cited by 305
Priority list of biodiversity metrics to observe from space
Skidmore, A. K., Coops, N. C., Neinavaz, E., Ali, A., Schaepman, M. E., Paganini, M., Kissling, W. D., Vihervaara, P., Darvishzadeh, R., Feilhauer, H., et al. (2021) · Nature Ecology & Evolution · doi:10.1038/s41559-021-01451-x · Cited by 278
Monitoring biodiversity in the Anthropocene using remote sensing in species distribution models
Randin, C. F., Ashcroft, M. B., Bolliger, J., Cavender-Bares, J., Coops, N. C., Dullinger, S., Dirnböck, T., Eckert, S., Ellis, E., Fernández, N., et al. (2020) · Remote Sensing of Environment · doi:10.1016/j.rse.2019.111626 · Cited by 265
Standardizing Ecosystem Morphological Traits from 3D Information Sources
Valbuena, R., O’Connor, B., Zellweger, F., Simonson, W., Vihervaara, P., Maltamo, M., Silva, C. A., Almeida, D. R. A., Danks, F., Morsdorf, F., et al. (2020) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2020.03.006 · Cited by 126
Metadata
- Authors
- Bush, A., Sollmann, R., Wilting, A., Bohmann, K., Cole, B., Balzter, H., Martius, C., Zlinszky, A., Calvignac-Spencer, S., Cobbold, C. A., Dawson, T. P., Emerson, B. C., Ferrier, S., Gilbert, M. T. P., Herold, M., Jones, L., Leendertz, F. H., Matthews, L., Millington, J. D. A., Olson, J. R., Ovaskainen, O., Raffaelli, D., Reeve, R., Rödel, M.-O., Rodgers, T. W., Snape, S., Visseren-Hamakers, I., Vogler, A. P., White, P. C. L., Wooster, M. J., & Yu, D. W.
- Venue
- Nature Ecology & Evolution
- Published
- 2017-06-22
- Volume
- 1
- Issue
- 7
- Pages
- 176-176
- ISSN
- 2397-334X (ISSN-L)
- OpenAlex
- W2611853687
- Cited by
- 229
- References
- 7
- FWCI
- 23.45
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Bush, A., Sollmann, R., Wilting, A., Bohmann, K., Cole, B., Balzter, H., Martius, C., Zlinszky, A., Calvignac-Spencer, S., Cobbold, C. A., Dawson, T. P., Emerson, B. C., Ferrier, S., Gilbert, M. T. P., Herold, M., Jones, L., Leendertz, F. H., Matthews, L., Millington, J. D. A., . . . Yu, D. W. (2017). Connecting Earth observation to high-throughput biodiversity data. Nature Ecology & Evolution. https://doi.org/10.1038/s41559-017-0176
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
