The DOI matches its Crossref record; 50 of the 50 references it cites were found in a registry or an index.
Bio‐ORACLE v2.0: Extending marine data layers for bioclimatic modelling
Abstract
Motivation: The availability of user‐friendly, high‐resolution global environmental datasets is crucial for bioclimatic modelling. For terrestrial environments, WorldClim has served this purpose since 2005, but equivalent marine data only became available in 2012, with pioneer initiatives like Bio‐ORACLE providing data layers for several ecologically relevant variables. Currently, the available marine data packages have not yet been updated to the most recent Intergovernmental Panel on Climate Change (IPCC) predictions nor to present times, and are mostly restricted to the top surface layer of the oceans, precluding the modelling of a large fraction of the benthic diversity that inhabits deeper habitats. To address this gap, we present a significant update of Bio‐ORACLE for new future climate scenarios, present‐day conditions and benthic layers (near sea bottom). The reliability of data layers was assessed using a cross‐validation framework against in situ quality‐controlled data. This test showed a generally good agreement between our data layers and the global climatic patterns. We also provide a package of functions in the R software environment (sdmpredictors) to facilitate listing, extraction and management of data layers and allow easy integration with the available pipelines for bioclimatic modelling. Main types of variable contained: Surface and benthic layers for water temperature, salinity, nutrients, chlorophyll, sea ice, current velocity, phytoplankton, primary productivity, iron and light at bottom. Spatial location and grain: Global at 5 arcmin (c. 0.08° or 9.2 km at the equator). Time period and grain: Present (2000–2014) and future (2040–2050 and 2090–2100) environmental conditions based on monthly averages. Major taxa and level of measurement: Marine biodiversity associated with sea surface and epibenthic habitats. Software format: ASCII and TIFF grid formats for geographical information systems and a package of functions developed for R software.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
R: A Language and Environment for Statistical Computing
R Core Team (2025) · doi:10.32614/r.manuals · Cited by 352,181
Very high resolution interpolated climate surfaces for global land areas
Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G., & Jarvis, A. (2005) · International Journal of Climatology · doi:10.1002/joc.1276 · Cited by 19,825
Extinction risk from climate change
Thomas, C. D., Cameron, A., Green, R. E., Bakkenes, M., Beaumont, L. J., Collingham, Y. C., Erasmus, B. F. N., de Siqueira, M. F., Grainger, A., Hannah, L., et al. (2004) · Nature · doi:10.1038/nature02121 · Cited by 7,695
Predicting species distribution: offering more than simple habitat models
Guisan, A., & Thuiller, W. (2005) · Ecology Letters · doi:10.1111/j.1461-0248.2005.00792.x · Cited by 6,587
The next generation of scenarios for climate change research and assessment
Moss, R. H., Edmonds, J. A., Hibbard, K. A., Manning, M. R., Rose, S. K., van Vuuren, D. P., Carter, T. R., Emori, S., Kainuma, M., Kram, T., et al. (2010) · Nature · doi:10.1038/nature08823 · Cited by 6,467
Rapid Range Shifts of Species Associated with High Levels of Climate Warming
Chen, I.-C., Hill, J. K., Ohlemüller, R., Roy, D. B., & Thomas, C. D. (2011) · Science · doi:10.1126/science.1206432 · Cited by 5,518
Climate Change and Distribution Shifts in Marine Fishes
Perry, A. L., Low, P. J., Ellis, J. R., & Reynolds, J. D. (2005) · Science · doi:10.1126/science.1111322 · Cited by 3,182
BIOMOD – a platform for ensemble forecasting of species distributions
Thuiller, W., Lafourcade, B., Engler, R., & Araújo, M. B. (2009) · Ecography · doi:10.1111/j.1600-0587.2008.05742.x · Cited by 2,749
Mechanistic niche modelling: combining physiological and spatial data to predict species’ ranges
Kearney, M., & Porter, W. (2009) · Ecology Letters · doi:10.1111/j.1461-0248.2008.01277.x · Cited by 2,220
Predicting species distributions for conservation decisions
Guisan, A., Tingley, R., Baumgartner, J. B., Naujokaitis‐Lewis, I., Sutcliffe, P. R., Tulloch, A. I. T., Regan, T. J., Brotons, L., McDonald‐Madden, E., Mantyka‐Pringle, C., et al. (2013) · Ecology Letters · doi:10.1111/ele.12189 · Cited by 2,068
Cited by
Melo-Merino, S. M., Reyes-Bonilla, H., & Lira-Noriega, A. (2020) · Ecological Modelling · doi:10.1016/j.ecolmodel.2019.108837 · Cited by 555
Osorio‐Olvera, L., Lira‐Noriega, A., Soberón, J., Peterson, A. T., Falconi, M., Contreras‐Díaz, R. G., Martínez‐Meyer, E., Barve, V., & Barve, N. (2020) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.13452 · Cited by 371
The evolution of critical thermal limits of life on Earth
Bennett, J. M., Sunday, J., Calosi, P., Villalobos, F., Martínez, B., Molina-Venegas, R., Araújo, M. B., Algar, A. C., Clusella-Trullas, S., Hawkins, B. A., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-21263-8 · Cited by 353
Global estimates of the extent and production of macroalgal forests
Duarte, C. M., Gattuso, J., Hancke, K., Gundersen, H., Filbee‐Dexter, K., Pedersen, M. F., Middelburg, J. J., Burrows, M. T., Krumhansl, K. A., Wernberg, T., et al. (2022) · Global Ecology and Biogeography · doi:10.1111/geb.13515 · Cited by 280
Self-citationBorges, F. O., Guerreiro, M., Santos, C. P., Paula, J. R., & Rosa, R. (2022) · Frontiers in Marine Science · doi:10.3389/fmars.2022.1018766 · Cited by 28
“The mean, max, min, and range for each predictor were obtained from Bio-ORACLE, which offers global geophysical, biotic, and climate layers at a common spatial resolution (5 arcmins) and a uniform landmask (Tyberghein et al., 2012; Assis et al., 2018).”
Method
Metadata
- Authors
- Assis, J., Tyberghein, L., Bosch, S., Verbruggen, H., Serrão, E. A., & De Clerck, O.
- Venue
- Global Ecology and Biogeography
- Publisher
- Wiley
- Published
- 2017-12-29
- Volume
- 27
- Issue
- 3
- Pages
- 277-284
- ISSN
- 1466-822X (ISSN-L)
- 1466-8238
- OpenAlex
- W2779441842
- Cited by
- 931
- References
- 50
- FWCI
- 20.61
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Bio‐ORACLE v2.0: Extending marine data layers for bioclimatic modelling. https://app.cochat.ai/papers/10.1111/geb.12693
- The paper
- Assis, J., Tyberghein, L., Bosch, S., Verbruggen, H., Serrão, E. A., & De Clerck, O. (2018). Bio‐ORACLE v2.0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography. https://doi.org/10.1111/geb.12693
Data sources
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.
